Repository: je-suis-tm/quant-trading Branch: master Commit: 611b73f2c3f5 Files: 61 Total size: 5.4 MB Directory structure: gitextract_is6png7e/ ├── Awesome Oscillator backtest.py ├── Bollinger Bands Pattern Recognition backtest.py ├── Dual Thrust backtest.py ├── Heikin-Ashi backtest.py ├── LICENSE ├── London Breakout backtest.py ├── MACD Oscillator backtest.py ├── Monte Carlo project/ │ ├── Monte Carlo backtest.py │ └── README.md ├── Oil Money project/ │ ├── Oil Money CAD.py │ ├── Oil Money COP.py │ ├── Oil Money NOK.py │ ├── Oil Money RUB.py │ ├── Oil Money Trading backtest.py │ ├── README.md │ ├── data/ │ │ ├── brent crude nokjpy.csv │ │ ├── urals crude rubaud.csv │ │ ├── vas crude copaud.csv │ │ └── wcs crude cadaud.csv │ └── oil production/ │ ├── oil production choropleth.csv │ ├── oil production choropleth.py │ ├── oil production cost curve.csv │ ├── oil production cost curve.py │ └── worldmapshape.json ├── Options Straddle backtest.py ├── Ore Money project/ │ ├── README.md │ ├── iron ore audeur.csv │ ├── iron ore brlaud.csv │ ├── iron ore production/ │ │ ├── iron ore production bubble map.csv │ │ └── iron ore production bubble map.py │ └── iron ore uahusd.csv ├── Pair trading backtest.py ├── Parabolic SAR backtest.py ├── README.md ├── RSI Pattern Recognition backtest.py ├── Shooting Star backtest.py ├── Smart Farmers project/ │ ├── README.md │ ├── check consistency.py │ ├── cleanse data.py │ ├── country selection.py │ ├── data/ │ │ ├── capita.csv │ │ ├── cme.csv │ │ ├── forecast.csv │ │ ├── grand.csv │ │ ├── malay_gdp.csv │ │ ├── malay_land.csv │ │ ├── malay_pop.csv │ │ ├── malay_prix.csv │ │ ├── malay_prod.csv │ │ ├── mapping.csv │ │ ├── palm.csv │ │ └── tres_grand.csv │ ├── estimate demand.py │ └── forecast.py ├── VIX Calculator.py └── data/ ├── bitcoin.csv ├── cme holidays.csv ├── gbpusd.csv ├── henry hub european options.csv ├── stoxx50.xlsx └── treasury yield curve rates.csv ================================================ FILE CONTENTS ================================================ ================================================ FILE: Awesome Oscillator backtest.py ================================================ # coding: utf-8 #details of awesome oscillator can be found here # https://www.tradingview.com/wiki/Awesome_Oscillator_(AO) #basically i use awesome oscillator to compare with macd oscillator #lets see which one makes more money #there is not much difference between two of em #this time i use exponential smoothing on macd #for awesome oscillator, i use simple moving average instead #the rules are quite simple #these two are momentum trading strategy #they compare the short moving average with long moving average #if the difference is positive #we long the asset, vice versa #awesome oscillator has slightly more conditions for signals #we will see about it later #for more details about macd # https://github.com/je-suis-tm/quant-trading/blob/master/MACD%20oscillator%20backtest.py # In[1]: #need to get fix yahoo finance package first import matplotlib.pyplot as plt import numpy as np import pandas as pd import fix_yahoo_finance as yf # In[2]: #this part is macd #i will not go into details as i have another session called macd #the only difference is that i use ewma function to apply exponential smoothing technique def ewmacd(signals,ma1,ma2): signals['macd ma1']=signals['Close'].ewm(span=ma1).mean() signals['macd ma2']=signals['Close'].ewm(span=ma2).mean() return signals def signal_generation(df,method,ma1,ma2): signals=method(df,ma1,ma2) signals['macd positions']=0 signals['macd positions'][ma1:]=np.where(signals['macd ma1'][ma1:]>=signals['macd ma2'][ma1:],1,0) signals['macd signals']=signals['macd positions'].diff() signals['macd oscillator']=signals['macd ma1']-signals['macd ma2'] return signals # In[3]: #for awesome oscillator #moving average is based on the mean of high and low instead of close price def awesome_ma(signals): signals['awesome ma1'],signals['awesome ma2']=0,0 signals['awesome ma1']=((signals['High']+signals['Low'])/2).rolling(window=5).mean() signals['awesome ma2']=((signals['High']+signals['Low'])/2).rolling(window=34).mean() return signals #awesome signal generation,AWESOME! def awesome_signal_generation(df,method): signals=method(df) signals.reset_index(inplace=True) signals['awesome signals']=0 signals['awesome oscillator']=signals['awesome ma1']-signals['awesome ma2'] signals['cumsum']=0 for i in range(2,len(signals)): #awesome oscillator has an extra way to generate signals #its called saucer #A Bearish Saucer setup occurs when the AO is below the Zero Line #in another word, awesome oscillator is negative #A Bearish Saucer entails two consecutive green bars (with the second bar being higher than the first bar) being followed by a red bar. #in another word, green bar refers to open price is higher than close price if (signals['Open'][i]>signals['Close'][i] and signals['Open'][i-1]signals['awesome oscillator'][i-2] and signals['awesome oscillator'][i-1]<0 and signals['awesome oscillator'][i]<0): signals.at[i,'awesome signals']=1 #this is bullish saucer #vice versa if (signals['Open'][i]signals['Close'][i-1] and signals['Open'][i-2]>signals['Close'][i-2] and signals['awesome oscillator'][i-1]0 and signals['awesome oscillator'][i]>0): signals.at[i,'awesome signals']=-1 #this part is the same as macd signal generation #nevertheless, we have extra rules to get signals ahead of moving average #if we get signals before moving average generate any signal #we will ignore signals generated by moving average then #as it is delayed and probably deliver fewer profit than previous signals #we use cumulated sum to see if there has been created any open positions #if so, we will take a pass if signals['awesome ma1'][i]>signals['awesome ma2'][i]: signals.at[i,'awesome signals']=1 signals['cumsum']=signals['awesome signals'].cumsum() if signals['cumsum'][i]>1: signals.at[i,'awesome signals']=0 if signals['awesome ma1'][i]new['Close'],'r','g') cx.bar(range(len(new)),new['awesome oscillator'],color=c,label='awesome oscillator') plt.grid(True) plt.legend(loc='best') plt.title('Oscillator') dx=fig.add_subplot(212,sharex=cx) new['macd oscillator'].plot(kind='bar',label='macd oscillator') plt.grid(True) plt.legend(loc='best') plt.xlabel('') plt.xticks([]) plt.show() #moving average fig=plt.figure() ex=fig.add_subplot(211) new['awesome ma1'].plot(label='awesome ma1') new['awesome ma2'].plot(label='awesome ma2',linestyle=':') plt.legend(loc='best') plt.grid(True) plt.xticks([]) plt.xlabel('') plt.title('Moving Average') fig=plt.figure() fx=fig.add_subplot(212,sharex=bx) new['macd ma1'].plot(label='macd ma1') new['macd ma2'].plot(label='macd ma2',linestyle=':') plt.legend(loc='best') plt.grid(True) plt.show() # In[5]: #normally i dont include backtesting stats #for the comparison, i am willing to make an exception #capital0 is intial capital #positions defines how much shares we buy for every single trade def portfolio(signals): capital0=5000 positions=100 portfolio=pd.DataFrame() portfolio['Close']=signals['Close'] #cumsum is used to calculate the change of value while holding shares portfolio['awesome holding']=signals['cumsum']*portfolio['Close']*positions portfolio['macd holding']=signals['macd positions']*portfolio['Close']*positions #basically cash is initial capital minus the profit we make from every trade #note that we have to use cumulated sum to add every profit into our cash portfolio['awesome cash']=capital0-(signals['awesome signals']*portfolio['Close']*positions).cumsum() portfolio['macd cash']=capital0-(signals['macd signals']*portfolio['Close']*positions).cumsum() portfolio['awesome asset']=portfolio['awesome holding']+portfolio['awesome cash'] portfolio['macd asset']=portfolio['macd holding']+portfolio['macd cash'] portfolio['awesome return']=portfolio['awesome asset'].pct_change() portfolio['macd return']=portfolio['macd asset'].pct_change() return portfolio # In[6]: #lets plot how two strategies increase our asset value def profit(portfolio): gx=plt.figure() gx.add_subplot(111) portfolio['awesome asset'].plot() portfolio['macd asset'].plot() plt.legend(loc='best') plt.grid(True) plt.title('Awesome VS MACD') plt.show() # In[7]: #i use a function to calculate maximum drawdown #the idea is simple #for every day, we take the current asset value #to compare with the previous highest asset value #we get our daily drawdown #it is supposed to be negative if it is not the maximum for this period so far #we implement a temporary variable to store the minimum value #which is called maximum drawdown #for each daily drawdown that is smaller than our temporary value #we update the temp until we finish our traversal #in the end we return the maximum drawdown def mdd(series): temp=0 for i in range(1,len(series)): if temp>(series[i]/max(series[:i])-1): temp=(series[i]/max(series[:i])-1) return temp def stats(portfolio): stats=pd.DataFrame([0]) #lets calculate some sharpe ratios #note that i set risk free return at 0 for simplicity #alternatively we can use snp500 as a benchmark stats['awesome sharpe']=(portfolio['awesome asset'].iloc[-1]/5000-1)/np.std(portfolio['awesome return']) stats['macd sharpe']=(portfolio['macd asset'].iloc[-1]/5000-1)/np.std(portfolio['macd return']) stats['awesome mdd']=mdd(portfolio['awesome asset']) stats['macd mdd']=mdd(portfolio['macd asset']) #ta-da! print(stats) # In[8]: def main(): #awesome oscillator uses 5 lags as short ma #34 lags as long ma #for the consistent comparison #i apply the same to macd oscillator ma1=5 ma2=34 #downloading stdate=input('start date in format yyyy-mm-dd:') eddate=input('end date in format yyyy-mm-dd:') ticker=input('ticker:') df=yf.download(ticker,start=stdate,end=eddate) #slicing the downloaded dataset #if the dataset is too large #backtesting plot would look messy slicer=int(input('slicing:')) signals=signal_generation(df,ewmacd,ma1,ma2) sig=awesome_signal_generation(signals,awesome_ma) new=sig[slicer:] plot(new,ticker) portfo=portfolio(sig) profit(portfo) stats(portfo) #from my tests #macd has demonstrated a higher sharpe ratio #it executes fewer trades but brings more profits #however its maximum drawdown is higher than awesome oscillator #which one is better? #it depends on your risk averse level if __name__ == '__main__': main() ================================================ FILE: Bollinger Bands Pattern Recognition backtest.py ================================================ # coding: utf-8 # In[1]: #bollinger bands is a simple indicator #just moving average plus moving standard deviation #but pattern recognition is a differenct case #visualization is easy for human to identify the pattern #but for the machines, we gotta find a different approach #when we talk about pattern recognition these days #people always respond with machine learning #why machine learning when u can use arithmetic approach #which is much faster and simpler? #there are many patterns for recognition #top m, bottom w, head-shoulder top, head-shoulder bottom, elliott waves #in this content, we only discuss bottom w #top m is just the reverse of bottom w #rules of bollinger bands and bottom w can be found in the following link: # https://www.tradingview.com/wiki/Bollinger_Bands_(BB) import os import pandas as pd import matplotlib.pyplot as plt import copy import numpy as np # In[2]: os.chdir('d:/') # In[3]: #first step is to calculate moving average and moving standard deviation #we plus/minus two standard deviations on moving average #we get our upper, mid, lower bands def bollinger_bands(df): data=copy.deepcopy(df) data['std']=data['price'].rolling(window=20,min_periods=20).std() data['mid band']=data['price'].rolling(window=20,min_periods=20).mean() data['upper band']=data['mid band']+2*data['std'] data['lower band']=data['mid band']-2*data['std'] return data # In[4]: #the signal generation is a bit tricky #there are four conditions to satisfy #for the shape of w, there are five nodes #from left to right, top to bottom, l,k,j,m,i #when we generate signals #the iteration node is the top right node i, condition 4 #first, we find the middle node j, condition 2 #next, we identify the first bottom node k, condition 1 #after that, we point out the first top node l #l is not any of those four conditions #we just use it for pattern visualization #finally, we locate the second bottom node m, condition 3 #plz refer to the following link for my poor visualization # https://github.com/je-suis-tm/quant-trading/blob/master/preview/bollinger%20bands%20bottom%20w%20pattern.png def signal_generation(data,method): #according to investopedia #for a double bottom pattern #we should use 3-month horizon which is 75 period=75 #alpha denotes the difference between price and bollinger bands #if alpha is too small, its unlikely to trigger a signal #if alpha is too large, its too easy to trigger a signal #which gives us a higher probability to lose money #beta denotes the scale of bandwidth #when bandwidth is larger than beta, it is expansion period #when bandwidth is smaller than beta, it is contraction period alpha=0.0001 beta=0.0001 df=method(data) df['signals']=0 #as usual, cumsum denotes the holding position #coordinates store five nodes of w shape #later we would use these coordinates to draw a w shape df['cumsum']=0 df['coordinates']='' for i in range(period,len(df)): #moveon is a process control #if moveon==true, we move on to verify the next condition #if false, we move on to the next iteration #threshold denotes the value of node k #we would use it for the comparison with node m #plz refer to condition 3 moveon=False threshold=0.0 #bottom w pattern recognition #there is another signal generation method called walking the bands #i personally think its too late for following the trend #after confirmation of several breakthroughs #maybe its good for stop and reverse #condition 4 if (df['price'][i]>df['upper band'][i]) and \ (df['cumsum'][i]==0): for j in range(i,i-period,-1): #condition 2 if (np.abs(df['mid band'][j]-df['price'][j])df['lower band'][m]) and \ (df['price'][m]intraday['range2'],intraday['range1'],intraday['range2']) return intraday #signal generation #even replace assignment with pandas.at #it still takes a while for us to get the result #any optimization suggestion besides using numpy array? def signal_generation(df,intraday,param,column,rg): #as the lags of days have been set to 5 #we should start our backtesting after 4 workdays of current month #cumsum is to control the holding of underlying asset #sigup and siglo are the variables to store the upper/lower threshold #upper and lower are for the purpose of tracking sigup and siglo signals=df[df.index>=intraday['date'].iloc[rg-1]] signals['signals']=0 signals['cumsum']=0 signals['upper']=0.0 signals['lower']=0.0 sigup=float(0) siglo=float(0) #for traversal on time series #the tricky part is the slicing #we have to either use [i:i] or pd.Series #first we set up thresholds at the beginning of london market #which is est 3am #if the price exceeds either threshold #we will take long/short positions for i in signals.index: #note that intraday and dataframe have different frequencies #obviously different metrics for indexes #we use variable date for index convertion date='%s-%s-%s'%(i.year,i.month,i.day) #market opening #set up thresholds if (i.hour==3 and i.minute==0): sigup=float(param*intraday['range'][date]+pd.Series(signals[column])[i]) siglo=float(-(1-param)*intraday['range'][date]+pd.Series(signals[column])[i]) #thresholds got breached #signals generating if (sigup!=0 and pd.Series(signals[column])[i]>sigup): signals.at[i,'signals']=1 if (siglo!=0 and pd.Series(signals[column])[i]1 or pd.Series(signals['cumsum'])[i]<-1): signals.at[i,'signals']=0 #if the price goes from below the lower threshold to above the upper threshold during the day #we reverse our positions from short to long if (pd.Series(signals['cumsum'])[i]==0): if (pd.Series(signals[column])[i]>sigup): signals.at[i,'signals']=2 if (pd.Series(signals[column])[i]data['HA close'][n] and data['HA open'][n]==data['HA high'][n] and np.abs(data['HA open'][n]-data['HA close'][n])>np.abs(data['HA open'][n-1]-data['HA close'][n-1]) and data['HA open'][n-1]>data['HA close'][n-1]): data.at[n,'signals']=1 data['cumsum']=data['signals'].cumsum() #accumulate too many longs if data['cumsum'][n]>stls: data.at[n,'signals']=0 #exit positions elif (data['HA open'][n]0: data.at[n,'signals']=-1*(data['cumsum'][n-1]) if data['cumsum'][n]<0: data.at[n,'signals']=0 return data # In[5]: #since matplotlib remove the candlestick #plus we dont wanna install mpl_finance #we implement our own version #simply use fill_between to construct the bar #use line plot to construct high and low def candlestick(df,ax=None,titlename='',highcol='High',lowcol='Low', opencol='Open',closecol='Close',xcol='Date', colorup='r',colordown='g',**kwargs): #bar width #use 0.6 by default dif=[(-3+i)/10 for i in range(7)] if not ax: ax=plt.figure(figsize=(10,5)).add_subplot(111) #construct the bars one by one for i in range(len(df)): #width is 0.6 by default #so 7 data points required for each bar x=[i+j for j in dif] y1=[df[opencol].iloc[i]]*7 y2=[df[closecol].iloc[i]]*7 barcolor=colorup if y1[0]>y2[0] else colordown #no high line plot if open/close is high if df[highcol].iloc[i]!=max(df[opencol].iloc[i],df[closecol].iloc[i]): #use generic plot to viz high and low #use 1.001 as a scaling factor #to prevent high line from crossing into the bar plt.plot([i,i], [df[highcol].iloc[i], max(df[opencol].iloc[i], df[closecol].iloc[i])*1.001],c='k',**kwargs) #same as high if df[lowcol].iloc[i]!=min(df[opencol].iloc[i],df[closecol].iloc[i]): plt.plot([i,i], [df[lowcol].iloc[i], min(df[opencol].iloc[i], df[closecol].iloc[i])*0.999],c='k',**kwargs) #treat the bar as fill between plt.fill_between(x,y1,y2, edgecolor='k', facecolor=barcolor,**kwargs) #only show 5 xticks plt.xticks(range(0,len(df),len(df)//5),df[xcol][0::len(df)//5].dt.date) plt.title(titlename) #plotting the backtesting result def plot(df,ticker): df.set_index(df['Date'],inplace=True) #first plot is Heikin-Ashi candlestick #use candlestick function and set Heikin-Ashi O,C,H,L ax1=plt.subplot2grid((200,1), (0,0), rowspan=120,ylabel='HA price') candlestick(df,ax1,titlename='',highcol='HA high',lowcol='HA low', opencol='HA open',closecol='HA close',xcol='Date', colorup='r',colordown='g') plt.grid(True) plt.xticks([]) plt.title('Heikin-Ashi') #the second plot is the actual price with long/short positions as up/down arrows ax2=plt.subplot2grid((200,1), (120,0), rowspan=80,ylabel='price',xlabel='') df['Close'].plot(ax=ax2,label=ticker) #long/short positions are attached to the real close price of the stock #set the line width to zero #thats why we only observe markers ax2.plot(df.loc[df['signals']==1].index,df['Close'][df['signals']==1],marker='^',lw=0,c='g',label='long') ax2.plot(df.loc[df['signals']<0].index,df['Close'][df['signals']<0],marker='v',lw=0,c='r',label='short') plt.grid(True) plt.legend(loc='best') plt.show() # In[6]: #backtesting #initial capital 10k to calculate the actual pnl #100 shares to buy of every position def portfolio(data,capital0=10000,positions=100): #cumsum column is created to check the holding of the position data['cumsum']=data['signals'].cumsum() portfolio=pd.DataFrame() portfolio['holdings']=data['cumsum']*data['Close']*positions portfolio['cash']=capital0-(data['signals']*data['Close']*positions).cumsum() portfolio['total asset']=portfolio['holdings']+portfolio['cash'] portfolio['return']=portfolio['total asset'].pct_change() portfolio['signals']=data['signals'] portfolio['date']=data['Date'] portfolio.set_index('date',inplace=True) return portfolio # In[7]: #plotting the asset value change of the portfolio def profit(portfolio): fig=plt.figure() bx=fig.add_subplot(111) portfolio['total asset'].plot(label='Total Asset') #long/short position markers related to the portfolio #the same mechanism as the previous one #replace close price with total asset value bx.plot(portfolio['signals'].loc[portfolio['signals']==1].index,portfolio['total asset'][portfolio['signals']==1],lw=0,marker='^',c='g',label='long') bx.plot(portfolio['signals'].loc[portfolio['signals']<0].index,portfolio['total asset'][portfolio['signals']<0],lw=0,marker='v',c='r',label='short') plt.legend(loc='best') plt.grid(True) plt.xlabel('Date') plt.ylabel('Asset Value') plt.title('Total Asset') plt.show() # In[8]: #omega ratio is a variation of sharpe ratio #the risk free return is replaced by a given threshold #in this case, the return of benchmark #integral is needed to calculate the return above and below the threshold #you can use summation to do approximation as well #it is a more reasonable ratio to measure the risk adjusted return #normal distribution doesnt explain the fat tail of returns #so i use student T cumulated distribution function instead #to make our life easier, i do not use empirical distribution #the cdf of empirical distribution is much more complex #check wikipedia for more details # https://en.wikipedia.org/wiki/Omega_ratio def omega(risk_free,degree_of_freedom,maximum,minimum): y=scipy.integrate.quad(lambda g:1-scipy.stats.t.cdf(g,degree_of_freedom),risk_free,maximum) x=scipy.integrate.quad(lambda g:scipy.stats.t.cdf(g,degree_of_freedom),minimum,risk_free) z=(y[0])/(x[0]) return z #sortino ratio is another variation of sharpe ratio #the standard deviation of all returns is substituted with standard deviation of negative returns #sortino ratio measures the impact of negative return on return #i am also using student T probability distribution function instead of normal distribution #check wikipedia for more details # https://en.wikipedia.org/wiki/Sortino_ratio def sortino(risk_free,degree_of_freedom,growth_rate,minimum): v=np.sqrt(np.abs(scipy.integrate.quad(lambda g:((risk_free-g)**2)*scipy.stats.t.pdf(g,degree_of_freedom),risk_free,minimum))) s=(growth_rate-risk_free)/v[0] return s #i use a function to calculate maximum drawdown #the idea is simple #for every day, we take the current asset value marked to market #to compare with the previous highest asset value #we get our daily drawdown #it is supposed to be negative if the current one is not the highest #we implement a temporary variable to store the minimum negative value #which is called maximum drawdown #for each daily drawdown that is smaller than our temporary value #we update the temp until we finish our traversal #in the end we return the maximum drawdown def mdd(series): minimum=0 for i in range(1,len(series)): if minimum>(series[i]/max(series[:i])-1): minimum=(series[i]/max(series[:i])-1) return minimum # In[9]: #stats calculation def stats(portfolio,trading_signals,stdate,eddate,capital0=10000): stats=pd.DataFrame([0]) #get the min and max of return maximum=np.max(portfolio['return']) minimum=np.min(portfolio['return']) #growth_rate denotes the average growth rate of portfolio #use geometric average instead of arithmetic average for percentage growth growth_rate=(float(portfolio['total asset'].iloc[-1]/capital0))**(1/len(trading_signals))-1 #calculating the standard deviation std=float(np.sqrt((((portfolio['return']-growth_rate)**2).sum())/len(trading_signals))) #use S&P500 as benchmark benchmark=yf.download('^GSPC',start=stdate,end=eddate) #return of benchmark return_of_benchmark=float(benchmark['Close'].iloc[-1]/benchmark['Open'].iloc[0]-1) #rate_of_benchmark denotes the average growth rate of benchmark #use geometric average instead of arithmetic average for percentage growth rate_of_benchmark=(return_of_benchmark+1)**(1/len(trading_signals))-1 del benchmark #backtesting stats #CAGR stands for cumulated average growth rate stats['CAGR']=stats['portfolio return']=float(0) stats['CAGR'][0]=growth_rate stats['portfolio return'][0]=portfolio['total asset'].iloc[-1]/capital0-1 stats['benchmark return']=return_of_benchmark stats['sharpe ratio']=(growth_rate-rate_of_benchmark)/std stats['maximum drawdown']=mdd(portfolio['total asset']) #calmar ratio is sorta like sharpe ratio #the standard deviation is replaced by maximum drawdown #it is the measurement of return after worse scenario adjustment #check wikipedia for more details # https://en.wikipedia.org/wiki/Calmar_ratio stats['calmar ratio']=growth_rate/stats['maximum drawdown'] stats['omega ratio']=omega(rate_of_benchmark,len(trading_signals),maximum,minimum) stats['sortino ratio']=sortino(rate_of_benchmark,len(trading_signals),growth_rate,minimum) #note that i use stop loss limit to limit the numbers of longs #and when clearing positions, we clear all the positions at once #so every long is always one, and short cannot be larger than the stop loss limit stats['numbers of longs']=trading_signals['signals'].loc[trading_signals['signals']==1].count() stats['numbers of shorts']=trading_signals['signals'].loc[trading_signals['signals']<0].count() stats['numbers of trades']=stats['numbers of shorts']+stats['numbers of longs'] #to get the total length of trades #given that cumsum indicates the holding of positions #we can get all the possible outcomes when cumsum doesnt equal zero #then we count how many non-zero positions there are #we get the estimation of total length of trades stats['total length of trades']=trading_signals['signals'].loc[trading_signals['cumsum']!=0].count() stats['average length of trades']=stats['total length of trades']/stats['numbers of trades'] stats['profit per trade']=float(0) stats['profit per trade'].iloc[0]=(portfolio['total asset'].iloc[-1]-capital0)/stats['numbers of trades'].iloc[0] del stats[0] print(stats) # In[10]: def main(): #initializing #stop loss positions, the maximum long positions we can get #without certain constraints, you will long indefinites times #as long as the market condition triggers the signal #in a whipsaw condition, it is suicidal stls=3 ticker='NVDA' stdate='2015-04-01' eddate='2018-02-15' #slicer is used for plotting #a three year dataset with 750 data points would be too much slicer=700 #downloading data df=yf.download(ticker,start=stdate,end=eddate) trading_signals=signal_generation(df,heikin_ashi,stls) viz=trading_signals[slicer:] plot(viz,ticker) portfolio_details=portfolio(viz) profit(portfolio_details) stats(portfolio_details,trading_signals,stdate,eddate) #note that this is the only py file with complete stats calculation if __name__ == '__main__': main() ================================================ FILE: LICENSE ================================================ Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. ================================================ FILE: London Breakout backtest.py ================================================ # coding: utf-8 # In[1]: #this is to London, the greatest city in the world #i was a Londoner, proud of being Londoner, how i love the city! #to St Paul, Tate Modern, Millennium Bridge and so much more! #okay, lets get down to business #the idea of london break out strategy is to take advantage of fx trading hour #basically fx trading is 24 hour non stop for weekdays #u got tokyo, before tokyo closes, u got london #in the afternoon, u got new york, when new york closes, its sydney #and several hours later, tokyo starts again #however, among these three major players #london is where the majority trades are executed #not sure if it will stay the same after brexit actually takes place #what we intend to do is look at the last trading hour before london starts #we set up our thresholds based on that hours high and low #when london market opens, we examine the first 30 minutes #if it goes way above or below thresholds #we long or short certain currency pairs #and we clear our positions based on target and stop loss we set #if they havent reach the trigger condition by the end of trading hour #we exit our trades and close all positions #it sounds easy in practise #just a simple prediction of london fx market based on tokyo market #but the code of london breakout is extremely time consuming #first, we need to get one minute frequency dataset for backtest #i would recommend this website # http://www.histdata.com/download-free-forex-data/?/excel/1-minute-bar-quotes #we can get as many as free datasets of various currency pairs we want #before our backtesting, we should cleanse the raw data #what we get from the website is one minute frequency bid-ask price #i take the average of em and add a header called price #i save it on local disk then read it via python #please note that this website uses new york time zone utc -5 #for non summer daylight saving time #london market starts at gmt 8 am #which is est 3 am #daylight saving time is another story #what a stupid idea it is import os os.chdir('d:/') import matplotlib.pyplot as plt import pandas as pd # In[2]: def london_breakout(df): df['signals']=0 #cumsum is the cumulated sum of signals #later we would use it to control our positions df['cumsum']=0 #upper and lower are our thresholds df['upper']=0.0 df['lower']=0.0 return df def signal_generation(df,method): #tokyo_price is a list to store average price of #the last trading hour of tokyo market #we use max, min to define the real threshold later tokyo_price=[] #risky_stop is a parameter set by us #it is to reduce the risk exposure to volatility #i am using 100 basis points #for instance, we have defined our upper and lower thresholds #however, when london market opens #the price goes skyrocketing #say 200 basis points above upper threshold #i personally wouldnt get in the market as its too risky #also, my stop loss and target is 50 basis points #just half of my risk interval #i will use this variable for later stop loss set up risky_stop=0.01 #this is another parameter set by us #it is about how long opening volatility would wear off #for me, 30 minutes after the market opening is the boundary #as long as its under 30 minutes after the market opening #if the price reaches threshold level, i will trade on signals open_minutes=30 #this is the price when we execute a trade #we need to save it to set up the stop loss executed_price=float(0) signals=method(df) signals['date']=pd.to_datetime(signals['date']) #this is the core part #the time complexity for this part is extremely high #as there are too many constraints #if u have a better idea to optimize it #plz let me know for i in range(len(signals)): #as mentioned before #the dataset use eastern standard time #so est 2am is the last hour before london starts #we try to append all the price into the list called threshold if signals['date'][i].hour==2: tokyo_price.append(signals['price'][i]) #est 3am which is gmt 8am #thats when london market starts #good morning city of london and canary wharf! #right at this moment #we get max and min of the price of tokyo trading hour #we set up the threshold as the way it is #alternatively, we can put 10 basis points above and below thresholds #we also use upper and lower list to keep track of our thresholds #and now we clear the list called threshold elif signals['date'][i].hour==3 and signals['date'][i].minute==0: upper=max(tokyo_price) lower=min(tokyo_price) signals.at[i,'upper']=upper signals.at[i,'lower']=lower tokyo_price=[] #prior to 30 minutes i have mentioned before #as long as its under 30 minutes after market opening #signals will be generated once conditions are met #this is a relatively risky way #alternatively, we can set the signal generation time at a fixed point #when its gmt 8 30 am, we check the conditions to see if there is any signal elif signals['date'][i].hour==3 and signals['date'][i].minute0: signals.at[i,'signals']=1 #we use cumsum to check the cumulated sum of signals #we wanna make sure that #only the first price above upper threshold triggers the signal #also, if it goes skyrocketing #say 200 basis points above, which is 100 above our risk tolerance #we set it as a false alarm signals['cumsum']=signals['signals'].cumsum() if signals['price'][i]-upper>risky_stop: signals.at[i,'signals']=0 elif signals['cumsum'][i]>1: signals.at[i,'signals']=0 else: #we also need to store the price when we execute a trade #its for stop loss calculation executed_price=signals['price'][i] #vice versa if signals['price'][i]-lower<0: signals.at[i,'signals']=-1 signals['cumsum']=signals['signals'].cumsum() if lower-signals['price'][i]>risky_stop: signals.at[i,'signals']=0 elif signals['cumsum'][i]<-1: signals.at[i,'signals']=0 else: executed_price=signals['price'][i] #when its gmt 5 pm, london market closes #we use cumsum to see if there is any position left open #we take -cumsum as a signal #if there is no open position, -0 is still 0 elif signals['date'][i].hour==12: signals['cumsum']=signals['signals'].cumsum() signals.at[i,'signals']=-signals['cumsum'][i] #during london trading hour after opening but before closing #we still use cumsum to check our open positions #if there is any open position #we set our condition at original executed price +/- half of the risk interval #when it goes above or below our risk tolerance #we clear positions to claim profit or loss else: signals['cumsum']=signals['signals'].cumsum() if signals['cumsum'][i]!=0: if signals['price'][i]>executed_price+risky_stop/2: signals.at[i,'signals']=-signals['cumsum'][i] if signals['price'][i]=signals['ma2'][ma1:],1,0) #as positions only imply the holding #we take the difference to generate real trade signal signals['signals']=signals['positions'].diff() #oscillator is the difference between two moving average #when it is positive, we long, vice versa signals['oscillator']=signals['ma1']-signals['ma2'] return signals # In[4]: #plotting the backtesting result def plot(new, ticker): #the first plot is the actual close price with long/short positions fig=plt.figure() ax=fig.add_subplot(111) new['Close'].plot(label=ticker) ax.plot(new.loc[new['signals']==1].index,new['Close'][new['signals']==1],label='LONG',lw=0,marker='^',c='g') ax.plot(new.loc[new['signals']==-1].index,new['Close'][new['signals']==-1],label='SHORT',lw=0,marker='v',c='r') plt.legend(loc='best') plt.grid(True) plt.title('Positions') plt.show() #the second plot is long/short moving average with oscillator #note that i use bar chart for oscillator fig=plt.figure() cx=fig.add_subplot(211) new['oscillator'].plot(kind='bar',color='r') plt.legend(loc='best') plt.grid(True) plt.xticks([]) plt.xlabel('') plt.title('MACD Oscillator') bx=fig.add_subplot(212) new['ma1'].plot(label='ma1') new['ma2'].plot(label='ma2',linestyle=':') plt.legend(loc='best') plt.grid(True) plt.show() # In[5]: def main(): #input the long moving average and short moving average period #for the classic MACD, it is 12 and 26 #once a upon a time you got six trading days in a week #so it is two week moving average versus one month moving average #for now, the ideal choice would be 10 and 21 global ma1,ma2,stdate,eddate,ticker,slicer #macd is easy and effective #there is just one issue #entry signal is always late #watch out for downward EMA spirals! ma1=int(input('ma1:')) ma2=int(input('ma2:')) stdate=input('start date in format yyyy-mm-dd:') eddate=input('end date in format yyyy-mm-dd:') ticker=input('ticker:') #slicing the downloaded dataset #if the dataset is too large, backtesting plot would look messy #you get too many markers cluster together slicer=int(input('slicing:')) #downloading data df=yf.download(ticker,start=stdate,end=eddate) new=signal_generation(df,macd) new=new[slicer:] plot(new, ticker) #how to calculate stats could be found from my other code called Heikin-Ashi # https://github.com/je-suis-tm/quant-trading/blob/master/heikin%20ashi%20backtest.py if __name__ == '__main__': main() ================================================ FILE: Monte Carlo project/Monte Carlo backtest.py ================================================ # coding: utf-8 # In[1]: #assuming you already know how monte carlo works #if not, plz click the link below # https://datascienceplus.com/how-to-apply-monte-carlo-simulation-to-forecast-stock-prices-using-python/ #monte carlo simulation is a buzz word for people outside of financial industry #in the industry, everybody jokes about it but no one actually uses it #including my risk quant friends, they be like why the heck use that #you may argue its application in option pricing to monitor fat tail events #seriously, did anyone predict 2008 financial crisis? #or did anyone foresee the vix surging in early 2018? #the weakness of monte carlo, perhaps in every forecast methodology #is that our pseudo random number is generated via empirical distribution #in another word, we use the past to predict the future #if something has never happened in the past #how can you predict it with our limited imagination #its like muggles trying to understand the wizard world #laplace smoothing is actually better than monte carlo in this case #the idea presented here is very straight forward #we construct a model to get mean and variance of its residual (return) #we generate the next possible price by geometric brownian motion #we run this simulations as many times as possible #naturally we should acquire a large amount of data in the end #we pick the forecast that has the least std against the original data series #we would check if the best forecast can predict the future direction (instead of actual price) #and how well monte carlo catches black swans import pandas as pd import numpy as np import matplotlib.pyplot as plt import fix_yahoo_finance as yf import random as rd from sklearn.model_selection import train_test_split # In[2]: #this list is purely designed to generate gradient color global colorlist colorlist=['#fffb77', '#fffa77', '#fff977', '#fff876', '#fff776', '#fff676', '#fff576', '#fff475', '#fff375', '#fff275', '#fff175', '#fff075', '#ffef74', '#ffef74', '#ffee74', '#ffed74', '#ffec74', '#ffeb73', '#ffea73', '#ffe973', '#ffe873', '#ffe772', '#ffe672', '#ffe572', '#ffe472', '#ffe372', '#ffe271', '#ffe171', '#ffe071', '#ffdf71', '#ffde70', '#ffdd70', '#ffdc70', '#ffdb70', '#ffda70', '#ffd96f', '#ffd86f', '#ffd76f', '#ffd66f', '#ffd66f', '#ffd56e', '#ffd46e', '#ffd36e', '#ffd26e', '#ffd16d', '#ffd06d', '#ffcf6d', '#ffce6d', '#ffcd6d', '#ffcc6c', '#ffcb6c', '#ffca6c', '#ffc96c', '#ffc86b', '#ffc76b', '#ffc66b', '#ffc56b', '#ffc46b', '#ffc36a', '#ffc26a', '#ffc16a', '#ffc06a', '#ffbf69', '#ffbe69', '#ffbd69', '#ffbd69', '#ffbc69', '#ffbb68', '#ffba68', '#ffb968', '#ffb868', '#ffb768', '#ffb667', '#ffb567', '#ffb467', '#ffb367', '#ffb266', '#ffb166', '#ffb066', '#ffaf66', '#ffad65', '#ffac65', '#ffab65', '#ffa964', '#ffa864', '#ffa763', '#ffa663', '#ffa463', '#ffa362', '#ffa262', '#ffa062', '#ff9f61', '#ff9e61', '#ff9c61', '#ff9b60', '#ff9a60', '#ff9860', '#ff975f', '#ff965f', '#ff955e', '#ff935e', '#ff925e', '#ff915d', '#ff8f5d', '#ff8e5d', '#ff8d5c', '#ff8b5c', '#ff8a5c', '#ff895b', '#ff875b', '#ff865b', '#ff855a', '#ff845a', '#ff8259', '#ff8159', '#ff8059', '#ff7e58', '#ff7d58', '#ff7c58', '#ff7a57', '#ff7957', '#ff7857', '#ff7656', '#ff7556', '#ff7455', '#ff7355', '#ff7155', '#ff7054', '#ff6f54', '#ff6d54', '#ff6c53', '#ff6b53', '#ff6953', '#ff6852', '#ff6752', '#ff6552', '#ff6451', '#ff6351', '#ff6250', '#ff6050', '#ff5f50', '#ff5e4f', '#ff5c4f', '#ff5b4f', '#ff5a4e', '#ff584e', '#ff574e', '#ff564d', '#ff544d', '#ff534d', '#ff524c', '#ff514c', '#ff4f4b', '#ff4e4b', '#ff4d4b', '#ff4b4a', '#ff4a4a'] # In[3]: #this is where the actual simulation happens #testsize denotes how much percentage of dataset would be used for testing #simulation denotes the number of simulations #theoretically speaking, the larger the better #given the constrained computing power #we have to take a balance point between efficiency and effectiveness def monte_carlo(data,testsize=0.5,simulation=100,**kwargs): #train test split as usual df,test=train_test_split(data,test_size=testsize,shuffle=False,**kwargs) forecast_horizon=len(test) #we only care about close price #if there has been dividend issued #we use adjusted close price instead df=df.loc[:,['Close']] #here we use log return returnn=np.log(df['Close'].iloc[1:]/df['Close'].shift(1).iloc[1:]) drift=returnn.mean()-returnn.var()/2 #we use dictionary to store predicted time series d={} #we use geometric brownian motion to compute the next price # https://en.wikipedia.org/wiki/Geometric_Brownian_motion for counter in range(simulation): d[counter]=[df['Close'].iloc[0]] #we dont just forecast the future #we need to compare the forecast with the historical data as well #thats why the data range is training horizon plus testing horizon for i in range(len(df)+forecast_horizon-1): #we use standard normal distribution to generate pseudo random number #which is sufficient for our monte carlo simulation sde=drift+returnn.std()*rd.gauss(0,1) temp=d[counter][-1]*np.exp(sde) d[counter].append(temp.item()) #to determine which simulation is the best fit #we use simple criterias, the smallest standard deviation #we iterate through every simulation and compare it with actual data #the one with the least standard deviation wins std=float('inf') pick=0 for counter in range(simulation): temp=np.std(np.subtract( d[counter][:len(df)],df['Close'])) if temphere for explanation) right in front of everything? Have I caught your attention? Hopefully I have. These days, blogs on data science topic are dime a dozen. Some blogs teach you how to use decision tree/random forrest to predict the stock price movement, others illustrate the possibility of back-propagation neural network to forecast a bond price. The brutal truth is, most of them are nothing but house of cards. So far, I have not heard any quant shops hit the jackpot via machine learning. Most applications of machine learning in trading are leaned towards analytics rather than prediction or execution. One quant estimates the failure rate of machine learning in live tests of trading is at about 90%. Monte Carlo, my first thought on these two words is the grand casino, where you dress up in tuxedo, meet Famke Janssen after car chase and introduce yourself in a deep sexy voice, 'Bond, James Bond'. Indeed, the simulation is named after the infamous casino in Monaco near Côte d'Azur. It actually refers to the computer simulation of massive amount of random events. This unconventional mathematical method is extremely powerful in the study of stochastic process. Here comes the argument on Linkedin that caught my eyes the other day. "Stock price can be seemed as a Wiener Process. Hence, we can use Monte Carlo simulation to predict the stock price." said a data science blog. Well, in order to be a Wiener Process, we have to assume the stock price is continuous in time. In reality, the market closes. The overnight volatility exists. But that is not the biggest issue here. The biggest issue is, can we really use Monte Carlo simulation to predict the stock price, even a range or its direction? The author offered a quite interesting idea. As he suggested, the first step was to run as many simulations as possible on stochastic differential equations to predict stock price. The goal of simulations was to pick a best fitted curve (in translation, the smallest standard deviation) compared to the historical data. There might exist a hidden pattern in the historical log return. The best fitted curve had the potential to replicate the hidden pattern and reflect it in the future forecast. The idea sounds neat, doesn't it? Inspired by his idea, we can build up the simulation accordingly. To fully unlock the potential of Monte Carlo simulation on fat tail events, the ticker we pick is General Electric, one of the worst performing stock in 2018. The share price of GE plunged 57.9% in 2018 thanks to its long history of M&A failures. The time horizon of the data series is 2016/1/15-2019/1/15. We split the series into halves, the first half as training horizon and the second half as testing horizon. Monte Carlo simulation will only justify its power if it can predict an extreme event like this. Let's take a look at the figure below. Wow, what a great fit! The best fit is almost like running a cool linear regression with valid input. As you can see, it smoothly fits the curve in training horizon. ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/ge%20simulation.png) If we extend it to testing horizon... ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/ge%20versus.png) Oops, house of cards collapses. The real momentum is completely the opposite to the forecast, let alone the actual price. The forecast looks quite okay for the first 50 days of testing horizon. After that, the real momentum falls like a stone down through the deep sea while the forecast is gently climbing up. You may argue the number of the iterations is too small so we cannot make a case. Not exactly, let's look at the figure below. ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/ge%20accuracy.png) We start from 500 times of simulation to 1500 times of simulation. Each round we increase the number by 50. We don't look at the actual price forecast, just the direction. If the end price of testing horizon is larger than the end price of training horizon, we define it as gain. Vice versa. Only when both actual and forecast directions align, we consider the forecast is accurate. As the result shows, the prediction accuracy is irrelavant to the numbers of simulation. The accuracy is more sort of tossing a coin to guess heads or tails regardless of the times of simulation. If you think 1500 is still not large enough, you can definitely try 150000, be my guest. We don't have so much computing power as an individual user (frankly no patience is the real reason) but I can assure you the result is gonna stay the same. Law of Large Numbers theorem would not work here. Now that the prophet of Monte Carlo turns out to be a con artist. Does Monte Carlo simulation have any application in risk management? Unless you are drinking the Kool-Aid. Let's extend the first figure a little bit longer to the end of testing horizon. ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/ge%20simulation2.png) Obviously, out of 500 times of simulation, none of them successfully predict the scale of the downslide. The lowest price of 500 predictions is 10.99 per share. It is still way higher than the real bottom price at 6.71 per share (no wonder GE got its ass kicked out of DJIA). The so-called fat tail event simulation is merely a mirage. If you think GE in 2018 is an extreme case, you'd be so wrong. The next ticker we test is Nvidia from 2006/1/15 to 2009/1/15. In 2008, the share price of Nvidia dropped 75.6%!! The financial crisis is the true playground for risk quants. By default, we continue to split the time horizon of NVDA into two parts by 50:50. The result is in the figure below. ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/nvda%20versus.png) Undoubtedly, the best forecast fails the expectation again. It cannot accurately predict the direction of the momentum. For the extreme event, Monte Carlo simulation cannot predict the scale of downslide, again! 6.086 per share is the lowest price we achieve from our 500 times of simulation, yet the actual lowest is at 5.9 per share. ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/nvda%20simulation.png) Still thinking about Monte Carlo for your next big project? ================================================ FILE: Oil Money project/Oil Money CAD.py ================================================ # coding: utf-8 # In[1]: import pandas as pd import os import matplotlib.pyplot as plt import copy import matplotlib.patches as mpatches from mpl_toolkits import mplot3d import matplotlib.cm as cm import statsmodels.api as sm import numpy as np from sklearn.cluster import KMeans from sklearn.metrics import silhouette_score,silhouette_samples from sklearn.model_selection import train_test_split os.chdir('d:/') # In[2]: #plot two curves on same x axis, different y axis def dual_axis_plot(xaxis,data1,data2,fst_color='r', sec_color='b',fig_size=(10,5), x_label='',y_label1='',y_label2='', legend1='',legend2='',grid=False,title=''): fig=plt.figure(figsize=fig_size) ax=fig.add_subplot(111) ax.set_xlabel(x_label) ax.set_ylabel(y_label1, color=fst_color) ax.plot(xaxis, data1, color=fst_color,label=legend1) ax.tick_params(axis='y',labelcolor=fst_color) ax.yaxis.labelpad=15 plt.legend(loc=3) ax2=ax.twinx() ax2.set_ylabel(y_label2, color=sec_color,rotation=270) ax2.plot(xaxis, data2, color=sec_color,label=legend2) ax2.tick_params(axis='y',labelcolor=sec_color) ax2.yaxis.labelpad=15 fig.tight_layout() plt.legend(loc=4) plt.grid(grid) plt.title(title) plt.show() #get distance between a point and a line def get_distance(x,y,a,b): temp1=y-x*a-b temp2=(a**2+1)**0.5 return np.abs(temp1/temp2) #create line equation from two points def get_line_params(x1,y1,x2,y2): a=(y1-y2)/(x1-x2) b=y1-a*x1 return a,b # In[3]: df=pd.read_csv('wcs crude cadaud.csv',encoding='utf-8') df.set_index('date',inplace=True) # In[4]: df.index=pd.to_datetime(df.index,format='%m/%d/%Y') # In[5]: df=df.reindex(columns= ['cny', 'gbp', 'usd', 'eur', 'krw', 'mxn', 'gas', 'wcs', 'edmonton', 'wti', 'gold', 'jpy', 'cad']) # In[6]: #create r squared bar charts var=locals() for i in df.columns: if i!='cad': x=sm.add_constant(df[i]) y=df['cad'] m=sm.OLS(y,x).fit() var[str(i)]=m.rsquared ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) width=0.7 colorlist=['#9499a6','#9499a6','#9499a6','#9499a6', '#9499a6','#9499a6','#9499a6','#582a20', '#be7052','#f2c083','#9499a6','#9499a6'] temp=list(df.columns) for i in temp: if i!='cad': plt.bar(temp.index(i)+width, var[str(i)],width=width,label=i, color=colorlist[temp.index(i)]) plt.title('Regressions on Loonie') plt.ylabel('R Squared\n') plt.xlabel('\nRegressors') plt.xticks(np.arange(len(temp))+width, ['Yuan', 'Sterling', 'Dollar', 'Euro', 'KRW', 'MXN', 'Gas', 'WCS', 'Edmonton', 'WTI', 'Gold', 'Yen'],fontsize=10) plt.show() # In[7]: #normalized value of loonie,yuan and sterling ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) (df['cny']/df['cny'].iloc[0]).plot(c='#77c9d4',label='Yuan') (df['gbp']/df['gbp'].iloc[0]).plot(c='#57bc90',label='Sterling') (df['cad']/df['cad'].iloc[0]).plot(c='#015249',label='Loonie') plt.legend(loc=0) plt.xlabel('Date') plt.ylabel('Normalized Value by 100') plt.title('Loonie vs Yuan vs Sterling') plt.show() # In[8]: #normalized value of wti,wcs and edmonton ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) (df['wti']/df['wti'].iloc[0]).plot(c='#2a78b2', label='WTI',alpha=0.5) (df['wcs']/df['wcs'].iloc[0]).plot(c='#7b68ee', label='WCS',alpha=0.5) (df['edmonton']/df['edmonton'].iloc[0]).plot(c='#110b3c', label='Edmonton',alpha=0.5) plt.legend(loc=0) plt.xlabel('Date') plt.ylabel('Normalized Value by 100') plt.title('Crude Oil Blends') plt.show() # In[9]: dual_axis_plot(df.index,df['cad'],df['wcs'], x_label='Date',y_label1='Canadian Dollar', y_label2='Western Canadian Select', legend1='Loonie', legend2='WCS', title='Loonie VS WCS in AUD', fst_color='#a5a77f',sec_color='#d8dc2c') dual_axis_plot(df.index, np.divide(df['cad'],df['usd']), np.divide(df['wcs'],df['usd']), x_label='Date',y_label1='Canadian Dollar', y_label2='Western Canadian Select', legend1='Loonie', legend2='WCS', title='Loonie VS WCS in USD', fst_color='#eb712f',sec_color='#91371b') # In[10]: #using elbow method to find optimal number of clusters df['date']=[i for i in range(len(df.index))] x=df[['cad','wcs','date']].reset_index(drop=True) sse=[] for i in range(1, 8): kmeans = KMeans(n_clusters = i) kmeans.fit(x) sse.append(kmeans.inertia_/10000) a,b=get_line_params(0,sse[0],len(sse)-1,sse[-1]) distance=[] for i in range(len(sse)): distance.append(get_distance(i,sse[i],a,b)) dual_axis_plot(np.arange(1,len(distance)+1),sse,distance, x_label='Numbers of Cluster',y_label1='Sum of Squared Error', y_label2='Perpendicular Distance',legend1='SSE',legend2='Distance', title='Elbow Method for K Means',fst_color='#116466',sec_color='#e85a4f') # In[11]: #using silhouette score to find optimal number of clusters sil=[] for n in range(2,8): clf=KMeans(n).fit(x) projection=clf.predict(x) sil.append(silhouette_score(x,projection)) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.plot(np.arange(2,len(sil)+2),sil, label='Silhouette',c='#5c0811', drawstyle='steps-mid') ax.plot(sil.index(max(sil))+2,max(sil), marker='*',markersize=20,lw=0, label='Max Score',c='#d94330') plt.ylabel('Silhouette Score') plt.xlabel('Numbers of Cluster') plt.title('Silhouette Analysis for K Means') plt.legend(loc=0) plt.show() # In[12]: #k means clf=KMeans(n_clusters=2).fit(x) df['class']=clf.predict(x) threshold=df[df['class']==0].index[-1] # In[13]: #plot clusters in 3d figure ax=plt.figure(figsize=(10,7)).add_subplot(111, projection='3d') xdata=df['wcs'] ydata=df['cad'] zdata=df['date'] ax.scatter3D(xdata[df['class']==0],ydata[df['class']==0], zdata[df['class']==0],c='#faed26',s=10,alpha=0.5, label='Before {}'.format(threshold.strftime('%Y-%m-%d'))) ax.scatter3D(xdata[df['class']==1],ydata[df['class']==1], zdata[df['class']==1],c='#46344e',s=10,alpha=0.5, label='After {}'.format(threshold.strftime('%Y-%m-%d'))) ax.grid(False) for i in ax.w_xaxis, ax.w_yaxis, ax.w_zaxis: i.pane.set_visible(False) ax.set_xlabel('WCS') ax.set_ylabel('Loonie') ax.set_zlabel('Date') ax.set_title('K Means on Loonie') ax.legend(loc=6,bbox_to_anchor=(0.12, -0.1), ncol=4) plt.show() #to generate gif, u can use the following code #it generates 3d figures from different angles #use imageio to concatenate """ for ii in range(0,360,10): ax.view_init(elev=10., azim=ii) plt.savefig("cad kmeans%d.png" % (ii)) import imageio filenames=["movie%d.png" % (ii) for ii in range(0,360,10)] images=list(map(lambda filename:imageio.imread(filename), filenames)) imageio.mimsave('cad kmeans.gif',images,duration = 0.2) """ # In[14]: #create before/after regression comparison #the threshold is based upon the finding of k means m=sm.OLS(df['cad'][df['class']==0],sm.add_constant(df['wcs'][df['class']==0])).fit() before=m.rsquared m=sm.OLS(df['cad'][df['class']==1],sm.add_constant(df['wcs'][df['class']==1])).fit() after=m.rsquared ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.bar(['Before {}'.format(threshold.strftime('%Y-%m-%d')), 'After {}'.format(threshold.strftime('%Y-%m-%d'))], [before,after],color=['#f172a1','#a1c3d1']) plt.ylabel('R Squared') plt.title('Cluster + Regression') plt.show() # In[15]: #create 1 std, 2 std band for i in range(2): x_train,x_test,y_train,y_test=train_test_split( sm.add_constant(df['wcs'][df['class']==i]), df['cad'][df['class']==i],test_size=0.5,shuffle=False) m=sm.OLS(y_test,x_test).fit() forecast=m.predict(x_test) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) forecast.plot(label='Fitted',c='#ab987a') y_test.plot(label='Actual',c='#ff533d') ax.fill_between(y_test.index, forecast+np.std(m.resid), forecast-np.std(m.resid), color='#0f1626', \ alpha=0.6, \ label='1 Sigma') ax.fill_between(y_test.index, forecast+2*np.std(m.resid), forecast-2*np.std(m.resid), color='#0f1626', \ alpha=0.8, \ label='2 Sigma') plt.legend(loc=0) title='Before '+threshold.strftime('%Y-%m-%d') if i==0 else 'After '+threshold.strftime('%Y-%m-%d') plt.title(f'{title}\nCanadian Dollar Positions\nR Squared {round(m.rsquared*100,2)}%\n') plt.xlabel('\nDate') plt.ylabel('CADAUD') plt.show() ================================================ FILE: Oil Money project/Oil Money COP.py ================================================ # coding: utf-8 # In[1]: import pandas as pd import os import matplotlib.pyplot as plt import statsmodels.api as sm import seaborn as sns import numpy as np from sklearn.model_selection import train_test_split os.chdir('k:/') # In[2]: #plot two curves on same x axis, different y axis def dual_axis_plot(xaxis,data1,data2,fst_color='r', sec_color='b',fig_size=(10,5), x_label='',y_label1='',y_label2='', legend1='',legend2='',grid=False,title=''): fig=plt.figure(figsize=fig_size) ax=fig.add_subplot(111) ax.set_xlabel(x_label) ax.set_ylabel(y_label1, color=fst_color) ax.plot(xaxis, data1, color=fst_color,label=legend1) ax.tick_params(axis='y',labelcolor=fst_color) ax.yaxis.labelpad=15 plt.legend(loc=3) ax2=ax.twinx() ax2.set_ylabel(y_label2, color=sec_color,rotation=270) ax2.plot(xaxis, data2, color=sec_color,label=legend2) ax2.tick_params(axis='y',labelcolor=sec_color) ax2.yaxis.labelpad=15 fig.tight_layout() plt.legend(loc=4) plt.grid(grid) plt.title(title) plt.show() # In[3]: #read dataframe df=pd.read_csv('vas crude copaud.csv',encoding='utf-8') df.set_index('date',inplace=True) df.index=pd.to_datetime(df.index) # In[4]: #run regression on each input D={} for i in df.columns: if i!='cop': x=sm.add_constant(df[i]) y=df['cop'] m=sm.OLS(y,x).fit() D[i]=m.rsquared D=dict(sorted(D.items(),key=lambda x:x[1],reverse=True)) # In[5]: #create r squared bar charts colorlist=[] for i in D: if i =='wti': colorlist.append('#447294') elif i=='brent': colorlist.append('#8fbcdb') elif i=='vasconia': colorlist.append('#f4d6bc') else: colorlist.append('#cdc8c8') ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) width=0.7 for i in D: plt.bar(list(D.keys()).index(i)+width, D[i],width=width,label=i, color=colorlist[list(D.keys()).index(i)]) plt.title('Regressions on COP') plt.ylabel('R Squared\n') plt.xlabel('\nRegressors') plt.xticks(np.arange(len(D))+width, [i.upper() for i in D.keys()],fontsize=8) plt.show() # In[6]: #normalized value of wti,brent and vasconia ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) (df['vasconia']/df['vasconia'].iloc[0]).plot(c='#6f6ff4', label='Vasconia',alpha=0.5) (df['brent']/df['brent'].iloc[0]).plot(c='#e264c0', label='Brent',alpha=0.5) (df['wti']/df['wti'].iloc[0]).plot(c='#fb6630', label='WTI',alpha=0.5) plt.legend(loc=0) plt.xlabel('Date') plt.ylabel('Normalized Value by 100') plt.title('Crude Oil Blends') plt.show() # In[7]: #cop vs gold dual_axis_plot(df.index,df['cop'],df['gold'], x_label='Date',y_label1='Colombian Peso', y_label2='Gold LBMA', legend1='COP', legend2='Gold', title='COP VS Gold', fst_color='#96CEB4',sec_color='#FFA633') #cop vs usd dual_axis_plot(df.index,df['cop'],df['usd'], x_label='Date',y_label1='Colombian Peso', y_label2='US Dollar', legend1='COP', legend2='USD', title='COP VS USD', fst_color='#9DE0AD',sec_color='#5C4E5F') # In[8]: #cop vs brl dual_axis_plot(df.index,df['cop'],df['brl'], x_label='Date',y_label1='Colombian Peso', y_label2='Brazilian Real', legend1='COP', legend2='BRL', title='COP VS BRL', fst_color='#a4c100',sec_color='#f7db4f') #usd vs mxn dual_axis_plot(df.index,df['usd'],df['mxn'], x_label='Date',y_label1='US Dollar', y_label2='Mexican Peso', legend1='USD', legend2='MXN', title='USD VS MXN', fst_color='#F4A688',sec_color='#A2836E') #cop vs mxn dual_axis_plot(df.index,df['cop'],df['mxn'], x_label='Date',y_label1='Colombian Peso', y_label2='Mexican Peso', legend1='COP', legend2='MXN', title='COP VS MXN', fst_color='#F26B38',sec_color='#B2AD7F') # In[9]: #cop vs vasconia dual_axis_plot(df.index,df['cop'],df['vasconia'], x_label='Date',y_label1='Colombian Peso', y_label2='Vasconia Crude', legend1='COP', legend2='Vasconia', title='COP VS Vasconia', fst_color='#346830',sec_color='#BBAB9B') # In[10]: #create before/after regression comparison m=sm.OLS(df['cop'][:'2016'],sm.add_constant(df['vasconia'][:'2016'])).fit() before=m.rsquared m=sm.OLS(df['cop']['2017':],sm.add_constant(df['vasconia']['2017':])).fit() after=m.rsquared ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.bar(['Before 2017', 'After 2017'], [before,after],color=['#82b74b', '#5DD39E']) plt.ylabel('R Squared') plt.title('Before/After Regression') plt.show() # In[11]: #create 1 std, 2 std band before 2017 x_train,x_test,y_train,y_test=train_test_split( sm.add_constant(df['vasconia'][:'2016']), df['cop'][:'2016'],test_size=0.5,shuffle=False) m=sm.OLS(y_test,x_test).fit() forecast=m.predict(x_test) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) forecast.plot(label='Fitted',c='#FEFBD8') y_test.plot(label='Actual',c='#ffd604') ax.fill_between(y_test.index, forecast+np.std(m.resid), forecast-np.std(m.resid), color='#F4A688', alpha=0.6, label='1 Sigma') ax.fill_between(y_test.index, forecast+2*np.std(m.resid), forecast-2*np.std(m.resid), color='#8c7544', alpha=0.8, label='2 Sigma') plt.legend(loc=0) plt.title(f'Colombian Peso Positions\nR Squared {round(m.rsquared*100,2)}%\n') plt.xlabel('\nDate') plt.ylabel('COPAUD') plt.show() # In[12]: #create 1 std, 2 std band after 2017 x_train,x_test,y_train,y_test=train_test_split( sm.add_constant(df['vasconia']['2017':]), df['cop']['2017':],test_size=0.5,shuffle=False) m=sm.OLS(y_test,x_test).fit() forecast=m.predict(x_test) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) forecast.plot(label='Fitted',c='#FEFBD8') y_test.plot(label='Actual',c='#ffd604') ax.fill_between(y_test.index, forecast+np.std(m.resid), forecast-np.std(m.resid), color='#F4A688', alpha=0.6, label='1 Sigma') ax.fill_between(y_test.index, forecast+2*np.std(m.resid), forecast-2*np.std(m.resid), color='#8c7544', \ alpha=0.8, \ label='2 Sigma') plt.legend(loc=0) plt.title(f'Colombian Peso Positions\nR Squared {round(m.rsquared*100,2)}%\n') plt.xlabel('\nDate') plt.ylabel('COPAUD') plt.show() # In[13]: #shrink data size for better viz dataset=df['2016':] dataset.reset_index(inplace=True) # In[14]: #import the strategy script as this is a script for analytics and visualization #the official trading strategy script is in the following link # https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/Oil%20Money%20Trading%20backtest.py import oil_money_trading_backtest as om #generate signals,monitor portfolio performance #plot positions and total asset signals=om.signal_generation(dataset,'vasconia','cop',om.oil_money,stop=0.001) p=om.portfolio(signals,'cop') om.plot(signals,'cop') om.profit(p,'cop') # In[15]: #try different holding period and stop loss/profit point dic={} for holdingt in range(5,20): for stopp in np.arange(0.001,0.005,0.0005): signals=om.signal_generation(dataset,'vasconia','cop',om.oil_money, holding_threshold=holdingt, stop=round(stopp,4)) p=om.portfolio(signals,'cop') dic[holdingt,round(stopp,4)]=p['asset'].iloc[-1]/p['asset'].iloc[0]-1 profile=pd.DataFrame({'params':list(dic.keys()),'return':list(dic.values())}) # In[16]: #plotting the distribution of return ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) profile['return'].apply(lambda x:x*100).hist(histtype='bar', color='#b2660e', width=0.45,bins=20) plt.title('Distribution of Return on COP Trading') plt.grid(False) plt.ylabel('Frequency') plt.xlabel('Return (%)') plt.show() # In[17]: #plotting the heatmap of return under different parameters #try to find the optimal parameters to maximize the return #convert the dataframe into a matrix format first matrix=pd.DataFrame(columns=[round(i,4) for i in np.arange(0.001,0.005,0.0005)]) matrix['index']=np.arange(5,20) matrix.set_index('index',inplace=True) for i,j in profile['params']: matrix.at[i,round(j,4)]= profile['return'][profile['params']==(i,j)].item()*100 for i in matrix.columns: matrix[i]=matrix[i].apply(float) #plotting fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) sns.heatmap(matrix,cmap=plt.cm.viridis, xticklabels=3,yticklabels=3) ax.collections[0].colorbar.set_label('Return(%)\n', rotation=270) plt.xlabel('\nStop Loss/Profit (points)') plt.ylabel('Position Holding Period (days)\n') plt.title('Profit Heatmap\n',fontsize=10) plt.style.use('default') #it seems like the return doesnt depend on the stop profit/loss point #it is correlated with the length of holding period #the ideal one should be 17 trading days #as for stop loss/profit point could range from 0.002 to 0.005 ================================================ FILE: Oil Money project/Oil Money NOK.py ================================================ # coding: utf-8 # In[1]: #i call it oil money #cuz its a statistical arbitrage on crude benchmark and petrocurrency #the inspiration came from an article i read #it suggested to trade on petrocurrency when the oil price went uprising #plus overall volatility for forex market was low #the first thing is to build up a model to explore the causality #we split the historical datasets into two parts #one for the model estimation, the other for the model validation #we do a regression on estimation horizon #we use linear regression to make a prediction on ideal price level #we set up thresholds based on the standard deviation of residual #take one deviation above as the upper threshold #if the currency price breaches the upper threshold #take a short position as it is assumed to revert to its 'normal' price range soon #vice versa #so its kinda like bollinger bands #however, our regression is based on statistics #we still need to consider fundamental influence #what if the market condition has changed #in that case our model wont work any more #well,all models lose their creditability over the time #denote the price deviating two sigmas away from predicted value as model failure #which we should revert our positions #e.g. the price is two sigmas above our predicted value #we change our short to long since the market has changed its sentiment #there is probably hidden information in the uprising price #lets follow the trend and see where it ends #this idea sounds very silly #nobody actually does it or not that i know of #i just wanna to see if the idea would work #perhaps the idea would bring a huge loss #nonetheless, it turns out to be a big surprise! #first, we choose our currency norwegian krone #norway is one of the largest oil producing countries with floating fx regime #other oil producing countries such as saudi, iran, venezuela have their fx pegged to usd #russia is supposed to be a good training set #nevertheless, russia gets sanctioned by uncle sam a lot #we would see this in the next script # https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/Oil%20Money%20RUB.py #after targetting at norwegian krone, we have to choose a currency to evaluate nok #take a look at norway's biggest trading partners #we should include us dollar, euro and uk sterling as well as brent crude price in our model #in addition, the base currency would be japanese yen #cuz its not a big trading partner with norway #which implies it doesnt have much correlation with nok #preparation is done, lets get started! import matplotlib.pyplot as plt import statsmodels.api as sm import pandas as pd import numpy as np import seaborn as sns from sklearn.linear_model import ElasticNetCV as en from statsmodels.tsa.stattools import adfuller as adf import os os.chdir('d:/') # In[2]: df=pd.read_csv('brent crude nokjpy.csv') df.set_index(pd.to_datetime(df[list(df.columns)[0]]),inplace=True) del df[list(df.columns)[0]] # In[3]: #identification #first of first, using scatter plot to visualize the correlation #lets denote data from 2013-4-25 to 2017-4-25 as estimation horizon/training set #lets denote data from 2017-4-25 to 2018-4-25 as validation horizon/testing set ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.scatter(df['brent'][df.index<'2017-04-25'],df['nok'][df.index<'2017-04-25'],s=1,c='#5f0f4e') plt.title('NOK Brent Correlation') plt.xlabel('Brent in JPY') plt.ylabel('NOKJPY') plt.show() #if we run a covariance matrix on nok and brent, we got #np.corrcoef(df['nok'],df['brent']) #array([[1. , 0.89681228],[0.89681228, 1. ]]) #dual axis plot def dual_axis_plot(xaxis,data1,data2,fst_color='r', sec_color='b',fig_size=(10,5), x_label='',y_label1='',y_label2='', legend1='',legend2='',grid=False,title=''): fig=plt.figure(figsize=fig_size) ax=fig.add_subplot(111) ax.set_xlabel(x_label) ax.set_ylabel(y_label1, color=fst_color) ax.plot(xaxis, data1, color=fst_color,label=legend1) ax.tick_params(axis='y',labelcolor=fst_color) ax.yaxis.labelpad=15 plt.legend(loc=3) ax2 = ax.twinx() ax2.set_ylabel(y_label2, color=sec_color,rotation=270) ax2.plot(xaxis, data2, color=sec_color,label=legend2) ax2.tick_params(axis='y',labelcolor=sec_color) ax2.yaxis.labelpad=15 fig.tight_layout() plt.legend(loc=4) plt.grid(grid) plt.title(title) plt.show() #nok vs ir dual_axis_plot(df.index,df['nok'],df['interest rate'], fst_color='#34262b',sec_color='#cb2800', fig_size=(10,5),x_label='Date', y_label1='NOKJPY',y_label2='Norges Bank Interest Rate %', legend1='NOKJPY',legend2='Interest Rate', grid=False,title='NOK vs Interest Rate') #nok vs brent dual_axis_plot(df.index,df['nok'],df['brent'], fst_color='#4f2d20',sec_color='#3feee6', fig_size=(10,5),x_label='Date', y_label1='NOKJPY',y_label2='Brent in JPY', legend1='NOKJPY',legend2='Brent', grid=False,title='NOK vs Brent') #nok vs gdp #cuz gdp is released quarterly #we need to convert nok into quarterly data as well ind=df['gdp yoy'].dropna().index dual_axis_plot(df.loc[ind].index, df['nok'].loc[ind], df['gdp yoy'].dropna(), fst_color='#116466',sec_color='#ff652f', fig_size=(10,5),x_label='Date', y_label1='NOKJPY',y_label2='Norway GDP YoY %', legend1='NOKJPY',legend2='GDP', grid=False,title='NOK vs GDP') #Now we do our linear regression x0=pd.concat([df['usd'],df['gbp'],df['eur'],df['brent']],axis=1) x1=sm.add_constant(x0) x=x1[x1.index<'2017-04-25'] y=df['nok'][df.index<'2017-04-25'] model=sm.OLS(y,x).fit() print(model.summary(),'\n') # In[4]: #from the summary u can tell there is multicollinearity #the condition number is skyrocketing #alternatively, i can use elastic net regression to achieve the convergence #check the link below for more details # https://github.com/je-suis-tm/machine-learning/blob/master/coordinate%20descent%20for%20elastic%20net.ipynb m=en(alphas=[0.0001, 0.0005, 0.001, 0.01, 0.1, 1, 10], l1_ratio=[.01, .1, .5, .9, .99], max_iter=5000).fit(x0[x0.index<'2017-04-25'], y) print(m.intercept_,m.coef_) #elastic net estimation results: #3.79776228406 [ 0.00388958 0.01992038 0.02823187 0.00050092] # In[5]: #calculate the fitted value of nok df['sk_fit']=(df['usd']*m.coef_[0]+df['gbp']*m.coef_[1]+ df['eur']*m.coef_[2]+df['brent']*m.coef_[3]+m.intercept_) # In[6]: #getting the residual df['sk_residual']=df['nok']-df['sk_fit'] #one can always argue what if we eliminate some regressors #in econometrics, if adding extra variables do not decrease adjusted r squared #or worsen AIC, BIC #we should include more information as long as it makes sense # In[7]: #lets generate signals based on the elastic net #we set one sigma of the residual as thresholds #two sigmas of the residual as stop orders #which is common practise in statistics upper=np.std(df['sk_residual'][df.index<'2017-04-25']) lower=-upper signals=pd.concat([df[i] for i in ['nok', 'usd', 'eur', 'gbp', 'brent', 'sk_fit','sk_residual']], \ axis=1)[df.index>='2017-04-25'] signals['fitted']=signals['sk_fit'] del signals['sk_fit'] signals['upper']=signals['fitted']+upper signals['lower']=signals['fitted']+lower signals['stop profit']=signals['fitted']+2*upper signals['stop loss']=signals['fitted']+2*lower signals['signals']=0 # In[8]: #while doing a traversal #we apply the rules mentioned before #if actual price goes beyond upper threshold #we take a short and bet on its reversion process #vice versa #we use cumsum to make sure our signals only get generated #for the first time condions are met #when actual price hits the stop order boundary #we revert our positions #u may wonder whats next for breaking the boundary #well, we stop the signal generation algorithm #we need to recalibrate our model or use other trend following strategies index=list(signals.columns).index('signals') for j in range(len(signals)): if signals['nok'].iloc[j]>signals['upper'].iloc[j]: signals.iloc[j,index]=-1 if signals['nok'].iloc[j]1 or signals['cumsum'].iloc[j]<-1: signals.iloc[j,index]=0 if signals['nok'].iloc[j]>signals['stop profit'].iloc[j]: signals['cumsum']=signals['signals'].cumsum() signals.iloc[j,index]=-signals['cumsum'].iloc[j]+1 signals['cumsum']=signals['signals'].cumsum() break if signals['nok'].iloc[j]0].index, signals['nok'][signals['signals']>0], lw=0,marker='^',c='#83af9b',label='LONG', markersize=10) ax.plot(signals.loc[signals['signals']<0].index, signals['nok'][signals['signals']<0], lw=0,marker='v',c='#fe4365',label='SHORT', markersize=10) ax.plot(pd.to_datetime('2017-12-20'), signals['nok'].loc['2017-12-20'], lw=0,marker='*',c='#f9d423', markersize=15, alpha=0.8, label='Potential Exit Point of Momentum Trading') plt.axvline('2017/11/15',linestyle=':',c='k',label='Exit') plt.legend() plt.title('NOKJPY Positions') plt.ylabel('NOKJPY') plt.xlabel('Date') plt.show() # In[10]: #the second figure explores thresholds and boundaries for signal generation #we can see after 2017/11/15, nokjpy price went skyrocketing #as a data scientist, we must ask why? #is it a problem of our model identification #or the fundamental situation of nokjpy or oil changed ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) signals['fitted'].plot(lw=2.5,label='Fitted',c='w',alpha=0.6) signals['nok'].plot(lw=2,label='Actual',c='#04060f',alpha=0.8) ax.fill_between(signals.index,signals['upper'], signals['lower'],alpha=0.2,label='1 Sigma',color='#2a3457') ax.fill_between(signals.index,signals['stop profit'], signals['stop loss'],alpha=0.1,label='2 Sigma',color='#720017') plt.legend(loc='best') plt.title('Fitted vs Actual') plt.ylabel('NOKJPY') plt.xlabel('Date') plt.show() # In[11]: #if we decompose nokjpy into long term trend and short term random process #we could clearly see that brent crude price has dominated short term random process #so what changed the long term trend? #there are a few possible reasons #saudi and iran endorsed an extension of production caps on that particular date #donald trump got elected as potus so he would encourage a depreciated us dollar #which ultimately pushed up the oil price # In[12]: #lets normalize all prices by 100 #its easy to see that nok follows euro #and economics explanation would be norway is in eea #its economy heavily relies on eu ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) (df['nok']/df['nok'][0]*100).plot(c='#ff8c94',label='Norwegian Krone',alpha=0.9) (df['usd']/df['usd'][0]*100).plot(c='#9de0ad',label='US Dollar',alpha=0.9) (df['eur']/df['eur'][0]*100).plot(c='#45ada8',label='Euro',alpha=0.9) (df['gbp']/df['gbp'][0]*100).plot(c='#f8b195',label='UK Sterling',alpha=0.9) (df['brent']/df['brent'][0]*100).plot(c='#6c5b7c',label='Brent Crude',alpha=0.5) plt.legend(loc='best') plt.ylabel('Normalized Price by 100') plt.xlabel('Date') plt.title('Trend') plt.show() # In[13]: #that still doesnt sound convincable #lets try cointegration test #academically we should use johansen test which works on multi dimensions #unfortunately, there is no johansen test in statsmodels (at the time i wrote this script) #well, here we go again #we have to use Engle-Granger two step! #salute to Engle, mentor of my mentor Gallo #to the nobel prize winner #im not gonna explain much here #if u have checked my other codes, u sould know #details are in pair trading session # https://github.com/je-suis-tm/quant-trading/blob/master/Pair%20trading%20backtest.py x2=df['eur'][df.index<'2017-04-25'] x3=sm.add_constant(x2) model=sm.OLS(y,x3).fit() ero=model.resid print(adf(ero)) print(model.summary()) #(-2.5593457642922992, 0.10169409761939013, 0, 1030, #{'1%': -3.4367147300588341, '5%': -2.8643501440982058, '10%': -2.5682662399849185}, -1904.8360920752475) #0.731199409071 #unfortunately, the residual hasnt even reached 90% confidence interval #we cant conclude any cointegration from the test #still, from the visualization #we can tell nok and eur are somewhat correlated #our rsquared suggested euro has the power of 73% explanation on nok # In[14]: #then lets do a pnl analysis capital0=2000 positions=100 portfolio=pd.DataFrame(index=signals.index) portfolio['holding']=signals['nok']*signals['cumsum']*positions portfolio['cash']=capital0-(signals['nok']*signals['signals']*positions).cumsum() portfolio['total asset']=portfolio['holding']+portfolio['cash'] portfolio['signals']=signals['signals'] # In[15]: portfolio=portfolio[portfolio.index>'2017-10-01'] portfolio=portfolio[portfolio.index<'2018-01-01'] # In[16]: #we plot how our asset value changes over time ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) portfolio['total asset'].plot(c='#594f4f',alpha=0.5,label='Total Asset') ax.plot(portfolio.loc[portfolio['signals']>0].index,portfolio['total asset'][portfolio['signals']>0], lw=0,marker='^',c='#2a3457',label='LONG',markersize=10,alpha=0.5) ax.plot(portfolio.loc[portfolio['signals']<0].index,portfolio['total asset'][portfolio['signals']<0], lw=0,marker='v',c='#720017',label='The Big Short',markersize=15,alpha=0.5) ax.fill_between(portfolio['2017-11-20':'2017-12-20'].index, (portfolio['total asset']+np.std(portfolio['total asset']))['2017-11-20':'2017-12-20'], (portfolio['total asset']-np.std(portfolio['total asset']))['2017-11-20':'2017-12-20'], alpha=0.2, color='#547980') plt.text(pd.to_datetime('2017-12-20'), (portfolio['total asset']+np.std(portfolio['total asset'])).loc['2017-12-20'], 'What if we use MACD here?') plt.axvline('2017/11/15',linestyle=':',label='Exit',c='#ff847c') plt.legend() plt.title('Portfolio Performance') plt.ylabel('Asset Value') plt.xlabel('Date') plt.show() #surprising when our model is valid for prediction #its difficult to make money from thresholds oscillating #when actual price goes beyond stop order boundary #that is basically the most profitable trade ever #best to follow up with a momentum strategy #maybe this is not a statistical arbitrage after all #the model is a trend following entry indicator # In[17]: #now lets construct a trend following strategy based on the previous strategy #call it oil money version 2 or whatever #here i would only import the strategy script as this is a script for analytics and visualization #the official trading strategy script is in the following link # https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/Oil%20Money%20Trading%20backtest.py import oil_money_trading_backtest as om #generate signals,monitor portfolio performance #plot positions and total asset signals=om.signal_generation(dataset,'brent','nok',om.oil_money) p=om.portfolio(signals,'nok') om.plot(signals,'nok') om.profit(p,'nok') #but thats not enough, we are not happy with the return #come on, 2 percent return? #i may as well as deposit the money into the current account #and get 0.75% risk free interest rate #therefore, we gotta try different holding period and stop loss/profit point #the double loop is very slow, i almost wanna do it in julia #plz go get a coffee or even lunch and dont wait for it dic={} for holdingt in range(5,20): for stopp in np.arange(0.3,1.1,0.05): signals=om.signal_generation(dataset,'brent','nok',om.oil_money \ holding_threshold=holdingt, \ stop=stopp) p=om.portfolio(signals,'nok') dic[holdingt,stopp]=p['asset'].iloc[-1]/p['asset'].iloc[0]-1 profile=pd.DataFrame({'params':list(dic.keys()),'return':list(dic.values())}) # In[18]: #plotting the distribution of return #in average the return is 2% #but we can get -6% and 6% as extreme values #we dont give a crap about average #we want the largest positive return ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) profile['return'].apply(lambda x:x*100).hist(histtype='bar', \ color='#f09e8c', \ width=0.45,bins=20) plt.title('Distribution of Return on NOK Trading') plt.grid(False) plt.ylabel('Frequency') plt.xlabel('Return (%)') plt.show() # In[19]: #plotting the heatmap of return under different parameters #try to find the optimal parameters to maximize the return #turn the dataframe into a matrix format first matrix=pd.DataFrame(columns= \ [round(i,2) for i in np.arange(0.3,1.1,0.05)]) matrix['index']=np.arange(5,20) matrix.set_index('index',inplace=True) for i,j in profile['params']: matrix.at[i,round(j,2)]= \ profile['return'][profile['params']==(i,j)].item()*100 for i in matrix.columns: matrix[i]=matrix[i].apply(float) #plotting fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) sns.heatmap(matrix,cmap='gist_heat_r',square=True, \ xticklabels=3,yticklabels=3) ax.collections[0].colorbar.set_label('Return(%) \n', \ rotation=270) plt.xlabel('\nStop Loss/Profit (points)') plt.ylabel('Position Holding Period (days)\n') plt.title('Profit Heatmap\n',fontsize=10) plt.style.use('default') #it seems like the return doesnt depend on the stop profit/loss point #it is correlated with the length of holding period #the ideal one should be 9 trading days #as for stop loss/profit point could range from 0.6 to 1.05 ================================================ FILE: Oil Money project/Oil Money RUB.py ================================================ # coding: utf-8 # In[1]: import os import pandas as pd import numpy as np import statsmodels.api as sm import matplotlib.pyplot as plt import re os.chdir('d:/') df=pd.read_csv('urals crude rubaud.csv') # In[2]: df.set_index('date',inplace=True) df.index=pd.to_datetime(df.index) df.dropna(inplace=True) # In[3]: #this is the part to create r squared of different regressors #in different years for stepwise regression #we can use locals to create lists for different currency #each list contains r squared of different years year=df.index.year.drop_duplicates().tolist() var=locals() for i in df.columns: if i!='rub': var[i]=[] for j in year: x=sm.add_constant(df[i][str(j):str(j)]) y=df['rub'][str(j):str(j)] m=sm.OLS(y,x).fit() var[i].append(m.rsquared) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) #to save you from the hassle #just use these codes to generate the bar chart width=0.3 colorlist=['#c0334d','#d6618f','#f3d4a0','#f1931b'] bar=locals() for j in range(len(year)): bar[j]=[var[i][j] for i in df.columns if i!='rub'] plt.bar(np.arange(1,len([i for i in df.columns if i!='rub'])*2+1,2)+j*width, bar[j],width=width,label=year[j],color=colorlist[j]) plt.legend(loc=0) plt.title('Stepwise Regression Year by Year') plt.ylabel('R Squared') plt.xlabel('Regressors') plt.xticks(np.arange(1,len([i for i in df.columns if i!='rub'])*2+1,2)+(len(year)-1)*width/2, ['Urals Crude', 'Japanese\nYen', 'Euro', 'Henry Hub', 'Chinese\nYuan', 'Korean\nWon', 'Ukrainian\nHryvnia'],fontsize=10) plt.show() # In[4]: #this is similar to In[3] #In[3] is r squared of each regressor in each year #In[4] is r squared of each regressor of years cumulated var=locals() for i in df.columns: if i!='rub': var[i]=[] for j in year: x=sm.add_constant(df[i][:str(j)]) y=df['rub'][:str(j)] m=sm.OLS(y,x).fit() var[i].append(m.rsquared) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) width=0.3 colorlist=['#04060f','#03353e','#0294a5','#a79c93'] bar=locals() for j in range(len(year)): bar[j]=[var[i][j] for i in df.columns if i!='rub'] plt.bar(np.arange(1,len([i for i in df.columns if i!='rub'])*2+1,2)+j*width, bar[j],width=width,label=year[j],color=colorlist[j]) plt.legend(loc=0) plt.title('Stepwise Regression Year Cumulated') plt.ylabel('R Squared') plt.xlabel('Regressors') plt.xticks(np.arange(1,len([i for i in df.columns if i!='rub'])*2+1,2)+(len(year)-1)*width/2, ['Urals Crude', 'Japanese\nYen', 'Euro', 'Henry Hub', 'Chinese\nYuan', 'Korean\nWon', 'Ukrainian\nHryvnia'],fontsize=10) plt.show() # In[5]: #print model summary and actual vs fitted line chart x=sm.add_constant(pd.concat([df['urals']],axis=1)) y=df['rub'] m=sm.OLS(y['2017':'2018'],x['2017':'2018']).fit() print(m.summary()) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.plot(df.loc['2017':'2018'].index,m.predict(), \ c='#0abda0',label='Fitted') ax.plot(df.loc['2017':'2018'].index, \ df['rub']['2017':'2018'],c='#132226',label='Actual') plt.legend(loc=0) plt.title('Russian Ruble 2017-2018') plt.ylabel('RUBAUD') plt.xlabel('Date') plt.show() # In[6]: #print model summary and actual vs fitted line chart x=sm.add_constant(pd.concat([df['urals'],df['eur']],axis=1)) y=df['rub'] m=sm.OLS(y[:'2016'],x[:'2016']).fit() print(m.summary()) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.plot(df.loc[:'2016'].index,m.predict(), \ c='#c05640',label='Fitted') plt.plot(df.loc[:'2016'].index,df['rub'][:'2016'], \ c='#edd170',label='Actual') plt.legend(loc=0) plt.title('Russian Ruble Before 2017') plt.ylabel('RUBAUD') plt.xlabel('Date') plt.show() # In[7]: #normalize different regressors by 100 as the initial value #so that we can observe the trend of different regressors in the same scale ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) (df['urals']['2017':'2018']/df['urals']['2017':'2018'].iloc[0]*100).plot(label='Urals Crude',c='#728ca3',alpha=0.5) (df['jpy']['2017':'2018']/df['jpy']['2017':'2018'].iloc[0]*100).plot(label='Japanese Yen',c='#99bfaa') (df['eur']['2017':'2018']/df['eur']['2017':'2018'].iloc[0]*100).plot(label='Euro',c='#5c868d') (df['rub']['2017':'2018']/df['rub']['2017':'2018'].iloc[0]*100).plot(label='Russian Ruble',c='#000000') plt.legend(loc=0) plt.title('2017-2018 Trend') plt.ylabel('Normalized Value by 100') plt.xlabel('Date') plt.show() # In[8]: #plot actual vs fitted line chart for each year #including one sigma and two sigma confidence interval for i in df.index.year.drop_duplicates(): temp=df.loc[str(i):str(i)] train=temp.iloc[:int(len(temp)/3)] test=temp.iloc[int(len(temp)/3):] x=sm.add_constant(train['urals']) y=train['rub'] m=sm.OLS(y,x).fit() forecast=m.predict(sm.add_constant(test['urals'])) resid=np.std(train['rub']-m.predict()) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.plot(test.index, \ forecast, \ label='Fitted',c='#f5ca99') test['rub'].plot(label='Actual',c='#ed5752') ax.fill_between(test.index, \ forecast+resid, \ forecast-resid, \ color='#1e1f26', \ alpha=0.8, \ label='1 Sigma') ax.fill_between(test.index, \ forecast+2*resid, \ forecast-2*resid, \ color='#d0e1f9', \ alpha=0.7, \ label='2 Sigma') plt.legend(loc='best') plt.title(f'{i} Russian Ruble Positions\nR Squared {round(m.rsquared*100,2)}%\n') plt.ylabel('RUBAUD') plt.xlabel('Date') plt.legend() plt.show() ================================================ FILE: Oil Money project/Oil Money Trading backtest.py ================================================ # coding: utf-8 # In[1]: #here is the official trading strategy script for this lil project #the details could be found in the readme of the repo, section norwegian krone and brent crude # https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/README.md import statsmodels.api as sm import copy import pandas as pd import numpy as np import matplotlib.pyplot as plt import os os.chdir('d:/') # In[2]: #theoratically we only need two sigma to trigger the trading signals #i only add one sigma to make it look better in visualization def oil_money(dataset): df=copy.deepcopy(dataset) df['signals']=0 df['pos2 sigma']=0.0 df['neg2 sigma']=0.0 df['pos1 sigma']=0.0 df['neg1 sigma']=0.0 df['forecast']=0.0 return df # In[3]: #the trading idea is straight forward #we run regression on nok and brent of the past 50 data points by default #if the rsquared exceeds 0.7 by default #the regression model is deemed valid #we calculate the standard deviation of the residual #and use +/- two sigma as the threshold to trigger the trading signals #once the trade is executed #we would start a counter to count the period of position holding #if the holding period exceeds 10 days by default #we clear our positions #meanwhile, if the spread between current price and entry price exceeds stop limit #which is 0.5 points by default in both ways #we clear our positions to claim profit/loss #once our positions are cleared #we recalibrate our regression model based on the latest 50 data points #we keep doing this on and on def signal_generation(dataset,x,y,method, \ holding_threshold=10, \ stop=0.5,rsquared_threshold=0.7, \ train_len=50): df=method(dataset) #variable holding takes 3 values, -1,0,1 #0 implies no holding positions #1 implies long, -1 implies short #when we wanna clear our positions #we just reverse the sign of holding #which is quite convenient holding=0 #trained is a boolean value #it indicates whether the current model is valid #in another word,when trained==True, r squared is over 0.7 by default #and the regressand is within two sigma range from the fitted value trained=False #counter counts the days of position holding counter=0 for i in range(train_len,len(df)): #when we have uncleared positions if holding!=0: #when counter exceeds holding threshold #we clear our positions and reset all the parameters if counter>holding_threshold: df.at[i,'signals']=-holding holding=0 trained=False counter=0 #we use continue to skip this round of iteration #only if the clearing condition gets triggered continue #plz note i make stop loss and stop profit symmetric #thats why we use absolute value of the spread between current price and entry price #usually stop loss and stop profit are asymmetric #as ppl cannot take as much loss as profit if np.abs( \ df[y].iloc[i]-df[y][df['signals']!=0].iloc[-1] \ )>=stop: df.at[i,'signals']=-holding holding=0 trained=False counter=0 continue counter+=1 else: #if we do not have a valid model yet #we would keep trying the latest 50 data points if not trained: X=sm.add_constant(df[x].iloc[i-train_len:i]) Y=df[y].iloc[i-train_len:i] m=sm.OLS(Y,X).fit() #if r squared meets the statistical request #which is 0.7 by default #we can start to build up confidence intervals if m.rsquared>rsquared_threshold: trained=True sigma=np.std(Y-m.predict(X)) #plz note that we set the forecast and confidence intervals #for every data point after the current one #this would fill in the blank once our model turns invalid #when we have a new valid model #the new forecast and confidence intervals would cover the former one df.at[i:,'forecast']= \ m.predict(sm.add_constant(df[x].iloc[i:])) df.at[i:,'pos2 sigma']= \ df['forecast'].iloc[i:]+2*sigma df.at[i:,'neg2 sigma']= \ df['forecast'].iloc[i:]-2*sigma df.at[i:,'pos1 sigma']= \ df['forecast'].iloc[i:]+sigma df.at[i:,'neg1 sigma']= \ df['forecast'].iloc[i:]-sigma #once we have a valid model #we can feel free to generate trading signals if trained: if df[y].iloc[i]>df['pos2 sigma'].iloc[i]: df.at[i,'signals']=1 holding=1 #once the positions are entered #we set confidence intervals back to the fitted value #so we could avoid the confusion in our visualization #for instance. if we dont do that, #there would be confidence intervals even when the model is broken #we could have been asking why no trade has been executed, #even when actual price falls out of the confidence intervals? df.at[i:,'pos2 sigma']=df['forecast'] df.at[i:,'neg2 sigma']=df['forecast'] df.at[i:,'pos1 sigma']=df['forecast'] df.at[i:,'neg1 sigma']=df['forecast'] if df[y].iloc[i]Intro * Norwegian Krone and Brent Crude * Russian Ruble and Urals Crude * Canadian Dollar and Western Canadian Select * Colombian Peso and Vasconia Crude * Discussion * Further Reading ------------------------------------------------   ### Intro This project is inspired by an article on oil-backed foreign exchange. Amid the bullish outlook for crude oil, the currency exchange of oil producing countries would also bounce back. Does this statement really hold? Prior to this article by Bloomberg (or many other similar research), market analysts test the correlation between petrocurrency and oil price, instead of the causality. The issue is that correlation does not equal to causality. Correlation could be a coincidence of a math game. We simply cannot draw the conclusion that oil price moves the currency (the cause can be a third common factor such as inflation). Some researchers even introduce bootstrapping which, unfortunately, destroys the autocorrelation of time series. Thus, it is necessary for us to apply empirical analysis and computer simulation on various petrocurrencies to examine the underlying phenomenon. The following figure is a global oil production choropleth. The map lists out a couple of petrocurrencies with potential arbitrage opportunities. What can be easily overlooked is that some of the oil exporting economies peg domestic currencies to US dollar. For the central banks, the peg eliminates the volatile currency risk for oil exporting. For the traders, the room for petrocurrency arbitrage is squeezed. So it is crucial to verify the exchange rate regime of any oil exporting country from wikipedia before moving onto any further analysis. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/oil%20production%20choropleth.PNG) ###### Unfortunately GitHub ReadMe does not support javascript. Click here to be redirected to an interactive version of the oil production choropleth. The figure below is a global oil production cost curve. Don't ask me why the data is 2015. They said data is the new oil, this is true especially when it comes to oil data. As we can see, the marginal players in this chart are Brazil and UK. Their production cost has reached 90% percentile among these countries. This explains the decade-long inactivity in North Sea oil field. The only feature of Aberdeen has been Angus beef (proudly made in Scotland) since the time of Margaret Thatcher. And for Brazil, I'd say the production cost absolutely has something to do with the corruption probe in Petrobras. Probably it is why iron ore export makes more money than crude oil in Amazon jungles (Vale is de jure privatized yet Petrobras is state-owned). Hence, we will exclude the largest crude oil producer in LATAM from our oil money project. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/oil%20production%20cost%20curve.png) Okay, enough about bad jokes. You may ask why I talk so much about commodity market at the beginning. If you think quantitative trading is about solving some complex stochastic process on commodity options, prepare to lose a big chunk of money. You simply cannot quantify geopolitical risk or supply disruption by force majeure. Some basic knowledge of underlying commodity is vital to your trading strategy. ### Norwegian Krone and Brent Crude In the original article by Bloomberg, the first mention is Norwegian Krone. Norway is one of my favorite places in Europe. Unlike Qatar or Saudi Arabia or any other Gulf/OPEC countries, the government doesn't heavily rely on oil or gas for its gross income (even though Equinor formerly Statoil is still a major player in Oslo Stock Exchange). According to wikipedia, over 60% of GDP is contributed by services in contrast to approximately 30% by industry in 2016 (arguably those services could still be oil-based like Dubai). Norway has established the largest sovereign fund in the world to hedge against oil price decline, ever since the discovery of north sea oil fields. Norway has non-petroleum industries such as fishing, maritime, renewable energy, etc. I doubt if oil price is the major driver of the exchange rate of NOK. I look into international trading statistics of Norway. Apparently, most trading partners are inside European Union. Prior to this report, I include Sterling and Euro into the price evaluation model of NOK. To my surprise, Norway actually does a lot of business with US. Hence, the model regressor consists of EUR, GBP, USD and Brent Crude. After the selection, we have to choose a base currency to evaluate NOK. It should be a stable entity with free floating FX regime with not much economic tie to Norway. I pick the safe haven currency in East Asia, Japanese Yen. In a released report by OEC, Japan only accounts for less than 2% of exports in 2017 which makes a perfect candidate. Then all regressors in the model would be priced in JPY. Some of you may question why we do not use trade-weighted exchange rate. Indeed, trade-weighted exchange rate is a better choice as it eliminates all other trading partner currencies in the model. The model can solemnly focus on the exporting commodities. However, the pain point is how to construct such exchange rate index. When we talk about trade weights, do we refer to surplus or deficit or total amount of trade? A country can certainly trade with more than 100 partners. Is it reasonable to include every trading partner currency into the weight? Or at what percentile of trade in values do we cut off the list? Why does that percentile make more sense than the others? Constructing a new index is rather state of art than social science. Obviously, it is easier and more efficient to use a non-trading partner currency for evaluation of all the variables. Hence, our regressor variables become EURJPY, GBPJPY, USDJPY and Brent Crude in JPY. Our regressand variable is NOKJPY. Arguably, the model should involve natural gas (Dutch TTF?) as well. From the website of norskpetroleum, Norway supplies 25% of EU natural gas demand (mainly France and UK). It is interesting that many natural gas contracts are not tied to gas benchmark such as Henry Hub or TTF. In most cases, the price is linked to Brent, sometimes even coal. Of course, there are other elements that affect NOK. It is widely acknowledged that change of interest rate impacts the foreign exchange significantly. However, the downside of interest rate is its slow response to the financial market. Central bankers assess the overall condition and review their decisions carefully and patiently. The rate hike may only occur after pickup of inflation rate or employment rate. It could be several times one year and silent for the next couple of years. By the time inflation rate is boosted by soaring oil price, NOK has priced that factor in for a long while. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20vs%20ir.png) Another important element is economic activity, GDP Year-on-Year growth. Inadequate amount of the data is its biggest flaw. GDP is usually released by statistics bureau quarterly. Forex market is agile and it moves every weekday 24/7. We cannot trade only 4 days a year and stay put for the rest of 246 days. Some indicators are seen as early signs, such as active oil rigs or social financing. These indicators are released on a monthly basis, slightly better than GDP. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20vs%20gdp.png) Thus, Brent and other currency pairs are undisputedly better inputs to reflect whether NOK is undervalued or overvalued at the moment. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20vs%20brent.png) The data of the past five years is collected from Thomson Reuters (now called Refinitiv). We denote the time horizon before 2017-04-25 as training period. We use that period to fit a regression model. From 2017-04-25 to the end of our dataset is defined as testing period. We use our model from training horizon to predict "reasonable" range of the value of NOK in testing horizon. This is a standard practice called cross validation by data scientists. Economists call it out-of-sample data for forward testing and in-sample data for backtesting. The regression result comes out as below. We have a pretty high R squared. All T stats and F stats seem to be significant. I have to take back my words. Brent shows a major influence on NOK which implies Norway still heavily depends on petrochemical industry. As the summary suggests, there could be multicollinearity (condition number is large and R squared is large). Obviously, Brent crude and US dollar should be negatively correlated. Most commodity future contracts are priced in US dollar. When US dollar appreciates or depreciates, the underlying commodity price is likely to go the opposite direction. There could be a cointegration relationship between Sterling and Euro for pre-Brexit time as well. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20correlation.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20model%20summary.png) In this case, we will use elastic net regression to implement regularization. Elastic net is a statistics/machine learning technique that consists of both Lasso (L1) and Ridge (L2) regression to act as a penalty. Ideally it is a perfect tool for multicollinearity issues. Before backtesting, we ought to set up thresholds for signal generation. One sigma two-sided range is the common practice in statistical arbitrage. When actual NOK price goes above the upper threshold (larger than one sigma), we take a short position. We hold the belief that NOK is overvalued and it should fall back to its normal range very soon. Vice versa. However, the model is based on historical data. No models can precisely predict the future from the past. Our estimation is most likely to be overfitted and fail very quickly in the near future. We need to set up some thresholds for stop orders. When the model breaks, we could clear our positions and exit the trades gracefully. In that case, let's use another golden rule in statistics, two sigmas with 95% confidence interval, to do the trick. If NOK deviates 2 sigmas away from our fitted value, we need to realize the model is broken and we shall exit the trades right away. The figures below show the initial trading strategy. They demonstrate the positions of our statistical arbitrage and the actual price movement against the fitted value within confidence intervals. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20oil%20money%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20fitted%20vs%20actual.png) To our surprise, there is a strong momentum after our model breaks. The momentum is independent of the selection of our training horizon. In another word, no matter which period we use as training horizon, the strong momentum always follows through right after the model breaks. The failure of this model doesn't really upset me. On the contrary, it is a blessing in disguise. What I see is an opportunity for trend following strategy! We will get back to that very soon. What also interests me is why the model fails after 2017/11/15. Well, there is no way that a universal model can exist and work forever. Most models have short memory due to the dynamic environment of macroeconomics and geo-politics. Based on adaptive market hypothesis developed by Professor Andrew Lo from MIT, the players in the market are always evolving along with the fast-paced environment. Therefore, we should anticipate our model to lose its power sooner or later. Still, what is the cause of the break? For a quantamental analysis, we have only completed the quant part. I would not get into too much of rigorous and boring part of the fundamentals. Instead, I intend to bring up a short but insightful discussion here. What could possibly be the reason of this dramatic change? Could it be that Saudi and Iran endorsed an extension of oil production cap to boost up the oil price on that particular date? Or Donald Trump got elected as POTUS so he would encourage a weak US dollar and lift up restrictions on oil export as promised during his campaign? If we consider the price of NOK as a stochastic process, we can decompose NOK price into long term trend and short term random disturbance. Well, apparently short term is dominated by Brent Crude. It partially justifies our model. What really drives the long term trend though? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20trend.png) Ta-da, its Euro. As Norway is in EEA, its economic tie with EU totally dominates the long term trend of NOK. From the normalized figure, we clearly see the trend of both NOK and EUR are somewhat correlated. To get a formal conclusion, we need a cointegration test. Nevertheless, there is no Johansen Test in statsmodel package (not on the date when the first draft of oil money was finished, but there is now). We would have to use Engle-Granger two step test. I have to honorably mention that this method is co-developed by the mentor of my mentor, Robert F. Engle, a Nobel Laureate! Unfortunately, we can't get any confirmation of cointegration from the test. The residual of the first step regression is not stationary under Augmented Dickey-Fuller Test. Sometimes we have to use the old fashion way to make a qualitative judgement, rule of thumb. Most researchers in big organizations recalibrate their forecast with policy or experience or consensus views or simply instinct (as an insider, I guarantee you this is 100% true). This is the moment that I exercise my sacred right to declare that EUR is the driver of NOK's long term trend! ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20EG%20failed.png) Well, I am not an economist (even though my work has a lot to do with them). I do not expect to really find out what happened on 2017/11/15 through our quantamental analysis. Let's call it an end to this twist (if you are an economics-savvy person who is eager to know more, feel free to read this paper by the Central Bank of Norway). In fact, we can simplify our model to NOK driven by Brent. From an econometrician's perspective, it does not sound like a good idea. Every coefficient of the model is statistically significant. Adding more variables does not worsen AIC, BIC or adjusted R squared. There is no incentive for us to remove variables as more information in the model is always better. From a trader's perspective, the requirement is a universal model. Ideally, the model contains two variables, one is the underlying petrocurrency, the other is the local crude oil contract. In this sense, the reduced form model can be replicated to any petrocurrency without too much focus on analyzing trade partners or exporting products. The argument here could be, is linear regression model too naïve? Nick Patterson, a cold war cryptographer who later worked in Renaissance Technologies, said (check here for the original version of 45-minute-long interview), >One tool that Renaissance uses is simple regression with one target and one independent.
It's simple, but effective if you know how to avoid mistakes just waiting to be made. In the world of modelling, the identification is far more important than the estimation. As long as we find an element with causal effect, there is no need for fancy spatial time series analysis when we can solve everything in its simplest form. We will take the trader's perspective in the following context. Next, let's take a look at the portfolio performance. So far so good, we actually make a few bucks from statistical arbitrage. Interestingly, after we place the stop order, I decide to add an extra position to see what would happen if we follow the trend. In the figure below, we could see the downwards momentum doesn't stop until two months later (probably another major event in financial market). ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20asset%20value.png) Wow, did we just discover a momentum trading strategy! We started off this project to seek for a statistical arbitrage opportunity between crude price and petrocurrency. What we got in the end is an entry signal of momentum trading strategy. Also, we found out Euro is the major and long term influence on Norwegian Krone, and Brent Crude is the short term disturbance. My explanation for our discovery is that, when the model breaks, there must be something fundamental that change investors' outlook in NOK or Brent, e.g. an increase in north sea refinery capacity limit. That sort of change is supposed to last for quite a while which offers us a chance for trend following (this is how CTA makes money). Here are the rules of our latest momentum trading strategy. * The first step is always about regression. Run linear regression on NOKJPY and Brent in JPY of the past 50 data points. If the R squared exceeds 70%, the model is deemed as valid, which has successfully verified the petrocurrency status of Norwegian Krone for the past 50 trading days. Then the forecast derived from the model becomes reliable. * Calculate the standard deviation of the residual. Set +/- two sigma from the predicted price as the threshold to trigger trading signals. If the actual price sits above the upper threshold, the position is net long. If the actual price sits below the lower threshold, the position is net short. * Once the trade is executed, a counter will start as well. It will keep track of how long the position has been held. If the holding period exceeds 10 days, the position will be cleared. Because the underlying momentum could have vanished into the thin air after such a long time. * Meanwhile, if the absolute spread between the current price and the entry price exceeds preset limit, which is 0.5 points by default, the position will be cleared to claim profit/loss. The preset spread limit varies along with each individual's risk averse level. When the market gets too volatile, it is sensible to reduce the risk exposure. * After the position gets cleared, the model has to be recalibrated by the latest 50 data points. Now that a trade cycle has completed, the whole thing goes back to the first step. So on and so forth. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20trading%20positions.png) As shown in the portfolio performance, each momentum takes different length of time to decay. Holding the position too short may not reach the peak of the asset price. On the other hand, Holding the position too long may surpass the peak and head towards the lower side of the profit curve. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20trading%20asset.png) Nonetheless, we are not satisfied with the return. We are greedy creatures. 2% return? Why don't we deposit the money into the current account and get some risk free interest (Norges Bank interest rate at 1% as on the 30th of April, 2019)? We certainly need to tune the parameters, such as different holding period and stop loss/profit point (even the amount of backtesting data points or acceptable R squared level), to maximize the return. After several attempts, we have gathered the below statistics. In average, the return is around 2%, positively skewed. Yet, extreme values can go as far as -6% to 6%. Needless to say, 6% is the goal. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20profit%20distribution.png) The heatmap below is the visualization of return using different parameters. The darker the tile is, the more money you make. From the chart, you can easily tell stop profit/loss point doesn't have much explanatory power on the return. The return is more correlated with the length of holding period. It makes sense since this is a trend following strategy. The optimal holding period to maximize the return appears to be 9 trading days. The optimal stop loss/profit point is more flexible, which could range from 0.6 to 1.05. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/nok%20profit%20heatmap.png) It turns out that our momentum trading is much more robust and profitable than our original idea of statistical arbitrage. But does it work on any other petrocurrencies? Unfortunately, Norway is one of the largest oil producing countries with floating FX regime. The rest are US, Russia and Canada. US dollar is a totally different case. Petroleum business only takes up a very small share in US economy even including shale boom in Permian Basin. What about Russian Ruble? Well, let's find out! ### Russian Ruble and Urals Crude For Norway, I may have doubts in how much petroleum business contributes to its overall GDP. As for Russia, I suspect if any person in her/his rightful mind would question the role of oil in the economy of Russia. According to Wikipedia, Russian oil business (mostly Rosneft) accounted for 16% of GDP, 52% of federal budget revenues and over 70% of total exports in 2012. Usually, countries with large natural resource reserves suffer from Dutch Disease (USA is an exception), especially Russia! Hence, we don't need any extra step to validate if Russian Ruble is a petrocurrency. First step, let's identify the regressors. If we look at trade statistics, the biggest trading partners with Russia are EU, China, Ukraine, Belarus, Japan and Korea. Belarusian Ruble BYR is very strange. It has been pegged to both Russian Ruble and US dollar. But the central bank interferes the currency rate too frequently. I would argue the currency regime is a completely mess (thanks to oligarchs). I'd rather not include Belarusian Ruble as it is not a big player in global or regional economy. So we are left with Euro, Chinese Yuan, Ukrainian Hryvnia, Japanese Yen and Korean Won. Australia, another country with rich natural resources, basically doesn't make many direct trades with Russia. Fantastic! Australian dollar can be leveraged as the base to evaluate RUB,EUR,CNY,UAH,JPY and KRW. Instead of Brent, Russia has its own version of blending called Urals. We would take Urals spot price as a benchmark for oil. Apart from Urals, Russia also exports natural gas to Europe via Gazprom. The best benchmark for natural gas in the continent is Dutch TTF gas future contracts. When the tension of Nord Stream 2 pipeline is settled, the benchmark is probably gonna be German NCG gas future contracts (or maybe some extra benchmarks for South Stream and Power of Siberia). The saying goes, gas is the power and oil is the money when it comes to Russian exports. There we go, the preparation is done. Yet, Russian Ruble is very special. Russia has been sanctioned by US and EU for so many times (really feel sorry for those innocent Russian civilians). To know when and what, someone actually creates a timeline for us. Each major sanction should make a huge impact on the currency. In this case, we use a method called stepwise regression to test each potential regressor for each year. We would pick out the R squared winners out of 7 variables from the past 4 years to construct a robust model. The figure below shows R squared of each variable for each year. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%20stepwise1.png) The figure below shows R squared of each variable for cumulated years. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%20stepwise2.png) Here are some interesting facts. Apart from Japanese Yen, Korean Won and Ukrainian Hryvnia, R squared year by year on other currencies or commodities are literally plunging from 2015 to 2018. The biggest cause is the sanctions. Ever since the annexation of Crimea, military intervention in Syria and nerve agent attack in UK, the sanction on Russia is getting more and more severe. Most countries except some rogue ones (e.g. China, Iran, Venezuela) decline to trade with Russia. Thus, we are able to observe the R squared downhill of Dutch TTF gas, Euro and Chinese Yuan over the years. Even though R squared on Urals jumps up in 2018, there is another key indicator that warns us of the danger. We would find out very soon. Before that, it is also strange that there are some spikes of R squared on Japanese Yen. My initial guess was that Japanese Yen became the safe haven for Russia turmoil. Frankly, it is more of a coincidence after some digging into the data. The spikes are simply because of the sluggish growth of Japan economy, which coincides with the downtrend of Russian Ruble. The same applies to Korean Won. As for Ukrainian Hryvnia, its R squared barely exceeds 20% so we simply ignore it. Now let us take a look at R squared of year cumulated. We could easily draw the same conclusion as before that R squared of most regressors are declining over the years (Korean Won looks like a bell shape curve though). 2017 and 2018 seem to be the roughest years for Russia. In that case, I prefer to split the backtesting data into pre-2017 and post-2017. For pre-2017 data, the model seems to be very robust. Urals alone explains more than 80% of the price movement of Russian Ruble. The introduction of Euros into the model is optional. It indeed increases a significant amount (more than 2%) of R squared compared to other regressors. AIC, BIC and adjusted R squared also justifies the theory. Although in the following models, we would only include Urals Crude as a regressor. The reason behind that is to keep the model consistent across different currencies and different commodities (recalled from NOK section, we prefer trader's perspective). ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%20ols%20-2016.PNG) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%20model%20-2016.png) For post-2017 data, we can tell this is when the sanction bites. Urals can only explain less than 30% of the price movement of Russian Ruble. Moreover, the coefficient of Urals is even negative which contradicts the fact that Russian Ruble is a petrocurrency. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%20ols%202017-.PNG) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%20model%202017-.png) If we track the price for Urals, Japanese Yen, Euro and Russian Ruble from 2017 and 2018, we will get a clear picture of how these assets move along the time axis. The stagnant performance of Japanese Yen and Euro implies the post-recession economy growth of two of the most influential blocs in the world. The surge of Urals from the beginning of 2018 does not translate into the performance of Russian Ruble. The sanction on Rusal which deeply disrupted aluminum market and the sanction in response to Russia's gas attack on UK soil hit Russian Ruble further down. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%202017-%20trend.png) In terms of trading strategies, Russian Ruble is too geopolitical event driven for any quantitative analysis. What we do here is trying to split the data of each year with a ratio of 30:70 into training and testing. We would apply whatever we have learned from the training dataset to backtest our momentum trading entry points. For the first two years, our model captures pretty solid R squared. The actual price of Russian Ruble barely drifts two standard deviations away from our forecast price. Nonetheless, there are two sides of this story. The good news is that our model identification is perfectly correct but the bad news is that our strategy only works when the model begins to break. We only want the model to be 80% correct instead of 100%! As an old saying goes, there is no way to beat the markets if the markets are fully efficient. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%202015%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%202016%20positions.png) For 2017 and 2018, the R squared becomes total failures. It drops from less than 10% to less than 1% within 2 years. Still, you can argue that this strategy sort of works. When the model breaks in 2017, the downward pressure on Russian Ruble lasts more than a month. Although it sounds very tempting for the wide margin we can exploit, the R squared for that model is only 7%! Is it really worth the risk? I don't know what you folks think. I had a formal academic statistics training. A model with ridiculously low R squared and insignificant coefficients does not appeal to me. I strongly urge people to be cautious. When the model isn't robust (say R squared less than 50%), this trading strategy isn't plausible. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%202017%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/rub%202018%20positions.png) My conclusion for Russian Ruble is DON'T TRADE IT!! Its political agendas always screw up its petrocurrency status. A recent article by Financial Times coincides with my theory. Trading is more like a marathon rather than a 100m sprint. Nobody would love to see sanctions kick in like Bête Noire. I don't really think Russian Ruble is worth the risk. Is that it? Nope, lucky for us, we still have one more petrocurrency, Canadian Dollar, to test our strategies. ### Canadian Dollar and Western Canadian Select For some bizarre reason, everybody says Canadian Dollar is a petrocurrency. We all know Canada is a country with huge deposits of natural resources. However, it never strikes me as a heavy weight player in the petroleum industry. According to Canadian government, Canada is the fourth largest crude oil exporter. But hey, why does it catch so little attention in the oil market? Because 96% of its production is shipped to Uncle Sam. Similar to U.S., Canada has oil pipeline bottleneck as well. Both have attempted to expand the capacity. But both have faced huge resistance from indigenous people and environmental protection. For Canada, there are two major local crude oil contracts we need to take into consideration. One is Western Canadian Select. In contrast to the conventional crude oil, WCS comes from oil sands. It is extracted via open pit mining or steam injection rather than oil rig drilling. The molecular level of WCS is quite heavy and its sulfur content is graded as sour. The other local contract is called Edmonton Synthetic Crude. It is a form of light sweet crude oil upgraded from oil sands. The upgrade facilities break down the heavy molecule and remove sulfur content from bitumen. Thus, the synthetic crude can directly flow to refinery as inputs. Because the crude oil export mainly serves the Yankees, we choose West Texas Intermediate, the domestic benchmark for U.S., instead of Brent. You can check Alberta government website for the pricing of WCS. Based upon the information from International Trade Centre, mineral fuel is not the only export. Canada also exports a lot of other natural resources including natural gas, precious gems, base metals and agricultural products. In that sense, we also welcome gold and LNG into the model. Despite both Canada and Australia are in Five Eyes Alliance, the trade flow between Canada and Australia is quite limited. Australian dollar becomes the ideal base currency. Canada is a member of NAFTA. It is no surprise that both United States and Mexico are Canada's predominant trading partners. Also, Canada is in the ring of Asia Pacific. It maintains active trading relationships with west Pacific countries like Japan, China and Korea. The only surprise is the trade flow between Canada and EU (including UK). Hence, we come up with a model contains WCS, Edmonton, WTI, LNG, Gold, USD, MXN, EUR, GBP, JPY, CNY and KRW. When we run regressand on each regressor individually, in-sample data regression shows no sign of petrocurrency at all. None of the hydrocarbon products (as highlighted in the figure below) have R squared over 5%! The astonishing result really contradicts the market belief that Loonie is a petrocurrency. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20model.png) Nobody has expected 35% of the outcome can be explained by UK Sterling and Chinese Yuan. It is quite unusual that US dollar does not have the strongest R squared. If we look at GBP and CNY, normalized values on forex imply UK Sterling and Chinese Yuan were in sync until Brexit referendum ruined everything. The cointegration between GBP and CNY doesn't make a lot of sense. Is it because of the golden era between UK and China? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20currency.png) If we look at the hydrocarbon products, normalized values on crude oil blends demonstrate that Canadian blends are indeed associated with West Texas Intermediate. The light sweet synthetic crude is closely stick to the movement of WTI. WCS drifts off the course occasionally. It is probably caused by some tightening market condition (e.g. the reduction of heavy sour refinery capacity by force majeure). In general, all three crude oil contracts move towards the same direction. With that being said, we can exclude the possibility of faulty petroleum data. So where does the theory of Canadian petrocurrency come from? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20crude.png) Let's take a step back and look at what most market analysts focus on. Most studies on Loonie use raw exchange rate of CADUSD. As shown by the figures below, Loonie and WCS priced in different currencies show diverging results. It appears that so-called petrocurrency status is possibly due to the dollar effect. Most commodities are evaluated in US dollar. It's very intuitive that the commodity price in US dollar tends to show a smaller volatility compared to the commodity price in other currencies. The reason is quite simple. For commodities priced in other currencies, they need to convert to US dollar for international settlement. US dollar is the one and only global currency (hopefully Euro can find its rightful place). Given the bid and ask spread of currency exchange, it tends to widen the gap between currency and underlying asset. Some studies use trade-weighted exchange rate. Nevertheless, the bilateral trade between Canada and U.S. makes up 75% of the trade surplus for Canada. The significant impact of dollar effect on trade-weighted exchange rate makes it de facto CADUSD. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20wcs%20in%20aud.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20wcs%20in%20usd.png) Our finding is still not solid enough. Recall how Russian Ruble gets flagged by aggressive espionage? Perhaps Canadian Dollar shows different attributes across different time horizon as well. It is definitely not caused by sanction. It could be the monetary policy change by central bank or one of the revolutionary reforms by Justin Trudeau (no sarcasm intended). To confess, Canada is not the spotlight of the financial market, so most people are not familiar with its internal situation. Thanks to the over publicity of machine learning, we have the luxury to borrow some tools from unsupervised learning. K-Means is applied here to find out the clustering on time horizon. Loonie, WCS and date are the dimensions. There are various techniques to determine the optimal number of the cluster. For this mission, both elbow method and silhouette score are taken into consideration. I have encountered several occasions that two metrics give out two different answers. That is why we ought to use different methods to reach a final decision. Fortunately, we can observe the consistent performance of K-Means with K equals to 2. Thus, we shall split the dataset into two different parts. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20elbow.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20silhouette.png) There are some shortcomings of using K-Means. While most cluster problems in machine learning focus on discrete variable, the autocorrelation of time series is not taken into account. Hence, we need to visualize the data to make a judgmental call. In some cases, cluster A is uniformly distributed across the time horizon. we do not see a clear threshold on a specific date to separate two different clusters. Lucky for us, we get a clean cut on March 2nd of 2016. The boundary of two clusters is a flat surface on z axis. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20kmeans.gif) Don't ask me what happened on March 2nd of 2016. I did a thorough search in the historical archives but came back empty handed. Nonetheless, even if we split the timeframe in regard to the threshold, we still cannot observe a significant R squared from in-sample regression. For the first period, we get respectively 20% R squared. And for the second, we get roughly 10% R squared. It seems that I cannot justify the causal relationship between Loonie and WCS. Is Canadian Dollar really a petrocurrency? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20groups.png) The next step is to conduct out-of-sample regression. The result surprisingly outperforms in-sample regression. For each period, we take a 70/30 train test split. The R squared is guaranteed to be above 20%. Though it hasn't hit our 70% target. If we merely take a look at the visualization, we will see the actual price is often within the two standard deviation bandwidth. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20before.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cad%20after.png) In a nutshell, we have exhausted approaches to validate the petrocurrency status of Canadian Dollar. I personally do not believe Loonie is a petrocurrency. In 2018, mineral fuel takes up about 22% of the total export, compared to 53% for Russia and 62% for Norway. Loonie and WCS are in sync if and only if both assets are denominated in US dollar. Therefore, I reject the null hypothesis that Canadian Dollar is a petrocurrency. Some market analysts talk about the relationship between Mexican Peso and Maya crude oil. In 2018, the vehicles occupy 26% of the total export. On the contrary, mineral oil is such a niche segment in the export business. The number is as pathetic as 7%. I really hope those analysts can give me a more convincing narrative. Even though Loonie is not a petrocurrency, that shouldn't stop us from deploying our trading strategy. Unlike the eccentric volatility of Russian Ruble, the political environment of Canada is harmonic, so unusual spikes are not expected. The model per se is based upon rolling period of the past 50 trading days. The market is dynamic so there will always be a moment when both Loonie and WCS enter Nirvana. The bottom line is the preset model threshold. As long as we can obtain a 70% R squared, the game is on. ### Colombian Peso and Vasconia Crude Thus far, we have tested three different currencies yet only one of them is really applicable. Don't worry, here comes the bonus stage. Just when I thought this project is finished, one day my colleague came to my desk and asked me, "do you know what the biggest export of Colombia is?" "La cocaína!" I answered without hesitation. "Well, you watched too much Narcos and Escobar, not that." One of his eyebrows lifted. "Prostitutes? A large part of web cam models come from Colombia, maybe de facto Venezuelan refugees in Bogotá or Medellín." "Jeez, if I am Colombian, I'm gonna execute you the drug cartel way. On the book, it's CRUDE OIL!!" Lo siento, no offense, Colombians. Surprisingly, mineral fuels took up 52.5% of export in terms of value! In 2018, U.S., China and Panama have taken roughly 76.4% of Colombia's crude oil export. However, it only has a very small market share (not even top 20) compared to other big major oil producers and it is not a member of OPEC. Its supply has been eroded by frequent attacks from guerillas on pipelines from Cupiagua to Coveñas. That's why the country is almost invisible when we discuss the oil market. The good news is we don't really care about how Colombia impacts the overall oil market. We merely want to profit from its currency fluctuation caused by oil export. Anyhow, let's take a peep at local crude blends in Colombia. The major products are Cusiana, Caño Limón, Vasconia, Puerto Bahía and Castilla (API from light to heavy, sulfur content from sweet to sour). Although Castilla is the major export to U.S. (find more details from EIA), we can only obtain Vasconia price from Bloomberg, so we have to cope with constrained data availability. Similar to Canada, the biggest customer of Colombian crude blends is Uncle Sam. Thus, West Texas Intermediate is a more appropriate benchmark than Brent. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20crude.png) Besides crude oil, Colombia has other exports, one of the most well-known is coffee beans. Colombia is the second largest coffee bean producer trailing only after Brazil. There are two types of coffee beans, Arabica and Robusta. Arabica is the predominant species in Colombia with its bright acidity, sweet notes, and caramel aroma rising from every brew. However, Robusta has a higher yield and less demanding conditions to grow. Concerning the rising menace of climate change, the bitter and intensive taste has been gradually introduced to Colombia as well. Hence, we would love to test ICE Arabica and Robusta futures price to make sure Vasconia crude is the major factor of Colombian Peso. Apart from the high-profile coffee beans, coal briquette is another big export business in Colombia. Most coals are shipped to Europe, so we pick Rotterdam API 2 coal futures as our benchmark. As for the gold in Colombia, we still follow gold LBMA price in London. If you recall, we have been using Australian dollar to evaluate Russian Ruble and Canadian Dollar. It is still applicable to Colombian Peso. It seems that there are few trades among big commodity exporters. The input of the model also considers Colombia's top trading partners. Inevitably, we have US dollar and Chinese Yuan, the high-tech manufacturer and the cheap-shit manufacturer. It's hard to imagine there is a country in the world who doesn't trade with this pair (even with sanction you can still trade with one of the pair, you know which one). Most of Colombia's trading partners are in Latin America. These trading partners either use US dollar (Ecuador) or issue their own currencies pegged to US dollar (Eastern Caribbean Dollar). All we need is to add a few currencies from south American countries, Argentina Peso, Peruvian Sol and Brazilian Real. Additionally, we cannot forget Mexican Peso and Turkish Lira. You may wonder, what about Euros? What a sad story! US dollar is the one and only global currency. ICE Rotterdam API 2 coal futures are priced in US dollar. The regression on the input has verified our theory, Colombian Peso is a petrocurrency! Crude oil can achieve roughly 50% of R squared. Coffee beans or coal briquettes do not have R squared over 20%. Although Colombia has a larger market share in these two commodities than oil, they do not have enough influence in absolute USD value. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20model.png) The shining performance of US dollar should be within our expectation. After all, all crude oils are priced in US dollar. Oil price and US dollar are negatively correlated. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20usd.png) The gold has outperformed crude oil in terms of R squared but its coefficient is negative which implies the gold just represents the negative correlation with crude oil. This is hardly a surprise. Both gold and US dollar are regarded as safe haven assets where crude oil is a leading indicator of the economy. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20gold.png) For Brazilian Real, the raison d'être of high R squared is straight forward. Brazil is a huge commodity exporter as well. Brazil and Colombia have a vast overlap in terms of commodity export (you can check OEC for detailed export breakdown). They both export a massive amount of oil, coffee, sugar and gold. Commodity price has a negative relationship with US dollar and a positive relationship with local currency. Thus, we see a quasi-causality between Brazilian Real and Colombian Peso. Why quasi? Colombia doesn't even make it to top 10 of Brazil's trading partners. Brazil has the 7th largest trading deficit with Colombia. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20brl.png) For Mexican Peso, it is slightly complicated. Both Mexico and Colombia have some degree of overlap in terms of commodity export (check OEC for detailed export breakdown). Oil is one of them. Mexican Peso has been called "la petrocurrency" by many analysts. Indeed, we have barely heard of Ecopetrol in Colombia but certainly Pemex with its Maya crude oil. Still, I believe its petrocurrency status was in 2000s. In 2019, the petroleum industry only occupied 5.6% of export. Even in absolute USD value, Colombia exceeds Mexico in oil export. These days the major export for Mexico is automobiles and machineries which Donald Trump has tried very hard to lure U.S. companies to bring back the supply chain. Some other commodities include gold and agricultural products. Yet, it is not a solid argument. Unlike Brazilian Real, Mexican Peso doesn't strictly follow negative correlation with US dollar. They are more like a couple, sometimes they :smile: sometimes they :sob: ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20usd%20vs%20mxn.png) Another point is Mexico has the second largest trading deficit with Colombia. Colombia is a very small trading partner to Mexico. Thus, we see the following figure. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20mxn.png) From the chart below, we can observe the intertwined relationship between Colombian Peso and Vasconia Crude until 2017. In 2017, the value of Colombian Peso went fiasco, but the crude oil enjoyed a bonanza caused by OPEC production cut. Intuitively we should split the dataset into two groups, pre-2017 and post-2017. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20vs%20vas.png) By running a standard oil money regression, pre-2017 dataset demonstrates a bona fide 80% R squared. In comparison, post-2017 dataset confirms no more entangled relationship between Colombian Peso and Vasconia Crude. R squared doesn’t even exceed 30%. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20groups.png) Using a traditional train test split, pre-2017 dataset turns out with a lower R squared, 50%. It seems that all the great fitness comes from late 2015 to 2016. There is only one feasible opportunity on late October of 2015 where the surging momentum could be captured. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20before%202017.png) For the post-2017 dataset, things are quite the opposite. The out-of-sample data indicates a higher R squared than in-sample data, about 40%. The whole year of 2018 seems to be a perfect fit where no momentum trading signal emerges. Here comes the greatest dilemma of our strategy. If two assets are perfectly matched, we will lose the chance to make money. Alternatively, if two assets are terribly mismatched or completely detached, we won’t be able to do oil money trading at all. It’s all about the delicate balance of semi-efficient market. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20after%202017.png) Although we cannot trade Colombian Peso as frequently as Norwegian Krone, the profit of LATAM oil money is as marvelous as Nordic oil money. Judging by the figure below, roughly 70% of the signals generate positive incomes. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20trading%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20trading%20asset.png) Similar to the previous trading tactics, we aim to maximize our profit by searching for the optimal holding period and stop loss/profit. The profit distribution of different parameters is positively skewed. It’s what every investor loves, a positive fat tail. The mean return is respectively 7% (the Colombian interest rate is 4.498% in 2019). ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20profit%20distribution.png) The heatmap tells a consistent story. The return is independent of stop profit/loss point. The length of holding period determines how well we have been riding the waves. The warmer color the tile is, the more profit we will churn out. By setting stop profit/loss point from 0.002 to 0.0045 and holding period at 17 days, we shall be able to achieve our maximum return, 9%! Coincidentally, the excess return α, which interest rate is deducted, for both Norway and Colombia is 4%. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/cop%20profit%20heatmap.png) ### Discussion In this project, the petrocurrency trading does produce lucrative cash in our account but not the way most market analysts proclaim. Many papers which you will find in further reading session have declared that using oil price to forecast petrocurrency is urban legend. We started off with this awfully wrong direction led by market analysts who are only good at being report :monkey: but suck at conducting quantitative analytics. Fortunately, we ended up on the right foot, discovering a great momentum trading strategy. The greatness of this strategy is its market neutrality. It is reasonably immune to market turmoil or bull run. Moreover, the foundation of this strategy comes from the fundamentals of oil market. Unlike the treasure hunt of tiny anomaly of trading signals, neither the phenomenon will vanish into thin air nor the opportunity will cease to exist when the rest of your competitors catches on to it. As planned, we have examined three petrocurrencies of free floating FX regime, Norwegian Krone, Russian Ruble, and Colombian Peso. We use solid evidence to debunk the petrocurrency myth of Canadian Dollar. We also strongly advise people to be cautious when dealing with assets from autocratic regimes like Russia. In that sense, we are only left with two options, Norway and Colombia, both alphas are approximately 4%. Well, after such a long time of hard work, perhaps now we deserve an Emirati feast generated by oil wealth. ### Further Reading 1. Beckmann J, Czudaj R, Arora V (2017) The Relationship Between Oil Prices And Exchange Rates: Theory And Evidence *This paper was documented by US EIA. It summarized the literatures on short-term and long-term bidirectional forecast, direct and indirect transmission channels, nonlinear relationship, time-variation and related policy implications.* 2. Bernhardsen T, Røisland Ø (2000) Factors That Influence The Krone Exchange Rate *This paper was published by two senior economists of Norges Bank. Who knows Norwegian Krone more than insiders?* 3. Ferraro D, Rogoff K, Rossi B (2011) Can Oil Prices Forecast Exchange Rates? *This paper was featured by Bank of Canada. Click here for its workshop presentation. Oil Money project uses a similar approach from the paper, yet the results are completely the opposite.* 4. Fratzscher M, Schneider D, Robays IV (2014) Oil Prices, Exchange Rates And Asset Prices *This paper analyzed the causality between oil and asset prices – exploiting the heteroskedasticity of the underlying time-series data. The economists in ECB didn't only verify the causality between oil price and exchange rate, but also the causality among oil price, equity market shocks and risk shocks.* 5. Ghalayini L (2011) The Interaction Between Oil Price And Economic Growth *This paper illustrated the mechanism of how oil shock affects different types of economy. That is why dollar effect matters to our oil money trading.* 6. Karlsen JLS, Mjøen MB (2015) Forecasting The Norwegian Krone Exchange Rate Using The Oil Price *This paper took two different approaches to construct a true forecasting model. Nonetheless, the random walk seemed to outperform any of these sophisticated models in a high frequency dataset.* ================================================ FILE: Oil Money project/data/brent crude nokjpy.csv ================================================ date,nok,usd,eur,gbp,brent,gdp yoy,interest rate 4/25/2013,16.90188456,99.25500188,129.1655903,153.1862745,10263.95955,, 4/26/2013,16.76066607,98.05000119,127.7465508,151.7680983,10114.838,, 4/29/2013,16.81831178,97.76500402,128.0737705,151.5381118,10148.98465,, 4/30/2013,16.88276607,97.42499883,128.2873637,151.3317191,9973.39725,,1.5 5/1/2013,16.8830511,97.38999678,128.3532281,151.4921982,9734.1305,,1.5 5/2/2013,16.88404879,97.96500239,127.9918085,152.1838381,10075.70025,,1.5 5/3/2013,17.06324492,99.03500293,129.8869983,154.2138947,10318.45665,,1.5 5/6/2013,17.02417433,99.34499856,129.9038711,154.4043851,10476.9237,,1.5 5/7/2013,16.94168671,99.01499879,129.5001295,153.3272002,10337.166,,1.5 5/8/2013,17.22059583,99.00499975,130.2083333,153.7988311,10330.1817,,1.5 5/9/2013,17.40068559,100.6049982,131.2163758,155.4243084,10510.20435,,1.5 5/10/2013,17.54262859,101.6149976,132.0306311,156.128025,10558.81465,,1.5 5/13/2013,17.54986355,101.8249993,132.1353066,155.7875058,10469.6465,,1.5 5/14/2013,17.54247472,102.365,132.2576379,155.702608,10502.649,,1.5 5/15/2013,17.48389296,102.2350002,131.7523057,155.7632399,10599.7248,,1.5 5/16/2013,17.52510471,102.2549988,131.7175975,156.1524047,10614.069,,1.5 5/17/2013,17.63155343,103.209996,132.5029813,156.5802865,10799.8944,,1.5 5/20/2013,17.52756209,102.269995,131.7523057,156.0062402,10717.896,,1.5 5/21/2013,17.70115146,102.4950052,132.2926313,155.3398058,10650.25545,,1.5 5/22/2013,17.73946054,103.1549955,132.6435867,155.2312946,10583.703,,1.5 5/23/2013,17.50148763,102.0250025,131.9783555,154.1425819,10451.441,,1.5 5/24/2013,17.36653815,101.289999,130.9757695,153.2097441,10396.4056,,1.5 5/27/2013,17.26787657,100.9449966,130.5312622,152.4622656,10358.9759,,1.5 5/28/2013,17.35900151,102.3749976,131.6135825,153.9882969,10670.54625,,1.5 5/29/2013,17.14824659,101.1549979,130.9071868,153.0924679,10361.30665,,1.5 5/30/2013,17.29161443,100.7350029,131.4578678,153.4448366,10294.10965,,1.5 5/31/2013,17.12050266,100.4850009,130.6165099,152.7300496,10087.68915,,1.5 6/3/2013,17.14795253,99.52999944,130.1405518,152.5087693,10158.0318,,1.5 6/4/2013,17.21155584,100.0249962,130.8386759,153.1745424,10326.581,,1.5 6/5/2013,17.05000767,99.06500467,129.7185108,152.6135063,10207.6576,,1.5 6/6/2013,16.87322304,96.96000332,128.4356537,151.2859304,10046.0256,,1.5 6/7/2013,16.91003018,97.54499726,128.9823294,151.7680983,10199.3052,,1.5 6/10/2013,17.1445716,98.76999747,130.9414692,153.7988311,10267.1415,,1.5 6/11/2013,16.6239984,96.02499723,127.8608874,150.2855425,9886.734,,1.5 6/12/2013,16.67959335,96.03000438,128.0737705,150.5570611,9938.1447,,1.5 6/13/2013,16.61253748,95.37499924,127.5672917,149.9250375,9942.84375,,1.5 6/14/2013,16.45792531,94.08499846,125.5808113,147.7541371,9966.42405,,1.5 6/17/2013,16.51145895,94.50999921,126.3423879,148.5773717,9967.9697,,1.5 6/18/2013,16.61847309,95.33000244,127.6813075,149.1313101,10106.8866,,1.5 6/19/2013,16.71136958,96.47499658,128.2544568,149.3986704,10237.927,,1.5 6/20/2013,16.21810102,97.28499942,128.6173633,150.8864579,9937.66275,,1.5 6/21/2013,16.15782968,97.89999613,128.4686536,150.9433962,9879.089,,1.5 6/24/2013,15.93117731,97.72999606,128.2051282,150.8295626,9886.3668,,1.5 6/25/2013,16.05858171,97.81000465,127.9918085,150.8295626,9904.2406,,1.5 6/26/2013,16.000128,97.74500323,127.1779219,149.6893945,9936.7567,,1.5 6/27/2013,16.27100994,98.35500274,128.2380097,150.0712839,10112.8611,,1.5 6/28/2013,16.33466461,99.13499758,128.9823294,150.8068165,10127.6316,0.29,1.5 7/1/2013,16.3591153,99.66499605,130.2083333,151.6645181,10265.495,,1.5 7/2/2013,16.45765446,100.6300042,130.5994515,152.4971407,10465.52,,1.5 7/3/2013,16.34788295,99.91500231,129.9714063,152.6601023,10567.0104,,1.5 7/4/2013,16.37693145,100.0450002,129.1989664,150.7840772,10558.7493,,1.5 7/5/2013,16.1922342,101.1999992,129.8532658,150.6704837,10901.264,,1.5 7/8/2013,16.44168955,100.9650033,129.9376299,150.954789,10846.66995,,1.5 7/9/2013,16.36808551,101.1549979,129.2824822,150.3872472,10905.52055,,1.5 7/10/2013,16.37451798,99.66499605,129.3326436,149.6110114,10814.64915,,1.5 7/11/2013,16.32866334,98.95999968,129.6008294,150.2629602,10660.9608,,1.5 7/12/2013,16.35109062,99.22500311,129.6680498,149.9025633,10796.67225,,1.5 7/15/2013,16.47527884,99.86500249,130.4461258,150.795446,10894.27285,,1.5 7/16/2013,16.54560797,99.09499514,130.4291118,150.2403846,10840.993,,1.5 7/17/2013,16.63506005,99.58499943,130.701869,151.503674,10815.92685,,1.5 7/18/2013,16.78133915,100.4199966,131.6482359,152.9285824,10915.654,,1.5 7/19/2013,16.85843132,100.6499977,132.2751323,153.6688436,10877.2455,,1.5 7/22/2013,16.796419,99.66499605,131.4060447,153.0924679,10778.76975,,1.5 7/23/2013,16.92448296,99.42999765,131.4751512,152.8117359,10780.2006,,1.5 7/24/2013,16.91474966,100.2549986,132.3451562,153.5390757,10746.33345,,1.5 7/25/2013,16.81788751,99.2949956,131.8391562,152.8234125,10689.10675,,1.5 7/26/2013,16.638243,98.2749986,130.4971943,151.1601542,10532.13175,,1.5 7/29/2013,16.49566164,97.95500319,129.9207483,150.2516715,10525.26475,,1.5 7/30/2013,16.51241321,98.03499634,130.0221038,149.3763537,10480.92185,,1.5 7/31/2013,16.61129568,97.87499679,130.1913813,148.8538255,10541.1375,,1.5 8/1/2013,16.73528132,99.54499972,131.4751512,150.5117399,10904.1593,,1.5 8/2/2013,16.66069658,98.96500419,131.4578678,151.3088213,10782.23675,,1.5 8/5/2013,16.59599539,98.31000191,130.3441084,150.9889778,10686.297,,1.5 8/6/2013,16.51391297,97.74500323,130.0728408,150.0150015,10574.0541,,1.5 8/7/2013,16.32972991,96.33500227,128.48516,149.2091913,10350.2324,,1.5 8/8/2013,16.36005202,96.73500027,129.4498382,150.2742505,10319.6898,,1.5 8/9/2013,16.44277094,96.2199974,128.3861856,149.142431,10412.9284,,1.5 8/12/2013,16.50628064,96.90499967,128.882588,149.8464074,10559.73785,,1.5 8/13/2013,16.68084539,98.2049992,130.2422506,151.7220452,10784.8731,,1.5 8/14/2013,16.65348266,98.13500315,130.0897619,152.11439,10814.477,,1.5 8/15/2013,16.48016612,97.36999742,129.9714063,152.2997259,10818.7807,,1.5 8/16/2013,16.48329006,97.53000389,130.0052002,152.4390244,10767.312,,1.5 8/19/2013,16.48464867,97.56500195,130.1066875,152.6717557,10722.3935,,1.5 8/20/2013,16.33679946,97.28000249,130.5142261,152.4041759,10715.392,,1.5 8/21/2013,16.06103192,97.67500284,130.4631442,152.975371,10725.69175,,1.5 8/22/2013,16.16984808,98.72999656,131.8565401,153.8935057,10850.427,,1.5 8/23/2013,16.40527594,98.74500042,132.1353066,153.7279016,10964.6448,,1.5 8/26/2013,16.31481059,98.50999689,131.7002502,153.4330648,10908.0123,,1.5 8/27/2013,16.12344106,97.02999906,129.9545159,150.8409382,11096.3508,,1.5 8/28/2013,16.14205004,97.64000209,130.2592158,151.6070346,11385.8004,,1.5 8/29/2013,16.14113811,98.35000169,130.2252898,152.4855139,11325.986,,1.5 8/30/2013,16.05626114,98.16500162,129.8026999,152.2417599,11191.79165,,1.5 9/2/2013,16.33133002,99.33500183,131.0444241,154.4163064,11356.97055,,1.5 9/3/2013,16.40339222,99.58000143,131.147541,154.9426712,11519.4144,,1.5 9/4/2013,16.46334436,99.7599974,131.7696666,155.8967963,11463.4216,,1.5 9/5/2013,16.34962028,100.124996,131.3715187,156.0914696,11540.4075,,1.5 9/6/2013,16.29779328,99.11500215,130.6335728,154.9306685,11509.2338,,1.5 9/9/2013,16.5682238,99.58499943,131.9957761,156.262208,11324.8062,,1.5 9/10/2013,16.96295291,100.4100042,133.2267519,157.9903626,11170.6125,,1.5 9/11/2013,16.89560207,99.87499645,132.9433661,157.9778831,11136.0625,,1.5 9/12/2013,16.92061693,99.55000412,132.3977228,157.3440327,11212.3165,,1.5 9/13/2013,16.75462847,99.36499804,132.1003963,157.7411468,11206.3847,,1.5 9/16/2013,16.75827859,99.08000254,132.1178491,157.492716,10905.7356,,1.5 9/17/2013,16.77838273,99.1200027,132.4152542,157.6416805,10723.7928,,1.5 9/18/2013,16.82864235,97.93999863,132.4327904,158.1402704,10832.164,,1.5 9/19/2013,17.05887872,99.45000171,134.5532831,159.4260662,10816.182,,1.5 9/20/2013,16.7347212,99.31500455,134.3183345,158.9698752,10847.1843,,1.5 9/23/2013,16.70104298,98.84499622,133.3688984,158.579131,10691.0752,,1.5 9/24/2013,16.52278078,98.73499734,133.0317946,158.0153275,10726.5704,,1.5 9/25/2013,16.38820377,98.44000161,133.1557923,158.290463,10663.0208,,1.5 9/26/2013,16.54834599,98.98999518,133.5291761,158.7931719,10810.6979,,1.5 9/27/2013,16.4067563,98.26000206,132.8727079,158.579131,10673.9838,,1.5 9/30/2013,16.33426439,98.23000339,132.8727079,158.9951506,10645.1851,2.77,1.5 10/1/2013,16.33906835,97.99500265,132.5556734,158.7049675,10577.5803,,1.5 10/2/2013,16.19656147,97.35500092,132.1877065,157.9404564,10630.19245,,1.5 10/3/2013,16.33439779,97.26499586,132.4503311,157.1338781,10601.885,,1.5 10/4/2013,16.32493144,97.47499791,132.1527686,156.0427557,10669.6135,,1.5 10/7/2013,16.20325361,96.71000306,131.3542624,155.6662516,10607.1528,,1.5 10/8/2013,16.22073172,96.87999901,131.4924392,155.823919,10672.3008,,1.5 10/9/2013,16.24114857,97.34500266,131.6482359,155.3277415,10616.4457,,1.5 10/10/2013,16.25236675,98.15500009,132.7140013,156.7152484,10973.729,,1.5 10/11/2013,16.42912885,98.5749998,133.4935256,157.2821642,10969.426,,1.5 10/14/2013,16.49797487,98.5749998,133.6898396,157.567163,10945.768,,1.5 10/15/2013,16.30177852,98.16500162,132.7492367,157.0351759,10794.2234,,1.5 10/16/2013,16.48057352,98.7650029,133.671969,157.5423395,10949.0879,,1.5 10/17/2013,16.50682557,97.91000328,133.9046599,158.2654111,10682.9601,,1.5 10/18/2013,16.56945917,97.73500112,133.74348,158.0153275,10744.9859,,1.5 10/21/2013,16.58333541,98.19000473,134.354427,158.5539876,10765.5516,,1.5 10/22/2013,16.63339987,98.14000162,135.2447931,159.3371574,10792.4558,,1.5 10/23/2013,16.45075057,97.38000082,134.1561578,157.4059499,10497.564,,1.5 10/24/2013,16.50777929,97.28000249,134.2462075,157.6044129,10407.9872,,1.5 10/25/2013,16.52919883,97.41999699,134.4809037,157.492716,10417.1206,,1.5 10/28/2013,16.55588023,97.68000227,134.643867,157.6789656,10706.7048,,1.5 10/29/2013,16.6482149,98.18500116,134.9527665,157.5547503,10703.14685,,1.5 10/30/2013,16.70536743,98.50999689,135.3179973,157.9903626,10822.3086,,1.5 10/31/2013,16.55231774,98.35500274,133.6183859,157.790927,10704.9582,,1.5 11/1/2013,16.52059705,98.68999882,133.1026221,157.1832757,10452.2579,,1.5 11/4/2013,16.57399044,98.60499568,133.2622601,157.4555188,10474.80915,,1.5 11/5/2013,16.44520458,98.50499947,132.7316167,158.065281,10375.53165,,1.5 11/6/2013,16.56904736,98.65999988,133.3155579,158.6671956,10382.9784,,1.5 11/7/2013,16.22533749,98.0900013,131.6309069,157.9030475,10148.3914,,1.5 11/8/2013,16.14739341,99.07499621,132.4854266,158.6923748,10414.764,,1.5 11/11/2013,16.13410669,99.15500108,132.9256945,158.5539876,10550.092,,1.5 11/12/2013,16.08971626,99.63499715,133.8688086,158.4660486,10542.37935,,1.5 11/13/2013,16.0939889,99.24500356,133.8508901,159.375249,10631.1244,,1.5 11/14/2013,16.25012188,100.020004,134.6257404,160.6812887,10856.1708,,1.5 11/15/2013,16.4036613,100.1850016,135.2082207,161.51175,10870.0725,,1.5 11/18/2013,16.3281301,100,135.0438893,161.108426,10847,,1.5 11/19/2013,16.44547503,100.1500047,135.5932203,161.4465612,10708.038,,1.5 11/20/2013,16.35376464,100.029999,134.4266703,161.108426,10809.2418,,1.5 11/21/2013,16.60591669,101.1549979,136.369835,163.8806949,11135.1424,,1.5 11/22/2013,16.69853303,101.2750016,137.3060552,164.3250349,11246.58875,,1.5 11/25/2013,16.65570166,101.6799976,137.4381528,164.2710472,11286.48,,1.5 11/26/2013,16.62261673,101.3000032,137.4759417,164.2710472,11232.144,,1.5 11/27/2013,16.72926199,102.1649989,138.7347392,166.4031949,11371.98615,,1.5 11/28/2013,16.80516927,102.3200038,139.2175971,167.2100995,11343.1952,,1.5 11/29/2013,16.71416275,102.4450037,139.2369813,167.6727029,11237.19205,,1.5 12/2/2013,16.8231217,102.9550042,139.4116827,168.3926918,11474.33475,,1.5 12/3/2013,16.81180861,102.5150005,139.3145723,168.038985,11545.2393,,1.5 12/4/2013,16.63035705,102.3550044,139.1401141,167.7148847,11451.4774,,1.5 12/5/2013,16.53726259,101.7850036,139.1207568,166.2786831,11296.0993,,1.5 12/6/2013,16.73080141,102.9099963,141.0437236,168.2510305,11485.7851,,1.5 12/9/2013,16.82156525,103.2750053,141.8842225,169.6928559,11297.25225,,1.5 12/10/2013,16.82736803,102.8399985,141.5227852,169.1331924,11248.6392,,1.5 12/11/2013,16.7000668,102.4399978,141.2229911,167.7430177,11237.668,,1.5 12/12/2013,16.68641225,103.3799987,142.2070535,169.0331305,11234.3046,,1.5 12/13/2013,16.70257721,103.2199995,141.8640942,168.2368775,11233.4326,,1.5 12/16/2013,16.75476883,103.0249994,141.7635384,167.8838244,11381.17175,,1.5 12/17/2013,16.79811189,102.6699948,141.3627368,166.9867246,11133.5348,,1.5 12/18/2013,16.98182096,104.2799951,142.7144284,170.9255619,11432.2164,,1.5 12/19/2013,16.94685466,104.2450024,142.4298533,170.6921567,11497.18105,,1.5 12/20/2013,16.88775553,104.0750048,142.2879909,170.0102006,11632.46275,,1.5 12/23/2013,16.91474966,104.1100026,142.5923285,170.2852278,11614.5116,,1.5 12/24/2013,16.9436961,104.3650037,142.8163382,170.8963514,11678.4435,,1.5 12/26/2013,17.06499202,104.8049946,143.4926101,171.998624,11736.0639,,1.5 12/27/2013,17.1102499,105.1699994,144.5295563,173.3252448,11797.9706,,1.5 12/30/2013,17.32801941,105.1550032,145.158949,173.5207357,11694.28755,,1.5 12/31/2013,17.35493444,105.314995,144.7596989,174.3831197,11668.902,1.75,1.5 1/2/2014,16.98860065,104.7649948,143.2254368,172.3840717,11291.5717,,1.5 1/3/2014,17.0526244,104.854996,142.4907381,172.131853,11207.95095,,1.5 1/6/2014,16.89132124,104.2200034,142.0252805,170.9693965,11123.4006,,1.5 1/7/2014,16.95432505,104.6199982,142.4501425,171.6148962,11230.957,,1.5 1/8/2014,16.90531334,104.854996,142.3487544,172.4583944,11235.21325,,1.5 1/9/2014,16.97202162,104.8300003,142.6533524,172.7712509,11152.8637,,1.5 1/10/2014,16.95130737,104.1500027,142.3690205,171.6738197,11170.0875,,1.5 1/13/2014,16.83841854,102.9999986,140.8252359,168.7336539,10995.25,,1.5 1/14/2014,17.13018081,104.2149964,142.551675,171.3355607,11087.43385,,1.5 1/15/2014,17.03693608,104.5550014,142.2475107,171.1742554,11200.97715,,1.5 1/16/2014,16.88704257,104.3600044,142.1464108,170.6630259,11175.9124,,1.5 1/17/2014,16.94800353,104.3150004,141.2628902,171.3355607,11107.4612,,1.5 1/20/2014,16.8685267,104.1800039,141.1831145,171.1742554,11079.543,,1.5 1/21/2014,16.90902942,104.3199953,141.4827391,171.8656011,11134.0736,,1.5 1/22/2014,16.95346274,104.5149956,141.5828968,173.2351667,11315.83905,,1.5 1/23/2014,16.95791892,103.2650018,141.4227125,171.8065458,11109.2487,,1.5 1/24/2014,16.65126425,102.2949985,139.9188471,168.6198466,11035.5846,,1.5 1/27/2014,16.67945425,102.549998,140.2131239,170.0680272,10941.0595,,1.5 1/28/2014,16.80841766,102.9650008,140.7459536,170.7067258,11059.47065,,1.5 1/29/2014,16.59131445,102.3000007,139.7819402,169.4340901,11033.055,,1.5 1/30/2014,16.43236848,102.7249962,139.256371,169.3480102,11089.16375,,1.5 1/31/2014,16.24708568,102.0349962,137.6083666,167.7008217,10856.524,,1.5 2/3/2014,16.06516029,100.990005,136.5933616,164.6632636,10708.9796,,1.5 2/4/2014,16.17782667,101.6500032,137.4192662,165.9475606,10752.537,,1.5 2/5/2014,16.27895619,101.4400017,137.2872048,165.4533422,10778,,1.5 2/6/2014,16.42683488,102.1049966,138.7539892,166.6388935,10944.63495,,1.5 2/7/2014,16.57055743,102.3400042,139.5478649,167.9684219,11213.3938,,1.5 2/10/2014,16.68432424,102.2549988,139.5478649,167.7148847,11107.96065,,1.5 2/11/2014,16.75238303,102.6349997,139.9776036,168.8333615,11154.3718,,1.5 2/12/2014,16.7661458,102.5350037,139.3922498,170.1693185,11154.78265,,1.5 2/13/2014,16.73500126,102.1699988,139.7819402,170.212766,11108.9441,,1.5 2/14/2014,16.749016,101.799997,139.3922498,170.4884494,11104.344,,1.5 2/17/2014,16.76291373,101.9350016,139.7233478,170.3432416,11129.2633,,1.5 2/18/2014,16.95030172,102.3699985,140.8450704,170.8087796,11307.7902,,1.5 2/19/2014,16.83728448,102.3249979,140.5283867,170.6921567,11303.84275,,1.5 2/20/2014,16.77627164,102.2649958,140.291807,170.2852278,11279.8295,,1.5 2/21/2014,16.86881125,102.5249959,140.8649106,170.3577513,11262.37125,,1.5 2/24/2014,16.99004383,102.4950052,140.7855836,170.7650273,11340.0468,,1.5 2/25/2014,16.93193363,102.2350002,140.5283867,170.53206,11195.75485,,1.5 2/26/2014,16.90759997,102.3749976,140.1345291,170.6921567,11212.11,,1.5 2/27/2014,16.91503578,102.1300029,140.016802,170.4448611,11128.0848,,1.5 2/28/2014,16.9573438,101.8050027,140.5086413,170.4739175,11103.87135,,1.5 3/3/2014,16.77669382,101.4500046,139.3339836,169.0902942,11281.24,,1.5 3/4/2014,17.00492293,102.2100052,140.469167,170.3287345,11171.553,,1.5 3/5/2014,17.06732205,102.3149996,140.5086413,171.1010352,11025.4644,,1.5 3/6/2014,17.23588166,103.0700018,142.8571429,172.5327812,11141.867,,1.5 3/7/2014,17.24836787,103.2799971,143.328078,172.6370306,11257.52,,1.5 3/10/2014,17.34109058,103.2650018,143.307538,171.895144,11160.8812,,1.5 3/11/2014,17.28638352,103.0200004,142.7755568,171.188907,11182.821,,1.5 3/12/2014,17.26757839,102.764995,142.8775539,170.7796089,11100.6753,,1.5 3/13/2014,17.05436933,101.8400045,141.2429379,169.3193363,10936.5976,,1.5 3/14/2014,16.96885367,101.3550049,141.023833,168.7194196,11004.11235,,1.5 3/17/2014,17.0995708,101.7700043,141.6831964,169.305003,10812.0448,,1.5 3/18/2014,17.03533981,101.4450029,141.3627368,168.3076664,10833.31155,,1.5 3/19/2014,16.95691249,102.3450003,141.5828968,169.305003,10833.21825,,1.5 3/20/2014,16.88105608,102.4,141.1034288,169.0045631,10900.48,,1.5 3/21/2014,16.90131323,102.2649958,141.0636197,168.6056314,10934.1738,,1.5 3/24/2014,16.99423046,102.2450038,141.5027593,168.676731,10920.78845,,1.5 3/25/2014,16.96525516,102.2649958,141.4027149,169.0045631,10941.33235,,1.5 3/26/2014,16.86084743,102.0450023,140.6469761,169.247694,10921.87635,,1.5 3/27/2014,17.02808783,102.1749992,140.390285,169.7360604,11017.53025,,1.5 3/28/2014,17.11815809,102.8150028,141.4027149,171.0863986,11111.21705,,1.5 3/31/2014,17.23499048,103.2150028,142.1464108,171.998624,11122.4484,2.04,1.5 4/1/2014,17.32231634,103.6449976,142.9592566,172.3692149,10946.9849,,1.5 4/2/2014,17.39659896,103.8750051,143.000143,172.7115717,10885.06125,,1.5 4/3/2014,17.31541765,103.9249977,142.5923285,172.5030188,11031.63875,,1.5 4/4/2014,17.21259273,103.2850001,141.5227852,171.2328767,11022.5752,,1.5 4/7/2014,17.20770561,103.1049967,141.6831964,171.2475383,10910.5711,,1.5 4/8/2014,17.03838749,101.8149948,140.469167,170.5175207,10962.42105,,1.5 4/9/2014,17.17962153,101.9849952,141.3028119,171.2768691,11012.3403,,1.5 4/10/2014,17.12548701,101.5249968,141.0039481,170.4303366,10909.8765,,1.5 4/11/2014,17.12563365,101.6149976,141.0835214,170.039109,10906.33795,,1.5 4/14/2014,17.0746075,101.8450037,140.7459536,170.386778,11108.23415,,1.5 4/15/2014,17.11903723,101.9300039,140.8054069,170.53206,11083.8682,,1.5 4/16/2014,17.11962337,102.2350002,141.2429379,171.7475311,11204.956,,1.5 4/17/2014,17.10659117,102.3899976,141.4427157,171.9394773,11214.7767,,1.5 4/21/2014,17.10761546,102.6200015,141.5428167,172.3246597,11283.069,,1.5 4/22/2014,17.13047426,102.6200015,141.6631251,172.6370306,11213.2874,,1.5 4/23/2014,17.10337279,102.5399978,141.6831964,172.0874204,11188.1394,,1.5 4/24/2014,17.052479,102.3200038,141.5428167,171.9394773,11288.9656,,1.5 4/25/2014,16.97202162,102.1699988,141.3227812,171.7032967,11195.7886,,1.5 4/28/2014,17.0718383,102.4999954,141.9647927,172.2801275,11082.3,,1.5 4/29/2014,17.0773776,102.6349997,141.7635384,172.7115717,11185.1623,,1.5 4/30/2014,17.188628,102.2599971,141.8037436,172.5476663,11051.2382,,1.5 5/1/2014,17.22237531,102.3400042,141.9446416,172.8907331,11028.1584,,1.5 5/2/2014,17.21140772,102.1850014,141.7434444,172.3543606,11096.26915,,1.5 5/5/2014,17.14192658,102.1399963,141.723356,172.2801275,11002.5208,,1.5 5/6/2014,17.17018226,101.6850018,141.6229996,172.6072322,10886.3961,,1.5 5/7/2014,17.24881414,101.9150033,141.7836382,172.7861771,11020.06895,,1.5 5/8/2014,17.23202054,101.6599959,140.7063459,172.146669,10983.3464,,1.5 5/9/2014,17.22445183,101.8649953,140.1541696,171.6590851,10990.21485,,1.5 5/12/2014,17.25164106,102.1249965,140.4889014,172.2801275,11071.37125,,1.5 5/13/2014,17.26519337,102.2599971,140.1345291,172.0578114,11170.8824,,1.5 5/14/2014,17.1972003,101.8899983,139.7428731,170.8379602,11227.2591,,1.5 5/15/2014,17.06906999,101.5750017,139.275766,170.5466019,11217.943,,1.5 5/16/2014,17.10615223,101.519998,139.0240512,170.7212975,11141.82,,1.5 5/19/2014,17.11332443,101.5100019,139.1594768,170.6630259,11102.1487,,1.5 5/20/2014,17.02113174,101.3249966,138.8503194,170.604794,11114.33925,,1.5 5/21/2014,17.05189745,101.3749998,138.7539892,171.3355607,11207.00625,,1.5 5/22/2014,17.099717,101.7349988,138.9274799,171.6296233,11227.4746,,1.5 5/23/2014,17.10732279,101.9699992,139.0240512,171.6738197,11271.7638,,1.5 5/26/2014,17.11420308,101.9549973,139.1207568,171.718039,11247.6756,,1.5 5/27/2014,17.13062099,101.9899982,139.0627173,171.4530647,11220.9398,,1.5 5/28/2014,17.04375985,101.8450037,138.4083045,170.198281,11183.59945,,1.5 5/29/2014,17.06455521,101.7950022,138.4657989,170.1693185,11194.39615,,1.5 5/30/2014,17.04259797,101.7850036,138.7347392,170.5029838,11136.29685,,1.5 6/2/2014,17.07694015,102.3849971,139.1982183,171.4530647,11142.55955,,1.5 6/3/2014,17.07548217,102.5049966,139.6843135,171.688557,11154.5941,,1.5 6/4/2014,17.10805447,102.744997,139.7233478,171.9542602,11137.558,,1.5 6/5/2014,17.11347087,102.3949985,139.8797035,172.2356183,11139.55205,,1.5 6/6/2014,17.23736716,102.4850052,139.8210291,172.2059583,11130.89585,,1.5 6/9/2014,17.1688557,102.5299995,139.3728223,172.2801275,11277.2747,,1.5 6/10/2014,17.12578029,102.3550044,138.6770212,171.5118772,11209.9196,,1.5 6/11/2014,17.00882758,102.0800025,138.1406272,171.3649216,11223.696,,1.5 6/12/2014,16.97764045,101.7250017,137.8739832,172.2059583,11496.9595,,1.5 6/13/2014,17.0253337,102.07,138.2361073,173.1601732,11575.7587,,1.5 6/16/2014,17.00145362,101.8450037,138.2552191,172.9654934,11502.3743,,1.5 6/17/2014,17.01360238,102.1450042,138.3700014,173.2952084,11588.35025,,1.5 6/18/2014,16.96194587,101.9249962,138.5809313,173.2051615,11645.9505,,1.5 6/19/2014,16.6573663,101.9350016,138.7154945,173.7015807,11728.6411,,1.5 6/20/2014,16.68446343,102.075001,138.8117712,173.6563341,11719.23075,,1.5 6/23/2014,16.68961489,101.9499976,138.7154945,173.596042,11634.534,,1.5 6/24/2014,16.68154104,101.9750008,138.7347392,173.2051615,11672.0585,,1.5 6/25/2014,16.61557378,101.8749992,138.8503194,173.0103806,11613.75,,1.5 6/26/2014,16.58649859,101.7349988,138.4849744,173.2201628,11517.41935,,1.5 6/27/2014,16.53835658,101.3749998,138.3700014,172.6966583,11485.7875,,1.5 6/30/2014,16.51745895,101.3249966,138.7347392,173.3252448,11384.877,2.06,1.5 7/1/2014,16.46876698,101.5249968,138.8888889,174.1250218,11400.24225,,1.5 7/2/2014,16.4845128,101.7899975,139.0433815,174.7335314,11323.1196,,1.5 7/3/2014,16.51350392,102.1900033,139.0820584,175.3002016,11343.09,,1.5 7/4/2014,16.496478,102.120001,138.8310426,175.2387628,11298.5568,,1.5 7/7/2014,16.54300768,101.8450037,138.5617293,174.4287459,11227.3928,,1.5 7/8/2014,16.411199,101.5799956,138.2743363,174.0341107,11066.1252,,1.5 7/9/2014,16.51650412,101.6350023,138.6770212,174.3831197,11005.0378,,1.5 7/10/2014,16.43020858,101.3349974,137.9120121,173.6111111,11012.07445,,1.5 7/11/2014,16.41039106,101.3800049,137.9690949,173.6111111,10813.1908,,1.5 7/14/2014,16.41712635,101.544997,138.3125864,173.4755833,10863.2841,,1.5 7/15/2014,16.37773611,101.6850018,138.0071764,174.3071292,10780.6437,,1.5 7/16/2014,16.40742928,101.6799976,137.532664,174.2463844,10762.828,,1.5 7/17/2014,16.2980589,101.1749958,136.8550705,173.0103806,10915.77075,,1.5 7/18/2014,16.37103309,101.3349974,137.0426203,173.1751667,10867.1654,,1.5 7/21/2014,16.35777731,101.3999994,137.136588,173.1451822,10918.752,,1.5 7/22/2014,16.39035264,101.4650024,136.6306873,173.1451822,10890.23845,,1.5 7/23/2014,16.37693145,101.4849996,136.6493577,172.9654934,10963.42455,,1.5 7/24/2014,16.42211402,101.8149948,137.0801919,172.9505361,10901.33205,,1.5 7/25/2014,16.36246124,101.8400045,136.7801942,172.860847,11038.4376,,1.5 7/28/2014,16.35831248,101.8600044,136.9112815,172.9954156,10957.0802,,1.5 7/29/2014,16.33893486,102.1300029,136.9487812,173.0552912,11001.4436,,1.5 7/30/2014,16.42885893,102.7949959,137.7220768,173.8676867,10948.69545,,1.5 7/31/2014,16.35523572,102.7949959,137.6273053,173.5809755,10898.3259,,1.5 8/1/2014,16.38015053,102.6299963,137.8359752,172.6370306,10759.7292,,1.5 8/4/2014,16.38176055,102.5949968,137.7031121,173.0103806,10814.53895,,1.5 8/5/2014,16.33413098,102.5949968,137.2306848,173.2501733,10732.46295,,1.5 8/6/2014,16.29712926,102.1100011,136.6493577,172.1022287,10679.6849,,1.5 8/7/2014,16.34347446,102.1049966,136.4442625,171.8508335,10765.9512,,1.5 8/8/2014,16.36567463,102.0599994,136.8738024,171.188907,10718.3412,,1.5 8/11/2014,16.52687683,102.1949952,136.7989056,171.556013,10697.7726,,1.5 8/12/2014,16.54738758,102.2599971,136.7240908,171.9394773,10534.8252,,1.5 8/13/2014,16.62690066,102.4299981,136.8925394,170.9401709,10681.4004,,1.5 8/14/2014,16.63035705,102.4450037,136.9112815,170.9547825,10450.41445,,1.5 8/15/2014,16.68752607,102.360002,137.1553971,170.9109554,10597.3308,,1.5 8/18/2014,16.66083537,102.5700043,137.0614035,171.5854496,10421.112,,1.5 8/19/2014,16.6935154,102.9049978,137.0614035,170.998632,10451.0318,,1.5 8/20/2014,16.74929653,103.7549971,137.5894331,172.1763085,10612.0614,,1.5 8/21/2014,16.89089327,103.8350004,137.9120121,172.1614875,10656.58605,,1.5 8/22/2014,16.84919966,103.9450039,137.6651982,172.2356183,10632.53405,,1.5 8/25/2014,16.85019336,104.0550026,137.2683596,172.5030188,10681.24575,,1.5 8/26/2014,16.84111252,104.0700008,137.0426203,172.131853,10667.175,,1.5 8/27/2014,16.80008736,103.8650037,137.0238421,172.1614875,10669.0128,,1.5 8/28/2014,16.78457833,103.7149987,136.7240908,172.0282126,10626.6389,,1.5 8/29/2014,16.79853517,104.0750048,136.6680333,172.7414061,10739.49925,,1.5 9/1/2014,16.85573179,104.3650037,137.0050692,173.3102253,10727.67835,,1.5 9/2/2014,16.98182096,105.0749962,137.988133,173.0702665,10543.2255,,1.5 9/3/2014,16.85473745,104.8049946,137.8359752,172.5327812,10770.80985,,1.5 9/4/2014,16.8149182,105.2699949,136.2769147,171.924697,10719.6441,,1.5 9/5/2014,16.73276107,105.0999984,136.1099769,171.6001716,10596.182,,1.5 9/8/2014,16.74116485,106.0300003,136.7427868,170.7650273,10624.206,,1.5 9/9/2014,16.73542136,106.1950023,137.3815084,171.0425041,10530.2962,,1.5 9/10/2014,16.84323997,106.8450038,138.0071764,173.2201628,10475.0838,,1.5 9/11/2014,16.78993276,107.110005,138.4466288,174.1098633,10505.3488,,1.5 9/12/2014,16.87236896,107.3349944,139.1594768,174.6267354,10423.30185,,1.5 9/15/2014,16.76516199,107.175002,138.6962552,173.973556,10358.46375,,1.5 9/16/2014,16.73164121,107.1250017,138.8310426,174.3679163,10610.73125,,1.5 9/17/2014,16.81887751,108.3900041,139.4505648,176.3979538,10727.3583,,1.5 9/18/2014,17.1906964,108.7099972,140.4889014,178.3007934,10620.967,,1.5 9/19/2014,17.16266777,109.0449992,139.8992725,177.6041204,10728.93755,,1.5 9/22/2014,17.15839775,108.8449946,139.8601399,178.0785326,10554.69965,,1.5 9/23/2014,17.13340929,108.895001,139.8992725,178.4598911,10546.48075,,1.5 9/24/2014,17.05771478,109.0250025,139.3339836,178.1419792,10569.97375,,1.5 9/25/2014,16.99466368,108.7549946,138.6770212,177.4622893,10549.235,,1.5 9/26/2014,16.9210464,109.2849953,138.6193513,177.5410564,10600.645,,1.5 9/29/2014,16.99394166,109.4850033,138.8888889,177.8251978,10641.942,,1.5 9/30/2014,17.06368166,109.6550023,138.5233412,177.7935817,10381.03885,1.49,1.5 10/1/2014,16.88718516,108.895001,137.4759417,176.2425097,10253.5532,,1.5 10/2/2014,16.82467844,108.4250022,137.3626374,175.0393839,10129.0635,,1.5 10/3/2014,16.82439537,109.7700022,137.4003847,175.2541185,10132.8687,,1.5 10/6/2014,16.80262793,108.8000056,137.6841526,174.9934377,10095.552,,1.5 10/7/2014,16.71975188,108.0349947,136.8738024,173.882803,9951.10385,,1.5 10/8/2014,16.77922732,108.0849954,137.6273053,174.7487986,9876.8073,,1.5 10/9/2014,16.6583375,107.8400004,136.8550705,173.8223536,9710.992,,1.5 10/10/2014,16.5395875,107.6700018,135.9619307,173.100225,9712.9107,,1.5 10/13/2014,16.50968706,106.8649967,136.2769147,171.895144,9499.22985,,1.5 10/14/2014,16.27100994,107.0549994,135.5197181,170.2562356,9103.9572,,1.5 10/15/2014,16.19905398,105.9249996,135.9804188,169.707255,8874.3965,,1.5 10/16/2014,16.24840563,106.3350035,136.2026696,171.0717646,8982.11745,,1.5 10/17/2014,16.32853002,106.8750017,136.4070386,172.013417,9208.35,,1.5 10/20/2014,16.31760588,106.9549945,136.8925394,172.8907331,9133.957,,1.5 10/21/2014,16.29155364,106.9950015,136.0544218,172.3840717,9225.1089,,1.5 10/22/2014,16.20666742,107.1449962,135.5197181,171.9838335,9076.25295,,1.5 10/23/2014,16.4594152,108.2650046,136.9112815,173.5508504,9400.64995,,1.5 10/24/2014,16.39277079,108.1600015,137.0426203,174.0341107,9315.8208,,1.5 10/27/2014,16.34120435,107.8150028,136.9112815,173.8072478,9253.76145,,1.5 10/28/2014,16.35670707,108.1549948,137.7220768,174.4591766,9304.57465,,1.5 10/29/2014,16.22968247,108.8899971,137.5515818,174.3375174,9486.4968,,1.5 10/30/2014,16.29420822,109.2099956,137.7410468,174.7487986,9418.2704,,1.5 10/31/2014,16.6313251,112.3249948,140.6865504,179.6945193,9644.2245,,1.5 11/3/2014,16.75238303,114.0500023,142.3690205,182.1659532,9669.159,,1.5 11/4/2014,16.56136399,113.5999987,142.5110446,181.8016544,9408.352,,1.5 11/5/2014,16.79289325,114.6450052,143.1434297,183.1669567,9509.80275,,1.5 11/6/2014,16.77078529,115.2100013,142.5719989,182.3985408,9546.3006,,1.5 11/7/2014,16.8245369,114.5400062,142.6533524,181.8181818,9551.4906,,1.5 11/10/2014,16.85786293,114.8600012,142.6737052,181.9505095,9457.5724,,1.5 11/11/2014,17.03853264,115.7800041,144.4251878,184.3148097,9455.7526,,1.5 11/12/2014,16.97490261,115.4850029,143.6575205,182.2655609,9282.6843,,1.5 11/13/2014,17.03708121,115.7549958,144.4251878,181.8512457,9019.6296,,1.5 11/14/2014,17.21525961,116.2800027,145.6239988,182.1991437,9233.7948,,1.5 11/17/2014,17.18213058,116.6500032,145.22219,182.4484583,9251.5115,,1.5 11/18/2014,17.36111111,116.8699971,146.5201465,182.6984562,9170.7889,,1.5 11/19/2014,17.38238643,117.9799984,148.1042654,185.013876,9214.238,,1.5 11/20/2014,17.47167405,118.2150054,148.2359917,185.528757,9377.99595,,1.5 11/21/2014,17.30717642,117.809997,145.9640928,184.4337883,9467.2116,,1.5 11/24/2014,17.44348311,118.2750017,147.1670346,185.7527631,9424.152,,1.5 11/25/2014,17.33778336,117.9750016,147.1670346,185.3052905,9240.98175,,1.5 11/26/2014,17.23677293,117.7299961,147.2320377,185.9081614,9153.5075,,1.5 11/27/2014,16.99148726,117.7049974,146.7351431,185.2194851,8543.0289,,1.5 11/28/2014,16.87322304,118.6400059,147.7323091,185.6493085,8322.596,,1.5 12/1/2014,17.06324492,118.3949948,147.6450613,186.2370798,8588.3733,,1.5 12/2/2014,16.95777514,119.2150026,147.6232654,186.4106627,8409.4261,,1.5 12/3/2014,17.03127794,119.7949972,147.4708745,187.9169407,8376.0664,,1.5 12/4/2014,16.9702935,119.7849955,148.2799526,187.7405426,8341.8274,,1.5 12/5/2014,17.02475399,121.425005,149.1869312,189.2326616,8386.82475,,1.5 12/8/2014,16.85118717,120.6950053,148.6546752,188.9287739,7988.80205,,1.5 12/9/2014,16.79994624,119.694998,148.1262035,187.5820672,8000.4138,,1.5 12/10/2014,16.44371727,117.8149937,146.6490688,185.1166235,7568.4356,,1.5 12/11/2014,16.27975125,118.6699942,147.275405,186.6716446,7556.9056,,1.5 12/12/2014,16.12383102,118.8000059,148.03849,186.758801,7347.78,,1.5 12/15/2014,15.74356875,117.8250023,146.5416178,184.2468908,7194.3945,,1.5 12/16/2014,15.67643831,116.4100039,145.6452083,183.3180568,6968.3026,,1.5 12/17/2014,16.01396418,118.6549981,146.4557704,184.808723,7259.3129,,1.5 12/18/2014,16.06206381,118.8350034,146.0067163,186.202402,7043.35045,,1.5 12/19/2014,16.22757552,119.504996,146.1347362,186.7936864,7335.2169,,1.5 12/22/2014,16.16618842,120.0599964,146.8428781,187.1607711,7216.8066,,1.5 12/23/2014,16.21021406,120.6849984,146.9075951,187.3360809,7445.05765,,1.5 12/24/2014,16.17494824,120.5049979,146.9507715,187.4941408,7259.2212,,1.5 12/26/2014,16.124091,120.4049991,146.6060695,187.3185352,7158.07725,,1.5 12/29/2014,16.17507906,120.6749932,146.6490688,187.2308556,6984.669,,1.5 12/30/2014,16.07639503,119.4799944,145.2643812,185.8908821,6917.892,,1.5 12/31/2014,16.01473355,119.694998,144.8225923,186.4280388,6862.11435,2.91,1.25 1/2/2015,15.86999302,120.5049979,144.6340758,184.6892603,6798.8921,,1.25 1/5/2015,15.66232037,119.6349984,142.7755568,182.4318161,6353.81485,,1.25 1/6/2015,15.28444349,118.4050041,140.7657658,179.4043775,6050.4955,,1.25 1/7/2015,15.4778396,119.254995,141.1831145,180.1964141,6099.89325,,1.25 1/8/2015,15.69834069,119.6599933,141.1034288,180.5543017,6097.8736,,1.25 1/9/2015,15.47137409,118.5299957,140.3508772,179.6945193,5939.5383,,1.25 1/12/2015,15.27988937,118.3500021,140.0560224,179.5654516,5613.3405,,1.25 1/13/2015,15.1998784,117.9299937,138.8310426,178.7629603,5494.3587,,1.25 1/14/2015,15.39551067,117.3350029,138.3317195,178.7310098,5713.04115,,1.25 1/15/2015,15.32801962,116.1649984,135.098622,176.4602082,5537.58555,,1.25 1/16/2015,15.57632399,117.6400004,136.1099769,178.2372338,5901.9988,,1.25 1/19/2015,15.4223408,117.5700021,136.4442625,177.6830135,5742.1188,,1.25 1/20/2015,15.48574924,118.809999,137.2306848,179.937022,5701.6919,,1.25 1/21/2015,15.54388037,117.9550046,136.9487812,178.619273,5783.33365,,1.25 1/22/2015,15.48383101,118.4899967,134.6801347,177.8568253,5749.1348,,1.25 1/23/2015,15.15553366,117.775004,131.9957761,176.5380881,5746.24225,,1.25 1/26/2015,15.17450683,118.460001,133.1380642,178.6352269,5705.0336,,1.25 1/27/2015,15.25355217,117.8699995,134.1561578,179.147259,5846.352,,1.25 1/28/2015,15.00746621,117.550004,132.6963907,177.9201139,5697.6485,,1.25 1/29/2015,15.10927785,118.2899998,133.9046599,178.2213509,5811.5877,,1.25 1/30/2015,15.19976288,117.4549992,132.5908247,176.9911504,6223.94045,,1.25 2/2/2015,15.37349916,117.5949988,133.3688984,176.8502962,6438.32625,,1.25 2/3/2015,15.64492283,117.5700021,134.9892009,178.3166904,6808.4787,,1.25 2/4/2015,15.42638529,117.2749936,133.0671989,178.0468263,6351.614,,1.25 2/5/2015,15.63758337,117.5349996,134.8981519,180.1639492,6648.95495,,1.25 2/6/2015,15.5966093,118.9799987,134.6257404,181.3894431,6877.044,,1.25 2/9/2015,15.57765852,118.6400059,134.354427,180.5054152,6921.4576,,1.25 2/10/2015,15.75324123,119.4299941,135.2082207,182.1825469,6739.4349,,1.25 2/11/2015,15.75410985,120.4650046,136.5374113,183.5704452,6584.6169,,1.25 2/12/2015,15.59332606,119.1050021,135.8142062,183.2340815,6794.94025,,1.25 2/13/2015,15.64773812,118.7550011,135.2082207,182.8655024,7305.8076,,1.25 2/16/2015,15.6528817,118.4800011,134.4989913,182.0333121,7274.672,,1.25 2/17/2015,15.86961524,119.254995,136.0914535,183.1334127,7457.01515,,1.25 2/18/2015,15.78120931,118.7900003,135.3912808,183.3516685,7190.3587,,1.25 2/19/2015,15.67434971,118.9450007,135.1899419,183.3348611,7161.67845,,1.25 2/20/2015,15.8101517,119.0300054,135.4646437,183.3180568,7167.9866,,1.25 2/23/2015,15.59758237,118.8149963,134.643867,183.6547291,6998.2035,,1.25 2/24/2015,15.68061719,118.9799987,134.9345567,183.87423,6979.3668,,1.25 2/25/2015,15.75485446,118.8600042,135.0438893,184.569952,7325.3418,,1.25 2/26/2015,15.5927182,119.4199962,133.7255951,183.9757152,7171.171,,1.25 2/27/2015,15.5949067,119.5399958,133.8329764,184.501845,7480.8132,,1.25 3/2/2015,15.60500609,120.1300047,134.354427,184.569952,7152.5402,,1.25 3/3/2015,15.52216565,119.7299945,133.8150676,183.9249586,7305.9246,,1.25 3/4/2015,15.38899533,119.6799996,132.5908247,182.6817684,7246.624,,1.25 3/5/2015,15.55560741,120.1499953,132.5381047,183.1166453,7266.672,,1.25 3/6/2015,15.2817574,120.8400072,131.0444241,181.7025529,7217.7732,,1.25 3/9/2015,15.2780218,121.1549948,131.4751512,183.3012556,7091.20215,,1.25 3/10/2015,14.9799269,121.1350059,129.5840352,182.5483753,6830.80265,,1.25 3/11/2015,14.79749626,121.4500013,128.0901755,181.3236627,6988.233,,1.25 3/12/2015,14.97073222,121.3000012,129.0156109,180.5217077,6923.804,,1.25 3/13/2015,14.78262155,121.3949936,127.4047649,179.0029535,6636.66465,,1.25 3/16/2015,14.67405261,121.3350005,128.2380097,179.9208348,6484.1424,,1.25 3/17/2015,14.60024528,121.364997,128.6173633,178.9549034,6494.24115,,1.25 3/18/2015,14.70772082,120.1050006,130.5142261,179.9046505,6715.07055,,1.25 3/19/2015,14.93506978,120.7999956,128.7664177,178.2213509,6575.144,,1.25 3/20/2015,14.94489072,120.035007,129.9038711,179.4687724,6640.3362,,1.25 3/23/2015,15.1773857,119.7349977,131.061599,179.0350013,6695.5812,,1.25 3/24/2015,15.23983693,119.7450054,130.8386759,177.8568253,6599.14695,,1.25 3/25/2015,15.24239214,119.4999977,131.1131506,177.8251978,6749.36,,1.25 3/26/2015,15.06353044,119.1999964,129.7353399,177.0068148,7055.448,,1.25 3/27/2015,14.93785851,119.1349989,129.7185108,177.2421127,6720.40535,,1.25 3/30/2015,14.98183453,120.0750037,130.0897619,177.8568253,6759.02175,,1.25 3/31/2015,14.90468454,120.1349981,128.915818,178.0151313,6620.63985,2.14,1.25 4/1/2015,14.90846204,119.7649971,128.915818,177.5410564,6838.5815,,1.25 4/2/2015,14.98228345,119.7150017,130.2931596,177.5095411,6578.33925,,1.25 4/6/2015,15.0171571,119.5349945,130.5823975,177.8726432,6947.3742,,1.25 4/7/2015,14.87630354,120.2749968,130.0897619,178.09439,7108.2525,,1.25 4/8/2015,14.90712859,120.1400064,129.516902,178.603322,6673.777,,1.25 4/9/2015,14.87022015,120.5899938,128.5347044,177.430802,6821.7763,,1.25 4/10/2015,14.8424107,120.2249939,127.4859765,175.9169672,6957.42075,,1.25 4/13/2015,14.82755553,120.1349981,126.9518852,176.3046544,6959.42055,,1.25 4/14/2015,15.02279709,119.3849954,127.1940982,176.4446405,6975.66555,,1.25 4/15/2015,15.24006919,119.1500029,127.3236567,176.8346596,7187.128,,1.25 4/16/2015,15.37019105,119.0100034,128.0737705,177.7461785,7614.2598,,1.25 4/17/2015,15.18925816,118.9150005,128.5181853,177.9201139,7545.15675,,1.25 4/20/2015,15.12584705,119.1999964,127.9918085,177.6830135,7563.24,,1.25 4/21/2015,15.19352756,119.665005,128.4686536,178.603322,7428.8032,,1.25 4/22/2015,15.16288732,119.9150042,128.6339079,180.3101334,7522.26795,,1.25 4/23/2015,15.2579742,119.584997,129.4665976,180.0828381,7755.08725,,1.25 4/24/2015,15.32625771,118.9849961,129.3828438,180.7174483,7767.3408,,1.25 4/27/2015,15.40665876,119.0399948,129.617628,181.3894431,7717.3632,,1.25 4/28/2015,15.55826961,118.8550032,130.5142261,182.3154057,7682.7872,,1.25 4/29/2015,15.82453753,119.0399948,132.5029813,183.7728567,7837.5936,,1.25 4/30/2015,15.8462282,119.3650021,133.9764202,183.2340815,7971.1947,,1.25 5/1/2015,15.80477937,120.1750036,134.6076188,181.967064,7986.8305,,1.25 5/4/2015,15.81765408,120.1349981,133.9046599,181.6530427,7982.97075,,1.25 5/5/2015,15.83054979,119.8500005,134.0662287,182.0167455,8092.272,,1.25 5/6/2015,16.06787069,119.465007,135.6300014,182.1327748,8096.14305,,1.25 5/7/2015,16.07368176,119.7349977,134.8981519,182.5317149,7847.4319,,1.25 5/8/2015,16.0248706,119.8050006,134.2281879,185.16804,7834.04895,,1.25 5/11/2015,15.86671956,120.0849962,133.9584729,187.1607711,7794.71735,,1.25 5/12/2015,16.01614427,119.8649984,134.4086022,187.8287002,8014.1739,,1.25 5/13/2015,16.12929241,119.1599983,135.3363107,187.6172608,7961.0796,,1.25 5/14/2015,16.16788734,119.1649966,135.9619307,187.9875928,7935.19735,,1.25 5/15/2015,16.31960311,119.290005,136.6120219,187.5644753,7969.7649,,1.25 5/18/2015,16.20154725,119.9899976,135.7773252,187.8110621,7951.7373,,1.25 5/19/2015,16.01640079,120.6950053,134.5713901,187.1958068,7726.8939,,1.25 5/20/2015,16.02435702,121.3549965,134.6257404,188.554728,7891.71565,,1.25 5/21/2015,16.01588776,121.039995,134.4989913,189.5734597,8054.0016,,1.25 5/22/2015,15.89863033,121.5450072,133.9046599,188.2707333,7945.39665,,1.25 5/25/2015,15.90343435,121.5600038,133.4400854,188.0582981,7964.6112,,1.25 5/26/2015,15.87414974,123.1049986,133.8508901,189.3939394,7844.2506,,1.25 5/27/2015,15.91609037,123.6650054,134.8617667,189.8794266,7674.6499,,1.25 5/28/2015,15.88007368,123.9549974,135.7036233,189.8433792,7757.1039,,1.25 5/29/2015,15.97661024,124.1449979,136.4070386,189.8253607,8138.9462,,1.25 6/1/2015,15.68160078,124.7799973,136.3512408,189.6813354,8095.7264,,1.25 6/2/2015,15.85527307,124.114998,138.4466288,190.4399162,8128.29135,,1.25 6/3/2015,16.01511827,124.249996,140.0952648,190.6395958,7927.15,,1.25 6/4/2015,16.02795275,124.3750001,139.7819402,191.1132346,7714.98125,,1.25 6/5/2015,15.80315589,125.6250001,139.6063102,191.8465228,7953.31875,,1.25 6/8/2015,15.92876656,124.4850055,140.5678943,191.0767173,7803.96465,,1.25 6/9/2015,15.9813338,124.3400033,140.291807,191.2960306,8067.1792,,1.25 6/10/2015,15.80253157,122.675002,138.9467834,190.5306278,8059.7475,,1.25 6/11/2015,15.73452706,123.4199927,138.9467834,191.5341889,8035.8762,,1.25 6/12/2015,15.93016217,123.3849983,139.0433815,191.9754271,7880.59995,,1.25 6/15/2015,15.91913082,123.4199927,139.256371,192.5483778,7727.3262,,1.25 6/16/2015,15.8988831,123.3600058,138.7539892,193.0315607,7858.032,,1.25 6/17/2015,16.11720431,123.4349985,139.9384271,195.427008,7883.79345,,1.25 6/18/2015,15.77199997,122.965006,139.6843135,195.2743605,7901.7309,,1.25 6/19/2015,15.87226005,122.675002,139.275766,194.8558067,7730.9785,,1.25 6/22/2015,15.93231951,123.3749971,139.9188471,195.2362358,7814.5725,,1.25 6/23/2015,15.84020402,123.9549974,138.4657989,194.9887881,7988.89975,,1.25 6/24/2015,15.77647885,123.8500062,138.7925052,194.5146859,7863.2365,,1.25 6/25/2015,15.82766835,123.619999,138.5041551,194.6661476,7812.784,,1.25 6/26/2015,15.80003476,123.8550069,138.2934587,195.0838861,7835.0673,,1.25 6/29/2015,15.59514991,122.5399943,137.6841526,192.8640309,7598.7054,,1.25 6/30/2015,15.61621588,122.5000046,136.4349546,192.4557352,7789.775,1.93,1 7/1/2015,15.52276802,123.1749931,136.1563074,192.3816853,7638.08175,,1 7/2/2015,15.45368145,123.0650028,136.4163427,192.0860546,7638.64455,,1 7/3/2015,15.34836962,122.8149984,136.490821,191.2228703,7408.2008,,1 7/6/2015,15.18130271,122.5750067,135.5289015,191.2960306,6930.3905,,1 7/7/2015,15.02054059,122.5449948,134.943661,189.4477598,6966.68325,,1 7/8/2015,14.67749866,120.7049993,133.7255951,185.4427446,6886.22025,,1 7/9/2015,14.90635085,121.3449977,133.949501,186.6193898,7112.03045,,1 7/10/2015,15.31393568,122.7549953,137.0520112,190.5850962,7209.40115,,1 7/13/2015,15.26251526,123.4399962,135.8326542,191.1863111,7141.004,,1 7/14/2015,15.23159642,123.3800051,135.8603356,192.9198418,7218.9638,,1 7/15/2015,15.17899834,123.7799934,135.5197181,193.5546308,7061.649,,1 7/16/2015,15.21352178,124.1550011,135.0256549,193.7984496,7140.15405,,1 7/17/2015,15.17404631,124.0750053,134.354427,193.6670863,7084.6825,,1 7/20/2015,15.0845489,124.2650036,134.5442314,193.4235977,7039.61225,,1 7/21/2015,15.26869079,123.8900075,135.501355,192.7525058,7066.6856,,1 7/22/2015,15.19456642,123.9650007,135.5380862,193.5546308,6958.15545,,1 7/23/2015,15.153926,123.9150003,136.0821936,192.2337562,6848.78205,,1 7/24/2015,15.09354223,123.8199954,135.998912,192.0860546,6763.0484,,1 7/27/2015,15.07931721,123.2450065,136.7240908,191.7545542,6589.91015,,1 7/28/2015,15.13122555,123.5600009,136.6586949,192.9012346,6585.748,,1 7/29/2015,15.20114921,123.9349956,136.1563074,193.4048931,6615.6503,,1 7/30/2015,15.19018107,124.1449979,135.7220413,193.6858416,6618.16995,,1 7/31/2015,15.16323219,123.9400031,136.1841209,193.6295866,6470.9074,,1 8/3/2015,15.02708632,124.0350076,135.8234295,193.3488012,6142.2132,,1 8/4/2015,14.99374011,124.3849939,135.3546291,193.6108422,6218.00615,,1 8/5/2015,15.12950859,124.9000019,136.2119458,194.8747929,6193.791,,1 8/6/2015,15.07079506,124.7399951,136.2769147,193.498452,6177.1248,,1 8/7/2015,15.02290994,124.2250068,136.2583458,192.4927815,6038.57725,,1 8/10/2015,15.1998784,124.6300047,137.3343405,194.3068105,6282.5983,,1 8/11/2015,15.1183007,125.1299944,138.1501692,194.8747929,6153.8934,,1 8/12/2015,15.23542541,124.2099934,138.5809313,193.9487975,6168.2686,,1 8/13/2015,15.13798271,124.425001,138.7251162,194.2313295,6124.1985,,1 8/14/2015,15.09228935,124.3149933,138.0738695,194.4579485,6095.16445,,1 8/17/2015,15.14635162,124.390007,137.8074829,193.8735944,6062.7686,,1 8/18/2015,15.01219741,124.405002,137.1083842,194.8368242,6072.20805,,1 8/19/2015,14.91947215,123.8100002,137.6746747,194.118218,5838.8796,,1 8/20/2015,14.99587613,123.4050057,138.7251162,193.5921014,5753.1411,,1 8/21/2015,14.88549334,122.025,138.9757487,191.5525333,5547.2565,,1 8/24/2015,14.42075435,118.4199931,137.6273053,186.8111339,5055.3498,,1 8/25/2015,14.44700477,118.8799983,136.8925394,186.4801865,5136.8048,,1 8/26/2015,14.30993897,119.9150042,135.6852103,185.3911754,5173.1331,,1 8/27/2015,14.58682809,121.0349993,136.1099769,186.3932898,5756.4246,,1 8/28/2015,14.69021999,121.7150033,136.0729351,187.35363,6091.83575,,1 8/31/2015,14.63978802,121.2249931,135.9434475,186.0119048,6564.33375,,1 9/1/2015,14.40424061,119.375005,135.0621286,182.6984562,5916.225,,1 9/2/2015,14.59204296,120.3249978,135.0894968,184.1112032,6076.4125,,1 9/3/2015,14.49779633,120.0750037,133.5648457,183.200513,6085.401,,1 9/4/2015,14.33311595,119.0050039,132.6523844,180.5543017,5903.83805,,1 9/7/2015,14.33034307,119.2749941,133.2001332,182.1327748,5681.06825,,1 9/8/2015,14.5458777,119.8050006,134.1741581,184.4507977,5932.7436,,1 9/9/2015,14.66361663,120.5099935,135.0347715,185.150898,5733.8658,,1 9/10/2015,14.74121792,120.6149966,136.045167,186.2891207,5896.86735,,1 9/11/2015,14.79082082,120.5800043,136.7334382,186.0465116,5804.7212,,1 9/14/2015,14.68191628,120.2349969,136.1192405,185.4771399,5575.29695,,1 9/15/2015,14.69637294,120.4400059,135.6944162,184.774575,5616.1172,,1 9/16/2015,14.79432194,120.5650014,136.1099769,186.7762421,5998.10875,,1 9/17/2015,14.84362244,120.0050018,137.2401016,187.1082421,5889.8454,,1 9/18/2015,14.70642303,119.9949938,135.6576002,186.3759202,5696.16265,,1 9/21/2015,14.65953236,120.5500022,134.8890538,186.9508319,5897.306,,1 9/22/2015,14.49863713,120.1499953,133.6183859,184.6381093,5896.962,,1 9/23/2015,14.51926707,120.2999993,134.5713901,183.4021091,5744.325,,1 9/24/2015,14.20615979,120.0849962,134.8526735,183.0328544,5784.49445,,1 9/25/2015,14.15708704,120.5800043,134.9892009,183.0663616,5860.188,,1 9/28/2015,14.05382615,119.9249989,134.8617667,181.967064,5677.2495,,1 9/29/2015,14.1299817,119.7349977,134.6892047,181.4058957,5774.81905,,1 9/30/2015,14.07528872,119.8649984,133.9764202,181.3401034,5797.87005,2.69,0.75 10/1/2015,14.21342885,119.9349952,134.2822613,181.4717358,5719.70015,,0.75 10/2/2015,14.3088128,119.9049969,134.4086022,182.0498817,5771.02765,,0.75 10/5/2015,14.33085648,120.4599982,134.7345729,182.4318161,5932.655,,0.75 10/6/2015,14.52749328,120.2500046,135.5472721,183.099881,6243.38,,0.75 10/7/2015,14.61037775,120.0149971,134.8435814,183.8404265,6160.36995,,0.75 10/8/2015,14.73014377,119.9349952,135.2722354,184.0942563,6362.55175,,0.75 10/9/2015,14.88737699,120.2749968,136.6120219,184.0773125,6332.47875,,0.75 10/12/2015,14.82447818,120.035007,136.3047775,184.1959845,5984.9451,,0.75 10/13/2015,14.67986876,119.7450054,136.2769147,182.5483753,5896.2438,,0.75 10/14/2015,14.70296338,118.8300045,136.3326517,183.9249586,5840.4945,,0.75 10/15/2015,14.67997651,118.8900049,135.3363107,183.7728567,5791.1319,,0.75 10/16/2015,14.72493816,119.4450012,135.5289015,184.3657817,6027.1947,,0.75 10/19/2015,14.6925942,119.4949998,135.3088424,184.7575058,5808.65195,,0.75 10/20/2015,14.75296166,119.840004,135.9896648,185.0481125,5837.4064,,0.75 10/21/2015,14.63860933,119.95,136.0081605,184.9454411,5739.6075,,0.75 10/22/2015,14.55095745,120.6899944,134.0482574,185.8045336,5802.7752,,0.75 10/23/2015,14.48246897,121.465004,133.8240214,186.0119048,5829.10535,,0.75 10/26/2015,14.53329942,121.095004,133.8867318,185.8908821,5756.8563,,0.75 10/27/2015,14.25598038,120.4599982,133.1026221,184.2638659,5638.7326,,0.75 10/28/2015,14.12688771,121.095004,132.2488924,184.808723,5939.70975,,0.75 10/29/2015,14.14477174,121.1300024,132.9610424,185.4599407,5911.144,,0.75 10/30/2015,14.21797579,120.6250064,132.7580485,186.115764,5978.175,,0.75 11/2/2015,14.22637,120.754994,133.0406439,186.1504095,5891.63645,,0.75 11/3/2015,14.23224172,121.0649942,132.7756755,186.7239287,6118.6251,,0.75 11/4/2015,14.05678943,121.5549947,132.0829481,187.0382493,5905.1419,,0.75 11/5/2015,14.2345715,121.7500054,132.5205407,185.1337591,5841.565,,0.75 11/6/2015,14.21130794,123.1600049,132.2926313,185.3568119,5840.2472,,0.75 11/9/2015,14.21373189,123.1900001,132.4240217,186.202402,5813.3361,,0.75 11/10/2015,14.27572128,123.1450052,132.0829481,186.202402,5841.9988,,0.75 11/11/2015,14.26798122,122.8450068,131.9870653,186.8809568,5627.52945,,0.75 11/12/2015,14.12688771,122.609994,132.6347901,186.7413632,5402.1966,,0.75 11/13/2015,14.13487498,122.6450013,132.2051824,186.8460389,5348.54845,,0.75 11/16/2015,14.16540949,123.1749931,131.6309069,187.2133296,5488.678,,0.75 11/17/2015,14.21201484,123.4499928,131.4060447,187.8287002,5378.7165,,0.75 11/18/2015,14.25872456,123.6349924,131.7870322,188.377131,5457.2489,,0.75 11/19/2015,14.28673477,122.8650055,131.8826245,187.8639865,5428.1757,,0.75 11/20/2015,14.23740879,122.9100075,130.8472359,186.7239287,5489.1606,,0.75 11/23/2015,14.19537089,122.8450068,130.6506402,185.8045336,5507.14135,,0.75 11/24/2015,14.1719339,122.5349942,130.3865963,184.8599686,5651.3142,,0.75 11/25/2015,14.20071288,122.7200005,130.4035991,185.6493085,5665.9824,,0.75 11/26/2015,14.15368066,122.620007,130.0982242,185.2023335,5574.3052,,0.75 11/27/2015,14.10954652,122.8450068,130.1320841,184.7404397,5510.8267,,0.75 11/30/2015,14.15147741,123.0999977,130.0474673,185.3396349,5491.491,,0.75 12/1/2015,14.25161221,122.8700024,130.6250408,185.3052905,5460.3428,,0.75 12/2/2015,14.2428839,123.2450065,130.8215594,184.280844,5236.68005,,0.75 12/3/2015,14.45306007,122.6150003,134.1111782,185.6837805,5375.4416,,0.75 12/4/2015,14.44898785,123.1749931,134.0931948,186.1330852,5296.525,,0.75 12/7/2015,14.24917533,123.3749971,133.6809037,185.7182654,5025.06375,,0.75 12/8/2015,14.00158218,122.9249953,133.9225927,184.501845,4948.9605,,0.75 12/9/2015,14.00658309,121.4350023,133.8867318,184.3657817,4870.75785,,0.75 12/10/2015,14.0620276,121.6000031,133.0406439,184.3317972,4831.168,,0.75 12/11/2015,13.91856249,120.8649969,132.8197636,183.9249586,4584.40945,,0.75 12/14/2015,13.98063682,121.0300041,133.0317946,183.2676624,4589.4576,,0.75 12/15/2015,14.00324875,121.6800066,132.9610424,182.9993595,4678.596,,0.75 12/16/2015,13.94923872,122.2149952,133.3688984,183.368479,4545.17585,,0.75 12/17/2015,13.97907333,122.5599989,132.6787847,182.6317231,4542.0736,,0.75 12/18/2015,13.86722136,121.2199968,131.7436269,180.5543017,4470.5936,,0.75 12/21/2015,13.79938455,121.1850051,132.2663845,180.3914494,4405.07475,,0.75 12/22/2015,13.88561034,121.0750056,132.6259947,179.4848784,4372.01825,,0.75 12/23/2015,13.86779828,120.9299952,131.9348242,179.8399425,4517.9448,,0.75 12/24/2015,13.84399205,120.4350016,132.1091221,179.6299623,4563.28215,,0.75 12/28/2015,13.83680868,120.4049991,132.0567844,179.1312136,4409.2311,,0.75 12/29/2015,13.81587582,120.4650046,131.5183797,178.4280489,4552.37235,,0.75 12/30/2015,13.7059525,120.515004,131.7523057,178.5714286,4393.9769,,0.75 12/31/2015,13.60729351,120.3200031,130.6762496,177.3364072,4485.5296,0.56,0.75 1/4/2016,13.44971823,119.4399936,129.3661061,175.7778168,4445.5568,,0.75 1/5/2016,13.36362421,119.060007,127.9672404,174.7182668,4336.1652,,0.75 1/6/2016,13.23451562,118.475004,127.7302337,173.2952084,4055.39925,,0.75 1/7/2016,13.24713862,117.6799954,128.6918474,172.0282126,3971.7,,0.75 1/8/2016,13.25679742,117.4549992,128.3944277,170.53206,3940.61525,,0.75 1/11/2016,13.17158625,117.7650039,127.8608874,171.2182176,3715.48575,,0.75 1/12/2016,13.24591033,117.6449966,127.7383918,169.9668565,3630.5247,,0.75 1/13/2016,13.3435634,117.6849949,128,169.5489997,3567.03235,,0.75 1/14/2016,13.45297513,118.0499982,128.2709082,170.1548409,3663.0915,,0.75 1/15/2016,13.25486454,117.0649979,127.7955272,166.9031127,3387.8611,,0.75 1/18/2016,13.1834811,117.344999,127.8200294,167.1262639,3350.19975,,0.75 1/19/2016,13.34783798,117.6400004,128.328521,166.5140288,3383.3264,,0.75 1/20/2016,13.17505698,116.9349935,127.3560876,165.9475606,3260.1478,,0.75 1/21/2016,13.38517859,117.7049974,128,167.4060434,3442.87125,,0.75 1/22/2016,13.59628549,118.7850052,128.2544568,169.4484453,3822.5013,,0.75 1/25/2016,13.50530083,118.2949953,128.3449913,168.5630004,3607.9975,,0.75 1/26/2016,13.6107198,118.4249996,128.7498391,169.9668565,3765.915,,0.75 1/27/2016,13.7014455,118.6749937,129.2741258,168.9189189,3928.1425,,0.75 1/28/2016,13.79491106,118.8250061,129.9798531,170.6484642,4026.97925,,0.75 1/29/2016,13.95176874,121.0549992,131.1819494,172.4732666,4205.4507,,0.75 2/1/2016,13.92301962,120.9850067,131.7349493,174.6114894,4142.5264,,0.75 2/2/2016,13.74069926,119.9649942,130.9929264,172.8757887,3925.2548,,0.75 2/3/2016,13.76178353,117.9150033,130.9157557,172.1763085,4131.7416,,0.75 2/4/2016,13.73286825,116.7650023,130.8814868,170.3722634,4023.7219,,0.75 2/5/2016,13.6107198,116.8999991,130.4461258,169.5346274,3981.614,,0.75 2/8/2016,13.48617667,115.8450012,129.7185108,167.1821449,3808.9836,,0.75 2/9/2016,13.40320873,115.1150028,130.0136514,166.6111296,3490.2868,,0.75 2/10/2016,13.30840226,113.3450026,127.9672404,164.5955065,3495.5598,,0.75 2/11/2016,13.13421858,112.4249971,127.3074475,162.7604167,3379.4955,,0.75 2/12/2016,13.19452691,113.2249966,127.4941034,164.2710472,3777.186,,0.75 2/15/2016,13.28841848,114.5750064,127.8118609,165.3986107,3825.65925,,0.75 2/16/2016,13.22436457,114.074995,127.1294177,163.1853786,3670.9335,,0.75 2/17/2016,13.35586022,114.104998,126.976065,163.132137,3936.6225,,0.75 2/18/2016,13.1813089,113.2449992,125.7861635,162.3508402,3882.0386,,0.75 2/19/2016,13.15902018,112.5700059,125.3446979,162.166545,3715.9357,,0.75 2/22/2016,13.12818358,112.9250003,124.5485116,159.7826955,3917.36825,,0.75 2/23/2016,13.02312255,112.1150013,123.55594,157.2079862,3730.06605,,0.75 2/24/2016,12.9445649,112.1849958,123.55594,156.2377939,3860.28585,,0.75 2/25/2016,13.09440411,112.9950014,124.5640259,157.778479,3987.59355,,0.75 2/26/2016,13.12396239,113.9999977,124.6416552,158.1277672,4001.4,,0.75 2/29/2016,12.96319102,112.6899982,122.5264964,156.8135487,4053.4593,,0.75 3/1/2016,13.17835587,114.0100055,123.8927089,159.0330789,4196.7081,,0.75 3/2/2016,13.09483278,113.4800062,123.3121647,159.7316508,4190.8164,,0.75 3/3/2016,13.24196378,113.6850027,124.5873046,161.1603546,4214.30295,,0.75 3/4/2016,13.42182792,113.7600001,125.1799462,161.8515821,4404.7872,,0.75 3/7/2016,13.34374145,113.4650057,124.9687578,161.8646811,4633.9106,,0.75 3/8/2016,13.14302237,112.6149968,123.9310943,160.0384092,4465.18475,,0.75 3/9/2016,13.30654283,113.3400053,124.8049922,161.2773163,4654.8738,,0.75 3/10/2016,13.28109436,113.195006,126.4942129,161.5900461,4533.45975,,0.75 3/11/2016,13.53006041,113.8150015,126.9116061,163.599182,4596.98785,,0.75 3/14/2016,13.43778975,113.8250027,126.4142595,162.7736632,4499.50225,,0.75 3/15/2016,13.24213914,113.1849999,125.738715,160.1922307,4384.7869,,0.75 3/16/2016,13.31265434,112.5900059,126.3823065,160.5522999,4540.7547,,0.75 3/17/2016,13.383835,111.3849944,126.0795562,161.2773163,4626.9329,,0.75 3/18/2016,13.28877165,111.5699985,125.738715,161.5508885,4596.684,,0.75 3/21/2016,13.29840286,111.9450019,125.8415655,160.8622215,4650.1953,,0.75 3/22/2016,13.37095027,112.3750053,126.0477721,159.6678908,4696.15125,,0.75 3/23/2016,13.25143944,112.3800062,125.6834035,158.6420243,4548.0186,,0.75 3/24/2016,13.30521498,112.9049959,126.1590866,159.8082301,4565.8782,,0.75 3/28/2016,13.45252268,113.4550032,127.0244522,161.7207083,4568.83285,,0.75 3/29/2016,13.4261528,112.6950018,127.2507476,162.1008267,4410.8823,,0.75 3/30/2016,13.5296943,112.4249971,127.4616022,161.6684181,4413.8055,,0.75 3/31/2016,13.61674315,112.5749989,128.1147909,161.6684181,4457.97,1.84,0.5 4/1/2016,13.42993936,111.6649943,127.1617497,158.8562351,4318.08555,,0.5 4/4/2016,13.36487444,111.3250036,126.8311244,158.7931719,4195.83925,,0.5 4/5/2016,13.24933256,110.3249965,125.6360324,156.2866297,4178.00775,,0.5 4/6/2016,13.19435282,109.7949985,125.148614,155.0387597,4374.2328,,0.5 4/7/2016,13.00144966,108.2150011,123.1148046,152.11439,4266.91745,,0.5 4/8/2016,13.11888332,108.0550035,123.1982259,152.6368007,4531.8267,,0.5 4/11/2016,13.1633506,107.9450003,123.1451265,153.7279016,4623.28435,,0.5 4/12/2016,13.28859506,108.5449988,123.5864796,154.9426712,4850.87605,,0.5 4/13/2016,13.27924255,109.344995,123.2817605,155.3036186,4830.8621,,0.5 4/14/2016,13.28568202,109.3999979,123.2741617,154.8467018,4796.096,,0.5 4/15/2016,13.17965852,108.7650017,122.7219734,154.3924656,4687.7715,,0.5 4/18/2016,13.24626124,108.8250001,123.1299637,155.3398058,4669.68075,,0.5 4/19/2016,13.4524322,109.2000019,124.0310078,157.1709234,4808.076,,0.5 4/20/2016,13.53070116,109.845001,124.0925731,157.4555188,5030.901,,0.5 4/21/2016,13.33760137,109.4549962,123.55594,156.7766716,4874.03115,,0.5 4/22/2016,13.56106888,111.7899994,125.5808113,161.0046691,5042.8469,,0.5 4/25/2016,13.54793259,111.2050052,125.305432,161.0435623,4946.3984,,0.5 4/26/2016,13.64405392,111.3150031,125.7703434,162.3244866,5091.5481,,0.5 4/27/2016,13.65700434,111.4650001,126.1988894,162.1008267,5258.9187,,0.5 4/28/2016,13.28109436,108.1150041,122.7445686,157.95293,5204.6561,,0.5 4/29/2016,13.20934165,106.3649985,121.8546274,155.4363877,5119.34745,,0.5 5/2/2016,13.2750999,106.4199993,122.7219734,156.115838,4877.2286,,0.5 5/3/2016,13.12224023,106.6050006,122.5640397,154.9426712,4794.02685,,0.5 5/4/2016,13.12232633,107.0150048,122.9331858,155.0868486,4775.0093,,0.5 5/5/2016,13.12516817,107.2549961,122.324159,155.36394,4827.54755,,0.5 5/6/2016,13.06335728,107.1250017,122.1747098,154.5953467,4860.26125,,0.5 5/9/2016,13.17123928,108.325004,123.3121647,156.0671089,4726.21975,,0.5 5/10/2016,13.30432989,109.2649941,124.2544732,157.8282828,4973.7428,,0.5 5/11/2016,13.27536424,108.4250022,123.8466778,156.6170713,5161.03,,0.5 5/12/2016,13.40788115,109.0250025,124.0310078,157.5423395,5241.922,,0.5 5/13/2016,13.23267677,108.6150055,122.8124041,155.9940722,5195.05545,,0.5 5/16/2016,13.34730351,109.0250025,123.4110823,157.0105197,5338.95425,,0.5 5/17/2016,13.34196113,109.1350036,123.4720336,157.8407387,5378.1728,,0.5 5/18/2016,13.25618235,110.1949989,123.6017551,160.8622215,5391.84135,,0.5 5/19/2016,13.14570037,109.9649948,123.1982259,160.6812887,5367.39165,,0.5 5/20/2016,13.22427713,110.1500034,123.6323175,159.7188947,5366.508,,0.5 5/23/2016,13.08189923,109.235,122.5490196,158.2278481,5281.51225,,0.5 5/24/2016,13.16759718,109.9899953,122.5490196,160.9917089,5346.6139,,0.5 5/25/2016,13.24362981,110.1949989,122.9483002,161.9695497,5481.0993,,0.5 5/26/2016,13.25855508,109.7650019,122.8727653,161.0435623,5443.24635,,0.5 5/27/2016,13.22296565,110.2350001,122.5264964,161.2123166,5436.7902,,0.5 5/30/2016,13.31646581,111.1300032,123.8696891,162.6942162,5529.8288,,0.5 5/31/2016,13.21134855,110.7099965,123.2437762,160.2820965,5501.1799,,0.5 6/1/2016,13.18965404,109.5349998,122.5715511,157.9155152,5446.0802,,0.5 6/2/2016,13.06037157,108.8649964,121.3960546,157.0105197,5447.6046,,0.5 6/3/2016,13.02354657,106.5249969,121.0873645,154.6670791,5287.901,,0.5 6/6/2016,13.16387044,107.5600056,122.1224889,155.3277415,5437.158,,0.5 6/7/2016,13.23355235,107.3600004,121.9363492,156.1402139,5522.5984,,0.5 6/8/2016,13.20349893,106.984997,121.8991894,155.1470018,5617.78235,,0.5 6/9/2016,13.12947633,107.095001,121.1900867,154.8586914,5563.58525,,0.5 6/10/2016,12.93008702,106.984997,120.3731568,152.5436656,5407.0219,,0.5 6/13/2016,12.85760206,106.2449959,119.9688081,151.6415194,5349.43575,,0.5 6/14/2016,12.69043585,106.1150045,118.9343482,149.7902936,5287.71045,,0.5 6/15/2016,12.75982187,106.0150052,119.367353,150.5910699,5191.55455,,0.5 6/16/2016,12.42482978,104.2450024,117.0275015,148.0604086,4919.32155,,0.5 6/17/2016,12.46556388,104.124995,117.4191276,149.4991778,5119.82625,,0.5 6/20/2016,12.55390332,103.9349999,117.5917215,152.7767168,5264.30775,,0.5 6/21/2016,12.59469637,104.7450009,117.7509567,153.4330648,5302.1919,,0.5 6/22/2016,12.58993938,104.4050037,117.9453913,153.5626536,5207.7214,,0.5 6/23/2016,13.02829746,106.1550052,120.8970562,157.95293,5404.35105,,0.5 6/24/2016,12.17137293,102.2300044,113.6492783,139.8503601,4948.9543,,0.5 6/27/2016,11.89732608,102.0050001,112.4416709,134.9254537,4810.5558,,0.5 6/28/2016,12.12422481,102.76,113.7203616,137.1083842,4992.0808,,0.5 6/29/2016,12.25062325,102.8250039,114.3902997,138.0548078,5203.97325,,0.5 6/30/2016,12.34263145,103.2900035,114.7117866,137.4948439,5131.4472,0.93,0.5 7/1/2016,12.29460328,102.5249959,114.1682841,135.9711741,5162.13375,,0.5 7/4/2016,12.3706494,102.5649967,114.416476,136.323359,5138.5065,,0.5 7/5/2016,12.10001876,101.7250017,112.6760563,132.476651,4878.731,,0.5 7/6/2016,12.01562031,101.3249966,112.4669628,131.0186702,4944.66,,0.5 7/7/2016,11.84967502,100.7850043,111.5013659,130.1066875,4676.424,,0.5 7/8/2016,11.79266143,100.5450042,111.1481605,130.2677001,4701.4842,,0.5 7/11/2016,12.08451913,102.8050037,113.6815779,133.5826877,4754.73125,,0.5 7/12/2016,12.40810249,104.6949947,115.7876455,138.6481802,5074.56665,,0.5 7/13/2016,12.39917917,104.4949987,115.8882837,137.3815084,4833.9387,,0.5 7/14/2016,12.59255528,105.3450054,117.1440286,140.5580153,4990.19265,,0.5 7/15/2016,12.36147423,104.8450029,115.7072606,138.3125864,4991.67045,,0.5 7/18/2016,12.56518188,106.1599976,117.5640724,140.7360495,4985.2736,,0.5 7/19/2016,12.4653308,106.1250046,116.9727454,139.1401141,4951.7925,,0.5 7/20/2016,12.57086827,106.8450038,117.6955217,141.1432604,5039.87865,,0.5 7/21/2016,12.45981709,105.8149998,116.6588894,140.0364095,4888.653,,0.5 7/22/2016,12.40294694,106.0750001,116.4212119,139.0723872,4846.56675,,0.5 7/25/2016,12.34080363,105.7850009,116.2993545,139.014388,4730.7052,,0.5 7/26/2016,12.21456098,104.6550022,114.9887886,137.4287089,4695.86985,,0.5 7/27/2016,12.34506938,105.4000004,116.5569089,139.3534002,4581.738,,0.5 7/28/2016,12.30352804,105.2649973,116.5840863,138.5809313,4494.8155,,0.5 7/29/2016,12.08532238,102.0649995,114.064104,134.9983125,4333.6799,,0.5 8/1/2016,12.04819277,102.3949985,114.298777,134.9345567,4314.9253,,0.5 8/2/2016,11.9654438,100.8949992,113.2823563,134.7618085,4217.411,,0.5 8/3/2016,11.97382522,101.2349961,112.8668172,134.9254537,4363.2285,,0.5 8/4/2016,11.99270843,101.2149949,112.6379815,132.6699834,4482.81235,,0.5 8/5/2016,11.97719542,101.8099985,112.8604481,133.0937646,4507.1287,,0.5 8/8/2016,12.09577434,102.4450037,113.6363636,133.5826877,4649.97855,,0.5 8/9/2016,12.12187331,101.8950025,113.3016089,132.4854266,4583.2371,,0.5 8/10/2016,12.25024807,101.2850028,113.1990038,131.7783488,4461.60425,,0.5 8/11/2016,12.36009913,101.9549973,113.5460429,132.0829481,4694.0082,,0.5 8/12/2016,12.34118438,101.3050009,113.0646164,130.9157557,4758.29585,,0.5 8/15/2016,12.32802406,101.2549949,113.2438707,130.4206065,4895.67925,,0.5 8/16/2016,12.23900326,100.3049974,113.13497,130.8557969,4938.01515,,0.5 8/17/2016,12.22142783,100.269997,113.1925972,130.7787877,4998.4595,,0.5 8/18/2016,12.26016061,99.8850024,113.4108307,131.5270288,5083.14765,,0.5 8/19/2016,12.19556813,100.220003,113.5138203,131.0358383,5099.1936,,0.5 8/22/2016,12.22718102,100.3349985,113.5589371,131.830466,4932.4686,,0.5 8/23/2016,12.20293481,100.2449988,113.320868,132.3013825,5008.2402,,0.5 8/24/2016,12.22538724,100.4450015,113.13497,132.9168605,4926.82725,,0.5 8/25/2016,12.23054579,100.5250019,113.4236942,132.5996155,4993.07675,,0.5 8/26/2016,12.30784379,101.8349953,114.0380887,133.7792642,5083.6032,,0.5 8/29/2016,12.31019222,101.9150033,114.0380887,133.5380917,5020.3329,,0.5 8/30/2016,12.34072749,102.9650008,114.7381103,134.6982759,4980.41705,,0.5 8/31/2016,12.41688448,103.4250017,115.4134688,135.8787961,4865.112,,0.5 9/1/2016,12.38719907,103.2450007,115.6002543,136.9863014,4692.48525,,0.5 9/2/2016,12.50875613,103.9900028,116.0092807,138.2361073,4869.8517,,0.5 9/5/2016,12.45353276,103.4350041,115.2870648,137.6178353,4926.60905,,0.5 9/6/2016,12.48665489,102.0150003,114.8237456,137.0989855,4821.2289,,0.5 9/7/2016,12.43672815,101.7349988,114.3706754,135.7220413,4881.2453,,0.5 9/8/2016,12.51862145,102.4950052,115.406809,136.2769147,5123.72505,,0.5 9/9/2016,12.44183442,102.6950045,115.3535587,136.239782,4930.38695,,0.5 9/12/2016,12.36544846,101.8550037,114.4230219,135.8511072,4921.6336,,0.5 9/13/2016,12.38835,102.5550041,115.0681779,135.3179973,4830.3405,,0.5 9/14/2016,12.42961729,102.4250042,115.2272858,135.5564593,4696.18625,,0.5 9/15/2016,12.40248546,102.0949996,114.7907938,135.1533991,4756.60605,,0.5 9/16/2016,12.30458777,102.2949985,114.1357074,132.9964091,4682.04215,,0.5 9/19/2016,12.29649304,101.9350016,113.9017028,132.8197636,4683.91325,,0.5 9/20/2016,12.23930285,101.7099994,113.4494299,132.1003963,4666.4548,,0.5 9/21/2016,12.14306965,100.3149991,112.2397441,130.6847883,4697.75145,,0.5 9/22/2016,12.38627848,100.7500032,112.9177958,131.7609856,4800.7375,,0.5 9/23/2016,12.44841687,100.9950028,113.3722578,131.0272537,4634.66055,,0.5 9/26/2016,12.37286877,100.3349985,112.9177958,130.182907,4750.86225,,0.5 9/27/2016,12.37577813,100.4450015,112.6506703,130.795893,4617.45665,,0.5 9/28/2016,12.52332469,100.6650031,112.9050469,131.0530109,4901.37885,,0.5 9/29/2016,12.5520124,101.0249996,113.3786848,131.0186702,4974.471,,0.5 9/30/2016,12.6905969,101.3450002,113.9211666,131.5097317,4971.9857,-1.05,0.5 10/3/2016,12.73601426,101.6450024,113.9536209,130.539782,5172.71405,,0.5 10/4/2016,12.84769063,102.8950023,115.2937107,130.9671927,5234.26865,,0.5 10/5/2016,12.90930567,103.5050002,115.9823707,131.9522333,5367.7693,,0.5 10/6/2016,12.91005564,103.9450039,115.9017153,131.1045559,5458.15195,,0.5 10/7/2016,12.71835831,102.9149952,115.2737752,127.9672404,5344.37595,,0.5 10/10/2016,12.81385947,103.6049981,115.3934918,128.0901755,5505.5697,,0.5 10/11/2016,12.65198193,103.5149966,114.4295686,125.4862593,5425.22115,,0.5 10/12/2016,12.6844799,104.2050054,114.7183664,127.2183703,5398.86105,,0.5 10/13/2016,12.72143243,103.6949949,114.6526026,127.0809506,5395.25085,,0.5 10/14/2016,12.67491381,104.1949947,114.3118427,126.976065,5412.93025,,0.5 10/17/2016,12.69970283,103.8950029,114.279184,126.5822785,5352.6704,,0.5 10/18/2016,12.74039533,103.8650037,114.0510949,127.7220768,5367.7432,,0.5 10/19/2016,12.71633668,103.4449977,113.5202634,127.1051795,5448.44815,,0.5 10/20/2016,12.7025259,103.9549991,113.6234519,127.3641979,5341.2079,,0.5 10/21/2016,12.59001863,103.8350004,113.0135051,127.0486596,5376.5763,,0.5 10/24/2016,12.62100387,104.1849967,113.3658315,127.5103602,5361.3601,,0.5 10/25/2016,12.58368148,104.2299972,113.4880554,127.0325203,5293.8417,,0.5 10/26/2016,12.62076494,104.4749985,113.9731023,127.9344975,5221.6605,,0.5 10/27/2016,12.73747429,105.2900013,114.7315282,128.0573697,5313.9863,,0.5 10/28/2016,12.6695342,104.7050031,115.0417026,127.5835672,5204.88555,,0.5 10/31/2016,12.69091901,104.820001,115.1079137,128.3367556,5062.806,,0.5 11/1/2016,12.67828843,104.1550035,115.1476769,127.5184902,5014.0217,,0.5 11/2/2016,12.61304441,103.3049954,114.6394589,127.0971022,4840.8723,,0.5 11/3/2016,12.5802779,102.9849996,114.3706754,128.328521,4773.35475,,0.5 11/4/2016,12.64078676,103.1400046,114.9095088,129.1155584,4701.1212,,0.5 11/7/2016,12.68625001,104.4650013,115.3336024,129.516902,4821.05975,,0.5 11/8/2016,12.77865454,105.1600015,115.9487507,130.1574906,4841.5664,,0.5 11/9/2016,12.66327713,105.6649963,115.2737752,131.0873697,4898.6294,,0.5 11/10/2016,12.77041351,106.8249956,116.3670216,134.1201717,4896.858,,0.5 11/11/2016,12.69140221,106.6800031,115.8144652,134.4357061,4773.93,,0.5 11/14/2016,12.79500483,108.4250022,116.4144354,135.4371233,4817.32275,,0.5 11/15/2016,12.94674357,109.1750016,117.0548987,135.9896648,5125.76625,,0.5 11/16/2016,12.8666182,109.074996,116.6180758,135.7220413,5086.16725,,0.5 11/17/2016,12.89365954,110.1149986,117.0069619,136.7240908,5119.24635,,0.5 11/18/2016,12.90672311,110.9499994,117.4743025,136.9675387,5199.117,,0.5 11/21/2016,12.97075743,110.829997,117.806444,138.4657989,5419.587,,0.5 11/22/2016,13.04656973,111.1250017,118.1125613,138.0834024,5458.46,,0.5 11/23/2016,13.06361326,112.5149982,118.7366421,139.9286364,5507.60925,,0.5 11/24/2016,13.18113516,113.3400053,119.6172249,141.1333004,5553.66,,0.5 11/25/2016,13.18209081,113.0799972,119.7174668,141.0835214,5341.8992,,0.5 11/28/2016,13.11045559,111.9350025,118.8142339,138.9757487,5399.7444,,0.5 11/29/2016,13.171673,112.384995,119.6673248,140.3607271,5212.4163,,0.5 11/30/2016,13.42795566,114.4649992,121.1974306,143.1536755,5777.04855,,0.5 12/1/2016,13.54857503,114.0949996,121.6471018,143.6575205,6154.2843,,0.5 12/2/2016,13.48899635,113.5799996,121.2194678,144.571346,6185.5668,,0.5 12/5/2016,13.59859662,113.8449975,122.5415109,144.9590491,6254.6443,,0.5 12/6/2016,13.56318409,114.0149971,122.2045705,144.5504481,6148.82895,,0.5 12/7/2016,13.60322124,113.7649956,122.3316411,143.636886,6029.545,,0.5 12/8/2016,13.52246758,114.0349937,121.0507203,143.523502,6145.34615,,0.5 12/9/2016,13.57386217,115.4000035,121.8843318,145.137881,6269.682,,0.5 12/12/2016,13.6317784,115.025003,122.324159,145.8044762,6405.74225,,0.5 12/13/2016,13.67296991,115.1849998,122.406512,145.8044762,6418.1082,,0.5 12/14/2016,13.64824381,117.0450068,123.3197682,147.0588235,6308.7255,,0.5 12/15/2016,13.63354397,118.1749952,123.0693496,146.7566774,6383.8135,,0.5 12/16/2016,13.60414654,117.9899933,123.3121647,147.4491301,6514.2279,,0.5 12/19/2016,13.4801774,117.0849957,121.7952622,145.1800232,6430.3082,,0.5 12/20/2016,13.53912808,117.8800036,122.4289912,145.71949,6524.658,,0.5 12/21/2016,13.53876147,117.550004,122.5415109,145.22219,6401.773,,0.5 12/22/2016,13.48726802,117.5400006,122.6692836,144.37306,6470.577,,0.5 12/23/2016,13.4877228,117.3499977,122.7069145,144.2481067,6473.026,,0.5 12/27/2016,13.48744993,117.4250012,122.7897839,144.092219,6586.36825,,0.5 12/28/2016,13.44095054,117.2549995,122.1001221,143.3486239,6592.0761,,0.5 12/29/2016,13.48244922,116.5449956,122.2718102,142.9183936,6542.8363,,0.5 12/30/2016,13.53033501,116.8949977,122.92563,144.2377037,6641.9739,1.85,0.5 1/3/2017,13.60331377,117.7550055,122.5415109,144.1129846,6531.86985,,0.5 1/4/2017,13.65075898,117.2649957,123.00123,144.4877908,6620.7819,,0.5 1/5/2017,13.60423908,115.3549958,122.3540927,143.2664756,6562.54595,,0.5 1/6/2017,13.6980672,116.9249988,123.1602931,143.66784,6676.4175,,0.5 1/9/2017,13.58621814,116.025002,122.6843332,141.1133846,6374.4135,,0.5 1/10/2017,13.45188932,115.7700048,122.1896383,140.9741312,6209.9028,,0.5 1/11/2017,13.49609625,115.4100056,122.1299463,140.944327,6359.091,,0.5 1/12/2017,13.45107508,114.7149975,121.7359547,139.4797406,6425.18715,,0.5 1/13/2017,13.47336652,114.529997,121.9066195,139.4797406,6350.6885,,0.5 1/16/2017,13.38625366,114.2000056,121.0873645,137.5988992,6379.212,,0.5 1/17/2017,13.3336889,112.6350001,120.6709304,139.8210291,6247.86345,,0.5 1/18/2017,13.49855565,114.6649999,121.8991894,140.5678943,6182.7368,,0.5 1/19/2017,13.59776453,114.8700022,122.4964782,141.7735876,6221.3592,,0.5 1/20/2017,13.62657728,114.6250043,122.6843332,141.8439716,6360.54125,,0.5 1/23/2017,13.5021097,112.7000059,121.3224143,141.2728685,6224.421,,0.5 1/24/2017,13.62416382,113.7950042,122.1001221,142.4704374,6308.7948,,0.5 1/25/2017,13.62954886,113.2849999,121.7581882,143.1331854,6239.7378,,0.5 1/26/2017,13.73277395,114.5349948,122.3540927,144.2273022,6441.4484,,0.5 1/27/2017,13.79538682,115.080003,123.1223836,144.4877908,6389.2416,,0.5 1/30/2017,13.68344713,113.7750011,121.676705,142.0656343,6283.79325,,0.5 1/31/2017,13.67876782,112.7950026,121.8100981,141.9043565,6282.6815,,0.5 2/1/2017,13.75402305,113.2449992,121.9660934,143.3486239,6432.316,,0.5 2/2/2017,13.66979249,112.8050036,121.3592233,141.3227812,6380.2508,,0.5 2/3/2017,13.73145396,112.7049977,121.5436038,140.7360495,6402.77105,,0.5 2/6/2017,13.53912808,111.7450033,120.127335,139.3436912,6226.4314,,0.5 2/7/2017,13.5065777,112.384995,120.0624325,140.5876564,6186.79425,,0.5 2/8/2017,13.46193973,111.9350025,119.7819968,140.390285,6169.8572,,0.5 2/9/2017,13.58714113,113.2550032,120.6927765,141.5428167,6300.37565,,0.5 2/10/2017,13.53363107,113.214998,120.4674136,141.4227125,6419.2905,,0.5 2/13/2017,13.55638099,113.745003,120.5472847,142.4602892,6323.08455,,0.5 2/14/2017,13.60423908,114.2600025,120.860527,142.4704374,6395.1322,,0.5 2/15/2017,13.69047212,114.1649995,121.0287443,142.2475107,6364.69875,,0.5 2/16/2017,13.66437561,113.234997,120.867831,141.412713,6301.52775,,0.5 2/17/2017,13.53720362,112.8749961,119.8035222,140.1345291,6299.55375,,0.5 2/20/2017,13.56566801,113.0999997,120.0408139,140.934395,6353.958,,0.5 2/21/2017,13.59850416,113.6850027,119.7891711,141.7936902,6441.3921,,0.5 2/22/2017,13.54141982,113.2949981,119.5957663,141.0636197,6326.3928,,0.5 2/23/2017,13.50356832,112.5950006,119.1540066,141.3727292,6370.6251,,0.5 2/24/2017,13.39423244,112.190005,118.5044735,139.8797035,6281.5181,,0.5 2/27/2017,13.46592784,112.7049977,119.3246226,140.2229545,6303.59065,,0.5 2/28/2017,13.43517194,112.7800046,119.2890373,139.6258028,6269.4402,,0.5 3/1/2017,13.5242964,113.7350029,119.9544173,139.8210291,6410.1046,,0.5 3/2/2017,13.48590386,114.4049962,120.1995312,140.3311816,6301.4274,,0.5 3/3/2017,13.53692874,114.0149971,121.1166959,140.1836406,6373.4385,,0.5 3/6/2017,13.41255684,113.8849953,120.5109665,139.3534002,6378.69885,,0.5 3/7/2017,13.48444906,113.9850023,120.4383958,139.0627173,6374.0412,,0.5 3/8/2017,13.37738954,114.3499986,120.5400193,139.1691601,6073.1285,,0.5 3/9/2017,13.39234895,114.9449994,121.5805471,139.8503601,5998.97955,,0.5 3/10/2017,13.33884672,114.7499993,122.4589762,139.6648045,5894.7075,,0.5 3/13/2017,13.41138761,114.880005,122.3840411,140.3705783,5899.088,,0.5 3/14/2017,13.31256573,114.7449959,121.676705,139.4602887,5842.8154,,0.5 3/15/2017,13.34525509,113.379996,121.7137293,139.3631106,5874.2178,,0.5 3/16/2017,13.31673181,113.3149997,121.9958521,140.0560224,5862.9181,,0.5 3/17/2017,13.2946901,112.7149954,121.0287443,139.7038279,5834.1284,,0.5 3/20/2017,13.27836092,112.5550042,120.875136,139.091731,5810.0891,,0.5 3/21/2017,13.19583276,111.7250028,120.7802404,139.4116827,5693.506,,0.5 3/22/2017,13.13637528,111.155005,120.0264058,138.7828742,5628.8892,,0.5 3/23/2017,13.06839344,110.9450018,119.6243794,138.8985346,5609.3792,,0.5 3/24/2017,13.10487174,111.3449975,120.2356619,138.8599597,5656.326,,0.5 3/27/2017,13.03424095,110.6599995,120.2356619,138.9854065,5615.995,,0.5 3/28/2017,13.03933969,111.155005,120.1923077,138.3891503,5705.58615,,0.5 3/29/2017,13.06489333,111.0450023,119.5600191,138.0738695,5820.9789,,0.5 3/30/2017,13.07163912,111.9149965,119.4814505,139.5673412,5927.0184,,0.5 3/31/2017,12.95831957,111.3949951,118.666192,139.8503601,5884.99785,1.33,0.5 4/3/2017,12.9269948,110.8950014,118.3081928,138.475386,5890.7424,,0.5 4/4/2017,12.89341018,110.7450004,118.2033097,137.7695116,5999.05665,,0.5 4/5/2017,12.85785004,110.704996,118.049817,138.1883507,6017.9238,,0.5 4/6/2017,12.8481033,110.8150011,117.9523473,138.1788034,6082.63535,,0.5 4/7/2017,12.82881866,111.0700029,117.6193837,137.4381528,6135.5068,,0.5 4/10/2017,12.86024769,110.9349956,117.5502527,137.7220768,6210.1413,,0.5 4/11/2017,12.75079214,109.619999,116.2182579,136.9112815,6163.9326,,0.5 4/12/2017,12.75469532,109.029995,116.2925922,136.7240908,6090.4158,,0.5 4/13/2017,12.70696469,109.0949992,115.7943492,136.4070386,6097.31955,,0.5 4/17/2017,12.7260464,108.9049984,115.9151501,136.8363437,6028.9808,,0.5 4/18/2017,12.73917807,108.4250022,116.3534819,139.1982183,5951.44825,,0.5 4/19/2017,12.68753767,108.8649964,116.6044776,139.1207568,5762.22445,,0.5 4/20/2017,12.68037838,109.3200001,117.1646163,140.0854521,5792.8668,,0.5 4/21/2017,12.58059443,109.0850026,117.0275015,139.7721714,5668.0566,,0.5 4/24/2017,12.84150374,109.7650019,119.2819228,140.4395759,5663.874,,0.5 4/25/2017,12.96899114,111.0950023,121.3813194,142.6635281,5788.0495,,0.5 4/26/2017,12.93744744,111.0550037,121.0873645,142.6533524,5754.8701,,0.5 4/27/2017,12.99106215,111.265003,120.9774982,143.5750179,5723.4716,,0.5 4/28/2017,12.99511384,111.5449964,121.5509906,144.4564825,5770.22285,,0.5 5/1/2017,13.01236174,111.8399972,121.8991894,144.1129846,5761.9968,,0.5 5/2/2017,13.03670484,111.9850048,122.3990208,144.8960371,5650.7631,,0.5 5/3/2017,13.03169308,112.7550039,122.7370359,145.0852376,5726.82645,,0.5 5/4/2017,12.95991498,112.4599938,123.5330451,145.3382748,5440.8148,,0.5 5/5/2017,13.11733456,112.7249949,123.9695035,146.3271876,5534.7975,,0.5 5/8/2017,13.09766272,113.2550032,123.7240953,146.5523558,5588.0017,,0.5 5/9/2017,13.11630225,113.9850023,123.954137,147.4382602,5554.48905,,0.5 5/10/2017,13.25591877,114.2849959,124.2004595,147.8633742,5739.3927,,0.5 5/11/2017,13.24178844,113.8649994,123.6705417,146.7243783,5780.92605,,0.5 5/12/2017,13.24231449,113.3450026,123.9003841,146.113384,5762.4598,,0.5 5/15/2017,13.302914,113.7849953,124.8829223,146.713615,5896.3387,,0.5 5/16/2017,13.36541032,113.1199966,125.3604112,146.1240593,5842.648,,0.5 5/17/2017,13.18608868,110.8199993,123.6552492,143.7607821,5785.9122,,0.5 5/18/2017,13.14682373,111.4950008,123.7853562,144.1961067,5854.60245,,0.5 5/19/2017,13.28700597,111.2749945,124.7038284,145.0536699,5965.45275,,0.5 5/22/2017,13.34846159,111.2949952,125.0625313,144.6863922,5995.46165,,0.5 5/23/2017,13.34846159,111.7850008,125.015627,144.9065353,6053.15775,,0.5 5/24/2017,13.38374544,111.4999983,125.0938204,144.6549978,6016.54,,0.5 5/25/2017,13.31611116,111.8349942,125.3682693,144.7073294,5755.0291,,0.5 5/26/2017,13.29168605,111.3449975,124.5174947,142.551675,5806.64175,,0.5 5/29/2017,13.22506414,111.2600017,124.2081729,142.8673477,5817.7854,,0.5 5/30/2017,13.14639164,110.8499978,123.9848738,142.5313569,5746.464,,0.5 5/31/2017,13.13232127,110.7749952,124.5485116,142.7959446,5573.09025,,0.5 6/1/2017,13.17314786,111.3550033,124.8673285,143.4411533,5637.90365,,0.5 6/2/2017,13.12344569,110.4150058,124.5717845,142.2879909,5515.22925,,0.5 6/5/2017,13.07044315,110.4650013,124.3085338,142.5212,5464.70355,,0.5 6/6/2017,12.9428895,109.4050009,123.3806292,141.2529133,5483.3786,,0.5 6/7/2017,12.92791395,109.8150013,123.6170344,142.3183662,5277.7089,,0.5 6/8/2017,12.94967755,110.0049986,123.3654083,142.4907381,5264.8393,,0.5 6/9/2017,12.99139969,110.3449981,123.5406758,140.637086,5313.11175,,0.5 6/12/2017,12.97294492,109.935002,123.1602931,139.1401141,5308.76115,,0.5 6/13/2017,13.05644956,110.0699957,123.3806292,140.380431,5362.6104,,0.5 6/14/2017,13.00796087,109.5750035,122.9180751,139.7331098,5150.025,,0.5 6/15/2017,13.03806463,110.9349956,123.6170344,141.4827391,5205.0702,,0.5 6/16/2017,13.12465138,110.8650031,124.1387872,141.6430595,5251.67505,,0.5 6/19/2017,13.11690441,111.5250052,124.3394467,142.0555437,5231.63775,,0.5 6/20/2017,13.04325142,111.4450003,124.100273,140.775674,5128.6989,,0.5 6/21/2017,13.05304103,111.3799948,124.3781095,141.1233418,4992.0516,,0.5 6/22/2017,13.11312033,111.3299983,124.1541995,141.1831145,5034.3426,,0.5 6/23/2017,13.1728008,111.2900036,124.5717845,141.5428167,5068.1466,,0.5 6/26/2017,13.18765372,111.8450007,125.0547114,142.2778687,5125.85635,,0.5 6/27/2017,13.34409757,112.3550059,127.3966495,143.9884809,5241.36075,,0.5 6/28/2017,13.32791332,112.2999937,127.7791975,145.158949,5312.913,,0.5 6/29/2017,13.37560023,112.1799995,128.3449913,145.9214942,5319.5756,,0.5 6/30/2017,13.46320842,112.3800062,128.4026708,146.3914507,5385.2496,2.42,0.5 7/3/2017,13.54912574,113.3849968,128.8410745,146.6705779,5632.9668,,0.5 7/4/2017,13.55729993,113.2799951,128.5181853,146.3593121,5619.8208,,0.5 7/5/2017,13.49673379,113.264996,128.5760206,146.5094132,5412.93435,,0.5 7/6/2017,13.5605172,113.2199971,129.3326436,146.8644441,5447.0142,,0.5 7/7/2017,13.61581613,113.8949959,129.8532658,146.8320975,5320.03545,,0.5 7/10/2017,13.69365915,114.0400004,129.9967501,146.896805,5346.1952,,0.5 7/11/2017,13.76538282,113.9400008,130.667712,146.4021668,5414.4288,,0.5 7/12/2017,13.66008251,113.1550048,129.1322314,145.7938475,5402.0197,,0.5 7/13/2017,13.71478728,113.2799951,129.1155584,146.5845793,5485.0176,,0.5 7/14/2017,13.74853922,112.5300019,129.0655653,147.3730749,5503.8423,,0.5 7/17/2017,13.80481374,112.6350001,129.2908397,147.0480112,5453.7867,,0.5 7/18/2017,13.85626892,112.075006,129.5001295,146.1454147,5473.743,,0.5 7/19/2017,13.90462816,111.9749982,128.9407517,145.7725948,5565.1575,,0.5 7/20/2017,13.90820584,111.9099993,130.1490206,145.1694854,5517.163,,0.5 7/21/2017,13.82705124,111.1250017,129.6008294,144.4147592,5340.6675,,0.5 7/24/2017,13.87636162,111.1050003,129.3493727,144.749222,5399.703,,0.5 7/25/2017,14.03380744,111.8900023,130.318629,145.7301078,5616.878,,0.5 7/26/2017,14.08579659,111.1699942,130.4546344,145.8789205,5666.3349,,0.5 7/27/2017,13.98992725,111.2500006,129.9038711,145.3699666,5728.2625,,0.5 7/28/2017,13.9869921,110.6649959,130.055924,145.3699666,5812.1258,,0.5 7/31/2017,14.01954324,110.2550055,130.565348,145.6982589,5804.92575,,0.5 8/1/2017,13.91991871,110.3600009,130.2422506,145.7088737,5714.4408,,0.5 8/2/2017,14.02082092,110.7350058,131.2852829,146.4236035,5798.0846,,0.5 8/3/2017,13.91817505,110.0449952,130.6250408,144.5922499,5723.44045,,0.5 8/4/2017,13.92592799,110.6849985,130.3016483,144.2897338,5802.1077,,0.5 8/7/2017,13.97506848,110.7450004,130.6250408,144.3626389,5799.71565,,0.5 8/8/2017,13.86356862,110.3150045,129.6512382,143.307538,5751.8241,,0.5 8/9/2017,13.83585146,110.0849966,129.4498382,143.1639227,5801.4795,,0.5 8/10/2017,13.73013421,109.2150051,128.5677552,141.713314,5668.2585,,0.5 8/11/2017,13.76235171,109.1850027,129.0572369,142.0757264,5688.5385,,0.5 8/14/2017,13.78901429,109.6349977,129.1489087,142.1464108,5561.78355,,0.5 8/15/2017,13.90772226,110.6750024,129.8785635,142.4298533,5622.29,,0.5 8/16/2017,13.90868945,110.1949989,129.6764572,142.0656343,5539.50265,,0.5 8/17/2017,13.7501461,109.5699969,128.4604021,140.9940078,5591.3571,,0.5 8/18/2017,13.81053329,109.1950057,128.4356537,140.5975395,5756.7604,,0.5 8/21/2017,13.79776614,108.9799952,128.7581279,140.5876564,5629.9068,,0.5 8/22/2017,13.85262196,109.5699969,128.882588,140.5086413,5683.3959,,0.5 8/23/2017,13.85770904,109.0349999,128.7415513,139.5673412,5731.96995,,0.5 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4/23/2018,13.78321755,108.7099972,132.7228084,151.5495946,8121.7241,,0.5 4/24/2018,13.79405476,108.7549946,132.8285847,151.6875237,8150.0997,,0.5 ================================================ FILE: Oil Money project/data/urals crude rubaud.csv ================================================ date,urals,jpy,ttf gas,eur,cny,krw,uah,rub 2015-03-23,68.32487309999999,0.010713,29.375658,1.3889200000000002,0.2042,0.00115,0.056091370999999994,0.0216 2015-03-24,68.00812492,0.0106,30.106173960000003,1.38687,0.2046,0.00115,0.054716263,0.022000000000000002 2015-03-25,69.64945825,0.0106,29.92469,1.39835,0.2052,0.001158,0.057233907,0.0222 2015-03-26,72.99437915,0.010669,31.283325,1.39037,0.2056,0.0011560000000000001,0.054547777,0.0223 2015-03-27,70.17543859999999,0.010717,30.620716,1.40462,0.2076,0.001169,0.055082559,0.0223 2015-03-30,71.77946172,0.010835,31.386495,1.4154,0.2105,0.001179,0.055395871,0.0227 2015-03-31,70.35625082,0.010882,31.563828400000002,1.4108,0.212,0.001185,0.05613251,0.0226 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2015-10-20,63.80165289,0.011544,28.753311999999994,1.5626799999999998,0.217,0.001217,0.061983471,0.0222 2015-10-21,63.56449376,0.011493999999999999,29.091805,1.57253,0.2185,0.001217,0.062274619,0.0222 2015-10-22,63.84572697,0.011566,28.279185000000002,1.5411,0.2182,0.001227,0.062014427999999996,0.0221 2015-10-23,63.67793792,0.011496,27.634356000000004,1.5267600000000001,0.2182,0.001219,0.06097561,0.0222 2015-10-26,62.32583805,0.01141,27.458099999999998,1.52545,0.2172,0.001221,0.060835977,0.0219 2015-10-27,62.21326289,0.011394,28.118499,1.53653,0.2188,0.001224,0.06075351,0.0213 2015-10-28,65.8186929,0.011542,27.5563015,1.5351700000000001,0.2212,0.001228,0.06113844,0.022000000000000002 2015-10-29,65.39440204,0.011613,28.243669999999998,1.55185,0.2224,0.0012380000000000002,0.060503250999999994,0.022000000000000002 2015-10-30,65.97086018,0.011672,27.408694499999996,1.54198,0.2218,0.001228,0.061081535,0.0219 2015-11-02,66.16762278,0.011616,27.130224000000002,1.54149,0.2208,0.00123,0.06072478,0.022000000000000002 2015-11-03,67.74283329,0.011589,26.472803500000005,1.52581,0.2197,0.001231,0.059838575,0.0222 2015-11-05,64.99160134,0.011493999999999999,26.053218,1.52358,0.2206,0.00123,0.061590146,0.0221 2015-11-06,65.17109186,0.011498,25.265034,1.52199,0.2235,0.001232,0.063183303,0.0222 2015-11-09,64.55229176,0.011529000000000001,25.32911,1.52585,0.223,0.001225,0.06229601200000001,0.022000000000000002 2015-11-11,61.97022391,0.01152,25.4832825,1.52139,0.2224,0.0012259999999999999,0.06188048700000001,0.0216 2015-11-12,59.38815605,0.011525,24.886343999999998,1.51746,0.2204,0.00121,0.061044064,0.021 2015-11-13,58.6642346,0.011445,24.5678875,1.51187,0.2202,0.001199,0.060614564,0.021 2015-11-16,62.90868095,0.011442,25.297944,1.50583,0.2212,0.0012050000000000001,0.060315670999999994,0.0216 2015-11-17,57.58683729,0.01144,25.924956749999996,1.4963899999999999,0.2205,0.001202,0.06018844,0.0216 2015-11-18,58.40247504,0.011393,25.8969525,1.4991,0.2203,0.0012050000000000001,0.059063423,0.0217 2015-11-19,57.95107034,0.011373999999999999,26.335211999999995,1.4920799999999999,0.2178,0.001202,0.05852099,0.0215 2015-11-20,57.96380716,0.011312000000000001,25.588439999999995,1.4706,0.2164,0.001196,0.05732836,0.0213 2015-11-23,59.48275862,0.011251,25.511715,1.47894,0.2176,0.0012,0.058120133,0.0211 2015-11-24,60.02480364,0.011319,25.85393625,1.46689,0.2158,0.001202,0.057875155,0.0211 2015-11-25,60.52123552,0.011251,26.18848375,1.46509,0.2158,0.0012050000000000001,0.05846663,0.021 2015-11-27,59.30766023,0.011239,25.842375,1.4725,0.2174,0.001202,0.059085222,0.0209 2015-11-30,58.68271759,0.011321,26.787485,1.4618,0.2163,0.001193,0.058253770999999996,0.0208 2015-12-01,58.26846921,0.011239,26.278485000000003,1.45185,0.2134,0.001182,0.057216987999999996,0.0205 2015-12-02,56.60145027,0.011113,25.6701095,1.45234,0.2138,0.001176,0.058421125,0.0203 2015-12-03,57.96213050000001,0.0111,25.928957999999998,1.49017,0.2129,0.00118,0.05898379,0.0202 2015-12-08,53.61053361,0.01111,25.438108,1.50968,0.2159,0.001174,0.060568261,0.02 2015-12-10,51.43524241,0.011271,25.019622,1.50268,0.2133,0.001165,0.058371103,0.02 2015-12-11,49.96522465,0.011293000000000001,25.218269999999997,1.5283799999999998,0.2155,0.001172,0.05842259,0.0198 2015-12-14,49.17149959,0.011495,24.583337999999998,1.51749,0.2138,0.001166,0.058133112,0.0196 2015-12-15,50.04171301,0.011408,24.31568,1.51973,0.2151,0.001184,0.058120133,0.0199 2015-12-16,48.65201161,0.011425,23.3095695,1.50871,0.2136,0.001179,0.058620213,0.0196 2015-12-17,48.43596577,0.011312000000000001,23.6156295,1.5186899999999999,0.2164,0.001184,0.059896199000000004,0.0197 2015-12-18,47.71460424,0.011447,22.258887,1.51421,0.2151,0.001178,0.058807135,0.0196 2015-12-21,47.21835883,0.011507,21.67187675,1.51817,0.2146,0.001184,0.059805285,0.0195 2015-12-22,47.26368159,0.011476,21.19866,1.51419,0.2133,0.00118,0.060392482000000004,0.0194 2015-12-23,48.74205142,0.011417,21.11928,1.50852,0.2134,0.001178,0.060547415,0.0198 2015-12-24,48.67134793,0.011434,21.430356,1.50918,0.2126,0.001178,0.060167975,0.0196 2015-12-28,46.76507104,0.011431,22.0134225,1.51295,0.2126,0.00118,0.058766726,0.0191 2015-12-29,47.88925439,0.011458,23.19854,1.49668,0.2113,0.00117,0.05756578900000001,0.019 2015-12-30,46.9740634,0.011379,22.354172,1.5002799999999998,0.2114,0.001165,0.057087965,0.0187 2015-12-31,47.84518254,0.011386,21.030291000000002,1.4915100000000001,0.2112,0.001166,0.05709580000000001,0.0188 2016-01-04,49.35335836,0.011414,22.443572,1.5062799999999998,0.2129,0.001168,0.057571965,0.0192 2016-01-06,46.01244344,0.011643,23.286890250000003,1.52451,0.2157,0.001178,0.060520362,0.019 2016-01-07,45.50770108,0.011934,23.700752,1.55926,0.2163,0.001191,0.06103822,0.0191 2016-01-08,45.23227384,0.012123,22.87385925,1.56939,0.2181,0.001191,0.061556163,0.0192 2016-01-11,41.95854182,0.012268000000000001,22.353839999999998,1.55235,0.2176,0.001186,0.061043602999999995,0.0188 2016-01-12,40.79587747,0.012143000000000001,22.03177725,1.55427,0.2178,0.001183,0.061694818,0.0186 2016-01-13,40.14378145,0.012165,22.515984,1.56361,0.2187,0.001189,0.061682243,0.0188 2016-01-14,41.37437366,0.012215,21.66186925,1.55561,0.2173,0.001186,0.059413028,0.0188 2016-01-15,39.01515152,0.01213,21.639776,1.5911600000000001,0.2205,0.001201,0.059731935,0.0187 2016-01-19,38.64524533,0.012453,21.198612,1.57904,0.2193,0.001199,0.058619192,0.0184 2016-01-20,37.04400695,0.012304,20.7698605,1.57646,0.2213,0.0011970000000000001,0.059206717,0.0178 2016-01-21,39.03414774,0.012378,19.888256000000002,1.55377,0.21899999999999997,0.001187,0.057436777,0.0173 2016-01-22,42.55926878,0.012139,20.737478999999997,1.54182,0.2162,0.001192,0.05812625,0.0183 2016-01-25,39.72681524,0.012023,19.810094999999997,1.55985,0.2176,0.001198,0.057943925,0.018000000000000002 2016-01-26,41.01356174,0.012155,20.4078795,1.55193,0.2171,0.001191,0.05738758,0.0181 2016-01-27,43.47516721,0.012056,20.928240000000002,1.55024,0.2161,0.001178,0.05706560400000001,0.0182 2016-01-28,45.35573123,0.011992000000000001,21.505770000000002,1.5444,0.2144,0.001169,0.056182947000000004,0.0185 2016-01-29,46.44268775,0.011881000000000001,20.182536,1.52898,0.2148,0.001169,0.055053642,0.0187 2016-02-02,42.25031965,0.011654000000000001,20.2445955,1.55131,0.2156,0.001172,0.054837335,0.0178 2016-02-03,45.64095411,0.011842,20.44878,1.54915,0.2146,0.0011619999999999998,0.05412191400000002,0.0182 2016-02-05,44.10641007,0.011835,19.417149000000002,1.57863,0.2142,0.001172,0.054620065,0.0183 2016-02-16,41.47096048,0.012426000000000001,19.3538085,1.56711,0.2161,0.0011539999999999999,0.052453945,0.0181 2016-02-17,44.70424495,0.012325,19.2824355,1.54879,0.2148,0.001137,0.05177453,0.0185 2016-02-18,43.52382283,0.0122,18.6990695,1.55179,0.2145,0.001137,0.05295514900000002,0.0183 2016-02-19,42.37548965,0.012336,18.759560500000003,1.55681,0.2164,0.001134,0.05190263,0.0182 2016-02-22,44.48595544,0.01242,18.771399000000002,1.52613,0.2121,0.001131,0.051058531,0.0184 2016-02-23,42.3910025,0.012254000000000001,19.354753000000002,1.5300200000000002,0.212,0.001127,0.050958067,0.0182 2016-02-24,44.01056142,0.012385,19.435826,1.5303799999999999,0.2135,0.001127,0.05086159,0.0183 2016-02-25,44.637921500000004,0.012387,18.424912,1.52272,0.2124,0.001119,0.050995025,0.0184 2016-02-26,45.87426326,0.012229,18.78856,1.53376,0.2133,0.001129,0.051361212,0.0184 2016-02-29,47.59837558,0.012311,19.2597515,1.52251,0.2139,0.001131,0.052093544000000006,0.0187 2016-03-02,47.16929404,0.012426999999999999,18.847235,1.4899,0.2106,0.001119,0.051542152,0.0187 2016-03-03,46.64036997,0.012079000000000001,18.778913999999997,1.4903899999999999,0.2081,0.0011220000000000002,0.051822633,0.0186 2016-03-08,49.32114532,0.011964,18.502374999999997,1.48019,0.2066,0.001111,0.051216560999999994,0.0184 2016-03-10,50.06707808,0.011937,18.293412,1.49946,0.20600000000000002,0.001114,0.052455058,0.0188 2016-03-11,49.61004627,0.011848000000000001,18.0627475,1.47451,0.2032,0.001113,0.051817580999999995,0.019 2016-03-14,49.07518297,0.011612,18.619272000000002,1.4777200000000001,0.2049,0.001119,0.050565535999999994,0.019 2016-03-15,48.54499128,0.011691,18.474884000000003,1.48991,0.2058,0.0011220000000000002,0.049751910999999996,0.0189 2016-03-16,49.67562558,0.011847,18.504932999999998,1.48634,0.2062,0.001123,0.049119555,0.0192 2016-03-17,50.80402667,0.011761,18.348156,1.47969,0.2026,0.001132,0.049418225,0.0192 2016-03-18,51.15667718,0.011736,17.932926,1.48206,0.203,0.001129,0.049421661,0.0192 2016-03-21,51.28002111,0.01179,17.76263725,1.4833100000000001,0.2031,0.0011359999999999999,0.050145157,0.0195 2016-03-22,51.24639202,0.011788,17.955227999999998,1.47174,0.2019,0.001134,0.050118079,0.0195 2016-03-23,50.50451407,0.011678000000000001,18.0367965,1.48451,0.2038,0.0011359999999999999,0.050716940999999995,0.0194 2016-03-24,50.25239107,0.011815,17.7367875,1.48425,0.2043,0.001137,0.050743889,0.0193 2016-03-28,49.76805832,0.011767,17.7341585,1.48403,0.2036,0.001137,0.050629556,0.0193 2016-03-29,48.23652812,0.011683,17.76312,1.4802600000000001,0.2032,0.001134,0.049822997,0.0192 2016-03-30,47.81645157,0.011625,17.698570999999998,1.47796,0.2015,0.00114,0.049667579,0.0192 2016-03-31,48.09977798,0.011595000000000001,18.429376,1.48624,0.2017,0.001141,0.04988899,0.0195 2016-04-01,47.07568060000001,0.011601,17.3296695,1.48434,0.2015,0.001137,0.050019539,0.0193 2016-04-05,47.39493570000001,0.011812000000000001,17.354995,1.5091299999999999,0.205,0.001142,0.050908127000000004,0.0193 2016-04-07,49.47368421,0.012014,17.206146,1.51596,0.2062,0.0011480000000000001,0.051698867,0.0195 2016-04-08,52.06458444,0.012312,16.9749,1.50888,0.2043,0.00115,0.051614611,0.0197 2016-04-11,53.06122449,0.012251,16.781050500000003,1.50166,0.2036,0.001152,0.051612902999999995,0.0198 2016-04-13,53.86123089,0.012195000000000001,16.869055999999997,1.47328,0.2018,0.00114,0.051221743,0.0197 2016-04-14,53.28135153,0.011951,16.766234999999998,1.4643,0.2004,0.001126,0.05081221599999999,0.0197 2016-04-15,51.97411003,0.01188,16.659162000000002,1.46133,0.2004,0.001129,0.050873786,0.0195 2016-04-18,52.14193548,0.011903,17.005271999999998,1.4596799999999999,0.1992,0.001127,0.050580645,0.0195 2016-04-19,52.65583003,0.011858,17.299268,1.4537200000000001,0.1982,0.001134,0.050300780999999996,0.0194 2016-04-20,54.81139338,0.011719,17.682924,1.4494200000000002,0.1977,0.001132,0.050423403,0.0197 2016-04-21,54.17420522,0.011681,18.745323,1.45878,0.1987,0.001132,0.05091755,0.0193 2016-04-22,55.08562532,0.011806,19.218144,1.45592,0.1995,0.0011279999999999999,0.05124545900000002,0.0195 2016-04-25,54.24497732,0.011607,19.277016,1.46038,0.1995,0.001126,0.051198963,0.0195 2016-04-26,56.03303652,0.011656999999999999,21.54032475,1.45789,0.1989,0.001125,0.051232417,0.0197 2016-04-27,58.41127651,0.011595000000000001,21.362729249999997,1.49129,0.2029,0.001147,0.05243051,0.0202 2016-04-28,59.055737699999995,0.011821,19.500136,1.48856,0.2021,0.001153,0.052065574,0.0202 2016-04-29,58.77942917,0.012133,19.56981,1.50537,0.2027,0.001149,0.052347757,0.0203 2016-05-04,57.18117205,0.01226,19.487198499999998,1.54049,0.2058,0.001149,0.05337267,0.0201 2016-05-05,57.46818486,0.012534,19.554560000000002,1.5277,0.2055,0.001147,0.053181514000000006,0.0204 2016-05-09,56.27392017,0.012490000000000001,19.8381075,1.55593,0.2096,0.001163,0.054264625,0.0205 2016-05-10,58.31862013,0.012618,20.309123000000003,1.5444200000000001,0.2086,0.00116,0.05391824,0.0205 2016-05-12,62.14334471,0.012429,20.18991,1.5530700000000002,0.2093,0.001167,0.054061433,0.021 2016-05-13,62.48108926,0.012527,19.901696,1.55482,0.2105,0.001169,0.053912804,0.021 2016-05-16,64.01426808,0.01266,20.305605749999998,1.55301,0.2102,0.001165,0.054054054000000004,0.0211 2016-05-17,63.87713311,0.012583,20.312805,1.5447,0.209,0.00116,0.054061433,0.0211 2016-05-18,63.92308756,0.012506,20.12980425,1.5514299999999999,0.2099,0.0011619999999999998,0.054779361,0.021 2016-05-19,64.20863309,0.012551999999999999,20.304607,1.54997,0.2121,0.001166,0.05478694,0.0207 2016-05-20,64.09581833,0.012582,19.967101,1.55386,0.2115,0.001164,0.055247854000000006,0.0207 2016-05-23,63.51052049,0.012570999999999999,20.19277,1.55329,0.2113,0.00117,0.055094131,0.0206 2016-05-24,65.04246137,0.012674,20.316789999999997,1.5509,0.2121,0.001172,0.05540860400000002,0.021 2016-05-25,66.06001667,0.012657,20.339025,1.54964,0.2121,0.001175,0.055432064,0.0212 2016-05-26,65.31967894,0.012607,20.912445,1.5490700000000002,0.2112,0.001173,0.055078882,0.021 2016-05-27,65.84516848,0.012609,21.807342000000002,1.54662,0.2116,0.001173,0.055416319000000006,0.0211 2016-05-31,64.58390932,0.012625,22.19877675,1.53891,0.2097,0.001161,0.055156207,0.0207 2016-06-01,65.08198979999999,0.012486,22.19832,1.54155,0.2095,0.0011560000000000001,0.054981397,0.0206 2016-06-06,65.23214771,0.012579,22.895136,1.54176,0.2067,0.001167,0.054439315999999995,0.0208 2016-06-07,65.77289181,0.012623,22.8429,1.52286,0.2042,0.001159,0.053626491,0.0207 2016-06-13,64.46459997,0.012679000000000001,21.018662499999998,1.52863,0.205,0.001155,0.054419927,0.0206 2016-06-14,63.65860288,0.012737,21.513363750000003,1.5230700000000001,0.2061,0.001155,0.054498505,0.0206 2016-06-15,62.42743351,0.012809000000000001,21.583574,1.51997,0.205,0.001155,0.05400297,0.0206 2016-06-16,60.64104305,0.012734,21.761951999999997,1.5244799999999998,0.2073,0.001158,0.054597310999999996,0.0206 2016-06-17,63.57113849,0.013028,22.082481,1.52556,0.2057,0.001155,0.054419927,0.0209 2016-06-20,64.52997184,0.012981,22.903227,1.5167700000000002,0.2037,0.001155,0.053909079000000006,0.0209 2016-06-21,65.18120805,0.012903,22.144575000000003,1.5090000000000001,0.2033,0.001164,0.053959732,0.0211 2016-06-22,63.28489535,0.012811000000000001,23.193324,1.50606,0.2027,0.001161,0.053592854,0.0206 2016-06-23,63.94325496,0.012764,22.6597035,1.49569,0.2004,0.001151,0.052935768,0.0206 2016-06-24,61.63943209,0.012376,22.06330625,1.48825,0.2027,0.001141,0.053844092999999996,0.0207 2016-06-27,61.45975443,0.013084,21.197657999999997,1.50338,0.2048,0.0011560000000000001,0.05484311099999999,0.0208 2016-06-28,62.78093691,0.013378,21.196983000000003,1.4980200000000001,0.2046,0.00116,0.054427295,0.0211 2016-06-29,64.44772514,0.013175999999999998,21.499200000000002,1.493,0.2025,0.001163,0.053818279000000004,0.0211 2016-06-30,62.78351899,0.013052000000000001,20.831694,1.49064,0.20199999999999999,0.001164,0.054086699999999995,0.0209 2016-07-01,64.07041878,0.013006,21.253947,1.48629,0.2006,0.001159,0.053747666,0.0209 2016-07-06,62.12765957,0.013005000000000001,20.66652,1.4761799999999998,0.1992,0.001147,0.053590426,0.0206 2016-07-07,58.73779917,0.013125,21.434625,1.47825,0.1998,0.0011539999999999999,0.053884209,0.0207 2016-07-11,57.83324482,0.013267,20.55466,1.4681899999999999,0.1983,0.0011539999999999999,0.053372277999999995,0.0206 2016-07-12,60.1075692,0.012915000000000001,20.568066750000003,1.4510100000000001,0.1961,0.001147,0.052866326,0.0205 2016-07-13,58.26761304,0.012531,20.699908,1.45774,0.1962,0.001147,0.053101998,0.0206 2016-07-14,58.90985325,0.012581,20.762249999999998,1.4569999999999999,0.1959,0.001157,0.05293501,0.0208 2016-07-15,60.57007126,0.012439,20.56416375,1.45587,0.1969,0.001158,0.053180259,0.0208 2016-07-18,59.04360427,0.012584,20.935645499999996,1.4589299999999998,0.1964,0.00116,0.05295745,0.021 2016-07-19,59.31503198,0.012409,20.81924775,1.4687299999999999,0.1994,0.001168,0.053704691,0.021 2016-07-20,60.00267451,0.012556999999999999,21.7094925,1.47183,0.2001,0.00117,0.053891415,0.021 2016-07-21,58.54569713,0.012512,21.73683225,1.47119,0.1998,0.001173,0.053769179,0.0207 2016-07-22,58.00053605,0.012611,21.32747,1.47086,0.201,0.001179,0.054140981,0.0207 2016-07-25,56.54618474,0.012626,21.71259,1.47204,0.2007,0.001172,0.05408299900000002,0.0205 2016-07-26,56.22500666,0.012653,21.233655,1.4643899999999999,0.1994,0.001172,0.053719008,0.0202 2016-07-27,54.75904419,0.012738,21.3321015,1.47627,0.2008,0.00118,0.053797890999999994,0.0202 2016-07-28,53.72517660000001,0.012666,20.7777965,1.47622,0.2001,0.001185,0.053711849000000006,0.0199 2016-07-29,53.46234860000001,0.01266,20.148042,1.47066,0.1984,0.001184,0.053054239,0.0199 2016-08-01,52.86624204,0.012891999999999999,20.100909749999996,1.4807299999999999,0.1991,0.0011970000000000001,0.053476645,0.0198 2016-08-02,51.93849389,0.01296,20.05524,1.47465,0.1982,0.001182,0.052963595999999995,0.0197 2016-08-03,53.91407486,0.013027,19.321032,1.46928,0.1986,0.00118,0.053110174,0.0199 2016-08-04,54.62768747,0.013016999999999999,19.404567,1.45899,0.1972,0.0011769999999999999,0.05296276900000002,0.0199 2016-08-08,55.7835577,0.012952000000000002,18.44196075,1.44927,0.196,0.00118,0.052672853,0.0202 2016-08-09,55.50632087,0.012758,17.532416,1.44896,0.1958,0.001182,0.05252183,0.0201 2016-08-11,56.57877646,0.012792,17.35812,1.44651,0.1953,0.001183,0.052084686,0.0202 2016-08-12,58.69053842,0.012738,17.025068750000003,1.45825,0.196,0.001184,0.052143231,0.0202 2016-08-15,59.74719833,0.012901,16.5781525,1.4574200000000002,0.196,0.001187,0.051993745,0.0203 2016-08-16,60.61078622,0.01287,16.89138575,1.46563,0.1961,0.001186,0.052111761,0.0204 2016-08-17,62.01175702,0.012956,17.43631725,1.47453,0.1976,0.001179,0.051992162,0.0204 2016-08-18,63.29690346,0.013025,16.1747925,1.47715,0.1963,0.001174,0.051652355,0.0204 2016-08-19,63.51121017,0.013025,15.591660000000001,1.48492,0.1972,0.001175,0.051920808,0.0205 2016-08-22,61.40833989,0.013083000000000001,16.120821499999998,1.48579,0.1972,0.001167,0.051796485999999996,0.0202 2016-08-23,62.06172029,0.013068000000000001,17.1097845,1.48458,0.19699999999999998,0.001172,0.051871307,0.0203 2016-08-24,61.31616971,0.0131,16.53151275,1.47933,0.1975,0.001172,0.051884934,0.0201 2016-08-25,62.26043581,0.013075999999999999,16.442207999999997,1.48128,0.1973,0.0011769999999999999,0.051588342999999995,0.0202 2016-08-26,62.55949233,0.013058000000000002,17.316702,1.48006,0.1961,0.001178,0.051824432000000004,0.0204 2016-08-29,61.97648302,0.012985,17.738039999999998,1.47817,0.1977,0.00118,0.051790197,0.0204 2016-08-30,61.25982155,0.012962999999999999,17.211268,1.48373,0.1993,0.001189,0.051804500999999996,0.0204 2016-08-31,58.9996009,0.012934000000000001,17.4397025,1.48423,0.1992,0.001192,0.050685114,0.0203 2016-09-02,58.18037766,0.012862,17.729299250000004,1.4743700000000002,0.1983,0.001183,0.049518025,0.0202 2016-09-06,58.29322232,0.012706,17.459631,1.46412,0.1955,0.001188,0.048393390999999994,0.0202 2016-09-08,61.63810022,0.012752,16.497935999999996,1.4730299999999998,0.1953,0.001191,0.049064502999999995,0.0204 2016-09-09,60.124651899999996,0.012766,16.94545125,1.48971,0.1977,0.001196,0.049728153,0.0205 2016-09-12,60.25641026,0.012912999999999999,16.1119245,1.4849700000000001,0.1989,0.001193,0.049696008,0.0204 2016-09-13,59.64630225,0.012979,17.0602985,1.50311,0.2001,0.001188,0.051045016,0.0205 2016-09-14,58.20056232,0.013065,16.9439625,1.50613,0.2002,0.001189,0.050876958,0.0205 2016-09-19,57.81789222,0.013049000000000002,19.727092,1.48324,0.1985,0.001186,0.051499867000000005,0.0205 2016-09-20,57.95394389,0.013024,18.816705000000002,1.4758200000000001,0.1984,0.001185,0.05108523,0.0204 2016-09-21,58.63064008,0.013013999999999998,19.741103,1.46774,0.1977,0.001188,0.050629590999999995,0.0205 2016-09-22,58.9820751,0.013075999999999999,19.502322,1.46634,0.1962,0.001185,0.05037289,0.0205 2016-09-23,57.32651187,0.012983000000000001,19.582388,1.4723600000000001,0.1966,0.001189,0.050505050999999995,0.0205 2016-09-26,58.34206391,0.012988999999999999,19.232307000000002,1.47374,0.1962,0.001181,0.050550026,0.0205 2016-09-27,56.98447894,0.013052000000000001,18.720384,1.4625299999999999,0.1959,0.001189,0.050606495,0.0205 2016-09-28,59.91939678,0.012987,19.394858000000003,1.4582600000000001,0.1956,0.00119,0.050182007,0.0206 2016-09-29,60.98742797,0.012911,20.135164,1.4697200000000001,0.1955,0.001188,0.050680985,0.0208 2016-09-30,61.26043841,0.012962000000000001,19.350935999999997,1.4659799999999998,0.1956,0.001185,0.050365344000000006,0.0208 2016-10-10,63.73142626,0.012681999999999999,23.098859250000004,1.4642700000000002,0.1959,0.001186,0.050874195,0.0212 2016-10-11,66.20241411,0.012688,22.652480999999995,1.4661799999999998,0.1971,0.001179,0.051465712000000004,0.0212 2016-10-13,65.26621747,0.012813999999999999,22.639454999999998,1.46061,0.1967,0.001169,0.051261725,0.021 2016-10-14,64.93830402,0.012740000000000001,22.293285,1.4406,0.1952,0.0011560000000000001,0.050932002999999997,0.0207 2016-10-17,64.47765107,0.012598999999999999,23.215234000000002,1.44194,0.1947,0.001153,0.050989645,0.0208 2016-10-18,64.57083225,0.012618,24.028342249999998,1.43239,0.1936,0.001159,0.050873989,0.0208 2016-10-19,64.58171458,0.01256,24.15972,1.42116,0.1926,0.0011560000000000001,0.05037555,0.0208 2016-10-20,64.19299856,0.012518000000000001,24.504300000000004,1.433,0.1942,0.001158,0.051134129,0.021 2016-10-21,64.99737119,0.012612,23.739494,1.4300899999999999,0.1947,0.001157,0.05126183,0.0211 2016-10-24,64.24911313,0.012659,24.949660999999995,1.4297799999999998,0.1942,0.001157,0.051241624000000006,0.0211 2016-10-25,62.38556108,0.01261,24.993657,1.42414,0.1929,0.001157,0.051007063,0.0211 2016-10-26,62.18794929,0.012548,24.59574,1.42584,0.1929,0.0011480000000000001,0.051365835,0.0208 2016-10-27,63.49980235,0.012511,24.843146,1.43602,0.1939,0.0011480000000000001,0.051653709000000006,0.021 2016-10-28,62.46874589,0.012513,24.4905465,1.44487,0.1948,0.001147,0.051585735,0.0209 2016-10-31,59.70561178,0.012565999999999999,25.974719999999998,1.4430399999999999,0.1943,0.001149,0.051517939000000006,0.0208 2016-11-01,59.67067433,0.012537999999999999,26.583215999999997,1.44474,0.1931,0.00114,0.050967067000000005,0.0206 2016-11-02,58.33442109,0.012546999999999999,27.958752,1.44864,0.1929,0.00114,0.051168255,0.0206 2016-11-03,57.22468107,0.012638,27.321650999999996,1.44559,0.1925,0.0011380000000000001,0.050768029000000006,0.0205 2016-11-04,56.23615274,0.012639,26.270159,1.45139,0.193,0.001142,0.050957904000000005,0.0202 2016-11-07,56.6252588,0.012638,25.572118999999997,1.42861,0.1918,0.001134,0.050595238,0.0203 2016-11-08,56.10667354,0.012387,25.5699,1.42055,0.1911,0.001141,0.050373615,0.0202 2016-11-10,57.36240641,0.012251,26.183823000000004,1.4308100000000001,0.1932,0.001126,0.051359517,0.02 2016-11-11,56.924518000000006,0.012296,26.326746,1.43862,0.1945,0.0011380000000000001,0.051683010999999994,0.0201 2016-11-14,56.4866296,0.012422,25.018576000000003,1.42151,0.1933,0.001132,0.051363516,0.0201 2016-11-15,59.4919963,0.012208,25.63920675,1.41849,0.193,0.0011330000000000001,0.050403493,0.0206 2016-11-16,59.27807487,0.012115,25.152864,1.4291399999999999,0.1944,0.001142,0.051871658,0.0207 2016-11-17,59.46529841,0.012253,25.1833725,1.43495,0.1947,0.001144,0.051984877,0.0208 2016-11-18,61.20196239,0.012256999999999999,26.044525500000002,1.4429100000000001,0.1972,0.0011539999999999999,0.052739166,0.021 2016-11-21,63.73999186,0.012287000000000001,24.704525,1.4426,0.1968,0.00115,0.052788709,0.0212 2016-11-22,63.75303972,0.012247,25.1592405,1.4356200000000001,0.1967,0.001155,0.052688463,0.0212 2016-11-23,63.99458362,0.012156,25.364395,1.42898,0.1955,0.001146,0.052809749,0.0211 2016-11-25,61.49402123,0.012034999999999999,25.349645499999998,1.42214,0.1945,0.00114,0.052129518,0.0207 2016-11-28,62.4298316,0.011865,26.172062999999998,1.41854,0.1932,0.001141,0.0521251,0.0206 2016-11-29,59.99465526,0.011939,26.752964000000002,1.42303,0.19399999999999998,0.001144,0.05224478900000002,0.0205 2016-11-30,66.31008802,0.011890000000000001,26.23854,1.4338,0.1958,0.00115,0.052945159000000006,0.0211 2016-12-01,69.83142279,0.011831999999999999,26.384364,1.43784,0.1965,0.001155,0.052461227,0.0211 2016-12-02,70.36341692,0.01182,25.710002000000003,1.43032,0.1949,0.0011480000000000001,0.051629342,0.0209 2016-12-05,69.8875803,0.011814,24.994063,1.44058,0.195,0.001147,0.051525695999999996,0.021 2016-12-07,67.97647688,0.011755,23.85752,1.4372,0.1946,0.0011539999999999999,0.051590484000000006,0.0211 2016-12-08,69.44928313,0.011748999999999999,23.8243625,1.42235,0.1951,0.0011560000000000001,0.051989815999999994,0.0212 2016-12-09,70.19734193,0.011751000000000001,23.81904,1.4178,0.19399999999999998,0.001149,0.051550544000000004,0.0215 2016-12-12,71.14845938,0.011642,24.47016,1.41856,0.1932,0.001146,0.050953715,0.0219 2016-12-13,71.02666667,0.011598,24.510640000000002,1.4168,0.1934,0.001145,0.050933333,0.022000000000000002 2016-12-14,69.8352687,0.011578,24.468376,1.42258,0.1928,0.001145,0.051174723,0.0217 2016-12-15,71.01114433,0.011536,24.695937999999998,1.41524,0.1957,0.001149,0.051644469000000005,0.022000000000000002 2016-12-16,72.89156627,0.011501,25.03235,1.43042,0.1969,0.0011539999999999999,0.052163198,0.0221 2016-12-19,73.19530711,0.011609,25.555103999999996,1.4356799999999998,0.1979,0.0011619999999999998,0.052587992,0.0223 2016-12-20,73.66028379,0.011788,25.4000725,1.43099,0.1988,0.001155,0.052073287999999995,0.0224 2016-12-21,72.50621719,0.011687999999999999,25.599021750000002,1.4401700000000002,0.1985,0.001157,0.052362531,0.0226 2016-12-22,73.28529859999998,0.011755,26.175496000000003,1.4461600000000001,0.19899999999999998,0.00115,0.052930581,0.0227 2016-12-23,74.01059086,0.011788,26.9214005,1.45718,0.2008,0.00116,0.052954292,0.0226 2016-12-27,75.3375087,0.01188,27.076950000000004,1.45575,0.2,0.001153,0.052331246,0.0229 2016-12-28,75.33788491,0.011852,27.421820999999998,1.45089,0.2004,0.00115,0.05141424,0.023 2016-12-29,75.14891259,0.011881999999999998,27.752872999999997,1.4530299999999998,0.1997,0.0011480000000000001,0.051115113,0.023 2016-12-30,74.98612653,0.011885,28.172017,1.45969,0.1993,0.001149,0.051193119,0.0225 2017-01-03,74.0961352,0.011871,26.807994,1.44129,0.1992,0.0011480000000000001,0.051115113,0.0227 2017-01-05,74.73426002,0.011764,27.716312000000002,1.44544,0.1981,0.001151,0.051785227999999996,0.023 2017-01-06,75.09930147,0.01181,27.149979749999996,1.44223,0.1973,0.001139,0.050814957,0.023 2017-01-09,71.75686701,0.01171,27.969489,1.43802,0.1964,0.0011300000000000001,0.050448735,0.0226 2017-01-11,71.8451821,0.011715,29.260119,1.42212,0.1959,0.001131,0.049321328,0.0225 2017-01-12,72.7151256,0.011644,29.213478,1.41813,0.1934,0.001137,0.048904329,0.0225 2017-01-13,71.96747534,0.011648,28.784994,1.41798,0.1939,0.001135,0.048120500999999996,0.0224 2017-01-17,71.12462006,0.011642,28.528974499999997,1.41583,0.1936,0.001139,0.047839302,0.0223 2017-01-18,70.05996003,0.011734999999999999,28.57405425,1.41631,0.1932,0.001131,0.048367755,0.0224 2017-01-19,69.59396905,0.011622,29.0169225,1.4103,0.1929,0.001125,0.048009523,0.0221 2017-01-20,71.3170086,0.011514,29.749229999999997,1.4166299999999998,0.1927,0.001126,0.048312376,0.0222 2017-01-23,70.83333333,0.011544,31.937175,1.41943,0.1925,0.001132,0.048523207,0.0221 2017-01-24,70.5486679,0.011701000000000001,31.113963000000002,1.41588,0.192,0.0011279999999999999,0.048404115,0.0223 2017-01-25,70.93238246,0.011590999999999999,29.4581525,1.41967,0.1924,0.0011359999999999999,0.048335975,0.0222 2017-01-26,72.23623092,0.011658,29.132913000000006,1.4176600000000001,0.1927,0.001132,0.048706038,0.022000000000000002 2017-02-03,71.62760417,0.011576999999999999,32.580224,1.40432,0.1894,0.001143,0.047916667,0.022000000000000002 2017-02-06,70.31331593,0.011559,32.419233,1.40343,0.1908,0.00115,0.048172324,0.0222 2017-02-08,69.77109222,0.011683,28.547964,1.39941,0.1905,0.001142,0.048659254000000006,0.0222 2017-02-10,71.39692468,0.011687000000000001,27.882921000000003,1.38721,0.1896,0.001137,0.047823820999999996,0.0223 2017-02-13,70.64136126,0.011506,26.637887999999997,1.38739,0.1902,0.0011380000000000001,0.047905759000000006,0.0226 2017-02-14,70.57288268,0.011507,25.672464,1.38024,0.1903,0.001146,0.048153465,0.0229 2017-02-15,69.89623865,0.011420999999999999,25.915357000000004,1.3748200000000002,0.1894,0.001142,0.047859922,0.0227 2017-02-16,70.21055368,0.011362,26.36174,1.3874600000000001,0.1895,0.0011380000000000001,0.048219392,0.0226 2017-02-17,70.4723382,0.011475,25.274425,1.3849,0.1899,0.001134,0.048277662,0.0224 2017-02-21,71.51791531,0.011559999999999999,24.6771585,1.37286,0.1894,0.001139,0.048208469000000004,0.0227 2017-02-22,70.98533039,0.011461,24.32886,1.3706399999999999,0.1892,0.001139,0.048163053,0.0224 2017-02-23,71.25081011,0.011457,25.13328725,1.37153,0.1888,0.001144,0.048217758,0.0224 2017-02-24,70.54455446,0.01151,23.977497,1.37604,0.1895,0.001153,0.048332465,0.0221 2017-02-27,70.53303793,0.011626000000000001,23.870367,1.37979,0.1893,0.0011480000000000001,0.048221035,0.0224 2017-02-28,70.74572287,0.011564,23.205672,1.38129,0.1893,0.001149,0.048060597999999996,0.0224 2017-03-01,70.96522079,0.011581999999999999,23.493861000000003,1.37391,0.1898,0.001143,0.047935390999999994,0.0223 2017-03-02,70.43053354,0.011454,23.587329999999998,1.38749,0.1916,0.0011480000000000001,0.048864237000000005,0.0225 2017-03-03,71.05055292,0.011542,23.24557375,1.3982299999999999,0.1916,0.001143,0.048578199,0.0227 2017-03-07,70.86188719,0.011545,23.185125,1.3925,0.1909,0.001145,0.048892989000000005,0.0226 2017-03-08,68.22529224,0.011563,22.650661250000002,1.40035,0.1918,0.00115,0.049282677999999996,0.0226 2017-03-10,65.68549456,0.011614,23.1390105,1.41523,0.1919,0.001155,0.049588968,0.0225 2017-03-13,65.63201691,0.011552,22.373844,1.40716,0.1906,0.001151,0.049002774000000006,0.0225 2017-03-14,66.14631565,0.011497,22.163923999999998,1.40278,0.1912,0.001151,0.049212859000000005,0.0223 2017-03-15,65.49487612,0.01153,22.348501499999998,1.3924299999999998,0.1905,0.001149,0.048255285999999994,0.0222 2017-03-16,65.16019797,0.011441,21.874475999999998,1.40221,0.1891,0.0011539999999999999,0.048319875,0.0225 2017-03-17,64.97923157,0.011495,21.881247,1.39371,0.1881,0.001146,0.048286604000000004,0.0227 2017-03-20,64.5970767,0.01152,21.739102,1.3890799999999999,0.1874,0.001161,0.048117967000000005,0.0226 2017-03-21,63.68482642,0.011495,21.927203999999996,1.40559,0.1882,0.001158,0.048368222999999995,0.0225 2017-03-22,63.64938786,0.011639,22.14828,1.40624,0.1891,0.001166,0.048319875,0.0226 2017-03-23,63.76032516,0.011717,21.5942675,1.4137,0.1902,0.001168,0.048249639000000004,0.0228 2017-03-24,64.42345533,0.01182,21.1804125,1.41675,0.1905,0.001174,0.048406139,0.023 2017-03-27,64.29509057,0.011783,21.108648000000002,1.42626,0.1909,0.001181,0.04843791,0.0231 2017-03-28,64.70588235,0.011863,20.965680000000003,1.4166,0.19,0.001173,0.048342722000000005,0.023 2017-03-29,65.69752282,0.011787,21.1601745,1.4036600000000001,0.1894,0.001173,0.048239896,0.023 2017-03-30,66.58814291,0.011742,21.75998825,1.39711,0.1892,0.00117,0.048553854,0.0233 2017-03-31,67.28273692,0.011693,21.9928275,1.3963700000000001,0.1901,0.001173,0.04836806900000002,0.0233 2017-04-05,68.95640687,0.011937999999999999,22.855508500000003,1.40866,0.1915,0.0011710000000000002,0.048612946,0.0234 2017-04-07,71.17333333,0.011935,22.17939,1.4127,0.1929,0.001175,0.049466667,0.0233 2017-04-10,72.40367951,0.012003,22.356452249999997,1.4127299999999998,0.1931,0.001166,0.049593387999999995,0.0235 2017-04-12,71.4969423,0.012017,22.539999,1.41761,0.1936,0.0011710000000000002,0.049454932,0.0235 2017-04-13,71.39270613,0.012195000000000001,22.577835,1.40235,0.1913,0.001163,0.049154334,0.0235 2017-04-17,71.02385031,0.012112000000000001,22.4042985,1.40246,0.1911,0.001163,0.049150085999999996,0.0236 2017-04-18,70.22486772,0.012098000000000001,23.277503999999997,1.41936,0.1925,0.001158,0.049338624000000005,0.0235 2017-04-19,68.46738695,0.012199,23.216862499999998,1.4287299999999998,0.1935,0.001166,0.049886621,0.0236 2017-04-20,68.10150126,0.012254000000000001,22.9961465,1.42391,0.1926,0.001167,0.049687790999999995,0.0236 2017-04-21,66.76833311,0.012153,23.652553750000003,1.4227100000000001,0.1929,0.001168,0.049595544000000005,0.0234 2017-04-24,65.63201691,0.012154,23.579073,1.43556,0.1921,0.001164,0.049531106,0.0237 2017-04-25,66.30391506,0.012034,23.451808999999997,1.4498799999999998,0.1926,0.001176,0.049900464000000005,0.0236 2017-04-26,66.40353225,0.011945,23.9964375,1.45875,0.1943,0.001181,0.050307733,0.0234 2017-04-27,66.45679839,0.012048,23.70730425,1.4566700000000001,0.1946,0.001184,0.050502344000000005,0.0235 2017-04-28,66.17254274,0.012039,23.717967,1.45509,0.1941,0.001174,0.050347222000000004,0.0234 2017-05-04,63.22040761,0.011881999999999998,23.98283425,1.48271,0.1962,0.001189,0.051019031,0.0231 2017-05-05,64.70905172,0.012001999999999999,23.59623175,1.48171,0.1955,0.001186,0.05078125,0.0232 2017-05-09,64.83321988,0.011956,23.57871425,1.48061,0.1969,0.001196,0.051327434000000005,0.0233 2017-05-10,66.41780915,0.011945,23.565201749999996,1.4751299999999998,0.1962,0.0012,0.051309895,0.0236 2017-05-12,67.33450657,0.011877,23.3117325,1.48011,0.1959,0.0012,0.05117097599999999,0.0237 2017-05-15,68.28544449,0.011943,22.94775,1.4805,0.1954,0.001206,0.050991500999999995,0.0239 2017-05-16,67.14247239,0.011855,23.20682,1.4924,0.1954,0.001207,0.050902235,0.0238 2017-05-17,68.36652314,0.011903,23.385551,1.50148,0.1958,0.001198,0.050995694,0.0236 2017-05-18,69.07939075,0.012140999999999999,23.5700325,1.49651,0.1953,0.001194,0.051085052,0.0234 2017-05-19,70.30433034,0.012089,23.3534565,1.50183,0.1949,0.001199,0.050811101,0.0237 2017-05-22,69.81409656,0.012055,22.7696925,1.50295,0.1942,0.001198,0.050822522,0.0236 2017-05-23,70.40652581,0.012019,23.479664000000003,1.4955200000000002,0.1937,0.001188,0.050949452,0.0237 2017-05-24,69.69212315,0.011963,22.687687250000003,1.4950700000000001,0.1943,0.001191,0.050779687999999996,0.0236 2017-05-25,66.91709149,0.011951999999999999,22.7830245,1.50383,0.1951,0.0011970000000000001,0.05097934,0.0236 2017-05-26,68.25993555,0.011994,22.598779,1.50158,0.196,0.0012,0.051020407999999996,0.0238 2017-05-31,66.32570659,0.012085,23.001247999999997,1.51324,0.1973,0.001202,0.051144010999999996,0.0238 2017-06-01,66.30051532,0.012149,23.22579025,1.52051,0.1988,0.001209,0.051668023,0.024 2017-06-02,65.26938063,0.012175,22.274763,1.51529,0.1974,0.001201,0.051189037,0.0237 2017-06-06,64.72155609,0.012167,22.15804,1.50224,0.1958,0.001191,0.050759392,0.0236 2017-06-07,61.94197907,0.012177,22.369799999999998,1.49132,0.1948,0.001178,0.050602729000000006,0.0232 2017-06-09,62.1628803,0.01206,22.535473500000002,1.48749,0.1952,0.00118,0.050750631,0.0232 2017-06-12,62.00769129,0.012042,22.357979,1.48558,0.1952,0.001172,0.050921628,0.0233 2017-06-13,62.08040334,0.01206,22.421951999999997,1.48736,0.1951,0.0011769999999999999,0.050948652999999997,0.0233 2017-06-14,59.93408042,0.012055,22.256843000000003,1.47886,0.1933,0.0011769999999999999,0.050626236,0.0229 2017-06-15,59.84958438,0.012025,21.616790999999996,1.47053,0.1937,0.001167,0.050666315,0.0228 2017-06-16,60.14958667,0.011892,22.113266000000003,1.4693200000000002,0.1926,0.001158,0.050387088,0.0229 2017-06-19,59.84210526,0.011838,22.660669499999997,1.46671,0.1929,0.001158,0.050526315999999995,0.0225 2017-06-20,58.60158311,0.011798000000000001,22.473558,1.46886,0.1933,0.0011560000000000001,0.050659631,0.0221 2017-06-21,57.52681054,0.011838,22.51305525,1.47869,0.1939,0.001158,0.050840725999999996,0.022000000000000002 2017-06-22,58.40625829,0.011886,22.585615,1.4786,0.1939,0.001164,0.050914877000000004,0.0221 2017-06-23,58.66807611,0.011909000000000001,22.36790875,1.4788700000000001,0.1931,0.001164,0.050739957999999995,0.0222 2017-06-26,58.89255109,0.011876000000000001,22.702371999999997,1.4741799999999998,0.1926,0.001163,0.050626236,0.0224 2017-06-27,59.4092048,0.011784000000000001,22.803935,1.49534,0.1935,0.0011560000000000001,0.050639589000000006,0.0222 2017-06-28,60.41884817,0.011738,22.935066,1.48929,0.193,0.001149,0.05026178,0.0221 2017-06-29,59.80736691,0.011656999999999999,22.261148,1.48904,0.1919,0.001134,0.049850319000000004,0.0219 2017-06-30,61.65951359,0.011603,22.881936,1.48584,0.1922,0.001135,0.050071530999999996,0.0222 2017-07-03,62.9160684,0.011572,22.697856000000005,1.4835200000000002,0.1922,0.001135,0.050254535999999995,0.022000000000000002 2017-07-06,61.36303717,0.011512999999999999,22.700538,1.50584,0.1939,0.001139,0.050619562,0.0219 2017-07-07,60.04473096,0.011645,22.655889,1.50039,0.1934,0.00114,0.050519668,0.0218 2017-07-11,61.22021472,0.011547,22.632549749999995,1.5013299999999998,0.1932,0.001139,0.05053679,0.0215 2017-07-12,60.38030737,0.01149,21.997092,1.48629,0.192,0.001144,0.050273509,0.0217 2017-07-13,60.87181477,0.01151,22.186559499999998,1.47419,0.1908,0.001137,0.049799508,0.0217 2017-07-14,60.94228805,0.011419,22.262375999999996,1.4646299999999999,0.1889,0.001131,0.049029622,0.0216 2017-07-17,60.4025125,0.011354000000000001,21.95960025,1.47133,0.18899999999999997,0.0011359999999999999,0.049352647,0.0216 2017-07-18,59.95452249,0.011385,21.820272499999998,1.45955,0.1871,0.001123,0.048762001,0.0213 2017-07-19,60.78973843,0.011271999999999999,21.939018,1.44812,0.1864,0.001118,0.048415493,0.0213 2017-07-20,60.39205831,0.011233,22.069254,1.46154,0.1859,0.001121,0.048504649000000004,0.0213 2017-07-21,59.01970692,0.01123,22.0253865,1.47327,0.1867,0.001129,0.048762001,0.0213 2017-07-24,59.95709238,0.011367,22.0027675,1.4693,0.1869,0.001131,0.048965169,0.021 2017-07-25,62.3661333,0.011359000000000001,22.231413000000003,1.4674200000000002,0.1864,0.001125,0.048758977,0.021 2017-07-26,62.1361649,0.011261,22.500644,1.46584,0.187,0.001123,0.048344785,0.021 2017-07-27,63.21074432,0.011236,22.130107,1.46557,0.18600000000000005,0.001123,0.048449856,0.0211 2017-07-28,64.4672593,0.011281999999999999,22.0713,1.4714200000000002,0.1858,0.001113,0.048328534000000006,0.021 2017-07-31,64.65075597,0.011315,22.492351999999997,1.47976,0.1863,0.001116,0.048481819,0.0209 2017-08-02,64.0311245,0.011333,22.50312625,1.48781,0.1864,0.001118,0.048318272999999995,0.0207 2017-08-03,63.74842767,0.011333,22.54732,1.4932,0.1874,0.001114,0.04855345900000002,0.0208 2017-08-08,64.07632044,0.011434,23.051054250000004,1.4847700000000001,0.1887,0.001119,0.049153399,0.0211 2017-08-09,65.31440162,0.011453,23.778738499999996,1.4908299999999999,0.1903,0.001113,0.049315415999999994,0.0211 2017-08-11,64.41601216,0.011521,24.15283125,1.49785,0.1906,0.001108,0.049404610999999994,0.0212 2017-08-14,62.90117168,0.011603,23.6308275,1.50037,0.1906,0.001118,0.049668874,0.0213 2017-08-15,63.57243319,0.011618,23.7808645,1.50037,0.1913,0.001125,0.049993607,0.0214 2017-08-16,61.99369085,0.011553,24.201914000000002,1.48478,0.1896,0.001111,0.04933753900000002,0.0213 2017-08-17,63.08180089,0.011451000000000001,23.9711025,1.48658,0.1891,0.0011099999999999999,0.049714648,0.0214 2017-08-18,65.12801110000001,0.011574,24.360410249999997,1.4831299999999998,0.1895,0.0011070000000000001,0.049564888,0.0214 2017-08-21,63.48406600000001,0.011545999999999999,24.146369500000002,1.48822,0.1889,0.001106,0.049376496,0.0213 2017-08-22,63.67083807,0.011556,24.454899,1.48662,0.1895,0.001117,0.049677664,0.0214 2017-08-23,64.77732794,0.011535,24.75956925,1.49379,0.19,0.001123,0.049468622999999996,0.0214 2017-08-24,64.18722328,0.011603,24.812313749999998,1.49247,0.1899,0.0011220000000000002,0.049462365999999994,0.0214 2017-08-25,64.2713061,0.011551,24.585658500000005,1.50371,0.1897,0.001124,0.049293999000000005,0.0215 2017-08-28,63.48110009,0.011525,24.82095,1.5043,0.1899,0.001123,0.049353259000000003,0.0215 2017-08-29,63.65237077,0.011493000000000001,25.070570999999994,1.5057399999999999,0.1903,0.001118,0.049427745,0.0214 2017-08-30,62.78304870000001,0.011458,24.916866,1.50328,0.1921,0.001125,0.049462365999999994,0.0216 2017-08-31,65.26991317,0.011479999999999999,24.615326250000003,1.49865,0.1915,0.001119,0.049075123,0.0217 2017-09-01,64.55172414,0.011444,24.419211750000002,1.48671,0.1912,0.001118,0.048652037999999995,0.0218 2017-09-05,64.96998499,0.01138,25.032168000000002,1.49001,0.1908,0.001104,0.048274137,0.0217 2017-09-06,66.0875,0.011493999999999999,25.32286,1.48958,0.1917,0.001104,0.048125,0.0218 2017-09-08,65.39702233,0.011443,25.23508,1.4932,0.1909,0.001097,0.04764268,0.0217 2017-09-11,65.774069,0.011507,25.904075999999996,1.48874,0.1908,0.001102,0.047826627999999996,0.0218 2017-09-13,67.44302529,0.011384,26.383839750000003,1.48851,0.1915,0.001106,0.047958928,0.0216 2017-09-14,67.75765147,0.011334,26.726114,1.48892,0.1912,0.001101,0.047720175,0.0217 2017-09-15,67.94551362,0.011332,26.568814,1.49263,0.1907,0.001103,0.047738065,0.0217 2017-09-18,68.14526263,0.011276000000000001,27.384338250000006,1.5025700000000002,0.1907,0.001112,0.04812767,0.0216 2017-09-19,67.7278402,0.011259,26.614862999999996,1.49732,0.1898,0.001104,0.047815231,0.0215 2017-09-20,68.74610883,0.011189,25.766963999999998,1.48086,0.1886,0.0011,0.047565683,0.0214 2017-09-21,69.99621642,0.011097,25.827556999999995,1.5059799999999999,0.1912,0.001113,0.048051457,0.0218 2017-09-22,70.25872896,0.011207,25.377884999999996,1.50165,0.1903,0.001108,0.047726702,0.0218 2017-09-25,73.55423964,0.011215000000000001,26.460589000000002,1.49284,0.1899,0.0011099999999999999,0.047877032,0.0219 2017-09-26,73.25640375,0.011276999999999999,26.619188,1.49546,0.1911,0.001114,0.048059853,0.0219 2017-09-27,72.45508982,0.011297,26.334880000000002,1.4963,0.1913,0.001112,0.04815900099999999,0.0219 2017-09-28,72.19959267,0.011292,26.294159499999996,1.5003799999999998,0.1916,0.0011099999999999999,0.047988798,0.022000000000000002 2017-09-29,71.40668879,0.011329,23.7546225,1.50823,0.1916,0.001115,0.047995915,0.0222 2017-10-10,71.5865261,0.011371,26.6442345,1.51819,0.1953,0.001132,0.048341475999999994,0.0222 2017-10-11,71.55880842,0.011434,26.645149999999997,1.5225799999999998,0.1951,0.0011330000000000001,0.048279404000000005,0.0222 2017-10-13,71.40864714,0.011413,24.434515,1.49905,0.1928,0.001125,0.047800178,0.0221 2017-10-16,72.80601197,0.011336,23.742028,1.50266,0.193,0.001129,0.048019360999999997,0.0223 2017-10-17,72.91613561,0.011353,24.745215,1.49971,0.1928,0.001127,0.048177415,0.0222 2017-10-18,73.2857507,0.011359999999999999,25.238136,1.50227,0.1927,0.001125,0.048177415,0.0222 2017-10-19,71.78217822,0.011285,25.576159999999998,1.5044799999999998,0.1919,0.001124,0.047854785,0.0222 2017-10-20,73.08430344,0.011278,24.652530000000002,1.5078,0.1932,0.0011300000000000001,0.048228220999999995,0.0222 2017-10-23,72.43499424,0.011269,25.69736275,1.5049700000000001,0.1931,0.0011330000000000001,0.048161906,0.0223 2017-10-24,74.29269547,0.011293000000000001,24.803688,1.51242,0.1938,0.001137,0.048225309,0.0223 2017-10-25,74.97403946,0.011289,25.915643,1.53347,0.1956,0.001151,0.048416407,0.0225 2017-10-26,76.72323759999998,0.011413,26.008929000000002,1.52099,0.196,0.0011560000000000001,0.048694517,0.0226 2017-10-27,78.02527029,0.011452,25.97014575,1.51209,0.1962,0.001157,0.048586687999999996,0.0224 2017-10-30,78.22580645,0.011458,27.239135250000004,1.51539,0.1963,0.0011560000000000001,0.04851717,0.0224 2017-10-31,79.23197492,0.011493000000000001,27.6459925,1.5211,0.1969,0.001168,0.048589342,0.0224 2017-11-01,77.68368942,0.011493999999999999,27.62612,1.51376,0.1972,0.001172,0.048462741,0.0225 2017-11-07,82.04054938,0.01141,29.135872000000003,1.51552,0.1973,0.001174,0.048920862999999995,0.022000000000000002 2017-11-08,81.53164887,0.011475,29.221402500000003,1.51015,0.1966,0.001169,0.048971086,0.022000000000000002 2017-11-09,82.109375,0.011441,29.559269999999998,1.51586,0.1966,0.001165,0.049088542,0.022000000000000002 2017-11-10,81.73867641,0.011476,30.151242,1.5227899999999999,0.1961,0.001164,0.049210286,0.022000000000000002 2017-11-13,81.43775417,0.011498999999999999,30.573934750000003,1.53061,0.1971,0.001172,0.049455595,0.0221 2017-11-14,79.34739877,0.011544,30.070477999999998,1.5460399999999999,0.1978,0.001174,0.049534792,0.0217 2017-11-15,80.30043484,0.011549,29.948724,1.55376,0.19899999999999998,0.001192,0.049808934000000006,0.0219 2017-11-16,79.69161834,0.011674,29.784575999999998,1.55128,0.1986,0.001199,0.049815498,0.0221 2017-11-17,81.84822845,0.011658,29.464344,1.5589600000000001,0.2,0.001207,0.049841354000000004,0.0224 2017-11-20,81.29801325,0.01179,30.147018,1.55397,0.1996,0.001206,0.050066225,0.0223 2017-11-21,81.92135128,0.011761,30.475001000000002,1.54892,0.19899999999999998,0.001209,0.049881235,0.0223 2017-11-22,82.27648681,0.011736,30.264975,1.55205,0.1993,0.001209,0.049231980999999994,0.0225 2017-11-27,82.93870034,0.011805,32.711635,1.56515,0.1991,0.0012050000000000001,0.049066035,0.0225 2017-11-28,82.5674786,0.011839,32.152725000000004,1.55892,0.19899999999999998,0.001215,0.048979592,0.0225 2017-11-29,82.37780713,0.01181,32.86878,1.56518,0.1997,0.001221,0.048877147,0.0225 2017-11-30,82.48744383,0.011801,32.488231999999996,1.57328,0.1994,0.001215,0.048902987,0.0226 2017-12-01,82.62183108,0.011744,32.4204225,1.56243,0.19899999999999998,0.001213,0.048601077,0.0223 2017-12-04,81.20558042,0.011703,33.6919515,1.56162,0.1989,0.0012109999999999998,0.048302185,0.0224 2017-12-05,81.37242014,0.011708,33.38482025,1.55459,0.1983,0.001209,0.048507953,0.0224 2017-12-06,80.03701745,0.011675,33.061824,1.55952,0.1998,0.001209,0.048783712,0.0223 2017-12-07,81.70682998,0.011774,33.972961500000004,1.56738,0.2009,0.001218,0.049127946,0.0225 2017-12-12,83.328923,0.011772,35.8097885,1.5535700000000001,0.2,0.0012109999999999998,0.04869013,0.0223 2017-12-13,81.00039282,0.011651,33.25425225,1.54851,0.1986,0.001207,0.048055519000000005,0.0224 2017-12-14,81.68536394,0.011635,33.8008,1.5364,0.1976,0.001198,0.04748239,0.0222 2017-12-15,81.74208737,0.011606,33.037115,1.53661,0.1974,0.001201,0.04721423,0.0222 2017-12-18,81.7980167,0.011615,33.63084375,1.53741,0.1971,0.001201,0.04697286,0.0222 2017-12-19,82.35677933,0.011590999999999999,31.5962725,1.54505,0.1978,0.001202,0.046717996,0.0222 2017-12-20,83.04421547,0.011559999999999999,31.704309000000002,1.54844,0.1984,0.001207,0.046824051,0.0222 2017-12-21,82.96546352,0.011503,31.6796745,1.54159,0.1975,0.001202,0.046481432999999996,0.0222 2017-12-22,83.27928395,0.011458,30.476556000000002,1.53922,0.1971,0.001204,0.046439227,0.0222 2017-12-26,85.30020704,0.011448999999999999,30.807697249999997,1.53463,0.1978,0.001202,0.046454450999999994,0.0224 2017-12-27,84.87384140000002,0.011427,30.264450999999998,1.53044,0.1962,0.0011970000000000001,0.045957775,0.0223 2017-12-28,84.75750577,0.011355,30.800034000000004,1.53234,0.1965,0.001199,0.04567616099999999,0.0223 2017-12-29,85.14534511,0.011366,29.668346000000003,1.53722,0.1968,0.0012,0.045588424,0.0222 2018-01-02,84.0357599,0.011367,30.262178999999996,1.54006,0.1969,0.001201,0.045466155999999994,0.0222 2018-01-03,85.71975498,0.011373999999999999,29.710787500000002,1.53346,0.1965,0.001199,0.045814191,0.0223 2018-01-05,85.24923703,0.011343,28.835410500000002,1.52973,0.1963,0.0011970000000000001,0.045015259,0.0224 2018-01-08,85.6669217,0.011251,29.376655,1.52606,0.1964,0.001193,0.045141546,0.0223 2018-01-16,86.03190554,0.011276000000000001,29.53237625,1.54015,0.1953,0.00118,0.043838714,0.0222 2018-01-17,86.0727729,0.011373000000000001,28.629963250000007,1.5289700000000002,0.1949,0.001175,0.04366373900000002,0.0221 2018-01-18,85.28933883,0.011275,28.639887500000004,1.5295,0.1948,0.001167,0.043369579000000005,0.0221 2018-01-19,84.91557223,0.01125,27.893665000000002,1.5284200000000001,0.1949,0.001172,0.043277048,0.0221 2018-01-22,85.13159536,0.011290000000000001,28.33417275,1.5295100000000001,0.1947,0.001167,0.043158289,0.0221 2018-01-23,86.1375,0.011245999999999999,27.516595999999996,1.53724,0.1953,0.001164,0.043375,0.0222 2018-01-24,86.35574299,0.011332,27.323285,1.53934,0.1947,0.001165,0.043041429000000006,0.0221 2018-01-25,85.93321704,0.011356,27.382289000000004,1.54484,0.1954,0.001168,0.043483678,0.0223 2018-01-26,85.30209618,0.011389,26.81805,1.53246,0.1954,0.001158,0.043279900999999996,0.0219 2018-01-29,84.2846553,0.011356,26.770975,1.52977,0.1948,0.0011539999999999999,0.043736101,0.0219 2018-01-30,82.71681306,0.011339,26.6626325,1.53454,0.1955,0.001153,0.044290486,0.0219 2018-01-31,84.00993172,0.011373000000000001,28.08527175,1.54103,0.1961,0.00116,0.044692737,0.0221 2018-02-01,84.97325538,0.01137,28.243033499999996,1.55609,0.1982,0.0011619999999999998,0.044657296,0.0222 2018-02-02,84.30210566,0.01137,28.408839,1.57172,0.2,0.001157,0.045265414000000004,0.0223 2018-02-05,83.13023609999998,0.011455,27.905150250000002,1.5699100000000001,0.2002,0.001159,0.045823813,0.0221 2018-02-07,81.56717372,0.011633,28.9647355,1.56778,0.2024,0.001173,0.047168605,0.0221 2018-02-08,80.67086493,0.011692000000000001,28.568462999999998,1.57402,0.2027,0.0011710000000000002,0.04742321,0.022000000000000002 2018-02-13,77.40170505,0.011819,29.072565,1.57149,0.2008,0.001172,0.047588752000000005,0.0221 2018-02-14,78.89225334,0.011801,28.62728325,1.57077,0.2009,0.001178,0.047312642,0.0222 2018-02-22,81.92709661,0.011889,35.674866,1.57158,0.2004,0.001179,0.047157787,0.0226 2018-02-23,83.08045391,0.011940000000000001,41.420130500000006,1.56746,0.2019,0.001185,0.047303328,0.0227 2018-02-26,83.33545512,0.011933,42.4162935,1.56807,0.2021,0.001189,0.047103756,0.0229 2018-02-27,82.53947875,0.011906,59.678239999999995,1.5704799999999999,0.2023,0.001187,0.047631275,0.0228 2018-02-28,80.59778408,0.011961,84.044755,1.57093,0.2026,0.001187,0.048054625,0.0229 2018-03-01,80.59566787,0.012077,159.69499174999999,1.5815299999999999,0.2032,0.001191,0.048349665,0.0227 2018-03-05,82.07340631,0.012137,31.134992000000004,1.5885200000000002,0.2034,0.001194,0.048679974,0.0228 2018-03-07,79.76996805,0.012125,29.4219695,1.58609,0.2024,0.001198,0.049073482,0.0225 2018-03-08,79.23995378,0.012048,30.465293999999997,1.58056,0.2023,0.001196,0.04917190900000002,0.0225 2018-03-09,80.72412035,0.012091,31.1472305,1.56913,0.2014,0.001196,0.048827129000000004,0.0225 2018-03-13,79.41475827,0.01193,39.80309,1.57636,0.2006,0.001193,0.049109415,0.0223 2018-03-14,79.43379459,0.011937999999999999,35.561406,1.5700399999999999,0.2011,0.001193,0.048622572,0.0222 2018-03-15,80.40523211,0.011939,39.919605,1.57785,0.2021,0.001199,0.048730444000000005,0.0223 2018-03-16,83.05458317,0.012059,33.134816,1.59302,0.2042,0.0012109999999999998,0.049137819000000006,0.0226 2018-03-19,83.15625809999997,0.012231,33.1636875,1.59825,0.205,0.001207,0.049105986,0.0224 2018-03-20,85.34426656,0.012212,34.9727155,1.5932899999999999,0.2051,0.001214,0.049459845999999995,0.0226 2018-03-21,87.45653574,0.012217,34.637147999999996,1.58886,0.2052,0.00121,0.04893754,0.0226 2018-03-22,86.96217340000004,0.012143000000000001,32.662026000000004,1.59912,0.2049,0.001202,0.049525543,0.0227 2018-03-23,88.88167294,0.012347,30.969938,1.60466,0.2048,0.001199,0.049486946,0.0227 2018-03-26,87.66133196,0.012403,29.272812750000003,1.60619,0.2064,0.0012,0.04917398,0.0226 2018-03-27,87.5504623,0.012245,30.082355,1.61516,0.2065,0.0012109999999999998,0.04948561,0.0227 2018-03-28,87.62725137,0.012362999999999999,30.283656,1.60656,0.2068,0.0012259999999999999,0.049334377,0.0226 2018-03-29,88.57775462,0.012216,31.1610395,1.6021100000000001,0.2073,0.0012259999999999999,0.049231570999999995,0.0227 2018-04-04,86.34007258,0.012239,30.391729,1.5911899999999999,0.20600000000000002,0.001225,0.049377915999999994,0.0226 2018-04-09,87.00792517,0.012187,31.292316500000002,1.60063,0.2059,0.001214,0.049889567,0.0214 2018-04-13,90.97114889,0.012165,31.836392500000002,1.58785,0.2051,0.001201,0.049330242,0.0208 2018-04-16,89.39724971,0.011996,31.02567,1.5910600000000001,0.205,0.0012,0.049222465,0.021 2018-04-17,89.60855009,0.011998,30.225846750000002,1.59293,0.2049,0.001206,0.049317538,0.0209 2018-04-18,92.17625899,0.012031,30.20354,1.58966,0.2047,0.001206,0.049203494,0.0211 2018-04-19,92.5614489,0.01198,31.782090999999994,1.59709,0.205,0.001212,0.049288486,0.0212 2018-04-20,93.28727842,0.01205,32.270628,1.60152,0.2069,0.001217,0.049791449,0.0212 2018-04-23,95.7790927,0.012109,31.989189000000003,1.60548,0.2079,0.001216,0.050361604000000004,0.0213 2018-04-24,94.23987375,0.012097,31.65333675,1.60881,0.2086,0.001221,0.050236718,0.0214 2018-04-25,94.80502313,0.012086,32.27196775,1.6075700000000002,0.2089,0.001222,0.050363516,0.0212 2018-04-26,95.55202542,0.012081,32.60497350000001,1.6022100000000001,0.2089,0.001228,0.050569235,0.0211 2018-04-27,94.71046036,0.012111,32.564273500000006,1.6002100000000001,0.2087,0.001235,0.050257222000000004,0.0211 2018-05-02,95.11544108,0.012152,32.97393725,1.59487,0.2094,0.001236,0.050980915999999994,0.0208 2018-05-03,95.4062666,0.012152,32.153147999999995,1.59174,0.2096,0.001234,0.050584174,0.0211 2018-05-04,96.97572622,0.012159,32.40814325,1.58669,0.209,0.001235,0.050404563,0.0212 2018-05-07,97.93800718,0.012158,32.194785,1.58595,0.2088,0.001231,0.050685114,0.0211 2018-05-09,101.5275358,0.012195000000000001,33.310607250000004,1.5881100000000001,0.2107,0.001242,0.051051856,0.0213 2018-05-14,102.0728142,0.012211,34.466137499999995,1.58465,0.2091,0.001241,0.050757374,0.0215 2018-05-15,102.4357602,0.012116,33.9834495,1.58431,0.2098,0.0012380000000000002,0.051124197,0.0215 2018-05-16,103.4060671,0.012129000000000001,34.092002,1.5710600000000001,0.2092,0.001235,0.050691857,0.0216 2018-05-17,103.8210624,0.012054,35.094640500000004,1.57023,0.209,0.00123,0.050858741,0.0214 2018-05-18,102.92903740000001,0.012019,35.263125,1.56725,0.2087,0.001232,0.050991879000000004,0.0214 2018-05-21,103.07306779999999,0.012020999999999999,34.526772,1.55526,0.2072,0.001224,0.050514376,0.0214 2018-05-22,103.062302,0.011877,35.606065,1.55485,0.207,0.0012259999999999999,0.050686378,0.0216 2018-05-23,103.7566138,0.011902,35.118489000000004,1.5470700000000002,0.2075,0.001228,0.050793650999999995,0.0216 2018-05-24,102.3627244,0.012018000000000001,35.15489325000001,1.5469700000000002,0.2072,0.00122,0.050554382,0.0214 2018-05-25,99.48330684,0.01208,33.922148250000006,1.54367,0.2071,0.001228,0.050609432999999995,0.0214 2018-05-29,98.86742172,0.012112000000000001,34.979034999999996,1.53754,0.2073,0.0012289999999999998,0.051032645,0.0212 2018-05-30,100.660066,0.01225,35.41977,1.53999,0.2061,0.001225,0.05056105599999999,0.0212 2018-05-31,99.76215645,0.012119,34.3371805,1.54498,0.2063,0.0012230000000000001,0.050607822000000004,0.0212 2018-06-04,96.875,0.012143000000000001,33.881083,1.52962,0.2042,0.001221,0.050078452,0.0211 2018-06-06,96.92187296,0.011907,33.0911025,1.53555,0.2041,0.001222,0.04982392099999999,0.0211 2018-06-07,99.61962225,0.011837,33.93617275,1.5478299999999998,0.2048,0.0012230000000000001,0.050104932000000005,0.021 2018-06-08,98.65807131,0.011956999999999999,33.3254355,1.5482200000000002,0.2054,0.001225,0.050388107,0.0211 2018-06-13,99.08946952,0.012014,35.165148,1.55598,0.2057,0.001215,0.05054104,0.0211 2018-06-14,99.83952929,0.011958,35.2315585,1.54694,0.2074,0.001228,0.051083177,0.0214 2018-06-15,96.35850578,0.012086,33.81408375,1.56005,0.2084,0.001218,0.05092717,0.0213 2018-06-19,99.8374204,0.012184,34.190234,1.57016,0.2091,0.001218,0.051212573,0.0212 2018-06-20,98.83279045,0.012308,34.35753125,1.57063,0.2095,0.001222,0.051302932,0.0213 2018-06-21,97.04567015,0.012299,34.402375,1.5726799999999999,0.2089,0.00122,0.051497493,0.0213 2018-06-22,99.55645161,0.012322,33.827760000000005,1.5661,0.207,0.001209,0.051209677,0.0213 2018-06-25,98.65120043,0.012222,34.096896,1.57856,0.2064,0.001209,0.051524144,0.0214 2018-06-26,101.2577766,0.012287000000000001,33.90940875,1.57535,0.2055,0.001209,0.051528265999999996,0.0214 2018-06-27,102.7792916,0.012293,34.430156249999996,1.57395,0.2053,0.001213,0.051771117,0.0216 2018-06-28,103.0331882,0.012355,34.303826,1.5735700000000001,0.2052,0.001213,0.051686616,0.0217 2018-06-29,104.79405809999999,0.012311,34.414570000000005,1.57865,0.2042,0.0012109999999999998,0.051316678,0.0215 2018-07-02,103.5558583,0.012193,35.125691499999995,1.58581,0.2049,0.001218,0.051907357,0.0215 2018-07-03,103.4118603,0.012287000000000001,34.805484,1.5784799999999999,0.2039,0.001214,0.051448687,0.0215 2018-07-05,102.6803845,0.012243,35.1315,1.5825,0.2039,0.001209,0.051441722,0.0214 2018-07-06,101.4939435,0.012232999999999999,35.21655224999999,1.58099,0.2026,0.001207,0.051144010999999996,0.0214 2018-07-09,102.169546,0.012187,35.724125,1.57375,0.2024,0.0012029999999999999,0.05115843,0.0215 2018-07-13,98.28933190000001,0.012084000000000001,35.45412475,1.57399,0.2016,0.001192,0.051320042999999996,0.0215 2018-07-16,94.24450735,0.011995,34.410864,1.5784799999999999,0.2015,0.001194,0.05135463,0.0216 2018-07-17,94.09933685,0.012001000000000001,34.6425875,1.57825,0.2016,0.001201,0.051698470999999996,0.0216 2018-07-18,95.99891863,0.01199,35.003699999999995,1.5732,0.2015,0.0011949999999999999,0.051500406,0.0215 2018-07-19,95.89729656,0.01198,35.1970525,1.58189,0.2014,0.0011970000000000001,0.05148757,0.0214 2018-07-20,95.83277141,0.012087,34.79014,1.5813700000000002,0.1993,0.0011949999999999999,0.050977747999999996,0.0212 2018-07-23,96.31486248,0.0121,35.164356,1.58398,0.1994,0.001194,0.051212573,0.0215 2018-07-24,96.86110737,0.012168,35.0684235,1.57434,0.1984,0.001196,0.050788090999999994,0.0213 2018-07-25,97.46478873,0.012123,35.084144,1.57328,0.1994,0.0012,0.050435949,0.0214 2018-07-26,98.59021282,0.012089,35.116507500000004,1.57827,0.1992,0.001206,0.050833672,0.0215 2018-07-27,97.95945946,0.012188,34.892894999999996,1.5753,0.1982,0.0012109999999999998,0.050675675999999996,0.0216 2018-07-30,98.86593763,0.01217,35.084436,1.58038,0.198,0.001208,0.05035777,0.0217 2018-07-31,96.64601293,0.012156,34.605570750000005,1.57477,0.1973,0.001209,0.050107759,0.0215 2018-08-01,95.46191248,0.012034999999999999,34.92008125,1.57475,0.198,0.001206,0.05010805,0.0215 2018-08-02,97.01086957,0.012089,35.062631999999994,1.57408,0.1981,0.001204,0.050271739,0.0214 2018-08-03,96.62344679,0.01217,35.192384249999996,1.56237,0.1977,0.0012029999999999999,0.049972987999999996,0.0211 2018-08-06,97.08948152,0.012142,35.1540465,1.5641399999999999,0.1974,0.001202,0.050087992000000005,0.0212 2018-08-08,94.5498587,0.012152,35.309336,1.56236,0.1972,0.0012050000000000001,0.049791414000000006,0.0205 2018-08-13,97.40027509999999,0.012125,36.8068855,1.56959,0.1994,0.001209,0.05048143099999999,0.0204 2018-08-14,97.12826177,0.012419,36.962320000000005,1.5662,0.2005,0.001224,0.050393482999999996,0.0208 2018-08-15,95.23414836,0.012426000000000001,36.8292,1.5672,0.1996,0.001218,0.050283188,0.0205 2018-08-16,95.71684341,0.012473999999999999,37.05482,1.5668,0.1995,0.001222,0.049579948,0.0206 2018-08-17,96.32161903,0.012419,37.7319825,1.56402,0.1996,0.001221,0.04909066,0.0207 2018-08-20,96.3760218,0.012375,37.901708250000006,1.56457,0.1995,0.001219,0.049182561,0.0203 2018-08-21,96.81053203,0.01238,37.925884499999995,1.57043,0.1987,0.001216,0.048995657000000005,0.0202 2018-08-22,100.0272183,0.012308,38.935669499999996,1.57794,0.1989,0.001216,0.048992923,0.02 2018-08-23,101.365894,0.012306000000000001,39.484080000000006,1.5921,0.2,0.001227,0.049530905,0.0202 2018-08-24,101.35079820000001,0.012398000000000001,39.803078,1.58578,0.2003,0.001224,0.048847046,0.0204 2018-08-27,102.0541423,0.012274,40.986912000000004,1.58864,0.1998,0.0012259999999999999,0.048700857,0.0202 2018-08-28,101.9760153,0.012253,41.15446175,1.59359,0.2,0.0012289999999999998,0.048650859000000005,0.0201 2018-08-29,104.4863904,0.012255,42.279863999999996,1.60151,0.201,0.001232,0.048693749,0.0201 2018-08-30,105.70012390000001,0.012249,42.099731999999996,1.60686,0.201,0.001234,0.04874019,0.0202 2018-08-31,106.63513700000001,0.012403,41.75371125,1.6136700000000002,0.2031,0.001247,0.049380999,0.0206 2018-09-04,106.9796601,0.012519,43.11597700000001,1.61332,0.2037,0.0012460000000000001,0.049038729,0.0204 2018-09-05,105.6026693,0.012501,43.982127999999996,1.61699,0.2037,0.001241,0.04907549,0.0204 2018-09-07,106.81018710000001,0.012465,46.002066,1.62408,0.2041,0.0012439999999999999,0.049810046,0.0201 ================================================ FILE: Oil Money project/data/vas crude copaud.csv ================================================ date,cop,usd,cny,try,mxn,brl,pen,ars,gold,arabica,robusta,api2,wti,brent,vasconia 1/2/2014,0.0578,1.1222,0.1855,0.51697,0.0853,0.47,0.3999,0.1715,1374.695,125.01308,1823.575,90.61765,107.102768,120.670166,112.994318 1/3/2014,0.0577,1.1179,0.1847,0.51335,0.0853,0.4695,0.398,0.1705,1380.04755,130.067665,1855.714,88.87305,105.037884,119.05635,111.767642 1/6/2014,0.0575,1.1152,0.1842,0.51359,0.0852,0.4692,0.3976,0.1692,1389.818,134.9392,1903.6464,88.9372,104.193136,119.002992,110.538624 1/7/2014,0.0581,1.1202,0.1851,0.51693,0.0861,0.4722,0.3996,0.1697,1375.0455,131.34345,1935.7056,89.16792,104.929134,119.906208,110.765376 1/8/2014,0.0581,1.1235,0.1857,0.51394,0.0855,0.4692,0.4006,0.1701,1371.7935,135.83115,1938.0375,92.01465,103.732755,120.135855,111.04674 1/9/2014,0.0581,1.1237,0.1856,0.51605,0.0858,0.4691,0.4008,0.1696,1377.6562,134.113595,1958.6091,94.3908,102.998342,119.314466,110.043941 1/10/2014,0.0578,1.1118,0.1837,0.51326,0.0857,0.4694,0.3974,0.1669,1383.35715,134.13867,1953.4326,92.94648,103.086096,119.01819,110.045964 1/13/2014,0.0573,1.1045,0.1827,0.50674,0.0844,0.4686,0.3949,0.165,1378.416,132.374325,1933.9795,92.66755,101.3931,116.96655,108.26309 1/14/2014,0.0576,1.1153,0.1846,0.51071,0.0852,0.4738,0.398,0.1663,1395.79795,132.94376,1945.0832,93.46214,103.265627,118.054505,109.042881 1/15/2014,0.0577,1.1216,0.1855,0.5119,0.085,0.4754,0.3993,0.1672,1386.2976,131.45152,1929.152,94.66304,105.621072,119.405536,111.722576 1/16/2014,0.0581,1.1337,0.1872,0.5137,0.0854,0.4796,0.4036,0.1674,1407.48855,134.173395,1982.8413,95.79765,106.522452,120.013482,112.905183 1/17/2014,0.058,1.1388,0.1882,0.50977,0.086,0.486,0.4056,0.1676,1423.5,133.41042,1964.43,96.05778,107.468556,121.62384,112.490664 1/20/2014,0.0578,1.1349,0.1875,0.50657,0.0857,0.4841,0.4041,0.1662,1425.150675,132.953535,1946.3535,95.3316,107.100513,121.786119,112.105422 1/21/2014,0.0572,1.1356,0.1877,0.50435,0.0856,0.4814,0.4043,0.165,1405.8728,131.95672,1949.8252,95.16328,107.870644,122.974124,112.810504 1/22/2014,0.0568,1.1297,0.1867,0.50009,0.0849,0.476,0.4022,0.1629,1401.9577,129.746045,1915.9712,94.160495,109.332366,123.736041,113.783384 1/23/2014,0.0571,1.1404,0.1884,0.49745,0.0851,0.476,0.4054,0.1443,1440.3252,131.37408,1961.488,94.9383,111.040748,124.486064,113.549628 1/24/2014,0.0577,1.1517,0.1904,0.49296,0.0856,0.4801,0.4079,0.1438,1459.2039,131.75448,1986.6825,95.93661,111.346356,125.708055,115.031796 1/27/2014,0.057,1.1443,0.1892,0.50113,0.0856,0.4725,0.4053,0.1432,1442.39015,130.278555,1986.5048,95.32019,109.532396,124.15655,113.377244 1/28/2014,0.0569,1.1391,0.1882,0.50536,0.0859,0.4694,0.4032,0.1421,1425.298875,130.597815,1979.7558,94.88703,110.959731,123.501222,113.22654 1/29/2014,0.057,1.1443,0.1891,0.50606,0.0854,0.4698,0.405,0.143,1446.3952,133.99753,2015.1123,95.262975,111.409048,124.087892,114.08671 1/30/2014,0.0565,1.1371,0.1877,0.50108,0.0851,0.4719,0.4037,0.142,1412.84675,136.452,2068.3849,94.60672,111.697333,123.363979,113.48258 1/31/2014,0.0567,1.1421,0.1885,0.50646,0.0855,0.4735,0.4047,0.1425,1428.7671,142.99092,2077.4799,95.02272,111.343329,122.43312,112.428324 2/3/2014,0.0558,1.1425,0.1886,0.50035,0.0844,0.4685,0.4043,0.1426,1441.835,155.322875,2133.0475,91.000125,110.171275,120.933625,113.758725 2/4/2014,0.055,1.1205,0.1849,0.50058,0.0841,0.4658,0.3965,0.1399,1400.905125,152.668125,2026.9845,89.023725,108.901395,118.784205,111.478545 2/5/2014,0.0548,1.1223,0.1852,0.50138,0.0845,0.4679,0.3973,0.1422,1407.92535,160.60113,2084.1111,89.952345,109.289574,119.053584,111.825972 2/6/2014,0.0546,1.1162,0.1841,0.50521,0.0841,0.4685,0.3953,0.1418,1402.5053,151.52415,2076.132,89.35181,109.209008,119.60083,112.479474 2/7/2014,0.0545,1.1163,0.1841,0.50288,0.084,0.4687,0.3954,0.1425,1405.700775,151.48191,1982.5488,88.63422,111.496044,121.866471,114.934248 2/10/2014,0.0545,1.1175,0.1844,0.50438,0.0839,0.4641,0.3966,0.1429,1427.0475,152.2035,2007.03,88.338375,111.81705,120.835275,114.0744 2/11/2014,0.0543,1.1065,0.1826,0.50456,0.0833,0.4609,0.3929,0.1417,1418.533,151.756475,2006.0845,87.74545,110.58361,120.09951,113.46051 2/12/2014,0.0546,1.1079,0.1827,0.50528,0.0831,0.4573,0.3935,0.1419,1428.63705,156.269295,2018.5938,87.96726,111.199923,120.040965,113.703777 2/13/2014,0.0549,1.1137,0.1837,0.50975,0.084,0.4632,0.3954,0.1426,1443.3552,155.58389,2031.3888,88.149355,111.759795,121.660588,114.410401 2/14/2014,0.0549,1.1069,0.1825,0.50722,0.0836,0.4635,0.3932,0.1427,1461.108,154.85531,2003.489,87.77717,111.02207,120.729583,113.988562 2/17/2014,0.0549,1.1071,0.1826,0.50856,0.0838,0.4633,0.3948,0.1427,1469.67525,154.88329,2020.4575,87.23948,111.04213,120.640687,114.009158 2/18/2014,0.0546,1.1078,0.1826,0.50827,0.0837,0.4626,0.3946,0.1427,1463.12685,169.10567,2083.7718,87.12847,113.471954,122.733162,115.70971 2/19/2014,0.0542,1.1111,0.1828,0.5017,0.0833,0.4642,0.3952,0.1428,1467.20755,190.831425,2202.2002,86.44358,114.787741,122.865438,115.587733 2/20/2014,0.0543,1.1104,0.1825,0.50449,0.0836,0.4683,0.3955,0.1421,1461.564,187.43552,2193.04,86.11152,114.282368,122.676992,115.31504 2/21/2014,0.0545,1.114,0.1829,0.51186,0.084,0.475,0.3971,0.142,1474.1005,187.7647,2206.834,86.2236,114.185,122.21694,114.99822 2/24/2014,0.0542,1.1067,0.1815,0.50288,0.0834,0.4728,0.3944,0.141,1477.167825,194.33652,2239.9608,85.381905,114.178239,122.478489,115.229604 2/25/2014,0.0542,1.1088,0.1811,0.5012,0.0838,0.4736,0.3947,0.1409,1484.6832,194.76072,2259.7344,85.48848,113.241744,121.568832,114.284016 2/26/2014,0.0543,1.115,0.1821,0.50017,0.0836,0.4745,0.397,0.1416,1484.90125,197.4665,2253.415,85.9665,114.38785,122.14825,114.7781 2/27/2014,0.0543,1.1154,0.182,0.50389,0.0841,0.4804,0.3977,0.1414,1485.99165,199.37775,2341.2246,85.99734,114.21696,121.533984,115.968138 2/28/2014,0.0547,1.1205,0.1823,0.50771,0.0846,0.4781,0.4001,0.1423,1486.34325,201.4659,2373.219,86.39055,114.952095,122.47065,116.46477 3/3/2014,0.0545,1.1188,0.1821,0.50127,0.0839,0.4769,0.3988,0.1422,1509.8206,215.48088,2411.014,83.12684,117.384496,124.119672,118.53686 3/4/2014,0.0545,1.1173,0.1819,0.50652,0.0841,0.477,0.3992,0.142,1491.316175,206.868095,2358.6203,81.842225,115.450609,121.7857,116.377968 3/5/2014,0.0546,1.113,0.1816,0.50544,0.0841,0.4801,0.3974,0.1412,1488.081,223.32345,2351.769,81.41595,112.91385,119.60298,114.39414 3/6/2014,0.0542,1.1001,0.1798,0.50456,0.0836,0.4734,0.3928,0.1395,1479.909525,214.29948,2347.6134,81.132375,111.726156,118.931811,113.816346 3/7/2014,0.0541,1.1028,0.18,0.50022,0.0836,0.4709,0.3939,0.1402,1472.5137,216.20394,2378.7396,81.27636,113.125224,119.742024,113.5884 3/10/2014,0.0543,1.1087,0.1806,0.49972,0.0839,0.4719,0.3952,0.141,1490.0928,224.51175,2434.7052,81.60032,112.111744,119.307207,113.331314 3/11/2014,0.0545,1.114,0.1814,0.49578,0.0839,0.4713,0.3974,0.1417,1499.7225,228.4257,2500.93,83.2715,111.43342,120.32314,113.39406 3/12/2014,0.0544,1.1126,0.181,0.49846,0.084,0.4722,0.3962,0.1412,1519.8116,227.86048,2504.4626,83.83441,109.023674,119.982784,113.129168 3/13/2014,0.0541,1.1073,0.1804,0.49602,0.0833,0.4681,0.3949,0.1405,1515.616875,227.051865,2485.8885,83.545785,108.73686,118.691487,112.247001 3/14/2014,0.0542,1.1076,0.1801,0.50057,0.0839,0.4714,0.3949,0.1403,1534.026,219.13866,2482.1316,83.78994,109.530564,120.041688,113.606532 3/17/2014,0.0541,1.1004,0.1781,0.49588,0.0836,0.4686,0.3924,0.139,1516.9014,208.96596,2448.39,83.52036,107.927232,117.016536,110.337108 3/18/2014,0.0539,1.0957,0.1769,0.49388,0.0833,0.4683,0.3897,0.1379,1485.495275,209.223915,2411.6357,82.72535,109.24129,116.648222,110.293162 3/19/2014,0.0551,1.1059,0.1785,0.49389,0.0832,0.4706,0.3926,0.1391,1479.6942,204.70209,2377.685,83.38486,110.999183,116.971043,110.755885 3/20/2014,0.0555,1.1063,0.1776,0.49613,0.0834,0.4754,0.3932,0.1391,1468.0601,192.662145,2319.9111,83.19376,109.999409,117.356304,111.127835 3/21/2014,0.0552,1.1011,0.1769,0.49301,0.0832,0.4734,0.3917,0.1382,1471.0696,188.453265,2311.2089,83.02294,110.065956,117.729612,111.530419 3/24/2014,0.0549,1.095,0.1768,0.48952,0.0831,0.4717,0.3895,0.1375,1435.27125,193.158,2352.06,82.50825,109.6095,116.43135,110.3322 3/25/2014,0.0551,1.091,0.1759,0.49217,0.0832,0.4722,0.3876,0.1363,1433.0285,191.2523,2333.649,81.9341,108.59814,116.28969,110.24555 3/26/2014,0.055,1.0839,0.1746,0.49451,0.0826,0.4707,0.3855,0.1354,1413.4056,190.7664,2324.9655,81.40089,108.671814,115.565418,109.614807 3/27/2014,0.055,1.08,0.1738,0.49421,0.0826,0.4779,0.3839,0.1349,1399.68,190.458,2314.44,81.108,109.3824,115.6032,109.9764 3/28/2014,0.055,1.0814,0.174,0.49341,0.0827,0.4783,0.3846,0.1351,1400.14265,195.30084,2329.3356,81.32128,109.945938,116.001778,110.57315 3/31/2014,0.0547,1.0794,0.1736,0.50424,0.0827,0.4752,0.3839,0.1349,1394.31495,192.02526,2325.0276,83.70747,109.645452,115.474212,109.494336 4/1/2014,0.0552,1.0814,0.1742,0.50584,0.0829,0.4778,0.3852,0.1352,1388.24725,189.51535,2188.7536,83.32187,107.858836,113.049556,107.177554 4/2/2014,0.055,1.0813,0.1742,0.5081,0.0826,0.4761,0.3848,0.1351,1397.0396,186.74051,2184.226,82.340995,107.719106,112.401135,106.410733 4/3/2014,0.055,1.0832,0.1744,0.50805,0.0826,0.4744,0.385,0.1353,1390.8288,189.12672,2183.7312,82.81064,108.634128,113.985136,108.21168 4/4/2014,0.0552,1.0762,0.1732,0.50922,0.0828,0.4806,0.3832,0.1345,1396.10045,199.097,2243.877,82.00644,108.846868,114.109486,107.964384 4/7/2014,0.0556,1.0787,0.1736,0.5113,0.0829,0.4865,0.3854,0.1348,1401.2313,208.566645,2291.1588,82.682355,108.344628,113.748915,107.567964 4/8/2014,0.0553,1.0683,0.1724,0.50966,0.0819,0.4852,0.3827,0.1335,1398.93885,209.92095,2322.4842,81.244215,109.564848,114.051708,108.229473 4/9/2014,0.0552,1.0649,0.1718,0.50617,0.082,0.4859,0.3818,0.1331,1386.233575,212.820265,2279.9509,80.9324,110.32364,114.295717,108.097999 4/10/2014,0.0554,1.0623,0.171,0.50378,0.0813,0.4814,0.3812,0.1328,1402.76715,218.94003,2296.6926,81.58464,109.84182,113.538624,109.342539 4/11/2014,0.0552,1.0642,0.1714,0.50392,0.0816,0.4801,0.3825,0.133,1402.6156,214.11704,2278.4522,81.62414,110.400108,113.347942,109.29334 4/14/2014,0.0551,1.0611,0.1706,0.50038,0.0815,0.479,0.3837,0.1326,1406.753325,217.366335,2262.2652,81.651645,110.407455,115.02324,110.831895 4/15/2014,0.0552,1.0682,0.1717,0.49857,0.0815,0.4781,0.3841,0.1335,1386.5236,205.25463,2265.6522,82.51845,110.82575,116.188114,109.960508 4/16/2014,0.0553,1.0671,0.1715,0.49947,0.0817,0.4759,0.385,0.1334,1388.83065,198.427245,2202.4944,82.70025,110.722296,116.815437,110.775651 4/17/2014,0.0555,1.0719,0.1723,0.50388,0.0821,0.4793,0.3865,0.1339,1392.3981,215.66628,2270.2842,82.375515,111.79917,117.598149,111.359691 4/18/2014,0.0555,1.0716,0.1722,0.5033,0.0821,0.4789,0.3864,0.1339,1392.0084,215.60592,2269.6488,82.35246,111.76788,117.565236,111.328524 4/21/2014,0.0559,1.0721,0.1721,0.5025,0.0823,0.4792,0.3866,0.1334,1392.6579,210.88207,2270.7078,82.390885,111.895077,117.909558,111.60561 4/22/2014,0.0552,1.0676,0.1712,0.49855,0.0818,0.4766,0.3833,0.1334,1373.7343,226.11768,2291.0696,81.9383,109.033988,116.806116,110.485924 4/23/2014,0.0557,1.0763,0.1725,0.50039,0.0824,0.484,0.3857,0.1345,1383.314575,228.552305,2316.1976,82.713655,109.502762,117.338226,111.536969 4/24/2014,0.0557,1.0794,0.1727,0.50538,0.0824,0.4871,0.3865,0.1349,1394.0451,229.31853,2322.8688,82.89792,110.357856,119.014644,113.218266 4/25/2014,0.0555,1.0784,0.1725,0.50516,0.0821,0.4804,0.3846,0.1347,1403.268,220.8024,2303.4624,82.87504,108.81056,117.966176,111.873216 4/28/2014,0.0557,1.0801,0.1728,0.5082,0.0823,0.4856,0.3842,0.135,1403.0499,214.72388,2289.812,82.789665,108.917284,117.08284,110.688648 4/29/2014,0.0558,1.079,0.1725,0.50904,0.0824,0.4831,0.3842,0.1349,1400.27225,225.4031,2298.27,82.16585,109.28112,118.05339,111.2449 4/30/2014,0.0556,1.0768,0.1721,0.50972,0.0823,0.4831,0.3835,0.1346,1387.4568,218.64424,2333.4256,80.81384,107.400032,116.99432,110.285856 5/1/2014,0.0557,1.0783,0.1723,0.51208,0.0827,0.4828,0.384,0.1347,1378.60655,217.223535,2348.5374,80.76467,107.204586,115.928033,110.051298 5/2/2014,0.0559,1.0781,0.1722,0.51201,0.0828,0.4854,0.3847,0.1347,1381.315625,216.26686,2316.8369,80.8575,107.551256,117.232594,110.817899 5/5/2014,0.0561,1.0783,0.1727,0.5134,0.0826,0.4807,0.3846,0.1348,1381.571875,218.24792,2317.2667,80.8725,107.269284,115.744722,109.630761 5/6/2014,0.0558,1.0694,0.1717,0.51169,0.0821,0.4796,0.3816,0.1336,1396.90375,213.39877,2301.3488,80.52582,106.4053,114.63968,108.0094 5/7/2014,0.0561,1.0719,0.1719,0.51499,0.0827,0.4837,0.383,0.134,1389.1824,212.66496,2302.4412,80.231715,108.015363,115.636572,109.483866 5/8/2014,0.0561,1.0667,0.1713,0.5145,0.0824,0.4828,0.3836,0.1333,1372.8429,205.819765,2278.4712,80.162505,106.947342,114.851589,108.846068 5/9/2014,0.0561,1.0682,0.1715,0.51433,0.0825,0.4827,0.3829,0.1335,1379.31325,193.13056,2241.0836,80.38205,106.809318,115.013094,108.913672 5/12/2014,0.0558,1.0681,0.1713,0.51334,0.0825,0.4813,0.3832,0.1333,1387.194875,198.77341,2280.3935,80.1075,107.440179,115.56842,109.426845 5/13/2014,0.0556,1.0685,0.1715,0.51656,0.0828,0.4823,0.384,0.1332,1385.31025,196.230025,2239.576,80.24435,108.66645,116.306225,110.39742 5/14/2014,0.0555,1.0662,0.1712,0.51505,0.0827,0.4842,0.3833,0.1327,1391.65755,192.71565,2233.689,80.28486,109.146894,116.812872,110.83149 5/15/2014,0.0555,1.0688,0.1716,0.50933,0.0825,0.4816,0.3836,0.1327,1388.3712,207.50752,2285.0944,80.48064,108.4832,117.24736,111.358272 5/16/2014,0.0555,1.0677,0.1714,0.50909,0.0828,0.4823,0.383,0.1325,1378.93455,194.85525,2189.8527,80.344425,108.926754,117.735279,110.549658 5/19/2014,0.0559,1.0719,0.1718,0.51114,0.0831,0.4855,0.3844,0.133,1395.6138,193.102785,2188.8198,80.49969,109.987659,118.670049,110.51289 5/20/2014,0.0563,1.0819,0.1734,0.51187,0.0838,0.4882,0.3879,0.1342,1401.60145,200.90883,2208.1579,81.03431,110.829836,120.285642,111.998288 5/21/2014,0.0566,1.0808,0.1734,0.51617,0.0836,0.4893,0.3875,0.1341,1391.2598,196.05712,2152.9536,81.00596,112.965216,120.822632,112.554512 5/22/2014,0.0569,1.0839,0.1738,0.52087,0.0842,0.4892,0.3886,0.1345,1407.44415,196.565265,2168.8839,81.40089,112.855668,120.995757,112.855668 5/23/2014,0.0567,1.0833,0.1737,0.52056,0.0843,0.4873,0.3884,0.1344,1399.08195,197.05227,2165.5167,81.2475,113.692335,121.00461,113.009856 5/26/2014,0.0567,1.0825,0.1735,0.51961,0.0841,0.4871,0.3881,0.1343,1398.04875,196.90675,2163.9175,81.1875,113.608375,120.48225,112.9264 5/27/2014,0.0564,1.08,0.1729,0.51383,0.084,0.4823,0.3872,0.1339,1377.54,193.698,2122.2,80.784,112.4388,120.1824,112.1148 5/28/2014,0.0567,1.0827,0.1731,0.51579,0.0841,0.485,0.391,0.1341,1367.99145,190.717605,2063.6262,80.98596,111.214944,120.136392,112.135239 5/29/2014,0.0564,1.0745,0.1722,0.51502,0.0837,0.4832,0.3888,0.1331,1348.4975,195.505275,2093.126,80.3726,111.29671,119.344715,111.629805 5/30/2014,0.0566,1.0741,0.1719,0.51196,0.0835,0.4791,0.3884,0.1329,1343.16205,190.65275,2092.3468,80.288975,110.320811,118.859906,110.449703 6/2/2014,0.0568,1.0815,0.1731,0.51297,0.0837,0.475,0.39,0.1338,1348.900875,186.396525,2090.5395,80.2473,110.821305,118.197135,110.44278 6/3/2014,0.0569,1.0793,0.1726,0.50975,0.0834,0.4733,0.3869,0.1334,1341.300075,184.722195,2045.2735,80.030095,110.800938,117.85956,110.174944 6/4/2014,0.0568,1.0777,0.1724,0.50961,0.0834,0.4723,0.3864,0.1329,1342.005925,183.42454,2044.3969,79.64203,110.615128,116.520924,109.505097 6/5/2014,0.0566,1.0706,0.1712,0.51069,0.0832,0.4726,0.3838,0.1319,1340.9265,181.09199,2033.0694,78.10027,109.715088,116.898814,109.372496 6/6/2014,0.0569,1.0714,0.1714,0.51572,0.0829,0.4766,0.3841,0.1316,1336.5715,184.38794,2042.0884,77.94435,109.989924,116.88974,109.8185 6/9/2014,0.0567,1.0688,0.1713,0.5122,0.082,0.4798,0.3832,0.1315,1339.7408,176.72608,2012.5504,77.7552,111.593408,117.771072,110.503232 6/10/2014,0.0566,1.0669,0.1714,0.51306,0.0819,0.4792,0.3824,0.1312,1343.76055,176.731985,2000.4375,77.56363,111.331015,116.93224,110.157425 6/11/2014,0.0566,1.0657,0.1711,0.50351,0.0819,0.4767,0.3809,0.1311,1344.9134,182.87412,2071.7208,77.36982,111.25908,117.695908,110.363892 6/12/2014,0.0566,1.0609,0.1706,0.50245,0.0817,0.4754,0.3796,0.1305,1342.834175,182.421755,2076.1813,77.02134,113.017677,119.45734,113.282902 6/13/2014,0.0565,1.0636,0.1712,0.50102,0.0817,0.4782,0.3815,0.1308,1353.9628,184.74732,2109.1188,77.53644,113.709476,119.825176,113.709476 6/16/2014,0.0563,1.0637,0.1709,0.49641,0.0815,0.476,0.3803,0.1309,1357.547125,183.966915,2109.3171,77.703285,113.70953,120.070456,113.209591 6/17/2014,0.0563,1.071,0.172,0.49823,0.0817,0.4735,0.3824,0.1318,1357.4925,181.05255,2094.876,77.9688,113.91156,121.3443,115.01469 6/18/2014,0.0562,1.0628,0.1706,0.5,0.0819,0.4771,0.3796,0.1308,1349.4903,177.2219,2097.9672,77.10614,112.624916,121.31862,115.0481 6/19/2014,0.0565,1.0638,0.1708,0.49632,0.0817,0.4787,0.3793,0.1308,1375.4934,177.6546,2083.9842,77.28507,113.220234,122.337,115.932924 6/20/2014,0.0566,1.0653,0.1711,0.4976,0.082,0.4774,0.3797,0.131,1398.20625,184.563225,2119.947,77.23425,114.264078,122.030115,114.391914 6/23/2014,0.0564,1.0615,0.1705,0.49655,0.0815,0.4786,0.3785,0.1305,1394.28025,185.86865,2087.9705,76.8526,113.38943,120.65009,113.55927 6/24/2014,0.0565,1.0675,0.1713,0.49845,0.0817,0.4801,0.3806,0.1313,1407.49875,185.905125,2085.895,77.126875,113.827525,121.33205,114.37195 6/25/2014,0.0565,1.063,0.1705,0.4987,0.0817,0.4815,0.379,0.1307,1399.70525,191.28685,2119.622,76.9612,114.00675,120.93751,113.62407 6/26/2014,0.0564,1.0622,0.1706,0.4997,0.0816,0.4837,0.3787,0.1307,1393.34085,189.92136,2132.8976,76.85017,112.423248,119.92238,112.69942 6/27/2014,0.0564,1.061,0.1706,0.49998,0.0819,0.4833,0.3792,0.1304,1397.8675,180.84745,2149.586,76.76335,112.19014,119.77629,112.73125 6/30/2014,0.0564,1.0601,0.1709,0.50026,0.0817,0.479,0.3788,0.1304,1394.0315,183.3973,2118.0798,77.59932,111.702737,118.826609,112.020767 7/1/2014,0.0566,1.053,0.1698,0.49462,0.0814,0.4783,0.3765,0.1294,1397.8575,177.2199,2113.371,77.34285,110.92302,117.21996,111.13362 7/2/2014,0.057,1.0589,0.1705,0.49706,0.0815,0.4765,0.3789,0.1301,1404.63085,181.124845,2167.5683,77.564425,110.633872,116.743725,110.538571 7/3/2014,0.058,1.0699,0.1722,0.50264,0.0826,0.4837,0.3854,0.1314,1409.59325,181.24106,2209.3435,77.88872,111.333794,117.614107,111.708259 7/4/2014,0.0579,1.0678,0.1721,0.50059,0.0823,0.4827,0.3856,0.1312,1408.69515,180.88532,2192.1934,77.78923,111.115268,117.08427,111.488998 7/7/2014,0.0575,1.0669,0.172,0.50111,0.0819,0.4796,0.3842,0.1311,1400.8397,180.3061,2174.3422,77.77701,110.456157,116.228086,110.31746 7/8/2014,0.0574,1.0639,0.1715,0.50072,0.082,0.4803,0.3818,0.1307,1407.5397,181.07578,2196.9535,77.45192,110.00726,115.060785,108.379493 7/9/2014,0.0571,1.0623,0.1714,0.50219,0.0819,0.4801,0.3815,0.1305,1405.157325,180.80346,2186.2134,76.91052,108.662667,114.069774,107.547252 7/10/2014,0.0574,1.0644,0.1716,0.50109,0.0819,0.4796,0.3834,0.1307,1426.5621,170.5701,2141.5728,77.06256,109.558692,114.63588,108.313344 7/11/2014,0.0573,1.0648,0.1717,0.50295,0.0819,0.4792,0.3819,0.1306,1421.508,169.24996,2129.6,77.09152,107.363784,112.687784,106.37352 7/14/2014,0.0572,1.0646,0.1715,0.50307,0.0822,0.4809,0.3827,0.1306,1390.3676,172.78458,2156.8796,77.50288,107.428786,113.188272,106.917778 7/15/2014,0.0571,1.0672,0.1719,0.503,0.0824,0.4809,0.3835,0.131,1398.032,170.11168,2161.08,77.74552,106.677312,112.3228,106.13304 7/16/2014,0.0572,1.0674,0.172,0.50377,0.0827,0.4796,0.383,0.131,1388.6874,171.15759,2147.6088,77.70672,108.02088,112.39722,106.836066 7/17/2014,0.0571,1.0694,0.1724,0.49941,0.0823,0.4739,0.3834,0.1312,1392.8935,172.92198,2140.9388,78.01273,110.351386,114.415106,108.030788 7/18/2014,0.057,1.0644,0.1715,0.50137,0.0822,0.4783,0.3813,0.1307,1391.4369,181.69308,2134.122,77.7012,109.771572,112.677384,106.897692 7/21/2014,0.0574,1.0665,0.1718,0.50366,0.0822,0.48,0.3823,0.1307,1398.71475,183.064725,2159.6625,77.96115,111.545235,113.656905,107.812485 7/22/2014,0.0577,1.0645,0.1716,0.50539,0.0822,0.4808,0.3813,0.1303,1394.761125,179.15535,2126.871,77.974625,111.15509,112.17701,107.10999 7/23/2014,0.0572,1.0575,0.1706,0.50605,0.0818,0.4762,0.3796,0.1294,1383.21,186.7545,2113.9425,77.673375,113.80815,112.993875,107.2305 7/24/2014,0.0575,1.0617,0.1714,0.50765,0.0819,0.4779,0.3812,0.13,1372.512675,189.30111,2166.9297,78.14112,111.818244,112.11552,106.732701 7/25/2014,0.0576,1.0643,0.1719,0.50811,0.0822,0.4775,0.3822,0.1303,1378.002425,190.669345,2154.1432,78.22605,113.177662,113.518238,108.186095 7/28/2014,0.0575,1.0631,0.1718,0.50648,0.0817,0.4781,0.3816,0.13,1386.81395,192.52741,2164.4716,83.400195,108.085377,112.603552,107.181742 7/29/2014,0.0573,1.0657,0.1724,0.50353,0.0816,0.4778,0.382,0.1302,1384.610725,192.57199,2167.6338,82.538465,107.603729,113.134712,107.582415 7/30/2014,0.057,1.0718,0.1737,0.5024,0.0815,0.4769,0.3845,0.1309,1387.4451,195.6035,2193.9746,81.93911,107.469386,112.21746,106.236816 7/31/2014,0.0573,1.0758,0.1743,0.50201,0.0814,0.4753,0.3841,0.131,1382.67195,209.83479,2202.1626,82.08354,105.611286,111.77562,105.783414 8/1/2014,0.0573,1.0738,0.1738,0.50339,0.0815,0.4752,0.3837,0.1303,1386.54425,206.54543,2251.7586,81.93094,105.103544,111.202728,104.459264 8/4/2014,0.0569,1.0714,0.1734,0.50263,0.0812,0.4742,0.3819,0.1297,1382.6417,204.1017,2150.2998,82.06924,105.307906,111.672022,104.579354 8/5/2014,0.0568,1.0747,0.1742,0.49994,0.0808,0.4703,0.3822,0.1301,1380.720825,203.54818,2159.0723,82.7519,104.654286,111.629089,103.794526 8/6/2014,0.0567,1.069,0.1734,0.49522,0.0807,0.47,0.3804,0.1293,1396.6485,204.01865,2129.448,82.58025,103.60748,110.95151,103.39368 8/7/2014,0.0573,1.0786,0.1751,0.49773,0.0812,0.4702,0.3834,0.1305,1407.84265,198.4624,2122.6848,83.96901,104.990924,112.994136,105.605726 8/8/2014,0.057,1.0779,0.1751,0.50268,0.0814,0.4722,0.3858,0.1304,1411.779525,194.938215,2099.7492,84.345675,105.159924,111.810567,104.276046 8/11/2014,0.0573,1.0796,0.1754,0.50208,0.0819,0.4744,0.3868,0.1306,1411.3071,204.20634,2144.0856,83.72298,105.887168,111.90054,104.256972 8/12/2014,0.0575,1.0789,0.1752,0.49896,0.0821,0.4742,0.3866,0.1306,1419.562675,199.16494,2118.9596,83.50686,105.052493,110.101745,102.786803 8/13/2014,0.0571,1.0747,0.1746,0.49856,0.0818,0.4711,0.3847,0.13,1410.0064,199.088175,2111.7855,83.235515,104.879973,111.145474,103.49361 8/14/2014,0.057,1.0731,0.1744,0.49863,0.0821,0.4722,0.3838,0.1296,1409.51685,197.55771,2087.1795,82.467735,102.566898,108.071901,101.150406 8/15/2014,0.0569,1.0727,0.1745,0.49509,0.0821,0.4747,0.3825,0.1296,1390.2192,202.472125,2092.8377,83.295155,104.427345,109.404673,102.410669 8/18/2014,0.0569,1.0724,0.1746,0.49546,0.0822,0.4748,0.3808,0.1296,1390.6347,202.57636,2091.18,82.41394,103.390084,107.711856,100.762704 8/19/2014,0.0565,1.0749,0.175,0.49679,0.0824,0.4775,0.3802,0.1298,1393.60785,195.84678,2086.3809,82.498575,101.556552,106.974048,100.857867 8/20/2014,0.0562,1.0766,0.1753,0.49279,0.082,0.476,0.3807,0.1294,1394.197,198.20206,2114.4424,82.79054,103.428962,108.026044,102.00785 8/21/2014,0.056,1.075,0.1747,0.49373,0.082,0.4737,0.3809,0.1281,1370.89375,197.53125,2130.65,82.775,103.53325,108.231,102.37225 8/22/2014,0.0558,1.0734,0.1745,0.49337,0.0817,0.4709,0.3788,0.1279,1371.00015,194.92944,2131.7724,82.54446,103.10007,107.522478,101.693916 8/25/2014,0.0556,1.0756,0.1748,0.49399,0.0818,0.4704,0.3795,0.1282,1373.8101,196.5659,2136.1416,82.71364,102.28956,108.3667,102.407876 8/26/2014,0.0556,1.0745,0.1746,0.49626,0.082,0.4746,0.3788,0.128,1381.807,207.48595,2156.5215,82.7365,100.85257,108.18066,102.05601 8/27/2014,0.0555,1.071,0.1743,0.49688,0.0819,0.4767,0.3761,0.1274,1373.82525,206.0604,2174.13,82.467,100.54548,107.58195,101.93778 8/28/2014,0.0555,1.0688,0.174,0.49522,0.0817,0.4771,0.3757,0.1272,1380.8896,208.04192,2176.0768,82.2976,101.05504,107.222016,101.578752 8/29/2014,0.0557,1.0707,0.1743,0.49463,0.0818,0.4788,0.3764,0.1274,1376.652525,209.589525,2176.7331,82.390365,102.744372,108.419082,102.380334 9/1/2014,0.0558,1.0716,0.1744,0.49602,0.0818,0.477,0.3761,0.1275,1378.6134,209.7657,2206.4244,82.67394,102.830736,108.628092,102.466392 9/2/2014,0.0558,1.0782,0.1754,0.49634,0.0822,0.4806,0.3783,0.1283,1366.0794,220.43799,2253.438,82.53621,100.143216,107.55045,100.197126 9/3/2014,0.0556,1.07,0.1742,0.49595,0.0817,0.4784,0.3749,0.1272,1354.085,211.111,2191.36,81.4805,102.2278,108.391,101.543 9/4/2014,0.0553,1.0696,0.1742,0.49449,0.0813,0.477,0.3748,0.1273,1359.9964,211.19252,2213.0024,80.86176,101.02372,107.772896,100.97024 9/5/2014,0.055,1.0666,0.1737,0.49408,0.0818,0.4759,0.3741,0.1267,1350.3156,205.69381,2198.2626,80.20832,99.503114,106.81999,100.655042 9/8/2014,0.0553,1.0773,0.1754,0.49555,0.082,0.4751,0.3773,0.1282,1356.3207,204.309945,2209.5423,81.76707,99.822618,107.115939,101.126151 9/9/2014,0.0552,1.0866,0.1771,0.49473,0.0823,0.4753,0.3803,0.1293,1364.49795,204.38946,2223.1836,81.71232,100.78215,107.106162,100.814748 9/10/2014,0.0553,1.0924,0.1782,0.4979,0.0828,0.4768,0.3828,0.1301,1366.5924,193.3548,2180.4304,82.31234,100.140308,106.18128,100.260472 9/11/2014,0.0554,1.0989,0.1793,0.49943,0.0831,0.4785,0.3846,0.1308,1364.009625,198.406395,2164.833,82.96695,102.010887,107.131761,99.769131 9/12/2014,0.0554,1.1065,0.1804,0.49782,0.0835,0.4731,0.3871,0.1317,1362.65475,198.782725,2185.3375,83.817375,102.096755,106.677665,100.42594 9/15/2014,0.0557,1.1076,0.1804,0.5006,0.0837,0.473,0.3867,0.1318,1367.0553,196.37748,2165.358,83.67918,102.918192,106.927704,100.01628 9/16/2014,0.0557,1.0997,0.1789,0.49913,0.0836,0.4718,0.3849,0.1309,1355.105325,198.60582,2159.8108,82.752425,104.339536,107.044798,101.788232 9/17/2014,0.0565,1.1158,0.1817,0.50182,0.0842,0.4736,0.39,0.1328,1379.1288,201.56927,2182.5048,83.96395,105.353836,108.500392,103.09992 9/18/2014,0.0564,1.1124,0.1811,0.49982,0.084,0.4703,0.3886,0.1324,1357.6842,195.67116,2186.9784,83.65248,103.531068,107.279856,101.528748 9/19/2014,0.0568,1.1204,0.1824,0.50135,0.0848,0.4728,0.3909,0.133,1366.6079,199.4312,2162.372,84.14204,103.536164,108.62278,102.2365 9/22/2014,0.0565,1.127,0.1835,0.5029,0.0849,0.4704,0.3924,0.1338,1367.6145,202.1838,2175.11,84.58135,103.14304,107.38056,101.41873 9/23/2014,0.0566,1.1312,0.1843,0.50505,0.0849,0.4689,0.3935,0.1342,1382.3264,204.63408,2183.216,84.89656,104.703872,107.441376,102.724272 9/24/2014,0.056,1.1254,0.1835,0.50336,0.0848,0.4722,0.3916,0.1337,1369.89315,212.81314,2220.4142,84.405,105.7876,106.980524,102.613972 9/25/2014,0.0564,1.138,0.1854,0.50315,0.085,0.4691,0.3935,0.1352,1381.2475,207.4574,2216.824,85.35,107.34754,108.48554,103.59214 9/26/2014,0.0565,1.1409,0.1862,0.50433,0.0849,0.4723,0.3952,0.135,1384.767375,212.264445,2235.0231,85.5675,106.719786,108.636498,102.931998 9/29/2014,0.0566,1.147,0.1865,0.50331,0.085,0.4681,0.396,0.1352,1398.7665,219.36375,2257.296,82.75605,108.47179,109.44674,103.76909 9/30/2014,0.0565,1.1431,0.1863,0.50186,0.0851,0.4666,0.3956,0.1356,1390.58115,221.018385,2249.6208,82.53182,104.204996,106.502627,100.718541 10/1/2014,0.0564,1.1443,0.1865,0.50121,0.085,0.461,0.3954,0.1354,1392.04095,229.31772,2350.3922,83.133395,103.822339,107.003493,100.217794 10/2/2014,0.0564,1.1359,0.1851,0.50115,0.0849,0.4553,0.3918,0.1346,1376.426825,236.94874,2332.0027,83.14788,103.378259,105.547828,98.743787 10/3/2014,0.0569,1.1528,0.1878,0.50222,0.0855,0.466,0.3972,0.1365,1377.596,238.0532,2397.824,83.46272,103.452272,105.331336,98.368424 10/6/2014,0.0563,1.1411,0.1859,0.50327,0.0852,0.4703,0.393,0.1347,1364.470325,251.95488,2470.4815,82.38742,103.086974,105.152365,99.024658 10/7/2014,0.0559,1.1341,0.1847,0.49848,0.0842,0.4731,0.3902,0.1341,1372.82805,245.362535,2467.8016,82.052135,100.764785,103.214441,97.135665 10/8/2014,0.0552,1.1311,0.1843,0.50018,0.0848,0.4757,0.3889,0.1337,1376.5487,242.564395,2432.9961,82.174415,98.756341,102.975344,96.629873 10/9/2014,0.0557,1.1386,0.1857,0.50171,0.0847,0.4754,0.3917,0.1344,1396.77755,252.37069,2483.2866,82.37771,97.657722,100.561152,94.765678 10/10/2014,0.0562,1.1513,0.1878,0.50305,0.0854,0.4739,0.3961,0.1358,1403.4347,253.74652,2485.6567,83.411685,98.804566,103.191019,95.983881 10/13/2014,0.0557,1.14,0.1861,0.50237,0.0848,0.4762,0.3928,0.1345,1401.06,248.634,2472.66,82.308,97.7436,100.2174,93.3888 10/14/2014,0.056,1.1477,0.1874,0.50498,0.0854,0.478,0.3951,0.1355,1417.122575,254.67463,2473.2935,82.74917,93.927768,97.634839,90.507622 10/15/2014,0.0547,1.1327,0.1849,0.49918,0.0837,0.4609,0.3895,0.1337,1401.71625,244.6632,2440.9685,81.724305,92.632206,94.150024,87.78425 10/16/2014,0.0552,1.1421,0.1865,0.50486,0.0842,0.4618,0.3932,0.1347,1413.634275,247.94991,2460.0834,82.174095,94.45167,98.551809,89.335062 10/17/2014,0.0554,1.1428,0.1867,0.50924,0.0846,0.4696,0.3934,0.1349,1410.5009,240.73082,2419.3076,82.22446,94.5667,97.263708,91.526852 10/20/2014,0.0552,1.1384,0.1859,0.50747,0.0841,0.4625,0.3923,0.1343,1416.7388,226.99696,2332.5816,81.9648,94.157064,95.944352,90.309272 10/21/2014,0.0557,1.1387,0.186,0.50727,0.0841,0.4605,0.3923,0.1348,1423.659675,227.28452,2329.7802,82.21414,94.295747,97.142497,91.346514 10/22/2014,0.0555,1.1393,0.1862,0.5074,0.084,0.4584,0.3926,0.1342,1417.004375,217.72023,2307.0825,83.05497,92.761806,95.461947,89.537587 10/23/2014,0.0555,1.1412,0.1865,0.51061,0.0842,0.4564,0.3926,0.1345,1406.8143,220.59396,2291.5296,83.3076,93.966408,98.017668,92.197548 10/24/2014,0.055,1.1365,0.1858,0.50928,0.0838,0.4598,0.3903,0.1339,1401.020375,217.63975,2303.6855,82.907675,92.35199,96.932085,91.19276 10/27/2014,0.0549,1.1361,0.1857,0.50962,0.0839,0.4505,0.3895,0.1337,1395.982875,216.88149,2285.8332,82.764885,92.0241,96.11406,90.240423 10/28/2014,0.0549,1.1291,0.1847,0.51175,0.084,0.458,0.3872,0.1328,1387.946175,217.182385,2283.0402,82.08557,91.931322,96.233193,90.282836 10/29/2014,0.0555,1.1369,0.186,0.51309,0.0842,0.4616,0.3898,0.1337,1390.99715,215.55624,2321.5498,82.823165,93.45318,97.386854,92.327649 10/30/2014,0.0552,1.1319,0.1851,0.51502,0.0842,0.4713,0.3879,0.1331,1360.5438,212.34444,2304.5484,82.458915,91.819728,96.09831,91.763133 10/31/2014,0.0553,1.1366,0.186,0.51109,0.0843,0.4593,0.3891,0.1337,1323.28655,213.6808,2327.7568,82.80131,91.541764,96.38368,91.973672 11/3/2014,0.0558,1.1517,0.1882,0.51544,0.0846,0.4615,0.3937,0.1354,1344.897675,214.043445,2387.4741,82.9224,90.730926,96.224535,91.398912 11/4/2014,0.0551,1.1443,0.1871,0.51516,0.0844,0.4559,0.3909,0.1345,1334.82595,215.35726,2333.2277,81.874665,88.328517,93.969916,88.854895 11/5/2014,0.0561,1.1636,0.1903,0.5185,0.0857,0.4645,0.3975,0.1368,1328.8312,216.7205,2357.4536,83.25558,91.552048,96.299536,91.098244 11/6/2014,0.0556,1.1683,0.1911,0.51603,0.0857,0.4546,0.3987,0.1374,1337.7035,214.675125,2343.6098,83.241375,91.022253,95.987528,90.870374 11/7/2014,0.0552,1.158,0.1892,0.51285,0.0855,0.4525,0.3957,0.1361,1336.911,211.2192,2336.844,83.2602,91.0767,95.39604,90.45138 11/10/2014,0.055,1.16,0.1895,0.51344,0.0852,0.4544,0.3958,0.1363,1347.92,210.424,2345.52,84.738,89.784,94.2964,88.7864 11/11/2014,0.0547,1.1515,0.188,0.51021,0.0846,0.4501,0.3926,0.1353,1331.70975,212.509325,2338.6965,84.807975,89.74791,92.51151,87.110975 11/12/2014,0.054,1.147,0.1872,0.50952,0.0846,0.4469,0.3909,0.1347,1335.6815,211.5068,2337.586,84.1898,88.52546,90.44095,85.26798 11/13/2014,0.0534,1.1471,0.1872,0.51154,0.0843,0.4424,0.391,0.1348,1332.643425,216.515125,2380.2325,84.483915,85.126291,87.454904,81.925882 11/14/2014,0.053,1.143,0.1865,0.51254,0.0845,0.4394,0.3895,0.1344,1336.167,219.456,2370.582,83.8962,86.66226,89.45118,83.5533 11/17/2014,0.0532,1.1482,0.1874,0.51457,0.0845,0.4402,0.3918,0.1349,1357.7465,215.2875,2371.033,84.85198,86.849848,89.008464,83.35932 11/18/2014,0.0533,1.1467,0.1873,0.51617,0.0846,0.444,0.3917,0.1347,1367.726425,219.13437,2371.3756,85.027805,85.555287,88.123895,82.768806 11/19/2014,0.0537,1.1602,0.1895,0.51987,0.0852,0.4511,0.3965,0.1363,1387.5992,229.54557,2422.4976,85.79679,86.527716,88.87132,82.907892 11/20/2014,0.0538,1.1598,0.1893,0.52261,0.085,0.4509,0.3968,0.1362,1380.162,217.69446,2406.585,85.70922,87.657684,91.079094,84.20148 11/21/2014,0.0537,1.1537,0.1883,0.51918,0.0847,0.4584,0.3964,0.1354,1388.766375,218.799205,2395.0812,85.431485,88.154217,91.37304,85.062301 11/24/2014,0.0537,1.1603,0.1889,0.52039,0.085,0.4554,0.3979,0.1363,1389.45925,220.050895,2433.1491,85.804185,87.927534,90.607827,84.260986 11/25/2014,0.0543,1.1724,0.1911,0.52839,0.0857,0.4632,0.4023,0.1376,1405.7076,227.7387,2456.178,86.81622,86.921736,90.227904,83.427984 11/26/2014,0.0541,1.1695,0.1905,0.52906,0.0852,0.4677,0.4017,0.1373,1400.47625,226.29825,2450.1025,86.601475,86.180455,89.291325,82.47314 11/27/2014,0.0541,1.17,0.1906,0.53009,0.085,0.4625,0.4019,0.1373,1397.8575,226.395,2452.32,86.6385,86.2173,83.9124,82.5084 11/28/2014,0.053,1.1755,0.1913,0.52956,0.0844,0.4582,0.4019,0.1378,1390.322625,219.407075,2463.848,86.86945,77.759325,81.097745,73.93895 12/1/2014,0.0522,1.1774,0.1915,0.53172,0.0842,0.4606,0.402,0.138,1405.8156,222.94069,2428.9762,86.12681,81.2406,85.031828,77.308084 12/2/2014,0.0517,1.1842,0.1926,0.53082,0.084,0.4609,0.403,0.1388,1415.119,215.87966,2408.6628,85.97292,79.199296,83.651888,75.303278 12/3/2014,0.0519,1.1897,0.1934,0.53101,0.0844,0.466,0.4041,0.1382,1433.291075,217.179735,2440.0747,85.89634,80.161986,82.945884,74.915409 12/4/2014,0.0523,1.1927,0.1938,0.53391,0.0843,0.4604,0.4047,0.1395,1441.9743,216.534685,2442.6496,86.053305,79.684287,82.308227,74.555677 12/5/2014,0.0522,1.2012,0.1954,0.53116,0.0837,0.4642,0.4061,0.1406,1434.2328,215.13492,2448.0456,86.4864,79.087008,81.945864,74.126052 12/8/2014,0.052,1.2057,0.1954,0.5316,0.0838,0.4637,0.407,0.1411,1438.4001,213.469185,2428.2798,86.44869,76.019385,79.178319,71.317155 12/9/2014,0.0514,1.2058,0.1949,0.53205,0.0836,0.465,0.4079,0.141,1479.5166,216.38081,2404.3652,86.57644,76.954156,79.52251,72.094782 12/10/2014,0.0502,1.2018,0.1946,0.53063,0.0826,0.4596,0.4051,0.1406,1477.0122,213.37959,2373.555,86.10897,73.237692,76.590714,69.259734 12/11/2014,0.0503,1.2087,0.1952,0.53042,0.0818,0.4562,0.4067,0.1413,1470.081375,212.00598,2342.4606,86.845095,72.461565,75.882186,68.497029 12/12/2014,0.0504,1.2127,0.1959,0.52771,0.0821,0.4568,0.4094,0.1418,1475.8559,209.7971,2357.4888,86.70805,70.106187,74.083843,67.001675 12/15/2014,0.0501,1.2174,0.1966,0.51272,0.0825,0.4517,0.4107,0.1424,1472.14095,216.27111,2356.8864,87.10497,68.064834,72.837042,65.67873 12/16/2014,0.0501,1.2166,0.1965,0.51527,0.0825,0.4443,0.4094,0.1423,1462.9615,214.97322,2356.5542,86.74358,68.044438,71.986222,64.917776 12/17/2014,0.0512,1.2306,0.1987,0.52626,0.0845,0.4534,0.4164,0.144,1471.48995,210.24801,2356.599,87.68025,69.491982,73.700634,66.710826 12/18/2014,0.0528,1.2243,0.197,0.52708,0.084,0.46,0.4166,0.1432,1467.9357,212.599695,2340.8616,87.29259,66.246873,72.490803,65.096031 12/19/2014,0.0535,1.2277,0.1973,0.5308,0.0841,0.4617,0.4129,0.1436,1467.71535,214.47919,2327.7192,87.473625,69.389604,75.196625,68.837139 12/22/2014,0.0528,1.2296,0.1975,0.53109,0.0838,0.4616,0.4139,0.1438,1469.6794,211.67564,2279.6784,87.67048,67.578816,72.60788,65.820488 12/23/2014,0.0526,1.2337,0.1982,0.53178,0.0836,0.4577,0.4142,0.1443,1450.522775,210.9627,2309.4864,87.777755,70.19753,73.614879,67.915185 12/24/2014,0.0523,1.2328,0.1983,0.53154,0.0838,0.4575,0.4131,0.1442,1449.4646,209.76092,2297.9392,87.65208,68.592992,72.094144,66.01644 12/25/2014,0.0523,1.2317,0.1986,0.52892,0.0836,0.4565,0.4139,0.1441,1448.171275,209.573755,2295.8888,87.57387,68.531788,72.029816,65.957535 12/26/2014,0.052,1.2314,0.1982,0.53119,0.0837,0.4617,0.4135,0.144,1447.81855,207.61404,2295.3296,84.3509,67.394522,71.211862,65.153374 12/29/2014,0.0516,1.2292,0.1975,0.53027,0.0833,0.4545,0.4112,0.1437,1457.2166,203.00238,2255.582,82.6637,65.897412,69.191668,63.24234 12/30/2014,0.0514,1.2218,0.197,0.52293,0.0829,0.4599,0.4081,0.1438,1473.4908,201.35264,2285.9878,81.61624,66.123816,68.188658,62.507288 12/31/2014,0.0515,1.2239,0.1973,0.52444,0.083,0.4609,0.411,0.1447,1476.0234,203.90174,2316.8427,81.695325,65.197153,68.244664,62.761592 1/1/2015,0.0513,1.2224,0.1969,0.52443,0.0829,0.4599,0.4104,0.1444,1474.2144,203.65184,2314.0032,81.5952,65.117248,68.161024,62.684672 1/2/2015,0.052,1.2359,0.1991,0.52713,0.0833,0.4585,0.4153,0.1444,1448.4748,199.041695,2271.5842,80.95145,65.119571,68.827271,61.968026 1/5/2015,0.0509,1.2369,0.1989,0.53071,0.0828,0.4568,0.4131,0.1447,1484.28,207.92289,2336.5041,78.852375,61.894476,64.751715,57.812706 1/6/2015,0.0505,1.2368,0.1991,0.53251,0.083,0.4576,0.4142,0.1447,1496.8372,216.31632,2391.9712,77.54736,59.279824,62.112096,55.383904 1/7/2015,0.051,1.238,0.1993,0.53426,0.0841,0.462,0.414,0.1444,1498.599,216.7119,2427.718,75.3323,60.2287,62.09808,55.3386 1/8/2015,0.0513,1.2311,0.1981,0.53555,0.0839,0.4631,0.4129,0.1433,1496.40205,217.78159,2382.1785,74.60466,60.065369,61.899708,55.596476 1/9/2015,0.0504,1.2189,0.1963,0.53157,0.0835,0.4631,0.4083,0.1419,1484.315475,219.462945,2356.1337,73.25589,58.946004,60.177093,55.069902 1/12/2015,0.0507,1.226,0.1976,0.53652,0.0837,0.4586,0.4111,0.1427,1503.689,216.6955,2394.378,72.7631,56.48182,56.99674,52.25212 1/13/2015,0.0501,1.2245,0.1975,0.53582,0.0838,0.4635,0.4098,0.1426,1507.97175,216.675275,2377.979,73.041425,56.192305,56.731085,52.347375 1/14/2015,0.0506,1.2273,0.198,0.53791,0.0847,0.4689,0.4094,0.1428,1515.7155,220.729905,2415.3264,72.16524,59.499504,58.456299,54.12393 1/15/2015,0.0505,1.2162,0.1966,0.5264,0.083,0.4606,0.406,0.1415,1531.1958,214.84173,2399.5626,70.78284,56.24925,56.346546,52.807404 1/16/2015,0.0513,1.2157,0.1959,0.52243,0.0835,0.4638,0.4031,0.1413,1553.05675,207.8847,2359.6737,70.38903,59.192433,57.976733,55.666903 1/19/2015,0.0517,1.2177,0.1958,0.52081,0.0833,0.4597,0.4044,0.1415,1551.045375,208.2267,2361.1203,70.687485,59.289813,57.378024,55.758483 1/20/2015,0.0515,1.2238,0.1969,0.52147,0.0835,0.4682,0.4063,0.1421,1577.17225,201.07034,2347.2484,71.10278,56.772082,55.646186,53.675868 1/21/2015,0.052,1.2358,0.1991,0.52565,0.0838,0.4747,0.4111,0.1435,1598.5073,199.27275,2369.0286,72.47967,58.428624,57.09396,52.904598 1/22/2015,0.0525,1.2461,0.2006,0.53577,0.0851,0.4848,0.4146,0.1445,1614.634075,199.313695,2383.7893,73.02146,57.308139,57.968572,53.482612 1/23/2015,0.053,1.2641,0.2029,0.53786,0.0862,0.4893,0.4184,0.1467,1636.693475,205.353045,2405.5823,74.013055,57.162602,58.009549,53.939147 1/26/2015,0.0528,1.262,0.2018,0.53606,0.0866,0.4884,0.4171,0.1463,1616.9375,204.2547,2428.088,73.8901,56.9793,57.1055,53.2564 1/27/2015,0.0527,1.2599,0.2018,0.53289,0.0862,0.4896,0.4168,0.146,1623.38115,211.91518,2468.1441,73.83014,58.245177,58.635746,54.42768 1/28/2015,0.0536,1.2678,0.2029,0.53115,0.0859,0.4911,0.418,0.1469,1632.9264,212.61006,2488.6914,74.48325,56.35371,58.648428,53.843466 1/29/2015,0.0534,1.2881,0.2062,0.53312,0.0871,0.4945,0.4261,0.1492,1634.276875,206.096,2474.4401,75.804685,57.359093,60.347485,55.504229 1/30/2015,0.0528,1.287,0.206,0.52661,0.0859,0.4789,0.4204,0.1491,1621.94175,208.3653,2472.327,75.6756,62.08488,65.34099,59.4594 2/2/2015,0.0533,1.2817,0.2047,0.52729,0.0862,0.4697,0.4184,0.1482,1630.96325,208.212165,2457.0189,73.95409,63.533869,68.814473,62.534143 2/3/2015,0.0544,1.2835,0.2051,0.53436,0.0876,0.4755,0.42,0.1483,1622.664875,206.322625,2447.6345,75.2131,68.089675,71.349765,66.2286 2/4/2015,0.0539,1.2896,0.2064,0.52314,0.0866,0.4689,0.4218,0.149,1635.8576,212.65504,2490.2176,75.764,62.48112,68.568032,62.945376 2/5/2015,0.0539,1.2824,0.2051,0.52606,0.0867,0.4665,0.4194,0.1482,1614.8622,211.2754,2464.7728,77.96992,64.735552,71.87852,64.581664 2/6/2015,0.0539,1.2825,0.2054,0.5192,0.0864,0.4607,0.4177,0.1481,1591.5825,213.985125,2479.0725,78.553125,66.292425,73.7694,66.10005 2/9/2015,0.0542,1.2817,0.2052,0.51764,0.0864,0.4621,0.4179,0.1479,1587.38545,214.81292,2491.6248,79.144975,67.750662,73.274789,66.276707 2/10/2015,0.054,1.2868,0.2062,0.51551,0.086,0.4547,0.4172,0.1485,1588.5546,205.11592,2492.5316,79.33122,64.365736,72.433972,64.85472 2/11/2015,0.0534,1.2955,0.2075,0.51801,0.0859,0.4521,0.4203,0.1495,1585.368125,206.567475,2515.861,80.515325,63.27222,70.254965,62.9613 2/12/2015,0.0541,1.2928,0.207,0.52414,0.0866,0.4568,0.4213,0.1492,1580.448,212.73024,2570.0864,81.1232,66.204288,73.741312,65.35104 2/13/2015,0.054,1.2883,0.2064,0.52475,0.0864,0.4543,0.4179,0.1486,1587.82975,210.25056,2588.1947,80.454335,67.996474,76.537903,70.676138 2/16/2015,0.0538,1.2866,0.206,0.52384,0.0862,0.4534,0.4171,0.1482,1581.55305,209.97312,2625.9506,80.47683,67.906748,77.041608,70.582876 2/17/2015,0.0529,1.2791,0.2046,0.52168,0.0858,0.452,0.4147,0.1474,1547.07145,199.091915,2549.2463,79.879795,68.470223,78.319293,71.220288 2/18/2015,0.0527,1.2803,0.2047,0.52396,0.0861,0.4506,0.4149,0.1473,1544.0418,195.62984,2528.5925,79.954735,66.754842,74.935959,68.62408 2/19/2015,0.0525,1.2834,0.2052,0.52234,0.0855,0.4477,0.4158,0.1476,1552.2723,191.48328,2511.6138,79.5708,65.658744,76.156956,68.6619 2/20/2015,0.0519,1.275,0.2038,0.51989,0.0848,0.4446,0.4132,0.1465,1540.51875,189.52875,2476.05,79.36875,64.1835,76.23225,68.34 2/23/2015,0.0513,1.2815,0.2048,0.51792,0.0849,0.4453,0.4145,0.1473,1543.56675,185.112675,2454.0725,79.517075,62.216825,75.057455,66.497035 2/24/2015,0.0514,1.277,0.2041,0.51842,0.0856,0.4512,0.4129,0.1469,1522.8225,185.61195,2405.868,78.85475,62.03666,74.46187,65.86766 2/25/2015,0.051,1.268,0.2026,0.50969,0.0849,0.4419,0.41,0.1455,1527.623,177.203,2345.8,78.1088,63.89452,77.7284,69.27084 2/26/2015,0.0515,1.282,0.2049,0.51196,0.0855,0.4412,0.4146,0.1469,1548.9765,175.0571,2351.188,79.2276,61.75394,76.52258,68.70238 2/27/2015,0.0512,1.2802,0.2042,0.51011,0.0857,0.4505,0.4142,0.1468,1554.1628,175.06735,2395.2542,79.11636,63.702752,79.129162,70.47501 3/2/2015,0.0508,1.2878,0.2053,0.51161,0.0858,0.4448,0.4163,0.1475,1561.4575,173.98178,2404.3226,81.26018,63.862002,78.388386,68.06023 3/3/2015,0.0501,1.2793,0.2039,0.50433,0.0853,0.4363,0.4137,0.1464,1551.471075,161.511625,2376.9394,79.764355,64.630236,78.075679,69.286888 3/4/2015,0.0503,1.2792,0.204,0.49911,0.085,0.4293,0.4135,0.1463,1534.4004,171.47676,2346.0528,80.33376,65.917176,76.892712,68.232528 3/5/2015,0.0504,1.285,0.2051,0.49247,0.0846,0.4279,0.4153,0.1469,1544.57,169.04175,2364.4,80.441,65.2266,77.2542,69.647 3/6/2015,0.0502,1.296,0.2069,0.49408,0.0836,0.4228,0.4189,0.148,1523.772,176.904,2393.712,79.8984,64.29456,76.9176,69.0768 3/9/2015,0.05,1.2983,0.2072,0.49906,0.0839,0.4158,0.4185,0.1482,1517.06355,173.517795,2399.2584,80.429685,64.915,75.483162,66.291198 3/10/2015,0.0499,1.3114,0.2094,0.49724,0.0839,0.4226,0.4231,0.1495,1523.8468,172.71138,2401.1734,81.17566,63.327506,73.281032,64.337284 3/11/2015,0.0502,1.3165,0.2102,0.50463,0.085,0.421,0.4249,0.15,1513.975,169.0386,2373.6495,81.75465,63.415805,75.27747,66.29894 3/12/2015,0.0494,1.2974,0.2072,0.50205,0.0843,0.4098,0.4185,0.1478,1494.92915,167.16999,2271.7474,80.56854,61.04267,73.095516,64.506728 3/13/2015,0.0494,1.3095,0.2092,0.49606,0.0846,0.4029,0.4229,0.1492,1508.544,165.586275,2207.817,81.123525,58.71798,70.490385,61.769115 3/16/2015,0.0487,1.309,0.2091,0.49834,0.0849,0.4033,0.4226,0.149,1506.33175,176.5841,2276.351,80.5035,57.43892,68.86649,60.13546 3/17/2015,0.0494,1.3128,0.2101,0.50278,0.0854,0.4053,0.4236,0.1494,1510.7046,175.84956,2302.6512,80.54028,57.054288,67.386024,60.3888 3/18/2015,0.0489,1.2862,0.2064,0.50035,0.0852,0.4006,0.417,0.1463,1475.59295,175.24475,2308.729,79.03699,57.441692,69.827798,63.062386 3/19/2015,0.0497,1.3072,0.211,0.50204,0.0856,0.3972,0.4218,0.1487,1524.1952,183.008,2341.1952,79.7392,57.464512,68.549568,61.190032 3/20/2015,0.0499,1.2863,0.2072,0.49975,0.0854,0.3981,0.4168,0.1462,1521.82153,184.391105,2310.1948,78.399985,58.809636,68.418297,63.620398 3/23/2015,0.0495,1.2689,0.2042,0.4991,0.085,0.4049,0.4126,0.1442,1505.232625,179.993465,2300.5157,77.27601,59.447965,68.254131,63.495756 3/24/2015,0.0505,1.2693,0.2046,0.4975,0.0849,0.4044,0.4137,0.1443,1512.37095,174.27489,2275.8549,77.30037,59.796723,67.552146,62.754192 3/25/2015,0.0502,1.2748,0.2052,0.49267,0.0851,0.3981,0.4156,0.1449,1524.15088,178.40826,2283.1668,77.7628,62.031768,69.298128,64.670604 3/26/2015,0.0499,1.2774,0.2056,0.49087,0.0844,0.4013,0.4143,0.145,1536.90381,179.15535,2287.8234,77.79366,65.696682,72.607416,68.110968 3/27/2015,0.0504,1.2907,0.2076,0.49426,0.0847,0.3972,0.4174,0.1463,1543.354525,178.37474,2275.5041,78.797235,63.076509,70.162452,65.219071 3/30/2015,0.0507,1.3066,0.2105,0.50127,0.0856,0.4046,0.4219,0.1482,1548.9743,172.92851,2217.3002,77.35072,63.605288,71.588614,65.682782 3/31/2015,0.0506,1.3147,0.212,0.5061,0.0862,0.4113,0.425,0.1491,1560.5489,174.72363,2231.0459,77.370095,62.57972,70.126098,64.367712 4/1/2015,0.0511,1.3158,0.2123,0.50629,0.0868,0.4157,0.425,0.149,1575.0126,177.43563,2302.65,77.23746,65.908422,73.434798,66.592638 4/2/2015,0.0512,1.3171,0.2125,0.50949,0.0878,0.4216,0.4252,0.1492,1578.54435,185.57939,2341.8038,77.116205,64.722294,71.426333,64.643268 4/3/2015,0.051,1.3106,0.2116,0.50955,0.0884,0.4219,0.4236,0.1484,1570.7541,184.66354,2330.2468,76.73563,64.402884,71.113156,64.324248 4/6/2015,0.052,1.3176,0.2127,0.51243,0.0883,0.4214,0.4269,0.1491,1579.1436,192.63312,2342.6928,77.14548,68.699664,75.221784,68.225328 4/7/2015,0.0521,1.3098,0.2113,0.50344,0.0877,0.4186,0.4226,0.1481,1586.1678,185.92611,2365.4988,75.50997,70.703004,75.745734,69.22293 4/8/2015,0.0522,1.3013,0.2098,0.50066,0.0873,0.4268,0.4193,0.1471,1570.994425,176.58641,2329.327,74.69462,65.611546,71.922851,64.921857 4/9/2015,0.052,1.3,0.2095,0.4963,0.0862,0.425,0.4171,0.147,1553.24,178.685,2328.3,75.92,66.027,72.566,66.677 4/10/2015,0.052,1.3023,0.2097,0.49542,0.0855,0.4233,0.4178,0.1472,1572.331905,175.94073,2361.0699,76.900815,67.250772,74.673882,68.487957 4/13/2015,0.0516,1.3176,0.212,0.4934,0.0857,0.4219,0.4226,0.1487,1579.67064,176.229,2357.1864,78.52896,68.396616,74.70792,69.661512 4/14/2015,0.0513,1.3112,0.2111,0.48777,0.0859,0.4281,0.4202,0.148,1566.5562,176.48752,2350.9816,78.0164,69.873848,75.512008,70.188536 4/15/2015,0.0519,1.3018,0.2098,0.48234,0.0852,0.4298,0.4167,0.1468,1552.91722,176.78444,2335.4292,77.58728,73.408502,78.36836,73.668862 4/16/2015,0.0516,1.2815,0.2068,0.47839,0.0845,0.4243,0.4103,0.1443,1543.374525,178.8974,2301.574,76.825925,72.673865,79.65804,74.81397 4/17/2015,0.0514,1.2849,0.2073,0.47975,0.0838,0.4226,0.4104,0.1448,1546.184415,178.21563,2311.5351,77.029755,71.620326,78.648729,74.845425 4/20/2015,0.0521,1.2945,0.2087,0.47968,0.0837,0.4271,0.4137,0.146,1548.86925,179.54715,2335.278,77.54055,72.98391,79.19751,74.97744 4/21/2015,0.0525,1.2969,0.2091,0.48289,0.084,0.4279,0.414,0.1461,1550.18457,181.95507,2335.7169,77.489775,71.666694,76.932108,73.910331 4/22/2015,0.0517,1.2895,0.2082,0.47561,0.0835,0.4284,0.4118,0.1453,1533.537875,183.6248,2346.89,76.789725,70.99987,78.06633,74.24941 4/23/2015,0.0521,1.2857,0.2074,0.47595,0.0837,0.4328,0.4101,0.1445,1524.518775,180.576565,2328.4027,76.62772,72.757763,80.510534,76.550578 4/24/2015,0.0521,1.2783,0.2063,0.47062,0.0832,0.4332,0.4077,0.1434,1512.2289,180.432045,2294.5485,76.250595,71.009565,81.338229,76.710783 4/27/2015,0.0528,1.2724,0.2046,0.4757,0.0829,0.4362,0.4058,0.1428,1526.88,173.17364,2201.252,75.58056,72.514076,79.626792,75.606008 4/28/2015,0.0519,1.2466,0.2009,0.4689,0.0817,0.424,0.398,0.14,1507.1394,172.21779,2170.3306,74.04804,71.130996,78.124422,74.04804 4/29/2015,0.0525,1.2485,0.2014,0.46918,0.082,0.4217,0.4004,0.1404,1509.4365,172.729975,2171.1415,74.847575,73.13713,79.47951,75.23461 4/30/2015,0.0531,1.265,0.2039,0.47333,0.0824,0.4197,0.404,0.142,1493.01625,172.73575,2216.28,75.647,75.43195,82.0479,77.4939 5/1/2015,0.0533,1.2737,0.2054,0.47037,0.0819,0.4238,0.4067,0.143,1497.807515,169.975265,2206.0484,76.29463,75.339355,83.29998,78.141495 5/4/2015,0.053,1.2759,0.2055,0.47016,0.0826,0.4135,0.405,0.1433,1500.394605,168.227415,2209.8588,76.42641,75.188787,83.367306,78.123357 5/5/2015,0.0527,1.2591,0.2029,0.46561,0.0821,0.4121,0.3996,0.1414,1507.1427,166.893705,2184.5385,75.734865,76.04964,83.566467,78.378975 5/6/2015,0.0531,1.2552,0.2024,0.46609,0.0817,0.4137,0.3983,0.1405,1499.0226,160.72836,2123.7984,75.312,76.479336,83.119344,78.123648 5/7/2015,0.0533,1.2647,0.2038,0.47099,0.0826,0.418,0.4013,0.1417,1501.1989,165.485995,2122.1666,75.439355,74.541418,81.130505,76.109646 5/8/2015,0.0535,1.2604,0.203,0.46751,0.0834,0.4236,0.4007,0.141,1494.8344,167.50716,2164.1068,75.05682,74.855156,81.056324,76.178576 5/11/2015,0.0531,1.2673,0.2041,0.47048,0.0825,0.4139,0.402,0.1418,1507.136525,168.994455,2155.6773,75.40435,75.087525,80.942451,75.885924 5/12/2015,0.0526,1.2536,0.2019,0.47067,0.0817,0.4151,0.3977,0.1403,1493.6644,168.6092,2116.0768,74.40116,76.1562,83.101144,77.046256 5/13/2015,0.0516,1.2326,0.1987,0.46852,0.0807,0.4056,0.3911,0.1377,1492.0623,165.66144,2072.0006,73.15481,74.5723,81.142058,75.385816 5/14/2015,0.0518,1.2375,0.1996,0.47776,0.082,0.4133,0.393,0.1383,1515.9375,167.866875,2108.7,73.198125,74.1015,81.35325,75.438 5/15/2015,0.0515,1.2446,0.2005,0.48281,0.083,0.4153,0.3955,0.139,1519.0343,170.75912,2117.0646,73.49363,74.290174,81.882234,76.692252 5/18/2015,0.0515,1.2515,0.2017,0.4851,0.0828,0.4162,0.397,0.1398,1531.21025,177.274975,2162.592,73.901075,74.376645,82.07337,76.479165 5/19/2015,0.0509,1.2635,0.2036,0.48714,0.0832,0.4159,0.4007,0.1413,1534.26805,176.700475,2159.3215,74.42015,72.34801,79.80266,75.064535 5/20/2015,0.051,1.2698,0.2047,0.49253,0.0836,0.4229,0.402,0.1416,1537.0929,172.6928,2142.1526,74.79122,74.257904,80.835468,76.238792 5/21/2015,0.0511,1.2665,0.2044,0.48925,0.0832,0.4168,0.4046,0.1412,1526.1325,162.681925,2082.126,74.406875,75.952005,82.816435,78.11772 5/22/2015,0.0513,1.2777,0.206,0.49129,0.0837,0.4132,0.4058,0.1422,1538.47857,162.204015,2030.2653,75.064875,75.409854,82.769406,77.671383 5/25/2015,0.0513,1.2781,0.2061,0.48873,0.0838,0.4123,0.4055,0.1422,1538.96021,162.254795,2030.9009,75.088375,75.433462,83.229872,77.695699 5/26/2015,0.0508,1.2928,0.2084,0.48931,0.0845,0.41,0.4101,0.144,1532.48512,160.37184,1987.0336,75.952,75.021184,80.787072,75.835648 5/27/2015,0.051,1.2939,0.2086,0.48974,0.0846,0.412,0.4102,0.1441,1534.371315,161.09055,2044.362,76.08132,74.412189,79.05729,73.907568 5/28/2015,0.0515,1.3072,0.2108,0.49252,0.0854,0.4134,0.4141,0.1453,1549.032,163.59608,2070.6048,76.86336,75.399296,80.144432,75.216288 5/29/2015,0.0517,1.3081,0.2111,0.49081,0.0851,0.4117,0.4155,0.1453,1558.47034,165.016815,2072.0304,76.981685,78.87843,83.574509,78.87843 6/1/2015,0.0516,1.3147,0.2121,0.4901,0.0849,0.4147,0.4166,0.1459,1577.50853,170.64806,2233.6753,75.792455,79.14494,84.285417,78.724236 6/2/2015,0.0504,1.2866,0.2076,0.48111,0.0834,0.4108,0.4075,0.1429,1534.65648,170.73182,2216.8118,74.88012,78.817116,82.869906,77.942228 6/3/2015,0.0498,1.2843,0.2072,0.47833,0.0828,0.4096,0.4077,0.1425,1528.317,172.48149,2212.8489,73.71882,76.595652,80.474238,76.094775 6/4/2015,0.0501,1.3007,0.2098,0.48761,0.0837,0.4152,0.4137,0.1442,1529.6232,176.50499,2258.0152,74.00983,75.4406,79.381721,74.92032 6/5/2015,0.05,1.3113,0.2114,0.49265,0.0834,0.4172,0.4161,0.1452,1527.13998,177.15663,2265.9264,74.48184,77.537169,81.536634,76.815954 6/8/2015,0.0497,1.2984,0.2092,0.47188,0.0831,0.4169,0.4115,0.1438,1522.76352,177.29652,2238.4416,73.74912,75.488976,79.812648,75.398088 6/9/2015,0.0509,1.3003,0.2095,0.47237,0.0834,0.4197,0.4122,0.1441,1530.97322,178.596205,2254.7202,73.792025,78.200042,83.518269,77.900973 6/10/2015,0.051,1.2881,0.2076,0.47099,0.0834,0.4132,0.4084,0.1427,1530.90685,175.761245,2241.294,73.16408,79.127983,83.198379,78.599862 6/11/2015,0.0509,1.2895,0.2078,0.47717,0.084,0.4173,0.4088,0.1428,1519.67575,170.214,2206.3345,73.88835,78.362915,82.24431,77.847115 6/12/2015,0.0512,1.2936,0.2083,0.47672,0.084,0.4146,0.4099,0.1431,1530.07008,170.81988,2227.5792,74.7054,77.564256,81.095784,76.348272 6/15/2015,0.0507,1.2877,0.2074,0.47077,0.0834,0.4118,0.4074,0.1425,1521.28878,164.56806,2259.9135,74.55783,76.643904,80.185079,75.214557 6/16/2015,0.0508,1.2899,0.2078,0.47175,0.0838,0.4175,0.4084,0.1424,1519.179725,166.848565,2312.7907,74.620715,77.355303,80.10279,76.129898 6/17/2015,0.0506,1.2903,0.2078,0.47645,0.0846,0.4226,0.4076,0.1422,1519.9734,163.416495,2330.2818,74.8374,77.314776,79.366353,76.192215 6/18/2015,0.0504,1.2821,0.2065,0.47263,0.0836,0.419,0.4063,0.1416,1540.891885,165.00627,2420.6048,74.3618,77.502945,80.669732,76.195203 6/19/2015,0.0504,1.2868,0.2072,0.47741,0.0838,0.4155,0.4063,0.1421,1548.53512,163.61662,2401.1688,74.6344,76.706148,78.211704,74.801684 6/22/2015,0.051,1.294,0.2084,0.48517,0.0844,0.4201,0.4078,0.1428,1534.037,168.6729,2402.958,75.4402,77.22592,79.17986,75.73782 6/23/2015,0.0507,1.2925,0.2083,0.48249,0.0839,0.4204,0.4061,0.1427,1522.565,165.05225,2360.105,75.158875,78.55815,80.639075,77.2398 6/24/2015,0.0507,1.298,0.2091,0.48468,0.0837,0.4189,0.409,0.1431,1523.5275,173.0234,2475.286,75.4138,78.03576,80.57984,76.2575 6/25/2015,0.0505,1.2923,0.2081,0.48677,0.0835,0.4132,0.4073,0.1422,1515.415595,172.328205,2434.6932,75.21186,76.956465,80.1226,75.366936 6/26/2015,0.0505,1.3063,0.2103,0.48997,0.084,0.4174,0.4117,0.1436,1529.02415,172.03971,2513.3212,76.02666,77.894669,80.141505,76.105038 6/29/2015,0.0503,1.3022,0.2097,0.48162,0.083,0.4178,0.4098,0.1433,1531.3872,170.32776,2463.7624,76.96002,75.957326,78.796122,74.238422 6/30/2015,0.0498,1.2975,0.2093,0.48405,0.0825,0.4182,0.4084,0.1426,1519.3725,169.518375,2445.7875,78.1095,77.162325,79.6146,75.6183 7/1/2015,0.0496,1.308,0.2109,0.4859,0.0829,0.4153,0.411,0.1438,1527.744,163.6308,2371.404,78.153,74.50368,79.63104,74.24208 7/2/2015,0.0497,1.3103,0.2112,0.48808,0.0837,0.4231,0.4125,0.1439,1526.827075,164.57368,2456.8125,77.96285,74.595379,79.640034,74.176083 7/3/2015,0.0505,1.3295,0.2143,0.49461,0.0845,0.4241,0.4195,0.1462,1552.789525,166.9852,2463.5635,78.374025,75.688435,79.145135,75.262995 7/6/2015,0.0499,1.3334,0.2148,0.49792,0.0849,0.425,0.4196,0.1463,1554.7444,164.40822,2458.7896,78.0039,70.043502,74.163708,69.296798 7/7/2015,0.0498,1.3419,0.2161,0.49951,0.085,0.4212,0.4215,0.1474,1551.571875,164.91951,2471.7798,78.031485,70.221627,75.763674,70.422912 7/8/2015,0.0502,1.346,0.2168,0.50073,0.0849,0.4158,0.423,0.1476,1559.341,165.7599,2483.37,78.5391,69.5209,75.76634,70.44964 7/9/2015,0.0502,1.3429,0.2163,0.5013,0.0849,0.4169,0.4223,0.1473,1563.471325,164.840975,2491.0795,78.55965,70.878262,77.418185,72.006298 7/10/2015,0.0502,1.3431,0.2163,0.50335,0.0855,0.4251,0.4236,0.1469,1557.05583,165.134145,2484.735,78.907125,70.835094,77.966955,72.379659 7/13/2015,0.0503,1.3503,0.2175,0.51032,0.086,0.4308,0.425,0.148,1558.2462,170.94798,2516.9592,79.060065,70.48566,77.304675,71.957487 7/14/2015,0.05,1.342,0.2161,0.50994,0.0857,0.4273,0.4221,0.1469,1553.2308,174.2587,2505.514,78.5741,71.17968,77.47366,71.83726 7/15/2015,0.0499,1.3552,0.2182,0.51213,0.0859,0.4317,0.4256,0.1484,1554.95648,173.4656,2509.8304,79.07592,69.670832,76.243552,70.565264 7/16/2015,0.0496,1.3504,0.2175,0.50836,0.0853,0.4279,0.4252,0.1479,1545.39776,172.10848,2479.3344,78.79584,68.748864,76.23008,70.274816 7/17/2015,0.0492,1.3561,0.2184,0.5114,0.0851,0.4254,0.426,0.1486,1536.19008,172.2247,2435.5556,79.19624,69.011929,76.402674,71.141006 7/20/2015,0.0491,1.3565,0.2184,0.50277,0.0847,0.424,0.4259,0.148,1498.3899,170.715525,2459.3345,79.423075,68.028475,75.50279,70.361655 7/21/2015,0.0487,1.3478,0.217,0.50211,0.0842,0.425,0.4237,0.1469,1490.12768,166.92503,2427.3878,78.98108,67.875208,75.625058,71.339054 7/22/2015,0.0486,1.3556,0.2183,0.50073,0.0842,0.4207,0.4251,0.1478,1475.70616,169.51778,2467.192,79.43816,66.248172,75.059572,70.260748 7/23/2015,0.048,1.3594,0.2189,0.49661,0.0838,0.4137,0.4264,0.1482,1491.80556,165.23507,2446.92,79.5249,65.59105,74.196052,69.682844 7/24/2015,0.0482,1.3733,0.2211,0.50167,0.0844,0.4096,0.4309,0.1496,1484.26264,167.885925,2456.8337,80.406715,65.904667,73.897273,69.557645 7/27/2015,0.0481,1.3756,0.2215,0.49633,0.0844,0.409,0.4319,0.1498,1513.16,165.62224,2423.8072,80.54138,65.189684,71.765052,67.26684 7/28/2015,0.0476,1.363,0.2195,0.49382,0.0838,0.406,0.4279,0.1486,1494.1206,163.90075,2400.243,79.66735,65.39674,71.23038,66.97782 7/29/2015,0.0481,1.3707,0.2208,0.49551,0.0842,0.4115,0.4305,0.1493,1494.405675,167.431005,2411.0613,80.117415,66.876453,72.23589,68.26086 7/30/2015,0.0477,1.3713,0.2208,0.4927,0.0843,0.4066,0.4293,0.1492,1491.28875,171.27537,2432.6862,80.152485,66.535476,71.842407,67.865637 7/31/2015,0.0475,1.3687,0.2205,0.49413,0.085,0.3999,0.4299,0.1488,1503.38008,171.429675,2428.0738,80.000515,64.493144,69.215159,65.574417 8/3/2015,0.047,1.3726,0.221,0.49361,0.0848,0.3977,0.4307,0.1491,1498.74194,170.13377,2230.475,77.41464,62.000342,67.161318,62.823902 8/4/2015,0.0466,1.3553,0.2182,0.48688,0.0832,0.3905,0.4243,0.1473,1478.157945,169.27697,2221.3367,77.319865,61.991422,66.95182,62.709731 8/5/2015,0.0461,1.3595,0.2189,0.4878,0.083,0.39,0.4245,0.1476,1475.19345,171.16105,2247.2535,78.17125,61.381425,66.47955,62.23791 8/6/2015,0.0463,1.361,0.2192,0.49033,0.0834,0.3849,0.4242,0.1477,1483.14975,169.10425,2232.04,78.73385,60.78226,66.77066,62.15687 8/7/2015,0.0459,1.3479,0.2171,0.48478,0.0834,0.3841,0.4204,0.146,1473.92865,172.26162,2238.8619,77.032485,59.132373,64.766595,60.291567 8/10/2015,0.0464,1.349,0.2172,0.4854,0.0835,0.3924,0.4209,0.1463,1479.853,180.0915,2283.857,77.4326,60.65104,66.80248,62.44521 8/11/2015,0.0466,1.369,0.2164,0.49243,0.0839,0.3941,0.4253,0.1484,1517.19425,187.8268,2361.525,77.2116,58.97652,66.60185,60.08541 8/12/2015,0.0461,1.3552,0.2122,0.48787,0.0833,0.3892,0.4195,0.1468,1516.4688,178.68312,2302.4848,76.43328,58.68016,66.919776,59.926944 8/13/2015,0.0456,1.3586,0.2124,0.4819,0.0829,0.3861,0.4185,0.1471,1517.21655,186.19613,2315.0544,76.82883,57.373678,66.041546,59.126272 8/14/2015,0.0453,1.355,0.2121,0.47835,0.0828,0.3891,0.4182,0.1466,1515.22875,186.3125,2321.115,76.2865,57.5875,64.1186,57.8314 8/17/2015,0.0452,1.3565,0.2121,0.47294,0.0826,0.3898,0.4182,0.1468,1517.6522,182.788375,2311.476,76.37095,56.796655,64.46088,58.912795 8/18/2015,0.0454,1.3622,0.213,0.47053,0.083,0.3929,0.419,0.1473,1514.01719,184.30566,2357.9682,76.35131,58.056964,64.758988,58.969638 8/19/2015,0.045,1.3609,0.2128,0.46512,0.0818,0.3897,0.4172,0.1468,1532.577535,178.482035,2271.3421,76.142355,55.52472,61.64877,56.88562 8/20/2015,0.0445,1.3628,0.2133,0.46727,0.0811,0.3938,0.4171,0.1472,1564.08556,173.96142,2233.6292,76.24866,56.065592,61.407768,55.73852 8/21/2015,0.0441,1.3666,0.214,0.46814,0.0805,0.3905,0.4174,0.1476,1580.4729,166.58854,2212.5254,76.39294,54.991984,60.567712,54.882656 8/24/2015,0.0432,1.3975,0.2182,0.47476,0.0812,0.3931,0.4266,0.1507,1630.18375,164.20625,2234.6025,77.9805,53.230775,56.93415,52.140725 8/25/2015,0.0437,1.4027,0.2187,0.47732,0.0815,0.3878,0.4265,0.1512,1595.57125,164.186035,2219.0714,78.27066,54.887651,58.35232,53.050114 8/26/2015,0.0431,1.4041,0.2191,0.47868,0.0825,0.3905,0.4248,0.1513,1573.645075,166.66667,2219.8821,78.34878,54.19826,58.536929,53.889358 8/27/2015,0.0441,1.3954,0.2179,0.4798,0.0827,0.3927,0.4258,0.1502,1561.4526,168.91317,2242.4078,77.86332,59.388224,63.825596,58.760294 8/28/2015,0.0453,1.3938,0.2182,0.4767,0.0832,0.3892,0.4322,0.1501,1581.963,167.88321,2203.5978,77.77404,63.027636,67.278726,62.497992 8/31/2015,0.0459,1.4057,0.2204,0.4823,0.0839,0.3882,0.4343,0.1512,1595.4695,169.457135,2222.4117,77.243215,69.16044,72.084296,67.698512 9/1/2015,0.0458,1.4248,0.2239,0.48627,0.084,0.385,0.4383,0.153,1627.54904,166.77284,2255.4584,78.29276,64.700168,67.763488,62.6912 9/2/2015,0.0448,1.4207,0.2236,0.48297,0.0844,0.378,0.4367,0.1527,1616.401425,162.95429,2239.0232,77.925395,65.707375,70.60879,64.229847 9/3/2015,0.0458,1.425,0.2242,0.47966,0.0848,0.3809,0.4447,0.1529,1607.4,165.585,2258.625,78.58875,66.61875,71.20725,65.02275 9/4/2015,0.0463,1.4471,0.2276,0.48115,0.0854,0.3766,0.4502,0.1551,1618.219575,167.646535,2299.4419,78.939305,66.638955,70.444828,64.39595 9/7/2015,0.0457,1.4442,0.2269,0.47633,0.085,0.3757,0.4473,0.1551,1616.7819,167.31057,2274.615,77.48133,66.50541,67.73298,64.2669 9/8/2015,0.0458,1.4251,0.2238,0.47322,0.0847,0.3731,0.442,0.1527,1597.750865,167.73427,2260.2086,76.81289,65.469094,68.746824,63.13193 9/9/2015,0.0458,1.4248,0.2234,0.4694,0.0847,0.3769,0.4426,0.1525,1581.31428,167.84144,2272.556,76.36928,62.90492,66.238952,60.724976 9/10/2015,0.0463,1.4139,0.2217,0.46784,0.0843,0.3673,0.4399,0.1511,1568.72205,159.841395,2201.4423,76.06782,64.926288,67.980312,61.64604 9/11/2015,0.0464,1.4103,0.2212,0.46305,0.0837,0.3643,0.4394,0.1508,1551.682575,159.857505,2176.0929,75.944655,62.941689,66.862323,58.583862 9/14/2015,0.0463,1.4009,0.22,0.45818,0.0837,0.3671,0.4364,0.1497,1547.71432,163.9053,2216.2238,75.158285,61.6396,63.768968,57.030639 9/15/2015,0.0463,1.4003,0.2198,0.46223,0.0839,0.3627,0.4367,0.1494,1548.661785,161.73465,2204.0722,74.986065,62.439377,64.581836,57.622345 9/16/2015,0.0468,1.3895,0.2181,0.46335,0.084,0.3627,0.434,0.1482,1552.9052,158.1251,2194.0205,75.241425,65.514925,66.626525,60.901785 9/17/2015,0.0467,1.3937,0.219,0.46266,0.084,0.3576,0.4364,0.1486,1557.45975,158.18495,2179.7468,75.468855,65.36453,66.354057,60.138155 9/18/2015,0.0466,1.3905,0.2186,0.46293,0.0835,0.3526,0.4361,0.1482,1587.25575,157.613175,2163.618,75.22605,62.12754,64.171575,57.8448 9/21/2015,0.0466,1.4022,0.2201,0.46638,0.0842,0.3519,0.4387,0.1491,1589.04315,164.40795,2149.5726,75.7188,65.454696,65.805246,60.01416 9/22/2015,0.0459,1.4105,0.2212,0.46615,0.0835,0.3483,0.4383,0.1502,1583.85045,162.842225,2131.2655,76.02595,64.643215,66.60381,59.63594 9/23/2015,0.0458,1.4279,0.2236,0.4699,0.0834,0.3418,0.4436,0.152,1615.454665,165.92198,2198.966,76.96381,63.355923,65.569168,58.68669 9/24/2015,0.0456,1.4236,0.223,0.46823,0.0844,0.3605,0.4431,0.1515,1643.5462,168.41188,2229.3576,76.66086,63.763044,66.325524,59.093636 9/25/2015,0.0463,1.4231,0.2233,0.46753,0.0839,0.3582,0.4416,0.1512,1631.797615,174.61437,2271.2676,76.633935,65.03567,66.416077,59.215191 9/28/2015,0.0458,1.4307,0.2246,0.46785,0.0838,0.348,0.4421,0.152,1618.193235,170.467905,2207.5701,74.467935,63.566001,65.611902,58.014885 9/29/2015,0.046,1.4318,0.2251,0.4715,0.0841,0.3525,0.4422,0.152,1620.94078,173.03303,2249.3578,74.59678,64.760314,66.521428,59.06175 9/30/2015,0.0461,1.4251,0.2243,0.47099,0.0842,0.361,0.4403,0.1512,1587.5614,172.935885,2211.7552,73.25014,64.257759,67.164963,59.341164 10/1/2015,0.0465,1.4225,0.2238,0.46996,0.084,0.3548,0.4405,0.1509,1591.7775,171.766875,2213.41,72.5475,63.64265,67.127775,58.422075 10/2/2015,0.0469,1.4188,0.2232,0.47426,0.0847,0.3607,0.4402,0.1503,1618.4961,176.35684,2238.8664,72.50068,64.612152,67.265308,58.539688 10/5/2015,0.0477,1.4119,0.2221,0.4732,0.0841,0.3609,0.4387,0.1495,1609.213025,180.087845,2271.7471,73.4188,65.314494,68.463031,59.850441 10/6/2015,0.0479,1.3956,0.2196,0.47181,0.0838,0.3623,0.4333,0.1476,1601.451,178.77636,2232.96,73.47834,67.728468,71.831532,62.17398 10/7/2015,0.0479,1.3874,0.2183,0.4719,0.0833,0.357,0.4303,0.1468,1588.01804,174.88177,2162.9566,72.49165,66.331594,71.062628,61.031726 10/8/2015,0.048,1.378,0.2169,0.47621,0.0837,0.364,0.427,0.1465,1570.92,177.0041,2179.996,71.8627,68.11454,72.63438,62.80924 10/9/2015,0.0477,1.3634,0.2148,0.46813,0.083,0.3625,0.4245,0.1443,1570.02327,179.42344,2212.7982,71.44216,67.665542,70.937702,61.134856 10/12/2015,0.0473,1.3582,0.2148,0.46398,0.0825,0.3608,0.4208,0.1438,1582.16718,182.6779,2204.3586,70.69431,63.97122,67.461794,57.872902 10/13/2015,0.0474,1.3804,0.2177,0.4665,0.0829,0.3546,0.4259,0.1457,1608.44208,185.45674,2222.444,71.64276,64.409464,66.852772,56.030436 10/14/2015,0.0468,1.3697,0.2158,0.47016,0.0832,0.3593,0.4237,0.1447,1607.89083,184.430105,2233.9807,70.745005,63.882808,65.512751,55.774184 10/15/2015,0.0469,1.3645,0.215,0.47369,0.0832,0.3591,0.4226,0.1439,1615.909125,182.43365,2274.6215,70.612875,63.28551,66.410215,56.040015 10/16/2015,0.0477,1.3766,0.2166,0.47556,0.0838,0.3506,0.4234,0.1448,1625.55811,173.24511,2220.4558,71.37671,65.058116,67.508464,57.968626 10/19/2015,0.0473,1.3796,0.2169,0.47474,0.0837,0.355,0.425,0.1453,1621.58184,170.93244,2182.5272,71.53226,63.309844,65.641368,55.791024 10/20/2015,0.0469,1.3774,0.217,0.47494,0.0832,0.3528,0.4236,0.1456,1622.23285,171.83065,2144.6118,71.48706,62.74057,64.434772,55.591864 10/21/2015,0.0469,1.387,0.2185,0.479,0.0833,0.3521,0.4255,0.1458,1618.7677,167.827,2154.011,71.9853,61.92955,63.71878,54.93907 10/22/2015,0.0478,1.3873,0.2182,0.48291,0.0842,0.3551,0.4262,0.1459,1618.9791,166.267905,2166.9626,72.070235,62.192659,64.218117,55.492 10/23/2015,0.0475,1.3857,0.2182,0.47649,0.0835,0.3575,0.4236,0.1456,1609.144125,164.136165,2115.9639,72.264255,60.485805,63.797628,54.901434 10/26/2015,0.0471,1.3795,0.2172,0.47718,0.0835,0.3534,0.4219,0.1448,1609.0488,161.81535,2102.358,72.354775,60.67041,62.670685,54.02122 10/27/2015,0.0472,1.3904,0.2188,0.47856,0.084,0.3575,0.4239,0.1461,1620.78928,163.09392,2121.7504,73.20456,60.06528,62.679232,53.655536 10/28/2015,0.0482,1.4062,0.2212,0.48087,0.0845,0.36,0.4291,0.1476,1658.75352,167.47842,2165.548,73.89581,64.600828,66.358578,56.768294 10/29/2015,0.0485,1.4138,0.2224,0.48113,0.085,0.3673,0.4305,0.1485,1623.89068,170.08014,2214.0108,74.2245,65.119628,65.911356,56.325792 10/30/2015,0.0484,1.401,0.2218,0.4806,0.0849,0.3634,0.426,0.1472,1600.43235,169.45095,2264.016,73.48245,65.27259,66.71562,56.95065 11/2/2015,0.0483,1.3993,0.2208,0.49558,0.0851,0.3629,0.4256,0.1467,1586.8062,166.23684,2231.8835,74.44276,64.563702,66.872547,56.153909 11/3/2015,0.0497,1.3916,0.2197,0.49188,0.0849,0.3689,0.4243,0.1458,1562.90596,167.3399,2237.6928,74.58976,66.65764,68.04924,58.252376 11/4/2015,0.0493,1.3989,0.2208,0.4887,0.0846,0.3681,0.4263,0.1467,1559.35383,168.56745,2277.4092,74.351535,64.797048,66.573651,56.011956 11/5/2015,0.049,1.3998,0.2206,0.48927,0.0843,0.3704,0.4242,0.1461,1548.59874,169.23582,2291.4726,74.39937,63.27096,65.664618,55.138122 11/6/2015,0.0491,1.4197,0.2235,0.48634,0.0845,0.3765,0.429,0.1482,1545.91133,167.169675,2234.6078,75.67001,62.878513,66.15802,56.276908 11/9/2015,0.0485,1.419,0.223,0.48581,0.0846,0.3735,0.4286,0.1481,1546.1424,167.08725,2254.791,75.207,62.25153,65.75646,55.78089 11/10/2015,0.0483,1.4222,0.2235,0.48754,0.0849,0.3795,0.4289,0.1483,1546.07362,165.40186,2266.9868,75.73215,62.875462,65.193648,55.935126 11/11/2015,0.048,1.4161,0.2224,0.49259,0.0846,0.3765,0.4278,0.1478,1537.74299,165.40048,2262.9278,75.76135,60.793173,63.653695,53.882605 11/12/2015,0.0462,1.4034,0.2204,0.48983,0.0838,0.372,0.4228,0.1462,1526.05716,161.81202,2210.355,75.01173,58.59195,60.823356,51.097794 11/13/2015,0.0456,1.4021,0.2202,0.49045,0.0841,0.3645,0.4204,0.146,1516.37115,157.245515,2128.3878,74.942245,57.121554,59.112536,50.265285 11/16/2015,0.0458,1.4091,0.2212,0.48851,0.084,0.3688,0.4225,0.1464,1528.521225,161.130585,2164.3776,76.020945,58.815834,60.154479,52.221246 11/17/2015,0.0457,1.4063,0.2205,0.49017,0.0841,0.3686,0.4202,0.1459,1517.67896,160.669775,2143.2012,76.573035,57.194221,58.656773,50.415855 11/18/2015,0.0453,1.4064,0.2203,0.49144,0.084,0.3735,0.4198,0.146,1501.6836,158.5716,2073.0336,76.78944,57.3108,59.20944,51.277344 11/19/2015,0.0452,1.3898,0.2178,0.48904,0.0836,0.3738,0.4142,0.144,1504.59748,166.63702,2126.394,75.81359,56.342492,58.329906,50.366352 11/20/2015,0.045,1.3815,0.2164,0.4884,0.0835,0.3729,0.4105,0.1432,1494.437625,168.40485,2126.1285,75.084525,55.798785,58.38219,50.45238 11/23/2015,0.0452,1.3903,0.2176,0.4876,0.084,0.3726,0.4123,0.1442,1488.31615,166.766485,2093.7918,75.0762,55.681515,60.074863,51.371585 11/24/2015,0.0449,1.378,0.2158,0.47893,0.0834,0.373,0.4088,0.1426,1483.2792,168.7361,2090.426,74.3431,56.87006,61.08674,53.27348 11/25/2015,0.0447,1.379,0.2158,0.47743,0.0836,0.3681,0.4082,0.1431,1472.772,169.4791,2067.121,74.39705,57.62841,61.55856,53.11908 11/26/2015,0.0448,1.3839,0.2166,0.47366,0.0835,0.3695,0.4098,0.1432,1482.1569,170.08131,2055.0915,74.523015,57.833181,60.282684,53.307828 11/27/2015,0.0447,1.3902,0.2174,0.47521,0.0836,0.3614,0.4127,0.1438,1469.99748,168.2142,2058.8862,74.86227,57.985242,59.84811,51.868362 11/30/2015,0.044,1.3837,0.2163,0.47503,0.0835,0.3576,0.4103,0.1432,1469.35103,161.75453,2049.2597,69.115815,57.631105,59.250034,51.05853 12/1/2015,0.0437,1.3656,0.2134,0.47231,0.0826,0.3543,0.4057,0.141,1454.91024,159.98004,2034.744,67.87032,57.15036,59.376288,50.062896 12/2/2015,0.0433,1.368,0.2138,0.47352,0.0826,0.3568,0.4059,0.1412,1443.7872,161.1504,2050.632,67.1688,54.63792,57.27816,47.52432 12/3/2015,0.0433,1.3622,0.2129,0.4721,0.0815,0.3619,0.4052,0.1405,1437.73399,166.25651,2093.7014,66.67969,55.959176,58.560978,48.984712 12/4/2015,0.0425,1.3628,0.2128,0.47054,0.0818,0.363,0.4045,0.1402,1470.8019,168.9872,2093.2608,66.16394,54.471116,57.292112,47.861536 12/7/2015,0.0416,1.3759,0.2147,0.4722,0.0815,0.3652,0.4078,0.1417,1480.19322,168.754135,2112.0065,65.699225,51.802635,54.912169,46.409107 12/8/2015,0.0419,1.3856,0.2159,0.47618,0.0814,0.3651,0.4095,0.1428,1485.50176,169.3896,2121.3536,65.67744,51.973856,54.980608,46.20976 12/9/2015,0.0421,1.3831,0.2152,0.47432,0.081,0.3683,0.4106,0.1421,1495.1311,171.296935,2110.6106,65.628095,51.395996,54.881408,46.098723 12/10/2015,0.0423,1.3735,0.2133,0.46984,0.0799,0.3604,0.4072,0.141,1471.0185,168.459775,2090.467,65.1039,50.48986,53.62144,44.762365 12/11/2015,0.0419,1.3911,0.2155,0.46648,0.08,0.3592,0.4121,0.1424,1491.95475,164.28891,2085.2589,65.868585,49.550982,51.929763,43.151922 12/14/2015,0.0412,1.3808,0.2138,0.46334,0.0797,0.3566,0.4086,0.1413,1475.0396,161.8988,2036.68,65.79512,50.136848,51.310528,42.556256 12/15/2015,0.0419,1.3904,0.2151,0.46898,0.0813,0.3589,0.4121,0.1421,1475.9096,160.79976,2057.792,66.32208,51.93144,51.319664,43.51952 12/16/2015,0.0415,1.3824,0.2136,0.47066,0.0814,0.3564,0.4097,0.1408,1486.4256,163.26144,2054.2464,66.0096,49.102848,49.959936,41.789952 12/17/2015,0.0419,1.4028,0.2164,0.47892,0.0823,0.3618,0.4155,0.1054,1472.09832,165.24984,2078.9496,66.9837,49.02786,49.574952,42.420672 12/18/2015,0.0419,1.3937,0.2151,0.4792,0.0814,0.35,0.413,0.1061,1480.80625,165.083765,2072.4319,66.61886,48.403201,48.849185,42.08974 12/21/2015,0.0418,1.3909,0.2146,0.47733,0.0811,0.3469,0.4107,0.1087,1500.433375,163.43075,2061.3138,66.20684,48.319866,48.375502,41.198458 12/22/2015,0.0417,1.382,0.2133,0.47158,0.0804,0.3467,0.4071,0.1068,1485.5118,164.6653,2060.562,65.7832,48.63258,48.1627,41.01776 12/23/2015,0.042,1.3824,0.2134,0.47386,0.0803,0.3505,0.4066,0.1066,1476.7488,167.20128,2063.9232,66.07872,51.01056,50.029056,43.352064 12/24/2015,0.0432,1.3769,0.2126,0.47116,0.0798,0.3486,0.4056,0.1051,1470.873425,164.81493,2044.6965,65.81582,51.63375,50.243081,43.207122 12/25/2015,0.0437,1.3737,0.2121,0.46345,0.0797,0.3486,0.4056,0.1049,1467.455025,164.43189,2039.9445,65.66286,51.51375,50.126313,43.106706 12/28/2015,0.0434,1.3795,0.2126,0.47475,0.08,0.3573,0.4058,0.1065,1473.650875,164.367425,2048.5575,64.8365,50.779395,48.323885,41.453975 12/29/2015,0.0433,1.3706,0.2113,0.47167,0.0794,0.3546,0.4024,0.106,1466.67906,166.45937,2024.3762,64.96644,51.904622,49.82131,42.749014 12/30/2015,0.0432,1.3723,0.2114,0.47013,0.079,0.3468,0.4026,0.1059,1454.638,169.684895,2025.5148,65.04702,50.22618,48.099115,41.155277 12/31/2015,0.0432,1.3723,0.2112,0.46997,0.0797,0.3464,0.4018,0.1061,1454.638,173.87041,2046.0993,65.115635,50.829992,49.059725,42.500131 1/1/2016,0.0432,1.3694,0.2109,0.47037,0.0793,0.3458,0.4025,0.1063,1451.564,173.50298,2041.7754,64.97803,50.722576,49.490116,42.410318 1/4/2016,0.0432,1.3907,0.2129,0.46909,0.0803,0.3443,0.4073,0.1054,1505.085075,172.30773,2059.6267,66.33639,51.122132,50.385061,42.764025 1/5/2016,0.0435,1.3963,0.2143,0.46742,0.0805,0.3485,0.4098,0.1024,1503.8151,171.7449,2045.5795,66.673325,50.224911,49.70828,42.656965 1/6/2016,0.0434,1.4141,0.2157,0.47078,0.0806,0.3512,0.4152,0.1021,1543.34874,169.621295,2051.8591,68.513145,48.036977,46.594595,40.202863 1/7/2016,0.0436,1.4261,0.2163,0.4755,0.0799,0.3528,0.4166,0.1027,1577.765735,168.921545,2045.0274,69.16585,47.446347,46.262684,40.044888 1/8/2016,0.044,1.4382,0.2181,0.47579,0.0802,0.3565,0.4197,0.1036,1584.68067,171.1458,2071.008,67.81113,47.690712,46.09431,40.097016 1/11/2016,0.0438,1.4299,0.2176,0.47071,0.08,0.3527,0.4169,0.1044,1573.962425,163.652055,2006.1497,66.77633,44.913159,42.382236,36.662636 1/12/2016,0.0437,1.4314,0.2178,0.47182,0.08,0.3554,0.4173,0.1061,1553.64156,163.68059,2012.5484,66.13068,43.571816,41.052552,35.28401 1/13/2016,0.0442,1.4378,0.2187,0.47502,0.0801,0.3579,0.4195,0.1062,1564.54207,165.05944,2034.487,65.92313,43.824144,40.76163,34.320286 1/14/2016,0.0443,1.432,0.2173,0.47337,0.0801,0.358,0.4187,0.1081,1558.5888,165.9688,1991.912,65.4424,44.6784,42.6736,36.516 1/15/2016,0.0441,1.4573,0.2205,0.47823,0.0798,0.3594,0.4249,0.1085,1593.921875,167.44377,2031.4762,66.088555,42.873766,40.702389,35.70385 1/18/2016,0.0441,1.4565,0.2207,0.47975,0.08,0.3615,0.4242,0.1077,1586.4198,167.35185,1998.318,65.97945,42.85023,40.126575,35.68425 1/19/2016,0.0437,1.4476,0.2193,0.47624,0.0792,0.3558,0.4219,0.1075,1572.4555,167.41494,1974.5264,65.79342,41.198696,39.635288,33.482988 1/20/2016,0.0427,1.4477,0.2213,0.47589,0.0781,0.353,0.4202,0.1078,1595.003475,161.56332,1908.0686,65.797965,38.436435,38.204803,32.42848 1/21/2016,0.043,1.4288,0.219,0.47429,0.0763,0.3436,0.4144,0.1057,1566.6792,163.45472,1896.0176,65.43904,40.406464,40.277872,32.590928 1/22/2016,0.0431,1.4281,0.2162,0.47565,0.0774,0.3485,0.4144,0.1042,1565.554625,165.6596,1930.7912,65.478385,44.256819,44.242538,37.1306 1/25/2016,0.0423,1.4378,0.2176,0.47578,0.0773,0.3508,0.4144,0.1045,1591.06948,167.43181,1926.652,65.70746,40.819142,41.236104,34.79476 1/26/2016,0.0424,1.4277,0.2171,0.47438,0.0773,0.3522,0.412,0.1033,1589.88672,166.61259,1914.5457,65.24589,44.901165,42.759615,36.649059 1/27/2016,0.0424,1.4232,0.2161,0.47429,0.0771,0.3464,0.4108,0.1028,1588.647,168.22224,1945.5144,65.04024,45.96936,45.11544,38.170224 1/28/2016,0.043,1.4117,0.2144,0.47538,0.0771,0.3469,0.4074,0.102,1572.6338,168.204055,1931.2056,64.585275,46.896674,46.642568,40.275801 1/29/2016,0.043,1.4117,0.2148,0.4778,0.0779,0.3532,0.4061,0.1016,1569.52806,164.251295,1931.2056,64.585275,47.461354,46.86844,41.066353 2/1/2016,0.0422,1.4056,0.2147,0.47716,0.0771,0.3545,0.4035,0.0997,1583.4084,165.5094,1932.7,62.26808,44.445072,47.059488,39.77848 2/2/2016,0.0419,1.4208,0.2156,0.48124,0.0769,0.3553,0.4065,0.1006,1603.3728,170.28288,1984.8576,64.00704,42.453504,45.4656,38.276352 2/3/2016,0.0413,1.3951,0.2146,0.4784,0.0768,0.3576,0.3999,0.0986,1579.2532,169.574405,1955.9302,63.05852,45.033828,49.260981,41.071744 2/4/2016,0.0418,1.3886,0.2107,0.47682,0.076,0.3573,0.3993,0.0981,1605.70761,171.07552,1992.641,61.7927,44.046392,47.2124,39.866706 2/5/2016,0.0424,1.415,0.2142,0.48497,0.0767,0.3622,0.4064,0.0985,1627.74525,170.366,2019.205,62.47225,43.70935,47.67135,40.0445 2/8/2016,0.0419,1.4112,0.2152,0.47871,0.0756,0.3614,0.4037,0.0983,1683.9144,163.3464,1955.9232,62.30448,41.898528,46.28736,38.568096 2/9/2016,0.0417,1.4145,0.2157,0.48107,0.0752,0.362,0.4038,0.0985,1684.6695,162.313875,1961.9115,61.81365,39.52113,42.97251,35.291775 2/10/2016,0.0416,1.4093,0.214,0.48244,0.0744,0.3584,0.402,0.1001,1677.067,161.717175,1961.7456,61.44548,38.685285,43.617835,35.288872 2/11/2016,0.0409,1.4066,0.2142,0.47992,0.0735,0.3528,0.4002,0.0965,1745.5906,158.9458,1943.9212,61.32776,36.866986,43.660864,35.150934 2/12/2016,0.0416,1.4071,0.2146,0.4799,0.0744,0.3517,0.4015,0.0951,1744.452225,162.590405,1996.6749,61.279205,41.425024,45.421188,37.921345 2/15/2016,0.0414,1.4009,0.2155,0.47542,0.0744,0.3505,0.3997,0.0945,1692.56738,161.873995,1975.269,60.93915,41.242496,47.084249,37.754255 2/16/2016,0.0411,1.4062,0.2161,0.4724,0.0745,0.3461,0.4009,0.095,1700.7989,161.57238,1995.3978,61.09939,40.836048,44.660912,37.19399 2/17/2016,0.0414,1.3918,0.2148,0.47084,0.0758,0.3488,0.3972,0.0933,1684.078,159.43069,1968.0052,60.61289,42.672588,47.822248,38.914728 2/18/2016,0.0418,1.3973,0.2145,0.47069,0.0764,0.3467,0.3986,0.093,1690.87273,159.501795,1959.0146,60.64282,42.994921,46.739685,38.313966 2/19/2016,0.0417,1.3989,0.2164,0.47415,0.0768,0.3478,0.3982,0.0928,1722.255735,161.922675,1936.0776,60.85215,41.463396,45.492228,38.231937 2/22/2016,0.0418,1.3837,0.2121,0.47114,0.0765,0.3505,0.3932,0.0906,1675.6607,165.836445,1909.506,60.32932,43.558876,47.114985,39.809049 2/23/2016,0.0417,1.3885,0.212,0.47168,0.0763,0.3503,0.3938,0.0906,1695.844475,163.5653,1891.137,61.094,41.752195,45.04294,38.29483 2/24/2016,0.0416,1.3896,0.2135,0.47342,0.0763,0.3507,0.3939,0.0905,1738.0422,159.87348,1855.116,60.93396,42.24384,47.051856,41.396184 2/25/2016,0.0417,1.382,0.2124,0.47194,0.0762,0.3494,0.3911,0.0895,1708.152,158.4463,1836.678,60.5316,44.45894,47.63754,41.37708 2/26/2016,0.042,1.4028,0.2133,0.46913,0.0768,0.3506,0.3977,0.0907,1720.5342,158.5164,1860.1128,61.51278,45.983784,48.775356,42.238308 2/29/2016,0.0425,1.4004,0.2139,0.47224,0.0772,0.3486,0.3974,0.0885,1729.35396,157.75506,1925.55,62.03772,47.2635,50.330376,42.15204 3/1/2016,0.0432,1.3939,0.214,0.47493,0.0778,0.354,0.3964,0.0883,1723.55735,156.81375,1870.6138,62.377025,47.95016,50.487058,43.141205 3/2/2016,0.0428,1.3708,0.2106,0.46851,0.0769,0.352,0.3916,0.0875,1698.69536,155.38018,1861.5464,61.27476,47.511928,50.349484,42.659296 3/3/2016,0.0426,1.3602,0.2081,0.46765,0.0759,0.3578,0.3922,0.0894,1700.59005,157.23912,1858.0332,62.50119,47.022114,49.78332,42.547056 3/4/2016,0.0426,1.3441,0.2074,0.46279,0.0757,0.3584,0.3889,0.0884,1717.08775,159.67908,1832.0083,62.299035,48.280072,51.599999,44.422505 3/7/2016,0.043,1.3391,0.206,0.45898,0.0754,0.3537,0.3881,0.087,1697.84489,158.884215,1826.5324,62.53597,50.75189,53.845211,46.747981 3/8/2016,0.042,1.3444,0.2066,0.46123,0.075,0.358,0.3877,0.087,1703.3548,161.59688,1859.3052,62.24572,49.0706,52.377824,45.064288 3/9/2016,0.042,1.3359,0.2049,0.46206,0.0752,0.3619,0.3883,0.0869,1665.06576,161.443515,1860.9087,62.186145,51.151611,53.275692,46.689705 3/10/2016,0.0417,1.3415,0.206,0.46398,0.0753,0.3701,0.3917,0.0875,1699.00975,161.7849,1847.2455,62.446825,50.76236,52.841685,45.329285 3/11/2016,0.042,1.322,0.2032,0.46085,0.0746,0.3686,0.3936,0.0889,1671.9995,164.4568,1853.444,61.3408,50.897,52.16612,45.10664 3/14/2016,0.0422,1.3309,0.2049,0.46364,0.075,0.3636,0.3991,0.09,1653.975975,167.16104,1877.8999,61.08831,49.482862,51.319504,44.18588 3/15/2016,0.0424,1.3409,0.2058,0.46263,0.075,0.3559,0.3995,0.0923,1651.9888,166.40569,1866.5328,61.54731,48.728306,50.873746,43.471978 3/16/2016,0.0419,1.3241,0.2062,0.46138,0.0752,0.3537,0.3923,0.0907,1626.65685,168.69034,1847.1195,60.842395,50.924886,52.235745,44.979677 3/17/2016,0.0426,1.3074,0.2026,0.46009,0.0755,0.3604,0.3882,0.0876,1655.8221,172.5768,1866.9672,60.66336,52.55748,53.028144,45.837444 3/18/2016,0.0428,1.3143,0.203,0.45865,0.0756,0.3629,0.3894,0.089,1645.63503,175.919055,1901.7921,61.24638,51.835992,53.281722,46.276503 3/21/2016,0.0429,1.3197,0.2031,0.46111,0.0758,0.3646,0.387,0.0912,1642.89453,173.606535,1897.7286,61.432035,52.669227,53.513835,46.84935 3/22/2016,0.0433,1.3121,0.2019,0.45766,0.0757,0.3664,0.3851,0.0912,1643.40525,176.674265,1940.5959,60.75023,52.418395,53.651769,46.907575 3/23/2016,0.0432,1.3277,0.2038,0.46166,0.0755,0.3603,0.3928,0.0918,1616.60752,174.06147,1964.996,61.406125,51.103173,52.829183,45.606495 3/24/2016,0.0432,1.3285,0.2043,0.46249,0.0754,0.361,0.3936,0.0918,1622.0985,169.450175,1936.953,61.443125,50.42986,52.52889,45.46127 3/25/2016,0.0433,1.3319,0.2043,0.46298,0.0759,0.361,0.3948,0.0921,1626.2499,169.883845,1941.9102,61.600375,50.558924,52.676645,45.577618 3/28/2016,0.0438,1.3256,0.2036,0.46216,0.076,0.3655,0.3941,0.0918,1618.5576,170.40588,1932.7248,59.12176,52.215384,52.082824,45.123424 3/29/2016,0.0429,1.3109,0.2032,0.46211,0.0756,0.3601,0.39,0.0895,1607.1634,167.074205,1917.8467,58.269505,50.181252,50.626958,43.482553 3/30/2016,0.0432,1.3036,0.2015,0.45959,0.0757,0.3621,0.3876,0.0893,1611.5755,165.5572,1917.5956,58.14056,49.953952,50.592716,43.253448 3/31/2016,0.0435,1.3059,0.2017,0.46345,0.0756,0.3636,0.394,0.0888,1615.3983,166.436955,1920.9789,58.700205,50.068206,50.564448,43.604001 4/1/2016,0.0428,1.3021,0.2015,0.46176,0.0751,0.3668,0.3892,0.0881,1580.22856,165.692225,1933.6185,58.399185,47.904259,49.297506,41.953662 4/4/2016,0.0429,1.3151,0.2027,0.46771,0.0752,0.363,0.3935,0.0893,1604.093225,161.49428,1938.4574,58.65346,46.94907,48.237868,40.952214 4/5/2016,0.043,1.3256,0.205,0.46804,0.0749,0.3602,0.3936,0.0903,1632.145,160.26504,1931.3992,59.25432,47.575784,49.458136,41.464768 4/6/2016,0.0427,1.316,0.2037,0.46317,0.0746,0.3613,0.3878,0.0901,1607.3624,159.894,1934.52,58.4962,49.679,51.17924,43.57276 4/7/2016,0.0429,1.3324,0.2062,0.46551,0.0745,0.3614,0.3923,0.0921,1654.97404,159.62152,1993.2704,58.55898,49.645224,51.56388,43.795988 4/8/2016,0.0428,1.3242,0.2043,0.46465,0.0745,0.369,0.3929,0.0915,1641.3459,159.49989,2003.5146,59.19174,52.597224,54.305442,46.360242 4/11/2016,0.0431,1.3164,0.2036,0.4647,0.0746,0.3766,0.401,0.0906,1651.7529,162.37794,2037.7872,59.17218,53.129904,55.143996,47.693172 4/12/2016,0.0431,1.3016,0.202,0.45909,0.0745,0.373,0.4026,0.0897,1632.98736,162.17936,2029.1944,58.37676,54.888472,56.35928,49.122384 4/13/2016,0.0435,1.3068,0.2018,0.45901,0.075,0.3733,0.3995,0.0908,1627.9461,159.1029,1979.802,58.60998,54.571968,55.944108,48.704436 4/14/2016,0.0434,1.2995,0.2004,0.45634,0.0745,0.373,0.3972,0.0907,1603.388075,160.033425,1979.1385,59.2572,53.92925,55.46266,48.02952 4/15/2016,0.0432,1.2946,0.2004,0.45362,0.0738,0.3665,0.3954,0.0923,1588.60366,159.17107,1974.265,59.22795,52.250056,54.321416,46.890412 4/18/2016,0.0434,1.2903,0.1992,0.45429,0.074,0.3568,0.3943,0.0913,1592.61729,159.9972,1974.159,59.418315,51.328134,54.244212,46.541121 4/19/2016,0.0442,1.2799,0.1982,0.45226,0.0739,0.3622,0.3934,0.0903,1606.78646,161.075415,1964.6465,58.939395,52.578292,54.920509,47.458692 4/20/2016,0.0443,1.283,0.1977,0.456,0.0743,0.3635,0.3958,0.0894,1606.316,163.13345,1984.801,58.69725,54.69429,56.9652,49.30569 4/21/2016,0.0439,1.2923,0.1987,0.4563,0.074,0.3659,0.3955,0.0905,1614.405775,159.663665,1982.3882,58.864265,54.573829,56.189204,48.939401 4/22/2016,0.0439,1.297,0.1995,0.45521,0.0742,0.3634,0.3963,0.0905,1612.49525,159.20675,1976.628,59.20805,55.35596,57.068,49.62322 4/25/2016,0.0437,1.2962,0.1995,0.45574,0.0738,0.3644,0.3941,0.0905,1605.86218,159.56222,1989.667,59.17153,53.455288,56.268042,48.73712 4/26/2016,0.0437,1.2907,0.1989,0.45754,0.0743,0.3657,0.3929,0.0901,1602.66219,161.660175,2008.3292,58.98499,56.842428,57.926616,50.104974 4/27/2016,0.0449,1.3174,0.2029,0.46747,0.0761,0.3735,0.4004,0.0927,1643.32476,159.47127,2022.209,60.20518,59.717742,60.587226,52.854088 4/28/2016,0.0456,1.3114,0.2021,0.46624,0.0759,0.3759,0.3992,0.0915,1647.1184,157.89256,2022.1788,59.99655,60.363742,61.163696,53.400208 4/29/2016,0.0461,1.3148,0.2027,0.47067,0.0765,0.3827,0.4002,0.092,1690.37262,158.89358,2045.8288,60.1521,60.375616,60.954128,53.31514 5/2/2016,0.046,1.3043,0.2022,0.4651,0.0758,0.3724,0.395,0.092,1676.873295,155.34213,2029.4908,59.802155,58.406554,59.189134,51.950269 5/3/2016,0.0458,1.3361,0.2052,0.469,0.0759,0.3755,0.4011,0.0941,1728.9134,158.46146,2076.2994,60.725745,58.320765,59.523255,52.014373 5/4/2016,0.0454,1.3411,0.2058,0.4526,0.0753,0.3778,0.4028,0.0942,1720.6313,159.72501,2081.3872,61.42238,58.713358,59.464374,51.873748 5/5/2016,0.0454,1.3396,0.2055,0.45794,0.0749,0.3787,0.4033,0.0941,1715.0229,161.95764,2121.9264,62.15744,59.371072,59.906912,52.927596 5/6/2016,0.0459,1.3574,0.2091,0.46362,0.076,0.3876,0.4101,0.0954,1749.6886,167.57103,2197.6306,64.13715,60.621484,60.87939,53.997372 5/9/2016,0.0462,1.367,0.2096,0.46419,0.0751,0.3888,0.41,0.0961,1729.59675,171.08005,2195.402,64.5224,59.38248,58.781,52.45179 5/10/2016,0.0457,1.3581,0.2086,0.46037,0.0755,0.3907,0.4072,0.0954,1715.00868,172.34289,2215.0611,64.306035,60.652746,61.331796,55.451223 5/11/2016,0.0462,1.3559,0.2081,0.45914,0.0754,0.3929,0.4072,0.0955,1731.280915,173.41961,2226.3878,64.879815,62.683257,63.171381,57.693545 5/12/2016,0.0463,1.3653,0.2093,0.46122,0.076,0.3922,0.4105,0.0964,1746.560025,175.03146,2251.3797,65.39787,63.75951,64.824444,58.694247 5/13/2016,0.046,1.3757,0.2105,0.46308,0.0757,0.3895,0.4125,0.0973,1741.49863,177.19016,2271.2807,65.89603,63.571097,65.084367,58.824932 5/16/2016,0.0453,1.3718,0.2102,0.46088,0.0749,0.3917,0.412,0.0968,1763.79185,182.03786,2274.4444,66.12076,65.462296,66.5323,60.63356 5/17/2016,0.0453,1.365,0.209,0.46056,0.0747,0.3913,0.4122,0.0965,1743.105,179.97525,2279.55,65.86125,65.94315,66.5301,60.94725 5/18/2016,0.0457,1.3832,0.2099,0.46276,0.075,0.3881,0.4152,0.0979,1760.67528,178.84776,2268.448,66.46276,66.656408,66.227616,60.515 5/19/2016,0.0453,1.3836,0.2121,0.46306,0.0751,0.3882,0.4141,0.0982,1724.3115,171.49722,2231.7468,66.20526,66.634176,66.89706,60.94758 5/20/2016,0.0454,1.3846,0.2115,0.46512,0.0755,0.3932,0.4154,0.0985,1736.56532,172.65962,2259.6672,66.4608,66.11465,66.848488,61.074706 5/23/2016,0.0452,1.3843,0.2113,0.46215,0.0748,0.3874,0.414,0.099,1724.69937,169.092245,2235.6445,66.16954,65.726564,66.155697,60.438538 5/24/2016,0.0454,1.3921,0.2121,0.47243,0.0753,0.3898,0.4164,0.0991,1721.818885,169.55778,2255.202,66.68159,67.057457,67.489008,60.431061 5/25/2016,0.0454,1.3891,0.2121,0.47302,0.0752,0.388,0.4163,0.0989,1695.53546,168.63674,2244.7856,66.746255,68.288156,68.454848,61.620476 5/26/2016,0.0453,1.3839,0.2112,0.4717,0.075,0.3864,0.4137,0.0988,1693.686015,168.14385,2240.5341,66.70398,68.475372,68.959737,60.946956 5/27/2016,0.0453,1.3918,0.2116,0.4699,0.0754,0.3852,0.4154,0.1001,1692.77675,168.82534,2268.634,67.08476,68.657494,68.142528,61.225282 5/30/2016,0.0454,1.3922,0.2114,0.4712,0.0753,0.3898,0.4137,0.0997,1693.26325,168.87386,2269.286,70.86298,68.677226,68.412708,61.242878 5/31/2016,0.0447,1.3826,0.2097,0.46878,0.0749,0.3827,0.4096,0.0989,1675.84946,168.05503,2270.2292,70.71999,67.88566,66.793406,60.41962 6/1/2016,0.0443,1.378,0.2095,0.46838,0.0744,0.3825,0.4096,0.0986,1673.581,167.9782,2268.188,69.9335,67.53578,67.34286,61.14186 6/2/2016,0.0448,1.3833,0.2101,0.46903,0.0741,0.3849,0.4095,0.0995,1677.11292,170.1459,2257.5456,70.68663,68.016861,67.933863,60.934365 6/3/2016,0.0449,1.3574,0.2083,0.46756,0.073,0.3849,0.4071,0.0976,1683.8547,172.52554,2227.4934,70.31332,65.996788,66.566896,59.603434 6/6/2016,0.045,1.3575,0.2067,0.46734,0.0727,0.3891,0.4103,0.0985,1688.73,178.78275,2260.2375,71.4045,67.454175,66.54465,60.748125 6/7/2016,0.0456,1.3406,0.2042,0.46289,0.073,0.3894,0.4062,0.097,1663.6846,177.22732,2264.2734,69.64417,67.512616,67.003188,61.26542 6/8/2016,0.0458,1.3385,0.204,0.46267,0.0739,0.3981,0.4062,0.0963,1690.5255,186.921525,2271.4345,68.2635,68.571355,68.705205,62.40087 6/9/2016,0.0458,1.3456,0.2051,0.46529,0.0737,0.3954,0.4067,0.0974,1700.70384,180.24312,2267.336,68.2892,68.033536,67.804784,62.234 6/10/2016,0.0456,1.3562,0.206,0.46296,0.0727,0.3963,0.4071,0.0982,1729.8331,185.73159,2228.2366,68.28467,66.548734,66.304618,60.595016 6/13/2016,0.0452,1.3537,0.205,0.4636,0.0719,0.3888,0.4069,0.0981,1733.81896,185.86301,2232.2513,68.22648,66.168856,65.370173,60.050132 6/14/2016,0.0452,1.359,0.2061,0.463,0.0718,0.3902,0.4071,0.0989,1749.23685,183.6009,2198.862,68.56155,65.89791,64.62045,59.83677 6/15/2016,0.0453,1.35,0.205,0.46147,0.0714,0.3885,0.4082,0.0983,1732.455,186.57,2174.85,68.31,64.8135,63.5715,58.0365 6/16/2016,0.045,1.3583,0.2073,0.46354,0.0717,0.3919,0.4075,0.0976,1780.391725,189.48285,2190.9379,68.86581,62.767043,61.734735,55.921211 6/17/2016,0.0449,1.3524,0.2057,0.46204,0.0718,0.3963,0.4076,0.0972,1745.54268,190.3503,2224.698,68.83716,64.888152,64.604148,58.653588 6/20/2016,0.0451,1.3412,0.2037,0.46151,0.0719,0.395,0.408,0.0964,1719.15016,187.0974,2233.098,69.0718,66.215044,65.638328,59.763872 6/21/2016,0.0451,1.3423,0.2033,0.4613,0.0721,0.3932,0.4083,0.0962,1708.21098,185.90855,2259.0909,68.72576,65.571355,66.403581,59.839734 6/22/2016,0.0457,1.3331,0.2027,0.4608,0.0721,0.3947,0.4058,0.0948,1686.171535,182.568045,2232.9425,68.38803,64.562033,64.468716,58.78971 6/23/2016,0.0453,1.3137,0.2004,0.46046,0.0721,0.3934,0.4001,0.0913,1658.086455,182.932725,2212.2708,67.39281,64.647177,65.093835,59.221596 6/24/2016,0.0451,1.3391,0.2027,0.45677,0.0706,0.3963,0.4039,0.0897,1761.58605,179.908085,2200.1413,68.69583,62.857354,62.843963,57.005487 6/27/2016,0.0446,1.3641,0.2048,0.46434,0.0711,0.4021,0.4103,0.0892,1806.818655,183.47145,2235.7599,72.2973,63.198753,62.803164,56.88297 6/28/2016,0.0454,1.3535,0.2046,0.46605,0.0719,0.41,0.4098,0.0908,1772.67895,188.00115,2263.052,72.344575,64.764975,64.088225,57.82152 6/29/2016,0.046,1.342,0.2025,0.46438,0.0726,0.4168,0.4086,0.0897,1773.453,191.7047,2276.032,72.1325,66.93896,65.32856,59.37008 6/30/2016,0.046,1.3422,0.202,0.46651,0.0734,0.4176,0.4084,0.0893,1772.71065,193.41102,2265.6336,73.821,64.868526,64.989324,58.076994 7/1/2016,0.0455,1.3347,0.2006,0.45949,0.0726,0.4121,0.4058,0.0885,1788.498,193.331295,2314.3698,75.27708,65.386953,65.760669,59.514273 7/4/2016,0.0452,1.3265,0.199,0.45617,0.072,0.4058,0.4038,0.0883,1791.769875,192.143525,2338.6195,75.676825,64.985235,64.348515,59.148635 7/5/2016,0.0449,1.3399,0.2003,0.4574,0.0712,0.4056,0.408,0.0901,1809.869925,193.21358,2355.5442,75.771345,62.43934,62.332148,56.583977 7/6/2016,0.0443,1.3297,0.1992,0.45265,0.071,0.3993,0.4049,0.0905,1816.702625,188.750915,2324.3156,75.194535,63.067671,62.881513,56.977645 7/7/2016,0.0448,1.3371,0.1998,0.45507,0.071,0.397,0.4075,0.0909,1814.04357,187.795695,2353.296,76.34841,60.356694,60.009048,54.15255 7/8/2016,0.0451,1.3212,0.1978,0.4579,0.0714,0.4003,0.4026,0.0898,1789.2351,188.6013,2371.554,74.58174,59.995692,58.978368,53.77284 7/11/2016,0.0452,1.3277,0.1983,0.45706,0.0719,0.4012,0.4047,0.0903,1801.82167,196.433215,2425.7079,74.815895,59.427852,58.843664,53.426648 7/12/2016,0.045,1.3119,0.1961,0.45455,0.0715,0.3979,0.399,0.0901,1761.09456,191.471805,2370.6033,75.69663,61.39692,60.950874,55.637679 7/13/2016,0.0447,1.3145,0.1962,0.45328,0.0716,0.4025,0.4008,0.0902,1765.044875,192.1799,2379.245,76.5039,58.823875,59.323385,53.23725 7/14/2016,0.0449,1.3103,0.1959,0.45524,0.0714,0.4029,0.3996,0.089,1734.31308,196.93809,2405.7108,76.12843,59.854504,59.867607,54.90157 7/15/2016,0.0451,1.3198,0.1969,0.43712,0.0709,0.4025,0.4026,0.0884,1751.3746,192.29486,2388.838,76.48241,60.64481,61.661056,55.919926 7/18/2016,0.0451,1.3173,0.1964,0.44248,0.0716,0.4049,0.4014,0.0869,1758.20031,194.69694,2377.7265,75.87648,59.594652,60.161091,55.036794 7/19/2016,0.0455,1.3326,0.1994,0.43806,0.072,0.4101,0.4038,0.0888,1773.55734,192.76059,2400.0126,76.15809,59.50059,60.380106,55.182966 7/20/2016,0.0457,1.3374,0.2001,0.43276,0.0716,0.4102,0.4037,0.0887,1759.88466,196.5978,2418.0192,76.16493,60.102756,61.266294,56.117304 7/21/2016,0.0453,1.3345,0.1998,0.43484,0.0718,0.4079,0.4011,0.089,1763.074675,195.971325,2415.445,75.999775,58.651275,59.718875,54.674465 7/22/2016,0.0454,1.339,0.201,0.43626,0.0722,0.4115,0.4032,0.0898,1768.48425,190.0041,2383.42,75.9213,58.23311,59.47838,54.28306 7/25/2016,0.0444,1.3387,0.2007,0.44084,0.0713,0.4071,0.3967,0.0896,1757.913905,188.89057,2380.2086,76.3059,56.734106,58.059419,53.025907 7/26/2016,0.0435,1.3328,0.1994,0.43762,0.071,0.4068,0.3966,0.0892,1763.2944,188.72448,2403.0384,76.10288,57.203776,57.670256,52.525648 7/27/2016,0.0433,1.3349,0.2008,0.44226,0.0709,0.4092,0.3982,0.089,1774.0821,188.48788,2397.4804,76.35628,55.959008,56.399525,50.99318 7/28/2016,0.0431,1.3326,0.2001,0.44256,0.0705,0.4047,0.3976,0.0886,1788.01605,189.42909,2405.343,76.15809,54.823164,54.90312,50.278998 7/29/2016,0.0429,1.3161,0.1984,0.44026,0.0702,0.4047,0.3918,0.0875,1766.2062,192.41382,2375.5605,75.215115,54.74976,53.973261,49.88019 8/1/2016,0.0429,1.3271,0.1991,0.4437,0.0703,0.4064,0.3967,0.0887,1791.120515,190.372495,2412.6678,81.948425,53.163626,54.158951,49.275223 8/2/2016,0.0423,1.3142,0.1982,0.43927,0.0694,0.4032,0.3923,0.0885,1792.24025,185.63075,2399.7292,80.95472,51.924042,53.330236,48.415128 8/3/2016,0.0426,1.3179,0.1986,0.43736,0.0698,0.4069,0.3937,0.0882,1790.89431,185.03316,2407.8033,80.52369,53.809857,55.852602,50.594181 8/4/2016,0.0425,1.311,0.1972,0.43534,0.0693,0.4106,0.3934,0.0883,1786.56525,186.2931,2382.087,77.54565,54.97023,56.43855,51.33876 8/5/2016,0.0432,1.3125,0.1973,0.43776,0.07,0.4146,0.394,0.0887,1759.275,187.03125,2392.6875,75.796875,54.8625,56.77875,51.58125 8/8/2016,0.0436,1.3071,0.196,0.43834,0.0704,0.4121,0.3946,0.0892,1747.33128,184.43181,2385.4575,78.622065,56.231442,57.590826,52.323213 8/9/2016,0.0437,1.3033,0.1958,0.43923,0.0707,0.4144,0.3943,0.0882,1747.7253,183.89563,2370.7027,79.24064,55.742141,57.019375,51.936505 8/10/2016,0.0441,1.2982,0.1954,0.43902,0.0705,0.415,0.3917,0.0885,1749.58414,179.99543,2360.1276,77.50254,54.147922,55.277356,50.590854 8/11/2016,0.0449,1.2988,0.1953,0.43922,0.0712,0.413,0.3921,0.0885,1759.874,178.84476,2348.2304,79.2268,56.484812,58.082336,52.99104 8/12/2016,0.0446,1.3071,0.196,0.44162,0.0716,0.4095,0.3945,0.0891,1767.46062,178.876635,2356.7013,80.321295,58.152879,60.401091,54.610638 8/15/2016,0.0445,1.3032,0.196,0.44317,0.0721,0.409,0.394,0.0888,1745.50608,178.47324,2347.0632,79.4952,59.608368,61.471944,56.3634 8/16/2016,0.0448,1.2996,0.1961,0.4436,0.0719,0.4058,0.3929,0.0885,1746.6624,178.56504,2306.79,79.34058,60.535368,62.64072,58.066128 8/17/2016,0.0449,1.3061,0.1976,0.44685,0.072,0.4074,0.3946,0.0884,1754.549435,176.388805,2289.5933,79.737405,61.112419,64.077266,59.179391 8/18/2016,0.0452,1.301,0.1963,0.4446,0.0715,0.4017,0.3942,0.0872,1756.41505,179.73315,2327.489,78.7105,62.73422,65.08903,59.62483 8/19/2016,0.0459,1.3113,0.1972,0.44751,0.072,0.409,0.395,0.0879,1765.53432,182.00844,2341.9818,78.80913,63.624276,65.420757,60.044427 8/22/2016,0.0454,1.3112,0.1972,0.44585,0.0717,0.4097,0.3915,0.0884,1751.63208,188.94392,2358.8488,79.13092,61.69196,63.094944,58.112384 8/23/2016,0.0449,1.3132,0.197,0.44465,0.0707,0.406,0.3906,0.0886,1762.3144,190.80796,2351.9412,78.85766,62.57398,63.913444,59.396036 8/24/2016,0.0446,1.3135,0.1975,0.445,0.0712,0.4073,0.3918,0.0884,1743.342875,186.714025,2336.7165,78.67865,61.038345,63.533995,58.00416 8/25/2016,0.0453,1.3127,0.1973,0.44727,0.0715,0.4059,0.3919,0.0884,1734.47051,188.37245,2311.6647,79.02454,61.605011,64.309173,58.953357 8/26/2016,0.0456,1.3224,0.1961,0.44777,0.0711,0.4046,0.3947,0.0882,1743.915,190.29336,2357.8392,79.74072,62.999136,64.969512,59.336088 8/29/2016,0.0452,1.3212,0.1977,0.4478,0.0709,0.4089,0.3911,0.0875,1742.3325,190.2528,2355.6996,78.9417,62.069976,64.329228,58.740552 8/30/2016,0.0453,1.3316,0.1993,0.44922,0.0708,0.4111,0.3941,0.0887,1755.24854,192.7491,2370.248,81.49392,61.71966,63.144472,58.297448 8/31/2016,0.0448,1.3302,0.1992,0.44991,0.0708,0.4119,0.3921,0.0891,1741.56435,194.07618,2385.0486,81.54126,59.45994,61.428636,55.788588 9/1/2016,0.0443,1.3242,0.1985,0.44728,0.0706,0.4066,0.3901,0.0888,1734.0399,198.76242,2417.9892,81.10725,57.152472,59.761146,54.464346 9/2/2016,0.045,1.3206,0.1983,0.44754,0.0711,0.4054,0.3904,0.0882,1749.39882,198.22206,2431.2246,81.74514,58.687464,60.54951,55.451994 9/5/2016,0.0447,1.3188,0.1975,0.44766,0.071,0.4016,0.3881,0.0879,1749.19038,197.95188,2446.374,81.17214,58.607472,61.52202,55.376412 9/6/2016,0.0454,1.3009,0.1955,0.44516,0.0712,0.4069,0.3876,0.0866,1739.628525,198.322205,2428.7803,80.330575,58.319347,60.765039,55.535421 9/7/2016,0.0455,1.3033,0.1956,0.44388,0.0709,0.4079,0.3877,0.0866,1757.304555,200.512705,2478.8766,78.84965,59.30015,61.828552,56.445923 9/8/2016,0.046,1.3083,0.1953,0.44338,0.07,0.4071,0.3888,0.0869,1757.57022,201.08571,2514.5526,78.301755,62.301246,63.936621,59.213658 9/9/2016,0.0454,1.3262,0.1977,0.44658,0.0702,0.4053,0.3906,0.0881,1764.97327,198.86369,2523.7586,79.70462,60.846056,62.278352,57.35815 9/12/2016,0.045,1.3217,0.1989,0.44543,0.0703,0.4068,0.389,0.0885,1750.72382,197.85849,2536.3423,79.764595,61.181493,62.159551,57.044572 9/13/2016,0.045,1.3399,0.2001,0.44876,0.0702,0.4044,0.3934,0.0894,1773.558635,197.434265,2594.0464,81.46592,60.16151,61.568405,56.342795 9/14/2016,0.0454,1.3391,0.2002,0.44956,0.0695,0.4003,0.3934,0.0891,1769.955425,197.91898,2588.4803,81.01555,58.357978,59.978289,54.688844 9/15/2016,0.0454,1.3307,0.1998,0.44822,0.0687,0.4029,0.3933,0.0884,1744.28156,196.41132,2564.2589,81.30577,58.431037,60.254096,55.144208 9/16/2016,0.0451,1.3347,0.2002,0.44817,0.068,0.4089,0.3934,0.0883,1746.254745,196.33437,2566.6281,81.55017,57.432141,59.968071,54.442413 9/19/2016,0.0454,1.3274,0.1985,0.44596,0.0674,0.4057,0.3919,0.0876,1745.33189,201.1011,2592.4122,81.6351,57.47642,59.480794,54.211016 9/20/2016,0.0454,1.3236,0.1984,0.44448,0.0668,0.4062,0.3907,0.0874,1738.94568,205.8198,2582.3436,81.4014,57.497184,59.482584,54.519084 9/21/2016,0.0453,1.3117,0.1977,0.44379,0.0664,0.4088,0.3884,0.0866,1739.44537,205.346635,2599.7894,81.653325,59.210138,60.298849,55.379974 9/22/2016,0.0453,1.3083,0.1962,0.44473,0.0667,0.4062,0.3914,0.0863,1751.94453,203.113575,2612.6751,81.24543,60.404211,60.495792,56.073738 9/23/2016,0.0449,1.3114,0.1966,0.44234,0.0663,0.4044,0.3908,0.0866,1755.50561,198.54596,2571.6554,82.09364,58.134362,58.829404,54.278846 9/26/2016,0.0448,1.3096,0.1962,0.43922,0.0659,0.4038,0.3886,0.086,1755.5188,201.08908,2579.912,81.91548,60.149928,59.809432,55.474656 9/27/2016,0.0452,1.3043,0.1959,0.4385,0.0673,0.4033,0.3875,0.0854,1730.8061,200.47091,2595.557,81.192675,58.263081,58.628285,54.089321 9/28/2016,0.0446,1.3,0.1956,0.4362,0.0671,0.4041,0.3855,0.0847,1719.25,199.03,2588.3,81.64,61.165,61.854,57.057 9/29/2016,0.0453,1.3096,0.1955,0.43647,0.0671,0.4017,0.3858,0.0852,1726.18376,196.63644,2625.748,82.30836,62.638168,62.638168,58.395064 9/30/2016,0.0453,1.3055,0.1956,0.43511,0.0673,0.3999,0.3859,0.085,1726.52375,197.848525,2617.5275,81.9854,62.97732,62.285405,58.760555 10/3/2016,0.0445,1.3034,0.1956,0.43162,0.0676,0.406,0.3848,0.0858,1711.75522,192.31667,2576.8218,97.42915,63.618954,64.088178,60.360454 10/4/2016,0.0441,1.3123,0.196,0.42913,0.0679,0.4028,0.3856,0.0866,1684.07459,193.498635,2569.4834,99.20988,63.895887,65.523139,60.798859 10/5/2016,0.0448,1.3121,0.1967,0.42997,0.0683,0.4074,0.3854,0.0864,1665.57974,194.45322,2616.3274,99.32597,65.381943,65.880541,61.786789 10/6/2016,0.0454,1.3183,0.1979,0.43345,0.0685,0.4083,0.387,0.0867,1653.80735,192.99912,2618.1438,101.77276,66.495052,67.457411,63.133387 10/7/2016,0.0451,1.3179,0.1978,0.432,0.0684,0.4092,0.3873,0.0868,1658.906625,195.0492,2637.1179,101.148825,65.644599,66.329907,62.231238 10/10/2016,0.0453,1.3146,0.1959,0.42777,0.0695,0.41,0.3873,0.0865,1655.7387,200.93661,2651.5482,99.44949,67.50471,67.780776,63.534618 10/11/2016,0.0454,1.3265,0.1971,0.43003,0.0701,0.415,0.3899,0.0873,1662.701425,200.0362,2690.142,98.55895,67.372935,67.797415,63.80465 10/12/2016,0.0455,1.3224,0.1968,0.42851,0.0699,0.4136,0.3886,0.0877,1661.5956,201.13704,2695.0512,99.04776,66.358032,66.080328,62.298264 10/13/2016,0.0453,1.3212,0.1967,0.42815,0.0698,0.4157,0.3931,0.0874,1666.09926,201.74724,2691.2844,99.09,66.641328,66.548844,62.347428 10/14/2016,0.045,1.3131,0.1952,0.4248,0.0691,0.4096,0.3859,0.0866,1643.672925,204.05574,2683.9764,99.467325,66.114585,66.127716,61.623783 10/17/2016,0.0449,1.3109,0.1947,0.42347,0.0695,0.409,0.3858,0.0862,1644.91732,205.94239,2734.5374,101.529205,65.466346,65.453237,60.930632 10/18/2016,0.0449,1.3045,0.1936,0.4214,0.0701,0.4092,0.3855,0.0858,1641.3219,207.089375,2772.0625,104.49045,65.603305,65.681575,60.933195 10/19/2016,0.0444,1.2951,0.1926,0.42294,0.0699,0.4086,0.3831,0.0854,1643.546655,204.431535,2724.8904,101.341575,66.82716,65.894688,61.102818 10/20/2016,0.0448,1.3111,0.1942,0.4285,0.0704,0.4173,0.3884,0.0863,1667.260315,204.40049,2746.7545,102.92135,66.118773,65.017449,60.612153 10/21/2016,0.0448,1.3145,0.1947,0.4267,0.0707,0.4166,0.3914,0.0866,1664.222725,205.19345,2797.256,104.042675,66.447975,65.725,61.36086 10/24/2016,0.0447,1.3138,0.1942,0.42657,0.0708,0.4207,0.3907,0.0866,1662.67959,207.44902,2801.0216,104.11865,65.847656,65.217032,61.709186 10/25/2016,0.0445,1.3077,0.1929,0.42582,0.0706,0.4202,0.3891,0.0859,1659.99438,215.11665,2815.4781,103.635225,64.744227,63.135756,60.02343 10/26/2016,0.044,1.3071,0.1929,0.4242,0.0699,0.4162,0.3882,0.086,1660.67055,213.97227,2815.4934,103.91445,64.283178,63.13293,58.767216 10/27/2016,0.0445,1.3178,0.1939,0.42315,0.0699,0.4161,0.3919,0.0868,1668.66425,217.17344,2859.626,104.69921,65.521016,64.005546,59.920366 10/28/2016,0.044,1.3161,0.1948,0.42353,0.0693,0.4112,0.3909,0.0867,1675.3953,217.81455,2879.6268,104.695755,64.09407,63.133317,58.882314 10/31/2016,0.0437,1.3142,0.1943,0.42474,0.0697,0.4116,0.3909,0.0867,1671.6624,215.72593,2929.3518,110.85277,61.583412,61.359998,55.866642 11/1/2016,0.0429,1.3068,0.1931,0.42004,0.0681,0.4043,0.3884,0.0867,1683.74646,210.98286,2882.8008,112.25412,60.988356,62.556516,56.610576 11/2/2016,0.0425,1.3053,0.1929,0.41925,0.0674,0.4043,0.3853,0.0864,1701.784875,212.63337,2889.9342,110.42838,59.182302,61.192464,55.409985 11/3/2016,0.0426,1.3017,0.1925,0.41851,0.0679,0.4014,0.3853,0.0864,1693.5117,215.626605,2893.6791,111.29535,58.133922,60.359829,54.345975 11/4/2016,0.0426,1.3033,0.193,0.4127,0.0685,0.4026,0.3857,0.0864,1697.93924,223.320455,2925.9085,113.452265,57.436431,59.391381,53.448333 11/7/2016,0.0426,1.2941,0.1918,0.40829,0.0696,0.4036,0.3833,0.0858,1660.395005,225.626335,2913.0191,113.557275,58.092149,59.709774,53.718091 11/8/2016,0.0436,1.2885,0.1911,0.40801,0.0703,0.4065,0.3816,0.0862,1652.307975,215.82375,2759.967,112.22835,57.95673,57.93096,53.55006 11/9/2016,0.0436,1.3095,0.1922,0.40805,0.066,0.406,0.3881,0.0877,1677.9933,222.74595,2867.805,117.265725,59.281065,59.176305,55.15614 11/10/2016,0.0421,1.3135,0.1932,0.40401,0.0638,0.3875,0.3873,0.0873,1664.86125,212.589975,2801.6955,116.77015,58.66091,59.13377,54.27382 11/11/2016,0.0432,1.3249,0.1945,0.40781,0.0637,0.3895,0.3889,0.0866,1638.172605,211.255305,2759.7667,118.44606,57.513909,57.990873,52.956253 11/14/2016,0.0424,1.3236,0.1933,0.40223,0.064,0.3855,0.3853,0.0849,1606.32096,214.15848,2829.8568,116.41062,57.338352,57.881028,52.388088 11/15/2016,0.0424,1.3229,0.193,0.40192,0.0653,0.3853,0.3872,0.0854,1623.132155,214.04522,2901.1197,116.67978,60.602049,60.906316,55.945441 11/16/2016,0.0427,1.3368,0.1944,0.40229,0.0661,0.3903,0.3927,0.0863,1643.19456,215.559,2961.012,115.6332,60.917976,61.118496,55.757928 11/17/2016,0.0428,1.3499,0.1947,0.4005,0.0661,0.3941,0.3966,0.0871,1655.989825,215.03907,2996.778,116.76635,61.312458,60.947985,56.047848 11/18/2016,0.0428,1.3631,0.1972,0.40499,0.0661,0.4031,0.3941,0.088,1650.7141,215.165335,3000.1831,117.703685,62.280039,62.579921,57.468296 11/21/2016,0.0431,1.3573,0.1968,0.40369,0.0664,0.4051,0.3972,0.0882,1648.101525,215.335645,2866.6176,117.81364,64.458177,65.218265,60.26412 11/22/2016,0.0428,1.351,0.1967,0.39895,0.0656,0.4026,0.4007,0.0875,1637.74975,212.44475,2872.226,117.73965,62.99713,65.5235,59.9844 11/23/2016,0.0427,1.3541,0.1955,0.39885,0.0656,0.3993,0.3987,0.0871,1605.082435,209.411565,2808.4034,115.166205,63.182306,65.728014,59.98663 11/24/2016,0.0431,1.3499,0.195,0.39179,0.0651,0.3974,0.3956,0.0869,1601.11639,208.762035,2767.295,116.968835,62.986334,65.078679,59.80057 11/25/2016,0.0423,1.344,0.1945,0.3893,0.065,0.3937,0.393,0.0864,1596.2688,204.6912,2765.952,116.928,60.15744,62.60352,56.81088 11/28/2016,0.0424,1.3367,0.1932,0.39137,0.0648,0.3944,0.3974,0.086,1586.6629,204.5151,2807.07,112.750645,62.931836,63.613553,57.798908 11/29/2016,0.0423,1.3362,0.194,0.39202,0.0648,0.3939,0.3909,0.0852,1585.46811,200.29638,2739.21,113.24295,60.436326,61.385028,55.291956 11/30/2016,0.044,1.3543,0.1958,0.39405,0.0658,0.4,0.3966,0.0854,1595.50083,199.75925,2776.315,115.92808,66.956592,67.525398,61.458134 12/1/2016,0.0439,1.3487,0.1965,0.38476,0.0649,0.3892,0.3949,0.0853,1566.987095,191.24566,2683.913,114.841805,68.864622,71.494587,65.991891 12/2/2016,0.0435,1.3402,0.1949,0.38102,0.065,0.3859,0.3925,0.0841,1572.7247,189.23624,2766.1728,112.71082,69.261536,72.196574,66.393508 12/5/2016,0.0441,1.3383,0.195,0.37977,0.065,0.3909,0.3914,0.0843,1555.37226,187.62966,2762.2512,111.21273,69.310557,71.451837,65.884509 12/6/2016,0.0446,1.3403,0.1948,0.38932,0.0657,0.393,0.3926,0.0842,1571.50175,184.894385,2732.8717,106.218775,68.261479,70.968885,65.232401 12/7/2016,0.0445,1.3365,0.1946,0.3941,0.0657,0.3941,0.3929,0.0835,1573.929225,184.30335,2713.095,107.788725,66.517605,69.431175,64.57968 12/8/2016,0.0446,1.3399,0.1951,0.38925,0.066,0.3972,0.3939,0.0838,1569.089895,184.37024,2699.8985,110.67574,68.120516,71.135291,65.735494 12/9/2016,0.0446,1.3423,0.194,0.38603,0.0658,0.397,0.3868,0.0839,1561.90028,181.948765,2669.8347,112.686085,69.12845,71.933857,66.108275 12/12/2016,0.0446,1.3341,0.1932,0.38449,0.066,0.3997,0.3922,0.0832,1542.35301,184.172505,2708.223,115.39965,70.480503,72.721791,66.931797 12/13/2016,0.0449,1.3334,0.1934,0.3821,0.0657,0.3999,0.393,0.0835,1544.81057,185.20926,2737.4702,116.73917,70.643532,72.496958,66.990016 12/14/2016,0.0456,1.3503,0.1928,0.38258,0.066,0.4004,0.3988,0.0846,1569.386175,189.379575,2788.3695,120.04167,68.919312,71.538894,65.543562 12/15/2016,0.0453,1.3591,0.1957,0.38696,0.0668,0.404,0.3996,0.0852,1531.637745,187.96353,2814.6961,122.45491,69.17819,72.589531,65.970714 12/16/2016,0.0455,1.369,0.1969,0.39017,0.067,0.4044,0.4027,0.0863,1549.1604,189.1958,2870.793,122.3886,71.0511,74.6105,67.91609 12/19/2016,0.0459,1.3806,0.1979,0.39078,0.0677,0.4093,0.4047,0.087,1568.70675,194.94072,2979.3348,122.94243,71.956872,75.090834,68.671044 12/20/2016,0.046,1.3775,0.1988,0.39046,0.0673,0.4112,0.4047,0.0868,1550.65175,198.153375,2949.2275,123.975,71.946825,75.6523,68.888775 12/21/2016,0.0461,1.3816,0.1985,0.39363,0.0672,0.4148,0.4068,0.0875,1566.25084,199.71028,2927.6104,124.6894,70.862264,74.385344,68.085248 12/22/2016,0.0462,1.3856,0.199,0.39463,0.0667,0.421,0.4086,0.0881,1567.59856,192.73696,2876.5056,124.704,71.98192,75.09952,68.892032 12/23/2016,0.0464,1.3936,0.2008,0.39639,0.0677,0.4259,0.4123,0.09,1576.64936,189.73864,2930.7408,125.49368,72.495072,75.783968,69.54064 12/26/2016,0.0464,1.3905,0.2,0.39595,0.0674,0.4238,0.4103,0.0885,1573.142175,189.316575,2924.2215,125.214525,72.33381,75.740535,69.38595 12/27/2016,0.0465,1.3917,0.2,0.39525,0.067,0.4251,0.4116,0.0895,1574.499795,186.76614,2926.7451,125.322585,75.01263,77.072346,70.767945 12/28/2016,0.046,1.3933,0.2004,0.39367,0.0671,0.4249,0.414,0.0887,1580.83818,186.00555,2905.0305,126.23298,75.321798,77.021624,70.91897 12/29/2016,0.0461,1.3852,0.1997,0.39266,0.0668,0.4263,0.4129,0.087,1587.30068,187.62534,2943.55,125.49912,74.482204,76.975564,70.43742 12/30/2016,0.0462,1.3887,0.1993,0.3935,0.067,0.4257,0.4137,0.0875,1591.31133,190.321335,2998.2033,125.26074,74.600964,76.947867,71.420841 1/2/2017,0.0464,1.3919,0.2004,0.39304,0.0671,0.4236,0.4141,0.0878,1594.97821,190.759895,3005.1121,125.54938,74.772868,78.155185,71.585417 1/3/2017,0.0465,1.3851,0.1992,0.38547,0.0656,0.4241,0.4083,0.0869,1594.2501,190.31274,2959.9587,114.27075,72.482283,76.152798,70.058358 1/4/2017,0.0462,1.373,0.1985,0.38447,0.064,0.4261,0.405,0.0854,1598.51525,194.6914,2990.394,115.6066,73.12598,76.59967,70.27014 1/5/2017,0.0465,1.3627,0.1981,0.37926,0.0636,0.4257,0.4045,0.0854,1603.48909,195.888125,2951.6082,116.851525,73.258752,76.883534,70.424336 1/6/2017,0.0468,1.3702,0.1973,0.37596,0.0646,0.4254,0.406,0.0867,1611.14967,195.73307,2958.2618,116.12445,73.977098,77.183366,70.811936 1/9/2017,0.0464,1.3598,0.1964,0.36627,0.0636,0.4249,0.4022,0.0856,1602.5243,196.08316,2929.0092,114.29119,70.655208,73.524386,67.595658 1/10/2017,0.0459,1.357,0.1962,0.35783,0.0622,0.4248,0.4007,0.0857,1614.1515,200.4289,2947.404,117.2448,68.96274,71.75816,65.8145 1/11/2017,0.0452,1.3438,0.1959,0.34776,0.0615,0.4203,0.397,0.0848,1583.73549,200.2262,2993.9864,119.19506,70.21355,73.129596,67.284066 1/12/2017,0.0457,1.336,0.1934,0.35536,0.0613,0.4193,0.3975,0.0845,1609.9468,199.8656,2952.56,118.3696,70.82136,74.2816,68.2028 1/13/2017,0.0453,1.3331,0.1939,0.35799,0.0621,0.4144,0.3964,0.0841,1586.855585,199.03183,2951.4834,117.57942,69.814447,73.507134,67.401536 1/16/2017,0.0456,1.3375,0.194,0.35157,0.0615,0.4126,0.3969,0.0842,1609.0125,199.68875,2997.3375,117.766875,70.044875,73.602625,67.624 1/17/2017,0.0453,1.3215,0.1936,0.3512,0.0614,0.4114,0.3952,0.0831,1607.010075,198.09285,2978.661,118.6707,69.35232,72.60321,66.31287 1/18/2017,0.0454,1.3324,0.1932,0.3509,0.0607,0.4133,0.3989,0.0834,1618.5329,198.79408,3011.224,119.84938,68.058992,71.443288,65.234304 1/19/2017,0.0449,1.3225,0.1929,0.34556,0.0602,0.4132,0.3989,0.0832,1581.776125,199.366875,3003.3975,117.107375,67.936825,70.872775,65.09345 1/20/2017,0.0453,1.3236,0.1927,0.35113,0.0613,0.4173,0.4014,0.0832,1589.04798,202.77552,3009.8664,118.06512,69.383112,72.718584,66.762384 1/23/2017,0.045,1.3188,0.1925,0.35109,0.0617,0.4168,0.3992,0.0828,1599.50658,204.94152,2981.8068,117.76884,68.51166,72.283428,66.216948 1/24/2017,0.045,1.3189,0.192,0.34861,0.0613,0.4158,0.4018,0.0828,1604.83752,200.934415,2937.1903,117.64588,69.281817,72.117452,65.931811 1/25/2017,0.0451,1.3205,0.1924,0.3447,0.0626,0.416,0.4019,0.0828,1577.9975,201.90445,2961.8815,117.326425,68.996125,72.244555,66.170255 1/26/2017,0.0451,1.3273,0.1927,0.34466,0.0626,0.4182,0.4023,0.0832,1579.08881,201.019585,2949.2606,117.46605,71.382194,73.718242,67.6923 1/27/2017,0.0452,1.3245,0.1922,0.3425,0.0634,0.4219,0.4026,0.0834,1569.333825,201.8538,2984.0985,117.21825,70.423665,72.66207,66.423675 1/30/2017,0.0452,1.3237,0.1923,0.35003,0.0637,0.4234,0.4025,0.0833,1578.90936,200.077255,2980.9724,108.94051,69.666331,72.088702,66.026156 1/31/2017,0.0451,1.3184,0.1912,0.34943,0.0633,0.4186,0.4031,0.0829,1598.95552,197.16672,2969.0368,112.45952,69.624704,72.090112,66.44736 2/1/2017,0.0454,1.3183,0.1923,0.34963,0.0637,0.4214,0.4031,0.0835,1586.771795,197.942745,2956.9469,111.594095,71.030004,74.009362,67.984731 2/2/2017,0.0454,1.3059,0.1891,0.3494,0.0635,0.4181,0.4021,0.0833,1595.744505,190.596105,2853.3915,111.13209,69.917886,73.613583,67.501971 2/3/2017,0.0456,1.3017,0.1894,0.35221,0.0639,0.4168,0.3994,0.0834,1581.82584,190.373625,2833.8009,110.058735,70.070511,73.493982,67.454094 2/6/2017,0.0457,1.3055,0.1908,0.35473,0.0635,0.4186,0.3971,0.0828,1601.522125,188.2531,2817.269,110.05365,69.204555,72.259425,66.52828 2/7/2017,0.0459,1.3111,0.1905,0.35004,0.0636,0.4202,0.3977,0.0836,1613.9641,186.96286,2814.9317,110.26351,68.400087,70.707623,65.410779 2/8/2017,0.0454,1.3081,0.1905,0.35165,0.0639,0.4201,0.3975,0.0835,1624.79101,186.92749,2754.8586,108.70311,68.465954,71.435341,65.405 2/9/2017,0.0459,1.3115,0.1909,0.35613,0.0644,0.4193,0.4007,0.0838,1622.0632,190.4298,2788.249,108.5922,69.5095,72.434145,66.25698 2/10/2017,0.0457,1.3026,0.1896,0.35233,0.064,0.4183,0.4004,0.0839,1599.98358,189.85395,2771.9328,105.77112,70.158036,72.9456,67.435602 2/13/2017,0.0456,1.3089,0.1902,0.35659,0.0645,0.4208,0.4017,0.0845,1599.803025,188.808825,2757.8523,105.36645,69.280077,72.068034,66.321963 2/14/2017,0.0454,1.305,0.1903,0.35747,0.0644,0.4229,0.4,0.0843,1606.12875,187.46325,2735.28,105.0525,69.426,71.9577,66.59415 2/15/2017,0.0452,1.297,0.1894,0.35439,0.064,0.424,0.399,0.0844,1588.0468,187.4165,2744.452,105.7055,68.88367,71.42579,65.55038 2/16/2017,0.0452,1.2996,0.1895,0.3544,0.0638,0.4207,0.4002,0.0843,1612.21878,190.13148,2792.8404,106.2423,69.346656,71.581968,65.707776 2/17/2017,0.0451,1.3045,0.1899,0.35952,0.0639,0.4209,0.4,0.0833,1620.123775,192.8051,2796.848,106.7081,69.6603,71.864905,65.864205 2/20/2017,0.0451,1.3006,0.1893,0.3589,0.0638,0.4211,0.4003,0.0829,1609.23238,192.22868,2804.0936,106.90932,69.45204,72.170294,65.667294 2/21/2017,0.0449,1.3029,0.1894,0.3599,0.0651,0.4206,0.4006,0.0836,1606.73628,195.891015,2811.6582,107.09838,70.434774,73.105719,66.851799 2/22/2017,0.0449,1.2982,0.1892,0.36261,0.0652,0.4235,0.4006,0.0833,1605.41903,193.69144,2765.166,106.58222,69.181078,72.56938,65.520154 2/23/2017,0.0452,1.2961,0.1888,0.36302,0.0659,0.4231,0.3997,0.0836,1617.40319,191.628385,2752.9164,106.40981,70.11901,72.84082,66.36032 2/24/2017,0.0451,1.3033,0.1895,0.3614,0.0655,0.4193,0.4016,0.0842,1633.882045,188.19652,2730.4135,107.00093,69.713517,72.385282,66.272805 2/27/2017,0.0451,1.3032,0.1893,0.36121,0.0654,0.4187,0.4004,0.0842,1638.38304,181.27512,2692.4112,102.49668,70.43796,72.379728,66.762936 2/28/2017,0.0446,1.306,0.1893,0.35815,0.0649,0.4199,0.4021,0.0844,1639.8136,183.7542,2746.518,101.7374,70.53706,72.56136,66.88026 3/1/2017,0.0445,1.3027,0.1898,0.35645,0.0658,0.4211,0.3997,0.0843,1615.86908,185.830155,2752.6051,102.65276,70.124341,72.495255,66.607051 3/2/2017,0.0444,1.3206,0.1916,0.35422,0.066,0.4189,0.4021,0.0857,1635.03486,187.78932,2894.7552,102.94077,69.476766,71.827434,65.871528 3/3/2017,0.0443,1.3165,0.1916,0.35539,0.0675,0.4226,0.4008,0.0853,1614.68725,185.955625,2859.438,101.23885,70.208945,72.4075,66.522745 3/6/2017,0.0444,1.3192,0.191,0.35544,0.0673,0.4204,0.4004,0.0853,1623.86924,184.22628,2836.28,101.31456,70.18144,72.740688,66.9494 3/7/2017,0.0446,1.318,0.1909,0.35809,0.0676,0.4226,0.401,0.0847,1603.5447,183.202,2824.474,99.9044,70.03852,72.25276,66.6249 3/8/2017,0.0444,1.3284,0.1918,0.35465,0.0675,0.419,0.403,0.0849,1606.30128,186.04242,2873.3292,101.09124,66.791952,69.794136,63.63036 3/9/2017,0.0444,1.3324,0.1928,0.35294,0.0672,0.4173,0.4043,0.0858,1607.60722,184.8705,2873.9868,99.53028,65.660672,69.08494,63.448888 3/10/2017,0.0444,1.326,0.1919,0.35486,0.0676,0.4216,0.4027,0.0857,1594.7139,185.1759,2854.878,99.9141,64.29774,67.17516,61.8579 3/13/2017,0.0443,1.3208,0.1906,0.35302,0.0673,0.4189,0.4023,0.085,1590.50736,185.5724,2834.4368,100.18268,63.92672,67.083432,61.588904 3/14/2017,0.0442,1.323,0.1912,0.35345,0.0673,0.4173,0.4031,0.0851,1593.6858,184.6908,2845.773,99.55575,63.13356,67.52592,61.14906 3/15/2017,0.0437,1.2971,0.1905,0.35288,0.0675,0.4179,0.3983,0.0833,1554.96348,180.55632,2803.0331,97.477065,63.376306,66.80065,60.976671 3/16/2017,0.0446,1.3024,0.1891,0.35925,0.0676,0.4175,0.3998,0.0838,1601.10544,182.0104,2813.184,97.28928,63.492,66.68288,61.14768 3/17/2017,0.0445,1.2976,0.1881,0.35676,0.068,0.4197,0.3993,0.0834,1595.52896,182.70208,2802.816,97.12536,63.296928,66.463072,60.883392 3/20/2017,0.0444,1.2938,0.1874,0.35783,0.0681,0.4211,0.3983,0.0828,1594.47912,186.3072,2812.7212,95.93527,62.387036,66.139056,60.562778 3/21/2017,0.0445,1.3003,0.1882,0.35792,0.0681,0.4212,0.4,0.0834,1614.45248,186.59305,2791.7441,95.96214,61.556202,65.431096,60.138875 3/22/2017,0.0446,1.3025,0.1891,0.35998,0.0685,0.4218,0.4017,0.0834,1626.887625,184.56425,2787.35,95.929125,61.66035,65.30735,59.875925 3/23/2017,0.0449,1.3111,0.1902,0.36074,0.0693,0.4175,0.4041,0.0839,1635.59725,184.20955,2804.4429,96.75918,61.6217,65.450112,60.17949 3/24/2017,0.0453,1.3118,0.1905,0.36326,0.0699,0.4221,0.405,0.084,1636.4705,180.50368,2766.5862,96.35171,62.074376,66.232782,60.762576 3/27/2017,0.0451,1.3127,0.1909,0.36293,0.0695,0.4199,0.4044,0.0842,1650.785885,182.72784,2836.7447,96.549085,62.655171,66.02881,60.016644 3/28/2017,0.0451,1.3099,0.19,0.35802,0.0688,0.4169,0.4044,0.084,1646.871775,181.879615,2807.1157,96.53963,63.359863,66.346435,60.805558 3/29/2017,0.0453,1.3038,0.1894,0.35763,0.0697,0.4178,0.4015,0.0845,1631.18418,181.61934,2797.9548,96.09006,64.551138,67.354308,61.904424 3/30/2017,0.0453,1.3087,0.1892,0.35831,0.0699,0.4154,0.4034,0.0849,1634.30456,182.30191,2795.3832,96.45119,65.893045,68.261792,62.856861 3/31/2017,0.0456,1.3108,0.1901,0.36069,0.07,0.4198,0.4034,0.0852,1631.74938,182.59444,2799.8688,97.26136,66.32648,69.092268,63.757312 4/3/2017,0.0458,1.3148,0.191,0.36076,0.0704,0.4222,0.4049,0.0854,1639.8843,181.24518,2826.82,100.97664,66.055552,68.76404,63.807244 4/4/2017,0.0461,1.322,0.192,0.35932,0.0702,0.4273,0.4067,0.086,1662.6133,182.1055,2834.368,100.6703,67.46166,70.58158,65.3068 4/5/2017,0.0462,1.3213,0.1915,0.35715,0.0702,0.4236,0.4068,0.0858,1646.07554,181.41449,2844.7589,102.070425,67.584495,70.200669,65.576119 4/6/2017,0.0464,1.3253,0.192,0.35703,0.0707,0.4216,0.4078,0.086,1659.93825,182.560075,2840.1179,103.10834,68.51801,71.645718,67.113192 4/7/2017,0.0466,1.3333,0.1929,0.35717,0.0714,0.4238,0.41,0.0869,1688.557785,186.728665,2893.261,102.197445,69.651592,72.318192,67.958301 4/10/2017,0.0465,1.3331,0.1931,0.35746,0.0714,0.4256,0.4107,0.0876,1666.441655,186.434035,2871.4974,100.64905,70.760948,73.560458,68.947932 4/11/2017,0.0464,1.3335,0.1937,0.36068,0.071,0.425,0.4098,0.0874,1670.74215,186.9567,2901.696,100.14585,71.2089,73.782555,68.528565 4/12/2017,0.0463,1.3294,0.1936,0.3643,0.0717,0.4253,0.4086,0.0875,1694.05442,183.85602,2867.5158,99.57206,70.604434,72.758062,67.93234 4/13/2017,0.0461,1.3213,0.1913,0.36063,0.071,0.4197,0.4058,0.0871,1696.747395,183.52857,2834.1885,99.692085,70.266734,72.27511,69.077564 4/14/2017,0.046,1.3194,0.1916,0.35646,0.0712,0.4198,0.4056,0.087,1694.30751,183.26466,2830.113,99.54873,70.165692,72.17118,68.978232 4/17/2017,0.0462,1.3176,0.1911,0.35599,0.0712,0.4249,0.4057,0.0871,1691.99604,185.91336,2826.252,99.41292,69.37164,72.20448,68.291208 4/18/2017,0.0466,1.3227,0.1925,0.36133,0.0711,0.4255,0.4067,0.0865,1691.667165,189.01383,2861.0001,100.062255,69.322707,71.544843,68.291001 4/19/2017,0.0465,1.3338,0.1935,0.36295,0.0708,0.423,0.4105,0.0867,1705.99689,184.0644,2862.3348,100.43514,67.276872,69.717726,65.88972 4/20/2017,0.0466,1.3286,0.1926,0.36488,0.0707,0.4219,0.4088,0.0863,1703.39806,174.91019,2787.4028,100.37573,66.788722,69.034056,65.486694 4/21/2017,0.0461,1.3262,0.1929,0.36429,0.0705,0.4215,0.409,0.0858,1699.98947,172.20707,2602.0044,100.06179,65.341874,67.83513,64.241128 4/24/2017,0.046,1.321,0.1921,0.36989,0.0705,0.4223,0.4072,0.0858,1676.8774,171.0695,2517.826,99.40525,64.57048,67.52952,63.47405 4/25/2017,0.0458,1.3272,0.1926,0.37075,0.0704,0.4217,0.409,0.0861,1682.62416,172.40328,2500.4448,99.8718,65.311512,68.191536,64.594824 4/26/2017,0.0457,1.338,0.1943,0.37401,0.0698,0.4216,0.4113,0.0864,1688.3553,171.4647,2539.524,100.8183,66.39156,68.38518,64.4916 4/27/2017,0.0455,1.3393,0.1946,0.37609,0.0704,0.4206,0.4127,0.0869,1691.26804,170.22503,2515.2054,101.65287,65.585521,67.969475,64.406937 4/28/2017,0.0454,1.3353,0.1941,0.37602,0.071,0.4204,0.4114,0.0868,1691.090685,174.991065,2559.7701,100.81515,65.870349,67.940064,64.161165 5/1/2017,0.0452,1.3288,0.1925,0.37387,0.0709,0.4181,0.4084,0.0863,1682.85876,177.52768,2547.3096,98.72984,64.898592,67.4366,63.901992 5/2/2017,0.0451,1.327,0.1929,0.37621,0.0707,0.4211,0.4089,0.0868,1665.98215,177.818,2603.574,98.5961,63.24482,67.13293,62.35573 5/3/2017,0.046,1.3472,0.1946,0.38112,0.0714,0.4255,0.4144,0.0881,1684.40416,181.872,2706.5248,99.89488,64.423104,67.346528,63.709088 5/4/2017,0.0453,1.3498,0.1962,0.37977,0.0708,0.4233,0.411,0.0879,1658.16181,179.11846,2655.0566,99.27779,61.442896,64.466448,60.714004 5/5/2017,0.0458,1.3474,0.1955,0.3801,0.0709,0.4241,0.412,0.0877,1654.67457,179.33894,2663.8098,99.0339,62.276828,65.874386,61.131538 5/8/2017,0.0457,1.3537,0.1962,0.37766,0.0705,0.4233,0.4119,0.0875,1664.78026,182.140335,2710.1074,98.41399,62.852291,66.06056,61.59335 5/9/2017,0.0457,1.3615,0.1969,0.37574,0.071,0.427,0.4138,0.0878,1661.5746,180.8072,2710.7465,99.1172,62.46562,65.56984,61.281115 5/10/2017,0.0461,1.3574,0.1962,0.37862,0.0714,0.4286,0.4121,0.0875,1660.03233,182.29882,2689.0094,99.22594,64.245742,67.435632,62.806898 5/11/2017,0.0463,1.3552,0.1965,0.37892,0.0719,0.4316,0.4124,0.0877,1657.61288,178.75088,2643.9952,98.45528,64.819216,68.003936,63.369152 5/12/2017,0.0463,1.3537,0.1959,0.37898,0.072,0.4334,0.4139,0.0877,1666.743125,179.50062,2661.3742,98.41399,64.761008,68.118184,63.393771 5/15/2017,0.0469,1.3489,0.1954,0.38014,0.0721,0.434,0.4128,0.0869,1663.59837,177.043125,2618.2149,98.132475,65.893765,69.212059,64.706733 5/16/2017,0.0467,1.3465,0.1954,0.38042,0.0722,0.4349,0.4128,0.0865,1661.8503,174.035125,2600.0915,98.631125,65.52069,68.34834,64.17419 5/17/2017,0.0464,1.3456,0.1958,0.37703,0.0716,0.4287,0.4107,0.0862,1691.95744,177.88832,2650.832,98.96888,66.028592,69.204208,65.05976 5/18/2017,0.0461,1.3478,0.1953,0.3719,0.0715,0.3992,0.411,0.0842,1692.70202,171.70972,2638.9924,99.87198,66.51393,70.01821,65.583948 5/19/2017,0.0463,1.3411,0.1949,0.37505,0.0716,0.4121,0.4096,0.0837,1679.0572,177.15931,2616.4861,99.50962,67.497563,71.561096,66.773369 5/22/2017,0.046,1.3375,0.1942,0.37582,0.0717,0.4093,0.4085,0.0827,1683.711875,174.6775,2534.5625,100.245625,67.851375,71.302125,66.888375 5/23/2017,0.046,1.3373,0.1937,0.37414,0.0718,0.409,0.4074,0.0831,1685.26546,174.183325,2551.5684,99.294525,68.429641,71.759518,67.413293 5/24/2017,0.0458,1.3326,0.1943,0.37429,0.0722,0.4067,0.4081,0.0828,1669.14813,171.30573,2501.2902,98.94555,68.109186,71.147514,66.936498 5/25/2017,0.046,1.3414,0.1951,0.37614,0.0725,0.4096,0.4105,0.0834,1686.07273,173.44302,2554.0256,99.53188,65.25911,68.196776,63.729914 5/26/2017,0.0462,1.3428,0.196,0.37522,0.0725,0.4119,0.4102,0.0839,1698.70914,176.17536,2633.2308,99.63576,66.87144,69.4899,65.085516 5/29/2017,0.0462,1.3442,0.1959,0.37586,0.0728,0.4126,0.4093,0.0841,1700.48021,176.35904,2635.9762,102.42804,66.94116,69.602676,65.153374 5/30/2017,0.0459,1.3395,0.1955,0.37744,0.0716,0.4112,0.4082,0.0828,1691.38665,176.94795,2664.2655,104.146125,66.51957,68.702955,64.577295 5/31/2017,0.0461,1.3458,0.1973,0.38148,0.0723,0.4171,0.4115,0.0836,1704.05196,174.07923,2676.7962,103.02099,65.029056,67.397664,62.754654 6/1/2017,0.0468,1.356,0.1988,0.38471,0.0727,0.4173,0.4142,0.0845,1715.1366,173.1612,2686.236,104.8188,65.57616,67.33896,63.44724 6/2/2017,0.0464,1.3435,0.1974,0.38279,0.0719,0.4137,0.4106,0.0838,1712.895325,168.676425,2661.4735,104.12125,64.03121,66.301725,62.190615 6/5/2017,0.0461,1.3358,0.1965,0.37902,0.0728,0.4052,0.4089,0.0833,1709.75721,171.58351,2666.2568,103.99203,63.31692,65.200398,61.219714 6/6/2017,0.046,1.3322,0.1958,0.379,0.0731,0.4064,0.4078,0.0832,1723.2007,167.25771,2644.417,103.11228,64.198718,65.517596,61.960622 6/7/2017,0.0454,1.3245,0.1948,0.37322,0.0727,0.4051,0.4051,0.0828,1709.9295,166.555875,2611.914,103.112325,60.55614,62.88726,59.0727 6/8/2017,0.0454,1.3252,0.1951,0.37601,0.0728,0.4061,0.4052,0.0831,1687.11212,167.43902,2627.8716,104.0282,60.482128,62.403668,58.719612 6/9/2017,0.0455,1.3285,0.1952,0.37548,0.0731,0.403,0.4064,0.0835,1682.611675,168.121675,2659.657,104.353675,60.885155,63.170175,59.22453 6/12/2017,0.0452,1.326,0.1952,0.37712,0.0731,0.3995,0.4042,0.0833,1679.2464,169.1976,2691.78,104.2899,61.10208,62.97174,59.21916 6/13/2017,0.0452,1.3268,0.1951,0.37694,0.0735,0.4004,0.4048,0.0835,1674.4216,167.70752,2682.7896,104.4855,61.643128,62.863784,59.745804 6/14/2017,0.045,1.3176,0.1933,0.37771,0.0735,0.4023,0.403,0.0828,1680.5988,165.42468,2685.2688,102.97044,58.936248,60.912648,57.091608 6/15/2017,0.0447,1.3195,0.1937,0.37556,0.0731,0.4029,0.4026,0.0826,1655.378725,165.9931,2757.755,103.31685,58.66497,60.74978,56.89684 6/16/2017,0.0441,1.3124,0.1926,0.37459,0.0733,0.3986,0.4011,0.0819,1647.58696,162.14702,2767.8516,103.08902,58.716776,61.22346,57.194392 6/19/2017,0.0442,1.316,0.1929,0.37364,0.0733,0.4007,0.4029,0.0815,1642.5654,163.4472,2751.756,104.1614,58.1672,60.9308,56.79856 6/20/2017,0.0435,1.3192,0.1933,0.37222,0.0725,0.3965,0.4031,0.0817,1638.71024,160.87644,2713.5944,104.28276,57.029016,59.654224,55.27448 6/21/2017,0.0433,1.3239,0.1939,0.37495,0.0726,0.3968,0.4047,0.0816,1644.94575,158.007465,2720.6145,104.654295,56.014209,58.529619,54.094554 6/22/2017,0.0438,1.3259,0.1939,0.37799,0.0732,0.3967,0.4066,0.0821,1658.43572,150.423355,2670.3626,104.61351,56.403786,59.307507,54.62708 6/23/2017,0.0437,1.3217,0.1931,0.37651,0.0734,0.3952,0.4056,0.0817,1659.65869,158.537915,2726.6671,104.216045,56.581977,59.714406,54.890201 6/26/2017,0.0436,1.3184,0.1926,0.37655,0.0738,0.4,0.4052,0.0808,1641.7376,160.77888,2736.9984,104.02176,57.192192,59.908096,55.860608 6/27/2017,0.0436,1.3187,0.1935,0.37401,0.0733,0.3979,0.405,0.0805,1647.781585,161.870425,2733.6651,104.30917,58.339288,60.26459,57.323889 6/28/2017,0.0434,1.3089,0.193,0.37256,0.0733,0.3992,0.4032,0.0798,1633.5072,160.667475,2721.2031,103.468545,58.560186,61.479033,57.657045 6/29/2017,0.0427,1.3015,0.1919,0.36925,0.0721,0.3941,0.4011,0.0789,1618.41525,162.362125,2761.783,102.8185,58.476395,60.897185,57.21394 6/30/2017,0.0427,1.3007,0.1922,0.36942,0.0718,0.3931,0.3998,0.0782,1615.794575,161.351835,2806.9106,102.7553,59.884228,62.732761,58.999752 7/3/2017,0.0429,1.3054,0.1922,0.36707,0.0716,0.3952,0.4007,0.0775,1604.66295,164.28459,2828.8018,105.34578,61.445178,64.09514,60.688046 7/4/2017,0.0432,1.3152,0.1934,0.36956,0.0723,0.3975,0.4037,0.0779,1609.476,165.51792,2868.4512,107.5176,61.906464,64.7736,61.143648 7/5/2017,0.0426,1.3152,0.1939,0.36469,0.0718,0.3999,0.4037,0.0767,1604.93856,167.88528,2882.9184,110.54256,59.354976,62.840256,58.552704 7/6/2017,0.0426,1.3183,0.1939,0.36411,0.0722,0.3997,0.4052,0.0772,1614.78567,167.094525,2876.5306,112.71465,60.009016,62.711531,58.835729 7/7/2017,0.0425,1.3152,0.1934,0.36346,0.0727,0.4008,0.4042,0.0775,1598.82288,166.43856,2822.4192,112.38384,58.171296,61.196256,57.198048 7/10/2017,0.0429,1.3146,0.1934,0.36441,0.0732,0.4038,0.4039,0.0774,1593.16374,165.96825,2806.671,111.28089,58.36824,61.168338,57.500604 7/11/2017,0.0426,1.3093,0.1932,0.36234,0.0731,0.4023,0.402,0.077,1585.627765,162.942385,2758.6951,110.832245,58.970872,62.217936,58.093641 7/12/2017,0.0427,1.3024,0.192,0.36513,0.0733,0.406,0.4006,0.0768,1587.36512,164.1024,2775.4144,109.79232,59.246176,61.27792,58.047968 7/13/2017,0.0425,1.2939,0.1908,0.36289,0.0732,0.4028,0.3988,0.0763,1577.13471,167.365965,2799.9996,107.587785,59.622912,61.822542,58.419585 7/14/2017,0.0422,1.2771,0.1889,0.36115,0.0727,0.4017,0.3931,0.0758,1571.21613,168.19407,2764.9215,106.38243,59.436234,62.041518,58.414554 7/17/2017,0.0423,1.2822,0.189,0.36338,0.0729,0.4029,0.3949,0.0758,1582.36302,168.67341,2743.908,107.0637,59.006844,61.22505,58.006728 7/18/2017,0.0419,1.2632,0.1871,0.35858,0.0723,0.4002,0.3895,0.0739,1567.3154,166.61608,2705.7744,105.35088,58.61248,60.772552,57.892456 7/19/2017,0.0419,1.2576,0.1864,0.3571,0.0716,0.3994,0.3879,0.0734,1562.12784,164.99712,2672.4,104.3808,59.258112,61.785888,58.704768 7/20/2017,0.0419,1.2566,0.1859,0.35631,0.0719,0.4026,0.3875,0.073,1556.55042,169.641,2675.3014,104.80044,58.796314,61.183854,58.11775 7/21/2017,0.0419,1.2634,0.1867,0.35729,0.0716,0.4019,0.3888,0.0726,1577.41807,172.51727,2737.7878,105.62024,57.636308,59.872526,57.055144 7/24/2017,0.0417,1.262,0.1869,0.35485,0.0712,0.4011,0.3889,0.0724,1584.5041,167.2781,2677.964,105.3139,58.29178,60.86626,57.88794 7/25/2017,0.0416,1.2599,0.1864,0.35275,0.0709,0.3972,0.3874,0.0721,1580.41856,164.54294,2668.4682,105.264645,60.185423,63.322574,59.631067 7/26/2017,0.0414,1.2492,0.187,0.35318,0.071,0.398,0.385,0.0714,1559.12652,168.39216,2698.272,104.3082,60.8985,62.997156,59.686776 7/27/2017,0.0416,1.2551,0.186,0.35491,0.0708,0.3984,0.3867,0.0712,1582.80661,170.630845,2709.7609,104.80085,61.550104,63.984998,60.583677 7/28/2017,0.0417,1.2523,0.1858,0.35496,0.0704,0.3999,0.3859,0.0704,1584.03427,172.629555,2681.1743,104.56705,62.251833,64.693818,61.249993 7/31/2017,0.0419,1.2494,0.1863,0.35499,0.0702,0.3999,0.3856,0.0708,1583.67697,173.97895,2674.9654,104.01255,62.682398,65.181198,61.795324 8/1/2017,0.0423,1.2549,0.1867,0.35582,0.0701,0.4014,0.3874,0.0714,1594.915155,172.987965,2647.839,103.215525,61.690884,64.037547,61.138728 8/2/2017,0.0423,1.2551,0.1864,0.35538,0.0704,0.4031,0.3874,0.0714,1593.47496,176.153285,2692.1895,103.04371,62.240409,65.089486,61.725818 8/3/2017,0.0426,1.2582,0.1874,0.35548,0.0705,0.4039,0.3885,0.0712,1595.52342,176.39964,2697.5808,104.17896,61.689546,64.696644,61.52598 8/4/2017,0.0422,1.2614,0.1876,0.35754,0.0705,0.4026,0.3903,0.0714,1586.46278,176.78521,2700.6574,105.45304,62.540212,65.46666,62.62851 8/7/2017,0.0424,1.2638,0.1882,0.358,0.0705,0.4042,0.3898,0.0714,1589.8604,179.52279,2733.5994,106.1592,62.419082,65.502754,62.583376 8/8/2017,0.0421,1.2635,0.1887,0.35771,0.0708,0.4042,0.3897,0.0713,1594.2843,180.364625,2734.214,105.50225,62.126295,65.12079,62.59379 8/9/2017,0.0422,1.268,0.1903,0.35849,0.0707,0.4017,0.3903,0.0716,1611.6914,180.8802,2708.448,106.6388,62.84208,66.36712,63.53948 8/10/2017,0.0424,1.2696,0.1907,0.35853,0.0706,0.3997,0.3905,0.0717,1630.67424,175.8396,2653.464,107.15424,61.689864,65.282832,62.565888 8/11/2017,0.0426,1.2667,0.1906,0.35825,0.071,0.3966,0.3906,0.0716,1629.10287,177.71801,2709.4713,107.79617,61.840294,65.551725,62.511645 8/14/2017,0.0429,1.2736,0.1906,0.36126,0.0717,0.3991,0.3927,0.0744,1633.13728,174.41952,2680.928,108.76544,60.610624,64.087552,61.311104 8/15/2017,0.0431,1.2787,0.1913,0.36171,0.0718,0.4033,0.3941,0.0749,1624.33261,168.7884,2630.2859,108.369825,60.802185,64.599924,61.88908 8/16/2017,0.0425,1.2618,0.1896,0.3588,0.0714,0.4003,0.3892,0.0733,1605.95595,165.23271,2596.7844,107.69463,59.027004,63.014292,60.478074 8/17/2017,0.0424,1.2682,0.1891,0.35973,0.071,0.3993,0.3912,0.0731,1629.82723,162.90029,2615.0284,109.19202,59.719538,63.841188,61.393562 8/18/2017,0.0422,1.2611,0.1895,0.35856,0.0712,0.4009,0.3887,0.0727,1634.13338,161.483855,2668.4876,108.769875,61.175961,66.169917,63.81166 8/21/2017,0.0422,1.2594,0.1889,0.36021,0.0713,0.3979,0.3887,0.0726,1628.27826,159.18816,2696.3754,107.30088,59.657778,64.531656,61.77357 8/22/2017,0.0423,1.2639,0.1895,0.36163,0.0716,0.3996,0.3903,0.0735,1623.10038,159.061815,2727.4962,107.747475,60.212196,64.635846,62.082768 8/23/2017,0.0424,1.2651,0.19,0.36362,0.0715,0.4026,0.3907,0.0734,1627.740915,159.718875,2695.9281,108.03954,61.053726,65.570133,62.913423 8/24/2017,0.0427,1.2656,0.1899,0.36323,0.0714,0.4021,0.3907,0.0735,1631.3584,160.35152,2671.6816,107.76584,59.774288,65.203712,62.356112 8/25/2017,0.0431,1.2605,0.1897,0.36639,0.0716,0.3989,0.3891,0.0732,1620.12065,164.1171,2710.075,107.457625,60.02501,65.16785,62.382145 8/28/2017,0.0426,1.2557,0.1899,0.3646,0.0703,0.3965,0.3878,0.0729,1613.95121,163.11543,2699.755,111.7573,58.477949,64.442524,61.566971 8/29/2017,0.0428,1.2575,0.1903,0.3648,0.0705,0.3975,0.3884,0.0724,1658.202375,160.07975,2698.595,112.609125,58.3983,64.572625,61.7684 8/30/2017,0.043,1.265,0.1921,0.36659,0.0714,0.4006,0.3905,0.0728,1655.2525,160.59175,2662.825,112.7115,58.1394,63.64215,61.9091 8/31/2017,0.0427,1.2586,0.1915,0.36451,0.0704,0.3997,0.3886,0.0726,1650.96855,161.28959,2612.8536,110.31629,59.443678,65.963226,64.100498 9/1/2017,0.0428,1.2549,0.1912,0.36614,0.0704,0.3995,0.3875,0.0729,1656.96996,160.313475,2598.8979,110.493945,59.344221,65.769309,63.447744 9/4/2017,0.0429,1.2587,0.1926,0.36651,0.0704,0.4011,0.3888,0.073,1677.97297,160.798925,2560.1958,111.52082,59.523923,65.288769,63.639872 9/5/2017,0.0427,1.2506,0.1908,0.36367,0.0699,0.4013,0.3866,0.0726,1670.23883,158.2009,2479.9398,111.49099,60.854196,66.15674,62.96771 9/6/2017,0.0429,1.2499,0.1917,0.36485,0.0703,0.4032,0.3862,0.0725,1672.178715,158.23734,2456.0535,111.428585,61.445084,67.282117,64.082373 9/7/2017,0.0427,1.2427,0.1918,0.36502,0.0703,0.4008,0.3842,0.0721,1669.56745,158.94133,2451.8471,110.786705,61.004143,67.441329,64.334579 9/8/2017,0.0427,1.241,0.1909,0.3638,0.0701,0.4021,0.3841,0.072,1670.69625,160.5854,2455.939,111.4418,58.92268,66.49278,62.72014 9/11/2017,0.0426,1.2455,0.1908,0.36559,0.0705,0.4014,0.3853,0.0727,1661.7461,162.6623,2456.126,112.281825,59.871185,66.95808,62.785655 9/12/2017,0.0429,1.2471,0.1905,0.36324,0.0703,0.3988,0.3857,0.0731,1654.27815,166.86198,2481.729,112.239,60.147633,67.46811,63.577158 9/13/2017,0.043,1.2521,0.1915,0.36211,0.0705,0.3993,0.3865,0.0734,1662.225355,171.03686,2534.2504,114.254125,61.72853,68.74029,64.908864 9/14/2017,0.0431,1.2492,0.1912,0.36391,0.0707,0.4002,0.3858,0.0735,1654.62786,169.70382,2515.8888,114.67656,62.322588,68.818428,64.983384 9/15/2017,0.0431,1.2497,0.1907,0.36344,0.0708,0.4018,0.3845,0.0736,1653.165645,174.958,2515.6461,114.59749,62.347533,69.10841,65.434292 9/18/2017,0.0432,1.2562,0.1907,0.36021,0.0707,0.4003,0.3871,0.0735,1648.26002,174.54899,2545.0612,115.13073,62.696942,69.191496,65.284714 9/19/2017,0.043,1.2486,0.1898,0.35799,0.0702,0.3982,0.3847,0.073,1635.16656,167.24997,2504.6916,115.30821,61.780728,68.54814,64.515162 9/20/2017,0.043,1.2451,0.1886,0.35532,0.0701,0.3972,0.3832,0.0724,1632.69963,170.018405,2562.4158,114.860475,62.765491,69.327168,65.479809 9/21/2017,0.0432,1.2612,0.1912,0.3596,0.0705,0.4016,0.3878,0.073,1629.59652,170.262,2566.542,115.52592,63.31224,70.526304,66.692256 9/22/2017,0.0432,1.256,0.1903,0.35934,0.0708,0.4019,0.3869,0.0726,1626.2688,168.8692,2547.168,115.238,63.18936,71.13984,66.71872 9/25/2017,0.0431,1.26,0.1899,0.35473,0.0703,0.3986,0.3865,0.072,1629.558,165.753,2551.5,116.865,65.4192,74.1636,69.5646 9/26/2017,0.0434,1.2679,0.1911,0.35786,0.0706,0.4004,0.3897,0.0722,1648.333395,167.679775,2562.4259,116.329825,65.778652,73.474805,69.316093 9/27/2017,0.0434,1.2741,0.1913,0.35615,0.07,0.3989,0.3894,0.0726,1634.096955,164.804835,2509.977,116.58015,66.431574,73.248009,68.941551 9/28/2017,0.0432,1.2727,0.1916,0.35778,0.0701,0.3999,0.3897,0.0726,1633.319545,163.54195,2503.4009,116.388415,65.620412,73.002072,68.687619 9/29/2017,0.0435,1.2765,0.1916,0.35817,0.0699,0.4035,0.3909,0.0738,1637.87715,163.455825,2510.8755,116.6721,65.956755,72.160545,67.9098 10/2/2017,0.0433,1.2776,0.1921,0.35796,0.0701,0.405,0.3903,0.0736,1627.27912,162.51072,2564.1432,115.81444,64.621008,71.583928,66.88236 10/3/2017,0.0432,1.2763,0.1919,0.35735,0.0701,0.4059,0.3911,0.0733,1622.496375,160.111835,2579.4023,117.16434,64.351046,71.204777,66.62286 10/4/2017,0.0433,1.2717,0.1914,0.35608,0.0696,0.4058,0.3902,0.0733,1620.463725,159.153255,2562.4755,117.63225,63.559566,70.986294,66.179268 10/5/2017,0.0438,1.2829,0.1927,0.3578,0.0694,0.4068,0.3935,0.0737,1635.05605,163.18488,2565.8,118.347525,65.158491,73.240761,68.237451 10/6/2017,0.044,1.2872,0.1937,0.35595,0.0694,0.4081,0.3937,0.0738,1624.18896,167.336,2593.708,116.87776,63.446088,71.63268,66.767064 10/9/2017,0.0439,1.2897,0.1945,0.34854,0.0691,0.4045,0.3943,0.0739,1649.203875,168.886215,2583.2691,117.10476,63.943326,71.823393,66.999915 10/10/2017,0.0435,1.2857,0.1953,0.34644,0.0683,0.4042,0.3938,0.0738,1660.35298,168.4267,2580.3999,116.805845,65.467844,72.629193,67.782104 10/11/2017,0.0434,1.284,0.1951,0.35197,0.0686,0.4044,0.3939,0.0737,1655.397,162.8112,2535.9,116.2662,65.8692,72.64872,68.21892 10/12/2017,0.0435,1.2787,0.194,0.34989,0.0676,0.4029,0.393,0.0734,1649.842675,161.563745,2553.5639,116.87318,64.70222,71.99081,66.952732 10/13/2017,0.0432,1.2677,0.1928,0.34881,0.067,0.4029,0.3901,0.0731,1647.50292,160.300665,2546.8093,115.61424,65.223165,72.347639,67.403609 10/16/2017,0.0434,1.2738,0.193,0.34934,0.0669,0.4019,0.3927,0.0735,1660.14354,157.63275,2532.3144,117.25329,66.072006,73.778496,68.606868 10/17/2017,0.0432,1.2747,0.1928,0.3475,0.0679,0.4033,0.3929,0.0736,1637.670825,158.254005,2525.1807,117.65481,66.131436,74.174793,68.8338 10/18/2017,0.0436,1.2745,0.1927,0.34641,0.0676,0.402,0.3937,0.0735,1631.6149,158.42035,2549,117.89125,66.32498,74.48178,68.89947 10/19/2017,0.0435,1.2692,0.1919,0.34808,0.0675,0.4003,0.3923,0.0728,1632.69888,160.99802,2573.9376,116.57602,65.097268,73.067844,67.52144 10/20/2017,0.0436,1.2793,0.1932,0.34849,0.0674,0.4006,0.3952,0.0735,1639.03916,160.232325,2584.186,117.631635,65.845571,74.45526,68.941477 10/23/2017,0.0434,1.281,0.1931,0.34467,0.0671,0.3959,0.3954,0.0736,1633.1469,159.29235,2585.058,117.5958,66.25332,73.46535,68.52069 10/24/2017,0.0432,1.286,0.1938,0.34359,0.0669,0.396,0.3974,0.0735,1641.5147,158.4352,2562.998,118.7621,67.24494,74.75518,69.97126 10/25/2017,0.0433,1.2981,0.1956,0.34456,0.0682,0.4013,0.4013,0.0743,1655.0775,161.09421,2609.181,119.360295,67.345428,75.536439,70.681545 10/26/2017,0.0433,1.305,0.196,0.34168,0.068,0.3959,0.4027,0.0739,1662.24375,162.53775,2603.475,120.25575,68.6952,77.21685,72.1665 10/27/2017,0.0433,1.3024,0.1962,0.34384,0.0681,0.4025,0.4012,0.074,1649.42448,164.88384,2585.264,120.27664,70.19936,78.586816,73.06464 10/30/2017,0.043,1.3007,0.1963,0.34414,0.0676,0.3965,0.4004,0.0735,1654.4904,163.75813,2529.8615,121.030135,70.432905,78.874448,73.541578 10/31/2017,0.0429,1.3062,0.1969,0.34437,0.0682,0.3993,0.4019,0.0741,1659.06993,163.40562,2484.3924,123.82776,71.031156,79.599828,74.623206 11/1/2017,0.0425,1.3028,0.1972,0.34163,0.0683,0.3988,0.4008,0.074,1663.74074,160.17926,2458.3836,124.0917,70.74204,78.793344,73.243416 11/2/2017,0.0428,1.2964,0.196,0.34142,0.0683,0.397,0.3996,0.074,1658.35488,163.86496,2483.9024,123.22282,70.705656,78.600732,73.155852 11/3/2017,0.043,1.3072,0.197,0.33624,0.0681,0.3944,0.403,0.0741,1656.48384,162.02744,2488.9088,122.8768,72.732608,81.072544,75.647664 11/6/2017,0.0428,1.3002,0.1968,0.3395,0.0684,0.3998,0.4014,0.0737,1652.42418,163.24011,2474.2806,123.19395,74.56647,83.381826,77.894982 11/7/2017,0.043,1.308,0.1973,0.33681,0.0683,0.3997,0.4034,0.0741,1668.4848,163.1076,2447.268,123.9984,74.8176,83.22804,77.87832 11/8/2017,0.0431,1.3024,0.1966,0.33687,0.0682,0.4007,0.4012,0.0743,1672.2816,163.7768,2419.8592,123.66288,73.989344,82.611232,77.128128 11/9/2017,0.0432,1.3021,0.1966,0.33693,0.0684,0.4006,0.4016,0.0744,1672.93808,164.58544,2438.8333,123.30887,74.441057,82.956791,77.722349 11/10/2017,0.0434,1.3054,0.1961,0.3377,0.0683,0.3975,0.4024,0.0747,1676.52522,166.50377,2434.571,124.46989,74.068396,82.879846,77.684354 11/13/2017,0.0436,1.3117,0.1971,0.3389,0.0686,0.4,0.4047,0.075,1676.287015,167.37292,2456.8141,124.283575,74.452092,82.427228,77.455885 11/14/2017,0.0434,1.3103,0.1978,0.33719,0.0684,0.3952,0.4035,0.0749,1670.10838,166.473615,2460.7434,123.495775,72.98371,79.902094,76.246357 11/15/2017,0.0435,1.3176,0.199,0.33949,0.0685,0.3975,0.4047,0.0752,1689.42672,167.0058,2495.5344,123.65676,72.902808,81.085104,76.35492 11/16/2017,0.0437,1.3179,0.1986,0.34118,0.0692,0.4021,0.406,0.0754,1686.912,166.97793,2482.9236,123.816705,72.669006,80.470974,75.739713 11/17/2017,0.044,1.3219,0.2,0.34086,0.0699,0.4056,0.4077,0.0756,1697.782265,163.65122,2462.6997,123.99422,74.753445,82.380808,77.621968 11/20/2017,0.0439,1.3245,0.1996,0.33718,0.0697,0.4067,0.409,0.0758,1703.5719,162.78105,2430.4575,124.569225,74.291205,82.079265,76.966695 11/21/2017,0.0441,1.3196,0.199,0.33359,0.0703,0.4056,0.4077,0.0755,1693.44268,163.43246,2399.0328,123.77848,74.847712,82.488196,77.143816 11/22/2017,0.0441,1.3124,0.1993,0.33499,0.0704,0.4072,0.4055,0.0753,1688.99318,163.45942,2342.634,123.23436,76.079828,82.864936,77.654708 11/23/2017,0.044,1.3115,0.1992,0.33448,0.0704,0.4069,0.4051,0.0754,1692.294025,163.347325,2339.716,123.41215,76.027655,82.96549,77.601455 11/24/2017,0.044,1.3129,0.1988,0.33187,0.0707,0.4062,0.4055,0.0757,1694.29745,163.84992,2317.2685,123.80647,77.264165,83.342892,78.406388 11/27/2017,0.0438,1.3154,0.1991,0.33678,0.0708,0.4078,0.4065,0.076,1703.31146,165.14847,2290.1114,120.81949,76.437894,83.501592,78.476764 11/28/2017,0.0439,1.3166,0.199,0.33212,0.071,0.4097,0.4072,0.0758,1700.84971,167.80067,2334.3318,121.19303,76.349634,83.024796,78.192874 11/29/2017,0.0439,1.3209,0.1997,0.33345,0.0711,0.4072,0.4085,0.0758,1695.837465,171.18864,2368.3737,122.8437,75.68757,82.846848,77.193396 11/30/2017,0.0438,1.3217,0.1994,0.33728,0.0709,0.4043,0.4088,0.0764,1692.04034,166.93071,2369.8081,122.52159,75.86558,82.976326,77.107978 12/1/2017,0.0438,1.3136,0.199,0.3356,0.0705,0.4032,0.4061,0.0763,1675.4968,167.54968,2302.7408,121.77072,76.661696,83.636912,77.63376 12/4/2017,0.044,1.3161,0.1989,0.33968,0.0707,0.4056,0.4071,0.0759,1675.987545,166.815675,2266.3242,123.121155,75.636267,82.111479,76.59702 12/5/2017,0.0439,1.3145,0.1983,0.34197,0.07,0.4054,0.4061,0.076,1664.55135,165.561275,2309.5765,122.708575,75.74149,82.31399,77.069135 12/6/2017,0.0439,1.3221,0.1998,0.34329,0.0701,0.4086,0.4088,0.0767,1670.73777,165.064185,2324.2518,124.14519,73.984716,81.057951,75.412584 12/7/2017,0.0442,1.3313,0.2009,0.34476,0.0702,0.4042,0.4115,0.0771,1670.7815,160.887605,2303.149,124.74281,75.471397,82.953303,77.375156 12/8/2017,0.0442,1.3317,0.2011,0.34716,0.0704,0.4044,0.4116,0.0771,1665.490605,160.60302,2330.475,125.71248,76.386312,84.789339,78.83664 12/11/2017,0.0441,1.3287,0.2005,0.34634,0.0697,0.4022,0.4106,0.0771,1657.088205,158.1153,2295.9936,125.82789,77.051313,86.644527,79.961166 12/12/2017,0.0437,1.3229,0.2,0.34376,0.069,0.3985,0.4091,0.0763,1641.58661,154.845445,2233.0552,126.07237,75.590506,85.697462,78.223077 12/13/2017,0.0434,1.3094,0.1986,0.34353,0.0689,0.3947,0.405,0.0757,1627.12591,155.75313,2241.6928,124.393,74.11204,82.81955,76.102328 12/14/2017,0.0435,1.3044,0.1976,0.33561,0.0682,0.3911,0.4023,0.0748,1631.8044,155.41926,2273.5692,124.04844,74.402976,83.533776,76.881336 12/15/2017,0.0435,1.3081,0.1974,0.33864,0.0684,0.3961,0.3967,0.0747,1641.14226,152.982295,2264.3211,124.465715,74.95413,83.45678,77.034009 12/18/2017,0.0438,1.3045,0.1971,0.34059,0.0684,0.3967,0.3977,0.0743,1644.4527,154.648475,2251.567,124.05795,74.56522,82.900975,77.06986 12/19/2017,0.0439,1.305,0.1978,0.34045,0.0679,0.3965,0.3976,0.0741,1644.75675,158.88375,2239.38,123.77925,74.9853,83.48085,77.8041 12/20/2017,0.0441,1.3043,0.1984,0.34153,0.0679,0.3957,0.3991,0.0735,1649.352565,160.624545,2232.9616,123.712855,75.675486,83.905619,78.727548 12/21/2017,0.0438,1.2984,0.1975,0.34004,0.0667,0.3927,0.3973,0.0724,1641.89172,158.7294,2213.772,123.08832,75.735672,83.7468,78.631104 12/22/2017,0.0437,1.2966,0.1971,0.34045,0.0656,0.3885,0.4006,0.0718,1639.61553,156.11064,2218.4826,122.91768,75.747372,83.89002,78.988872 12/25/2017,0.0438,1.2966,0.1981,0.34033,0.0657,0.3884,0.4005,0.0718,1639.61553,156.11064,2218.4826,122.91768,75.747372,83.864088,78.988872 12/26/2017,0.0436,1.2939,0.1978,0.33972,0.0651,0.3909,0.3993,0.0706,1636.201245,158.11458,2213.8629,122.66172,77.595183,85.91496,81.049896 12/27/2017,0.0433,1.2872,0.1962,0.33721,0.0654,0.3881,0.3972,0.0698,1646.84368,160.2564,2195.9632,122.02656,76.768608,85.032432,79.960864 12/28/2017,0.043,1.2828,0.1965,0.33987,0.0651,0.3873,0.3959,0.0669,1656.0948,160.09344,2192.3052,121.60944,76.762752,85.165092,80.136516 12/29/2017,0.0429,1.281,0.1968,0.33665,0.0652,0.3867,0.3955,0.0688,1653.771,161.6622,2195.634,121.4388,77.39802,85.59642,79.99845 1/1/2018,0.0429,1.2812,0.1968,0.33782,0.0652,0.3868,0.3957,0.0688,1654.0292,161.68744,2195.9768,121.45776,77.410104,85.558536,80.01094 1/2/2018,0.0436,1.2773,0.1969,0.33918,0.0654,0.3916,0.3945,0.0694,1675.881465,166.30446,2241.6615,123.451045,77.110601,85.183137,79.716293 1/3/2018,0.044,1.2763,0.1965,0.33751,0.066,0.3942,0.3966,0.0692,1678.20687,164.13218,2243.7354,123.099135,78.658369,87.120238,81.096102 1/4/2018,0.044,1.2715,0.1961,0.3393,0.0659,0.3936,0.3961,0.0683,1671.38675,164.722825,2226.3965,122.254725,78.845715,86.907025,80.91826 1/5/2018,0.0438,1.2718,0.1963,0.34072,0.0663,0.3939,0.3959,0.0674,1675.15137,163.36271,2221.8346,122.41075,78.139392,86.584144,80.606684 1/8/2018,0.0439,1.2753,0.1964,0.34053,0.0663,0.394,0.3966,0.067,1683.332235,159.603795,2178.2124,123.002685,78.724269,86.988213,81.10908 1/9/2018,0.0439,1.2782,0.196,0.33909,0.0664,0.3934,0.3971,0.0675,1675.7202,159.96673,2229.1808,122.83502,80.475472,88.77099,82.201042 1/10/2018,0.0441,1.2751,0.1956,0.33548,0.0661,0.3941,0.3957,0.0684,1682.813225,158.048645,2226.3246,121.963315,81.058107,88.36443,82.345958 1/11/2018,0.0444,1.2672,0.1952,0.33588,0.0657,0.3943,0.3937,0.0678,1676.56896,155.61216,2211.264,120.89088,80.84736,87.892992,81.92448 1/12/2018,0.0442,1.2631,0.1961,0.33691,0.0664,0.3941,0.3927,0.0677,1675.88108,154.413975,2205.3726,120.689205,81.21733,88.454893,82.530954 1/15/2018,0.0442,1.2554,0.1951,0.33037,0.0666,0.3904,0.391,0.067,1681.29445,153.47265,2193.1838,119.8907,80.72222,88.355052,82.027836 1/16/2018,0.0439,1.2562,0.1953,0.33078,0.0669,0.3896,0.3914,0.0665,1675.58237,151.30929,2189.5566,119.77867,80.057626,87.092346,81.452008 1/17/2018,0.0441,1.2546,0.1949,0.32859,0.067,0.3893,0.3907,0.0665,1675.70649,154.44126,2244.4794,119.43792,80.256762,87.094332,81.373356 1/18/2018,0.044,1.25,0.1948,0.33163,0.0672,0.3893,0.389,0.0662,1665.25,151.375,2258.75,118.75,79.9375,86.4125,81.3375 1/19/2018,0.0439,1.2511,0.1949,0.32883,0.0671,0.3915,0.3894,0.0659,1670.155945,151.695875,2221.9536,119.10472,79.282207,85.925548,80.508285 1/22/2018,0.0437,1.2474,0.1947,0.3304,0.0668,0.3893,0.3881,0.0652,1662.28524,152.86887,2224.1142,118.81485,79.197426,86.145444,80.70678 1/23/2018,0.0438,1.25,0.1953,0.33183,0.0669,0.3859,0.3883,0.0646,1666.75,151.1875,2211.25,119.0625,80.65,87.0125,82.125 1/24/2018,0.0441,1.2398,0.1947,0.33166,0.067,0.3946,0.3858,0.0631,1678.31726,151.8755,2218.0022,117.96697,81.467258,87.306716,82.19874 1/25/2018,0.0447,1.246,0.1954,0.33211,0.067,0.3957,0.3875,0.0637,1688.2677,154.0679,2214.142,118.6192,81.75006,87.04556,81.99926 1/26/2018,0.0438,1.2329,0.1954,0.32869,0.0667,0.3917,0.3835,0.0631,1668.298635,154.297435,2184.6988,117.49537,81.544006,86.512593,81.470032 1/29/2018,0.0435,1.2354,0.1948,0.32565,0.0664,0.3915,0.3842,0.0631,1660.19229,154.36323,2163.1854,112.66848,80.992824,85.48968,80.523372 1/30/2018,0.0434,1.2369,0.1955,0.32714,0.0659,0.3889,0.3846,0.063,1663.50681,151.27287,2137.3632,112.372365,79.78005,84.220521,79.681098 1/31/2018,0.0439,1.2413,0.1961,0.33054,0.0667,0.3895,0.386,0.0632,1669.610565,151.252405,2144.9664,111.22048,80.349349,85.438679,80.523131 2/1/2018,0.0445,1.2439,0.1982,0.33338,0.0678,0.3924,0.3873,0.0643,1668.505265,151.00946,2200.4591,109.152225,81.84862,86.849098,81.114719 2/2/2018,0.0444,1.2619,0.2,0.33478,0.0679,0.392,0.3922,0.0648,1679.778185,151.93276,2225.9916,111.55196,82.591355,85.872295,80.7616 2/5/2018,0.0447,1.2693,0.2002,0.33484,0.0676,0.3902,0.3914,0.0652,1692.73848,152.06214,2259.354,110.746425,81.425595,84.903477,79.800891 2/6/2018,0.0447,1.2649,0.2022,0.3355,0.068,0.391,0.3898,0.0646,1684.08786,155.392965,2281.8796,108.14895,80.182011,84.988631,79.157442 2/7/2018,0.0449,1.2784,0.2024,0.33607,0.0681,0.3907,0.3932,0.0649,1693.43256,157.62672,2283.2224,109.49496,78.992336,83.709632,78.007968 2/8/2018,0.0445,1.2851,0.2027,0.33623,0.068,0.3912,0.3934,0.0643,1690.484795,157.874535,2304.1843,107.498615,78.583865,82.37491,76.579109 2/9/2018,0.0435,1.2801,0.203,0.3351,0.0685,0.3878,0.3909,0.064,1682.17941,155.980185,2295.2193,105.288225,75.78192,79.903842,74.527422 2/12/2018,0.044,1.2718,0.2018,0.33467,0.0684,0.3853,0.3892,0.0636,1681.70114,154.39652,2275.2502,104.85991,75.405022,79.36032,73.980606 2/13/2018,0.0438,1.2724,0.2008,0.33395,0.0682,0.3855,0.3885,0.0637,1686.37534,156.1871,2297.9544,107.45418,75.313356,79.308692,74.130024 2/14/2018,0.044,1.2617,0.2009,0.33356,0.0679,0.3913,0.3868,0.0634,1685.946625,154.93676,2284.9387,107.307585,76.45902,81.013757,75.550596 2/15/2018,0.0441,1.2586,0.1991,0.33436,0.068,0.3895,0.3878,0.064,1702.19357,153.23455,2288.1348,106.85514,77.202524,80.92798,75.478242 2/16/2018,0.0446,1.2646,0.199,0.33715,0.0683,0.3914,0.389,0.064,1709.86566,149.15957,2262.3694,107.68069,78.000528,81.94608,76.25538 2/19/2018,0.0446,1.2638,0.1995,0.33621,0.0682,0.3909,0.3893,0.0635,1701.83308,149.06521,2245.7726,107.67576,77.951184,82.639882,76.20714 2/20/2018,0.0443,1.2684,0.1997,0.33389,0.0678,0.3899,0.3902,0.0639,1699.46574,149.92488,2298.3408,108.63846,78.51396,82.268424,76.890408 2/21/2018,0.0445,1.2813,0.201,0.33807,0.068,0.3923,0.3936,0.0644,1704.76965,149.848035,2315.3091,109.67928,78.966519,83.181996,77.403333 2/22/2018,0.0446,1.2746,0.2004,0.33688,0.0685,0.392,0.3924,0.0639,1693.11491,152.44216,2295.5546,109.6156,79.942912,84.18733,78.681058 2/23/2018,0.0448,1.2754,0.2019,0.33669,0.0688,0.3938,0.3924,0.0639,1693.66743,152.34653,2286.7922,109.42932,80.962392,85.57934,80.056858 2/26/2018,0.0448,1.2732,0.2021,0.33631,0.0682,0.3948,0.392,0.0631,1697.8122,153.4206,2279.028,106.37586,81.370212,85.699092,80.313456 2/27/2018,0.0449,1.2838,0.2023,0.33645,0.0681,0.395,0.3947,0.0635,1701.99785,153.99181,2290.2992,105.33579,80.892238,85.192968,79.78817 2/28/2018,0.0449,1.2884,0.2026,0.33912,0.0684,0.3968,0.3945,0.064,1697.91794,155.96082,2280.468,105.06902,79.416976,83.050264,77.767824 3/1/2018,0.0447,1.2894,0.2032,0.33887,0.0684,0.3965,0.3953,0.064,1686.21285,157.88703,2329.9458,102.12048,78.640506,82.547388,77.04165 3/2/2018,0.0449,1.2886,0.2035,0.33854,0.0685,0.3959,0.3952,0.0636,1703.91578,155.08301,2314.3256,101.73497,78.92675,83.011612,77.354658 3/5/2018,0.0451,1.2878,0.2034,0.33816,0.0685,0.397,0.3963,0.0637,1700.41112,153.50576,2320.6156,103.08839,80.577646,84.260754,78.800482 3/6/2018,0.0448,1.2773,0.2023,0.33664,0.0682,0.3978,0.3929,0.0629,1700.59722,153.212135,2332.3498,103.58903,79.95898,83.548193,78.234625 3/7/2018,0.0446,1.2779,0.2024,0.33608,0.0683,0.3941,0.3928,0.0627,1698.84026,152.45347,2344.9465,104.14885,78.143585,82.283981,76.865685 3/8/2018,0.0447,1.2844,0.2023,0.3359,0.0688,0.3934,0.3942,0.0632,1696.6924,152.8436,2324.764,104.16484,77.218128,81.674996,76.280516 3/9/2018,0.0444,1.2743,0.2014,0.33436,0.0684,0.3914,0.3913,0.063,1682.84058,151.450555,2331.969,103.60059,79.057572,83.186304,77.821501 3/12/2018,0.0446,1.2702,0.2009,0.33036,0.0683,0.3895,0.3896,0.0629,1675.58433,150.07413,2313.0342,102.82269,77.939472,82.232748,76.936014 3/13/2018,0.0446,1.2723,0.2006,0.32843,0.0684,0.3902,0.3899,0.063,1682.934825,153.248535,2309.2245,103.501605,77.241333,82.06335,76.617906 3/14/2018,0.0447,1.2694,0.2011,0.32721,0.0683,0.3892,0.3901,0.0628,1680.11437,152.26453,2289.9976,102.88487,77.382624,81.8763,77.699974 3/15/2018,0.045,1.2824,0.2021,0.32918,0.0686,0.3902,0.3931,0.0631,1691.165,150.87436,2277.5424,103.81028,78.470056,82.740448,78.777832 3/16/2018,0.0454,1.2964,0.2042,0.33057,0.0694,0.3952,0.3961,0.0642,1698.41364,151.61398,2314.074,103.712,80.817576,84.888272,80.999072 3/19/2018,0.0454,1.2956,0.205,0.32908,0.0693,0.3943,0.3961,0.0641,1700.34544,153.33426,2338.558,103.0002,80.404936,84.848844,80.871352 3/20/2018,0.0454,1.3016,0.2051,0.33086,0.0693,0.3931,0.3986,0.0643,1706.3976,154.82532,2345.4832,104.7788,82.52144,87.064024,82.78176 3/21/2018,0.0451,1.2878,0.2052,0.32947,0.0698,0.3934,0.3961,0.0635,1701.63453,153.05503,2318.04,103.53912,83.861536,89.167272,84.582704 3/22/2018,0.0455,1.2999,0.2049,0.33033,0.0697,0.3922,0.4016,0.0643,1727.762085,154.6881,2325.5211,104.25198,83.45358,88.926159,83.84355 3/23/2018,0.0457,1.2991,0.2048,0.3261,0.0701,0.3923,0.403,0.0644,1749.36806,152.25452,2261.7331,103.343405,85.519753,90.755126,86.182294 3/26/2018,0.046,1.2907,0.2064,0.32548,0.0704,0.3895,0.4012,0.064,1745.54268,152.496205,2240.6552,102.546115,84.605385,89.755278,85.237828 3/27/2018,0.0468,1.3022,0.2065,0.32706,0.0708,0.3914,0.4036,0.0646,1746.83619,154.89669,2321.8226,103.32957,84.96855,89.734602,85.202946 3/28/2018,0.0467,1.3051,0.2068,0.32543,0.0713,0.3928,0.404,0.0648,1738.980495,153.675525,2319.1627,103.62494,84.022338,89.830033,85.470999 3/29/2018,0.0467,1.3021,0.2073,0.33023,0.0716,0.3938,0.4036,0.0646,1723.785085,153.843115,2313.8317,103.51695,84.558374,90.131362,85.665159 3/30/2018,0.0465,1.3011,0.2072,0.32869,0.0715,0.393,0.4032,0.0645,1722.461235,153.724965,2312.0547,103.43745,84.493434,89.945043,85.599369 4/2/2018,0.0466,1.3053,0.2078,0.32864,0.0715,0.3939,0.4045,0.0648,1728.021405,151.93692,2319.5181,103.1187,82.246953,87.637842,83.186769 4/3/2018,0.0468,1.3012,0.2071,0.32622,0.0714,0.3895,0.4036,0.0645,1735.08514,151.71992,2262.7868,105.00684,82.639212,88.442564,83.576076 4/4/2018,0.0464,1.296,0.206,0.32411,0.0716,0.3891,0.4019,0.0643,1733.1408,151.5024,2274.48,103.5504,82.12752,88.08912,83.28096 4/5/2018,0.0466,1.3013,0.2065,0.32119,0.0715,0.3889,0.4033,0.0645,1727.73601,152.967815,2288.9867,104.819715,82.684602,88.956868,84.259175 4/6/2018,0.0466,1.303,0.2064,0.3221,0.0712,0.3867,0.4025,0.0646,1734.5536,153.03735,2254.19,105.8036,80.86418,87.01434,82.50596 4/9/2018,0.0468,1.299,0.2059,0.31896,0.0708,0.3796,0.4012,0.0643,1730.20305,154.12635,2264.157,106.6479,82.38258,89.02047,83.98035 4/10/2018,0.0465,1.2883,0.2053,0.31327,0.0705,0.3778,0.3977,0.0639,1724.969285,151.50408,2201.7047,105.833845,84.396533,91.482183,86.754122 4/11/2018,0.0474,1.2892,0.2055,0.31177,0.0707,0.3821,0.3985,0.0639,1741.3869,152.31898,2194.2184,106.0367,86.144344,92.873968,87.73006 4/12/2018,0.0476,1.2895,0.205,0.31378,0.0709,0.3778,0.3997,0.0638,1729.670825,152.03205,2206.3345,105.674525,86.486765,93.269535,87.9439 4/13/2018,0.0475,1.2881,0.2051,0.31445,0.0714,0.3762,0.3996,0.0637,1730.81997,151.09413,2206.5153,105.36658,86.805059,93.838085,88.183326 4/16/2018,0.0471,1.285,0.205,0.3138,0.0714,0.376,0.3988,0.0636,1733.91475,146.81125,2185.785,105.17725,85.0927,92.2887,86.5833 4/17/2018,0.0472,1.2875,0.2049,0.31423,0.0713,0.3778,0.3998,0.0638,1727.95375,146.195625,2208.0625,104.480625,85.6445,92.506875,86.85475 4/18/2018,0.0474,1.2847,0.2047,0.32054,0.071,0.3801,0.3993,0.0638,1736.207815,147.61203,2228.9545,104.44611,87.963409,94.952177,89.774836 4/19/2018,0.0473,1.2938,0.205,0.3202,0.0701,0.3823,0.4019,0.0642,1744.81868,147.81665,2238.274,105.83284,88.353602,95.314246,90.346054 4/20/2018,0.0472,1.3038,0.2069,0.31981,0.0703,0.3819,0.405,0.0646,1742.85465,150.91485,2245.1436,106.65084,89.153844,95.998794,91.357266 4/23/2018,0.0468,1.315,0.2079,0.32005,0.0694,0.3809,0.4067,0.0649,1741.4545,153.855,2282.84,107.76425,90.19585,98.0727,93.102 4/24/2018,0.0472,1.3151,0.2086,0.32189,0.0699,0.3788,0.407,0.0649,1747.570635,155.83935,2290.9042,107.57518,88.966515,96.594095,91.623017 4/25/2018,0.047,1.322,0.2089,0.32387,0.0701,0.3794,0.4085,0.0653,1747.2213,154.4757,2279.128,108.1396,89.9621,97.12734,92.0112 4/26/2018,0.0471,1.3238,0.2089,0.32559,0.0704,0.381,0.409,0.0644,1748.34266,155.67888,2300.7644,108.15446,90.269922,98.09358,93.208758 4/27/2018,0.047,1.3191,0.2087,0.32636,0.0709,0.3814,0.4077,0.0643,1743.19065,158.753685,2276.7666,107.90238,89.83071,97.415535,92.561247 4/30/2018,0.0473,1.3281,0.2094,0.32694,0.071,0.3789,0.4083,0.0647,1744.06092,160.235265,2280.3477,113.15412,91.067817,99.434847,94.374786 5/1/2018,0.0477,1.335,0.2109,0.32534,0.0704,0.3807,0.4098,0.065,1744.9785,163.671,2374.965,113.8755,89.77875,98.08245,92.55555 5/2/2018,0.0471,1.3347,0.2094,0.31957,0.0699,0.3757,0.408,0.063,1740.71574,162.29952,2411.8029,113.58297,90.666171,97.526529,92.267811 5/3/2018,0.0464,1.3276,0.2096,0.31514,0.0697,0.3763,0.4056,0.0597,1745.86038,162.23272,2430.8356,113.11152,90.847668,97.737912,92.66648 5/4/2018,0.047,1.3265,0.209,0.31364,0.0688,0.3759,0.4056,0.0607,1736.9191,159.776925,2398.312,113.084125,92.48358,99.35485,94.28762 5/7/2018,0.0471,1.3305,0.2088,0.31172,0.0684,0.3748,0.4058,0.0606,1742.1567,157.2651,2405.544,113.425125,94.106265,100.412835,94.83804 5/8/2018,0.0467,1.3417,0.2109,0.30972,0.0685,0.3765,0.408,0.0597,1753.06522,156.375135,2401.643,116.392475,92.657802,101.781362,96.293809 5/9/2018,0.0468,1.3405,0.2107,0.31275,0.0685,0.3731,0.4068,0.0591,1761.215925,154.82775,2335.151,116.75755,95.36317,103.231905,98.057575 5/10/2018,0.047,1.3274,0.2096,0.31347,0.0691,0.374,0.4062,0.0585,1750.57512,154.37662,2309.676,116.94394,94.723264,102.262896,97.537352 5/11/2018,0.0467,1.3261,0.2095,0.3073,0.0683,0.3684,0.4072,0.0576,1756.220535,152.833025,2322.0011,117.293545,93.75527,101.486433,97.269435 5/14/2018,0.0468,1.3288,0.2091,0.30423,0.0677,0.3669,0.4078,0.0531,1753.81668,151.01812,2305.468,119.12692,94.291648,103.340776,99.208208 5/15/2018,0.0465,1.3383,0.2098,0.3011,0.0679,0.3662,0.4084,0.0556,1733.0985,151.09407,2299.1994,119.77785,95.434173,103.865463,99.462456 5/16/2018,0.0465,1.3305,0.2092,0.30146,0.068,0.362,0.4077,0.0548,1718.008125,150.679125,2297.7735,119.34585,95.117445,104.457555,100.18665 5/17/2018,0.0459,1.3312,0.209,0.29861,0.0675,0.3601,0.4067,0.0548,1716.5824,151.55712,2316.288,120.07424,95.167488,104.991744,100.332544 5/18/2018,0.0456,1.3317,0.2087,0.29641,0.0667,0.3562,0.405,0.0546,1715.62911,151.747215,2330.475,119.32032,94.923576,103.992453,99.691062 5/21/2018,0.0459,1.319,0.2072,0.28833,0.0665,0.3589,0.4017,0.0541,1699.33365,158.5438,2351.777,118.1824,95.28456,104.13505,99.87468 5/22/2018,0.0463,1.3199,0.207,0.28263,0.0668,0.3618,0.4034,0.0544,1706.696695,159.509915,2323.024,118.329035,95.204387,104.100513,98.966102 5/23/2018,0.046,1.3229,0.2075,0.28912,0.0674,0.3645,0.4052,0.0541,1705.2181,157.888115,2283.3254,118.333405,95.023907,104.747222,99.654057 5/24/2018,0.0463,1.32,0.2072,0.28031,0.0674,0.3618,0.4041,0.0537,1722.402,159.126,2283.6,118.47,93.2976,103.3692,98.3004 5/25/2018,0.046,1.3249,0.2071,0.28153,0.0678,0.3626,0.4053,0.0539,1727.00715,159.51796,2278.828,118.71104,89.973959,100.493665,95.485543 5/28/2018,0.046,1.3252,0.207,0.2892,0.0676,0.3544,0.4045,0.0536,1727.3982,159.55408,2279.344,122.71352,89.994332,98.979188,95.507164 5/29/2018,0.0458,1.3323,0.2073,0.29307,0.0672,0.3574,0.4066,0.0536,1725.99465,160.209075,2276.9007,125.50266,88.904379,99.869208,94.713207 5/30/2018,0.0459,1.3198,0.2061,0.29546,0.0669,0.3542,0.4035,0.0529,1716.66386,158.77194,2243.66,126.37085,90.023558,101.782976,97.0053 5/31/2018,0.0457,1.3214,0.2063,0.2918,0.0664,0.3548,0.4039,0.0529,1724.88949,163.45718,2272.808,125.533,88.586656,101.919582,96.092208 6/1/2018,0.0461,1.3212,0.206,0.28374,0.0663,0.351,0.4037,0.0529,1710.42552,162.1773,2312.1,125.91036,86.948172,100.688652,93.950532 6/4/2018,0.0456,1.3079,0.2042,0.28465,0.0651,0.3491,0.4001,0.0524,1694.319055,158.90985,2282.2855,125.231425,84.686525,97.660893,91.448368 6/5/2018,0.046,1.3129,0.2052,0.2855,0.0642,0.3446,0.4017,0.0527,1696.332445,156.825905,2293.6363,124.59421,86.021208,97.614115,91.272808 6/6/2018,0.0461,1.3042,0.2041,0.28634,0.0642,0.3386,0.3997,0.0524,1695.59042,154.22165,2283.6542,123.63816,84.420866,97.841084,91.476588 6/7/2018,0.0461,1.3116,0.2048,0.29259,0.064,0.3356,0.4019,0.0525,1701.4731,151.75212,2273.0028,125.12664,86.50002,100.652184,93.989256 6/8/2018,0.046,1.3157,0.2054,0.29439,0.0648,0.3548,0.4035,0.052,1708.107525,154.265825,2264.3197,125.64935,86.494118,99.690589,93.269973 6/11/2018,0.046,1.314,0.2051,0.29061,0.0638,0.354,0.4024,0.0504,1707.6744,153.8694,2279.79,126.3411,86.8554,99.4041,93.13632 6/12/2018,0.0462,1.3204,0.2054,0.28731,0.0637,0.3549,0.4037,0.0513,1714.73746,154.94894,2282.9716,127.88074,87.621744,98.752716,92.903344 6/13/2018,0.0462,1.3196,0.2057,0.28325,0.0639,0.3546,0.4032,0.0504,1710.39954,153.53546,2251.2376,127.73728,87.938144,99.9597,94.28542 6/14/2018,0.0467,1.3371,0.2074,0.28292,0.064,0.3514,0.4073,0.0482,1741.907025,154.70247,2290.4523,129.364425,89.438619,100.563291,94.439373 6/15/2018,0.0464,1.3439,0.2084,0.28397,0.0651,0.3603,0.4097,0.0479,1727.247475,154.81728,2292.6934,129.68635,87.434134,97.473067,91.438956 6/18/2018,0.0461,1.347,0.2092,0.28633,0.0657,0.3598,0.411,0.0488,1726.24785,154.16415,2291.247,130.3896,88.69995,100.59396,94.18224 6/19/2018,0.0463,1.3548,0.2091,0.28542,0.066,0.3616,0.4123,0.0488,1728.92802,154.58268,2297.7408,131.4156,88.156836,100.648092,93.996024 6/20/2018,0.0464,1.3573,0.2095,0.28676,0.0667,0.3597,0.414,0.0489,1729.47166,154.257145,2315.5538,131.11518,89.880406,99.856561,93.314375 6/21/2018,0.0459,1.3557,0.2089,0.28723,0.0667,0.3596,0.414,0.0493,1716.519555,152.65182,2327.7369,130.1472,89.259288,98.274693,91.604649 6/22/2018,0.0461,1.3439,0.207,0.2872,0.0672,0.3551,0.4111,0.0497,1705.610685,153.003015,2316.8836,129.0144,92.702222,100.832817,94.193951 6/25/2018,0.0462,1.3487,0.2064,0.28803,0.0678,0.3575,0.4125,0.0498,1711.09569,153.954105,2263.1186,129.61007,96.539946,100.140975,93.357014 6/26/2018,0.0462,1.3528,0.2055,0.29318,0.0678,0.3557,0.414,0.05,1704.93384,155.30144,2294.3488,129.93644,95.412984,102.67752,95.899992 6/27/2018,0.0463,1.3624,0.2053,0.29481,0.0675,0.3529,0.4164,0.0497,1709.26704,155.72232,2361.0392,130.7904,99.128224,104.318968,98.0928 6/28/2018,0.0461,1.3602,0.2052,0.29666,0.069,0.3521,0.4152,0.0485,1702.35831,152.54643,2353.146,130.5792,99.90669,104.66739,98.111226 6/29/2018,0.0461,1.3503,0.2042,0.29433,0.0678,0.3482,0.4117,0.0467,1688.482635,150.55845,2326.5669,129.6288,100.124745,106.13358,99.814176 7/2/2018,0.0465,1.3626,0.2049,0.29519,0.0683,0.3483,0.4145,0.0482,1700.25228,146.88828,2368.1988,134.55675,100.750644,104.838444,97.657542 7/3/2018,0.0466,1.354,0.2039,0.28986,0.0696,0.3475,0.4118,0.0484,1694.8695,146.7059,2349.19,134.5876,100.38556,104.71836,98.0296 7/4/2018,0.0466,1.3545,0.2043,0.29018,0.0697,0.3461,0.4117,0.0483,1700.777925,146.760075,2355.4755,135.111375,100.42263,105.149835,98.0658 7/5/2018,0.0471,1.3536,0.2039,0.2947,0.0704,0.3443,0.4118,0.0482,1699.4448,143.88768,2305.1808,135.90144,98.731584,104.118912,97.1208 7/6/2018,0.0468,1.3463,0.2026,0.29425,0.0707,0.3484,0.4101,0.0482,1690.077705,149.775875,2338.5231,134.89926,99.35694,103.018876,96.098894 7/9/2018,0.0464,1.3393,0.2024,0.28295,0.0697,0.3458,0.4089,0.048,1690.263565,150.26946,2383.954,136.541635,98.907305,103.782357,97.126036 7/10/2018,0.0467,1.3407,0.2019,0.2849,0.0708,0.3515,0.4097,0.0489,1681.2378,150.091365,2399.853,137.01954,99.359277,104.856147,97.897914 7/11/2018,0.0469,1.3575,0.2024,0.27851,0.0712,0.3503,0.4139,0.0495,1698.7755,148.239,2378.34,139.2795,95.54085,99.66765,92.7987 7/12/2018,0.0469,1.3499,0.2024,0.27816,0.0711,0.3478,0.4125,0.0496,1681.84041,146.73413,2402.822,137.082345,94.938467,99.568624,93.00811 7/13/2018,0.0471,1.3478,0.2016,0.27747,0.0713,0.35,0.4121,0.0495,1673.56326,144.28199,2380.2148,136.66692,95.707278,100.07415,93.564276 7/16/2018,0.0469,1.3476,0.2015,0.27799,0.0716,0.3491,0.4127,0.0493,1672.50636,144.79962,2383.9044,135.70332,91.717656,96.259068,89.453688 7/17/2018,0.0472,1.3534,0.2016,0.28158,0.0716,0.3525,0.4136,0.0492,1668.47152,143.05438,2372.5102,136.42272,92.139472,96.321478,90.06877 7/18/2018,0.0472,1.3518,0.2015,0.28197,0.0715,0.3512,0.4135,0.0489,1655.2791,141.39828,2350.7802,137.68083,92.949768,97.964946,91.273536 7/19/2018,0.0472,1.3596,0.2014,0.28276,0.0713,0.3548,0.4152,0.049,1655.38098,143.0979,2396.9748,137.25162,94.437816,98.040756,91.256352 7/20/2018,0.0468,1.348,0.1993,0.28103,0.0709,0.3575,0.4116,0.0489,1656.355,149.1562,2402.136,135.0022,94.98008,98.01308,91.01696 7/23/2018,0.0467,1.3549,0.1994,0.28581,0.0718,0.358,0.413,0.0491,1659.684755,151.274585,2418.4965,136.506175,94.219746,98.50123,91.767377 7/24/2018,0.0465,1.3482,0.1984,0.27596,0.0714,0.3593,0.4114,0.0491,1656.06147,149.58279,2409.2334,136.03338,95.075064,98.62083,91.960722 7/25/2018,0.0465,1.3414,0.1994,0.28104,0.0719,0.3634,0.4098,0.049,1651.9341,148.8954,2397.0818,135.41433,95.37354,99.303842,92.395632 7/26/2018,0.047,1.3556,0.1992,0.27865,0.0728,0.3618,0.4141,0.0495,1665.0157,148.50598,2239.4512,136.9156,94.363316,100.355068,94.254868 7/27/2018,0.0468,1.3511,0.1982,0.27811,0.0725,0.3641,0.4132,0.0494,1653.678845,149.228995,2233.3683,136.4611,92.807059,99.670647,93.698785 7/30/2018,0.047,1.3501,0.198,0.27657,0.0728,0.3618,0.4128,0.0495,1652.25238,150.40114,2241.166,127.98948,94.682513,100.595951,94.398992 7/31/2018,0.0466,1.3463,0.1973,0.27403,0.0722,0.3584,0.4116,0.0491,1643.764985,147.95837,2213.3172,128.03313,92.571588,98.374141,92.208087 8/1/2018,0.0466,1.3506,0.198,0.27033,0.0727,0.3601,0.4128,0.0491,1646.3814,145.93233,2228.49,128.50959,91.381596,96.97308,90.746814 8/2/2018,0.0467,1.3584,0.1981,0.26814,0.0729,0.3622,0.4149,0.0495,1651.06728,144.94128,2233.2096,128.7084,93.675264,98.68776,92.57496 8/3/2018,0.0467,1.3511,0.1977,0.26581,0.0728,0.3644,0.4133,0.0495,1643.34293,145.581025,2245.5282,127.611395,92.536839,98.387102,92.14502 8/6/2018,0.0467,1.3538,0.1974,0.25382,0.0731,0.3624,0.4139,0.0495,1637.62417,147.22575,2277.0916,130.03249,93.425738,98.583716,92.708224 8/7/2018,0.0465,1.3476,0.1972,0.25699,0.073,0.3591,0.4125,0.0492,1633.76286,146.95578,2247.7968,130.3803,93.213492,99.035124,93.846864 8/8/2018,0.0462,1.3456,0.1972,0.25492,0.0729,0.3568,0.4117,0.0487,1627.57048,145.12296,2226.968,129.71584,90.074464,95.927824,90.76072 8/9/2018,0.0466,1.3562,0.1981,0.2441,0.0726,0.3568,0.4147,0.0483,1646.90147,145.99493,2266.2102,130.80549,90.607722,96.317324,90.743342 8/10/2018,0.0465,1.3698,0.1998,0.21324,0.0724,0.3544,0.4177,0.0469,1663.48512,146.5686,2293.0452,132.66513,92.639574,98.707788,92.612178 8/13/2018,0.0457,1.3755,0.1994,0.19979,0.0719,0.354,0.4184,0.0459,1651.081425,146.146875,2292.9585,134.2488,92.4336,98.92596,92.915025 8/14/2018,0.0458,1.3815,0.2005,0.21704,0.0731,0.3571,0.4186,0.0464,1653.6555,145.126575,2305.7235,135.6633,92.61576,98.597655,93.14073 8/15/2018,0.0453,1.3814,0.1996,0.23327,0.0722,0.3537,0.4164,0.0462,1632.8148,141.45536,2269.6402,134.82464,89.804814,96.55986,90.06728 8/16/2018,0.0456,1.3772,0.1995,0.23643,0.0725,0.3527,0.4156,0.0463,1625.64688,140.06124,2297.1696,134.75902,90.151512,96.803388,90.729936 8/17/2018,0.0451,1.3674,0.1996,0.22721,0.0724,0.3496,0.4128,0.0458,1611.34416,138.38088,2246.6382,134.27868,90.125334,97.044378,90.480858 8/20/2018,0.0449,1.3627,0.1995,0.2241,0.0717,0.3432,0.4118,0.0456,1613.913745,132.522575,2252.5431,133.81714,90.524161,97.405796,90.646804 8/21/2018,0.0456,1.3577,0.1987,0.22345,0.0716,0.3353,0.4121,0.0453,1616.952815,132.986715,2241.5627,132.37575,91.441095,97.822285,90.640052 8/22/2018,0.0459,1.3606,0.1989,0.22478,0.0726,0.3365,0.4141,0.045,1628.16199,131.16184,2227.3022,131.84214,93.963036,101.065368,94.01746 8/23/2018,0.0462,1.3798,0.2,0.22636,0.0726,0.3352,0.4178,0.0453,1645.20453,134.11656,2226.9972,133.77161,94.971634,102.394958,95.371776 8/24/2018,0.0459,1.3651,0.2003,0.22704,0.0722,0.3325,0.4144,0.0443,1634.98027,137.260805,2211.462,132.4147,95.311282,102.396151,95.461443 8/27/2018,0.0463,1.3611,0.1998,0.22235,0.0725,0.3332,0.4138,0.044,1630.18947,138.628035,2204.982,133.3878,93.738957,103.021659,96.039216 8/28/2018,0.0456,1.3626,0.2,0.21718,0.0714,0.3293,0.4137,0.0433,1651.81185,135.23805,2204.6868,132.98976,93.378978,102.958056,96.19956 8/29/2018,0.0456,1.368,0.201,0.2114,0.0722,0.3331,0.4154,0.0402,1647.3456,134.9532,2217.528,133.9272,95.08968,105.37704,98.26344 8/30/2018,0.0454,1.3766,0.201,0.20704,0.072,0.3317,0.4165,0.0355,1648.20318,136.21457,2210.8196,134.76914,96.70615,106.13586,99.541946 8/31/2018,0.0456,1.3906,0.2031,0.21255,0.0729,0.343,0.4213,0.0377,1672.12697,136.41786,2201.3198,136.13974,97.06388,107.28479,100.317884 9/3/2018,0.0455,1.3862,0.2031,0.20892,0.0723,0.3333,0.4194,0.0364,1663.50931,135.98622,2170.7892,137.64966,96.75676,107.388914,100.000468 9/4/2018,0.045,1.393,0.2037,0.2086,0.0718,0.3349,0.4198,0.0357,1658.85405,136.16575,2149.399,140.34475,97.32891,107.9575,100.78355 9/5/2018,0.0449,1.3902,0.2037,0.21059,0.0719,0.3353,0.4189,0.036,1663.65234,139.15902,2178.4434,141.03579,95.534544,106.447614,99.26028 9/6/2018,0.045,1.3888,0.2033,0.21106,0.0724,0.3426,0.418,0.0371,1673.71232,136.03296,2138.752,140.2688,94.118976,106.020992,98.035392 9/7/2018,0.046,1.4073,0.2047,0.21967,0.0729,0.3469,0.4229,0.0379,1687.21197,139.04124,2161.6128,140.378175,95.344575,107.925837,99.664986 9/10/2018,0.0455,1.4057,0.2048,0.21749,0.0729,0.3441,0.4217,0.0375,1682.06062,137.05575,2160.5609,140.921425,94.940978,108.281071,100.057726 9/11/2018,0.0456,1.4042,0.205,0.21841,0.0732,0.3382,0.4213,0.037,1670.78737,135.08404,2168.0848,141.75399,97.24085,111.100304,102.450432 9/12/2018,0.0458,1.3945,0.2034,0.21981,0.0733,0.3352,0.4188,0.0364,1667.2642,136.451825,2206.099,140.14725,98.130965,111.295045,102.426025 9/13/2018,0.0461,1.3906,0.2032,0.22872,0.0738,0.3306,0.4195,0.0352,1682.34788,134.05384,2162.383,139.61624,95.381254,109.078664,100.735064 9/14/2018,0.0462,1.3978,0.2028,0.22654,0.074,0.335,0.4219,0.035,1680.08571,133.42001,2148.4186,139.0811,96.434222,109.252048,100.767402 9/17/2018,0.0461,1.3931,0.2031,0.22055,0.0739,0.3371,0.4212,0.0352,1674.36689,130.185195,2118.9051,138.404485,95.998521,108.480697,100.261407 9/18/2018,0.046,1.3851,0.2022,0.21695,0.0736,0.3328,0.4192,0.0348,1662.39702,127.4292,2123.3583,136.640115,96.749235,109.021221,101.458575 9/19/2018,0.0454,1.3768,0.2009,0.22014,0.0733,0.3337,0.4169,0.035,1656.70344,133.13656,2135.4168,138.09304,97.918016,109.056328,101.208568 9/20/2018,0.0456,1.3714,0.2008,0.22121,0.0728,0.3364,0.4159,0.0359,1657.13119,136.79715,2150.3552,136.66001,97.09512,107.58633,100.029916 9/21/2018,0.0457,1.3722,0.2003,0.21801,0.0729,0.3388,0.4166,0.0369,1644.85614,137.08278,2190.0312,137.63166,98.496516,107.264874,99.951048 9/24/2018,0.046,1.379,0.2008,0.22415,0.0727,0.3372,0.4176,0.037,1658.59225,135.8315,2200.884,138.38265,100.77732,111.36804,104.14208 9/25/2018,0.0459,1.3793,0.2008,0.22388,0.0726,0.3386,0.4175,0.036,1657.78067,133.93003,2078.6051,138.34379,100.109594,112.012953,104.68887 9/26/2018,0.0459,1.3778,0.2003,0.22562,0.0731,0.3417,0.4172,0.0358,1645.43765,134.67995,2081.8558,138.19334,98.609146,111.987584,103.376334 9/27/2018,0.0465,1.3875,0.2012,0.23101,0.0738,0.3458,0.4205,0.0349,1644.7425,137.77875,2103.45,139.235625,100.0665,113.02575,104.92275 9/28/2018,0.0467,1.3844,0.2011,0.22863,0.0739,0.3417,0.4191,0.0335,1643.6289,141.83178,2151.3576,138.64766,101.4073,114.83598,106.612644 10/1/2018,0.0461,1.3845,0.2015,0.23306,0.074,0.3444,0.4184,0.0351,1646.655075,141.4959,2176.434,140.9421,104.25285,117.82095,109.223205 10/2/2018,0.0461,1.3912,0.2022,0.23238,0.074,0.353,0.4197,0.0365,1675.97864,149.76268,2231.4848,140.78944,104.659976,117.876376,109.403968 10/3/2018,0.0467,1.4078,0.2039,0.23274,0.0739,0.3608,0.4235,0.0373,1691.04936,150.07148,2235.5864,143.10287,107.569998,121.197502,112.877404 10/4/2018,0.0466,1.4126,0.2056,0.22919,0.074,0.3645,0.4244,0.0366,1699.99347,151.07757,2282.7616,142.39008,104.998558,120.169882,111.298754 10/5/2018,0.0468,1.4185,0.2062,0.23122,0.0753,0.3692,0.4268,0.0375,1707.5903,154.545575,2347.6175,143.764975,105.45129,119.4377,110.997625 10/8/2018,0.0464,1.4128,0.2042,0.23116,0.0746,0.3738,0.425,0.0377,1676.92296,158.02168,2379.1552,143.11664,104.956912,118.39264,110.452704 10/9/2018,0.046,1.4078,0.2038,0.23077,0.074,0.3792,0.4233,0.0377,1669.01729,159.29257,2383.4054,141.90624,105.528688,119.677078,111.554072 10/10/2018,0.0458,1.4171,0.2036,0.23319,0.074,0.3773,0.4256,0.0381,1684.36506,158.57349,2383.5622,141.56829,103.689207,117.364222,109.173384 10/11/2018,0.0454,1.4039,0.2043,0.23715,0.074,0.3713,0.4216,0.0383,1692.471645,158.50031,2373.9949,139.12649,99.634783,113.027989,105.01172 10/12/2018,0.0454,1.4061,0.203,0.23936,0.0745,0.3719,0.4215,0.0384,1715.090475,163.880955,2408.6493,139.34451,100.311174,113.711307,105.851208 10/15/2018,0.0453,1.4024,0.2024,0.24238,0.0744,0.3753,0.4204,0.0382,1724.88188,167.37644,2437.3712,138.97784,100.664272,113.66452,105.656816 10/16/2018,0.0459,1.4003,0.2026,0.24617,0.0747,0.376,0.4201,0.039,1723.34921,164.745295,2442.1232,138.699715,100.709576,114.362501,106.00271 10/17/2018,0.0459,1.4067,0.2025,0.25194,0.0745,0.3815,0.4218,0.0389,1728.904635,172.391085,2468.7585,139.68531,98.117325,113.140881,104.630346 10/18/2018,0.0456,1.4086,0.2021,0.24981,0.0735,0.3783,0.4224,0.0383,1722.7178,171.91963,2473.5016,140.43742,96.70039,111.800582,103.630702 10/19/2018,0.0456,1.4047,0.2026,0.24904,0.0729,0.3786,0.4216,0.0384,1724.760895,171.51387,2411.8699,141.17235,97.092864,112.544564,104.186599 10/22/2018,0.0458,1.4122,0.2032,0.24911,0.0728,0.3832,0.4237,0.0387,1726.13206,166.14533,2395.0912,141.71427,97.681874,112.298144,105.448974 10/23/2018,0.0452,1.4113,0.2038,0.24571,0.0731,0.3819,0.4231,0.0386,1744.296235,170.90843,2389.3309,141.69452,93.611529,106.807184,100.103509 10/24/2018,0.0447,1.416,0.2037,0.24844,0.0722,0.3792,0.4237,0.0382,1742.4588,170.274,2390.208,142.0956,94.54632,106.92216,100.29528 10/25/2018,0.0446,1.4125,0.2031,0.25065,0.0725,0.3813,0.4229,0.0384,1738.505,171.124375,2364.525,141.815,95.103625,107.54775,101.572875 10/26/2018,0.0443,1.4105,0.2035,0.25208,0.0728,0.3872,0.4213,0.0383,1740.345425,168.766325,2413.3655,141.3321,95.335695,108.97523,102.698505 10/29/2018,0.0445,1.4171,0.2029,0.25454,0.0706,0.3809,0.4224,0.0384,1744.16668,161.903675,2363.7228,140.57632,95.002384,108.138901,101.861148 10/30/2018,0.0439,1.4073,0.202,0.25721,0.0702,0.3804,0.4185,0.0383,1724.50542,158.18052,2333.3034,138.90051,93.135114,106.53261,100.270125 10/31/2018,0.0439,1.4138,0.2021,0.2532,0.0695,0.3796,0.4194,0.0394,1717.69631,159.33526,2342.6666,137.91619,92.335278,104.423268,99.03669 11/1/2018,0.0434,1.3877,0.2006,0.25183,0.0688,0.3749,0.4125,0.0389,1708.466855,163.47106,2350.7638,132.317195,88.382613,100.011539,94.446862 11/2/2018,0.0437,1.3897,0.2014,0.25593,0.0694,0.3758,0.4137,0.0392,1712.24937,166.833485,2377.7767,133.55017,87.745658,100.016709,94.569085 11/5/2018,0.0436,1.3868,0.2003,0.26104,0.0697,0.372,0.412,0.0389,1708.8843,162.39428,2315.956,131.32996,87.50708,100.043752,93.997304 11/6/2018,0.0438,1.3802,0.1999,0.2576,0.07,0.3665,0.4095,0.0388,1699.85432,156.30765,2278.7102,128.70365,85.862242,98.173626,92.183558 11/7/2018,0.0439,1.3745,0.1984,0.25635,0.0692,0.3677,0.4088,0.0385,1690.566275,158.8922,2291.2915,129.203,84.765415,98.02934,92.0915 11/8/2018,0.0437,1.3779,0.1977,0.2525,0.0682,0.3665,0.4095,0.0389,1686.756285,160.732035,2287.314,127.18017,83.597193,96.618348,90.417798 11/9/2018,0.0435,1.3838,0.1984,0.25338,0.0687,0.371,0.4106,0.0391,1676.33532,157.54563,2298.4918,126.89446,83.290922,95.108574,89.711754 11/12/2018,0.0438,1.394,0.1992,0.25496,0.0685,0.3702,0.4131,0.0392,1680.5367,153.5491,2273.614,129.3632,83.54242,94.792,89.67602 11/13/2018,0.0435,1.3852,0.1997,0.25287,0.0676,0.3636,0.4098,0.0384,1665.14892,151.26384,2257.876,126.67654,77.141788,88.902136,83.486004 11/14/2018,0.0432,1.3828,0.1993,0.25315,0.0678,0.3651,0.4081,0.0385,1663.8541,155.77242,2274.706,125.1434,77.7825,89.411848,84.751812 11/15/2018,0.0431,1.3742,0.1981,0.25695,0.0679,0.363,0.4062,0.0381,1665.32427,151.23071,2256.4364,123.60929,77.587332,90.394876,84.65072 11/16/2018,0.0431,1.3639,0.1971,0.25573,0.0676,0.3647,0.403,0.038,1667.23136,153.57514,2220.4292,121.52349,77.005794,90.453848,84.452688 11/19/2018,0.0432,1.3709,0.1973,0.25805,0.0673,0.3645,0.4066,0.0382,1674.69144,154.020615,2205.7781,121.667375,77.812284,90.918088,84.940964 11/20/2018,0.0434,1.3863,0.1988,0.25776,0.0681,0.369,0.4098,0.0383,1695.4449,153.394095,2216.6937,122.063715,73.931379,85.687203,79.504305 11/21/2018,0.0432,1.3769,0.1985,0.25946,0.068,0.3625,0.4078,0.038,1688.21709,151.87207,2182.3865,120.89182,74.944667,86.662086,80.149349 11/22/2018,0.043,1.3786,0.1991,0.26,0.0679,0.3624,0.4089,0.0378,1691.61113,152.05958,2186.4596,122.14396,75.037198,85.376698,80.248306 11/23/2018,0.0429,1.3827,0.199,0.26158,0.0678,0.3612,0.4087,0.0368,1691.940855,148.156305,2176.3698,122.023275,69.439194,80.984739,74.375433 11/26/2018,0.0427,1.3849,0.199,0.26407,0.0672,0.3522,0.4097,0.0354,1694.28666,148.1843,2179.8326,122.632895,71.502387,83.094,76.668064 11/27/2018,0.0424,1.3841,0.199,0.2625,0.0676,0.3571,0.4093,0.0359,1690.26292,151.55895,2276.8445,122.63126,71.364196,83.59964,76.762186 11/28/2018,0.0419,1.3688,0.199,0.26216,0.0675,0.3551,0.4051,0.0356,1660.6966,150.70488,2210.612,121.27568,68.836952,79.45884,73.682504 11/29/2018,0.0422,1.3663,0.1967,0.26465,0.0675,0.3546,0.4043,0.0362,1675.425375,148.24355,2198.3767,121.05418,70.296135,80.529722,74.586317 11/30/2018,0.0423,1.3677,0.1971,0.26208,0.067,0.3537,0.4042,0.0362,1665.243135,141.215025,2160.966,120.90468,69.656961,79.928388,73.787415 12/3/2018,0.0426,1.3591,0.1972,0.25894,0.0667,0.3537,0.4025,0.0372,1672.10073,140.66685,2128.3506,116.8826,71.964345,83.027419,77.224062 12/4/2018,0.0429,1.3628,0.1988,0.25288,0.0664,0.354,0.4031,0.0365,1690.28084,138.86932,2120.5168,116.92824,72.5691,82.285864,77.13448 12/5/2018,0.0435,1.3755,0.2008,0.25822,0.0671,0.3559,0.4069,0.0367,1699.98045,138.856725,2140.278,118.361775,72.750195,83.32779,77.949585 12/6/2018,0.0434,1.3823,0.2009,0.25887,0.0679,0.3561,0.4098,0.0367,1717.576865,139.128495,2135.6535,119.43072,71.174627,81.859806,76.261491 12/7/2018,0.0441,1.3888,0.2012,0.26192,0.0685,0.3553,0.4124,0.0372,1726.69504,137.21344,2129.0304,120.20064,73.064768,83.702976,78.4672 12/10/2018,0.0436,1.391,0.2006,0.26124,0.0685,0.3546,0.413,0.0369,1732.28185,139.72595,2119.884,120.39105,70.941,81.76298,76.01815 12/11/2018,0.0436,1.388,0.2011,0.25867,0.0687,0.3559,0.4121,0.0367,1728.4764,135.5382,2084.776,120.6866,71.6902,82.64152,76.39552 12/12/2018,0.0437,1.385,0.2011,0.25898,0.069,0.3594,0.4124,0.0369,1725.36375,135.38375,2076.115,121.4645,70.84275,81.92275,75.9257 12/13/2018,0.0436,1.3838,0.2013,0.25922,0.0681,0.3557,0.4113,0.0366,1719.71745,136.71944,2043.8726,121.63602,72.760204,83.941308,78.212376 12/14/2018,0.0436,1.3934,0.202,0.2596,0.0689,0.3562,0.4158,0.0365,1721.33669,135.09013,2010.6762,123.3159,71.34208,82.656488,76.469792 12/17/2018,0.0437,1.3932,0.202,0.25948,0.0694,0.3571,0.4173,0.0364,1729.86678,131.93604,2020.14,123.43752,69.492816,80.568756,74.508336 12/18/2018,0.0434,1.3926,0.2015,0.26053,0.0694,0.3562,0.4167,0.0364,1735.59738,131.39181,2030.4108,123.10584,64.393824,76.80189,70.702302 12/19/2018,0.0437,1.4068,0.2019,0.26615,0.0699,0.3611,0.42,0.0367,1765.534,141.87578,2077.8436,124.1501,66.40096,78.415032,72.070364 12/20/2018,0.0431,1.4067,0.2039,0.26723,0.0707,0.3658,0.42,0.037,1772.090325,144.18675,2101.6098,124.563285,64.187721,75.933666,69.308109 12/21/2018,0.0432,1.4209,0.2039,0.26797,0.0713,0.3645,0.4236,0.0374,1787.705335,141.66373,2075.9349,125.0392,64.494651,74.824594,68.828396 12/24/2018,0.043,1.4187,0.2053,0.26858,0.0714,0.3635,0.4226,0.0374,1784.937405,144.99114,2106.7695,124.8456,60.053571,70.551951,64.082679 12/25/2018,0.0431,1.421,0.2061,0.26755,0.0718,0.3636,0.4234,0.0374,1787.83115,145.2262,2110.185,125.048,60.15093,70.75159,64.18657 12/26/2018,0.0431,1.415,0.2057,0.26822,0.0711,0.3602,0.4196,0.0371,1780.28225,147.0185,2101.275,123.8125,65.4013,76.65055,70.2972 12/27/2018,0.0433,1.4221,0.2075,0.26906,0.0723,0.3672,0.4212,0.0371,1803.2228,144.698675,2114.6627,124.078225,63.439881,74.859344,67.606634 12/28/2018,0.0437,1.4206,0.2064,0.26947,0.0722,0.3664,0.422,0.0377,1816.9474,143.40957,2143.6854,125.0128,64.395798,73.714934,67.847856 12/31/2018,0.0436,1.4188,0.2063,0.26815,0.0722,0.3657,0.4211,0.0377,1814.6452,144.50478,2136.7128,123.00996,64.427708,75.437596,69.294192 1/1/2019,0.0437,1.4179,0.2068,0.27053,0.0721,0.3657,0.4209,0.0378,1813.4941,144.413115,2135.3574,122.93193,64.386839,74.893478,69.250236 ================================================ FILE: Oil Money project/data/wcs crude cadaud.csv ================================================ date,wcs,gas,wti,usd,eur,cny,mxn,jpy,gbp,krw,edmonton,gold,cad 9/10/2013,89.552521,3.89106187,115.326121,1.0739,1.4248,0.1755,0.082,0.010697,1.6896,0.000989,113.822661,1464.670732,1.0376 9/12/2013,88.82271,3.85426924,117.13596,1.0786,1.43433,0.1763,0.0826,0.010835,1.7047,0.000995,113.36086,1425.617978,1.0447 9/13/2013,88.656132,3.89714876,117.050757,1.0817,1.43801,0.1768,0.083,0.010885,1.7173,0.000996,113.264807,1434.518089,1.0448 9/16/2013,83.261829,3.90704979,114.381729,1.0731,1.43092,0.1753,0.083,0.010834,1.7059,0.000992,109.016229,1408.754949,1.0394 9/17/2013,80.876096,4.02894848,112.672896,1.0688,1.42791,0.1747,0.0827,0.010783,1.6999,0.000987,105.992896,1400.76928,1.0381 9/18/2013,82.267328,3.90034528,113.516728,1.0504,1.42039,0.1717,0.083,0.010725,1.696,0.000975,107.214328,1432.504008,1.0277 9/19/2013,84.121644,3.94923516,112.730844,1.0596,1.43351,0.1731,0.0834,0.010652,1.6986,0.000987,107.432844,1447.6785,1.0321 9/20/2013,81.17575,3.9187926,111.431682,1.0646,1.43962,0.1739,0.0828,0.010714,1.7038,0.000988,107.25845,1411.49991,1.0332 9/23/2013,78.695466,3.86150657,109.942507,1.0603,1.43069,0.1733,0.0828,0.01073,1.701,0.000987,105.733116,1402.480016,1.0312 9/24/2013,77.176704,3.82284496,109.855416,1.0648,1.43474,0.174,0.0822,0.010783,1.7042,0.000991,103.796704,1409.007248,1.0338 9/25/2013,76.913375,3.754611,109.6963,1.0675,1.44399,0.1745,0.0821,0.010845,1.7168,0.000992,103.334,1424.4293,1.0351 9/26/2013,76.920837,3.71981607,110.025737,1.0679,1.4403,0.1745,0.0817,0.01079,1.7129,0.000992,103.618337,1413.985032,1.036 9/27/2013,76.333096,3.75826728,110.410371,1.0733,1.45137,0.1755,0.0817,0.010924,1.7322,0.000998,103.970571,1434.873304,1.0417 9/30/2013,75.592519,3.74914423,109.830789,1.0733,1.45168,0.1754,0.082,0.010926,1.737,0.000997,103.390989,1426.447899,1.0414 10/10/2013,76.71558,3.9559678,108.98458,1.058,1.4304,0.173,0.0808,0.010779,1.6894,0.000987,99.19808,1362.2808,1.0174 10/14/2013,77.11064,4.0092052,107.94014,1.054,1.4292,0.1724,0.0811,0.010691,1.6844,0.000983,98.19064,1341.19392,1.0179 10/15/2013,74.231358,4.02052404,106.250258,1.0498,1.41965,0.172,0.0808,0.010695,1.6794,0.000984,95.122378,1346.21103,1.0109 10/16/2013,75.066599,4.02829841,107.107859,1.0471,1.41703,0.1716,0.0815,0.010602,1.6699,0.000981,96.113309,1342.916221,1.0137 10/17/2013,73.964006,3.89475962,104.475326,1.0378,1.41928,0.1702,0.0812,0.010599,1.6776,0.000979,94.616226,1370.228096,1.0084 10/18/2013,74.717923,3.8407761,104.166973,1.0333,1.41433,0.1695,0.0804,0.010572,1.6706,0.000974,93.833973,1360.081125,1.0046 10/21/2013,73.22448,3.9183592,102.79192,1.036,1.41727,0.17,0.0798,0.010551,1.6728,0.000975,93.94448,1363.39672,1.0054 10/22/2013,70.35583,3.8124001,100.74378,1.0301,1.41961,0.1691,0.0802,0.010497,1.6724,0.000974,92.50298,1380.447311,1.0014 10/23/2013,67.64929,3.8003503,100.11804,1.039,1.43157,0.1707,0.08,0.010668,1.6796,0.000982,90.76704,1385.47533,1.0006 10/24/2013,66.244982,3.79063889,100.510703,1.0393,1.43421,0.1709,0.0801,0.010683,1.6836,0.000978,91.188182,1399.677275,0.9972 10/25/2013,67.76883,3.83543406,101.78367,1.0434,1.44016,0.1715,0.081,0.010712,1.6867,0.000982,90.46278,1409.236908,0.9985 10/28/2013,68.803942,3.78254529,103.090996,1.0447,1.4401,0.1716,0.0811,0.010696,1.6864,0.000984,91.526167,1413.092561,1 10/29/2013,67.914462,3.7564989,103.59118,1.0549,1.44999,0.1732,0.0817,0.010743,1.6928,0.000992,91.122262,1418.893245,1.0077 10/30/2013,63.976515,3.7487475,102.043965,1.0545,1.44835,0.173,0.0815,0.010703,1.6912,0.000995,89.389965,1417.827975,1.0061 10/31/2013,62.2656,3.7712565,101.92185,1.0575,1.43644,0.1735,0.0812,0.010753,1.6962,0.000997,88.17435,1399.13595,1.0137 11/11/2013,59.98559,3.8683974,101.65709,1.0685,1.43247,0.1754,0.0809,0.010776,1.7083,0.000996,85.896715,1370.682485,1.0199 11/12/2013,60.248604,3.97109687,100.027304,1.0751,1.44438,0.1765,0.0816,0.010788,1.7099,0.001002,85.513454,1363.269804,1.0243 11/13/2013,62.373192,3.931712,100.301392,1.0684,1.44103,0.1754,0.082,0.010766,1.7157,0.000998,86.038252,1369.4217,1.0219 11/14/2013,63.609684,3.778368,100.641984,1.0734,1.44483,0.1762,0.0828,0.010733,1.7244,0.001004,86.848794,1381.659012,1.0257 11/15/2013,62.805816,3.799944,100.164816,1.0674,1.44052,0.1752,0.0825,0.010655,1.7204,0.001004,86.288616,1377.138132,1.0224 11/18/2013,59.750392,3.95751704,99.207192,1.0664,1.44023,0.175,0.0827,0.010663,1.718,0.001008,84.810792,1360.129216,1.0225 11/19/2013,59.726034,3.848163,98.949734,1.0601,1.43516,0.174,0.0818,0.010588,1.7088,0.001005,84.638384,1352.390772,1.0126 11/20/2013,67.331205,3.878106,99.984429,1.0713,1.43965,0.1758,0.0818,0.010709,1.7253,0.001014,88.757205,1333.050729,1.0253 11/21/2013,69.78852,3.98544,102.98247,1.083,1.46003,0.1777,0.0831,0.010705,1.7543,0.001019,91.44852,1346.07153,1.0295 11/22/2013,70.61076,4.1070546,102.89961,1.089,1.47698,0.1788,0.084,0.010763,1.7681,0.001027,91.30176,1354.4982,1.0363 11/25/2013,68.869044,4.20014932,102.523072,1.0916,1.47544,0.1791,0.0837,0.010736,1.7634,0.00103,89.609444,1366.006408,1.0352 11/26/2013,68.678476,4.240359,102.645176,1.0957,1.48712,0.1799,0.0839,0.010819,1.7768,0.001033,89.496776,1361.790745,1.0394 11/27/2013,69.16792,4.1748567,101.65922,1.1014,1.49573,0.1808,0.0839,0.010782,1.794,0.001034,90.09452,1363.42306,1.0396 11/29/2013,69.41556,4.161969,101.80656,1.098,1.4922,0.1802,0.0838,0.010719,1.7972,0.001037,90.27756,1376.1783,1.0344 12/9/2013,73.90565,4.6228895,106.83065,1.0975,1.50782,0.1807,0.0854,0.010629,1.8032,0.001043,98.873775,1361.284125,1.0329 12/11/2013,77.850288,4.68074304,107.690688,1.1052,1.5235,0.182,0.0848,0.010791,1.8095,0.00105,101.612088,1384.064064,1.0436 12/12/2013,77.931385,4.92327189,109.09275,1.1189,1.53887,0.1843,0.0863,0.010824,1.8295,0.001063,101.540175,1371.200761,1.0517 12/13/2013,75.96555,4.85833715,107.7573,1.1155,1.53315,0.1838,0.0866,0.010806,1.8185,0.001058,100.1719,1381.758695,1.054 12/16/2013,77.650848,4.71783664,108.943648,1.1176,1.53784,0.184,0.0864,0.010849,1.8213,0.001061,101.120448,1387.299232,1.0547 12/17/2013,80.598936,4.73265894,109.255836,1.1238,1.54717,0.1851,0.0867,0.010946,1.8277,0.001067,105.603486,1383.274182,1.0595 12/18/2013,82.44821,4.811924,110.3673,1.1285,1.54429,0.1859,0.0876,0.010822,1.8497,0.001073,107.557335,1375.111105,1.0546 12/19/2013,84.912062,4.804428,111.392806,1.1278,1.5407,0.1858,0.087,0.010821,1.8463,0.001062,108.877812,1340.593304,1.0575 12/20/2013,84.896656,4.87606678,110.849752,1.1206,1.53253,0.1846,0.0863,0.010766,1.8307,0.001053,108.149106,1348.350744,1.0535 12/23/2013,84.943677,5.059236,110.430138,1.1193,1.53301,0.1844,0.0861,0.010753,1.8308,0.001055,107.329677,1341.883998,1.0553 12/24/2013,85.569506,5.00067117,110.935473,1.1209,1.53348,0.1846,0.086,0.010752,1.8349,0.001057,108.547956,1349.955915,1.0542 12/26/2013,85.855154,4.957722,111.91411,1.1242,1.53908,0.1851,0.0859,0.010726,1.8449,0.001061,109.182304,1361.001488,1.0557 12/27/2013,86.693475,4.8723785,113.1108,1.1275,1.55017,0.1858,0.0864,0.010725,1.8584,0.001069,110.370975,1367.961925,1.0531 12/30/2013,85.276983,4.96241735,111.512599,1.1231,1.55009,0.1853,0.0859,0.010685,1.8533,0.001064,108.862083,1343.867767,1.0546 12/31/2013,84.744435,4.834527,110.397714,1.1217,1.54116,0.1853,0.086,0.010653,1.8572,0.001064,107.739285,1347.879588,1.0557 1/7/2014,84.395868,5.08413972,104.929134,1.1202,1.52521,0.1851,0.0861,0.01071,1.8374,0.001047,108.480168,1380.176016,1.0406 1/8/2014,82.33008,4.88801145,103.732755,1.1235,1.52513,0.1857,0.0855,0.010712,1.8479,0.001052,105.642705,1377.399765,1.0382 1/9/2014,81.457013,4.65144378,102.998342,1.1237,1.5291,0.1856,0.0858,0.01072,1.8519,0.001057,106.066043,1379.881126,1.0364 1/10/2014,82.21761,4.39461186,103.086096,1.1118,1.5196,0.1837,0.0857,0.010673,1.8323,0.001047,105.84336,1388.0823,1.0209 1/13/2014,80.860445,4.627855,101.3931,1.1045,1.51003,0.1827,0.0844,0.010723,1.8095,0.001044,104.386295,1384.280895,1.0169 1/14/2014,82.844484,4.862708,103.265627,1.1153,1.52566,0.1846,0.0852,0.010702,1.8336,0.001053,106.210019,1388.760407,1.0188 1/15/2014,84.310672,4.98001616,105.621072,1.1216,1.52598,0.1855,0.085,0.010728,1.8362,0.001053,106.966992,1392.892608,1.0258 1/16/2014,85.549002,5.14529745,106.522452,1.1337,1.5441,0.1872,0.0854,0.010864,1.8541,0.001066,107.656152,1408.497543,1.0371 1/17/2014,86.970156,5.0033178,107.468556,1.1388,1.54215,0.1882,0.086,0.010916,1.8704,0.001073,108.892056,1428.11214,1.0386 1/21/2014,87.429844,5.2044548,107.870644,1.1356,1.54005,0.1877,0.0856,0.010888,1.8711,0.00106,109.290144,1409.745196,1.0353 1/22/2014,88.941281,5.54603621,109.332366,1.1297,1.53045,0.1867,0.0849,0.010808,1.8724,0.001058,110.688006,1397.608355,1.0188 1/23/2014,90.456528,6.44326,111.040748,1.1404,1.56194,0.1884,0.0851,0.011041,1.8974,0.001059,112.409228,1441.613852,1.0272 1/24/2014,90.684858,5.97191001,111.346356,1.1517,1.57528,0.1904,0.0856,0.011256,1.8981,0.00106,112.164063,1462.728102,1.0387 1/27/2014,89.049426,6.52251,109.532396,1.1443,1.56467,0.1892,0.0856,0.011158,1.8978,0.001056,110.390621,1438.510973,1.0295 1/28/2014,90.569841,5.92332,110.959731,1.1391,1.55737,0.1882,0.0859,0.011065,1.8887,0.001057,111.814056,1431.655053,1.0213 1/29/2014,90.525573,5.94944456,111.409048,1.1443,1.56342,0.1891,0.0854,0.011187,1.8954,0.001062,112.267273,1450.217162,1.0242 1/30/2014,90.945258,5.992517,111.697333,1.1371,1.54126,0.1877,0.0851,0.01107,1.8745,0.001052,112.550158,1414.302238,1.0191 1/31/2014,90.214479,5.744763,111.343329,1.1421,1.54048,0.1885,0.0855,0.011194,1.8778,0.001056,109.915704,1421.400555,1.0265 2/4/2014,87.55587,6.442875,108.901395,1.1205,1.51466,0.1849,0.0841,0.011024,1.8292,0.00104,109.18152,1405.835325,1.011 2/5/2014,86.282424,9.012069,109.289574,1.1223,1.5188,0.1852,0.0845,0.011063,1.8303,0.001041,107.886699,1411.763616,1.0126 2/6/2014,85.601378,8.01063254,109.209008,1.1162,1.51688,0.1841,0.0841,0.010931,1.8219,0.001038,107.925378,1404.40284,1.0082 2/7/2014,87.997929,6.686637,111.496044,1.1163,1.52203,0.1841,0.084,0.010906,1.8318,0.001039,110.714634,1414.653501,1.012 2/10/2014,88.070175,8.5258545,111.81705,1.1175,1.52481,0.1844,0.0839,0.010928,1.8329,0.00104,110.978925,1424.56665,1.0105 2/12/2014,84.610323,6.680637,111.199923,1.1079,1.50591,0.1827,0.0831,0.010805,1.8385,0.001043,109.261098,1430.465085,1.0069 2/13/2014,84.474145,5.924884,111.759795,1.1137,1.5236,0.1837,0.084,0.010901,1.8553,0.001046,109.309655,1451.062004,1.0144 2/14/2014,83.90302,6.099019,111.02207,1.1069,1.51562,0.1825,0.0836,0.010873,1.8538,0.001042,108.58689,1459.624754,1.0079 2/18/2014,86.330854,6.325538,113.471954,1.1078,1.52416,0.1826,0.0837,0.010823,1.8481,0.00104,111.034794,1464.533756,1.0118 2/19/2014,86.732466,6.711044,114.787741,1.1111,1.52593,0.1828,0.0833,0.010859,1.8533,0.00104,112.565541,1457.31876,1.0028 2/20/2014,87.077568,6.60688,114.282368,1.1104,1.52322,0.1825,0.0836,0.010857,1.8488,0.001036,111.783968,1469.025888,1.0002 2/21/2014,87.3933,6.91794,114.185,1.114,1.53073,0.1829,0.084,0.010872,1.8509,0.001038,111.3443,1475.2145,1.0029 2/24/2014,88.060119,6.8881008,114.178239,1.1067,1.51968,0.1815,0.0834,0.010797,1.8429,0.00103,111.854169,1479.624699,1.0006 2/25/2014,86.575104,5.78982096,113.241744,1.1088,1.524,0.1811,0.0838,0.010845,1.8495,0.001033,110.691504,1486.3464,1.0002 2/26/2014,87.62785,5.395262,114.38785,1.115,1.52605,0.1821,0.0836,0.010892,1.8587,0.001042,111.60035,1483.6636,1.0019 2/27/2014,86.61081,5.09046252,114.21696,1.1154,1.52925,0.182,0.0841,0.010922,1.8614,0.001046,110.87076,1484.920866,1.0029 2/28/2014,86.65947,5.26220415,114.952095,1.1205,1.54619,0.1823,0.0846,0.011008,1.8761,0.00105,112.150845,1486.219995,1.0126 3/3/2014,89.134796,7.67317792,117.384496,1.1188,1.53668,0.1821,0.0839,0.01103,1.8647,0.001043,114.587496,1511.062468,1.0103 3/4/2014,89.194059,8.85426731,115.450609,1.1173,1.53552,0.1819,0.0841,0.010931,1.8619,0.001043,112.098709,1491.003331,1.0072 3/6/2014,86.533866,5.39456037,111.726156,1.1001,1.52483,0.1798,0.0836,0.010674,1.8415,0.001033,107.875806,1486.037082,1.0012 3/7/2014,89.029044,5.260356,113.125224,1.1028,1.53013,0.18,0.0836,0.01068,1.8432,0.001035,109.816824,1477.729944,0.9947 3/10/2014,87.831214,5.12940055,112.111744,1.1087,1.53844,0.1806,0.0839,0.010733,1.8454,0.001039,109.062819,1485.347564,0.9979 3/11/2014,86.92542,5.1846674,111.43342,1.114,1.544,0.1814,0.0839,0.010813,1.8511,0.001041,108.92692,1502.79714,1.003 3/12/2014,83.712024,5.18449348,109.023674,1.1126,1.54692,0.181,0.084,0.010828,1.849,0.001039,106.520324,1520.746184,1.0006 3/13/2014,84.653085,4.87212,108.73686,1.1073,1.53554,0.1804,0.0833,0.010873,1.8408,0.001034,106.3008,1517.311044,1 3/14/2014,85.052604,4.862364,109.530564,1.1076,1.54134,0.1801,0.0839,0.010925,1.8441,0.001033,107.315364,1531.722192,0.9973 3/17/2014,84.543732,5.0502858,107.927232,1.1004,1.53211,0.1781,0.0836,0.010815,1.8309,0.001031,106.826832,1504.323828,0.9956 3/18/2014,86.505515,4.86731854,109.24129,1.0957,1.52672,0.1769,0.0833,0.010802,1.818,0.001024,109.515215,1485.528146,0.9839 3/19/2014,88.051758,4.91340311,110.999183,1.1059,1.52983,0.1785,0.0832,0.01081,1.8294,0.001029,110.722708,1470.393581,0.9842 3/20/2014,88.94652,4.86772,109.999409,1.1063,1.52433,0.1776,0.0834,0.010803,1.8259,0.001024,111.62567,1468.911951,0.9838 3/21/2014,87.702615,4.745741,110.065956,1.1011,1.51892,0.1769,0.0832,0.010769,1.8154,0.001019,110.825715,1469.627159,0.9808 3/24/2014,87.41385,4.8316875,109.6095,1.095,1.51541,0.1768,0.0831,0.01071,1.8066,0.001016,110.40885,1433.0922,0.9784 3/25/2014,86.76723,4.907318,108.59814,1.091,1.50847,0.1759,0.0832,0.010669,1.8034,0.001012,109.67823,1430.48647,0.9769 3/26/2014,88.099392,4.7940897,108.671814,1.0839,1.49371,0.1746,0.0826,0.010622,1.7974,0.001007,110.048367,1413.925872,0.9763 3/27/2014,88.5924,4.736448,109.3824,1.08,1.48398,0.1738,0.0826,0.010571,1.794,0.001011,111.0024,1394.6148,0.9791 3/28/2014,89.096546,4.84748364,109.945938,1.0814,1.48706,0.174,0.0827,0.010515,1.7992,0.001011,111.265246,1400.661722,0.9774 3/31/2014,88.046658,4.82308302,109.645452,1.0794,1.48624,0.1736,0.0827,0.010457,1.7985,0.001014,111.793458,1385.960394,0.9768 4/2/2014,87.444731,4.692842,107.719106,1.0813,1.48867,0.1742,0.0826,0.010409,1.7978,0.001022,111.773981,1394.76887,0.98 4/3/2014,87.999168,4.85587728,108.634128,1.0832,1.48617,0.1744,0.0826,0.010421,1.7978,0.001023,113.237728,1393.75344,0.9814 4/4/2014,88.237638,4.82040742,108.846868,1.0762,1.47497,0.1732,0.0828,0.010418,1.7837,0.001023,113.689768,1402.8267,0.98 4/7/2014,87.687523,4.91229193,108.344628,1.0787,1.48233,0.1736,0.0829,0.010463,1.7916,0.001023,113.198778,1399.375936,0.9829 4/8/2014,89.747883,4.86706797,109.564848,1.0683,1.47394,0.1724,0.0819,0.010493,1.7889,0.001018,114.158538,1398.041478,0.978 4/9/2014,90.356765,4.96158208,110.32364,1.0649,1.47545,0.1718,0.082,0.010441,1.7883,0.001029,114.58324,1396.93582,0.9788 4/11/2014,90.286728,4.94895568,110.400108,1.0642,1.47765,0.1714,0.0816,0.010476,1.7807,0.001024,115.189008,1403.062564,0.9693 4/14/2014,89.87517,4.91119524,110.407455,1.0611,1.46652,0.1706,0.0815,0.010418,1.7752,0.001019,115.182405,1409.130189,0.9679 4/15/2014,90.42313,4.98667806,110.82575,1.0682,1.47567,0.1717,0.0815,0.010481,1.787,0.001025,114.56445,1391.480048,0.9729 4/16/2014,90.073911,4.93523079,110.722296,1.0671,1.47431,0.1715,0.0817,0.010438,1.7925,0.001028,114.030306,1389.929763,0.969 4/17/2014,91.240128,4.89343788,111.79917,1.0719,1.48071,0.1723,0.0821,0.010468,1.8002,0.001032,114.285978,1388.239128,0.9737 4/21/2014,91.02129,5.10941418,111.895077,1.0721,1.47866,0.1721,0.0823,0.01045,1.8001,0.001031,114.339465,1382.762417,0.9738 4/22/2014,88.8777,5.05636712,109.033988,1.0676,1.47382,0.1712,0.0818,0.010404,1.7961,0.001027,111.8311,1370.595556,0.9681 4/23/2014,88.730172,5.155477,109.502762,1.0763,1.48709,0.1725,0.0824,0.010498,1.8062,0.001035,112.247327,1381.872333,0.9755 4/24/2014,89.795286,5.18112,110.357856,1.0794,1.49295,0.1727,0.0824,0.010552,1.8137,0.00104,112.462686,1396.052784,0.9793 4/25/2014,88.53664,5.0700976,108.81056,1.0784,1.49066,0.1725,0.0821,0.010549,1.8107,0.001035,110.91344,1405.4248,0.9767 4/28/2014,88.827424,5.16320203,108.917284,1.0801,1.49618,0.1728,0.0823,0.010539,1.8155,0.001044,111.347509,1400.608874,0.9793 4/29/2014,89.04987,5.2043407,109.28112,1.079,1.49036,0.1725,0.0824,0.010512,1.8155,0.001047,113.86687,1398.29768,0.9859 4/30/2014,87.210032,5.157872,107.400032,1.0768,1.49337,0.1721,0.0823,0.01053,1.8167,0.001042,111.976432,1390.79488,0.9822 5/2/2014,88.954031,5.088632,107.551256,1.0781,1.4952,0.1722,0.0828,0.010545,1.8188,0.001047,110.246506,1401.20657,0.9824 5/5/2014,88.992099,5.078793,107.269284,1.0783,1.49614,0.1727,0.0826,0.010558,1.8186,0.001049,109.965034,1412.874924,0.9841 5/6/2014,87.42345,5.1165443,106.4053,1.0694,1.48977,0.1717,0.0821,0.010516,1.8157,0.001042,107.04694,1398.82867,0.9819 5/8/2014,86.040022,5.05669135,106.947342,1.0667,1.47629,0.1713,0.0824,0.010492,1.8062,0.001043,107.320687,1375.434981,0.9847 5/9/2014,85.445318,4.88583998,106.809318,1.0682,1.46962,0.1715,0.0825,0.010489,1.7997,0.001041,107.076368,1376.813662,0.9801 5/12/2014,86.078179,4.80645,107.440179,1.0681,1.4696,0.1713,0.0825,0.01046,1.8019,0.001042,107.707204,1384.04398,0.9803 5/13/2014,88.36495,4.76551,108.66645,1.0685,1.46399,0.1715,0.0828,0.01045,1.7976,0.001045,108.933575,1382.243655,0.9797 5/14/2014,89.262264,4.70044932,109.146894,1.0662,1.4623,0.1712,0.0827,0.010464,1.7878,0.001037,110.213094,1392.425214,0.9792 5/15/2014,88.55008,4.65173824,108.4832,1.0688,1.46524,0.1716,0.0825,0.010522,1.7945,0.001039,109.552,1385.399936,0.9819 5/16/2014,88.320144,4.72713498,108.926754,1.0677,1.46317,0.1714,0.0828,0.010522,1.7959,0.001043,110.101224,1381.091304,0.9838 5/19/2014,89.299989,4.83737751,109.987659,1.0719,1.4694,0.1718,0.0831,0.01056,1.8022,0.001049,111.166749,1385.934543,0.9856 5/20/2014,90.966152,4.901007,110.829836,1.0819,1.48243,0.1734,0.0838,0.010677,1.8218,0.001056,112.874627,1400.378903,0.9919 5/21/2014,91.770728,4.928448,112.965216,1.0808,1.47944,0.1734,0.0836,0.010663,1.8268,0.001053,112.576128,1396.436832,0.9904 5/22/2014,93.204561,4.866711,112.855668,1.0839,1.48021,0.1738,0.0842,0.010655,1.8286,0.001058,112.985736,1402.67499,0.9952 5/23/2014,93.542955,4.744854,113.692335,1.0833,1.47649,0.1737,0.0843,0.010624,1.8236,0.001057,113.31318,1400.284413,0.9968 5/27/2014,92.9988,4.786992,112.4388,1.08,1.47252,0.1729,0.084,0.010591,1.8155,0.001054,112.7088,1366.146,0.9946 5/28/2014,91.726344,4.92162939,111.214944,1.0827,1.47152,0.1731,0.0841,0.01063,1.8093,0.001058,110.944269,1362.188178,0.9953 5/29/2014,91.687085,4.96419,111.29671,1.0745,1.46141,0.1722,0.0837,0.010557,1.7961,0.001055,111.18926,1349.09922,0.9913 5/30/2014,89.912911,4.811968,110.320811,1.0741,1.46438,0.1719,0.0835,0.010555,1.7998,0.001052,109.515236,1342.281288,0.9901 6/2/2014,89.46168,4.88838,110.821305,1.0815,1.47048,0.1731,0.0837,0.010564,1.8111,0.001055,109.46943,1345.310295,0.9922 6/3/2014,89.268903,4.953987,110.800938,1.0793,1.4708,0.1726,0.0834,0.010528,1.8077,0.001055,108.750268,1343.674535,0.9895 6/5/2014,89.052508,4.967584,109.715088,1.0706,1.46251,0.1712,0.0832,0.010454,1.8008,0.00105,108.002128,1342.136278,0.9798 6/6/2014,89.472614,4.98201,109.989924,1.0714,1.46176,0.1714,0.0829,0.010454,1.8003,0.00105,108.061404,1342.710622,0.9802 6/10/2014,90.846535,4.875733,111.331015,1.0669,1.44534,0.1714,0.0819,0.010423,1.7877,0.001049,108.663765,1344.18731,0.9785 6/11/2014,90.90421,4.79565,111.25908,1.0657,1.44225,0.1711,0.0819,0.010441,1.7893,0.001047,108.59483,1343.922299,0.9807 6/13/2014,92.171576,4.977648,113.709476,1.0636,1.44007,0.1712,0.0817,0.010423,1.8047,0.001042,109.986876,1358.174656,0.9798 6/16/2014,91.637755,5.010027,113.70953,1.0637,1.44387,0.1709,0.0815,0.010446,1.8066,0.001042,108.39103,1353.0264,0.9809 6/17/2014,91.68831,4.99086,113.91156,1.071,1.4509,0.172,0.0817,0.010484,1.8169,0.001048,109.62756,1360.79118,0.986 6/18/2014,90.571816,5.005788,112.624916,1.0628,1.44507,0.1706,0.0819,0.010428,1.8063,0.001044,108.373716,1357.950188,0.9809 6/19/2014,91.53999,4.94667,113.220234,1.0638,1.44788,0.1708,0.0817,0.010435,1.813,0.001044,110.68839,1404.630882,0.9835 6/20/2014,92.499999,4.815156,114.264078,1.0653,1.4486,0.1711,0.082,0.010436,1.8121,0.001045,111.675399,1400.677746,0.9902 6/23/2014,91.20408,4.75552,113.38943,1.0615,1.44395,0.1705,0.0815,0.010412,1.8072,0.001042,110.73568,1398.54748,0.989 6/24/2014,91.303275,4.79745175,113.827525,1.0675,1.45242,0.1713,0.0817,0.010469,1.8132,0.001048,111.052025,1407.274575,0.9936 6/25/2014,91.15225,4.8545084,114.00675,1.063,1.44867,0.1705,0.0817,0.010435,1.8053,0.001043,111.34925,1402.28834,0.9916 6/26/2014,90.382598,4.83502818,112.423248,1.0622,1.44577,0.1706,0.0816,0.010442,1.8085,0.001045,110.829948,1398.471276,0.9937 6/27/2014,90.17439,4.65779,112.19014,1.061,1.44742,0.1706,0.0819,0.01046,1.8066,0.001046,110.33339,1396.45637,0.9946 6/30/2014,89.440637,4.675041,111.702737,1.0601,1.45156,0.1709,0.0817,0.010462,1.8134,0.001048,109.847562,1407.102533,0.9935 7/1/2014,88.44147,4.69638,110.92302,1.053,1.44034,0.1698,0.0814,0.010371,1.8058,0.001041,109.08027,1396.76238,0.9904 7/2/2014,89.455872,4.65916,110.633872,1.0589,1.44646,0.1705,0.0815,0.010405,1.8177,0.001049,109.045522,1405.012054,0.9929 7/3/2014,89.507834,4.59275973,111.333794,1.0699,1.4561,0.1722,0.0826,0.010469,1.8353,0.00106,109.193994,1411.765147,1.006 7/7/2014,87.784532,4.5385926,110.456157,1.0669,1.45158,0.172,0.0819,0.010473,1.8275,0.001055,107.522182,1408.243986,0.9986 7/8/2014,87.13341,4.436463,110.00726,1.0639,1.44821,0.1715,0.082,0.010475,1.8226,0.001051,107.081535,1403.539436,0.9964 7/10/2014,84.971052,4.385328,109.558692,1.0644,1.44853,0.1716,0.0819,0.010503,1.8236,0.00105,106.471932,1421.7723,0.9995 7/11/2014,82.873384,4.34885616,107.363784,1.0648,1.44886,0.1717,0.0819,0.010503,1.8221,0.001043,104.169384,1425.44776,0.992 7/14/2014,83.475286,4.3696507,107.428786,1.0646,1.44984,0.1715,0.0822,0.010485,1.8187,0.001044,103.968836,1391.59189,0.9938 7/15/2014,82.131712,4.386192,106.677312,1.0672,1.44793,0.1719,0.0824,0.010495,1.8295,0.001039,102.621952,1381.01016,0.9919 7/16/2014,83.20383,4.37708718,108.02088,1.0674,1.44374,0.172,0.0827,0.010498,1.8293,0.001036,103.5378,1386.776754,0.9936 7/17/2014,84.151086,4.298988,110.351386,1.0694,1.44643,0.1724,0.0823,0.01057,1.8286,0.001035,105.218266,1410.75248,0.9936 7/18/2014,83.693772,4.15903656,109.771572,1.0644,1.44016,0.1715,0.0822,0.010503,1.8198,0.001034,104.662452,1395.300672,0.9921 7/21/2014,85.415985,4.10015925,111.545235,1.0665,1.44276,0.1718,0.0822,0.010521,1.8217,0.001038,106.426035,1399.770585,0.9935 7/22/2014,83.71228,4.04052265,111.15509,1.0645,1.43346,0.1716,0.0822,0.010492,1.8166,0.001039,105.268405,1390.68409,0.9912 7/23/2014,83.933775,3.99735,113.80815,1.0575,1.42378,0.1706,0.0818,0.01042,1.8024,0.001033,105.8769,1379.603925,0.9857 7/24/2014,82.356069,4.03244277,111.818244,1.0617,1.42941,0.1714,0.0819,0.010428,1.8034,0.001031,104.651769,1373.478822,0.9881 7/25/2014,83.111187,4.02848193,113.177662,1.0643,1.42933,0.1719,0.0822,0.01045,1.8067,0.001037,104.397187,1391.274246,0.9843 7/28/2014,83.368302,4.071673,108.085377,1.0631,1.42886,0.1718,0.0817,0.010436,1.8056,0.001036,103.832977,1386.335555,0.9844 7/29/2014,83.092629,3.99829326,107.603729,1.0657,1.42897,0.1724,0.0816,0.010435,1.8057,0.001038,102.808079,1384.461527,0.982 7/30/2014,84.157736,4.008532,107.469386,1.0718,1.43575,0.1737,0.0815,0.010426,1.8126,0.001042,103.450136,1389.37434,0.983 7/31/2014,82.266426,4.03425,105.611286,1.0758,1.44056,0.1743,0.0814,0.010466,1.8165,0.001042,101.577036,1379.810322,0.9865 8/1/2014,81.802084,4.016012,105.103544,1.0738,1.4418,0.1738,0.0815,0.010465,1.8062,0.001041,101.076794,1389.22875,0.9837 8/4/2014,82.808506,4.060606,105.307906,1.0714,1.43798,0.1734,0.0812,0.010443,1.8066,0.001037,101.558006,1380.23105,0.9824 8/5/2014,83.160286,4.148342,104.654286,1.0747,1.43758,0.1742,0.0808,0.010476,1.8148,0.001038,102.504886,1385.051866,0.9805 8/7/2014,84.227874,4.292828,104.990924,1.0786,1.44144,0.1751,0.0812,0.010565,1.8156,0.00104,103.103374,1415.802718,0.9873 8/8/2014,85.380459,4.214589,105.159924,1.0779,1.44565,0.1751,0.0814,0.010566,1.8083,0.001045,102.896334,1411.596282,0.9823 8/12/2014,85.632293,4.229288,105.052493,1.0789,1.44235,0.1752,0.0821,0.01055,1.8138,0.00105,102.193408,1412.830339,0.9876 8/13/2014,85.535373,4.137595,104.879973,1.0747,1.43635,0.1746,0.0818,0.010494,1.7936,0.001043,99.882618,1410.995124,0.9846 8/14/2014,82.821858,4.109973,102.566898,1.0731,1.43413,0.1744,0.0821,0.010474,1.7906,0.001052,98.006223,1409.538312,0.9842 8/15/2014,84.689665,4.022625,104.427345,1.0727,1.43767,0.1745,0.0821,0.01048,1.7911,0.001054,100.136545,1399.55169,0.9842 8/18/2014,84.354984,4.03093712,103.390084,1.0724,1.43317,0.1746,0.0822,0.010455,1.794,0.001054,98.832384,1392.40416,0.9851 8/19/2014,80.198289,4.13019576,101.556552,1.0749,1.43187,0.175,0.0824,0.010444,1.7862,0.001054,96.321789,1392.780177,0.9824 8/20/2014,81.22947,4.1411419,103.428962,1.0766,1.4277,0.1753,0.082,0.010377,1.7869,0.001052,97.10932,1390.902604,0.9813 8/21/2014,82.1945,4.15939,103.53325,1.075,1.42762,0.1747,0.082,0.010352,1.7824,0.00105,98.05075,1372.5385,0.9824 8/22/2014,81.73941,4.14235794,103.10007,1.0734,1.42131,0.1745,0.0817,0.01033,1.7787,0.001054,97.57206,1375.13274,0.9808 8/25/2014,82.12206,4.227108,102.28956,1.0756,1.41884,0.1748,0.0818,0.010337,1.7831,0.001054,99.33166,1373.369104,0.9792 8/26/2014,82.90842,4.2369684,100.85257,1.0745,1.41487,0.1746,0.082,0.010326,1.7773,0.001057,99.77807,1376.6494,0.9811 8/27/2014,82.87398,4.2721119,100.54548,1.071,1.41299,0.1743,0.0819,0.010311,1.7753,0.001056,99.47448,1373.69673,0.9858 8/28/2014,83.15264,4.29839296,101.05504,1.0688,1.40893,0.174,0.0817,0.010304,1.7728,0.001052,100.30688,1378.37792,0.984 8/29/2014,84.810147,4.31138769,102.744372,1.0707,1.40622,0.1743,0.0818,0.010287,1.7773,0.001055,101.994882,1378.333524,0.9843 9/4/2014,86.04932,4.160744,101.02372,1.0696,1.38456,0.1742,0.0813,0.010161,1.7468,0.001047,100.75632,1349.482232,0.9833 9/5/2014,84.677374,4.095744,99.503114,1.0666,1.38095,0.1737,0.0818,0.010149,1.7409,0.001041,99.023144,1353.312746,0.9799 9/9/2014,85.8414,4.2801174,100.78215,1.0866,1.40577,0.1771,0.0823,0.010231,1.7501,0.00105,100.34751,1364.193702,0.9893 9/10/2014,85.392908,4.33092904,100.140308,1.0924,1.41071,0.1782,0.0828,0.010221,1.7703,0.001058,99.266388,1365.248748,0.9986 9/12/2014,86.99303,4.215765,102.096755,1.1065,1.43441,0.1804,0.0835,0.010309,1.7999,0.001069,100.71363,1360.607725,0.9976 9/15/2014,88.020972,4.3290546,102.918192,1.1076,1.43333,0.1804,0.0837,0.010334,1.7981,0.001067,101.921352,1365.914472,1.0021 9/16/2014,90.098421,4.233845,104.339536,1.0997,1.42504,0.1789,0.0836,0.010265,1.7898,0.001065,103.514761,1358.734335,1.0022 9/17/2014,89.732636,4.42615544,105.353836,1.1158,1.43603,0.1817,0.0842,0.010295,1.8167,0.001071,104.516986,1365.192458,1.0145 9/18/2014,87.679368,4.41044352,103.531068,1.1124,1.43737,0.1811,0.084,0.010233,1.8237,0.001065,102.418668,1362.85686,1.0169 9/19/2014,87.850564,4.32407176,103.536164,1.1204,1.43721,0.1824,0.0848,0.010273,1.8245,0.001073,102.415764,1362.07028,1.0222 9/22/2014,85.50549,4.3591233,103.14304,1.127,1.44816,0.1835,0.0849,0.010355,1.844,0.001083,100.71999,1369.39516,1.0205 9/23/2014,85.869392,4.40670272,104.703872,1.1312,1.45321,0.1843,0.0849,0.010387,1.8539,0.001087,101.706192,1383.932704,1.021 9/24/2014,87.409818,4.321536,105.7876,1.1254,1.43847,0.1835,0.0848,0.010321,1.839,0.001082,102.771528,1369.713086,1.0175 9/25/2014,88.91194,4.4132778,107.34754,1.138,1.45101,0.1854,0.085,0.010463,1.8568,0.00109,104.44564,1390.15804,1.0242 9/26/2014,90.290826,4.460919,106.719786,1.1409,1.44712,0.1862,0.0849,0.010438,1.8538,0.001087,105.864111,1390.049742,1.0227 9/29/2014,92.12704,4.61094,108.47179,1.147,1.45505,0.1865,0.085,0.010474,1.8629,0.001086,107.61154,1394.53407,1.0274 9/30/2014,87.915821,4.73071935,104.204996,1.1431,1.44417,0.1863,0.0851,0.010426,1.8537,0.00108,103.347671,1381.036265,1.0211 10/1/2014,88.717579,4.737402,103.822339,1.1443,1.44465,0.1865,0.085,0.010507,1.8524,0.001077,103.421834,1388.974226,1.0251 10/2/2014,88.384379,4.5436,103.378259,1.1359,1.43913,0.1851,0.0849,0.010474,1.834,0.001072,103.435054,1379.630063,1.0179 10/3/2014,88.408232,4.530504,103.452272,1.1528,1.44259,0.1878,0.0855,0.010502,1.8411,0.00108,103.798112,1373.468976,1.0248 10/6/2014,88.252674,4.427468,103.086974,1.1411,1.44411,0.1859,0.0852,0.01049,1.8353,0.001072,103.657524,1377.65003,1.025 10/7/2014,86.30501,4.38919382,100.764785,1.1341,1.4368,0.1847,0.0842,0.010499,1.8255,0.001063,100.764785,1371.138241,1.015 10/9/2014,83.197502,4.406382,97.657722,1.1386,1.44501,0.1857,0.0847,0.010559,1.8352,0.001065,97.088422,1394.022138,1.0178 10/10/2014,84.183056,4.4394128,98.804566,1.1513,1.45394,0.1878,0.0854,0.010698,1.8509,0.001073,98.401611,1408.224108,1.0282 10/13/2014,83.2656,4.414422,97.7436,1.14,1.45374,0.1861,0.0848,0.01067,1.8337,0.001069,97.3446,1408.8918,1.018 10/14/2014,79.524133,4.48280143,93.927768,1.1477,1.45272,0.1874,0.0854,0.010721,1.8252,0.001077,93.124378,1414.918991,1.0158 10/15/2014,78.133646,4.33121826,92.632206,1.1327,1.45402,0.1849,0.0837,0.010694,1.8145,0.001068,91.329601,1406.836054,1.0065 10/16/2014,79.49016,4.33232793,94.45167,1.1421,1.46277,0.1865,0.0842,0.01074,1.8372,0.001076,92.452995,1414.844901,1.0144 10/17/2014,78.96748,4.25110172,94.5667,1.1428,1.45926,0.1867,0.0846,0.010698,1.8405,0.001075,91.88112,1415.152096,1.0139 10/20/2014,78.617904,4.15516,94.157064,1.1384,1.45734,0.1859,0.0841,0.010646,1.8403,0.001078,91.481824,1419.482344,1.0087 10/21/2014,78.353947,4.122094,94.295747,1.1387,1.44846,0.186,0.0841,0.010642,1.8353,0.001079,91.619802,1421.89469,1.0147 10/22/2014,74.077286,4.192624,92.761806,1.1393,1.44085,0.1862,0.084,0.010632,1.8283,0.001081,90.027486,1414.178911,1.014 10/23/2014,75.992508,4.10501052,93.966408,1.1412,1.44338,0.1865,0.0842,0.010541,1.8296,0.001077,91.969308,1405.775808,1.0161 10/24/2014,75.020365,4.0145726,92.35199,1.1365,1.44152,0.1858,0.0838,0.010503,1.8305,0.001075,89.794865,1399.042865,1.011 10/27/2014,75.266625,4.02713367,92.0241,1.1361,1.44265,0.1857,0.0839,0.010537,1.8314,0.00108,90.31995,1393.562982,1.0101 10/28/2014,75.559372,3.97059306,91.931322,1.1291,1.438,0.1847,0.084,0.010439,1.8215,0.001078,91.366772,1387.121932,1.0111 10/29/2014,77.53658,4.04952411,93.45318,1.1369,1.43587,0.186,0.0842,0.010438,1.8201,0.001079,90.61093,1378.093335,1.0164 10/30/2014,75.293988,4.23489066,91.819728,1.1319,1.42769,0.1851,0.0842,0.010366,1.8112,0.001074,89.272953,1356.978315,1.0116 10/31/2014,74.208614,4.29668898,91.541764,1.1366,1.42364,0.186,0.0843,0.01012,1.8182,0.001059,87.847814,1333.163604,1.0088 11/3/2014,72.994746,4.27269183,90.730926,1.1517,1.43783,0.1882,0.0846,0.010101,1.8398,0.001063,85.836201,1342.456071,1.0141 11/4/2014,69.951059,4.188138,88.328517,1.1443,1.43576,0.1871,0.0844,0.010073,1.8314,0.001061,82.721447,1336.988677,1.003 11/6/2014,71.102738,4.57097375,91.022253,1.1683,1.44584,0.1911,0.0857,0.010141,1.8496,0.00107,84.012453,1334.105136,1.0227 11/7/2014,71.217,4.644159,91.0767,1.158,1.44196,0.1892,0.0855,0.010103,1.8375,0.001065,83.8392,1364.08926,1.0223 11/11/2014,72.36026,4.6785445,89.74791,1.1515,1.43622,0.188,0.0846,0.009944,1.8327,0.001052,83.99041,1340.725995,1.0156 11/12/2014,70.86166,4.8218733,88.52546,1.147,1.42661,0.1872,0.0846,0.009935,1.8098,0.001047,82.10226,1333.5022,1.0133 11/13/2014,67.346241,4.794878,85.126291,1.1471,1.43049,0.1872,0.0843,0.009907,1.8013,0.001045,78.817241,1333.561105,1.0087 11/14/2014,68.77431,4.62915,86.66226,1.143,1.43138,0.1865,0.0845,0.009827,1.7903,0.001039,80.60436,1358.74125,1.0122 11/17/2014,68.880518,4.84528918,86.849848,1.1482,1.4296,0.1874,0.0845,0.009843,1.7961,0.001043,80.764388,1362.419674,1.0153 11/18/2014,67.552097,4.94927187,85.555287,1.1467,1.4377,0.1873,0.0846,0.009814,1.7928,0.001042,81.312497,1372.691636,1.0151 11/19/2014,68.544616,5.09467024,86.527716,1.1602,1.45666,0.1895,0.0852,0.009835,1.8196,0.001041,82.234976,1372.145336,1.0231 11/20/2014,68.520984,5.1158778,87.657684,1.1598,1.4548,0.1893,0.085,0.009813,1.8207,0.001043,83.366424,1384.557642,1.0259 11/21/2014,69.233537,4.972447,88.154217,1.1537,1.42903,0.1883,0.0847,0.00979,1.8056,0.001038,84.000897,1386.228235,1.0267 11/24/2014,67.912359,4.70780122,87.927534,1.1603,1.44377,0.1889,0.085,0.00981,1.8225,0.001042,82.416109,1389.041542,1.0283 11/25/2014,66.053016,4.83661896,86.921736,1.1724,1.46232,0.1911,0.0857,0.009937,1.8415,0.001056,82.173516,1408.028952,1.0414 11/26/2014,65.42183,4.9579783,86.180455,1.1695,1.46301,0.1905,0.0852,0.009934,1.8474,0.001059,81.502455,1400.908965,1.0398 11/28/2014,56.8942,4.995875,77.759325,1.1755,1.46388,0.1913,0.0844,0.009914,1.8392,0.001056,73.057325,1372.25519,1.0298 12/2/2014,59.541576,4.43411848,79.199296,1.1842,1.4663,0.1926,0.084,0.009933,1.8516,0.001061,75.646696,1419.003176,1.0381 12/3/2014,60.948331,4.32134731,80.161986,1.1897,1.46468,0.1934,0.0844,0.009932,1.8661,0.001066,77.782586,1438.858871,1.0465 12/5/2014,59.147088,4.11603192,79.087008,1.2012,1.47671,0.1954,0.0837,0.009886,1.8733,0.00107,75.483408,1432.25082,1.0505 12/8/2014,55.34163,4.21524777,76.019385,1.2057,1.48513,0.1954,0.0838,0.00999,1.8874,0.001084,71.799435,1451.072007,1.0504 12/9/2014,55.370336,4.34473856,76.954156,1.2058,1.49213,0.1949,0.0836,0.010073,1.8892,0.001091,72.372116,1484.412148,1.0534 12/11/2014,51.61149,4.44245598,72.461565,1.2087,1.50082,0.1952,0.0818,0.010183,1.9025,0.001096,68.53329,1483.945164,1.0487 12/12/2014,48.883937,4.33964695,70.106187,1.2127,1.51117,0.1959,0.0821,0.010211,1.9058,0.001099,66.225547,1482.634893,1.0472 12/15/2014,47.247294,4.45251876,68.064834,1.2174,1.5144,0.1966,0.0825,0.010336,1.9042,0.001109,64.412634,1452.638202,1.0435 12/16/2014,48.676166,4.3323126,68.044438,1.2166,1.52229,0.1965,0.0825,0.010452,1.9164,0.001125,64.491966,1456.282366,1.0463 12/17/2014,50.073114,4.49796606,69.491982,1.2306,1.51946,0.1987,0.0845,0.010377,1.9174,0.001122,65.886324,1464.057126,1.0585 12/18/2014,46.780503,4.49820063,66.246873,1.2243,1.50475,0.197,0.084,0.010307,1.9191,0.001113,62.573973,1467.409251,1.058 12/19/2014,50.495301,4.21948213,69.389604,1.2277,1.50481,0.1973,0.0841,0.010273,1.9225,0.001116,66.455401,1468.009998,1.0582 12/22/2014,48.274096,3.73208192,67.578816,1.2296,1.50338,0.1975,0.0838,0.010244,1.9166,0.001118,64.258896,1446.550624,1.057 12/23/2014,50.729744,3.66581618,70.19753,1.2337,1.50183,0.1982,0.0836,0.010224,1.9151,0.001115,66.767844,1451.534409,1.062 12/24/2014,49.114752,3.39611744,68.592992,1.2328,1.50396,0.1983,0.0838,0.010234,1.9187,0.001117,65.141152,1447.06064,1.0606 12/26/2014,47.692122,3.3709575,67.394522,1.2314,1.49999,0.1982,0.0837,0.01023,1.9158,0.001113,63.700322,1472.7544,1.059 12/29/2014,45.984372,3.69767944,65.897412,1.2292,1.49437,0.1975,0.0833,0.010195,1.9082,0.001117,62.209812,1454.500068,1.0565 12/30/2014,46.575016,3.80871714,66.123816,1.2218,1.48555,0.197,0.0829,0.010231,1.9014,0.001114,62.458416,1466.83199,1.0521 12/31/2014,45.614753,3.66545811,65.197153,1.2239,1.47995,0.1973,0.083,0.010229,1.9063,0.001119,61.525453,1449.550443,1.053 1/5/2015,42.784371,3.96723306,61.894476,1.2369,1.47622,0.1989,0.0828,0.010341,1.8866,0.001115,57.874551,1490.291334,1.052 1/6/2015,41.098864,3.66389632,59.279824,1.2368,1.47076,0.1991,0.083,0.010449,1.8743,0.001125,55.198384,1507.139744,1.0451 1/7/2015,42.0301,3.7960794,60.2287,1.238,1.46555,0.1993,0.0841,0.010379,1.8704,0.001127,56.1433,1499.72558,1.0476 1/9/2015,42.003294,3.59709579,58.946004,1.2189,1.44345,0.1963,0.0835,0.010284,1.8481,0.001123,55.106469,1491.019425,1.0276 1/12/2015,39.44042,3.5506186,56.48182,1.226,1.45072,0.1976,0.0837,0.01036,1.86,0.001132,52.61992,1512.03806,1.0238 1/13/2015,40.763605,3.53941725,56.192305,1.2245,1.44172,0.1975,0.0838,0.010385,1.8565,0.001135,51.84533,1506.91868,1.024 1/14/2015,43.176414,3.84451725,59.499504,1.2273,1.44657,0.198,0.0847,0.010458,1.8692,0.001133,54.897129,1508.008056,1.0269 1/15/2015,39.22245,4.00689252,56.24925,1.2162,1.41568,0.1966,0.083,0.010475,1.8477,0.001131,51.26283,1535.75655,1.0176 1/16/2015,41.564783,3.75712085,59.192433,1.2157,1.40681,0.1959,0.0835,0.010334,1.8426,0.001126,54.025708,1556.643065,1.0145 1/20/2015,40.165116,3.5790031,56.772082,1.2238,1.41346,0.1969,0.0835,0.010303,1.8534,0.001125,54.116436,1585.212616,1.0103 1/21/2015,42.177854,3.63560002,58.428624,1.2358,1.43603,0.1991,0.0838,0.010484,1.8728,0.001142,56.265974,1598.000622,1.0021 1/22/2015,40.759931,3.65468669,57.308139,1.2461,1.41597,0.2006,0.0851,0.010514,1.87,0.001149,53.968591,1622.733725,1.0062 1/23/2015,40.438559,3.741736,57.162602,1.2641,1.41583,0.2029,0.0862,0.010731,1.8943,0.001173,53.838019,1635.846528,1.0172 1/26/2015,39.6899,3.6918548,56.9793,1.262,1.41814,0.2018,0.0866,0.010655,1.9026,0.001168,53.1933,1617.1268,1.0119 1/27/2015,40.984547,3.72023272,58.245177,1.2599,1.43396,0.2018,0.0862,0.01069,1.9148,0.001169,55.095427,1628.219166,1.0163 1/28/2015,39.23841,3.66368844,56.35371,1.2678,1.43089,0.2029,0.0859,0.010784,1.919,0.001167,53.50116,1628.476422,1.0115 1/29/2015,40.162958,3.70947038,57.359093,1.2881,1.45845,0.2062,0.0871,0.01089,1.9412,0.001171,54.782893,1619.489487,1.0207 1/30/2015,45.35388,3.4501896,62.08488,1.287,1.45464,0.206,0.0859,0.010953,1.9412,0.001168,59.51088,1652.23773,1.0117 2/2/2015,48.153469,3.37535695,63.533869,1.2817,1.45347,0.2047,0.0862,0.010898,1.9273,0.001166,61.162724,1633.411297,1.02 2/3/2015,51.789225,3.4233512,68.089675,1.2835,1.47329,0.2051,0.0876,0.010918,1.9463,0.001174,64.752575,1617.87742,1.0337 2/4/2015,45.4584,3.51880256,62.48112,1.2896,1.46338,0.2064,0.0866,0.010998,1.9581,0.001185,58.61232,1636.95376,1.0256 2/6/2015,49.0428,3.2757615,66.292425,1.2825,1.45125,0.2054,0.0864,0.010767,1.9543,0.001168,62.1243,1582.6563,1.0243 2/9/2015,50.704052,3.32767771,67.750662,1.2817,1.4514,0.2052,0.0864,0.010804,1.9502,0.00117,62.944287,1588.064751,1.0281 2/10/2015,46.993936,3.3894312,64.365736,1.2868,1.4569,0.2062,0.086,0.010776,1.9631,0.001171,59.411556,1587.33214,1.0224 2/11/2015,45.91252,3.68867715,63.27222,1.2955,1.46859,0.2075,0.0859,0.010756,1.9741,0.001169,58.21977,1578.994265,1.0257 2/12/2015,48.816128,3.71175808,66.204288,1.2928,1.47425,0.207,0.0866,0.010854,1.9889,0.001174,61.485568,1579.775744,1.0333 2/13/2015,51.055329,3.51602836,67.996474,1.2883,1.46793,0.2064,0.0864,0.010854,1.9835,0.001174,63.616254,1584.299808,1.0343 2/17/2015,51.969833,3.7682286,68.470223,1.2791,1.45943,0.2046,0.0858,0.010726,1.9637,0.001153,65.272473,1547.570299,1.0324 2/18/2015,50.238972,3.7551199,66.754842,1.2803,1.4592,0.2047,0.0861,0.010776,1.9762,0.001155,63.554092,1552.261326,1.0278 2/19/2015,48.332844,3.8059227,65.658744,1.2834,1.45892,0.2052,0.0855,0.010789,1.9783,0.001155,63.091944,1548.858456,1.027 2/20/2015,46.971,3.8121225,64.1835,1.275,1.45115,0.2038,0.0848,0.010715,1.9638,0.001148,61.6335,1532.4735,1.0174 2/23/2015,46.710675,4.08785685,62.216825,1.2815,1.45274,0.2048,0.0849,0.010788,1.9811,0.001156,62.088675,1540.145145,1.0194 2/24/2015,45.49951,3.9921574,62.03666,1.277,1.44808,0.2041,0.0856,0.010733,1.9734,0.001155,61.65356,1533.07681,1.0223 2/25/2015,47.85432,4.0498652,63.89452,1.268,1.44054,0.2026,0.0849,0.010669,1.969,0.001152,64.33832,1527.94,1.0196 2/26/2015,43.80594,3.9925326,61.75394,1.282,1.43568,0.2049,0.0855,0.010737,1.9752,0.001162,62.58724,1550.56618,1.0243 2/27/2015,46.100002,3.52656694,63.702752,1.2802,1.43351,0.2042,0.0857,0.010706,1.9766,0.001163,65.110972,1553.113036,1.0236 3/2/2015,46.090362,3.657352,63.862002,1.2878,1.44012,0.2053,0.0858,0.01072,1.9787,0.001167,65.149802,1554.155674,1.0272 3/3/2015,46.400211,3.74412731,64.630236,1.2793,1.42964,0.2039,0.0853,0.010684,1.9649,0.001166,64.758166,1539.944582,1.0238 3/4/2015,47.752536,4.16840112,65.917176,1.2792,1.41712,0.204,0.085,0.010688,1.9526,0.001161,66.173016,1535.474928,1.0294 3/6/2015,45.17856,3.733776,64.29456,1.296,1.40524,0.2069,0.0836,0.010726,1.9487,0.001166,64.94256,1512.80784,1.0265 3/9/2015,45.82999,3.52813025,64.915,1.2983,1.40888,0.2072,0.0839,0.010716,1.9641,0.001165,65.888725,1515.388743,1.0297 3/11/2015,44.91898,3.6717185,63.415805,1.3165,1.38864,0.2102,0.085,0.010839,1.9658,0.001163,65.71968,1520.965615,1.0325 3/12/2015,42.8142,3.65775982,61.04267,1.2974,1.37976,0.2072,0.0843,0.010697,1.9309,0.001152,63.31312,1496.849302,1.0226 3/13/2015,39.86118,3.52451925,58.71798,1.3095,1.37437,0.2092,0.0846,0.010787,1.9305,0.00115,60.55128,1517.02956,1.0245 3/16/2015,39.63652,3.4840344,57.43892,1.309,1.38295,0.2091,0.0849,0.010792,1.9405,0.001156,59.40242,1511.64629,1.0249 3/17/2015,39.003288,3.6620556,57.054288,1.3128,1.39119,0.2101,0.0854,0.010815,1.9363,0.001162,59.023488,1509.155496,1.0266 3/18/2015,42.89477,3.55750058,57.441692,1.2862,1.39717,0.2064,0.0852,0.010708,1.9264,0.001157,60.96588,1501.779982,1.0235 3/19/2015,42.261776,3.71650032,57.464512,1.3072,1.39363,0.211,0.0856,0.010824,1.9287,0.001165,61.804416,1530.966496,1.0279 3/20/2015,43.245406,3.63148216,58.809636,1.2863,1.39192,0.2072,0.0854,0.010713,1.9232,0.001155,61.639496,1521.101202,1.0247 3/23/2015,43.77705,3.40877296,59.447965,1.2689,1.38892,0.2042,0.085,0.0106,1.8974,0.00115,61.92232,1509.407306,1.0134 3/24/2015,43.867008,3.52573461,59.796723,1.2693,1.38687,0.2046,0.0849,0.0106,1.8853,0.00115,62.017998,1514.630304,1.0159 3/25/2015,46.160508,3.4948642,62.031768,1.2748,1.39835,0.2052,0.0851,0.010669,1.897,0.001158,64.645108,1523.985156,1.0184 3/26/2015,49.345962,3.49228386,65.696682,1.2774,1.39037,0.2056,0.0844,0.010717,1.8969,0.001156,67.612782,1539.024294,1.0233 3/27/2015,46.555549,3.39750961,63.076509,1.2907,1.40462,0.2076,0.0847,0.010835,1.9197,0.001169,65.657909,1546.968485,1.0231 3/30/2015,46.946138,3.41492976,63.605288,1.3066,1.4154,0.2105,0.0856,0.010882,1.9351,0.001179,66.218488,1549.719062,1.0307 3/31/2015,46.080235,3.44950986,62.57972,1.3147,1.4108,0.212,0.0862,0.010943,1.9479,0.001185,65.20912,1556.039479,1.0365 4/2/2015,48.521964,3.40773283,64.722294,1.3171,1.43301,0.2125,0.0878,0.011001,1.9531,0.001207,69.134579,1583.957631,1.0485 4/6/2015,52.559064,3.448818,68.699664,1.3176,1.43863,0.2127,0.0883,0.011022,1.96,0.001213,73.311264,1600.673184,1.0556 4/8/2015,49.995946,3.47395048,65.611546,1.3013,1.40295,0.2098,0.0873,0.010834,1.9347,0.001191,70.231161,1564.904341,1.0372 4/9/2015,50.557,3.41692,66.027,1.3,1.38567,0.2095,0.0862,0.010782,1.9128,0.001185,70.902,1553.253,1.0332 4/13/2015,53.705376,3.36949848,68.396616,1.3176,1.39235,0.212,0.0857,0.010968,1.9336,0.001196,73.535256,1579.644288,1.0463 4/14/2015,54.401688,3.34395336,69.873848,1.3112,1.39723,0.2111,0.0859,0.010982,1.9383,0.001201,74.987528,1563.973136,1.0503 4/15/2015,58.502892,3.3605967,73.408502,1.3018,1.39125,0.2098,0.0852,0.010926,1.9322,0.001192,77.639352,1565.518644,1.0593 4/16/2015,58.449215,3.30562925,72.673865,1.2815,1.37908,0.2068,0.0845,0.010769,1.9137,0.001182,76.390215,1535.941825,1.0514 4/17/2015,57.486426,3.38622546,71.620326,1.2849,1.38847,0.2073,0.0838,0.010806,1.9222,0.001186,75.796251,1547.302278,1.0493 4/20/2015,59.585835,3.2965737,72.98391,1.2945,1.39,0.2087,0.0837,0.010863,1.9297,0.001195,75.57291,1548.079605,1.0584 4/21/2015,58.049244,3.32836416,71.666694,1.2969,1.39224,0.2091,0.084,0.010837,1.9356,0.001197,73.093284,1559.405529,1.0559 4/22/2015,58.95594,3.3496052,70.99987,1.2895,1.38292,0.2082,0.0835,0.010753,1.939,0.00119,73.91414,1530.804135,1.0537 4/23/2015,59.129343,3.28213496,72.757763,1.2857,1.39152,0.2074,0.0837,0.01075,1.9357,0.001189,73.914893,1535.087229,1.0586 4/24/2015,58.03482,3.27270366,71.009565,1.2783,1.39002,0.2063,0.0832,0.010744,1.9415,0.001187,72.73527,1507.1157,1.0495 4/27/2015,57.881476,3.15924196,72.514076,1.2724,1.38582,0.2046,0.0829,0.010689,1.9389,0.00119,74.422676,1529.61566,1.0528 4/28/2015,57.418396,3.15813644,71.130996,1.2466,1.36853,0.2009,0.0817,0.010487,1.9118,0.001171,73.000896,1511.091122,1.0361 4/29/2015,60.215155,3.183675,73.13713,1.2485,1.38986,0.2014,0.082,0.01049,1.9277,0.001167,76.25838,1504.080435,1.0391 4/30/2015,62.3392,3.2420685,75.43195,1.265,1.41982,0.2039,0.0824,0.010599,1.942,0.001174,78.46795,1498.22805,1.0475 5/1/2015,64.19448,3.39593894,75.339355,1.2737,1.42629,0.2054,0.0819,0.010604,1.9293,0.001179,80.434155,1501.004502,1.0478 5/5/2015,65.59911,3.47524191,76.04964,1.2591,1.40842,0.2029,0.0821,0.010504,1.9116,0.001165,80.267625,1502.534394,1.0433 5/6/2015,66.061176,3.44665368,76.479336,1.2552,1.42396,0.2024,0.0817,0.010506,1.9132,0.001161,80.684256,1496.499648,1.0419 5/8/2015,64.267796,3.48765284,74.855156,1.2604,1.41266,0.203,0.0834,0.010526,1.9495,0.001159,79.140516,1497.846756,1.0439 5/11/2015,64.949125,3.60711599,75.087525,1.2673,1.41369,0.2041,0.0825,0.010554,1.9751,0.001155,79.71317,1500.445181,1.0473 5/13/2015,64.7115,3.5283175,74.5723,1.2326,1.39958,0.1987,0.0807,0.010344,1.9407,0.001128,79.13292,1498.53345,1.0307 5/14/2015,63.273375,3.5573175,74.1015,1.2375,1.41201,0.1996,0.082,0.010385,1.9524,0.001137,78.43275,1511.16075,1.0327 5/15/2015,63.586614,3.6815268,74.290174,1.2446,1.42408,0.2005,0.083,0.010428,1.9565,0.001147,78.770734,1524.38608,1.036 5/18/2015,63.738895,3.76638925,74.376645,1.2515,1.41602,0.2017,0.0828,0.010431,1.9588,0.001148,79.06977,1533.725765,1.0292 5/19/2015,61.418735,3.8809666,72.34801,1.2635,1.40889,0.2036,0.0832,0.010469,1.9604,0.001154,77.40201,1526.13111,1.0329 5/20/2015,62.943986,3.78870226,74.257904,1.2698,1.40872,0.2047,0.0836,0.010465,1.973,0.001158,81.229106,1536.20404,1.04 5/21/2015,65.0981,3.71223815,75.952005,1.2665,1.40745,0.2044,0.0832,0.010465,1.9839,0.001158,83.145725,1525.95519,1.0379 5/22/2015,64.39608,3.68258694,75.409854,1.2777,1.40777,0.206,0.0837,0.010507,1.9797,0.001165,82.603305,1541.174517,1.0401 5/26/2015,62.739584,3.64401536,75.021184,1.2928,1.40575,0.2084,0.0845,0.0105,1.9889,0.001167,80.192384,1534.94144,1.0398 5/27/2015,63.090564,3.6539736,74.412189,1.2939,1.41071,0.2086,0.0846,0.010462,1.9865,0.001166,79.070229,1537.269651,1.0392 5/28/2015,64.941696,3.61976752,75.399296,1.3072,1.4314,0.2108,0.0854,0.010546,2.0022,0.001179,80.301296,1553.47648,1.0512 5/29/2015,68.609845,3.45652344,78.87843,1.3081,1.43671,0.2111,0.0851,0.010539,1.9999,0.001173,83.783805,1557.397698,1.0509 6/1/2015,68.824545,3.41795706,79.14494,1.3147,1.43673,0.2121,0.0849,0.010537,1.9985,0.001178,84.075065,1563.44124,1.0499 6/2/2015,69.810916,3.3760384,78.817116,1.2866,1.43471,0.2076,0.0834,0.010366,1.9741,0.001162,82.676916,1534.926666,1.0372 6/3/2015,67.220262,3.38400207,76.595652,1.2843,1.44798,0.2072,0.0828,0.010338,1.9702,0.00116,79.806402,1522.113831,1.0314 6/4/2015,64.839895,3.36829272,75.4406,1.3007,1.46172,0.2098,0.0837,0.010458,1.9982,0.001168,78.69235,1530.780823,1.0404 6/5/2015,67.505724,3.3529941,77.537169,1.3113,1.45808,0.2114,0.0834,0.010452,2.0031,0.001167,80.749854,1536.764922,1.0543 6/8/2015,65.686056,3.44621328,75.488976,1.2984,1.46592,0.2092,0.0831,0.01043,1.9925,0.001161,78.734976,1524.412488,1.0462 6/10/2015,69.274018,3.7586758,79.127983,1.2881,1.4598,0.2076,0.0834,0.0105,2.0019,0.00116,82.219423,1527.763886,1.051 6/11/2015,68.62719,3.7016387,78.362915,1.2895,1.45168,0.2078,0.084,0.010447,2.0009,0.001158,81.586665,1524.201895,1.0489 6/15/2015,67.050539,3.6892605,76.643904,1.2877,1.45304,0.2074,0.0834,0.010435,2.009,0.001153,80.185079,1527.765911,1.045 6/16/2015,67.294083,3.78675943,77.355303,1.2899,1.45096,0.2078,0.0838,0.010456,2.0188,0.001153,80.902528,1524.752093,1.0492 6/17/2015,67.250436,3.78406281,77.314776,1.2903,1.46302,0.2078,0.0846,0.010454,2.0434,0.001157,81.508251,1529.715165,1.0553 6/18/2015,67.502565,3.66539569,77.502945,1.2821,1.45655,0.2065,0.0836,0.010427,2.0361,0.00116,81.66977,1541.007274,1.0488 6/19/2015,63.657996,3.61449252,76.706148,1.2868,1.4622,0.2072,0.0838,0.010489,2.0445,0.001166,77.812796,1544.507436,1.049 6/22/2015,64.54472,3.59085,77.22592,1.294,1.46751,0.2084,0.0844,0.01049,2.0477,0.001175,78.77872,1534.65812,1.0512 6/23/2015,64.59915,3.657775,78.55815,1.2925,1.44346,0.2083,0.0839,0.010429,2.033,0.001168,79.656775,1523.379275,1.0485 6/24/2015,63.23856,3.590917,78.03576,1.298,1.45441,0.2091,0.0837,0.01048,2.0388,0.001169,77.90596,1525.6692,1.0483 6/25/2015,62.41809,3.605517,76.956465,1.2923,1.44779,0.2081,0.0835,0.010452,2.0348,0.001162,76.827235,1516.087591,1.0484 6/26/2015,63.002849,3.61531588,77.894669,1.3063,1.4586,0.2103,0.084,0.010546,2.0566,0.001163,76.914944,1535.581776,1.0601 6/29/2015,60.656476,3.64694132,75.957326,1.3022,1.46317,0.2097,0.083,0.010626,2.0494,0.001163,74.980676,1536.374626,1.05 6/30/2015,61.592325,3.599265,77.162325,1.2975,1.44605,0.2093,0.0825,0.010594,2.0385,0.001159,76.513575,1521.124125,1.0385 7/1/2015,58.80768,3.6796656,74.50368,1.308,1.44585,0.2109,0.0829,0.010619,2.0429,0.001162,73.84968,1528.77732,1.0389 7/7/2015,54.320112,3.66419214,70.221627,1.3419,1.47769,0.2161,0.085,0.010951,2.0748,0.001182,69.751962,1550.243394,1.0558 7/8/2015,53.0324,3.644968,69.5209,1.346,1.49091,0.2168,0.0849,0.011151,2.0676,0.001185,68.9825,1559.11218,1.0561 7/9/2015,54.092012,3.60555221,70.878262,1.3429,1.48189,0.2163,0.0849,0.011068,2.0652,0.001186,70.341102,1556.998547,1.0565 7/10/2015,53.576259,3.69097311,70.835094,1.3431,1.4986,0.2163,0.0855,0.010939,2.0832,0.001187,70.163544,1563.019194,1.061 7/13/2015,53.404365,3.88818885,70.48566,1.3503,1.4858,0.2175,0.086,0.01094,2.0909,0.001188,69.742995,1563.620394,1.0598 7/14/2015,51.45228,3.9559476,71.17968,1.342,1.47714,0.2161,0.0857,0.010874,2.0982,0.001174,70.10608,1551.43252,1.0543 7/15/2015,49.749392,3.95501568,69.670832,1.3552,1.48392,0.2182,0.0859,0.010946,2.1195,0.001181,68.586672,1557.73464,1.0493 7/16/2015,47.007424,3.91737536,68.748864,1.3504,1.46879,0.2175,0.0853,0.010879,2.1082,0.001178,67.263424,1546.734656,1.0422 7/17/2015,47.178719,3.85661279,69.011929,1.3561,1.46943,0.2184,0.0851,0.010928,2.1165,0.001179,67.520219,1538.007254,1.0453 7/20/2015,45.646225,3.8473053,68.028475,1.3565,1.46853,0.2184,0.0847,0.010915,2.1114,0.001173,66.33285,1487.40225,1.0438 7/21/2015,46.984308,3.8836857,67.875208,1.3478,1.47383,0.217,0.0842,0.01088,2.0969,0.001173,65.853508,1484.26475,1.041 7/22/2015,45.127924,3.9217508,66.248172,1.3556,1.48154,0.2183,0.0842,0.010936,2.1165,0.001172,63.970764,1483.351744,1.0402 7/23/2015,44.45238,3.9599322,65.59105,1.3594,1.4934,0.2189,0.0838,0.010971,2.1093,0.00117,63.34804,1482.69758,1.0426 7/24/2015,44.343857,3.86666348,65.904667,1.3733,1.50784,0.2211,0.0844,0.011092,2.1289,0.001173,63.707387,1509.407763,1.0522 7/27/2015,43.386424,3.89060948,65.189684,1.3756,1.52535,0.2215,0.0844,0.011161,2.1402,0.001178,62.782384,1504.878888,1.055 7/28/2015,43.79319,3.9193065,65.39674,1.363,1.50757,0.2195,0.0838,0.011033,2.1283,0.001175,63.01149,1493.13924,1.0548 7/29/2015,45.150858,3.97653777,66.876453,1.3707,1.50564,0.2208,0.0842,0.01106,2.1384,0.00118,64.477728,1503.452295,1.0588 7/30/2015,44.800371,3.90463962,66.535476,1.3713,1.49907,0.2208,0.0843,0.011047,2.1394,0.001169,64.135701,1493.016588,1.0546 7/31/2015,42.593944,3.78691916,64.493144,1.3687,1.50287,0.2205,0.085,0.011052,2.1376,0.001173,61.413569,1499.82146,1.0463 8/4/2015,39.086852,3.82086176,61.991422,1.3553,1.47451,0.2182,0.0832,0.010899,2.109,0.001159,58.738702,1474.15981,1.0275 8/5/2015,37.590175,3.88205225,61.381425,1.3595,1.48257,0.2189,0.083,0.010888,2.1211,0.001158,57.302925,1475.098285,1.0316 8/6/2015,36.96476,3.7620762,60.78226,1.361,1.48718,0.2192,0.0834,0.010911,2.1116,0.001169,55.61046,1482.87755,1.0382 8/7/2015,35.207148,3.77668101,59.132373,1.3479,1.47832,0.2171,0.0834,0.010849,2.0875,0.001157,53.875563,1474.804785,1.0267 8/10/2015,34.61534,3.8480225,60.65104,1.349,1.48641,0.2172,0.0835,0.010824,2.1032,0.001164,54.91779,1489.98399,1.0375 8/12/2015,31.57616,3.9490528,58.68016,1.3552,1.51235,0.2122,0.0833,0.01091,2.116,0.001155,52.24296,1523.881744,1.0441 8/13/2015,30.948908,3.96154174,57.373678,1.3586,1.51486,0.2124,0.0829,0.010921,2.1211,0.001153,50.852398,1514.97486,1.0404 8/14/2015,31.63925,3.830043,57.5875,1.355,1.50581,0.2121,0.0828,0.0109,2.1199,0.00115,51.15125,1510.91985,1.0348 8/17/2015,30.616205,3.7496373,56.796655,1.3565,1.50273,0.2121,0.0826,0.010906,2.1143,0.001146,50.014155,1516.16005,1.0367 8/18/2015,32.992484,3.69183444,58.056964,1.3622,1.50166,0.213,0.083,0.01095,2.1336,0.001148,50.905414,1522.544562,1.0434 8/19/2015,34.15859,3.7179788,55.52472,1.3609,1.51334,0.2128,0.0818,0.010992,2.1339,0.001149,48.379995,1543.097292,1.0366 8/20/2015,34.669632,3.69373312,56.065592,1.3628,1.5322,0.2133,0.0811,0.011041,2.1386,0.00115,48.910892,1570.21816,1.0416 8/21/2015,34.43832,3.68626684,54.991984,1.3666,1.55664,0.214,0.0805,0.011198,2.145,0.001143,48.10432,1586.308282,1.0364 8/24/2015,33.0369,3.6824125,53.230775,1.3975,1.6236,0.2182,0.0812,0.0118,2.2043,0.001173,46.4529,1614.266225,1.052 8/25/2015,35.151662,3.78153893,54.887651,1.4027,1.61547,0.2187,0.0815,0.011799,2.2004,0.001178,48.827987,1599.765323,1.0515 8/26/2015,33.487785,3.81522052,54.19826,1.4041,1.58844,0.2191,0.0825,0.011707,2.1709,0.001186,49.28391,1579.977566,1.0561 8/27/2015,38.806074,3.7445559,59.388224,1.3954,1.56939,0.2179,0.0827,0.011531,2.1496,0.001189,54.853174,1569.825,1.0573 8/28/2015,42.469086,3.7019328,63.027636,1.3938,1.5594,0.2182,0.0832,0.01146,2.1467,0.001181,58.846236,1580.01168,1.0556 8/31/2015,48.566935,3.7644646,69.16044,1.4057,1.57607,0.2204,0.0839,0.011595,2.1571,0.001188,65.294765,1595.371101,1.0698 9/1/2015,44.610488,3.91193088,64.700168,1.4248,1.61223,0.2239,0.084,0.011938,2.1808,0.001207,63.987768,1624.656696,1.0745 9/2/2015,45.817575,3.85734257,65.707375,1.4207,1.59503,0.2236,0.0844,0.011808,2.1735,0.0012,65.707375,1611.144835,1.0708 9/3/2015,46.66875,3.8077425,66.61875,1.425,1.58507,0.2242,0.0848,0.011868,2.1742,0.001196,66.61875,1603.7805,1.0813 9/4/2015,46.88604,3.86259932,66.638955,1.4471,1.61373,0.2276,0.0854,0.012164,2.1953,0.001204,68.44783,1623.429135,1.0896 9/9/2015,43.95508,3.89084384,62.90492,1.4248,1.59698,0.2234,0.0847,0.011821,2.1897,0.001196,62.47748,1578.46468,1.0749 9/10/2015,45.909333,3.82983093,64.926288,1.4139,1.59506,0.2217,0.0843,0.011721,2.184,0.001196,64.502118,1570.489425,1.0668 9/11/2015,44.114184,3.75788538,62.941689,1.4103,1.59877,0.2212,0.0837,0.011696,2.1753,0.001192,63.223749,1562.541885,1.0633 9/14/2015,43.14772,3.78593225,61.6396,1.4009,1.58556,0.22,0.0837,0.011652,2.1614,0.001184,61.989825,1553.73819,1.0565 9/15/2015,43.955417,3.82379921,62.439377,1.4003,1.578,0.2198,0.0839,0.011629,2.1484,0.001188,62.439377,1547.821605,1.0569 9/16/2015,46.061925,3.72844535,65.514925,1.3895,1.56861,0.2181,0.084,0.011525,2.1528,0.001188,65.792825,1555.57304,1.0549 9/17/2015,45.85273,3.73023805,65.36453,1.3937,1.5939,0.219,0.084,0.011615,2.1734,0.001194,64.458625,1576.985487,1.0574 9/18/2015,43.21674,3.65075775,62.12754,1.3905,1.56734,0.2186,0.0835,0.0116,2.1576,0.001185,61.29324,1584.099315,1.0517 9/21/2015,46.104336,3.63408174,65.454696,1.4022,1.56908,0.2201,0.0842,0.011631,2.1745,0.00119,64.052496,1589.309568,1.058 9/22/2015,45.64378,3.64769405,64.643215,1.4105,1.5684,0.2212,0.0835,0.011739,2.1672,0.00119,63.98028,1586.47398,1.0627 9/23/2015,44.40769,3.69654752,63.355923,1.4279,1.59725,0.2236,0.0834,0.011871,2.1767,0.001195,62.97039,1613.95537,1.0717 9/24/2015,45.427076,3.6486868,63.763044,1.4236,1.59854,0.223,0.0844,0.011857,2.1697,0.001195,63.791516,1642.76322,1.0699 9/25/2015,46.53537,3.62250105,65.03567,1.4231,1.5938,0.2233,0.0839,0.011801,2.1602,0.001193,64.89336,1631.15722,1.0679 9/28/2015,44.609226,3.76932222,63.566001,1.4307,1.60877,0.2246,0.0838,0.011931,2.1711,0.001196,62.850651,1619.480865,1.0682 9/29/2015,45.645784,3.62331308,64.760314,1.4318,1.61043,0.2251,0.0841,0.011957,2.1692,0.001197,64.402364,1614.254274,1.0667 9/30/2015,44.235104,3.52669497,64.257759,1.4251,1.5927,0.2243,0.0842,0.011886,2.1558,0.001202,63.901484,1589.114759,1.0704 10/2/2015,43.330152,3.20833244,64.612152,1.4188,1.59557,0.2232,0.0847,0.011823,2.1576,0.001209,66.243772,1615.44568,1.0782 10/6/2015,46.096668,3.28077648,67.728468,1.3956,1.57309,0.2196,0.0838,0.011608,2.125,0.001202,68.147148,1601.088144,1.0707 10/7/2015,45.520594,3.41952478,66.331594,1.3874,1.55905,0.2183,0.0833,0.011561,2.1252,0.001197,66.817184,1589.322196,1.0627 10/8/2015,47.44454,3.3584616,68.11454,1.378,1.55325,0.2169,0.0837,0.011488,2.1142,0.001196,67.77004,1569.55578,1.0587 10/9/2015,47.010032,3.22675878,67.665542,1.3634,1.54795,0.2148,0.083,0.011338,2.0889,0.001188,67.392862,1576.813002,1.053 10/12/2015,43.25867,3.3078961,63.97122,1.3582,1.54282,0.2148,0.0825,0.011316,2.0847,0.001187,63.69958,1580.74107,1.045 10/13/2015,43.289344,3.361274,64.409464,1.3804,1.5707,0.2177,0.0829,0.011528,2.1048,0.0012,65.099664,1613.466736,1.0586 10/14/2015,43.474278,3.33754799,63.882808,1.3697,1.57167,0.2158,0.0832,0.011527,2.12,0.001205,64.430688,1621.902861,1.0589 10/15/2015,42.613335,3.40019755,63.28551,1.3645,1.55371,0.215,0.0832,0.011475,2.1092,0.001215,64.37711,1614.33995,1.0604 10/16/2015,44.064966,3.27603268,65.058116,1.3766,1.56264,0.2166,0.0838,0.011519,2.1245,0.001217,65.126946,1620.67118,1.0656 10/19/2015,42.270944,3.34428836,63.309844,1.3796,1.56274,0.2169,0.0837,0.011544,2.1336,0.001219,63.378824,1615.221884,1.0596 10/20/2015,41.87296,3.3718752,62.74057,1.3774,1.56268,0.217,0.0832,0.011494,2.1272,0.001217,63.42927,1619.877496,1.0612 10/21/2015,42.88604,3.2713782,61.92955,1.387,1.57253,0.2185,0.0833,0.011566,2.1383,0.001217,64.38454,1618.87866,1.0557 10/22/2015,43.311506,3.24503343,62.192659,1.3873,1.5411,0.2182,0.0842,0.011496,2.1357,0.001227,64.675926,1617.661165,1.0599 10/23/2015,42.568704,3.13874907,60.485805,1.3857,1.52676,0.2182,0.0835,0.01141,2.1219,0.001219,63.700629,1613.578365,1.0526 10/26/2015,40.322785,2.95309565,60.67041,1.3795,1.52545,0.2172,0.0835,0.011394,2.1179,0.001221,61.36016,1604.41368,1.0488 10/27/2015,40.04352,2.87298352,60.06528,1.3904,1.53653,0.2188,0.084,0.011542,2.1274,0.001224,61.45568,1622.429952,1.0478 10/28/2015,44.210928,2.95034822,64.600828,1.4062,1.53517,0.2212,0.0845,0.011613,2.1453,0.001228,65.585168,1625.70782,1.0661 10/29/2015,44.619528,2.9732214,65.119628,1.4138,1.55185,0.2224,0.085,0.011672,2.1644,0.001238,66.109288,1620.172386,1.0732 10/30/2015,43.97739,2.7149979,65.27259,1.401,1.54198,0.2218,0.0849,0.011616,2.1617,0.001228,66.39339,1600.09611,1.0712 11/2/2015,43.154412,2.69043411,64.563702,1.3993,1.54149,0.2208,0.0851,0.011589,2.1573,0.00123,66.662652,1586.582312,1.0686 11/3/2015,45.78364,2.64487496,66.65764,1.3916,1.52581,0.2197,0.0849,0.011494,2.146,0.001231,68.5363,1555.516564,1.0656 11/5/2015,42.55392,2.93272098,63.27096,1.3998,1.52358,0.2206,0.0843,0.011498,2.129,0.00123,65.16069,1545.267216,1.063 11/6/2015,42.079908,3.08543401,62.878513,1.4197,1.52199,0.2235,0.0845,0.011529,2.1341,0.001232,64.511168,1547.18906,1.0672 11/9/2015,41.60508,3.015375,62.25153,1.419,1.52585,0.223,0.0846,0.01152,2.1452,0.001225,64.09623,1549.98789,1.0679 11/11/2015,40.047308,2.99434345,60.793173,1.4161,1.52139,0.2224,0.0846,0.011525,2.1544,0.001226,62.563298,1538.252786,1.0676 11/12/2015,38.03214,2.8264476,58.59195,1.4034,1.51746,0.2204,0.0838,0.011445,2.1375,0.00121,60.3462,1522.96968,1.0557 11/13/2015,36.160159,2.81723953,57.121554,1.4021,1.51187,0.2202,0.0841,0.011442,2.1384,0.001199,59.014389,1519.750211,1.0528 11/16/2015,37.749789,3.01434672,58.815834,1.4091,1.50583,0.2212,0.084,0.01144,2.1422,0.001205,60.718119,1525.717116,1.0571 11/17/2015,36.591926,2.88193059,57.194221,1.4063,1.49639,0.2205,0.0841,0.011393,2.1389,0.001202,59.092726,1505.16289,1.0555 11/18/2015,36.77736,2.95076784,57.3108,1.4064,1.4991,0.2203,0.084,0.011374,2.1427,0.001205,58.85784,1505.874672,1.0572 11/19/2015,36.857496,2.98292774,56.342492,1.3898,1.49208,0.2178,0.0836,0.011312,2.1255,0.001202,59.719706,1504.055458,1.0464 11/20/2015,36.88605,2.9843163,55.798785,1.3815,1.4706,0.2164,0.0835,0.011251,2.0993,0.001196,59.611725,1489.270815,1.0352 11/23/2015,37.468585,2.97371267,55.681515,1.3903,1.47894,0.2176,0.084,0.011319,2.1029,0.0012,59.435325,1486.480954,1.0402 11/24/2015,38.68046,2.9064776,56.87006,1.378,1.46689,0.2158,0.0834,0.011251,2.0788,0.001202,60.45286,1482.2457,1.036 11/25/2015,38.94296,2.8360514,57.62841,1.379,1.46509,0.2158,0.0836,0.011239,2.0862,0.001205,60.93801,1477.07448,1.0377 11/27/2015,37.410282,2.8394835,57.985242,1.3902,1.4725,0.2174,0.0836,0.011321,2.0902,0.001202,59.583972,1470.06699,1.0396 11/30/2015,38.259305,2.88888886,57.631105,1.3837,1.4618,0.2163,0.0835,0.011239,2.0832,0.001193,58.66888,1473.322249,1.0355 12/1/2015,37.62228,2.93235288,57.15036,1.3656,1.45185,0.2134,0.0826,0.011113,2.0595,0.001182,57.28692,1460.222424,1.0221 12/2/2015,34.87032,2.9723904,54.63792,1.368,1.45234,0.2138,0.0826,0.0111,2.0457,0.001176,53.68032,1441.4616,1.0255 12/3/2015,36.411606,2.87887348,55.959176,1.3622,1.49017,0.2129,0.0815,0.01111,2.063,0.00118,55.005636,1446.806242,1.02 12/8/2015,33.545376,2.74127104,51.973856,1.3856,1.50968,0.2159,0.0814,0.011271,2.08,0.001174,53.013056,1489.464576,1.02 12/10/2015,31.329535,2.62105005,50.48986,1.3735,1.50268,0.2133,0.0799,0.011293,2.0821,0.001165,50.76456,1471.81513,1.0079 12/11/2015,30.353802,2.46252522,49.550982,1.3911,1.52838,0.2155,0.08,0.011495,2.1109,0.001172,49.829202,1495.112547,1.0113 12/14/2015,31.219888,2.3294096,50.136848,1.3808,1.51749,0.2138,0.0797,0.011408,2.0905,0.001166,49.860688,1463.454688,1.0053 12/15/2015,32.6744,2.287208,51.93144,1.3904,1.51973,0.2151,0.0813,0.011425,2.0908,0.001184,53.11328,1475.520288,1.0123 12/16/2015,30.094848,2.32077312,49.102848,1.3824,1.50871,0.2136,0.0814,0.011312,2.0745,0.001179,48.619008,1482.375168,1.0032 12/17/2015,31.801476,2.45097216,49.02786,1.4028,1.51869,0.2164,0.0823,0.011447,2.0904,0.001184,51.580956,1474.48308,1.0065 12/18/2015,31.302502,2.36873252,48.403201,1.3937,1.51421,0.2151,0.0814,0.011507,2.0753,0.001178,50.953672,1486.032625,0.9987 12/21/2015,30.891889,2.37259722,48.319866,1.3909,1.51817,0.2146,0.0811,0.011476,2.0704,0.001184,50.503579,1499.94656,0.9961 12/22/2015,31.15028,2.4099316,48.63258,1.382,1.51419,0.2133,0.0804,0.011417,2.0491,0.00118,50.63648,1482.09826,0.9928 12/23/2015,33.1776,2.24612352,51.01056,1.3824,1.50852,0.2134,0.0803,0.011434,2.0558,0.001178,52.5312,1479.8592,0.9978 12/24/2015,33.87174,2.10445396,51.63375,1.3769,1.50918,0.2126,0.0798,0.011431,2.0521,0.001178,53.14834,1481.68209,0.9961 12/28/2015,32.845895,2.8740503,50.779395,1.3795,1.51295,0.2126,0.08,0.011458,2.0527,0.00118,51.469145,1474.79586,0.992 12/29/2015,34.086822,3.24407314,51.904622,1.3706,1.49668,0.2113,0.0794,0.011379,2.0309,0.00117,52.589922,1465.322166,0.9901 12/30/2015,32.043205,3.11484654,50.22618,1.3723,1.50028,0.2114,0.079,0.011386,2.0336,0.001165,50.91233,1456.614112,0.9886 12/31/2015,32.647017,3.17330652,50.829992,1.3723,1.49151,0.2112,0.0797,0.011414,2.0228,0.001166,51.516142,1456.14753,0.9915 1/4/2016,32.069542,3.31779299,51.122132,1.3907,1.50628,0.2129,0.0803,0.011643,2.0465,0.001168,52.165157,1494.460127,0.9967 1/6/2016,28.239577,3.32299359,48.036977,1.4141,1.52451,0.2157,0.0806,0.011934,2.0687,0.001178,47.683452,1546.558747,1.0045 1/7/2016,27.124422,3.34591582,47.446347,1.4261,1.55926,0.2163,0.0799,0.012123,2.0848,0.001191,46.804602,1581.502117,1.0103 1/8/2016,26.836812,3.5516349,47.690712,1.4382,1.56939,0.2181,0.0802,0.012268,2.0879,0.001191,46.540152,1587.98853,1.0149 1/11/2016,23.750639,3.61178441,44.913159,1.4299,1.55235,0.2176,0.08,0.012143,2.079,0.001186,44.055219,1564.59658,1.0058 1/12/2016,22.243956,3.41045364,43.571816,1.4314,1.55427,0.2178,0.08,0.012165,2.068,0.001183,42.712976,1555.301984,1.0036 1/13/2016,22.688484,3.31024694,43.824144,1.4378,1.56361,0.2187,0.0801,0.012215,2.0711,0.001189,43.392804,1572.363702,1.0024 1/14/2016,23.8428,3.13966,44.6784,1.432,1.55561,0.2173,0.0801,0.01213,2.0635,0.001186,43.8908,1544.24016,0.9966 1/15/2016,22.034376,3.17924568,42.873766,1.4573,1.59116,0.2205,0.0798,0.012453,2.0796,0.001201,41.052141,1586.824824,1.0027 1/19/2016,21.511336,3.20701304,41.198696,1.4476,1.57904,0.2193,0.0792,0.012304,2.0496,0.001199,40.836796,1574.134716,0.9929 1/20/2016,20.99165,3.10082863,38.436435,1.4477,1.57646,0.2213,0.0781,0.012378,2.0545,0.001197,41.9833,1593.801884,0.9982 1/21/2016,22.403584,3.14864656,40.406464,1.4288,1.55377,0.219,0.0763,0.012139,2.0319,0.001187,42.835424,1573.39456,1.0016 1/22/2016,25.977139,3.16552646,44.256819,1.4281,1.54182,0.2162,0.0774,0.012023,2.037,0.001192,45.970539,1567.982395,1.0111 1/25/2016,23.349872,3.07876114,40.819142,1.4378,1.55985,0.2176,0.0773,0.012155,2.0487,0.001198,43.694742,1592.93862,1.0061 1/26/2016,24.056745,3.18205776,44.901165,1.4277,1.55193,0.2171,0.0773,0.012056,2.0486,0.001191,44.758395,1598.895507,1.0112 1/27/2016,25.54644,3.18569088,45.96936,1.4232,1.55024,0.2161,0.0771,0.011992,2.0258,0.001178,45.61356,1601.057304,1.0097 1/28/2016,26.074099,2.98758071,46.896674,1.4117,1.5444,0.2144,0.0771,0.011881,2.0274,0.001169,46.049654,1574.511361,1.0063 1/29/2016,25.932929,3.17872489,47.461354,1.4117,1.52898,0.2148,0.0779,0.011654,2.0106,0.001169,47.037844,1578.577057,1.0105 2/2/2016,20.431104,2.89147008,42.453504,1.4208,1.55131,0.2156,0.0769,0.011842,2.0473,0.001172,41.672064,1604.097408,1.011 2/3/2016,23.409778,2.87265041,45.033828,1.3951,1.54915,0.2146,0.0768,0.011835,2.0371,0.001162,43.987503,1594.083113,1.0123 2/5/2016,23.89935,2.952539,43.70935,1.415,1.57863,0.2142,0.0767,0.012112,2.0525,0.001172,44.6291,1660.361,1.0168 2/8/2016,22.706208,3.13879104,41.898528,1.4112,1.57931,0.2152,0.0756,0.012182,2.0363,0.001172,44.015328,1678.241376,1.0133 2/9/2016,20.213205,3.0652215,39.52113,1.4145,1.5972,0.2157,0.0752,0.012284,2.0465,0.001177,42.703755,1682.024385,1.0201 2/11/2016,19.706466,2.98466454,36.866986,1.4066,1.59283,0.2142,0.0735,0.012512,2.0365,0.001172,41.227446,1753.60822,1.0095 2/12/2016,23.906629,2.90833499,41.425024,1.4071,1.58356,0.2146,0.0744,0.012426,2.0402,0.001163,45.646324,1741.947587,1.0159 2/16/2016,23.328858,2.69807594,40.836048,1.4062,1.56711,0.2161,0.0745,0.012325,2.0117,0.001154,43.296898,1688.058728,1.0143 2/17/2016,27.460214,2.6618175,42.672588,1.3918,1.54879,0.2148,0.0758,0.0122,1.9896,0.001137,50.076964,1681.9903,1.0181 2/18/2016,28.407109,2.61798128,42.994921,1.3973,1.55179,0.2145,0.0764,0.012336,2.0032,0.001137,50.204989,1719.894651,1.0179 2/19/2016,26.85888,2.52963087,41.463396,1.3989,1.55681,0.2164,0.0768,0.01242,2.0136,0.001134,48.611775,1716.17052,1.0159 2/22/2016,28.559568,2.54808355,43.558876,1.3837,1.52613,0.2121,0.0765,0.012254,1.958,0.001131,49.660993,1672.381331,1.0095 2/23/2016,27.034095,2.538178,41.752195,1.3885,1.53002,0.212,0.0763,0.012385,1.9468,0.001127,49.944345,1703.481225,1.0064 2/24/2016,27.16668,2.49169176,42.24384,1.3896,1.53038,0.2135,0.0763,0.012387,1.9353,0.001127,50.23404,1707.471,1.0142 2/25/2016,28.28954,2.4395064,44.45894,1.382,1.52272,0.2124,0.0762,0.012229,1.9294,0.001119,51.36894,1703.88162,1.0214 2/26/2016,28.448784,2.33538144,45.983784,1.4028,1.53376,0.2133,0.0768,0.012311,1.9464,0.001129,51.945684,1716.269688,1.0383 2/29/2016,29.61846,2.26360656,47.2635,1.4004,1.52251,0.2139,0.0772,0.012427,1.9487,0.001131,54.2655,1734.633468,1.0337 3/2/2016,29.691528,2.17367756,47.511928,1.3708,1.4899,0.2106,0.0769,0.012079,1.93,0.001119,54.503008,1699.764584,1.0216 3/3/2016,28.659414,2.11728732,47.022114,1.3602,1.49039,0.2081,0.0759,0.011964,1.9286,0.001122,53.143014,1719.63285,1.0148 3/8/2016,31.52618,2.08234116,49.0706,1.3444,1.48019,0.2066,0.075,0.011937,1.9109,0.001111,55.85982,1695.879936,1.0026 3/10/2016,32.719185,2.27558645,50.76236,1.3415,1.49946,0.206,0.0753,0.011848,1.9157,0.001114,56.597885,1706.723375,1.0053 3/11/2016,33.1822,2.277145,50.897,1.322,1.47451,0.2032,0.0746,0.011612,1.9002,0.001113,56.6477,1651.7729,1.0004 3/14/2016,31.648802,2.24057015,49.482862,1.3309,1.47772,0.2049,0.075,0.011691,1.9033,0.001119,55.272277,1644.020843,1.0037 3/15/2016,30.492066,2.38304748,48.728306,1.3409,1.48991,0.2058,0.075,0.011847,1.8977,0.001122,54.091906,1652.498342,1.004 3/16/2016,33.380561,2.29877001,50.924886,1.3241,1.48634,0.2062,0.0752,0.011761,1.888,0.001123,55.757851,1671.768937,1.0109 3/17/2016,35.23443,2.3781606,52.55748,1.3074,1.47969,0.2026,0.0755,0.011736,1.8934,0.001132,57.32949,1644.669978,1.0076 3/18/2016,36.984402,2.41594626,51.835992,1.3143,1.48206,0.203,0.0756,0.01179,1.9022,0.001129,58.998927,1649.97222,1.0115 3/21/2016,37.637844,2.32372776,52.669227,1.3197,1.48331,0.2031,0.0758,0.011788,1.896,0.001136,59.742819,1641.376875,1.0074 3/22/2016,37.26364,2.30221066,52.418395,1.3121,1.47174,0.2019,0.0757,0.011678,1.8641,0.001134,59.30692,1637.920672,1.0055 3/23/2016,35.502698,2.403137,51.103173,1.3277,1.48451,0.2038,0.0755,0.011815,1.8742,0.001136,57.808058,1619.940047,1.0055 3/24/2016,35.085685,2.3315175,50.42986,1.3285,1.48425,0.2043,0.0754,0.011767,1.8799,0.001137,57.404485,1616.54537,1.0028 3/28/2016,34.916304,2.299916,52.215384,1.3256,1.48403,0.2036,0.076,0.011683,1.8894,0.001137,57.186384,1619.498776,1.0052 3/29/2016,32.942917,2.320293,50.181252,1.3109,1.48026,0.2032,0.0756,0.011625,1.8859,0.001134,54.441677,1628.39998,1.0026 3/30/2016,32.811612,2.395365,49.953952,1.3036,1.47796,0.2015,0.0757,0.011595,1.8743,0.00114,54.190652,1596.936072,1.0054 3/31/2016,32.895621,2.55277332,50.068206,1.3059,1.48624,0.2017,0.0756,0.011601,1.8755,0.001141,54.312381,1609.848225,1.0042 4/1/2016,30.651434,2.38219195,47.904259,1.3021,1.48434,0.2015,0.0751,0.011667,1.8533,0.001137,52.136084,1591.94746,1.0007 4/4/2016,29.523995,2.57036295,46.94907,1.3151,1.49762,0.2027,0.0752,0.011812,1.8755,0.001142,51.223145,1598.411993,1.0048 4/5/2016,29.282504,2.51426552,47.575784,1.3256,1.50913,0.205,0.0749,0.012014,1.8771,0.001142,48.503704,1632.27756,1.009 4/7/2016,29.725844,2.5775278,49.645224,1.3324,1.51596,0.2062,0.0745,0.012312,1.873,0.001148,50.111564,1652.77558,1.0136 4/8/2016,33.528744,2.64945936,52.597224,1.3242,1.50888,0.2043,0.0745,0.012251,1.8702,0.00115,51.935124,1642.921698,1.0193 4/11/2016,34.502844,2.46601212,53.129904,1.3164,1.50166,0.2036,0.0746,0.012195,1.8745,0.001152,52.142604,1655.873232,1.0207 4/13/2016,35.754048,2.5881174,54.571968,1.3068,1.47328,0.2018,0.075,0.011951,1.8562,0.00114,53.657208,1623.659796,1.0194 4/14/2016,35.021525,2.49724915,53.92925,1.2995,1.4643,0.2004,0.0745,0.01188,1.8395,0.001126,52.88965,1595.643055,1.0115 4/15/2016,33.413626,2.2234755,52.250056,1.2946,1.46133,0.2004,0.0738,0.011903,1.8384,0.001129,50.955456,1597.523454,1.0095 4/18/2016,32.296209,2.2786698,51.328134,1.2903,1.45968,0.1992,0.074,0.011858,1.8423,0.001127,50.037834,1590.281847,1.0093 4/19/2016,36.758728,2.43129804,52.578292,1.2799,1.45372,0.1982,0.0739,0.011719,1.8425,0.001134,53.397428,1600.118181,1.01 4/20/2016,39.04169,2.5858865,54.69429,1.283,1.44942,0.1977,0.0743,0.011681,1.839,0.001132,55.84899,1596.37275,1.0139 4/21/2016,37.773929,2.5057697,54.573829,1.2923,1.45878,0.1987,0.074,0.011806,1.8511,0.001132,55.219979,1612.855015,1.0147 4/22/2016,38.62466,2.4633921,55.35596,1.297,1.45592,0.1995,0.0742,0.011607,1.867,0.001128,56.13416,1599.23991,1.0237 4/25/2016,37.771268,2.56362436,53.455288,1.2962,1.46038,0.1995,0.0738,0.011657,1.8771,0.001126,56.566168,1604.656714,1.0224 4/26/2016,39.288908,2.42199855,56.842428,1.2907,1.45789,0.1989,0.0743,0.011595,1.8818,0.001125,58.133128,1604.85638,1.0241 4/27/2016,41.932842,2.47776592,59.717742,1.3174,1.49129,0.2029,0.0761,0.011821,1.9157,0.001147,61.035142,1641.256442,1.0457 4/28/2016,43.053262,2.48195564,60.363742,1.3114,1.48856,0.2021,0.0759,0.012133,1.9159,0.001153,61.347292,1660.573364,1.0446 4/29/2016,42.823036,2.50876988,60.375616,1.3148,1.50537,0.2027,0.0765,0.012372,1.9211,0.001149,61.230236,1700.733244,1.0477 5/2/2016,40.928934,2.48912612,58.406554,1.3043,1.50436,0.2022,0.0758,0.01226,1.9139,0.001147,58.406554,1684.568665,1.0408 5/4/2016,41.480223,2.67804259,58.713358,1.3411,1.54049,0.2058,0.0753,0.012534,1.9441,0.001149,60.054458,1716.178848,1.0421 5/5/2016,43.496812,2.74296496,59.371072,1.3396,1.5277,0.2055,0.0749,0.01249,1.9403,0.001147,61.782352,1711.660504,1.0422 5/9/2016,43.86703,2.6934001,59.38248,1.367,1.55593,0.2096,0.0751,0.012618,1.9693,0.001163,63.00503,1727.72396,1.0545 5/10/2016,44.083926,2.770524,60.652746,1.3581,1.54442,0.2086,0.0755,0.012429,1.9614,0.00116,61.467606,1719.137304,1.0521 5/12/2016,46.898055,2.73756303,63.75951,1.3653,1.55307,0.2093,0.076,0.012527,1.9727,0.001167,65.056545,1725.302304,1.0629 5/13/2016,47.337837,2.69595929,63.571097,1.3757,1.55482,0.2105,0.0757,0.01266,1.9751,0.001169,65.634647,1751.885165,1.0632 5/16/2016,49.137876,2.6146508,65.462296,1.3718,1.55301,0.2102,0.0749,0.012583,1.9758,0.001165,67.451406,1747.892688,1.0639 5/17/2016,50.24565,2.6754,65.94315,1.365,1.5447,0.209,0.0747,0.012506,1.9745,0.00116,69.35565,1745.76675,1.0576 5/18/2016,50.874096,2.6405288,66.656408,1.3832,1.55143,0.2099,0.075,0.012552,2.0194,0.001162,70.584696,1740.7572,1.0614 5/19/2016,50.736612,2.52520836,66.634176,1.3836,1.54997,0.2121,0.0751,0.012582,2.0216,0.001166,71.490612,1736.0721,1.0567 5/20/2016,50.413286,2.50667984,66.11465,1.3846,1.55386,0.2115,0.0755,0.012571,2.0095,0.001164,71.528436,1733.491508,1.0557 5/23/2016,49.945544,2.70395319,65.726564,1.3843,1.55329,0.2113,0.0748,0.012674,2.0051,0.00117,71.056119,1729.170659,1.0533 5/24/2016,50.978702,2.6519505,67.057457,1.3921,1.5509,0.2121,0.0753,0.012657,2.0373,0.001172,72.208227,1708.399041,1.0608 5/25/2016,52.174596,2.45384515,68.288156,1.3891,1.54964,0.2121,0.0752,0.012607,2.0417,0.001175,73.358371,1700.827931,1.067 5/26/2016,51.868572,2.41974915,68.475372,1.3839,1.54907,0.2112,0.075,0.012609,2.0302,0.001173,72.973047,1688.08122,1.0663 5/27/2016,52.373434,2.46640878,68.657494,1.3918,1.54662,0.2116,0.0754,0.012625,2.0369,0.001173,73.180844,1687.390484,1.0686 5/31/2016,51.64011,2.8923992,67.88566,1.3826,1.53891,0.2097,0.0749,0.012486,2.0022,0.001161,72.72476,1680.301432,1.056 6/1/2016,51.20648,3.1079412,67.53578,1.378,1.54155,0.2095,0.0744,0.012579,1.9863,0.001156,71.66978,1671.48644,1.0537 6/6/2016,51.3678,3.147228,67.454175,1.3575,1.54176,0.2067,0.0727,0.012623,1.9605,0.001167,72.68055,1690.54905,1.0592 6/7/2016,51.492446,3.06555002,67.512616,1.3406,1.52286,0.2042,0.073,0.012484,1.9501,0.001159,72.472836,1667.451686,1.0527 6/9/2016,51.819056,3.10793232,68.033536,1.3456,1.52293,0.2051,0.0737,0.012562,1.9457,0.00116,72.204896,1708.64288,1.0578 6/10/2016,49.935284,3.27847788,66.548734,1.3562,1.52601,0.206,0.0727,0.012679,1.9334,0.001158,71.024194,1728.124288,1.061 6/13/2016,49.315291,3.41606195,66.168856,1.3537,1.52863,0.205,0.0719,0.012737,1.9301,0.001155,70.906806,1737.961282,1.0544 6/14/2016,49.11426,3.4286211,65.89791,1.359,1.52307,0.2061,0.0718,0.012809,1.9181,0.001155,70.65441,1747.29348,1.0557 6/15/2016,48.546,3.53781,64.8135,1.35,1.51997,0.205,0.0714,0.012734,1.9174,0.001155,70.146,1743.8625,1.0456 6/16/2016,46.331613,3.54217474,62.767043,1.3583,1.52448,0.2073,0.0717,0.013028,1.9291,0.001158,67.724838,1736.491469,1.0472 6/17/2016,48.456492,3.4912206,64.888152,1.3524,1.52556,0.2057,0.0718,0.012981,1.9422,0.001155,69.621552,1756.29426,1.0489 6/20/2016,49.302512,3.66469488,66.215044,1.3412,1.51677,0.2037,0.0719,0.012903,1.9707,0.001155,70.359352,1730.01388,1.0472 6/21/2016,49.195295,3.70676145,65.571355,1.3423,1.509,0.2033,0.0721,0.012811,1.9667,0.001164,70.269405,1702.197476,1.047 6/22/2016,47.831628,3.70255194,64.562033,1.3331,1.50606,0.2027,0.0721,0.012764,1.9609,0.001161,68.827953,1687.997882,1.038 6/23/2016,48.225927,3.52689039,64.647177,1.3137,1.49569,0.2004,0.0721,0.012376,1.9535,0.001151,68.785332,1651.110708,1.0287 6/24/2016,45.716874,3.57981603,62.857354,1.3391,1.48825,0.2027,0.0706,0.013084,1.8305,0.001141,66.138149,1761.920825,1.0299 6/27/2016,44.919813,3.76232421,63.198753,1.3641,1.50338,0.2048,0.0711,0.013378,1.8038,0.001156,65.244903,1806.88686,1.0439 6/28/2016,46.492725,3.8723635,64.764975,1.3535,1.49802,0.2046,0.0719,0.013176,1.8066,0.00116,66.795225,1775.507765,1.0393 6/29/2016,48.68776,3.9323284,66.93896,1.342,1.493,0.2025,0.0726,0.013052,1.8023,0.001163,68.75066,1770.2993,1.0377 6/30/2016,46.346166,3.89117202,64.868526,1.3422,1.49064,0.202,0.0734,0.013006,1.7866,0.001164,66.210726,1774.25418,1.0386 7/1/2016,46.968093,3.83819679,65.386953,1.3347,1.48629,0.2006,0.0726,0.013005,1.772,0.001159,66.721653,1790.299845,1.0328 7/6/2016,44.252416,3.65747282,63.067671,1.3297,1.47618,0.1992,0.071,0.013125,1.7197,0.001147,62.801731,1813.418266,1.0262 7/7/2016,41.303019,3.81795534,60.356694,1.3371,1.47825,0.1998,0.071,0.013267,1.7253,0.001154,59.955564,1819.057695,1.0283 7/11/2016,40.707282,3.77770481,59.427852,1.3277,1.46819,0.1983,0.0719,0.012915,1.7253,0.001154,58.963157,1799.56458,1.0123 7/12/2016,43.095915,3.60956166,61.39692,1.3119,1.45101,0.1961,0.0715,0.012531,1.7377,0.001147,60.937755,1748.89389,1.006 7/13/2016,40.552325,3.6926934,58.823875,1.3145,1.45774,0.1962,0.0716,0.012581,1.7282,0.001147,58.49525,1764.90028,1.0129 7/14/2016,41.837879,3.63385499,59.854504,1.3103,1.457,0.1959,0.0714,0.012439,1.7483,0.001157,59.002809,1749.551869,1.0166 7/15/2016,42.56355,3.51871878,60.64481,1.3198,1.45587,0.1969,0.0709,0.012584,1.7419,0.001158,59.98491,1765.16651,1.0179 7/18/2016,42.272157,3.69976878,59.594652,1.3173,1.45893,0.1964,0.0716,0.012409,1.7461,0.00116,58.540812,1750.494105,1.0177 7/19/2016,41.04408,3.73887582,59.50059,1.3326,1.46873,0.1994,0.072,0.012557,1.7473,0.001168,58.76766,1775.036526,1.0234 7/20/2016,41.52627,3.64026906,60.102756,1.3374,1.47183,0.2001,0.0716,0.012512,1.766,0.00117,59.31369,1760.098644,1.0241 7/21/2016,40.035,3.60621935,58.651275,1.3345,1.47119,0.1998,0.0718,0.012611,1.7654,0.001173,57.850575,1776.793335,1.0198 7/22/2016,39.42016,3.7165284,58.23311,1.339,1.47086,0.201,0.0722,0.012626,1.7557,0.001179,57.42971,1771.13547,1.0206 7/25/2016,37.992306,3.76067604,56.734106,1.3387,1.47204,0.2007,0.0713,0.012653,1.759,0.001172,55.997821,1761.19372,1.0128 7/26/2016,37.544976,3.6192184,57.203776,1.3328,1.46439,0.1994,0.071,0.012738,1.7501,0.001172,55.471136,1759.642528,1.0108 7/27/2016,36.536213,3.73558416,55.959008,1.3349,1.47627,0.2008,0.0709,0.012666,1.7651,0.00118,54.156893,1788.872792,1.0123 7/28/2016,35.233944,3.68383944,54.823164,1.3326,1.47622,0.2001,0.0705,0.01266,1.7544,0.001185,52.957524,1780.02045,1.0129 7/29/2016,35.337285,3.87394035,54.74976,1.3161,1.47066,0.1984,0.0702,0.012892,1.7421,0.001184,52.90722,1778.419608,1.0097 8/1/2016,33.588901,3.80559196,53.163626,1.3271,1.48073,0.1991,0.0703,0.01296,1.7485,0.001197,51.239331,1795.765365,1.0114 8/2/2016,32.342462,3.66122978,51.924042,1.3142,1.47465,0.1982,0.0694,0.013027,1.755,0.001182,49.821322,1792.003694,1.0024 8/3/2016,34.436727,3.79871496,53.809857,1.3179,1.46928,0.1986,0.0698,0.013017,1.756,0.00118,51.964797,1789.945422,1.0086 8/4/2016,35.50188,3.7857747,54.97023,1.311,1.45899,0.1972,0.0693,0.012952,1.7184,0.001177,53.26593,1784.46765,1.0072 8/8/2016,36.755652,3.69464886,56.231442,1.3071,1.44927,0.196,0.0704,0.012758,1.7044,0.00118,54.401502,1745.383701,0.9934 8/9/2016,36.518466,3.58394467,55.742141,1.3033,1.44896,0.1958,0.0707,0.012792,1.6947,0.001182,54.569171,1747.373409,0.9936 8/11/2016,37.847032,3.46350996,56.484812,1.2988,1.44651,0.1953,0.0712,0.012738,1.6828,0.001183,55.315892,1738.807464,0.9995 8/12/2016,39.199929,3.52812432,58.152879,1.3071,1.45825,0.196,0.0716,0.012901,1.687,0.001184,56.976489,1746.246387,1.0089 8/15/2016,40.972608,3.5271108,59.608368,1.3032,1.45742,0.196,0.0721,0.01287,1.6785,0.001187,58.305168,1745.50608,1.0083 8/16/2016,42.340968,3.52464516,60.535368,1.2996,1.46563,0.1961,0.0719,0.012956,1.6954,0.001186,59.755608,1749.573504,1.0103 8/17/2016,42.827019,3.53613514,61.112419,1.3061,1.47453,0.1976,0.072,0.013025,1.7036,0.001179,60.328759,1761.576253,1.0169 8/18/2016,44.06487,3.5302635,62.73422,1.301,1.47715,0.1963,0.0715,0.013025,1.7132,0.001174,62.73422,1759.42036,1.0178 8/19/2016,44.938251,3.46248765,63.624276,1.3113,1.48492,0.1972,0.072,0.013083,1.714,0.001175,63.624276,1759.069611,1.0188 8/22/2016,43.217152,3.58665648,61.69196,1.3112,1.48579,0.1972,0.0717,0.013068,1.7245,0.001167,61.836192,1755.814808,1.0127 8/23/2016,44.05786,3.56244896,62.57398,1.3132,1.48458,0.197,0.0707,0.0131,1.7331,0.001172,63.0336,1756.483792,1.0169 8/24/2016,42.517995,3.64062795,61.038345,1.3135,1.47933,0.1975,0.0712,0.013076,1.738,0.001172,61.76077,1739.244755,1.016 8/25/2016,43.030306,3.75550343,61.605011,1.3127,1.48128,0.1973,0.0715,0.013058,1.7319,0.001177,62.195726,1735.350019,1.0159 8/26/2016,43.692096,3.80480928,62.999136,1.3224,1.48006,0.1961,0.0711,0.012985,1.7367,0.001178,62.866896,1747.128432,1.0168 8/29/2016,42.846516,3.89502972,62.069976,1.3212,1.47817,0.1977,0.0709,0.012963,1.7314,0.00118,62.136036,1748.449656,1.0155 8/30/2016,42.34488,3.89399788,61.71966,1.3316,1.48373,0.1993,0.0708,0.012934,1.7417,0.001189,61.78624,1745.874076,1.0166 8/31/2016,40.50459,3.91464558,59.45994,1.3302,1.48423,0.1992,0.0708,0.012862,1.7477,0.001192,59.92551,1741.191894,1.0151 9/2/2016,40.067004,3.76886034,58.687464,1.3206,1.47437,0.1983,0.0711,0.012706,1.7557,0.001183,59.545854,1750.072326,1.0169 9/6/2016,39.911612,3.66450521,58.319347,1.3009,1.46412,0.1955,0.0712,0.012752,1.7482,0.001188,59.360067,1756.215,1.0129 9/8/2016,43.919631,3.71230125,62.301246,1.3083,1.47303,0.1953,0.07,0.012766,1.7395,0.001191,64.067451,1750.89789,1.0113 9/9/2016,42.146636,3.87356496,60.846056,1.3262,1.48971,0.1977,0.0702,0.012913,1.7589,0.001196,61.907016,1760.968146,1.0164 9/12/2016,42.479438,3.95769848,61.181493,1.3217,1.48497,0.1989,0.0703,0.012979,1.7628,0.001193,62.040598,1754.979694,1.0136 9/13/2016,41.13493,4.113493,60.16151,1.3399,1.50311,0.2001,0.0702,0.013065,1.7675,0.001188,61.76939,1767.395095,1.0169 9/14/2016,39.275803,4.057473,58.357978,1.3391,1.50613,0.2002,0.0695,0.013073,1.772,0.001189,59.897943,1771.548954,1.0148 9/15/2016,39.535097,3.92463351,58.431037,1.3307,1.49613,0.1998,0.0687,0.013035,1.7617,0.001183,60.094412,1749.537825,1.0116 9/16/2016,38.746341,3.91787838,57.432141,1.3347,1.4895,0.2002,0.068,0.013049,1.7348,0.001185,59.300721,1748.924145,1.0104 9/19/2016,39.304314,3.94397088,57.47642,1.3274,1.48324,0.1985,0.0674,0.013024,1.7295,0.001186,59.812644,1743.128406,1.0053 9/20/2016,39.24474,4.07893812,57.497184,1.3236,1.47582,0.1984,0.0668,0.013014,1.719,0.001185,59.82672,1740.322224,1.0034 9/21/2016,40.649583,4.11952502,59.210138,1.3117,1.46774,0.1977,0.0664,0.013076,1.7095,0.001188,60.849763,1751.342489,1.0011 9/22/2016,41.891766,4.10570706,60.404211,1.3083,1.46634,0.1962,0.0667,0.012983,1.711,0.001185,61.647096,1749.288681,1.0031 9/23/2016,39.578052,3.97629594,58.134362,1.3114,1.47236,0.1966,0.0663,0.012989,1.6973,0.001189,59.380192,1754.076184,0.9962 9/26/2016,41.422648,3.98851776,60.149928,1.3096,1.47374,0.1962,0.0659,0.013052,1.6992,0.001181,61.197608,1752.17932,0.99 9/27/2016,39.742021,3.95398545,58.263081,1.3043,1.46253,0.1959,0.0673,0.012987,1.6986,0.001189,59.110876,1731.223476,0.9884 9/28/2016,43.16,3.87153,61.165,1.3,1.45826,0.1956,0.0671,0.012911,1.6924,0.00119,62.27,1718.002,0.9939 9/29/2016,44.434728,3.85965312,62.638168,1.3096,1.46972,0.1955,0.0671,0.012962,1.6984,0.001188,63.620368,1729.156552,0.9961 9/30/2016,44.70032,3.70618395,62.97732,1.3055,1.46598,0.1956,0.0673,0.012883,1.6923,0.001185,63.63007,1717.868285,0.9943 10/3/2016,45.306184,3.66568216,63.618954,1.3034,1.46061,0.1956,0.0676,0.012822,1.6734,0.00118,64.400994,1709.53944,0.9933 10/5/2016,46.946938,3.75234358,65.381943,1.3121,1.47003,0.1967,0.0683,0.012677,1.6726,0.001177,65.644363,1662.233885,0.9958 10/6/2016,48.104767,3.94184883,66.495052,1.3183,1.47016,0.1979,0.0685,0.012682,1.6633,0.001182,66.363222,1653.649154,0.9973 10/10/2016,49.2975,4.1285013,67.50471,1.3146,1.46427,0.1959,0.0695,0.012688,1.6252,0.001186,67.37325,1655.93589,0.9978 10/11/2016,49.26621,4.16534265,67.372935,1.3265,1.46618,0.1971,0.0701,0.012814,1.6081,0.001179,67.43926,1661.8392,1 10/13/2016,48.540888,4.17327444,66.641328,1.3212,1.46061,0.1967,0.0698,0.01274,1.6191,0.001169,66.112848,1662.188508,1.0015 10/14/2016,47.92815,4.10934645,66.114585,1.3131,1.4406,0.1952,0.0691,0.012599,1.5996,0.001156,65.39238,1642.727493,0.9993 10/17/2016,47.048201,4.14794978,65.466346,1.3109,1.44194,0.1947,0.0695,0.012618,1.5971,0.001153,64.810896,1646.293765,0.9985 10/18/2016,47.14463,4.19514155,65.603305,1.3045,1.43239,0.1936,0.0701,0.01256,1.6042,0.001159,64.36403,1646.93125,0.9951 10/19/2016,48.333132,4.07036979,66.82716,1.2951,1.42116,0.1926,0.0699,0.012518,1.591,0.001156,66.464532,1643.779773,0.9875 10/20/2016,47.370043,4.05247899,66.118773,1.3111,1.433,0.1942,0.0704,0.012612,1.6067,0.001158,65.725443,1659.537936,0.991 10/21/2016,47.782075,3.7949615,66.447975,1.3145,1.43009,0.1947,0.0707,0.012659,1.6064,0.001157,66.185075,1664.76167,0.9858 10/24/2016,47.454456,3.61965038,65.847656,1.3138,1.42978,0.1942,0.0708,0.01261,1.608,0.001157,64.927996,1661.221272,0.989 10/25/2016,46.632582,3.49208208,64.744227,1.3077,1.42414,0.1929,0.0706,0.012548,1.5941,0.001157,63.894222,1665.839799,0.9796 10/26/2016,45.460938,3.50237445,64.283178,1.3071,1.42584,0.1929,0.0699,0.012511,1.6009,0.001148,62.714658,1656.22641,0.9769 10/27/2016,46.281136,3.53908368,65.521016,1.3178,1.43602,0.1939,0.0699,0.012513,1.6028,0.001148,63.807876,1671.49752,0.9844 10/28/2016,45.01062,3.4929294,64.09407,1.3161,1.44487,0.1948,0.0693,0.012566,1.6034,0.001147,62.38314,1678.646067,0.9824 10/31/2016,42.724642,3.666618,61.583412,1.3142,1.44304,0.1943,0.0697,0.012538,1.6089,0.001149,59.809242,1678.509382,0.9801 11/1/2016,42.170436,3.30907896,60.988356,1.3068,1.44474,0.1931,0.0681,0.012547,1.5999,0.00114,58.701456,1683.41976,0.976 11/2/2016,40.255452,2.96002881,59.182302,1.3053,1.44864,0.1929,0.0674,0.012638,1.6061,0.00114,56.571702,1692.726093,0.9747 11/3/2016,38.803677,3.06953877,58.133922,1.3017,1.44559,0.1925,0.0679,0.012639,1.622,0.001138,55.790862,1695.72459,0.9715 11/4/2016,38.082426,2.85891888,57.436431,1.3033,1.45139,0.193,0.0685,0.012638,1.6308,0.001142,55.285986,1700.884698,0.9724 11/7/2016,38.745354,3.01835884,58.092149,1.2941,1.42861,0.1918,0.0696,0.012387,1.604,0.001134,56.021589,1658.570324,0.9684 11/8/2016,38.62923,2.98584105,57.95673,1.2885,1.42055,0.1911,0.0703,0.012251,1.5948,0.001141,55.76628,1643.71368,0.9696 11/10/2016,38.56436,2.72984705,58.66091,1.3135,1.43081,0.1932,0.0638,0.012296,1.6491,0.001126,56.230935,1653.9592,0.9752 11/11/2016,37.309184,2.68769214,57.513909,1.3249,1.43862,0.1945,0.0637,0.012422,1.6685,0.001138,54.532884,1626.500236,0.9786 11/14/2016,37.087272,2.94249516,57.338352,1.3236,1.42151,0.1933,0.064,0.012208,1.6535,0.001132,54.360252,1616.57886,0.976 11/15/2016,40.295534,3.29349184,60.602049,1.3229,1.41849,0.193,0.0653,0.012115,1.6479,0.001133,57.559379,1625.486917,0.9838 11/16/2016,40.464936,3.38517864,60.917976,1.3368,1.42914,0.1944,0.0661,0.012253,1.6634,0.001142,57.776496,1637.566632,0.994 11/17/2016,41.144952,3.15404135,61.312458,1.3499,1.43495,0.1947,0.0661,0.012257,1.6766,0.001144,59.841067,1642.045358,0.9979 11/18/2016,42.201576,3.51857003,62.280039,1.3631,1.44291,0.1972,0.0661,0.012287,1.683,0.001154,61.284976,1646.474859,1.0093 11/21/2016,44.777327,3.79881124,64.458177,1.3573,1.4426,0.1968,0.0664,0.012247,1.6957,0.00115,63.575932,1648.074379,1.0112 11/22/2016,43.94803,3.7066036,62.99713,1.351,1.43562,0.1967,0.0656,0.012156,1.6785,0.001155,62.99713,1637.84432,1.0052 11/23/2016,43.954086,3.70955695,63.182306,1.3541,1.42898,0.1955,0.0656,0.012035,1.6846,0.001146,62.843781,1609.104112,1.0039 11/25/2016,40.93824,3.666432,60.15744,1.344,1.42214,0.1945,0.065,0.011865,1.6772,0.00114,59.08224,1590.70464,0.9935 11/28/2016,42.012481,3.89527747,62.931836,1.3367,1.41854,0.1932,0.0648,0.011939,1.6595,0.001141,60.057931,1596.0198,0.9967 11/29/2016,39.391176,4.05630234,60.436326,1.3362,1.42303,0.194,0.0648,0.01189,1.6699,0.001144,57.563496,1587.819822,0.9949 11/30/2016,45.829512,4.4624185,66.956592,1.3543,1.4338,0.1958,0.0658,0.011832,1.6936,0.00115,63.706272,1588.86476,1.0081 12/1/2016,47.959772,4.60864277,68.864622,1.3487,1.43784,0.1965,0.0649,0.01182,1.6982,0.001155,65.088262,1580.258303,1.0124 12/2/2016,48.622456,4.56378306,69.261536,1.3402,1.43032,0.1949,0.065,0.011814,1.707,0.001148,65.777016,1577.991686,1.009 12/5/2016,48.633822,4.8205566,69.310557,1.3383,1.44058,0.195,0.065,0.011755,1.704,0.001147,66.433212,1566.319554,1.0083 12/7/2016,45.73503,5.0289822,66.517605,1.3365,1.4372,0.1946,0.0657,0.011749,1.6875,0.001154,63.51048,1569.02427,1.0098 12/8/2016,47.486056,4.90323006,68.120516,1.3399,1.42235,0.1951,0.066,0.011751,1.6862,0.001156,65.373721,1568.728122,1.0159 12/9/2016,48.524145,5.03389346,69.12845,1.3423,1.4178,0.194,0.0658,0.011642,1.6885,0.001149,66.779425,1556.880078,1.0186 12/12/2016,50.068773,4.7600688,70.480503,1.3341,1.41856,0.1932,0.066,0.011598,1.6911,0.001146,68.812878,1550.517702,1.0161 12/13/2016,50.109172,4.80410686,70.643532,1.3334,1.4168,0.1934,0.0657,0.011578,1.6877,0.001145,69.376802,1544.797236,1.0156 12/14/2016,48.124692,4.74846498,68.919312,1.3503,1.42258,0.1928,0.066,0.011536,1.6966,0.001145,67.771557,1543.325385,1.0164 12/15/2016,47.772365,4.82589228,69.17819,1.3591,1.41524,0.1957,0.0668,0.011501,1.6877,0.001149,67.479315,1533.74435,1.0192 12/16/2016,50.99525,4.7383828,71.0511,1.369,1.43042,0.1969,0.067,0.011609,1.7101,0.001154,70.7773,1553.65072,1.0266 12/19/2016,51.026976,4.86509634,71.956872,1.3806,1.43568,0.1979,0.0677,0.011788,1.7108,0.001162,71.597916,1571.412726,1.0295 12/20/2016,51.243,4.6284,71.946825,1.3775,1.43099,0.1988,0.0673,0.011688,1.7038,0.001155,72.387625,1559.812125,1.0305 12/21/2016,50.345504,4.80617192,70.862264,1.3816,1.44017,0.1985,0.0672,0.011755,1.7068,0.001157,71.483984,1563.432376,1.03 12/22/2016,51.12864,4.94257376,71.98192,1.3856,1.44616,0.199,0.0667,0.011788,1.7019,0.00115,72.12048,1563.483328,1.0277 12/23/2016,51.382032,5.00051552,72.495072,1.3936,1.45718,0.2008,0.0677,0.01188,1.7116,0.00116,73.470592,1579.36688,1.0294 12/27/2016,52.536675,5.1103224,75.01263,1.3917,1.45575,0.2,0.067,0.011852,1.7079,0.001153,74.59512,1584.840126,1.0254 12/28/2016,52.820003,5.10031398,75.321798,1.3933,1.45089,0.2004,0.0671,0.011882,1.7036,0.00115,74.903808,1590.688811,1.0276 12/29/2016,52.111224,5.09905972,74.482204,1.3852,1.45303,0.1997,0.0668,0.011885,1.6986,0.001148,74.066644,1604.324788,1.026 12/30/2016,52.242894,5.1131934,74.600964,1.3887,1.45969,0.1993,0.067,0.011871,1.7122,0.001149,74.045484,1593.53325,1.033 1/3/2017,50.736213,4.69576602,72.482283,1.3851,1.44129,0.1992,0.0656,0.011764,1.6952,0.001148,72.759303,1605.109284,1.0316 1/5/2017,52.818252,4.49132293,73.258752,1.3627,1.44544,0.1981,0.0636,0.01181,1.6923,0.001151,74.212642,1608.149524,1.0302 1/6/2017,54.177708,4.55742222,73.977098,1.3702,1.44223,0.1973,0.0646,0.01171,1.6824,0.001139,74.936238,1606.737626,1.0352 1/9/2017,51.821978,4.24230404,70.655208,1.3598,1.43802,0.1964,0.0636,0.011715,1.6542,0.00113,71.403098,1606.05978,1.029 1/11/2017,51.7363,4.40537954,70.21355,1.3438,1.42212,0.1959,0.0615,0.011644,1.6414,0.001131,71.15421,1601.298956,1.0197 1/12/2017,52.58496,4.4357872,70.82136,1.336,1.41813,0.1934,0.0613,0.011648,1.6252,0.001137,71.15536,1597.09448,1.0166 1/13/2017,51.817597,4.48068241,69.814447,1.3331,1.41798,0.1939,0.0621,0.011642,1.6241,0.001135,70.147722,1596.173954,1.0164 1/17/2017,52.17282,4.36848255,69.35232,1.3215,1.41583,0.1936,0.0614,0.011735,1.6407,0.001139,69.88092,1608.358005,1.0133 1/18/2017,50.484636,4.33443044,68.058992,1.3324,1.41631,0.1932,0.0607,0.011622,1.6337,0.001131,70.004296,1604.60932,1.0041 1/19/2017,50.479825,4.251573,67.936825,1.3225,1.4103,0.1929,0.0602,0.011514,1.6321,0.001125,69.788325,1593.414125,0.993 1/20/2017,51.779232,4.24465284,69.383112,1.3236,1.41663,0.1927,0.0613,0.011544,1.6375,0.001126,71.368512,1601.979552,0.9935 1/23/2017,51.4332,4.14947232,68.51166,1.3188,1.41943,0.1925,0.0617,0.011701,1.6528,0.001132,70.5558,1606.601724,0.9962 1/24/2017,52.004227,4.2851061,69.281817,1.3189,1.41588,0.192,0.0613,0.011591,1.6516,0.001128,71.062332,1594.470966,1.0024 1/25/2017,51.565525,4.29756725,68.996125,1.3205,1.41967,0.1924,0.0626,0.011658,1.6684,0.001136,70.580725,1585.511145,1.0102 1/26/2017,53.463644,4.53856962,71.382194,1.3273,1.41766,0.1927,0.0626,0.011588,1.6714,0.001132,72.244939,1577.49605,1.0136 1/27/2017,52.47669,4.3581348,70.423665,1.3245,1.41704,0.1922,0.0634,0.011509,1.6622,0.001123,71.28459,1577.7444,1.007 1/30/2017,51.862566,4.22975098,69.666331,1.3237,1.41561,0.1923,0.0637,0.011633,1.6527,0.001131,70.526736,1582.74809,1.009 1/31/2017,52.155904,3.96139648,69.624704,1.3184,1.42345,0.1912,0.0633,0.011689,1.6583,0.001145,70.217984,1596.213248,1.0119 2/1/2017,53.167039,4.11006391,71.030004,1.3183,1.41953,0.1923,0.0637,0.01164,1.6685,0.001143,71.557324,1594.932072,1.0102 2/2/2017,52.222941,4.04580879,69.917886,1.3059,1.40492,0.1891,0.0635,0.011577,1.6359,0.001141,70.505541,1587.922164,1.0025 2/3/2017,52.562646,3.90588102,70.070511,1.3017,1.40432,0.1894,0.0639,0.011559,1.6256,0.001143,70.851531,1588.46451,0.9992 2/6/2017,51.64558,3.8183264,69.204555,1.3055,1.40343,0.1908,0.0635,0.011683,1.6278,0.00115,70.05313,1612.984415,0.9977 2/8/2017,49.956339,3.98905095,68.465954,1.3081,1.39941,0.1905,0.0639,0.011687,1.6404,0.001142,68.923789,1624.045393,0.9952 2/10/2017,50.814426,3.81153786,70.158036,1.3026,1.38721,0.1896,0.064,0.011506,1.6267,0.001137,70.874466,1606.913412,0.9958 2/13/2017,50.431917,3.81138591,69.280077,1.3089,1.38739,0.1902,0.0645,0.011507,1.6395,0.001138,70.065417,1603.742814,1.0012 2/14/2017,50.634,3.8106,69.426,1.305,1.38024,0.1903,0.0644,0.011421,1.6269,0.001146,70.209,1602.70965,0.9983 2/15/2017,50.33657,3.7824411,68.88367,1.297,1.37482,0.1894,0.064,0.011362,1.616,0.001142,70.05097,1600.1089,0.9911 2/16/2017,51.39918,3.66201288,69.346656,1.2996,1.38746,0.1895,0.0638,0.011475,1.6234,0.001138,71.28306,1610.256384,0.9942 2/17/2017,51.89301,3.57863485,69.6603,1.3045,1.3849,0.1899,0.0639,0.01156,1.6183,0.001134,71.85186,1610.5357,0.9961 2/21/2017,52.155087,3.27835698,70.434774,1.3029,1.37286,0.1894,0.0651,0.011461,1.6252,0.001139,72.089457,1610.045646,0.9914 2/22/2017,51.071188,3.28496528,69.181078,1.2982,1.37064,0.1892,0.0652,0.011457,1.6162,0.001139,70.868738,1606.444608,0.986 2/23/2017,52.23283,3.3711561,70.11901,1.2961,1.37153,0.1888,0.0659,0.01151,1.6273,0.001144,71.998355,1619.554716,0.989 2/24/2017,52.509957,3.23674555,69.713517,1.3033,1.37604,0.1895,0.0655,0.011626,1.624,0.001153,71.733632,1638.495727,0.9955 2/27/2017,52.51896,3.17798352,70.43796,1.3032,1.37979,0.1893,0.0654,0.011564,1.6216,0.001148,71.54568,1632.557736,0.9888 2/28/2017,52.38366,3.28459,70.53706,1.306,1.38129,0.1893,0.0649,0.011582,1.6168,0.001149,71.58186,1630.46264,0.9819 3/1/2017,52.016811,3.38141839,70.124341,1.3027,1.37391,0.1898,0.0658,0.011454,1.6014,0.001143,70.645421,1627.971163,0.9777 3/2/2017,50.724246,3.41652426,69.476766,1.3206,1.38749,0.1916,0.066,0.011542,1.62,0.001148,70.137066,1629.95055,0.9862 3/3/2017,51.44882,3.29664765,70.208945,1.3165,1.39823,0.1916,0.0675,0.011545,1.6174,0.001143,70.93302,1625.627365,0.9841 3/7/2017,51.45472,3.50588,70.03852,1.318,1.3925,0.1909,0.0676,0.011563,1.6078,0.001145,71.09292,1602.50348,0.9827 3/8/2017,47.795832,3.57047352,66.791952,1.3284,1.40035,0.1918,0.0675,0.011614,1.6166,0.00115,67.721832,1605.119004,0.9846 3/10/2017,45.07074,3.9532038,64.29774,1.326,1.41523,0.1919,0.0676,0.011552,1.6132,0.001155,64.96074,1597.35264,0.9843 3/13/2017,44.70908,4.054856,63.92672,1.3208,1.40716,0.1906,0.0673,0.011497,1.6139,0.001151,64.7192,1590.63944,0.9823 3/14/2017,43.55316,4.0174218,63.13356,1.323,1.40278,0.1912,0.0673,0.01153,1.6077,0.001151,63.66276,1586.43576,0.9815 3/15/2017,44.308936,3.89713695,63.376306,1.2971,1.39243,0.1905,0.0675,0.011441,1.5945,0.001149,65.451666,1582.306348,0.975 3/16/2017,44.73744,3.737888,63.492,1.3024,1.40221,0.1891,0.0676,0.011495,1.6099,0.001154,66.68288,1597.536864,0.9779 3/17/2017,47.245616,3.724112,63.296928,1.2976,1.39371,0.1881,0.068,0.01152,1.6089,0.001146,68.526256,1595.087776,0.9718 3/20/2017,46.589738,3.77711972,62.387036,1.2938,1.38908,0.1874,0.0681,0.011495,1.5985,0.001161,65.867358,1596.859712,0.9689 3/21/2017,45.692542,3.97930809,61.556202,1.3003,1.40559,0.1882,0.0681,0.011639,1.6225,0.001158,65.587132,1618.626443,0.9739 3/22/2017,46.03035,3.882492,61.66035,1.3025,1.40624,0.1891,0.0685,0.011717,1.6261,0.001166,66.7401,1626.6141,0.9772 3/23/2017,45.75739,3.84584963,61.6217,1.3111,1.4137,0.1902,0.0693,0.01182,1.6416,0.001168,66.800545,1632.58172,0.982 3/24/2017,46.267186,3.909164,62.074376,1.3118,1.41675,0.1905,0.0699,0.011783,1.6366,0.001174,67.190396,1631.315126,0.9805 3/27/2017,46.377691,3.87325262,62.655171,1.3127,1.42626,0.1909,0.0695,0.011863,1.6487,0.001181,68.824861,1647.254722,0.9814 3/28/2017,47.248093,3.83957888,63.359863,1.3099,1.4166,0.19,0.0688,0.011787,1.6311,0.001173,69.254413,1639.759018,0.9788 3/29/2017,48.644778,4.054818,64.551138,1.3038,1.40366,0.1894,0.0697,0.011742,1.6212,0.001173,70.287858,1634.24811,0.9784 3/30/2017,50.842995,4.01954118,65.893045,1.3087,1.39711,0.1892,0.0699,0.011693,1.6319,0.00117,72.76372,1626.242968,0.9809 3/31/2017,51.38336,4.06321784,66.32648,1.3108,1.39637,0.1901,0.07,0.011767,1.6453,0.001173,72.68386,1637.45136,0.9844 4/4/2017,53.97726,4.059201,67.46166,1.322,1.41096,0.192,0.0702,0.011938,1.6444,0.001175,74.40216,1660.80216,0.9863 4/5/2017,54.635755,4.24480838,67.584495,1.3213,1.40866,0.1915,0.0702,0.011935,1.6491,0.001171,74.719515,1659.235688,0.9831 4/7/2017,56.918577,4.25869353,69.651592,1.3333,1.4127,0.1929,0.0714,0.012003,1.6494,0.001175,75.184787,1672.664849,0.9946 4/10/2017,58.629738,4.20366423,70.760948,1.3331,1.41273,0.1931,0.0714,0.012017,1.6551,0.001166,75.426798,1672.613908,1.0003 4/12/2017,58.772774,3.98035654,70.604434,1.3294,1.41761,0.1936,0.0717,0.012195,1.667,0.001171,74.127344,1710.645332,1.0032 4/13/2017,58.375034,3.95002635,70.266734,1.3213,1.40235,0.1913,0.071,0.012112,1.6519,0.001163,74.759154,1701.728696,0.9914 4/17/2017,57.51324,4.03396416,69.37164,1.3176,1.40246,0.1911,0.0712,0.012098,1.656,0.001163,73.85148,1692.733896,0.9894 4/18/2017,55.68567,4.04865243,69.322707,1.3227,1.41936,0.1925,0.0711,0.012199,1.6985,0.001158,73.872795,1705.965552,0.9885 4/19/2017,53.55207,4.16599092,67.276872,1.3338,1.42873,0.1935,0.0708,0.012254,1.7043,0.001166,70.6914,1707.544098,0.9892 4/20/2017,53.290146,4.12583444,66.788722,1.3286,1.42391,0.1926,0.0707,0.012153,1.7024,0.001167,70.163366,1703.13234,0.9864 4/21/2017,52.079874,4.0303218,65.341874,1.3262,1.42271,0.1929,0.0705,0.012154,1.6984,0.001168,68.193204,1703.424328,0.9823 4/24/2017,51.29443,3.9369763,64.57048,1.321,1.43556,0.1921,0.0705,0.012034,1.6903,0.001164,67.87298,1686.00551,0.9784 4/25/2017,52.504032,3.92559216,65.311512,1.3272,1.44988,0.1926,0.0704,0.011945,1.7042,0.001176,68.231352,1677.753336,0.9779 4/26/2017,53.27916,4.041429,66.39156,1.338,1.45875,0.1943,0.0698,0.012048,1.719,0.001181,68.73306,1698.21636,0.9824 4/27/2017,52.728241,4.11540104,65.585521,1.3393,1.45667,0.1946,0.0704,0.012039,1.7287,0.001184,67.795366,1693.27699,0.9824 4/28/2017,53.518824,4.22836098,65.870349,1.3353,1.45509,0.1941,0.071,0.011973,1.7295,0.001174,68.207124,1693.534284,0.978 5/1/2017,52.872952,4.21003704,64.898592,1.3288,1.44822,0.1925,0.0709,0.011882,1.7122,0.001168,66.227392,1669.743504,0.9714 5/4/2017,48.889756,4.14226624,61.442896,1.3498,1.48271,0.1962,0.0708,0.012002,1.7443,0.001189,62.117796,1657.770368,0.9817 5/5/2017,49.409158,4.149992,62.276828,1.3474,1.48171,0.1955,0.0709,0.011956,1.7489,0.001186,62.478938,1654.620674,0.9869 5/9/2017,48.71447,4.13011025,62.46562,1.3615,1.48061,0.1969,0.071,0.011945,1.7611,0.001196,62.05717,1662.704645,0.9924 5/10/2017,50.671742,4.22124252,64.245742,1.3574,1.47513,0.1962,0.0714,0.011877,1.7562,0.0012,64.110002,1654.80634,0.9939 5/12/2017,51.494748,4.39587001,64.761008,1.3537,1.48011,0.1959,0.072,0.011943,1.7453,0.0012,64.016473,1662.925691,0.9873 5/15/2017,52.809435,4.4068563,65.893765,1.3489,1.4805,0.1954,0.0721,0.011855,1.7397,0.001206,64.949535,1660.253098,0.9894 5/16/2017,52.123015,4.3459634,65.52069,1.3465,1.4924,0.1954,0.0722,0.011903,1.7395,0.001207,64.510815,1665.94366,0.9896 5/17/2017,52.693696,4.2547872,66.028592,1.3456,1.50148,0.1958,0.0716,0.012141,1.7452,0.001198,65.409616,1697.286016,0.9892 5/18/2017,53.049408,4.22157916,66.51393,1.3478,1.49651,0.1953,0.0715,0.012089,1.7441,0.001194,65.786118,1680.800946,0.9908 5/19/2017,54.140207,4.13957337,67.497563,1.3411,1.50183,0.1949,0.0716,0.012055,1.7467,0.001199,67.014767,1684.327723,0.9926 5/22/2017,54.610125,4.28976375,67.851375,1.3375,1.50295,0.1942,0.0717,0.012019,1.7388,0.001198,67.450125,1686.092625,0.9905 5/23/2017,55.324101,4.27909254,68.429641,1.3373,1.49552,0.1937,0.0718,0.011963,1.7332,0.001188,68.162181,1673.256506,0.9897 5/24/2017,55.049706,4.13825604,68.109186,1.3326,1.49507,0.1943,0.0722,0.011952,1.7287,0.001191,67.642776,1677.383598,0.994 5/25/2017,52.3146,4.10911062,65.25911,1.3414,1.50383,0.1951,0.0725,0.011994,1.7363,0.001197,65.92981,1684.355738,0.9948 5/26/2017,53.57772,4.16455992,66.87144,1.3428,1.50158,0.196,0.0725,0.012061,1.719,0.0012,66.87144,1701.005328,0.9986 5/30/2017,53.52642,4.0884219,66.51957,1.3395,1.49839,0.1955,0.0716,0.012085,1.7224,0.001191,66.92142,1691.909055,0.9952 5/31/2017,51.974796,4.0374,65.029056,1.3458,1.51324,0.1973,0.0723,0.012149,1.7346,0.001202,65.365506,1707.712536,0.9968 6/1/2017,51.67716,3.9770124,65.57616,1.356,1.52051,0.1988,0.0727,0.012175,1.7467,0.001209,65.30496,1716.64176,1.0032 6/2/2017,50.260335,3.84241,64.03121,1.3435,1.51529,0.1974,0.0719,0.012167,1.7313,0.001201,63.76251,1718.564895,0.9964 6/6/2017,50.277228,3.93824964,64.198718,1.3322,1.50224,0.1958,0.0731,0.012177,1.72,0.001191,63.466008,1724.386358,0.9903 6/7/2017,46.715115,3.96515565,60.55614,1.3245,1.49132,0.1948,0.0727,0.01206,1.7166,0.001178,60.225015,1704.830175,0.9803 6/9/2017,47.13518,3.9538817,60.885155,1.3285,1.48749,0.1952,0.0731,0.012042,1.6937,0.00118,61.018005,1682.89066,0.9864 6/12/2017,47.37798,4.08408,61.10208,1.326,1.48558,0.1952,0.0731,0.01206,1.6786,0.001172,61.69878,1678.95468,0.9952 6/13/2017,47.844408,3.99380068,61.643128,1.3268,1.48736,0.1951,0.0735,0.012055,1.6921,0.001177,62.306528,1680.45854,1.002 6/14/2017,45.167328,3.82156704,58.936248,1.3176,1.47886,0.1933,0.0735,0.012025,1.6811,0.001177,60.122088,1661.309136,0.9946 6/15/2017,45.20607,3.85518315,58.66497,1.3195,1.47053,0.1937,0.0731,0.011892,1.6834,0.001167,59.786545,1654.62661,0.9945 6/16/2017,45.527156,3.8965156,58.716776,1.3124,1.46932,0.1926,0.0733,0.011838,1.6773,0.001158,59.372976,1645.395252,0.9932 6/19/2017,43.86228,3.761786,58.1672,1.316,1.46671,0.1929,0.0733,0.011798,1.676,0.001158,58.93048,1636.89344,0.9957 6/20/2017,42.887192,3.7808272,57.029016,1.3192,1.46886,0.1933,0.0725,0.011838,1.666,0.001156,57.530312,1639.778792,0.9944 6/21/2017,42.272127,3.81442068,56.014209,1.3239,1.47869,0.1939,0.0726,0.011886,1.6774,0.001158,56.371662,1650.214872,0.993 6/22/2017,43.078491,3.77934536,56.403786,1.3259,1.4786,0.1939,0.0732,0.011909,1.6814,0.001164,56.536376,1658.051209,1.002 6/23/2017,43.232807,3.77992983,56.581977,1.3217,1.47887,0.1931,0.0734,0.011876,1.6807,0.001164,56.714147,1660.993607,0.9961 6/26/2017,43.678592,3.92500864,57.192192,1.3184,1.47418,0.1926,0.0738,0.011784,1.6774,0.001163,57.060352,1641.038848,0.9952 6/27/2017,44.822613,3.9284073,58.339288,1.3187,1.49534,0.1935,0.0733,0.011738,1.69,0.001156,58.339288,1644.643079,0.9992 6/28/2017,45.405741,3.965967,58.560186,1.3089,1.48929,0.193,0.0733,0.011657,1.6921,0.001149,58.625631,1635.169503,1.0039 6/29/2017,45.52647,3.91035675,58.476395,1.3015,1.48904,0.1919,0.0721,0.011603,1.693,0.001134,58.736695,1621.031265,1.001 6/30/2017,47.137368,3.82913073,59.884228,1.3007,1.48584,0.1922,0.0718,0.011572,1.6951,0.001135,60.274438,1614.962127,1.0033 7/3/2017,48.652258,3.77691382,61.445178,1.3054,1.48352,0.1922,0.0716,0.011513,1.6893,0.001135,61.902068,1592.84908,1.0036 7/6/2017,47.023761,3.79182629,60.009016,1.3183,1.50584,0.1939,0.0722,0.011645,1.71,0.001139,61.063656,1615.207526,1.016 7/7/2017,45.150816,3.79934976,58.171296,1.3152,1.50039,0.1934,0.0727,0.011547,1.6961,0.00114,59.289216,1594.627392,1.0215 7/11/2017,46.336127,3.91415235,58.970872,1.3093,1.50133,0.1932,0.0731,0.01149,1.682,0.001139,60.083777,1594.360796,1.0137 7/12/2017,47.003616,3.87581216,59.246176,1.3024,1.48629,0.192,0.0733,0.01151,1.678,0.001144,61.069536,1589.592224,1.0214 7/13/2017,47.783727,3.80251332,59.622912,1.2939,1.47419,0.1908,0.0732,0.011419,1.6737,0.001137,61.563762,1575.426762,1.0171 7/14/2017,47.750769,3.7406259,59.436234,1.2771,1.46463,0.1889,0.0727,0.011354,1.6728,0.001131,61.351884,1569.17277,1.0104 7/17/2017,47.082384,3.87275688,59.006844,1.2822,1.47133,0.189,0.0729,0.011385,1.6733,0.001136,61.186584,1582.375842,1.0099 7/18/2017,46.031008,3.89785624,58.61248,1.2632,1.45955,0.1871,0.0723,0.011272,1.6473,0.001123,61.378888,1569.488104,1.0004 7/19/2017,47.122272,3.90006912,59.258112,1.2576,1.44812,0.1864,0.0716,0.011233,1.6374,0.001118,62.590752,1560.996,0.9975 7/20/2017,46.582162,3.89784754,58.796314,1.2566,1.46154,0.1859,0.0719,0.01123,1.63,0.001121,61.724192,1563.826134,0.998 7/21/2017,45.381328,3.8236801,57.636308,1.2634,1.47327,0.1867,0.0716,0.011367,1.6418,0.001129,60.099938,1585.541732,1.0074 7/24/2017,45.98728,3.7372868,58.29178,1.262,1.4693,0.1869,0.0712,0.011359,1.6442,0.001131,60.62648,1584.1886,1.0087 7/25/2017,47.926596,3.73144583,60.185423,1.2599,1.46742,0.1864,0.0709,0.011261,1.641,0.001125,62.289456,1574.950594,1.0073 7/26/2017,48.46896,3.65278572,60.8985,1.2492,1.46584,0.187,0.071,0.011236,1.6391,0.001123,62.83476,1574.654076,1.0037 7/27/2017,49.061859,3.66802975,61.550104,1.2551,1.46557,0.186,0.0708,0.011282,1.6399,0.001123,63.495509,1580.359165,0.9998 7/28/2017,49.791448,3.65483755,62.251833,1.2523,1.47142,0.1858,0.0704,0.011315,1.6446,0.001113,64.192898,1589.970172,1.0073 7/31/2017,50.000988,3.54342334,62.682398,1.2494,1.47976,0.1863,0.0702,0.011333,1.6513,0.001116,64.556498,1586.038336,1.0013 8/2/2017,49.626654,3.47687802,62.240409,1.2551,1.48781,0.1864,0.0704,0.011333,1.6593,0.001118,63.495509,1589.772415,0.9985 8/3/2017,49.107546,3.49376976,61.689546,1.2582,1.4932,0.1874,0.0705,0.011434,1.6528,0.001114,63.325206,1596.15252,0.9997 8/8/2017,49.491295,3.50583345,62.126295,1.2635,1.48477,0.1887,0.0708,0.011453,1.6417,0.001119,63.20027,1593.22296,0.9975 8/9/2017,50.16208,3.6198864,62.84208,1.268,1.49083,0.1903,0.0707,0.011521,1.6486,0.001113,63.98328,1619.6164,0.9985 8/11/2017,49.109959,3.69192382,61.840294,1.2667,1.49785,0.1906,0.071,0.011603,1.6482,0.001108,63.233664,1633.168977,0.9992 8/14/2017,47.874624,3.7749504,60.610624,1.2736,1.50037,0.1906,0.0717,0.011618,1.6511,0.001118,61.756864,1632.94624,1.0011 8/15/2017,48.398795,3.74249916,60.802185,1.2787,1.50037,0.1913,0.0718,0.011553,1.6454,0.001125,61.63334,1625.905411,1.0024 8/16/2017,46.850634,3.64748526,59.027004,1.2618,1.48478,0.1896,0.0714,0.011451,1.6267,0.001111,59.910264,1619.028198,1 8/17/2017,47.925278,3.64632864,59.719538,1.2682,1.48658,0.1891,0.071,0.011574,1.6319,0.00111,60.543868,1633.63183,1 8/18/2017,48.754126,3.64003904,61.175961,1.2611,1.48313,0.1895,0.0712,0.011546,1.6218,0.001107,62.437061,1619.416343,1.002 8/21/2017,47.013402,3.74885598,59.657778,1.2594,1.48822,0.1889,0.0713,0.011556,1.6249,0.001106,60.677892,1626.993672,1.0029 8/22/2017,47.813337,3.80155842,60.212196,1.2639,1.48662,0.1895,0.0716,0.011535,1.6209,0.001117,61.337067,1624.212612,1.0063 8/23/2017,48.668397,3.69864636,61.053726,1.2651,1.49379,0.19,0.0715,0.011603,1.6194,0.001123,62.331477,1633.193496,1.0079 8/24/2017,47.83968,3.75263056,59.774288,1.2656,1.49247,0.1899,0.0714,0.011551,1.6192,0.001122,61.25504,1628.06784,1.0106 8/25/2017,48.17631,3.69439945,60.02501,1.2605,1.50371,0.1897,0.0716,0.011525,1.6244,0.001124,61.726685,1627.746675,1.0098 8/28/2017,45.732594,3.67329921,58.477949,1.2557,1.5043,0.1899,0.0703,0.011493,1.6239,0.001123,59.733649,1645.130241,1.0041 8/29/2017,44.5658,3.627636,58.3983,1.2575,1.50574,0.1903,0.0705,0.011458,1.6248,0.001118,59.6558,1646.356725,1.0052 8/30/2017,43.27565,3.626249,58.1394,1.265,1.50328,0.1921,0.0714,0.01148,1.635,0.001125,60.1634,1655.379,1.0028 8/31/2017,45.284428,3.64289184,59.443678,1.2586,1.49865,0.1915,0.0704,0.011444,1.6271,0.001119,61.331578,1663.151798,1.0082 9/1/2017,43.030521,3.64372764,59.344221,1.2549,1.48671,0.1912,0.0704,0.01138,1.623,0.001118,61.352061,1663.031127,1.0124 9/5/2017,44.658926,3.58146828,60.854196,1.2506,1.49001,0.1908,0.0699,0.011494,1.6299,0.001104,62.980216,1675.441326,1.0107 9/6/2017,47.383709,3.66270696,61.445084,1.2499,1.48958,0.1917,0.0703,0.011443,1.6305,0.001104,64.507339,1667.641578,1.0224 9/8/2017,44.96143,3.5069419,58.92268,1.241,1.4932,0.1909,0.0701,0.011507,1.6373,0.001097,62.02518,1671.11819,1.0208 9/11/2017,45.36111,3.5459385,59.871185,1.2455,1.48874,0.1908,0.0705,0.011384,1.6396,0.001102,63.607685,1653.45107,1.0286 9/13/2017,46.390305,3.74089917,61.72853,1.2521,1.48851,0.1915,0.0705,0.011334,1.6544,0.001106,66.73693,1655.739477,1.0287 9/14/2017,47.019888,3.79282104,62.322588,1.2492,1.48892,0.1912,0.0707,0.011332,1.6738,0.001101,67.319388,1661.111208,1.027 9/15/2017,47.038708,3.73122929,62.347533,1.2497,1.49263,0.1907,0.0708,0.011276,1.6987,0.001103,67.408818,1649.828946,1.0248 9/18/2017,48.17527,3.89823984,62.696942,1.2562,1.50257,0.1907,0.0707,0.011259,1.6961,0.001112,64.19182,1642.406128,1.0219 9/19/2017,47.32194,3.91635876,61.780728,1.2486,1.49732,0.1898,0.0702,0.011189,1.6852,0.001104,63.24159,1637.10189,1.0157 9/20/2017,48.670959,3.91023655,62.765491,1.2451,1.48086,0.1886,0.0701,0.011097,1.6802,0.0011,63.861179,1619.99961,1.0103 9/21/2017,49.24986,3.91653048,63.31224,1.2612,1.50598,0.1912,0.0705,0.011207,1.7123,0.001113,64.82568,1628.46144,1.0226 9/22/2017,49.12216,3.6986688,63.18936,1.256,1.50165,0.1903,0.0708,0.011215,1.6967,0.001108,65.26176,1629.4088,1.0179 9/25/2017,51.5592,3.736656,65.4192,1.26,1.49284,0.1899,0.0703,0.011277,1.6966,0.00111,68.0652,1651.5828,1.0185 9/26/2017,51.451382,3.74106574,65.778652,1.2679,1.49546,0.1911,0.0706,0.011297,1.7067,0.001114,68.060872,1640.637242,1.0269 9/27/2017,52.034244,3.76330917,66.431574,1.2741,1.4963,0.1913,0.07,0.011292,1.7054,0.001112,68.533839,1634.389998,1.0211 9/28/2017,51.238902,3.71908394,65.620412,1.2727,1.50038,0.1916,0.0701,0.011329,1.7112,0.00111,67.656732,1638.34671,1.0241 9/29/2017,51.59613,3.68410665,65.956755,1.2765,1.50823,0.1916,0.0699,0.011346,1.7106,0.001115,68.382105,1633.600875,1.0236 10/2/2017,50.184128,3.58443456,64.621008,1.2776,1.49908,0.1921,0.0701,0.011329,1.6961,0.001114,68.453808,1623.995688,1.0213 10/3/2017,50.311746,3.47778987,64.351046,1.2763,1.4987,0.1919,0.0701,0.011309,1.6896,0.001116,69.583876,1623.019658,1.0221 10/4/2017,49.316526,3.57691059,63.559566,1.2717,1.49517,0.1914,0.0696,0.011278,1.6844,0.001113,68.264856,1621.226745,1.0192 10/5/2017,50.725866,3.73041662,65.158491,1.2829,1.50234,0.1927,0.0694,0.011371,1.683,0.001123,70.418381,1626.999438,1.0211 10/10/2017,51.132289,3.72660145,65.467844,1.2857,1.51819,0.1953,0.0683,0.011434,1.6975,0.001132,72.089199,1656.020171,1.0273 10/11/2017,51.5526,3.7583964,65.8692,1.284,1.52258,0.1951,0.0686,0.011413,1.6978,0.001133,72.4818,1658.56848,1.0306 10/13/2017,50.83477,3.81907302,65.223165,1.2677,1.49905,0.1928,0.067,0.011336,1.6846,0.001125,71.87859,1652.852614,1.0168 10/16/2017,51.869136,3.65860836,66.072006,1.2738,1.50266,0.193,0.0669,0.011353,1.6882,0.001129,72.186246,1650.577302,1.0175 10/17/2017,52.683351,3.68362806,66.131436,1.2747,1.49971,0.1928,0.0679,0.01136,1.6811,0.001127,71.676381,1638.142464,1.018 10/18/2017,51.18392,3.58657045,66.32498,1.2745,1.50227,0.1927,0.0676,0.011285,1.683,0.001125,69.15437,1632.73646,1.0224 10/19/2017,50.146092,3.56937116,65.097268,1.2692,1.50448,0.1919,0.0675,0.011278,1.6701,0.001124,68.168732,1637.432996,1.0166 10/20/2017,50.967312,3.53841587,65.845571,1.2793,1.5078,0.1932,0.0674,0.011269,1.6872,0.00113,69.133372,1638.105271,1.0133 10/23/2017,50.4714,3.7634499,66.25332,1.281,1.50497,0.1931,0.0671,0.011293,1.6906,0.001133,69.4302,1642.58787,1.0129 10/24/2017,50.95132,3.7605212,67.24494,1.286,1.51242,0.1938,0.0669,0.011289,1.689,0.001137,70.43422,1641.68188,1.0146 10/25/2017,51.248988,3.80849559,67.345428,1.2981,1.53347,0.1956,0.0682,0.011413,1.7212,0.001151,70.915203,1658.361693,1.0144 10/26/2017,52.2522,3.765969,68.6952,1.305,1.52099,0.196,0.068,0.011452,1.718,0.001156,71.63145,1653.42195,1.0162 10/27/2017,53.3984,3.62353728,70.19936,1.3024,1.51209,0.1962,0.0681,0.011458,1.71,0.001157,73.45536,1658.41104,1.0169 10/30/2017,53.58884,3.73378942,70.432905,1.3007,1.51539,0.1963,0.0676,0.011493,1.7179,0.001156,73.034305,1660.070403,1.0135 10/31/2017,53.854626,3.65736,71.031156,1.3062,1.5211,0.1969,0.0682,0.011494,1.7349,0.001168,74.296656,1660.76799,1.0135 11/1/2017,52.30742,3.44434264,70.74204,1.3028,1.51376,0.1972,0.0683,0.01141,1.7256,0.001172,73.47792,1660.627048,1.0126 11/7/2017,57.0288,4.0248468,74.8176,1.308,1.51552,0.1973,0.0683,0.011475,1.7222,0.001174,77.6298,1668.0924,1.0237 11/8/2017,55.690624,4.10490432,73.989344,1.3024,1.51015,0.1966,0.0682,0.011441,1.7083,0.001169,76.789504,1668.843264,1.0235 11/9/2017,56.016342,4.14393325,74.441057,1.3021,1.51586,0.1966,0.0684,0.011476,1.7116,0.001165,77.240572,1673.289647,1.0266 11/10/2017,55.270636,4.10469976,74.068396,1.3054,1.52279,0.1961,0.0683,0.011499,1.723,0.001164,77.658246,1664.476378,1.0291 11/13/2017,56.022707,4.09027411,74.452092,1.3117,1.53061,0.1971,0.0686,0.011544,1.7206,0.001172,78.124852,1676.759227,1.0302 11/14/2017,54.442965,4.04004799,72.98371,1.3103,1.54604,0.1978,0.0684,0.011549,1.7253,0.001174,76.65255,1677.511575,1.0292 11/15/2017,54.258768,4.10287464,72.902808,1.3176,1.55376,0.199,0.0685,0.011674,1.7358,0.001192,76.328568,1684.077264,1.0324 11/16/2017,53.954826,4.02433944,72.669006,1.3179,1.55128,0.1986,0.0692,0.011658,1.7389,0.001199,76.227336,1685.040582,1.0331 11/17/2017,54.277214,4.03496756,74.753445,1.3219,1.55896,0.2,0.0699,0.01179,1.7472,0.001207,77.410464,1708.449998,1.0355 11/20/2017,53.867415,4.04012235,74.291205,1.3245,1.55397,0.1996,0.0697,0.011761,1.753,0.001206,77.90709,1691.28054,1.0332 11/21/2017,53.549368,4.0208212,74.847712,1.3196,1.54892,0.199,0.0703,0.011736,1.7472,0.001209,78.093928,1689.892956,1.0327 11/22/2017,53.506548,3.84100108,76.079828,1.3124,1.55205,0.1993,0.0704,0.011805,1.7496,0.001209,78.901488,1695.778288,1.034 11/27/2017,54.076094,3.70495564,76.437894,1.3154,1.56515,0.1991,0.0708,0.011839,1.7521,0.001205,78.739844,1702.811608,1.0302 11/28/2017,54.362414,3.8299894,76.349634,1.3166,1.55892,0.199,0.071,0.01181,1.7561,0.001215,78.192874,1703.654068,1.0274 11/29/2017,52.902045,4.081581,75.68757,1.3209,1.56518,0.1997,0.0711,0.011801,1.7714,0.001221,77.66892,1695.560076,1.0268 11/30/2017,53.26451,3.88804489,75.86558,1.3217,1.57328,0.1994,0.0709,0.011744,1.7874,0.001215,78.11247,1685.180717,1.0249 12/1/2017,54.133456,3.73114944,76.661696,1.3136,1.56243,0.199,0.0705,0.011703,1.7692,0.001213,78.763456,1682.222432,1.0356 12/4/2017,52.604517,3.81813771,75.636267,1.3161,1.56162,0.1989,0.0707,0.011708,1.7741,0.001211,77.281392,1679.580498,1.0386 12/5/2017,52.934915,3.7626248,75.74149,1.3145,1.55459,0.1983,0.07,0.011675,1.7672,0.001209,77.384615,1663.854665,1.036 12/6/2017,49.525866,3.85802001,73.984716,1.3221,1.55952,0.1998,0.0701,0.011774,1.7704,0.001209,74.183031,1670.301477,1.0338 12/7/2017,49.710742,3.73216642,75.471397,1.3313,1.56738,0.2009,0.0702,0.011772,1.794,0.001218,74.805747,1660.423986,1.0357 12/12/2017,40.533656,3.71245427,75.590506,1.3229,1.55357,0.2,0.069,0.011651,1.762,0.001211,71.621806,1646.335821,1.0284 12/13/2017,39.08559,3.5000262,74.11204,1.3094,1.54851,0.1986,0.0689,0.011635,1.7572,0.001207,70.0529,1643.9517,1.0217 12/14/2017,41.792976,3.47726952,74.402976,1.3044,1.5364,0.1976,0.0682,0.011606,1.7519,0.001198,70.554996,1634.361024,1.0194 12/15/2017,40.982773,3.42748362,74.95413,1.3081,1.53661,0.1974,0.0684,0.011615,1.7422,0.001201,71.199883,1643.549164,1.0168 12/18/2017,42.68324,3.53141195,74.56522,1.3045,1.53741,0.1971,0.0684,0.011591,1.7464,0.001201,71.38224,1646.61817,1.0142 12/19/2017,41.1858,3.576483,74.9853,1.305,1.54505,0.1978,0.0679,0.01156,1.7468,0.001202,70.87455,1646.5185,1.0133 12/20/2017,40.746332,3.5176971,75.675486,1.3043,1.54844,0.1984,0.0679,0.011503,1.7447,0.001207,71.201737,1650.682951,1.0162 12/21/2017,41.042424,3.37856664,75.735672,1.2984,1.54159,0.1975,0.0667,0.011458,1.7379,0.001202,71.230224,1644.55344,1.0193 12/22/2017,41.452302,3.38658954,75.747372,1.2966,1.53922,0.1971,0.0656,0.011449,1.7333,0.001204,71.274102,1652.075856,1.019 12/26/2017,43.306833,3.49055403,77.595183,1.2939,1.53463,0.1978,0.0651,0.011427,1.7308,0.001202,73.066533,1660.20309,1.02 12/27/2017,42.657808,3.54533496,76.768608,1.2872,1.53044,0.1962,0.0654,0.011355,1.7249,0.001197,72.263408,1656.858096,1.0171 12/28/2017,42.768552,3.8028606,76.762752,1.2828,1.53234,0.1965,0.0651,0.011366,1.7249,0.001199,72.272952,1661.277312,1.021 12/29/2017,44.09202,4.5342276,77.39802,1.281,1.53722,0.1968,0.0652,0.011367,1.7302,0.0012,72.91452,1668.8868,1.0186 1/2/2018,45.178101,9.11302458,77.110601,1.2773,1.54006,0.1969,0.0654,0.011374,1.7356,0.001201,74.236676,1682.919388,1.0209 1/3/2018,48.154799,8.67884,78.658369,1.2763,1.53346,0.1965,0.066,0.011343,1.7249,0.001199,74.829469,1676.049923,1.0182 1/5/2018,46.344392,3.72624682,78.139392,1.2718,1.52973,0.1963,0.0663,0.011251,1.7257,0.001197,73.179372,1678.254562,1.0246 1/8/2018,46.395414,3.685617,78.724269,1.2753,1.52606,0.1964,0.0663,0.011276,1.7304,0.001193,73.686834,1683.90612,1.0267 1/16/2018,53.677426,6.858852,80.057626,1.2562,1.54015,0.1953,0.0669,0.011373,1.7326,0.00118,75.974976,1681.310642,1.0103 1/17/2018,50.397282,4.918032,80.256762,1.2546,1.52897,0.1949,0.067,0.011275,1.7354,0.001175,77.998482,1664.653464,1.0087 1/18/2018,49.3625,4.425,79.9375,1.25,1.5295,0.1948,0.0672,0.01125,1.7363,0.001167,77.675,1658.7875,1.0068 1/19/2018,45.740216,4.00352,79.282207,1.2511,1.52842,0.1949,0.0671,0.01129,1.7328,0.001172,77.330491,1666.265024,1.0012 1/22/2018,46.241118,3.916836,79.197426,1.2474,1.52951,0.1947,0.0668,0.011246,1.7448,0.001167,76.802418,1663.931808,1.0024 1/23/2018,46.0125,4.1875,80.65,1.25,1.53724,0.1953,0.0669,0.011332,1.7499,0.001164,77.2625,1676.5125,1.0064 1/24/2018,46.318928,4.388892,81.467258,1.2398,1.53934,0.1947,0.067,0.011356,1.7665,0.001165,78.243778,1684.218708,1.0044 1/25/2018,46.56302,4.52298,81.75006,1.246,1.54484,0.1954,0.067,0.011389,1.7621,0.001168,78.64752,1679.93196,1.0068 1/26/2018,47.515966,4.413782,81.544006,1.2329,1.53246,0.1954,0.0667,0.011356,1.7461,0.001158,79.263141,1663.330048,1.0011 1/29/2018,46.401624,4.435086,80.992824,1.2354,1.52977,0.1948,0.0664,0.011339,1.7388,0.001154,78.830874,1655.843682,1.0011 1/30/2018,44.65209,4.465209,79.78005,1.2369,1.53454,0.1955,0.0659,0.011373,1.7504,0.001153,77.615475,1655.701971,1.0027 1/31/2018,44.351649,4.145942,80.349349,1.2413,1.54103,0.1961,0.0667,0.01137,1.7619,0.00116,78.177074,1669.722282,1.008 2/1/2018,43.971865,3.806334,81.84862,1.2439,1.55609,0.1982,0.0678,0.01137,1.7744,0.001162,78.73887,1677.759881,1.014 2/2/2018,44.04031,3.571177,82.591355,1.2619,1.57172,0.2,0.0679,0.011455,1.7801,0.001157,80.067555,1682.604841,1.0155 2/5/2018,42.585015,3.617505,81.425595,1.2693,1.56991,0.2002,0.0676,0.011633,1.7719,0.001159,79.07739,1700.443131,1.0123 2/7/2018,42.238336,3.490032,78.992336,1.2784,1.56778,0.2024,0.0681,0.011692,1.7744,0.001173,78.864496,1685.429776,1.0172 2/8/2018,45.171265,3.495472,78.583865,1.2851,1.57402,0.2027,0.068,0.011819,1.7882,0.001171,77.62004,1694.738476,1.0198 2/13/2018,48.720196,3.295516,75.313356,1.2724,1.57149,0.2008,0.0682,0.011801,1.7677,0.001172,75.249736,1691.71942,1.0105 2/14/2018,44.172117,3.192101,76.45902,1.2617,1.57077,0.2009,0.0679,0.01179,1.7663,0.001178,77.291742,1704.216041,1.01 2/15/2018,43.635662,3.171672,77.202524,1.2586,1.57424,0.1991,0.068,0.011858,1.7747,0.001183,77.932512,1703.729062,1.0085 2/16/2018,44.32423,3.199438,78.000528,1.2646,1.56924,0.199,0.0683,0.011905,1.774,0.001185,78.78458,1703.365616,1.0079 2/20/2018,42.859236,3.335892,78.51396,1.2684,1.56503,0.1997,0.0678,0.011818,1.7754,0.001179,79.008636,1685.944596,1.0029 2/21/2018,42.577599,3.421071,78.966519,1.2813,1.574,0.201,0.068,0.011889,1.7835,0.001191,79.991559,1697.248419,1.0087 2/22/2018,43.361892,3.364944,79.942912,1.2746,1.57158,0.2004,0.0685,0.01194,1.7788,0.001179,81.090052,1697.83093,1.0033 2/23/2018,45.97817,3.290532,80.962392,1.2754,1.56746,0.2019,0.0688,0.011933,1.7813,0.001185,81.81691,1694.636734,1.0096 2/26/2018,47.375772,3.31032,81.370212,1.2732,1.56807,0.2021,0.0682,0.011906,1.7782,0.001189,82.325112,1698.041376,1.0038 2/27/2018,48.283718,3.325042,80.892238,1.2838,1.57048,0.2023,0.0681,0.011961,1.7855,0.001187,82.176038,1692.510568,1.0049 2/28/2018,46.884876,3.427144,79.416976,1.2884,1.57093,0.2026,0.0684,0.012077,1.7728,0.001187,80.705376,1698.510604,1.0041 3/1/2018,46.792326,3.442698,78.640506,1.2894,1.58153,0.2032,0.0684,0.012137,1.776,0.001191,80.639076,1698.178482,1.0045 3/5/2018,47.738746,3.47706,80.577646,1.2878,1.58852,0.2034,0.0685,0.012125,1.7835,0.001194,83.603976,1700.037658,0.9934 3/7/2018,43.640285,3.57812,78.143585,1.2779,1.58609,0.2024,0.0683,0.012048,1.7758,0.001198,84.21361,1693.945903,0.9898 3/8/2018,43.502628,3.570632,77.218128,1.2844,1.58056,0.2023,0.0688,0.012091,1.7729,0.001196,82.869488,1697.963956,0.9959 3/9/2018,46.562922,3.453353,79.057572,1.2743,1.56913,0.2014,0.0684,0.01193,1.7656,0.001196,82.880472,1687.083999,0.9947 3/13/2018,44.797683,3.536994,77.241333,1.2723,1.57636,0.2006,0.0684,0.011938,1.7764,0.001193,81.058233,1687.718673,0.9814 3/14/2018,44.695574,3.414686,77.382624,1.2694,1.57004,0.2011,0.0683,0.011939,1.7724,0.001193,78.652024,1681.76459,0.9799 3/15/2018,44.486456,3.46248,78.470056,1.2824,1.57785,0.2021,0.0686,0.012059,1.7871,0.001199,79.752456,1687.76664,0.9824 3/16/2018,48.174224,3.396568,80.817576,1.2964,1.59302,0.2042,0.0694,0.012231,1.807,0.001211,82.852924,1703.780736,0.9899 3/19/2018,48.753428,3.472208,80.404936,1.2956,1.59825,0.205,0.0693,0.012212,1.8171,0.001207,82.633368,1706.11086,0.9908 3/20/2018,50.489064,3.527336,82.52144,1.3016,1.59329,0.2051,0.0693,0.012217,1.8218,0.001214,84.786224,1706.801096,0.9957 3/21/2018,52.374826,3.42335874,83.861536,1.2878,1.58886,0.2052,0.0698,0.012143,1.821,0.00121,86.823476,1715.658672,0.998 3/22/2018,53.03592,3.4031382,83.45358,1.2999,1.59912,0.2049,0.0697,0.012347,1.8322,0.001202,86.508345,1727.606097,1.0047 3/23/2018,55.055858,3.351678,85.519753,1.2991,1.60466,0.2048,0.0701,0.012403,1.8358,0.001199,88.182908,1750.316403,1.0074 3/26/2018,53.628585,3.317099,84.605385,1.2907,1.60619,0.2064,0.0704,0.012245,1.8366,0.0012,86.86411,1746.96245,1.0051 3/27/2018,55.53883,3.3883244,84.96855,1.3022,1.61516,0.2065,0.0708,0.012363,1.8436,0.001211,86.92185,1751.52411,1.0106 3/28/2018,55.310138,3.445464,84.022338,1.3051,1.60656,0.2068,0.0713,0.012216,1.8375,0.001226,85.327438,1729.270551,1.0101 3/29/2018,55.912174,3.658901,84.558374,1.3021,1.60211,0.2073,0.0716,0.012239,1.8258,0.001226,85.860474,1725.93355,1.0109 4/4/2018,60.67872,3.591216,82.12752,1.296,1.59119,0.206,0.0716,0.012138,1.8247,0.001225,80.18352,1727.81424,1.0149 4/5/2018,60.562502,3.552549,82.684602,1.3013,1.59295,0.2065,0.0715,0.012118,1.8224,0.001225,80.407327,1726.265541,1.0206 4/6/2018,58.71318,3.5564082,80.86418,1.303,1.5983,0.2064,0.0712,0.012187,1.8335,0.001217,78.45363,1736.93809,1.0182 4/9/2018,61.27383,3.5244468,82.38258,1.299,1.60063,0.2059,0.0708,0.012165,1.8358,0.001214,78.61548,1735.91865,1.0231 4/13/2018,67.483559,3.632442,86.805059,1.2881,1.58785,0.2051,0.0714,0.011996,1.8334,0.001201,84.100049,1734.04022,1.0214 4/16/2018,65.792,3.6256275,85.0927,1.285,1.59106,0.205,0.0714,0.011998,1.8428,0.0012,82.6255,1729.52005,1.0228 4/17/2018,64.259125,3.6629375,85.6445,1.2875,1.59293,0.2049,0.0713,0.012031,1.8399,0.001206,83.056625,1734.932,1.0257 4/18/2018,65.802334,3.65278751,87.963409,1.2847,1.58966,0.2047,0.071,0.01198,1.8246,0.001206,85.265539,1733.587027,1.0173 4/19/2018,66.087304,3.58356724,88.353602,1.2938,1.59709,0.205,0.0701,0.01205,1.8224,0.001212,85.688374,1740.846714,1.021 4/20/2018,66.68937,3.624564,89.153844,1.3038,1.60152,0.2069,0.0703,0.012109,1.8248,0.001217,86.44194,1742.346168,1.0212 4/23/2018,67.7751,3.6021795,90.19585,1.315,1.60548,0.2079,0.0694,0.012097,1.8332,0.001216,87.6316,1742.15145,1.0235 4/24/2018,66.54406,3.64598324,88.966515,1.3151,1.60881,0.2086,0.0699,0.012086,1.8384,0.001221,86.40207,1749.543285,1.0248 4/25/2018,67.3559,3.689041,89.9621,1.322,1.60757,0.2089,0.0701,0.012081,1.8415,0.001222,85.9961,1749.17786,1.029 4/26/2018,67.235802,3.71365614,90.269922,1.3238,1.60221,0.2089,0.0704,0.012111,1.8425,0.001228,85.967572,1743.17984,1.0285 4/27/2018,66.61455,3.719862,89.83071,1.3191,1.60021,0.2087,0.0709,0.012095,1.8179,0.001235,85.21386,1746.4884,1.0282 4/30/2018,69.021357,3.652275,91.067817,1.3281,1.60382,0.2094,0.071,0.012147,1.8275,0.001241,89.274882,1746.969459,1.0341 5/1/2018,69.954,3.6700485,89.77875,1.335,1.60113,0.2109,0.0704,0.012152,1.8177,0.001244,87.10875,1740.63975,1.0389 5/2/2018,70.311996,3.64746816,90.666171,1.3347,1.59487,0.2094,0.0699,0.012152,1.8117,0.001236,85.327371,1741.730112,1.0359 5/3/2018,69.738828,3.57243884,90.847668,1.3276,1.59174,0.2096,0.0697,0.012159,1.8023,0.001234,85.670028,1741.890856,1.0335 5/4/2018,71.12693,3.647875,92.48358,1.3265,1.58669,0.209,0.0688,0.012158,1.7949,0.001235,87.57553,1743.68425,1.0327 5/7/2018,73.01784,3.60578805,94.106265,1.3305,1.58595,0.2088,0.0684,0.012195,1.8034,0.001231,89.848665,1748.556405,1.0329 5/9/2018,74.652445,3.64977935,95.36317,1.3405,1.58811,0.2107,0.0685,0.012211,1.8154,0.001242,91.47572,1759.70116,1.0427 5/14/2018,74.027448,3.747216,94.291648,1.3288,1.58465,0.2091,0.0677,0.012116,1.8011,0.001241,90.504568,1745.3788,1.037 5/15/2018,77.367123,3.814155,95.434173,1.3383,1.58431,0.2098,0.0679,0.012129,1.8071,0.001238,92.891403,1727.116299,1.0394 5/16/2018,77.155695,3.6937341,95.117445,1.3305,1.57106,0.2092,0.068,0.012054,1.7944,0.001235,92.589495,1717.316265,1.0405 5/17/2018,72.643584,3.6608,95.167488,1.3312,1.57023,0.209,0.0675,0.012019,1.7994,0.00123,92.744704,1718.299648,1.0395 5/18/2018,71.871849,3.702126,94.923576,1.3317,1.56725,0.2087,0.0667,0.012021,1.7931,0.001232,92.380029,1721.941368,1.0335 5/21/2018,73.00665,3.6511239,95.28456,1.319,1.55526,0.2072,0.0665,0.011877,1.7707,0.001224,92.79165,1704.9394,1.0314 5/22/2018,71.868555,3.67275374,95.204387,1.3199,1.55485,0.207,0.0668,0.011902,1.7731,0.001226,92.327005,1704.175686,1.0298 5/23/2018,72.547836,3.78150965,95.023907,1.3229,1.54707,0.2075,0.0674,0.012018,1.7655,0.001228,92.391336,1711.052089,1.0307 5/24/2018,70.5144,3.786156,93.2976,1.32,1.54697,0.2072,0.0674,0.01208,1.7659,0.00122,90.6444,1722.1116,1.0246 5/25/2018,67.079687,3.84221,89.973959,1.3249,1.54367,0.2071,0.0678,0.012112,1.7631,0.001228,87.284412,1725.351025,1.0211 5/29/2018,62.924529,3.76214874,88.904379,1.3323,1.53754,0.2073,0.0672,0.01225,1.7648,0.001229,84.907479,1730.351271,1.0232 5/30/2018,56.698608,3.7337142,90.023558,1.3198,1.53999,0.2061,0.0669,0.012119,1.7542,0.001225,85.074308,1717.561324,1.0255 5/31/2018,55.551656,3.81527822,88.586656,1.3214,1.54498,0.2063,0.0664,0.012143,1.7571,0.001223,84.292106,1715.851114,1.0198 6/4/2018,66.637505,3.79526422,84.686525,1.3079,1.52962,0.2042,0.0651,0.011907,1.7406,0.001221,79.65111,1689.832958,1.0113 6/6/2018,64.531816,3.70510178,84.420866,1.3042,1.53555,0.2041,0.0642,0.011837,1.7493,0.001222,79.986586,1690.76488,1.0076 6/7/2018,65.18652,3.8442996,86.50002,1.3116,1.54783,0.2048,0.064,0.011957,1.7609,0.001223,82.04058,1701.381288,1.0112 6/8/2018,63.074658,3.841844,86.494118,1.3157,1.54822,0.2054,0.0648,0.012014,1.7627,0.001225,81.954953,1708.002269,1.0179 6/13/2018,63.525544,3.88133948,87.938144,1.3196,1.55598,0.2057,0.0639,0.011958,1.765,0.001215,83.187584,1714.569476,1.0161 6/14/2018,64.702269,3.95166534,89.438619,1.3371,1.54694,0.2074,0.064,0.012086,1.7734,0.001228,83.421669,1741.238475,1.0201 6/15/2018,62.907959,4.058578,87.434134,1.3439,1.56005,0.2084,0.0651,0.012144,1.7841,0.001218,82.394509,1718.767466,1.0187 6/18/2018,56.82993,4.0008594,88.69995,1.347,1.5657,0.2092,0.0657,0.012184,1.784,0.001221,83.09643,1721.89704,1.0204 6/19/2018,56.08872,3.92892,88.156836,1.3548,1.57016,0.2091,0.066,0.012308,1.7852,0.001218,82.50732,1726.909368,1.0195 6/20/2018,56.612983,4.00118467,89.880406,1.3573,1.57063,0.2095,0.0667,0.012299,1.7879,0.001222,85.116283,1720.866378,1.0198 6/21/2018,55.393902,4.06411746,89.259288,1.3557,1.57268,0.2089,0.0667,0.012322,1.7943,0.00122,83.863602,1717.929483,1.0181 6/22/2018,58.634357,3.95214112,92.702222,1.3439,1.5661,0.207,0.0672,0.012222,1.7826,0.001209,85.982722,1707.505584,1.0129 6/25/2018,59.787871,3.9503423,96.539946,1.3487,1.57856,0.2064,0.0678,0.012287,1.7913,0.001209,86.896741,1706.968668,1.0144 6/26/2018,67.680584,3.96383928,95.412984,1.3528,1.57535,0.2055,0.0678,0.012293,1.789,0.001209,91.692784,1703.229312,1.0165 6/27/2018,71.880224,4.08052424,99.128224,1.3624,1.57395,0.2053,0.0675,0.012355,1.7864,0.001213,96.062824,1706.20164,1.0212 6/28/2018,70.32234,4.03489728,99.90669,1.3602,1.57357,0.2052,0.069,0.012311,1.7788,0.001213,96.84624,1697.86965,1.0268 6/29/2018,71.768445,4.010391,100.124745,1.3503,1.57865,0.2042,0.0678,0.012193,1.7839,0.001211,96.41142,1691.38578,1.0281 7/2/2018,72.136044,3.9079368,100.750644,1.3626,1.58581,0.2049,0.0683,0.012287,1.7906,0.001218,97.548534,1692.403704,1.0332 7/3/2018,71.95156,3.8811056,100.38556,1.354,1.57848,0.2039,0.0696,0.012243,1.7861,0.001214,101.73956,1696.19642,1.0304 7/5/2018,71.388864,3.87251424,98.731584,1.3536,1.5825,0.2039,0.0704,0.012233,1.7902,0.001209,96.159744,1702.706976,1.0308 7/6/2018,72.96946,3.917733,99.35694,1.3463,1.58099,0.2026,0.0707,0.012187,1.7882,0.001207,98.68379,1690.252724,1.0286 7/9/2018,73.460605,3.82423722,98.907305,1.3393,1.57375,0.2024,0.0697,0.012084,1.7758,0.001203,99.91178,1684.410824,1.0218 7/13/2018,73.064238,3.854708,95.707278,1.3478,1.57399,0.2016,0.0713,0.011995,1.7806,0.001192,97.728978,1677.094496,1.0242 7/16/2018,69.819156,3.68945928,91.717656,1.3476,1.57848,0.2015,0.0716,0.012001,1.7838,0.001194,93.739056,1672.277268,1.0259 7/17/2018,67.480524,3.7685423,92.139472,1.3534,1.57825,0.2016,0.0716,0.01199,1.7749,0.001201,91.977064,1661.352636,1.0261 7/18/2018,57.78945,3.68149212,92.949768,1.3518,1.5732,0.2015,0.0715,0.01198,1.7667,0.001195,93.2742,1659.348018,1.0266 7/19/2018,57.089604,3.69240168,94.437816,1.3596,1.58189,0.2014,0.0713,0.012087,1.7681,0.001197,89.380104,1662.750012,1.0236 7/20/2018,56.62948,3.73396,94.98008,1.348,1.58137,0.1993,0.0709,0.0121,1.7716,0.001195,88.64448,1657.40644,1.0259 7/23/2018,56.079311,3.66473352,94.219746,1.3549,1.58398,0.1994,0.0718,0.012168,1.775,0.001194,88.596911,1659.07505,1.0285 7/24/2018,56.651364,3.66413796,95.075064,1.3482,1.57434,0.1984,0.0714,0.012123,1.7706,0.001196,89.008164,1650.897864,1.0248 7/25/2018,57.07657,3.71956806,95.37354,1.3414,1.57328,0.1994,0.0719,0.012089,1.7692,0.0012,89.60552,1652.108482,1.0282 7/26/2018,55.186476,3.7624678,94.363316,1.3556,1.57827,0.1992,0.0728,0.012188,1.7771,0.001206,90.974316,1657.478564,1.0366 7/27/2018,53.760269,3.756058,92.807059,1.3511,1.5753,0.1982,0.0725,0.01217,1.7711,0.001211,89.429309,1654.043642,1.035 7/30/2018,55.529613,3.672272,94.682513,1.3501,1.58038,0.198,0.0728,0.012156,1.7731,0.001208,91.307263,1649.079645,1.0358 7/31/2018,53.528888,3.79104617,92.571588,1.3463,1.57477,0.1973,0.0722,0.012035,1.7677,0.001209,89.878988,1648.073145,1.0356 8/1/2018,51.538896,3.7830306,91.381596,1.3506,1.57475,0.198,0.0727,0.012089,1.7729,0.001206,92.191956,1642.275576,1.0386 8/2/2018,51.836544,3.78898512,93.675264,1.3584,1.57408,0.1981,0.0729,0.01217,1.7686,0.001204,97.071264,1640.716272,1.0432 8/3/2018,50.652739,3.83874532,92.536839,1.3511,1.56237,0.1977,0.0728,0.012142,1.7561,0.001203,96.590139,1641.45139,1.0401 8/6/2018,51.119488,3.87362794,93.425738,1.3538,1.56414,0.1974,0.0731,0.012152,1.7522,0.001202,97.487138,1634.903032,1.0411 8/8/2018,48.360864,4.023344,90.074464,1.3456,1.56236,0.1972,0.0729,0.012125,1.7333,0.001205,92.429264,1633.396928,1.0335 8/13/2018,52.200225,4.01646,92.4336,1.3755,1.56959,0.1994,0.0719,0.012419,1.7572,0.001209,88.3071,1641.65925,1.047 8/14/2018,53.65746,4.17213,92.61576,1.3815,1.5662,0.2005,0.0731,0.012426,1.7568,0.001224,88.264035,1649.635335,1.0577 8/15/2018,51.816314,4.185642,89.804814,1.3814,1.5672,0.1996,0.0722,0.012474,1.754,0.001218,85.660614,1622.93779,1.0512 8/16/2018,50.901312,4.159144,90.151512,1.3772,1.5668,0.1995,0.0725,0.012419,1.7512,0.001222,85.331312,1617.053152,1.0468 8/17/2018,49.513554,4.115874,90.125334,1.3674,1.56402,0.1996,0.0724,0.012375,1.7431,0.001221,85.065954,1619.34345,1.0467 8/20/2018,48.948184,4.128981,90.524161,1.3627,1.56457,0.1995,0.0717,0.01238,1.7436,0.001219,84.378384,1622.267096,1.0446 8/21/2018,49.338818,4.086677,91.441095,1.3577,1.57043,0.1987,0.0716,0.012308,1.751,0.001216,84.639018,1623.795623,1.0413 8/22/2018,55.594116,4.109012,93.963036,1.3606,1.57794,0.1989,0.0726,0.012306,1.757,0.001216,87.568216,1627.00548,1.047 8/23/2018,56.337234,4.098006,94.971634,1.3798,1.5921,0.2,0.0726,0.012398,1.7677,0.001227,88.762534,1635.835688,1.0547 8/24/2018,56.951972,4.081649,95.311282,1.3651,1.58578,0.2003,0.0722,0.012274,1.7524,0.001224,89.031822,1645.423285,1.0477 8/27/2018,55.628157,4.056078,93.738957,1.3611,1.58864,0.1998,0.0725,0.012253,1.7538,0.001226,89.655657,1648.809318,1.0495 8/28/2018,56.248128,4.060548,93.378978,1.3626,1.59359,0.2,0.0714,0.012255,1.7543,0.001229,89.291178,1636.4826,1.0538 8/29/2018,58.49568,4.07664,95.08968,1.368,1.60151,0.201,0.0722,0.012249,1.7819,0.001232,90.98568,1650.6288,1.0597 8/30/2018,59.1938,4.06097,96.70615,1.3766,1.60686,0.201,0.072,0.012403,1.7911,0.001234,92.2322,1651.892468,1.0605 8/31/2018,59.17003,4.116176,97.06388,1.3906,1.61367,0.2031,0.0729,0.012519,1.8024,0.001247,92.54443,1670.31919,1.0662 9/4/2018,62.50391,4.12328,97.32891,1.393,1.61332,0.2037,0.0718,0.012501,1.7907,0.001246,92.31411,1659.78736,1.0563 9/5/2018,62.517294,4.1706,95.534544,1.3902,1.61699,0.2037,0.0719,0.012465,1.7942,0.001241,88.583544,1663.694046,1.0549 ================================================ FILE: Oil Money project/oil production/oil production choropleth.csv ================================================ Country,Oil Production Russia,10551497 Saudi Arabia,10460710 United States of America,8875817 Iraq,4451516 Iran,3990956 China,3980650 Canada,3662694 United Arab Emirates,3106077 Kuwait,2923825 Brazil,2515459 Venezuela,2276967 Mexico,2186877 Nigeria,1999885 Angola,1769615 Norway,1647975 Kazakhstan,1595199 Qatar,1522902 Algeria,1348361 Oman,1006841 Libya,1003000 United Kingdom,939760 Colombia,897784 Indonesia,833667 Azerbaijan,833538 India,734180 Malaysia,661240 Ecuador,548421 Argentina,510560 Romania,504000 Egypt,494325 Vietnam,301850 Australia,289749 Thailand,257525 Sudan,255000 South Sudan,255000 Turkmenistan,230779 Equatorial Guinea,227000 Gabon,210820 Denmark,140637 Chad,110156 Brunei,109117 Ghana,100549 Cameroon,93205 Pakistan,84746 Italy,70675 East Timor,60661 Trinidad and Tobago,60090 Bolivia,58077 Papua New Guinea,56667 Uzbekistan,52913 Cuba,50000 Turkey,49497 Tunisia,48757 Germany,46839 Peru,40266 New Zealand,35574 Ukraine,31989 Ivory Coast,30000 Syria,30000 Belarus,25000 Mongolia,23426 Albania,22915 Yemen,22000 Poland,20104 Democratic Republic of the Congo,20000 Philippines,20000 Republic of Serbia,20000 Netherlands,18087 Suriname,17000 France,16418 Austria,15161 Myanmar,15000 Hungary,13833 Croatia,13582 Niger,13000 Guatemala,8977 Mauritania,5000 Chile,4423 Bangladesh,4189 Japan,3918 Greece,3172 Spain,2667 Czech Republic,2333 Belize,2000 Lithuania,2000 South Africa,2000 Bulgaria,1000 Kyrgyzstan,1000 Georgia,400 Israel,390 Slovakia,200 Taiwan,196 Tajikistan,180 Morocco,160 Jordan,22 Slovenia,5 Afghanistan,0 Armenia,0 Antarctica,0 French Southern and Antarctic Lands,0 Burundi,0 Belgium,0 Benin,0 Burkina Faso,0 The Bahamas,0 Bosnia and Herzegovina,0 Bermuda,0 Bhutan,0 Botswana,0 Central African Republic,0 Switzerland,0 Republic of the Congo,0 Costa Rica,0 Northern Cyprus,0 Cyprus,0 Djibouti,0 Dominican Republic,0 Eritrea,0 Estonia,0 Ethiopia,0 Finland,0 Fiji,0 Falkland Islands,0 Guinea,0 Gambia,0 Guinea Bissau,0 Greenland,0 French Guiana,0 Guyana,0 Honduras,0 Haiti,0 Ireland,0 Iceland,0 Jamaica,0 Kenya,0 Cambodia,0 South Korea,0 Kosovo,0 Laos,0 Lebanon,0 Liberia,0 Sri Lanka,0 Lesotho,0 Luxembourg,0 Latvia,0 Moldova,0 Madagascar,0 Macedonia,0 Mali,0 Malta,0 Montenegro,0 Mozambique,0 Malawi,0 Namibia,0 New Caledonia,0 Nicaragua,0 Nepal,0 Panama,0 Puerto Rico,0 North Korea,0 Portugal,0 Paraguay,0 Rwanda,0 Western Sahara,0 Senegal,0 Solomon Islands,0 Sierra Leone,0 El Salvador,0 Somaliland,0 Somalia,0 Sweden,0 Swaziland,0 Togo,0 United Republic of Tanzania,0 Uganda,0 Uruguay,0 Vanuatu,0 West Bank,0 Zambia,0 Zimbabwe,0 ================================================ FILE: Oil Money project/oil production/oil production choropleth.py ================================================ # coding: utf-8 # In[1]: import folium import os os.chdir('h:/') import pandas as pd # In[2]: #this table comes from wikipedia # https://en.wikipedia.org/wiki/List_of_countries_by_oil_production #but i have changed the names of some countries #try to keep names consistent with geojson file df=pd.read_csv('oil production choropleth.csv') # In[3]: df['Oil Production']=df['Oil Production'].apply(lambda x: x/1000) # In[4]: #location takes two arguments, latitude and longitude #zoom_start implies zoom level #1 is world map, 2 is continent map, 3 is region map #4 is country map, 5 is county map etc m=folium.Map(location=(30,50), zoom_start=4) #geo_data is a geojson file #its a file that indicates country shape on a map #we can download country and even more detailed level from the first link #the second link converts all the files in first link to geojson #https://gadm.org/download_country_v3.html #https://mapshaper.org/ #here i found the map shape from github #i just cannot find the original link #so i just upload it to the repo #data is the dataframe #columns would be the columns we use in that dataframe #we need one column for the region name and the other one for value #the region name should be consistent with the region name in geojson #and key_on denotes the key in geojson for region names #fill_color is just matplotlib cmap #fill_opacity,line_opacity are plotting options #legend_name is just the name of the label in matplotlib #threshold_scale can only take up to six values in a list #for simplicity, we can use from branca.utilities import split_six #to get the quantile data equally divided into six parts m.choropleth( geo_data=(open("worldmapshape.json",encoding = "utf_8_sig").read()), name='choropleth', data=df, columns=['Country', 'Oil Production'], key_on='properties.name', fill_color='YlOrRd', fill_opacity=0.7, line_opacity=0.2, legend_name='Oil Production Thousand Barrels/Day', threshold_scale=[0.0,1.0, 150.0, 800.0, 2000.0, 4000.0] ) #layout control is just a map filter #we can unselect choropleth any time folium.LayerControl().add_to(m) display(m) #in general, folium is a really good wrap up for leaflet.js #it saves me a lot of time from learning javascript #it is very straight forward, a very flat learning curve #there is only one thing i hate about it #which is the location name is always in local language #at least google map provides english plus local language #this is quite annoying, other than that, its pretty cool ================================================ FILE: Oil Money project/oil production/oil production cost curve.csv ================================================ Country,Operational cost dollar per barrel,Capital cost dollar per barrel,Total cost dollar per barrel,Reserve k mil barrels,Daily production mil barrels,2015 average price United Kingdom,21.8,30.7,52.5,2.5423575,0.963415531,52.4 Brazil,17.3,31.5,48.8,12.99978129,2.524976918,52.4 Canada,18.7,22.4,41,171.5123079,4.388135578,52.4 US,21.5,14.8,36.2,47.987,12.77291501,52.4 Norway,24,12.1,36.1,8.005041226,1.9400792,52.4 Angola,18.8,16.6,35.4,9.524,1.795646188,52.4 Colombia,15.5,19.8,35.3,2.308,1.005574436,52.4 Nigeria,16.2,15.3,31.6,37.062,2.201408745,52.4 China,15.6,14.3,29.9,25.62646431,4.308835068,52.4 Mexico,18.3,10.7,29.1,7.9765,2.586540847,52.4 Kazakhstan,16.3,11.5,27.8,30,1.694757886,52.4 Libya,16.6,7.2,23.8,48.363,0.436643836,52.4 Venezuela,9.6,13.9,23.5,300.8783,2.630863,52.4 Algeria,13.2,7.2,20.4,12.2,1.557665233,52.4 Russian Federation,8.9,8.4,17.2,102.3752,11.00667742,52.4 Iran,6.9,5.7,12.6,158.4,3.852759885,52.4 United Arab Emirates,6.6,5.7,12.3,97.8,3.897972489,52.4 Iraq,5.6,5.1,10.7,142.503,3.985940667,52.4 Saudi Arabia,4.5,5.4,9.9,266.455,11.99793798,52.4 Kuwait,3.7,4.8,8.5,101.5,3.060775981,52.4 ================================================ FILE: Oil Money project/oil production/oil production cost curve.py ================================================ # coding: utf-8 # In[1]: import numpy as np import matplotlib.pyplot as plt import os os.chdir('d:/') import pandas as pd # In[2]: #traditional commodity cost curve #input two pandas series, the third one is optional def cost_curve(x,y1,y2=None, hline_var=0,hline_color='k',hline_name='', colormap='tab20c',legends=None,notes=None, ylabel='',xlabel='',title='',fig_size=(10,5)): y2 = [] if y2 is None else y2 legends = [] if legends is None else legends notes = [] if notes is None else notes ax=plt.figure(figsize=fig_size).add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) #set bar location on x axis wid=x cumwid=[0] for i in range(1,len(wid)): cumwid.append(wid[i-1]+cumwid[-1]) #assign colors to different bars from cmap cmap=plt.cm.get_cmap(colormap) colors=[cmap(i) for i in np.linspace(0,1,len(y1))] colors2=[tuple([i/1.3 for i in j if i!=1]+[1.0]) for j in colors] for i in range(len(y1)): plt.bar(cumwid[i], y1[i],width=wid[i],label=legends[i] if len(legends)>0 else '', color=colors[i],align='edge') if len(y2)>0: plt.bar(cumwid[i], y2[i],width=wid[i], color=colors2[i],bottom=y1[i],align='edge' ) #plot percentile line if needed plt.axhline(y=hline_var, linestyle='--', c=hline_color,label=hline_name) plt.title(title,pad=20) ax.yaxis.labelpad=10 ax.xaxis.labelpad=10 plt.ylabel(ylabel) plt.xlabel(xlabel) #slightly expand x axis to look nicer plt.xlim(min(cumwid),max(cumwid)+list(wid)[-1]) plt.xticks([min(cumwid), np.mean([min(cumwid), max(cumwid)+list(wid)[-1]]), 1.01*max(cumwid)+list(wid)[-1]]) #if cost curve breakdown is provided #add legends to the right if len(y2)>0: plt.text(1.1*max(cumwid)+list(wid)[-1], list(y1)[-1]/2,notes[0], verticalalignment='center', horizontalalignment='center') plt.text(1.1*max(cumwid)+list(wid)[-1], list(y1)[-1]+list(y2)[-1]/2,notes[1], verticalalignment='center', horizontalalignment='center') #legends of cost curve for different entities is plotted below the chart plt.legend(loc=6,bbox_to_anchor=(0.12, -0.4), ncol=4) plt.show() # In[3]: #why there is only 2015 data? #well, they said data is the new oil #especially true when it comes to oil data #i can only find oil production cost data of 2015 from the below address # https://www.statista.com/statistics/597669/cost-breakdown-of-producing-one-barrel-of-oil-in-the-worlds-leading-oil-producing-countries/ #and i have to do some scraping to actually get the data #if u dont know scraping, that will be a problem #data scientists cant wait for engineers to feed you data #maybe its time for you to learn # https://github.com/je-suis-tm/web-scraping #also you can use oil breakeven price to replace cost data #the following two links contain quite a lot of information #sadly, fiscal breakeven price is widely used by opec countries #if u have other countries in mind, you will be disappointed # https://www.cfr.org/report/interactive-oil-exporters-external-breakeven-prices # http://graphics.wsj.com/oil-barrel-breakdown/ #daily production data and proven reserve comes from bp # https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html #production capacity is a typical x axis for cost curve #you can find them from imf or eia, but again, only for opec countries #therefore, i used daily production data as alternative # https://www.imf.org/~/media/Files/Publications/REO/MCD-CCA/2018/May/English/mreo0518-statisticalappendix-elsx.ashx # https://www.eia.gov/opendata/qb.php?sdid=STEO.COPC_AG.A df=pd.read_csv('global oil cost curve.csv') # In[4]: cost_curve(df['Daily production mil barrels'], df['Operational cost dollar per barrel'], df['Capital cost dollar per barrel'], legends=df['Country'], notes=['Operational Cost','Capital Cost'], hline_var=np.percentile(df['Total cost dollar per barrel'],90), hline_color='#e08314', hline_name='90% Percentile', xlabel='Daily Production, Million Barrels', ylabel='US Dollar per Barrel', 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================================================ FILE: Options Straddle backtest.py ================================================ # coding: utf-8 # In[1]: #after a long while of struggle, i finally decided to write something on options strategy #the biggest issue of options trading is to find the backtesting data #the most difficult part is options greeks #after all, data is the new black gold #here are a couple of websites u can try your luck #currently they offer free trial for a limited period # http://base2.optionsdatamine.com/page.php # https://www.historicaloptiondata.com/ #in order to save u guys from the hassle, I also include a small dataset of stoxx 50 index #the dataset has 3 spreadsheets, the spot spreadsheet refers to spot price of stoxx 50 #aug spreadsheet refers to options settle at august 2019 #jul spreadsheet refers to options settle at july 2019 # https://github.com/je-suis-tm/quant-trading/tree/master/data #if you dont know what options straddle is #i recommend u to read a tutorial from fidelity #who else can explain the concept of options than one of the largest mutual funds # https://www.fidelity.com/learning-center/investment-products/options/options-strategy-guide/long-straddle #in simple words, options are a financial derivative #that enables u to trade underlying asset at certain price in the future #and options straddle enable you to profit from a certain level of volatility #in this script, we are only gonna talk about long straddle #basically long straddle implies buy call option and put option of same strike price and same strike date #preferably at the same option price as well #otherwise asymmetric option price means there is more one-sided risk than the other #you may wanna consider strangle or strap/strip in this case #short straddle is literally shorting call option and put option of the same strike price and the same strike date #preferably at the same option price as well #long straddle has unlimited profit for upside movement and limited loss #short straddle has unlimited loss for upside movement and limited profit #short straddle is commonly used in a sideway market #long straddle is commonly used in event driven strategy #for instance, brexit on 30th of October 2019, its do or die, no ifs and buts #if bojo delivers a no-deal Brexit, uk sterling gonna sink #or he secures a new deal without backstop from macron and merkel #even though unlikely, uk sterling gonna spike #or he has to postpone and look like an idiot, uk sterling still gonna surge #either way, there will be a lot of volatility around that particular date #to secure a profit from either direction, that is when options straddle kick in #but hey, options are 3 dimensional #apart from strike date, option price, which strike price should we pick #well, that is a one million us dollar question #who says quantitative trading is about algos and calculus? #this is when u need to consult with some economists to get a base case #their fundamental analysis will determine your best/worst scenario #therefore, u can pick a good strike price to maximize your profit #or the simplest way is to find a strike price closer to the current spot price #nevertheless, as u can see in our stoxx 50 dataset #not all strike price offer both call and put options #and even if they offer both, the price of options may be very different #there could be more upside/downside from the market consensus #we can pick the options which offer both call and put options #and we only trade when both option prices are converging #and please don’t arrogantly believe that you outsmart the rest of the players in the market #all the information you have obtained from any tips may have already been priced in #finding a good pair of call and put options at the same strike price, #the same strike date and almost the same price is tough #to make our life easier, we only consider european options with cash settlement in this script import os os.chdir('d:/') import pandas as pd import numpy as np import matplotlib.pyplot as plt import re # In[2]: #as we have gathered all the available call and put options #this function will only extract strike price existing in both call and put options #this is a fundamental requirement of options straddle def find_strike_price(df): temp=[re.search('\d{4}',i).group() for i in df.columns] target=[] for i in set(temp): if temp.count(i)>1: target.append(i) return target # In[3]: #this function is merely data cleansing #merging option price information with spot price def straddle(options,spot,contractsize,strikeprice): option=options[[i for i in options.columns if strikeprice in i]] df=pd.merge(spot,option,left_index=True,right_index=True) temp=[] for i in df.columns: if 'C'+strikeprice in i: temp.append('call') elif 'P'+strikeprice in i: temp.append('put') elif 'Index' in i: temp.append('spot') else: temp.append(i) df.columns=temp #we multiply contract size with spot price here #it makes our life a lot easier later with visualization df['spot']=df['spot'].apply(lambda x:x*contractsize) return df # In[4]: #signal generation is actually very simple #just find the option pair at the closest price we can def signal_generation(df,threshold): df['signals']=np.where( np.abs( df['call']-df['put'])0 and group1>0 and group2<0: group2=x.index(j) ax=plt.figure(figsize=(10,5)).add_subplot(111) ax.spines['bottom'].set_position(('data',0)) ax.spines['right'].set_visible(False) ax.spines['top'].set_visible(False) #pnl in different colors, red is loss, green is profit plt.plot(x[:group1],y[:group1],c='#57bc90',lw=5) plt.plot(x[group2:],y[group2:],c='#57bc90',lw=5) plt.plot(x[group1:group2],y[group1:group2],c='#ec576b',lw=5) #ploting strike price plt.plot([int(strikeprice)*contractsize, int(strikeprice)*contractsize], [0,-(df['call'][ind[0]]+df['put'][ind[0]])], linestyle=':',lw=3,c='#ec576b',alpha=0.5) #ploting spot price plt.axvline(df['spot'].iloc[-1],lw=5, linestyle='--',c='#e5e338',alpha=0.5) #adding annotations plt.annotate('Strike Price', xy=(int(strikeprice)*contractsize, 0), xytext=(int(strikeprice)*contractsize, df['call'][ind[0]]+df['put'][ind[0]]), arrowprops=dict(arrowstyle='simple', facecolor='#c5c1c0',), va='center',ha='center' ) plt.annotate('Lower Breakeven Point', xy=(int(strikeprice)*contractsize-(df['call'][ind[0]]+df['put'][ind[0]]), 0), xytext=(int(strikeprice)*contractsize-1.5*(df['call'][ind[0]]+df['put'][ind[0]]), -df['call'][ind[0]]-df['put'][ind[0]]), arrowprops=dict(arrowstyle='simple', facecolor='#c5c1c0'), va='center',ha='center' ) plt.annotate('Upper Breakeven Point', xy=(int(strikeprice)*contractsize+(df['call'][ind[0]]+df['put'][ind[0]]), 0), xytext=(int(strikeprice)*contractsize+1.5*(df['call'][ind[0]]+df['put'][ind[0]]), -df['call'][ind[0]]-df['put'][ind[0]]), arrowprops=dict(arrowstyle='simple', facecolor='#c5c1c0'), va='center',ha='center' ) plt.annotate('Spot Price', xy=(df['spot'].iloc[-1], 2*(df['call'][ind[0]]+df['put'][ind[0]])), xytext=(df['spot'].iloc[-1]*1.003, 2*(df['call'][ind[0]]+df['put'][ind[0]])), arrowprops=dict(arrowstyle='simple', facecolor='#c5c1c0'), va='center',ha='left' ) #limit x ticks to 3 for a tidy look plt.locator_params(axis='x',nbins=3) plt.title(f'Long Straddle Options Strategy\nP&L {round(profit,2)}') plt.ylabel('Profit & Loss') plt.xlabel('Price',labelpad=50) plt.show() # In[6]: #for stoxx 50 options, the contract size is 10 ticks per euro contractsize=10 #the threshold determines the price disparity between call and put options #the same call and put option price for the same strike price and the same strike date #only exists in an ideal world, in reality, it is like royal flush #when the price difference of call and put is smaller than 2 euros #we consider them identically the same option price threshold=2 # In[7]: def main(): data=pd.ExcelFile('stoxx50.xlsx') aug=data.parse('aug') aug.set_index('Dates',inplace=True) aug.index=pd.to_datetime(aug.index) spot=data.parse('spot') spot.set_index('Dates',inplace=True) spot.index=pd.to_datetime(spot.index) target=find_strike_price(aug) #we iterate through all the available option pairs #to find the optimal strike price to maximize our profit for strikeprice in target: df=straddle(aug,spot,contractsize,strikeprice) signal=signal_generation(df,threshold) plot(signal,strikeprice,contractsize) # In[8]: if __name__ == '__main__': main() ================================================ FILE: Ore Money project/README.md ================================================ This is an upcoming project similar to Quant Trading - Oil Money. It is designed to be an upgraded version of oil money trading strategy with introduction of more sophisticated models and alternative datasets. The project will examine the causality between iron ore spot price and forex of iron ore exporting countries. If the project can replicate the success of oil money trading strategy, we shall be able to apply it to the currency of any major natural resource exporter and correlated commodity contracts. The following figure is the global iron ore production bubble map (check subfolder for how it is visualized, this can also be done in choropleth, check this link for how to create a choropleth). It lists out a few iron ore and currency arbitrage opportunities. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Ore%20Money%20project/preview/iron%20ore%20production%20bubble%20map.png) ================================================ FILE: Ore Money project/iron ore audeur.csv ================================================ date,newcastle thermal coal 6000kcal,audeur,sgdeur,usdeur,krweur,jpyeur,cnyeur,gold lbma,iron ore 62%,henry hub natural gas 1/7/2014,61.65393,0.6943,0.5868,0.7345,0.68743,0.70215,0.12137,904.96276,98.489105,3.3336017 1/8/2014,61.535564,0.6937,0.5974,0.7366,0.69199,0.7024,0.12174,903.064234,98.7044,3.20472562 1/9/2014,61.342103,0.7108,0.6095,0.7349,0.69149,0.70107,0.12135,902.442502,98.425157,3.04204506 1/10/2014,60.882745,0.6923,0.6228,0.7315,0.68924,0.70223,0.12087,913.27775,97.94785,2.89140005 1/13/2014,59.850462,0.6623,0.5783,0.7314,0.69212,0.71009,0.12102,916.670934,97.42248,3.064566 1/14/2014,59.91276,0.6555,0.5759,0.731,0.6902,0.70143,0.12101,910.23389,97.223,3.18716 1/15/2014,60.30675,0.6553,0.5773,0.735,0.69166,0.703,0.12157,912.7818,96.7995,3.2634735 1/16/2014,60.380608,0.6476,0.5775,0.7342,0.69047,0.70363,0.12124,912.162738,95.95994,3.3321667 1/17/2014,60.77855,0.6486,0.5787,0.7385,0.69694,0.70796,0.12207,926.115925,96.005,3.24459975 1/21/2014,60.518418,0.6493,0.5767,0.7374,0.69222,0.70701,0.12188,915.415734,93.94476,3.3795042 1/22/2014,60.474153,0.6534,0.5772,0.7383,0.69159,0.70623,0.12198,913.387845,92.21367,3.62453619 1/23/2014,59.678374,0.6402,0.5711,0.7301,0.67996,0.70701,0.12064,922.941313,92.06561,4.125065 1/24/2014,59.607424,0.6348,0.5718,0.7312,0.67674,0.71417,0.12088,928.667872,92.64304,3.79149136 1/27/2014,58.504,0.6391,0.573,0.7313,0.67492,0.71316,0.12094,919.324543,92.50945,4.16841 1/28/2014,58.484104,0.6422,0.5737,0.7316,0.67665,0.71061,0.12089,919.496828,91.88896,3.80432 1/29/2014,58.573957,0.6396,0.573,0.7319,0.68404,0.71557,0.12088,927.566146,91.85345,3.80529448 1/30/2014,59.046134,0.6488,0.5785,0.7378,0.68269,0.71821,0.12174,917.660884,92.52012,3.888206 2/7/2014,57.014955,0.6913,0.5868,0.7335,0.68261,0.71634,0.12095,929.542545,91.90755,4.393665 2/10/2014,57.107104,0.6949,0.6205,0.7328,0.68416,0.71663,0.12092,934.158784,91.16032,5.59082432 2/12/2014,56.987322,0.682,0.6157,0.7357,0.69229,0.7175,0.12134,949.899055,90.41753,4.436271 2/13/2014,56.49899,0.6564,0.5779,0.731,0.68553,0.71545,0.12054,952.43452,89.7668,3.88892 2/14/2014,56.349948,0.6598,0.58,0.7303,0.6868,0.71743,0.12039,963.017398,89.8269,4.023953 2/18/2014,55.905456,0.6561,0.5763,0.7268,0.68198,0.71006,0.11979,960.844136,90.19588,4.150028 2/19/2014,56.216601,0.6554,0.5763,0.7281,0.68331,0.71168,0.11984,954.97596,90.21159,4.397724 2/20/2014,56.34397,0.6565,0.5767,0.7289,0.67982,0.71275,0.11981,964.312833,89.6547,4.336955 2/21/2014,56.25894,0.6533,0.5742,0.7278,0.6786,0.71027,0.1195,963.78915,88.4277,4.519638 2/24/2014,56.51464,0.6578,0.5765,0.728,0.67752,0.71033,0.1194,973.31416,87.7968,4.531072 2/25/2014,56.3376,0.6562,0.5757,0.7275,0.67818,0.71165,0.11882,975.21375,86.20875,3.79878675 2/26/2014,56.409626,0.6553,0.5768,0.7306,0.68592,0.71386,0.1193,972.165584,85.99162,3.53522728 2/27/2014,56.280504,0.6539,0.5771,0.7294,0.68232,0.71422,0.11902,971.042926,85.26686,3.32883572 2/28/2014,55.924628,0.6471,0.5715,0.7246,0.67867,0.71191,0.11791,961.102194,83.90868,3.40293898 3/3/2014,55.219104,0.6507,0.5729,0.7281,0.68036,0.71769,0.11847,983.379141,84.31398,4.99360104 3/4/2014,55.072336,0.6728,0.577,0.7277,0.67785,0.71201,0.11845,971.093819,83.17611,5.76680419 3/6/2014,54.4011,0.6799,0.5839,0.7215,0.678,0.70002,0.11791,974.61663,81.02445,3.53801955 3/7/2014,54.167502,0.6868,0.5893,0.7206,0.67925,0.69792,0.1176,965.589588,79.48218,3.437262 3/10/2014,52.200264,0.6933,0.6233,0.7206,0.67571,0.69784,0.11736,965.402232,75.95124,3.3338559 3/11/2014,52.06344,0.6955,0.6205,0.7215,0.67741,0.70041,0.11751,973.310715,74.7474,3.35793315 3/12/2014,51.868704,0.6828,0.619,0.7192,0.67186,0.69996,0.11704,983.031328,74.7968,3.35132816 3/13/2014,52.14993,0.6511,0.5692,0.721,0.67433,0.70799,0.11749,987.97188,75.705,3.1724 3/14/2014,52.465322,0.6492,0.5683,0.7189,0.67015,0.70925,0.1169,994.181188,75.34072,3.155971 3/17/2014,54.30348,0.6527,0.568,0.7183,0.67295,0.70588,0.11627,981.966381,75.4215,3.29663785 3/18/2014,54.32989,0.655,0.5679,0.7177,0.67123,0.70751,0.11585,973.043306,74.92788,3.18816694 3/19/2014,54.550034,0.6537,0.5676,0.7229,0.67522,0.70644,0.11671,961.160611,74.60328,3.21177241 3/20/2014,54.594676,0.656,0.568,0.7258,0.67438,0.70883,0.11652,963.695466,73.95902,3.19352 3/21/2014,54.4475,0.6585,0.569,0.725,0.67107,0.70893,0.11645,967.65025,73.805,3.12475 3/24/2014,53.927638,0.6598,0.5684,0.7226,0.67041,0.70674,0.11666,945.709976,74.21102,3.1884725 3/25/2014,53.697792,0.6629,0.5704,0.7233,0.67,0.70729,0.11664,948.369261,75.51252,3.2534034 3/26/2014,53.694255,0.6694,0.5724,0.7255,0.67504,0.71109,0.11686,946.40024,76.3226,3.2088865 3/27/2014,53.849922,0.6739,0.5756,0.7278,0.67924,0.71221,0.11714,939.815418,76.56456,3.19183968 3/28/2014,53.863704,0.6725,0.5778,0.7272,0.68012,0.70723,0.11705,941.891256,77.15592,3.25974672 3/31/2014,54.203769,0.6728,0.5775,0.7263,0.68204,0.7035,0.11681,932.576463,78.51303,3.24532629 4/2/2014,53.82624,0.6602,0.583,0.7264,0.68744,0.69928,0.11705,936.98336,79.904,3.152576 4/3/2014,53.770953,0.6513,0.5732,0.7289,0.68902,0.70125,0.11734,937.87563,80.10611,3.26758581 4/4/2014,53.654896,0.6781,0.5798,0.7298,0.69258,0.70652,0.11746,951.2943,80.13204,3.26884718 4/8/2014,53.048112,0.6954,0.598,0.7248,0.68877,0.71192,0.11696,948.516768,81.9024,3.30211632 4/9/2014,52.864737,0.7223,0.6154,0.7219,0.69297,0.70763,0.11641,946.98842,81.64689,3.36347648 4/11/2014,52.776256,0.6965,0.6185,0.7202,0.6956,0.70871,0.11596,949.526084,81.3826,3.34921808 4/14/2014,53.59688,0.6819,0.5773,0.7235,0.69648,0.71043,0.11634,960.800765,82.0449,3.3486474 4/15/2014,53.42382,0.6777,0.578,0.7239,0.69556,0.71028,0.11636,942.981096,81.65592,3.37938237 4/16/2014,53.322346,0.6782,0.5788,0.7238,0.69739,0.70804,0.11633,942.771214,80.92084,3.34750262 4/17/2014,53.250084,0.6754,0.5779,0.7239,0.69673,0.707,0.11641,937.537368,80.49768,3.30474828 4/22/2014,53.084032,0.6785,0.5768,0.7244,0.69812,0.70589,0.11615,929.991964,78.74228,3.43090328 4/23/2014,53.0037,0.6724,0.5761,0.7236,0.69611,0.70585,0.11602,929.037276,78.58296,3.466044 4/24/2014,52.90191,0.6697,0.5748,0.723,0.69567,0.70668,0.11568,935.09928,78.084,3.4704 4/25/2014,52.851136,0.6706,0.5752,0.7228,0.69422,0.70738,0.11562,941.9891,77.99012,3.3982442 4/28/2014,52.684262,0.6684,0.5746,0.7219,0.69739,0.70444,0.11547,936.116606,76.81016,3.45089857 4/29/2014,52.852,0.671,0.5765,0.724,0.7025,0.70537,0.11569,938.24608,75.9476,3.4920692 4/30/2014,52.654722,0.6697,0.5752,0.7211,0.69788,0.70539,0.11521,931.37276,74.92229,3.454069 5/5/2014,52.524696,0.6684,0.5764,0.7208,0.70019,0.70557,0.11542,944.449824,73.73784,3.394968 5/6/2014,52.33502,0.6838,0.5846,0.718,0.70052,0.70614,0.11531,939.1799,73.3078,3.435271 5/8/2014,52.93045,0.6956,0.5993,0.7226,0.70646,0.71078,0.11602,931.742118,71.75418,3.4254853 5/9/2014,53.405183,0.724,0.6157,0.7267,0.70978,0.71351,0.1167,936.650897,71.79796,3.32385313 5/12/2014,54.212202,0.6775,0.6154,0.7269,0.70949,0.71177,0.11654,941.91702,71.67234,3.27105 5/13/2014,54.501293,0.683,0.5826,0.7297,0.71393,0.71364,0.11716,943.961811,71.94842,3.254462 5/14/2014,54.412904,0.6838,0.5832,0.7292,0.70942,0.71555,0.11706,952.313324,72.11788,3.21475112 5/15/2014,54.39832,0.6825,0.5826,0.7292,0.71144,0.71807,0.11709,945.203624,72.1908,3.17369716 5/16/2014,54.48038,0.6836,0.5836,0.7303,0.71303,0.71943,0.11715,944.657656,72.22667,3.23333022 5/19/2014,54.30383,0.6806,0.5834,0.7294,0.71369,0.71866,0.11695,943.092318,71.04356,3.29170926 5/20/2014,54.450378,0.6746,0.5826,0.7298,0.7118,0.7203,0.11701,944.631226,70.57166,3.305994 5/21/2014,54.466378,0.6759,0.5839,0.7307,0.71144,0.72078,0.1172,944.093628,70.22027,3.331992 5/22/2014,54.497766,0.6755,0.5853,0.7323,0.71496,0.71981,0.11744,947.66943,70.3008,3.288027 5/23/2014,54.543354,0.6772,0.5854,0.7338,0.716,0.7195,0.11766,948.517218,69.85776,3.214044 5/27/2014,54.557832,0.6791,0.5837,0.7336,0.7168,0.71924,0.11739,927.96732,69.692,3.25160864 5/28/2014,54.66994,0.6796,0.5858,0.7358,0.72031,0.72245,0.11763,925.739412,69.38594,3.34472606 5/29/2014,54.390141,0.6843,0.5859,0.7353,0.72036,0.7223,0.11783,923.213268,69.41232,3.397086 5/30/2014,54.198315,0.6829,0.5849,0.7335,0.719,0.72076,0.11741,916.64028,67.6287,3.28608 6/3/2014,53.376612,0.6558,0.5711,0.7338,0.71731,0.71589,0.11733,913.54431,66.92256,3.368142 6/5/2014,53.165102,0.6714,0.5757,0.7321,0.71729,0.71829,0.11704,917.782523,66.91394,3.396944 6/6/2014,53.16464,0.6842,0.5855,0.7328,0.71834,0.71529,0.11727,918.366944,66.97792,3.40752 6/10/2014,53.578556,0.6925,0.6194,0.7382,0.72568,0.72121,0.11858,930.05818,67.10238,3.373574 6/11/2014,53.599532,0.6917,0.6235,0.7391,0.72746,0.72401,0.11866,932.056837,66.66682,3.32595 6/13/2014,53.45263,0.6944,0.5903,0.7385,0.72558,0.72377,0.1189,943.03496,64.8403,3.45618 6/16/2014,53.506521,0.6926,0.5891,0.7367,0.72236,0.72351,0.11836,937.0824,63.42987,3.469857 6/17/2014,53.489972,0.6892,0.5889,0.7382,0.72243,0.72267,0.11856,937.942156,63.4852,3.440012 6/18/2014,53.2502,0.692,0.589,0.7355,0.71938,0.72168,0.11804,939.755705,63.6943,3.464205 6/19/2014,52.964243,0.6906,0.588,0.7349,0.72139,0.72093,0.11798,970.354611,63.34838,3.417285 6/20/2014,52.823782,0.6903,0.5887,0.7354,0.7205,0.72036,0.11811,966.918628,63.09732,3.324008 6/23/2014,52.04508,0.6926,0.5887,0.7351,0.72174,0.72104,0.11806,968.508952,64.10072,3.293248 6/24/2014,51.979477,0.6885,0.5883,0.7349,0.72165,0.72071,0.11794,968.811321,64.08328,3.30271409 6/25/2014,51.864984,0.6903,0.5871,0.7338,0.71866,0.72033,0.11769,968.014284,64.42764,3.35111784 6/26/2014,51.950637,0.6917,0.5881,0.7347,0.72284,0.72227,0.11802,967.291326,65.75565,3.34428093 6/27/2014,51.934014,0.6907,0.5862,0.7326,0.72287,0.7226,0.11783,964.226142,66.08052,3.216114 6/30/2014,51.83628,0.6889,0.5859,0.7305,0.72179,0.72078,0.11774,969.614565,66.0372,3.221505 7/1/2014,51.864234,0.6556,0.5778,0.7311,0.72266,0.72008,0.11789,969.774906,65.57967,3.260706 7/2/2014,51.920532,0.657,0.5783,0.7321,0.72546,0.71932,0.11788,971.394206,65.81579,3.22124 7/3/2014,52.075536,0.6536,0.568,0.7347,0.72851,0.71897,0.11827,969.458691,66.71076,3.15384669 7/7/2014,51.53051,0.6889,0.5895,0.7351,0.72736,0.72155,0.11849,970.287894,67.99675,3.1271154 7/8/2014,51.524511,0.6937,0.5976,0.7347,0.72612,0.72327,0.11846,969.245628,68.03322,3.063699 7/10/2014,51.39926,0.696,0.619,0.7348,0.72508,0.72511,0.11848,981.5091,68.77728,3.027376 7/11/2014,51.36951,0.6935,0.6229,0.7349,0.72126,0.72526,0.11844,983.81063,68.71315,3.00147858 7/14/2014,50.703415,0.6897,0.5915,0.7343,0.72104,0.72314,0.11832,959.840245,68.65705,3.01393435 7/15/2014,50.743896,0.6906,0.5927,0.7367,0.71732,0.72472,0.11871,953.326635,69.2498,3.027837 7/16/2014,50.634112,0.6926,0.5951,0.7394,0.71645,0.72713,0.11916,960.635874,70.09512,3.03205758 7/17/2014,50.405474,0.6914,0.5944,0.7393,0.71822,0.73071,0.11916,975.28456,70.15957,2.971986 7/18/2014,50.41911,0.6946,0.5957,0.7395,0.71825,0.72964,0.11909,969.39576,69.73485,2.8895223 7/21/2014,49.68768,0.6931,0.5965,0.7394,0.72011,0.72927,0.11909,970.455106,69.05996,2.8426233 7/22/2014,50.139,0.6976,0.599,0.7428,0.72482,0.73194,0.11971,970.408776,68.78328,2.81944596 7/23/2014,50.251082,0.7023,0.6006,0.7427,0.7255,0.73187,0.11982,968.918993,68.69975,2.807406 7/24/2014,50.407688,0.6996,0.5984,0.7426,0.72199,0.72955,0.11991,960.671916,68.39346,2.82046906 7/25/2014,50.550894,0.6997,0.5994,0.7446,0.72562,0.73121,0.12025,973.356012,67.98198,2.81838546 7/28/2014,51.997708,0.6999,0.5993,0.7441,0.725,0.73048,0.12026,970.343605,68.53161,2.849903 7/29/2014,52.138878,0.6998,0.6001,0.7458,0.72795,0.7303,0.12065,968.876238,68.83734,2.79809244 7/30/2014,51.918051,0.6965,0.5999,0.7467,0.72866,0.72616,0.12094,967.94721,68.92041,2.792658 7/31/2014,51.746846,0.6942,0.5985,0.7466,0.72664,0.72652,0.12096,957.581694,68.91118,2.79975 8/1/2014,51.406096,0.6557,0.5783,0.7448,0.71797,0.72572,0.12052,963.585,69.04296,2.785552 8/4/2014,51.292684,0.6784,0.5793,0.7451,0.72087,0.72632,0.12057,959.875075,68.99626,2.823929 8/5/2014,51.778776,0.6774,0.5792,0.7476,0.72704,0.72869,0.12115,963.491928,69.60156,2.885736 8/7/2014,51.924537,0.6905,0.591,0.7483,0.7213,0.73293,0.12146,982.241029,70.04088,2.978234 8/8/2014,51.886304,0.6918,0.5954,0.7456,0.71937,0.73082,0.12111,976.422848,69.63904,2.915296 8/12/2014,52.83124,0.6734,0.6153,0.748,0.72857,0.73148,0.12146,979.51348,68.8908,2.93216 8/13/2014,52.395966,0.6962,0.5988,0.7483,0.72686,0.73058,0.12158,982.458036,68.54428,2.880955 8/14/2014,52.366518,0.6973,0.6004,0.7482,0.73288,0.73033,0.1216,982.775664,67.63728,2.865606 8/15/2014,52.151444,0.6956,0.5992,0.7463,0.73405,0.72907,0.1214,973.69761,67.46552,2.798625 8/18/2014,51.969435,0.6978,0.6011,0.7483,0.73521,0.72954,0.1218,971.59272,67.42183,2.81271004 8/19/2014,52.045456,0.6984,0.6019,0.7508,0.7379,0.72947,0.12224,972.834084,67.49692,2.88487392 8/20/2014,52.19064,0.7004,0.6027,0.7542,0.73747,0.72686,0.12281,974.381148,67.1238,2.9010303 8/21/2014,52.1076,0.7004,0.6026,0.753,0.73553,0.72507,0.12239,961.41534,66.5652,2.9135076 8/22/2014,52.312704,0.7036,0.6044,0.7552,0.74201,0.72668,0.12273,967.48672,66.23104,2.91439232 8/25/2014,52.93114,0.7048,0.6064,0.758,0.74307,0.72848,0.12317,967.84472,66.4008,2.97894 8/26/2014,53.127025,0.7068,0.6077,0.7595,0.74685,0.7298,0.12343,973.0714,66.30435,2.9948604 8/27/2014,52.9842,0.7077,0.6075,0.758,0.74732,0.72969,0.12338,972.23354,65.8702,3.0235862 8/28/2014,52.935108,0.7098,0.607,0.7586,0.7478,0.73138,0.12348,978.32849,65.39132,3.05086162 8/29/2014,53.068935,0.7111,0.6098,0.7615,0.75101,0.73156,0.12394,980.29418,65.6413,3.06633205 9/4/2014,52.281842,0.6777,0.579,0.7726,0.75822,0.73405,0.12585,974.766242,65.43922,3.005414 9/5/2014,52.078145,0.6804,0.5821,0.7721,0.75376,0.73471,0.12573,979.648201,64.00709,2.964864 9/9/2014,51.250999,0.7114,0.6122,0.7729,0.74926,0.72775,0.12595,970.352763,63.68696,3.0444531 9/10/2014,51.298492,0.692,0.6198,0.7742,0.74806,0.7245,0.1263,967.571934,63.25214,3.06939332 9/12/2014,50.973005,0.6702,0.6139,0.7715,0.74502,0.71839,0.12573,948.674975,62.9544,2.939415 9/15/2014,51.128448,0.6977,0.6115,0.7728,0.74451,0.72099,0.12583,953.032416,64.21968,3.0204888 9/16/2014,51.101974,0.7017,0.6123,0.7717,0.74429,0.72031,0.12554,953.473935,64.43695,2.971045 9/17/2014,51.441714,0.6964,0.6132,0.7773,0.7511,0.71727,0.1266,951.034323,64.90455,3.08339364 9/18/2014,51.224441,0.6957,0.6109,0.7739,0.7419,0.71195,0.12601,948.143585,64.54326,3.06835872 9/19/2014,51.549516,0.6958,0.615,0.7794,0.74613,0.7148,0.12693,947.51658,64.61226,3.00801636 9/22/2014,51.531243,0.6905,0.6129,0.7783,0.74775,0.71506,0.12674,945.696764,63.97626,3.01038657 9/23/2014,51.342075,0.6881,0.6134,0.7785,0.74853,0.71487,0.12681,952.43247,63.60345,3.0327246 9/24/2014,51.56675,0.6953,0.6175,0.7825,0.7524,0.71757,0.12756,952.372925,63.77375,3.0048 9/25/2014,51.644896,0.6892,0.6174,0.7844,0.75219,0.72115,0.12781,958.207352,63.85016,3.04198164 9/26/2014,51.900372,0.6911,0.6185,0.7884,0.75501,0.72145,0.12868,960.570792,64.33344,3.082644 9/29/2014,51.524634,0.6873,0.6179,0.7882,0.74802,0.71998,0.1281,958.301442,63.76538,3.168564 9/30/2014,51.373413,0.6925,0.6205,0.7917,0.75025,0.72203,0.12894,956.492355,63.96936,3.27645045 10/9/2014,51.19636,0.7087,0.6129,0.788,0.74027,0.73066,0.12853,964.77204,64.1432,3.04956 10/10/2014,51.410148,0.6878,0.6207,0.7919,0.73976,0.73553,0.12916,968.620404,64.46066,3.0535664 10/13/2014,50.135354,0.6879,0.6165,0.7841,0.73434,0.73396,0.128,969.045667,65.23712,3.03627043 10/14/2014,50.4415,0.6883,0.6194,0.79,0.74201,0.73794,0.12898,973.9357,66.281,3.085661 10/15/2014,49.561407,0.6878,0.6124,0.7789,0.73285,0.73546,0.12716,967.409378,64.72659,2.97835782 10/16/2014,49.644713,0.6836,0.6128,0.7807,0.73536,0.73427,0.12749,967.138967,64.32968,2.96142931 10/17/2014,49.824684,0.6858,0.6147,0.7839,0.7353,0.73326,0.12795,970.719048,64.43658,2.91602961 10/20/2014,49.089079,0.6862,0.6155,0.7813,0.73719,0.7305,0.12757,974.210783,64.22286,2.851745 10/21/2014,49.496016,0.6906,0.6186,0.7864,0.74557,0.73499,0.12844,981.97768,64.17024,2.846768 10/22/2014,49.97856,0.6941,0.6211,0.7908,0.75198,0.73788,0.12924,981.596316,64.52928,2.910144 10/23/2014,50.463998,0.6928,0.6192,0.7906,0.74872,0.73036,0.12921,973.892704,64.11766,2.84386726 10/24/2014,50.538879,0.6946,0.6188,0.7893,0.74629,0.72969,0.12902,971.636193,63.77544,2.78812332 10/27/2014,50.8095,0.6931,0.6179,0.7875,0.74837,0.73042,0.12875,965.96325,63.23625,2.79145125 10/28/2014,50.681862,0.6954,0.6173,0.7854,0.74814,0.72602,0.12843,964.879608,62.75346,2.76193764 10/29/2014,50.993397,0.6964,0.6195,0.7917,0.75589,0.72701,0.12954,959.659155,62.70264,2.81995623 10/30/2014,51.031044,0.7005,0.6206,0.7929,0.75109,0.72604,0.12965,950.568165,62.32194,2.96655606 10/31/2014,51.25086,0.7025,0.6211,0.7983,0.74702,0.71088,0.13063,936.358002,61.86825,3.01781349 11/3/2014,50.764032,0.6477,0.5692,0.8012,0.74693,0.7025,0.13093,933.902756,61.61228,2.97237188 11/4/2014,50.23491,0.6766,0.5769,0.797,0.7403,0.7017,0.13032,931.20683,60.8908,2.91702 11/6/2014,50.708275,0.6933,0.591,0.8081,0.74561,0.7014,0.1322,922.785552,61.17317,3.16169125 11/7/2014,50.309714,0.6901,0.5922,0.8029,0.7343,0.70038,0.13114,945.792113,60.13721,3.22003045 11/11/2014,50.090216,0.6963,0.6209,0.8017,0.73423,0.69232,0.13087,933.443361,59.96716,3.2573071 11/12/2014,50.37864,0.6666,0.6137,0.804,0.73354,0.69633,0.13123,934.7304,60.1392,3.3799356 11/13/2014,50.308416,0.699,0.6208,0.8016,0.73083,0.69231,0.13085,931.90008,59.95968,3.350688 11/14/2014,50.323152,0.6987,0.6151,0.7984,0.72536,0.68651,0.13026,949.098,59.72032,3.23352 11/17/2014,51.48512,0.6996,0.6186,0.8032,0.73426,0.68864,0.1311,953.053024,59.91872,3.38942368 11/18/2014,51.220317,0.6957,0.6146,0.7977,0.72571,0.6827,0.13033,954.910716,58.2321,3.44295297 11/19/2014,50.990366,0.6865,0.6101,0.7966,0.71993,0.67522,0.13013,942.122888,57.7535,3.49802992 11/20/2014,51.1038,0.6875,0.6134,0.7975,0.7152,0.67449,0.13018,952.047525,56.782,3.5177725 11/21/2014,51.727039,0.7001,0.6209,0.8071,0.72466,0.68509,0.13177,969.771005,57.46552,3.478601 11/24/2014,52.110354,0.6927,0.617,0.8038,0.72243,0.67957,0.13086,962.261132,57.0698,3.26133812 11/25/2014,51.966194,0.6838,0.6163,0.8017,0.72269,0.67949,0.13062,962.825666,56.19917,3.30733318 11/26/2014,51.806084,0.6836,0.6162,0.7996,0.72256,0.6791,0.13026,957.816852,55.49224,3.38982424 11/28/2014,51.820883,0.6832,0.6157,0.8033,0.72477,0.67709,0.13069,937.756354,56.55232,3.414025 12/2/2014,51.072624,0.664,0.5811,0.8076,0.72967,0.67739,0.13131,967.730928,57.09732,3.02397744 12/3/2014,51.036809,0.6465,0.5678,0.8123,0.72995,0.67812,0.13205,982.419989,56.77977,2.95051729 12/5/2014,50.677725,0.6804,0.5811,0.8141,0.73069,0.66995,0.1323,970.692135,57.8011,2.78959506 12/8/2014,50.248491,0.6933,0.5981,0.8119,0.72643,0.67267,0.13155,977.129769,57.6449,2.83848359 12/9/2014,50.053714,0.6973,0.6108,0.8081,0.72958,0.67515,0.1306,994.819586,56.64781,2.91174592 12/11/2014,50.283737,0.701,0.6233,0.8057,0.73186,0.67899,0.13018,989.174004,56.399,2.96126978 12/12/2014,50.276625,0.6618,0.6107,0.8025,0.72738,0.67571,0.12967,981.128475,55.77375,2.87174625 12/15/2014,50.4912,0.6603,0.6124,0.804,0.73146,0.68249,0.12982,959.35692,55.878,2.9405496 12/16/2014,50.20232,0.657,0.6136,0.7994,0.7358,0.68673,0.12913,956.889794,55.1586,2.8466634 12/17/2014,51.066906,0.6581,0.6182,0.8102,0.74005,0.68288,0.13074,963.903042,55.4987,2.96136202 12/18/2014,52.057044,0.6646,0.6195,0.8139,0.73841,0.68489,0.13094,975.516123,55.10103,2.99034999 12/19/2014,52.66632,0.6658,0.6219,0.8178,0.74209,0.6842,0.13145,977.876172,55.28328,2.81069682 12/22/2014,52.655175,0.6651,0.6201,0.8175,0.74586,0.68119,0.1314,961.7397,55.263,2.481276 12/23/2014,53.026064,0.6658,0.6197,0.8216,0.74487,0.68074,0.13196,966.669912,54.96504,2.44130224 12/24/2014,53.137719,0.6649,0.6195,0.8199,0.74341,0.68066,0.1319,962.39862,54.9333,2.25866052 12/29/2014,53.129966,0.6692,0.6217,0.8227,0.7495,0.6819,0.1322,973.492683,54.95636,2.47484614 12/30/2014,53.154647,0.6733,0.6226,0.8227,0.74852,0.68854,0.13262,987.692485,57.01311,2.56460271 12/31/2014,52.637888,0.6753,0.6237,0.8266,0.75764,0.69124,0.13337,979.000242,57.28338,2.47558434 1/5/2015,50.80794,0.701,0.6713,0.838,0.75517,0.70046,0.13473,1009.67268,58.4924,2.6878012 1/6/2015,51.54489,0.696,0.6748,0.841,0.7655,0.71047,0.13536,1024.82578,59.3746,2.4913784 1/7/2015,52.010468,0.6916,0.6687,0.8446,0.76793,0.70825,0.13595,1023.156886,59.62876,2.58979698 1/9/2015,51.542176,0.6203,0.6256,0.8444,0.77499,0.71242,0.13602,1032.9123,59.61464,2.49190884 1/12/2015,52.691985,0.6888,0.6689,0.8451,0.78134,0.714,0.13621,1042.270281,59.32602,2.44749411 1/13/2015,52.883644,0.6936,0.637,0.8494,0.78406,0.72032,0.13702,1045.305616,59.28812,2.4551907 1/14/2015,51.841984,0.6912,0.6353,0.8482,0.78401,0.72291,0.13688,1042.200304,58.86508,2.6569865 1/15/2015,53.954772,0.7064,0.6482,0.8597,0.79362,0.74017,0.13892,1085.586175,59.66318,2.83236762 1/16/2015,54.410859,0.7108,0.6517,0.8649,0.80259,0.73498,0.13926,1107.461205,59.50512,2.67297345 1/20/2015,52.257065,0.7074,0.6476,0.8659,0.79555,0.72893,0.13934,1121.617588,58.79461,2.53232455 1/21/2015,52.065585,0.6964,0.6453,0.8613,0.79506,0.73013,0.13865,1113.738417,58.22388,2.53385847 1/22/2015,54.5424,0.7063,0.6568,0.88,0.81092,0.74237,0.1417,1145.98,58.872,2.580952 1/23/2015,55.295831,0.7063,0.6636,0.8923,0.82313,0.75788,0.1433,1154.707584,58.80257,2.641208 1/26/2015,57.824,0.7051,0.6618,0.8896,0.82336,0.75121,0.14224,1139.93344,58.2688,2.60243584 1/27/2015,57.010056,0.6974,0.6563,0.8787,0.81378,0.74547,0.14074,1135.579158,56.85189,2.59462536 1/28/2015,57.43938,0.6991,0.6548,0.886,0.81696,0.7538,0.14181,1138.05814,56.8812,2.5603628 1/29/2015,57.571178,0.6858,0.6527,0.8834,0.8076,0.74682,0.14143,1110.672318,56.71428,2.54401532 1/30/2015,58.615515,0.6889,0.654,0.8861,0.80947,0.7537,0.14171,1137.566319,56.88762,2.37545688 2/2/2015,56.88255,0.6885,0.6524,0.8819,0.79926,0.74992,0.14086,1123.902179,56.26522,2.32248365 2/3/2015,58.81863,0.6944,0.6548,0.871,0.79379,0.74103,0.13922,1097.91292,55.5698,2.3231312 2/4/2015,60.8139,0.6978,0.6771,0.882,0.813,0.75193,0.14113,1119.5667,56.448,2.4066252 2/6/2015,61.55667,0.697,0.6649,0.8838,0.81095,0.74189,0.14152,1090.644552,56.5632,2.25740196 2/9/2015,61.523712,0.627,0.6293,0.8832,0.8066,0.74431,0.14135,1094.311296,56.5248,2.29305216 2/10/2015,62.18432,0.6286,0.6226,0.8833,0.81091,0.73972,0.14151,1089.594715,56.26621,2.3266122 2/11/2015,62.740353,0.6487,0.6497,0.8823,0.80391,0.73242,0.14133,1075.373709,56.4672,2.51217279 2/12/2015,62.426511,0.6886,0.6674,0.8769,0.78944,0.73648,0.1404,1071.554262,56.1216,2.51766759 2/13/2015,62.80659,0.6826,0.6476,0.8778,0.80039,0.73882,0.14064,1079.483328,56.88144,2.39569176 2/17/2015,63.119889,0.6852,0.6464,0.8763,0.79508,0.73483,0.14009,1060.226607,56.60898,2.5815798 2/25/2015,62.687844,0.6942,0.6505,0.8802,0.80089,0.74056,0.14061,1060.641,56.86092,2.81127078 2/26/2015,64.34958,0.6966,0.6577,0.893,0.81377,0.7478,0.14268,1080.07457,57.4199,2.7810699 2/27/2015,65.82147,0.6977,0.6556,0.8931,0.81347,0.74654,0.14246,1083.491058,57.33702,2.46022257 3/2/2015,59.348054,0.6792,0.6471,0.8942,0.81234,0.74434,0.14255,1079.147386,57.31822,2.539528 3/3/2015,59.23576,0.6995,0.6566,0.8948,0.81614,0.7473,0.1426,1077.106552,56.99876,2.61881116 3/4/2015,60.275628,0.6954,0.6747,0.9026,0.82231,0.75417,0.14393,1083.426884,57.3151,2.94121236 3/6/2015,61.065483,0.6906,0.6605,0.9223,0.83939,0.76346,0.14725,1076.591567,57.27483,2.6571463 3/9/2015,58.966785,0.6308,0.6347,0.9215,0.82852,0.76061,0.14709,1075.584015,56.85655,2.50417625 3/11/2015,61.541171,0.6554,0.6534,0.9481,0.84175,0.78065,0.1514,1095.349411,57.17043,2.6442509 3/12/2015,61.166515,0.6711,0.6555,0.9403,0.83478,0.77528,0.15014,1084.852319,56.70009,2.65098779 3/13/2015,62.030297,0.7277,0.6842,0.9527,0.84412,0.7848,0.15222,1103.683896,57.54308,2.56419205 3/16/2015,61.209678,0.723,0.6807,0.9462,0.83599,0.78012,0.15115,1092.681222,57.15048,2.51840592 3/17/2015,60.947124,0.7188,0.6796,0.9436,0.83587,0.77747,0.15099,1084.734252,56.89908,2.6321722 3/18/2015,58.5212,0.7158,0.6683,0.92,0.81483,0.76593,0.14768,1074.2012,55.2,2.544628 3/19/2015,58.149636,0.7175,0.6762,0.9382,0.83969,0.77675,0.15141,1098.801076,55.91672,2.66739642 3/20/2015,55.969552,0.7188,0.6703,0.9242,0.82302,0.76966,0.14893,1092.903468,54.15812,2.60920144 3/23/2015,53.052752,0.7199,0.6694,0.9136,0.81969,0.7631,0.14701,1086.763744,53.4456,2.45429504 3/24/2015,52.662962,0.7211,0.67,0.9154,0.82856,0.7644,0.14751,1092.328512,52.81858,2.54270658 3/25/2015,52.699596,0.7151,0.6649,0.9116,0.82786,0.7629,0.14672,1089.790452,52.50816,2.4991514 3/26/2015,54.337832,0.7192,0.6704,0.9188,0.8294,0.77081,0.14791,1106.979428,52.64724,2.51190732 3/27/2015,54.73068,0.7116,0.6705,0.9183,0.83225,0.77085,0.14773,1100.628465,51.97578,2.41724109 3/30/2015,55.955427,0.7065,0.6706,0.9229,0.8353,0.76877,0.14867,1094.624003,51.59011,2.41209144 3/31/2015,56.029134,0.7088,0.679,0.9318,0.83969,0.77559,0.15028,1102.850526,51.06264,2.44485684 4/2/2015,53.179126,0.6838,0.6535,0.9191,0.83889,0.76775,0.14832,1105.318851,47.60938,2.37798743 4/8/2015,50.489268,0.6781,0.6655,0.9276,0.8502,0.77218,0.14954,1115.503932,46.8438,2.47632096 4/9/2015,50.995116,0.6198,0.6296,0.9381,0.85862,0.77804,0.15117,1120.851261,47.37405,2.46570204 4/13/2015,51.1002,0.7183,0.69,0.9463,0.86154,0.78771,0.15224,1134.500144,47.69352,2.41997299 4/14/2015,51.795815,0.7159,0.6899,0.9385,0.85785,0.7861,0.15109,1119.42403,48.802,2.39345655 4/15/2015,52.906427,0.7187,0.6898,0.9359,0.8533,0.78564,0.15084,1125.494622,48.76039,2.41602585 4/16/2015,53.890107,0.7251,0.6884,0.9293,0.85354,0.78083,0.14995,1113.812515,48.50946,2.39712935 4/17/2015,53.793502,0.7202,0.6876,0.9254,0.85399,0.77828,0.14931,1114.385188,48.30588,2.43879916 4/20/2015,55.961817,0.7194,0.6907,0.9313,0.86296,0.78134,0.15017,1113.732357,48.52073,2.37164858 4/21/2015,57.67848,0.7183,0.6895,0.9315,0.85983,0.7784,0.1502,1120.044915,48.53115,2.3906016 4/22/2015,58.592016,0.723,0.6917,0.9324,0.86364,0.77758,0.15051,1106.880012,49.97664,2.42200224 4/23/2015,59.582311,0.7186,0.6886,0.9239,0.85375,0.77258,0.14907,1103.108883,50.07538,2.35853192 4/24/2015,58.691685,0.7195,0.6904,0.9195,0.85189,0.77287,0.14844,1084.0905,51.95175,2.3541039 4/27/2015,60.88992,0.7215,0.6914,0.9184,0.85587,0.77148,0.14765,1104.05456,53.08352,2.28029536 4/28/2015,60.354568,0.7306,0.6913,0.9106,0.85102,0.76599,0.14675,1103.802002,53.99858,2.30691404 4/29/2015,59.451376,0.7194,0.6807,0.8986,0.84115,0.755,0.14495,1082.552406,52.02894,2.29143 4/30/2015,58.839333,0.7043,0.6732,0.8911,0.83098,0.74644,0.14365,1055.392107,51.59469,2.28380019 5/5/2015,54.33732,0.7102,0.6712,0.894,0.82593,0.74586,0.14405,1066.84596,52.299,2.4675294 5/6/2015,53.644731,0.6859,0.6628,0.8813,0.81579,0.73767,0.14212,1050.721112,52.26109,2.41996167 5/8/2015,54.542994,0.6745,0.6624,0.8921,0.81967,0.74503,0.14367,1060.162719,52.27706,2.46852991 5/11/2015,53.784,0.6563,0.6531,0.8964,0.82135,0.74649,0.14437,1061.310708,53.15652,2.55142332 5/13/2015,51.908458,0.7145,0.6648,0.8807,0.80086,0.73913,0.14194,1070.711025,53.28235,2.52100375 5/14/2015,52.329844,0.7082,0.6639,0.8764,0.80371,0.73542,0.14132,1070.207096,52.05816,2.51929944 5/15/2015,52.11301,0.7022,0.6614,0.8735,0.80461,0.73211,0.14075,1069.8628,51.79855,2.583813 5/18/2015,50.358924,0.7062,0.6652,0.8838,0.81419,0.7366,0.14246,1083.105738,52.40934,2.6597961 5/19/2015,50.934951,0.7098,0.6713,0.8969,0.82428,0.74316,0.1445,1083.329634,53.18617,2.75491804 5/20/2015,51.100366,0.7099,0.6739,0.9014,0.82221,0.74282,0.14525,1090.51372,53.00232,2.68950718 5/21/2015,51.20431,0.7106,0.6733,0.8999,0.8227,0.74352,0.14522,1084.253514,53.00411,2.63769689 5/22/2015,51.79232,0.7109,0.6794,0.908,0.83305,0.74717,0.14652,1095.23868,53.6628,2.6170376 5/26/2015,52.732134,0.7112,0.6812,0.9198,0.83542,0.74705,0.14826,1092.07854,55.92384,2.59264026 5/27/2015,52.531488,0.7089,0.6789,0.9171,0.82954,0.74159,0.14788,1089.597339,56.40165,2.5898904 5/28/2015,52.401758,0.6986,0.6774,0.9134,0.82575,0.73691,0.14729,1085.48456,56.1741,2.52929594 5/29/2015,52.213422,0.6958,0.6751,0.9098,0.82097,0.73278,0.14678,1083.189684,55.58878,2.40405552 6/1/2015,52.1664,0.68,0.6308,0.9152,0.82434,0.73336,0.14764,1088.35584,56.55936,2.37933696 6/2/2015,51.74536,0.6892,0.6533,0.8968,0.80615,0.7226,0.14468,1069.891368,55.42224,2.3532032 6/3/2015,51.378117,0.7117,0.6695,0.8869,0.80297,0.71395,0.14311,1051.127273,55.51994,2.33689281 6/4/2015,51.69738,0.6948,0.6761,0.8898,0.79895,0.71552,0.14351,1047.196722,56.32434,2.30422608 6/5/2015,52.287378,0.7023,0.6659,0.8998,0.80978,0.71626,0.14505,1054.511612,57.04732,2.3007886 6/8/2015,51.5862,0.6724,0.6615,0.8856,0.78834,0.71125,0.14269,1039.756392,56.05848,2.35055952 6/10/2015,51.95572,0.6358,0.6252,0.883,0.79694,0.71973,0.14229,1047.29098,56.6003,2.576594 6/11/2015,52.640658,0.656,0.6556,0.8883,0.80127,0.71967,0.14311,1049.979483,57.56184,2.54995398 6/15/2015,54.120234,0.6882,0.6584,0.8862,0.79329,0.71816,0.14274,1051.414266,57.42576,2.538963 6/16/2015,54.34457,0.6893,0.6623,0.889,0.79486,0.72066,0.14319,1050.86023,56.9849,2.6098373 6/17/2015,53.90784,0.6835,0.6603,0.882,0.78898,0.7146,0.14202,1045.6551,55.8306,2.5866414 6/18/2015,53.771418,0.6864,0.6596,0.8802,0.79466,0.71554,0.14179,1057.947588,55.10052,2.51640378 6/19/2015,53.946316,0.6844,0.6604,0.8809,0.79599,0.7179,0.14191,1057.317843,54.43962,2.47436001 6/23/2015,55.14489,0.6929,0.6678,0.8955,0.81059,0.72249,0.14428,1055.463165,55.78965,2.534265 6/25/2015,55.159244,0.6906,0.664,0.8924,0.80378,0.72182,0.14373,1046.936908,56.04272,2.489796 6/26/2015,55.299278,0.6852,0.6631,0.8951,0.80167,0.7227,0.14415,1052.207952,55.76473,2.47727876 6/29/2015,54.8774,0.6834,0.6612,0.89,0.79098,0.72627,0.14335,1050.0487,54.735,2.492534 6/30/2015,54.978417,0.6917,0.6664,0.8979,0.80483,0.73281,0.14482,1052.653065,55.22085,2.4907746 7/7/2015,54.041031,0.6767,0.6707,0.9081,0.80353,0.74112,0.14624,1049.091606,50.39955,2.47965786 7/8/2015,53.833964,0.6763,0.6587,0.9028,0.79416,0.7479,0.1454,1045.740324,48.11924,2.4447824 7/9/2015,54.347878,0.6199,0.6271,0.9061,0.79897,0.74675,0.14594,1050.559523,48.9294,2.43278789 7/10/2015,53.843696,0.6414,0.63,0.8962,0.79362,0.72995,0.14437,1042.943788,48.3948,2.46284722 7/13/2015,54.89451,0.6732,0.6697,0.909,0.80403,0.73632,0.14638,1052.60382,49.086,2.6174655 7/14/2015,54.9582,0.6771,0.6673,0.9084,0.79537,0.73606,0.1463,1050.164904,48.69024,2.67778152 7/15/2015,55.205896,0.6739,0.6689,0.9134,0.79877,0.7379,0.14712,1049.90763,48.68422,2.66566656 7/16/2015,55.534644,0.6807,0.6728,0.9196,0.80019,0.74075,0.1481,1053.300644,49.01468,2.66766764 7/17/2015,55.884168,0.6809,0.6751,0.9234,0.80471,0.74418,0.14871,1047.264876,49.21722,2.62605726 7/20/2015,56.12085,0.6809,0.6739,0.9238,0.80169,0.74335,0.14877,1012.9467,49.8852,2.62008156 7/21/2015,55.306007,0.6783,0.6705,0.9143,0.78939,0.73791,0.14724,1006.872875,50.74365,2.63455545 7/22/2015,55.0464,0.675,0.6701,0.915,0.79324,0.73812,0.14736,1001.2296,48.7695,2.647095 7/23/2015,54.672424,0.6697,0.6653,0.9106,0.78163,0.73484,0.14662,993.19142,47.8065,2.6525778 7/24/2015,54.654212,0.6633,0.6641,0.9106,0.78001,0.7357,0.1467,1000.849566,47.8065,2.56388536 7/27/2015,54.613008,0.6556,0.6589,0.9018,0.7728,0.73179,0.14523,986.551164,47.07396,2.55056094 7/28/2015,54.60764,0.6633,0.6631,0.9041,0.77632,0.73179,0.14561,990.423468,47.82689,2.59973955 7/29/2015,54.869808,0.6641,0.6651,0.9104,0.78579,0.73453,0.14663,998.57224,48.88848,2.64116144 7/30/2015,55.092381,0.6672,0.6651,0.9147,0.78302,0.73685,0.1473,995.888772,50.49144,2.60451678 7/31/2015,54.80608,0.6651,0.6634,0.9104,0.77794,0.7348,0.14661,997.61632,49.98096,2.51889472 8/4/2015,54.30371,0.7129,0.6837,0.919,0.78855,0.73894,0.148,999.5963,51.3721,2.5908448 8/5/2015,54.390508,0.7077,0.6713,0.9169,0.78133,0.73419,0.14766,994.864007,52.53837,2.61820795 8/6/2015,54.377973,0.682,0.6544,0.9153,0.78501,0.73382,0.14741,997.265115,53.17893,2.53007226 8/7/2015,54.288572,0.6707,0.6687,0.9118,0.78114,0.7341,0.14687,997.64597,52.97558,2.55477242 8/10/2015,55.076175,0.6435,0.6314,0.9075,0.78031,0.72825,0.14616,1002.342825,52.272,2.58864375 8/12/2015,54.052752,0.6624,0.6519,0.8961,0.75277,0.72152,0.14032,1007.637567,50.45043,2.6112354 8/13/2015,53.906648,0.66,0.6421,0.8968,0.76413,0.72074,0.14016,1000.02168,50.57952,2.61497912 8/14/2015,54.012,0.6643,0.6397,0.9002,0.76239,0.72399,0.14083,1003.786014,51.49144,2.54450532 8/17/2015,52.925301,0.6654,0.6414,0.9027,0.76321,0.72576,0.14118,1008.94779,51.00255,2.49524334 8/18/2015,53.06857,0.666,0.6462,0.907,0.76528,0.72905,0.14184,1013.76297,50.9734,2.4581514 8/19/2015,52.342432,0.6608,0.6408,0.8992,0.75851,0.72641,0.1406,1019.584896,49.9056,2.4566144 8/20/2015,51.587904,0.6527,0.6343,0.8896,0.75062,0.72086,0.13924,1024.99712,49.3728,2.41117184 8/21/2015,50.733614,0.6429,0.6236,0.8782,0.73503,0.71945,0.13746,1019.388214,48.7401,2.36885668 8/24/2015,48.6239,0.6158,0.6102,0.8606,0.71786,0.72674,0.13438,994.087666,47.07482,2.267681 8/25/2015,48.97212,0.619,0.6178,0.8683,0.72628,0.73063,0.1354,990.287467,47.40918,2.34084997 8/26/2015,49.9347,0.6296,0.6286,0.8838,0.74534,0.73694,0.13789,994.504788,48.25548,2.40146136 8/27/2015,50.467775,0.6371,0.6357,0.8893,0.75029,0.73481,0.13882,1000.4625,48.46685,2.38643655 8/28/2015,51.05311,0.6412,0.6347,0.8941,0.76169,0.73455,0.13996,1013.55176,50.24842,2.3747296 8/31/2015,52.99372,0.6345,0.6319,0.892,0.75398,0.73575,0.13983,1012.35756,50.2196,2.388776 9/1/2015,52.67448,0.6927,0.6334,0.8838,0.75429,0.74037,0.13886,1007.770626,50.3766,2.42656128 9/2/2015,53.067906,0.6893,0.6523,0.8907,0.75433,0.74021,0.14013,1010.098335,50.7699,2.41833957 9/9/2015,51.280481,0.6262,0.6296,0.8923,0.75018,0.74028,0.13989,988.534555,53.00262,2.43669284 9/10/2015,50.823045,0.6459,0.6312,0.8865,0.74226,0.73499,0.13902,984.679875,53.27865,2.40126255 9/11/2015,50.44158,0.6554,0.6536,0.882,0.74466,0.73147,0.13834,977.2119,53.0082,2.3501772 9/14/2015,50.441596,0.6307,0.6282,0.8837,0.74681,0.73503,0.13877,980.11167,53.11037,2.38819925 9/15/2015,50.608422,0.6337,0.633,0.8874,0.74805,0.73694,0.13931,980.88759,52.62282,2.42322318 9/16/2015,50.52348,0.6375,0.634,0.8856,0.753,0.73447,0.13901,991.446912,51.89616,2.37633048 9/17/2015,49.785285,0.6273,0.6254,0.8745,0.75004,0.72865,0.13737,989.505495,51.2457,2.34059925 9/18/2015,50.395055,0.6377,0.6322,0.8849,0.76089,0.73752,0.13904,1008.104627,51.94363,2.32330495 9/21/2015,51.29838,0.6373,0.6339,0.8937,0.76084,0.74129,0.14031,1012.955328,52.37082,2.31620229 9/22/2015,51.592841,0.6374,0.6344,0.8993,0.76191,0.74807,0.14091,1011.496668,52.69898,2.32567973 9/23/2015,51.14574,0.6261,0.627,0.894,0.75059,0.74334,0.14005,1010.4882,51.6732,2.3143872 9/24/2015,50.871742,0.6255,0.6261,0.8903,0.74644,0.74154,0.13948,1027.361685,51.45934,2.2818389 9/25/2015,50.65096,0.6274,0.6266,0.893,0.74755,0.74057,0.1401,1023.5566,51.6154,2.2731315 9/28/2015,49.877552,0.6216,0.6225,0.8894,0.74418,0.7416,0.13964,1006.75633,51.40732,2.34321324 9/29/2015,49.54397,0.6209,0.6226,0.889,0.73953,0.7424,0.13967,1002.28527,51.0286,2.2497034 9/30/2015,49.244288,0.6278,0.629,0.8947,0.75475,0.74632,0.14075,997.671023,51.17684,2.21411409 10/8/2015,47.608792,0.6728,0.6571,0.8869,0.76549,0.73943,0.13958,1010.187969,50.73068,2.16155268 10/9/2015,47.286284,0.627,0.6273,0.8804,0.76944,0.73206,0.13875,1018.209012,50.79908,2.08364268 10/12/2015,46.361864,0.6655,0.6512,0.8804,0.76956,0.73338,0.13923,1024.65354,50.97516,2.1442142 10/13/2015,46.5764,0.6368,0.6267,0.8788,0.76444,0.73395,0.13859,1027.176592,50.70676,2.139878 10/14/2015,45.898456,0.6363,0.6322,0.8716,0.75982,0.73344,0.13729,1032.087708,49.59404,2.12382772 10/15/2015,46.458576,0.6437,0.6377,0.8784,0.77733,0.73894,0.13843,1039.23504,49.36608,2.18888496 10/16/2015,46.603144,0.6401,0.6366,0.8813,0.7803,0.73772,0.13869,1037.55449,49.17654,2.09731774 10/19/2015,46.677176,0.6398,0.6357,0.8827,0.78734,0.73866,0.13882,1033.456333,49.25466,2.13975307 10/20/2015,45.8328,0.6399,0.6338,0.8814,0.77946,0.73545,0.13883,1036.561656,48.9177,2.1576672 10/21/2015,45.823524,0.6359,0.6325,0.8819,0.77889,0.73535,0.13891,1029.336042,47.71079,2.08004934 10/22/2015,46.67537,0.6489,0.6456,0.9002,0.79069,0.74587,0.14158,1049.67821,48.34074,2.10565782 10/23/2015,47.049984,0.6555,0.6494,0.9076,0.80689,0.74722,0.14293,1056.85482,48.5566,2.05580476 10/26/2015,46.734224,0.6555,0.6495,0.9043,0.79744,0.74676,0.14236,1051.737072,48.38005,1.93583501 10/27/2015,46.736748,0.6508,0.6478,0.9054,0.80057,0.75129,0.14252,1056.493152,47.71458,1.87082802 10/28/2015,47.399412,0.6513,0.6528,0.9154,0.80962,0.75593,0.14398,1058.29394,47.50926,1.92060074 10/29/2015,47.11692,0.6443,0.6489,0.911,0.79746,0.75208,0.14331,1043.97867,46.461,1.915833 10/30/2015,47.15634,0.6485,0.6488,0.9086,0.79659,0.75323,0.14382,1037.721146,45.97516,1.76077594 11/2/2015,47.79567,0.6809,0.6482,0.9078,0.79849,0.75177,0.14325,1029.299952,45.48078,1.74542706 11/3/2015,48.09888,0.7201,0.6826,0.912,0.80498,0.75333,0.14394,1019.42448,44.4144,1.7333472 11/5/2015,48.264564,0.7074,0.6704,0.9188,0.80701,0.75468,0.14478,1014.281696,44.01052,1.92497788 11/6/2015,48.60342,0.6889,0.6607,0.9311,0.81535,0.75607,0.14654,1014.71278,43.94792,2.02355963 11/9/2015,48.74248,0.6253,0.6251,0.9302,0.80358,0.75515,0.14619,1016.066762,43.34732,1.976675 11/11/2015,48.690148,0.6573,0.6555,0.9308,0.80611,0.75772,0.14622,1011.090808,43.37528,1.9681766 11/12/2015,48.394784,0.6542,0.6438,0.9248,0.79835,0.75424,0.1452,1003.59296,43.0032,1.8625472 11/13/2015,48.63768,0.6616,0.6521,0.9282,0.79779,0.7573,0.1457,1006.085262,43.1613,1.86503226 11/16/2015,49.063994,0.6641,0.6579,0.9358,0.79716,0.7597,0.1469,1013.246808,43.60828,2.00186336 11/17/2015,49.479336,0.6683,0.6598,0.9396,0.80287,0.76113,0.14732,1005.65388,43.78536,1.92552228 11/18/2015,49.466013,0.6671,0.6601,0.9381,0.80034,0.75876,0.14694,1004.451813,42.87117,1.96822761 11/19/2015,49.300272,0.6702,0.6594,0.9316,0.80197,0.7582,0.14595,1008.186836,42.20148,1.99949308 11/20/2015,49.97076,0.6799,0.6649,0.9393,0.81371,0.76484,0.14713,1012.574793,42.2685,2.02907586 11/23/2015,49.934022,0.6761,0.6634,0.9402,0.81151,0.76536,0.14715,1005.243036,42.309,2.01099378 11/24/2015,50.043096,0.6817,0.6662,0.9396,0.81439,0.76678,0.14707,1010.68074,42.00012,1.98180432 11/25/2015,50.1189,0.6826,0.6699,0.9412,0.82321,0.76718,0.14731,1008.138144,41.60104,1.93567192 11/27/2015,50.243797,0.68,0.6677,0.9439,0.81862,0.76878,0.14764,998.127055,41.62599,1.92791575 11/30/2015,50.31179,0.6841,0.6709,0.9466,0.81749,0.76884,0.14794,1007.911282,40.98778,1.97631148 12/1/2015,49.97817,0.6893,0.6333,0.9405,0.81211,0.76544,0.14697,1005.667245,40.0653,2.01953565 12/2/2015,49.968984,0.6783,0.6466,0.9421,0.8091,0.76442,0.14723,992.69077,38.53189,2.04699488 12/3/2015,48.470884,0.7247,0.6805,0.9142,0.78498,0.74562,0.14288,970.980962,37.39078,1.93207028 12/8/2015,48.126802,0.6612,0.6406,0.9181,0.779,0.74678,0.14305,986.920776,35.98952,1.81636904 12/10/2015,47.85704,0.6482,0.6294,0.914,0.77358,0.75175,0.14196,979.42412,35.3718,1.7441862 12/11/2015,47.613698,0.659,0.6519,0.9097,0.77126,0.75211,0.14097,977.718269,34.47763,1.61035094 12/14/2015,47.230335,0.6589,0.6455,0.9095,0.76776,0.75156,0.14083,963.94267,34.47005,1.5343265 12/15/2015,47.715968,0.658,0.6508,0.9148,0.773,0.7519,0.14158,970.804056,34.67092,1.504846 12/16/2015,47.900228,0.6628,0.6513,0.9164,0.7791,0.74987,0.14158,982.674048,34.365,1.53845232 12/17/2015,48.143244,0.6584,0.6512,0.9237,0.78274,0.75369,0.14247,970.90107,34.63875,1.61388864 12/18/2015,47.739976,0.6603,0.6511,0.9202,0.77777,0.7595,0.14198,981.16325,35.61174,1.56397192 12/21/2015,46.350558,0.6587,0.6506,0.9162,0.77794,0.75602,0.14138,988.03008,36.1899,1.56285396 12/22/2015,46.159308,0.6604,0.65,0.9126,0.77793,0.75375,0.14087,978.699618,36.32148,1.59139188 12/23/2015,46.2782,0.6628,0.6524,0.9164,0.78117,0.7579,0.14148,981.0062,36.47272,1.48896672 12/24/2015,46.179623,0.6626,0.649,0.9121,0.7811,0.7573,0.14084,981.51081,36.57521,1.39405364 12/29/2015,46.504324,0.6681,0.6483,0.9158,0.78291,0.76008,0.14119,979.090938,38.0057,2.16760702 12/30/2015,46.343768,0.6665,0.6467,0.9148,0.78002,0.75886,0.14095,971.005312,39.3364,2.07641304 12/31/2015,46.50129,0.6711,0.6493,0.921,0.78397,0.76606,0.14177,977.2731,39.9714,2.1297204 1/4/2016,45.338352,0.6741,0.6499,0.9232,0.7773,0.77285,0.14129,992.079952,40.52848,2.20247824 1/6/2016,45.860544,0.6486,0.6491,0.9276,0.77482,0.78291,0.1415,1014.488292,40.72164,2.17976724 1/7/2016,45.319192,0.6735,0.6672,0.9148,0.76229,0.77743,0.13879,1014.485756,39.3364,2.14630376 1/8/2016,45.39888,0.675,0.6674,0.9153,0.76409,0.78077,0.13878,1010.628495,38.99178,2.26033335 1/11/2016,44.976756,0.6922,0.6513,0.9209,0.76121,0.78202,0.14014,1007.64878,38.76989,2.32610131 1/12/2016,44.83428,0.6955,0.6577,0.921,0.76094,0.78281,0.14012,1000.72176,38.5899,2.1943746 1/13/2016,44.618482,0.6395,0.6399,0.9194,0.76378,0.78125,0.13981,1005.446646,37.87928,2.11673462 1/14/2016,44.735783,0.6428,0.6405,0.9203,0.75851,0.7795,0.13964,992.433114,37.36418,2.01775775 1/15/2016,44.358083,0.6285,0.6366,0.9163,0.75526,0.78285,0.13875,997.740744,37.38504,1.99900008 1/19/2016,42.961248,0.6334,0.6382,0.9168,0.76021,0.77934,0.13948,996.937488,38.59728,2.03107872 1/20/2016,43.329858,0.6343,0.6386,0.9182,0.75646,0.78504,0.13929,1010.864744,38.65622,1.96669258 1/21/2016,43.469492,0.6437,0.642,0.9196,0.75757,0.78126,0.14051,1012.66352,38.07144,2.02652252 1/22/2016,43.869357,0.6503,0.6476,0.9261,0.77166,0.77968,0.14063,1016.811495,38.34054,2.05279326 1/25/2016,44.361421,0.641,0.6446,0.9217,0.77186,0.7792,0.14028,1021.15143,38.15838,1.97363621 1/26/2016,44.068,0.6443,0.6448,0.92,0.76413,0.77693,0.14019,1030.3172,37.72,2.050496 1/27/2016,44.07318,0.645,0.6408,0.918,0.76356,0.77347,0.13978,1032.72246,38.2806,2.0548512 1/28/2016,43.96821,0.6475,0.6402,0.9141,0.75638,0.76932,0.13903,1019.523153,37.93515,1.93450983 1/29/2016,44.447662,0.6541,0.6484,0.9233,0.77003,0.7623,0.14037,1032.443293,38.22462,2.07899461 2/2/2016,43.59208,0.6446,0.6411,0.9158,0.75868,0.76335,0.13912,1033.947358,38.09728,1.86374458 2/3/2016,43.27383,0.6712,0.6587,0.9006,0.73857,0.76401,0.13771,1029.052578,37.73514,1.85442546 2/5/2016,44.039268,0.6647,0.6468,0.8962,0.74835,0.76678,0.13675,1051.60108,37.6404,1.87001092 2/16/2016,46.103274,0.6381,0.6388,0.8973,0.73763,0.78663,0.13777,1077.154812,39.21201,1.72164951 2/17/2016,46.534686,0.6457,0.6405,0.8987,0.73241,0.78772,0.1377,1086.07895,39.99215,1.71876375 2/18/2016,46.45548,0.6445,0.6418,0.9003,0.73366,0.79489,0.1385,1108.152261,40.33344,1.68680208 2/19/2016,45.8235,0.6424,0.6394,0.8985,0.72782,0.79799,0.13794,1102.2798,40.52235,1.62475755 2/22/2016,46.123829,0.6552,0.6479,0.9067,0.73453,0.80305,0.13908,1095.864821,44.24696,1.66968805 2/23/2016,46.95405,0.6536,0.6449,0.9075,0.7371,0.80963,0.13921,1113.366375,43.83225,1.65891 2/24/2016,46.9436,0.6534,0.6461,0.908,0.73563,0.80944,0.13883,1115.705,42.8576,1.6281348 2/25/2016,46.505424,0.6567,0.6474,0.9076,0.73263,0.80327,0.13889,1118.989116,42.6572,1.60209552 2/26/2016,46.920092,0.6519,0.6498,0.9148,0.73887,0.80259,0.13949,1119.221208,42.5382,1.52295904 2/29/2016,47.677248,0.6568,0.6539,0.9197,0.74371,0.81619,0.14041,1139.204799,42.67408,1.48660308 3/2/2016,46.170618,0.6456,0.6371,0.9201,0.74956,0.81077,0.14081,1140.905598,44.07279,1.45900257 3/3/2016,45.744524,0.671,0.6571,0.9127,0.75132,0.80274,0.14006,1153.880975,45.17865,1.42070882 3/8/2016,46.518004,0.6806,0.6683,0.9082,0.75264,0.80637,0.13927,1145.639808,58.39726,1.40671098 3/10/2016,46.74657,0.6845,0.6534,0.8945,0.74333,0.79014,0.13812,1138.027625,53.40165,1.51734035 3/11/2016,47.17323,0.6917,0.6507,0.897,0.75183,0.78784,0.13793,1120.75665,51.7569,1.5450825 3/14/2016,47.674051,0.6768,0.6541,0.9007,0.75938,0.79133,0.13859,1112.607689,51.42997,1.51632845 3/15/2016,47.773614,0.6714,0.6517,0.9002,0.75802,0.79544,0.13829,1109.388476,48.52078,1.59983544 3/16/2016,47.182064,0.6729,0.6527,0.8909,0.74668,0.79146,0.13864,1124.823613,47.75224,1.54669149 3/17/2016,46.251225,0.6758,0.6545,0.8835,0.75305,0.79305,0.13657,1111.416495,48.50415,1.6070865 3/18/2016,46.574377,0.6744,0.6529,0.8873,0.76328,0.79542,0.13686,1113.91642,50.04372,1.63103486 3/21/2016,47.68256,0.6741,0.6542,0.8896,0.76461,0.79457,0.13695,1106.44,50.79616,1.56640768 3/22/2016,47.311905,0.6795,0.6557,0.8915,0.77244,0.79335,0.13725,1112.87728,50.36975,1.5642259 3/23/2016,48.20816,0.6736,0.6541,0.8944,0.77018,0.79594,0.13745,1091.266384,51.07024,1.618864 3/24/2016,47.912946,0.6738,0.6534,0.8949,0.76722,0.79285,0.13749,1088.932218,49.04052,1.5705495 3/29/2016,45.289584,0.6756,0.6539,0.8856,0.76103,0.78547,0.13732,1100.09232,46.58256,1.567512 3/30/2016,45.10548,0.6766,0.6532,0.882,0.76615,0.78431,0.13645,1080.46764,46.3932,1.620675 3/31/2016,44.971866,0.6729,0.6517,0.8787,0.76851,0.78054,0.13605,1083.217425,46.74684,1.71768276 4/1/2016,44.887027,0.6638,0.6482,0.8779,0.76066,0.78622,0.13578,1073.32054,46.87986,1.60611805 4/5/2016,43.849728,0.6491,0.6409,0.8784,0.76043,0.79617,0.13573,1081.61784,47.8728,1.66606128 4/7/2016,44.03289,0.6757,0.6662,0.8789,0.76338,0.8122,0.13577,1090.231505,47.63638,1.70023205 4/8/2016,43.992836,0.6854,0.6695,0.8774,0.76042,0.81181,0.13551,1088.581406,47.8183,1.75550192 4/11/2016,43.42562,0.6889,0.6489,0.8764,0.76452,0.81203,0.13553,1102.406032,48.99076,1.64176012 4/13/2016,44.68706,0.6788,0.6567,0.887,0.77538,0.81129,0.13681,1102.07089,52.8652,1.7567035 4/14/2016,44.809875,0.6829,0.651,0.8875,0.76744,0.81131,0.13707,1089.752375,52.7175,1.70550875 4/15/2016,45.045546,0.6845,0.6529,0.8862,0.77321,0.81482,0.13682,1093.561938,51.75408,1.5220485 4/18/2016,44.265712,0.685,0.6541,0.8839,0.76836,0.81226,0.13645,1089.397911,53.65273,1.5609674 4/19/2016,44.495416,0.6879,0.6588,0.8804,0.77487,0.80617,0.13605,1100.667276,54.76088,1.67240784 4/20/2016,45.207164,0.6899,0.6584,0.8852,0.77971,0.80586,0.13647,1101.4101,56.74132,1.7841206 4/21/2016,45.46952,0.6855,0.6566,0.886,0.78195,0.80944,0.13659,1105.7723,61.7542,1.717954 4/22/2016,45.756624,0.6867,0.6577,0.8909,0.77921,0.79684,0.13688,1098.506427,61.20483,1.69208637 4/25/2016,45.69595,0.6847,0.6564,0.8873,0.77293,0.79806,0.13661,1098.450781,60.15894,1.75490194 4/26/2016,44.755712,0.6859,0.6547,0.8852,0.76875,0.79516,0.13616,1100.65768,58.15764,1.6610778 4/27/2016,43.85088,0.6706,0.6546,0.8832,0.7692,0.7923,0.136,1100.317056,55.55328,1.66112256 4/28/2016,43.939292,0.6717,0.6549,0.8809,0.77395,0.81469,0.13642,1115.448434,56.81805,1.66719134 4/29/2016,43.621335,0.664,0.6496,0.8733,0.76652,0.82131,0.13481,1129.639749,57.46314,1.66634373 5/4/2016,43.951545,0.6627,0.6478,0.8705,0.75387,0.8134,0.13357,1113.96144,55.1897,1.73830145 5/5/2016,44.36608,0.6546,0.6452,0.8768,0.75301,0.81748,0.13466,1120.322432,54.27392,1.79533568 5/9/2016,44.299012,0.6802,0.6611,0.8786,0.75368,0.81108,0.13456,1110.444968,50.87094,1.73110558 5/10/2016,44.343099,0.6803,0.6515,0.8793,0.7497,0.80474,0.13465,1113.053112,48.80115,1.793772 5/12/2016,44.39829,0.6942,0.6547,0.879,0.75607,0.80632,0.1347,1110.77472,48.4329,1.7624829 5/13/2016,44.786016,0.6429,0.6446,0.8844,0.75487,0.81415,0.13563,1126.23918,47.66916,1.73315868 5/16/2016,45.000396,0.6438,0.6451,0.8834,0.74886,0.81025,0.13538,1125.592944,47.43858,1.6837604 5/17/2016,45.229163,0.6474,0.6455,0.8839,0.75303,0.80985,0.13526,1130.463905,47.81899,1.732444 5/18/2016,45.707205,0.6445,0.6454,0.8915,0.75382,0.80907,0.13557,1121.95275,48.6759,1.7018735 5/19/2016,45.852862,0.6452,0.6464,0.8926,0.74892,0.81179,0.13628,1119.98985,47.39706,1.62908426 5/20/2016,45.80631,0.6437,0.6449,0.891,0.74866,0.80901,0.13622,1115.51418,47.3121,1.6130664 5/23/2016,46.61499,0.6438,0.6468,0.8913,0.75344,0.81588,0.13615,1113.349569,46.70412,1.74097629 5/24/2016,46.639296,0.6448,0.6496,0.8976,0.75265,0.81606,0.13669,1101.543696,45.59808,1.709928 5/25/2016,46.680755,0.6453,0.6505,0.8965,0.75796,0.81357,0.13659,1097.683565,44.55605,1.58366725 5/26/2016,46.974972,0.6455,0.6504,0.8934,0.75688,0.81391,0.13635,1089.76932,43.59792,1.5621099 5/27/2016,47.315223,0.6466,0.6522,0.8997,0.76304,0.81597,0.13681,1090.778286,43.99533,1.59435837 5/31/2016,46.882277,0.6499,0.652,0.8983,0.75363,0.81128,0.13645,1091.721956,42.39976,1.8792436 6/1/2016,46.822482,0.6559,0.6459,0.8939,0.74919,0.81603,0.13601,1084.282822,42.19208,2.01610206 6/6/2016,47.681098,0.6487,0.6496,0.8807,0.75471,0.81881,0.13406,1096.770938,42.2736,2.04181488 6/7/2016,47.89376,0.6776,0.6672,0.8804,0.75719,0.81992,0.13409,1095.050324,43.40372,2.01321068 6/13/2016,45.027675,0.6542,0.6536,0.8855,0.75462,0.83341,0.13444,1136.85803,43.65515,2.23455925 6/14/2016,45.025458,0.6566,0.6585,0.8923,0.7606,0.84101,0.13532,1147.247956,43.99039,2.25118367 6/15/2016,44.93786,0.6579,0.6566,0.8881,0.75701,0.8378,0.13508,1147.203175,43.16166,2.32735486 6/16/2016,45.404076,0.6559,0.6604,0.8908,0.76047,0.85445,0.13615,1138.825444,43.6492,2.32302824 6/17/2016,45.306612,0.6559,0.6572,0.8868,0.75584,0.8511,0.13492,1151.64282,43.80792,2.2892742 6/20/2016,47.599944,0.6595,0.6581,0.8841,0.76146,0.85052,0.13425,1140.40059,43.49772,2.41571484 6/21/2016,48.3888,0.6626,0.662,0.8895,0.76873,0.84912,0.13464,1127.99274,43.7634,2.45635425 6/22/2016,48.06636,0.664,0.6614,0.8852,0.76648,0.84783,0.13474,1120.857944,44.08296,2.45855448 6/23/2016,47.518065,0.668,0.6568,0.8785,0.76342,0.8272,0.13381,1104.13394,44.01285,2.35850895 6/24/2016,48.55496,0.6734,0.6652,0.9005,0.7637,0.88107,0.13576,1184.832875,44.75485,2.40730665 6/27/2016,50.90991,0.6654,0.6654,0.907,0.76719,0.8893,0.1368,1201.4122,47.8896,2.5015967 6/28/2016,50.42646,0.6674,0.6677,0.9037,0.77169,0.87951,0.13612,1185.464623,48.07684,2.5854857 6/29/2016,49.70917,0.6698,0.6668,0.8989,0.77488,0.87419,0.1356,1185.783935,47.46192,2.63395678 6/30/2016,49.810128,0.6708,0.6683,0.9004,0.78174,0.87261,0.13549,1190.23876,48.26144,2.61034964 7/1/2016,50.722371,0.6414,0.6382,0.8979,0.78411,0.87584,0.13474,1204.398165,48.66618,2.58209103 7/6/2016,54.108054,0.6568,0.6515,0.9009,0.77292,0.88919,0.135,1228.629402,49.27923,2.47801554 7/7/2016,54.30328,0.676,0.6697,0.904,0.78303,0.89707,0.13523,1229.8468,49.4488,2.5812816 7/11/2016,54.185656,0.7,0.6519,0.9043,0.7884,0.87969,0.13523,1225.68822,49.46521,2.57300479 7/12/2016,54.842706,0.6958,0.6564,0.9041,0.78756,0.86369,0.13506,1205.25571,50.72001,2.48754074 7/13/2016,55.743094,0.686,0.6696,0.9017,0.78666,0.86304,0.13464,1210.658488,52.38877,2.53305564 7/14/2016,55.981425,0.6863,0.6699,0.8993,0.79031,0.85365,0.13466,1200.772339,51.70975,2.49402869 7/15/2016,56.392826,0.6865,0.6728,0.9062,0.79931,0.86438,0.13498,1211.99719,51.47216,2.41601982 7/18/2016,57.7856,0.6854,0.6701,0.9029,0.79447,0.85055,0.13459,1199.818665,50.74298,2.53588494 7/19/2016,57.75601,0.681,0.6704,0.9074,0.79891,0.85489,0.13565,1208.665874,49.81626,2.54589218 7/20/2016,57.215858,0.6785,0.6693,0.9079,0.7958,0.84933,0.13604,1194.850874,48.66344,2.47121301 7/21/2016,56.95332,0.6798,0.6692,0.9069,0.79833,0.85711,0.13615,1207.473867,50.60502,2.45071587 7/22/2016,57.29279,0.6797,0.6704,0.911,0.80297,0.85834,0.13643,1205.00703,50.9249,2.5285716 7/25/2016,56.11615,0.6793,0.6677,0.9095,0.8001,0.85961,0.1364,1196.5382,50.65915,2.5549674 7/26/2016,57.021192,0.683,0.6701,0.9103,0.80197,0.8698,0.13648,1201.832678,50.9768,2.47191965 7/27/2016,57.106545,0.6774,0.6685,0.9043,0.79724,0.85801,0.13635,1211.834344,51.45467,2.53059312 7/28/2016,58.013928,0.6773,0.6668,0.9028,0.80285,0.85769,0.13545,1205.9151,52.8138,2.49570032 7/29/2016,57.685254,0.6801,0.6678,0.8949,0.79885,0.8768,0.13488,1209.260472,52.17267,2.63413815 8/1/2016,60.771072,0.6364,0.6343,0.8958,0.80837,0.87483,0.13469,1212.15177,53.56884,2.56879608 8/2/2016,60.4989,0.6332,0.636,0.891,0.80272,0.88299,0.13443,1214.94087,53.7273,2.4822369 8/3/2016,60.542968,0.6756,0.6558,0.8968,0.80262,0.88589,0.13488,1218.015824,53.98736,2.58493632 8/4/2016,60.567885,0.6628,0.6504,0.8985,0.80649,0.8877,0.1352,1222.993275,53.0115,2.59459845 8/8/2016,59.5254,0.69,0.6696,0.9019,0.81366,0.88029,0.13552,1204.316089,54.92571,2.54931054 8/9/2016,59.70881,0.6788,0.657,0.8995,0.81324,0.88288,0.13523,1205.986635,54.59965,2.47353505 8/11/2016,60.042573,0.7041,0.6541,0.8979,0.81631,0.88066,0.13493,1202.090562,53.24547,2.39442993 8/12/2016,60.141767,0.7031,0.6619,0.8959,0.81211,0.88409,0.13482,1196.895523,52.49974,2.41821328 8/15/2016,61.985944,0.6862,0.6657,0.8942,0.8116,0.8831,0.13458,1197.69148,52.13186,2.4201523 8/16/2016,61.272926,0.6823,0.6618,0.8866,0.81159,0.88394,0.13386,1193.576384,52.13208,2.40454786 8/17/2016,60.991272,0.6782,0.6595,0.8856,0.79908,0.88338,0.13375,1194.435288,52.33896,2.39767344 8/18/2016,60.607848,0.677,0.6576,0.8808,0.79554,0.88173,0.13308,1191.158688,51.70296,2.3900508 8/19/2016,60.67093,0.6735,0.6558,0.883,0.79017,0.88109,0.13275,1184.51801,51.6555,2.3315615 8/22/2016,58.262468,0.6737,0.6541,0.8833,0.78423,0.88052,0.13283,1182.818197,52.02637,2.41617882 8/23/2016,58.491985,0.6736,0.6544,0.8845,0.79291,0.88236,0.13301,1183.07182,52.80465,2.3994716 8/24/2016,58.90553,0.6761,0.6555,0.8878,0.79126,0.88384,0.13352,1175.562614,52.91288,2.46071526 8/25/2016,58.88356,0.675,0.6547,0.886,0.7941,0.88134,0.1331,1171.26542,52.3626,2.5347574 8/26/2016,59.605494,0.6756,0.6572,0.8931,0.80197,0.8772,0.1332,1179.945858,52.60359,2.56962732 8/29/2016,60.179554,0.6766,0.657,0.8938,0.79444,0.87693,0.13396,1182.837044,52.10854,2.63501178 8/30/2016,60.816798,0.674,0.6576,0.8974,0.80145,0.87162,0.13432,1176.590114,52.0492,2.62426682 8/31/2016,61.380738,0.6738,0.6578,0.8962,0.80394,0.8665,0.13431,1173.098914,51.35226,2.63742698 9/2/2016,61.76196,0.6262,0.6337,0.8964,0.8024,0.86207,0.13423,1187.918244,51.543,2.55823596 9/6/2016,62.56817,0.6566,0.653,0.8885,0.80388,0.8709,0.13353,1199.475,50.91105,2.50281565 9/8/2016,62.75496,0.6902,0.6692,0.888,0.81279,0.86645,0.13302,1188.4104,50.172,2.5197 9/9/2016,62.864083,0.6713,0.6553,0.8903,0.8106,0.86691,0.13331,1182.167049,49.8568,2.60038824 9/12/2016,61.855,0.7054,0.6619,0.89,0.79929,0.87403,0.13332,1181.7598,49.306,2.665016 9/13/2016,62.268144,0.6656,0.6523,0.8912,0.79614,0.86899,0.13318,1175.53736,49.016,2.735984 9/14/2016,62.329668,0.6639,0.6519,0.8889,0.78964,0.86782,0.13294,1175.961366,48.8895,2.693367 9/19/2016,65.819895,0.6742,0.6572,0.8949,0.80032,0.87802,0.13414,1175.173731,49.04052,2.65892688 9/20/2016,66.246616,0.6776,0.6586,0.8968,0.80039,0.88166,0.13419,1179.148512,49.59304,2.76366856 9/21/2016,66.098052,0.6814,0.6604,0.8937,0.79784,0.89073,0.13447,1193.241429,49.77909,2.80675422 9/22/2016,66.192318,0.6819,0.6579,0.8922,0.80878,0.88541,0.13352,1192.933854,50.4093,2.79990204 9/23/2016,66.18644,0.6791,0.6554,0.8908,0.80809,0.88191,0.13359,1191.498448,50.50836,2.70099468 9/26/2016,66.645,0.6785,0.6531,0.8886,0.80205,0.88563,0.13303,1188.90237,50.614656,2.70632016 9/27/2016,67.61136,0.6836,0.6557,0.8915,0.81277,0.8878,0.13387,1183.30578,50.77984,2.70258225 9/28/2016,68.101685,0.6858,0.6559,0.8915,0.81272,0.88536,0.13382,1178.15291,50.9938,2.65497615 9/29/2016,69.11487,0.6803,0.6531,0.891,0.81086,0.88183,0.13345,1176.44967,51.4998,2.6259552 9/30/2016,70.273395,0.6813,0.6526,0.8901,0.80785,0.87772,0.1333,1171.255887,51.421077,2.52690489 10/10/2016,76.178822,0.6829,0.6529,0.8977,0.80985,0.86645,0.1337,1130.787805,51.240716,2.81922685 10/11/2016,77.062346,0.6989,0.6503,0.9047,0.80745,0.87407,0.13438,1133.40816,52.155955,2.84084847 10/13/2016,78.737064,0.6846,0.6548,0.9044,0.79626,0.87214,0.13463,1137.816596,52.654168,2.85672828 10/14/2016,80.513355,0.6945,0.6555,0.9113,0.80493,0.87497,0.13521,1140.063639,53.356615,2.85191335 10/17/2016,89.0918,0.6935,0.6543,0.9091,0.79898,0.87502,0.135,1141.693235,53.491444,2.87657422 10/18/2016,90.195728,0.6981,0.6572,0.9107,0.80642,0.87684,0.13505,1149.75875,53.576481,2.92872013 10/19/2016,90.346282,0.7036,0.6571,0.9113,0.81142,0.88093,0.1354,1156.649299,53.876056,2.86412477 10/20/2016,90.52095,0.6978,0.6572,0.915,0.81163,0.8802,0.13565,1158.1704,54.717,2.8281735 10/21/2016,90.850243,0.699,0.659,0.9187,0.80957,0.88524,0.136,1163.496802,54.488097,2.6522869 10/24/2016,91.9,0.6994,0.6596,0.919,0.81252,0.88211,0.13563,1162.02036,54.44156,2.5319369 10/25/2016,93.6768,0.7022,0.6609,0.9184,0.81036,0.8812,0.1354,1169.922208,56.233632,2.45249536 10/26/2016,95.272631,0.7014,0.6591,0.9167,0.80842,0.87747,0.13531,1161.55057,56.450386,2.45629765 10/27/2016,96.63381,0.6964,0.6579,0.9177,0.80322,0.87159,0.13503,1164.01068,56.557851,2.46457512 10/28/2016,96.308262,0.6921,0.6539,0.9102,0.79518,0.86909,0.13494,1160.932794,56.34138,2.4156708 10/31/2016,97.144369,0.693,0.6546,0.9107,0.79613,0.86876,0.13484,1163.155147,56.809466,2.540853 11/1/2016,98.66286,0.6442,0.642,0.9045,0.79362,0.86841,0.13378,1165.1769,56.65788,2.2903749 11/2/2016,98.985835,0.6278,0.6357,0.9011,0.78402,0.87229,0.13323,1168.555491,57.427103,2.04342447 11/3/2016,98.739825,0.6791,0.6532,0.9005,0.7904,0.87438,0.13331,1173.08135,57.388865,2.12346905 11/4/2016,98.412864,0.6659,0.6524,0.8976,0.78494,0.87059,0.13311,1171.421856,57.455376,1.96897536 11/7/2016,101.85721,0.6811,0.6694,0.9058,0.79246,0.86697,0.13373,1160.909512,59.837148,2.11268792 11/8/2016,102.52728,0.6913,0.6684,0.907,0.79926,0.86238,0.13332,1157.04176,60.53318,2.1017911 11/10/2016,102.9537,0.682,0.6558,0.918,0.79815,0.85938,0.13475,1155.9456,67.3812,1.9078794 11/11/2016,101.035459,0.6966,0.6521,0.9211,0.79077,0.86365,0.13499,1130.779204,70.528627,1.86854346 11/14/2016,98.095048,0.7035,0.6583,0.9314,0.79505,0.85899,0.13603,1137.56539,74.13944,2.07059534 11/15/2016,98.958186,0.705,0.6598,0.9326,0.79683,0.85411,0.13568,1145.913598,72.966624,2.32180096 11/16/2016,97.085166,0.6997,0.661,0.9354,0.79983,0.85754,0.13581,1145.855646,69.752778,2.36871342 11/17/2016,96.341232,0.697,0.6625,0.9412,0.80022,0.85452,0.13616,1144.894504,69.545268,2.1991138 11/18/2016,94.931088,0.6921,0.6621,0.9444,0.79827,0.85155,0.13699,1140.731316,68.969532,2.43777972 11/21/2016,83.26965,0.6932,0.6606,0.9409,0.79284,0.84907,0.13653,1142.469007,68.648064,2.63339092 11/22/2016,84.45475,0.6965,0.6609,0.941,0.80005,0.84649,0.13692,1140.79312,70.00099,2.5817276 11/23/2016,87.406371,0.6997,0.6618,0.9477,0.80563,0.84239,0.1372,1126.170864,72.328464,2.59622415 11/25/2016,88.6416,0.702,0.6613,0.944,0.80204,0.83375,0.13632,1117.28064,75.60496,2.575232 11/28/2016,86.7008,0.7049,0.6617,0.9424,0.80511,0.84177,0.13648,1125.2256,76.249584,2.74624784 11/29/2016,84.77292,0.7027,0.659,0.939,0.8034,0.83546,0.13646,1115.82309,76.08717,2.8505223 11/30/2016,84.467136,0.6974,0.6589,0.9444,0.80796,0.82503,0.13698,1107.97008,74.739816,3.111798 12/1/2016,83.651301,0.6434,0.6404,0.9379,0.80341,0.82199,0.13712,1098.928051,74.722493,3.20489809 12/2/2016,83.409375,0.6305,0.6356,0.9375,0.79963,0.82591,0.13628,1103.840625,74.56875,3.19246875 12/5/2016,79.94974,0.6439,0.6402,0.929,0.79087,0.81598,0.13538,1087.28302,75.10965,3.346258 12/7/2016,77.9898,0.6892,0.6715,0.93,0.79637,0.81762,0.13511,1091.8014,75.8229,3.499404 12/8/2016,78.467509,0.6855,0.6654,0.9421,0.81287,0.82614,0.13671,1102.991838,76.432573,3.44752074 12/9/2016,78.980929,0.6734,0.6563,0.9469,0.81219,0.8212,0.13726,1098.271434,76.215981,3.55106438 12/12/2016,78.309258,0.7049,0.6605,0.9402,0.80476,0.81742,0.13647,1092.719244,78.69474,3.3546336 12/13/2016,78.807714,0.7058,0.6608,0.9411,0.80642,0.81702,0.13623,1090.301994,77.621928,3.39068919 12/14/2016,79.411197,0.7029,0.6605,0.9491,0.8114,0.8109,0.13591,1084.773845,78.281768,3.33760506 12/15/2016,80.56917,0.7066,0.6656,0.9603,0.81494,0.81257,0.13819,1083.69855,78.226038,3.40983324 12/16/2016,80.447744,0.699,0.6621,0.9568,0.80825,0.81114,0.13784,1085.853184,77.730432,3.31167616 12/19/2016,82.892899,0.6965,0.6634,0.9613,0.8099,0.82103,0.13746,1094.161273,76.884774,3.38752507 12/20/2016,84.265131,0.6989,0.6658,0.9627,0.80671,0.81685,0.13856,1090.113345,76.034046,3.234672 12/21/2016,84.850085,0.6944,0.6638,0.9593,0.80352,0.81595,0.13795,1085.553473,75.755921,3.33711691 12/22/2016,85.826598,0.6914,0.6604,0.9581,0.79904,0.8151,0.13727,1081.100878,75.412051,3.41763851 12/23/2016,85.894284,0.6863,0.6611,0.9564,0.79512,0.81524,0.13773,1083.88812,74.924376,3.43175448 1/3/2017,87.661931,0.7278,0.6729,0.9611,0.79857,0.81621,0.13856,1113.761124,74.946578,3.25832122 1/5/2017,83.72064,0.6905,0.6568,0.9428,0.79479,0.81722,0.13755,1112.617136,74.283212,3.10737452 1/6/2017,82.285324,0.6577,0.6432,0.9493,0.79585,0.81137,0.13687,1113.177659,74.396641,3.15746673 1/9/2017,77.875947,0.6727,0.621,0.9459,0.78286,0.81496,0.13667,1117.20249,74.640969,2.95101882 1/11/2017,76.51665,0.6606,0.6324,0.945,0.78999,0.81885,0.13787,1126.0809,74.9385,3.0979935 1/12/2017,76.495914,0.6398,0.6243,0.9423,0.79539,0.82141,0.13608,1126.453689,75.657267,3.12862446 1/13/2017,76.58804,0.7048,0.6578,0.9395,0.79957,0.82046,0.13648,1124.90093,75.413665,3.15775345 1/17/2017,76.221444,0.7063,0.6595,0.9334,0.7948,0.8289,0.13651,1136.013138,78.162916,3.08554038 1/18/2017,77.559552,0.706,0.6581,0.9408,0.80639,0.8206,0.13652,1133.00544,78.5568,3.06051648 1/19/2017,77.379004,0.7091,0.6577,0.9377,0.7964,0.81645,0.13728,1129.787845,77.45402,3.01451796 1/20/2017,77.124285,0.706,0.6553,0.9345,0.79925,0.81535,0.13623,1131.04404,76.582275,2.99684805 1/23/2017,77.1999,0.7046,0.6553,0.929,0.79703,0.8243,0.13587,1131.73567,76.10368,2.9230056 1/24/2017,77.888202,0.7065,0.6556,0.9319,0.7993,0.81889,0.13557,1126.611186,77.757736,3.0277431 1/25/2017,78.069864,0.7045,0.6584,0.9304,0.79776,0.82135,0.13518,1117.121976,77.632576,3.0279868 1/26/2017,78.81962,0.7054,0.6562,0.9361,0.80723,0.81744,0.13597,1112.55485,78.108184,3.20090034 2/3/2017,76.512544,0.7207,0.6737,0.9272,0.80792,0.82354,0.13505,1131.46216,77.23576,2.78215632 2/6/2017,74.536926,0.659,0.6415,0.9302,0.81749,0.83247,0.13581,1149.290006,76.360118,2.72064896 2/8/2017,74.140404,0.672,0.6206,0.9347,0.8148,0.83504,0.13622,1160.458091,78.458718,2.85036765 2/10/2017,74.347578,0.6671,0.626,0.9398,0.81649,0.83012,0.1367,1159.356076,80.719422,2.74994878 2/13/2017,73.806777,0.721,0.6627,0.9437,0.81926,0.82969,0.13712,1156.277862,86.8204,2.74796003 2/14/2017,73.7412,0.7245,0.6654,0.9454,0.83115,0.8274,0.13761,1161.074102,87.137518,2.760568 2/15/2017,73.273878,0.7274,0.6649,0.9434,0.82596,0.82636,0.13765,1163.87258,86.953178,2.75123742 2/16/2017,72.272466,0.7209,0.6613,0.9369,0.8207,0.82727,0.13684,1160.856576,86.354073,2.63999682 2/17/2017,72.73784,0.722,0.6642,0.9422,0.82199,0.83497,0.13702,1163.24012,87.031014,2.58473726 2/21/2017,76.345604,0.7284,0.6681,0.9491,0.82797,0.83488,0.1379,1172.840834,90.079081,2.38812542 2/22/2017,76.449912,0.7295,0.6705,0.9471,0.8291,0.83589,0.13846,1171.979424,88.610676,2.39654184 2/23/2017,76.34655,0.7291,0.6719,0.945,0.83076,0.83917,0.13768,1180.8342,87.5259,2.457945 2/24/2017,76.813884,0.7265,0.6738,0.9468,0.83713,0.84437,0.13751,1190.307492,85.193064,2.3513778 2/27/2017,77.655566,0.7248,0.6727,0.9446,0.8332,0.83814,0.13725,1183.328758,86.922092,2.30350156 2/28/2017,77.956475,0.7239,0.674,0.9455,0.83651,0.83843,0.1371,1180.40002,87.42093,2.3779325 3/1/2017,78.008414,0.6938,0.6627,0.9482,0.82858,0.83369,0.13782,1184.956058,86.893048,2.46124274 3/2/2017,78.228442,0.7128,0.6577,0.9518,0.83372,0.83195,0.13807,1174.75915,86.832714,2.46240178 3/3/2017,76.772428,0.7151,0.6677,0.9413,0.8142,0.82556,0.1373,1162.326653,84.971151,2.35710933 3/7/2017,75.248264,0.6741,0.6364,0.9464,0.82563,0.8303,0.13707,1150.689904,82.308408,2.517424 3/8/2017,75.023196,0.6696,0.62,0.9487,0.8281,0.82941,0.13702,1146.323697,81.758966,2.54991586 3/10/2017,73.64034,0.6672,0.6251,0.9369,0.80951,0.81648,0.13611,1128.627216,79.374168,2.79317997 3/13/2017,74.072817,0.7107,0.6637,0.9387,0.82035,0.8171,0.13555,1130.47641,80.63433,2.881809 3/14/2017,75.20425,0.7128,0.6662,0.943,0.82084,0.82184,0.13595,1130.77016,81.0037,2.8635138 3/15/2017,74.862095,0.7182,0.6648,0.9317,0.81477,0.82177,0.136,1136.562196,82.539303,2.79929265 3/16/2017,74.971519,0.7131,0.663,0.9289,0.8205,0.81973,0.13513,1139.398029,81.910402,2.665943 3/17/2017,75.24096,0.7175,0.6642,0.9312,0.82282,0.82627,0.13485,1144.686912,82.78368,2.672544 3/20/2017,75.445824,0.7198,0.6666,0.9312,0.83126,0.82728,0.13462,1149.324288,82.1784,2.71854528 3/21/2017,75.02675,0.7114,0.661,0.925,0.82577,0.82799,0.13445,1151.44925,81.1225,2.8307775 3/22/2017,74.864746,0.7111,0.6625,0.9262,0.8245,0.83317,0.13435,1156.675608,78.81962,2.76081696 3/23/2017,75.202866,0.7073,0.6627,0.9274,0.82614,0.83597,0.13469,1154.79848,78.671342,2.72034242 3/24/2017,75.097449,0.7059,0.662,0.9261,0.82497,0.83167,0.13445,1151.670177,77.551614,2.759778 3/27/2017,76.13362,0.7012,0.6606,0.9206,0.82713,0.83186,0.1337,1155.224116,74.734308,2.71632236 3/28/2017,75.779165,0.706,0.6615,0.9247,0.83075,0.83205,0.13385,1157.557954,73.726331,2.71048064 3/29/2017,76.123355,0.7124,0.6663,0.9289,0.83358,0.83651,0.1349,1164.329705,74.646404,2.888879 3/30/2017,76.845704,0.7158,0.67,0.9368,0.83842,0.83693,0.13529,1164.105152,75.03768,2.87728752 3/31/2017,77.379325,0.716,0.6718,0.9385,0.83916,0.8426,0.13578,1172.3742,75.277085,2.9091623 4/5/2017,82.095012,0.6745,0.65,0.9378,0.83413,0.84711,0.13602,1177.651728,74.902086,3.01277628 4/7/2017,83.277817,0.6704,0.6373,0.9443,0.83245,0.85024,0.1365,1184.652679,72.229507,3.01618863 4/10/2017,82.1019,0.6687,0.6247,0.9437,0.82608,0.85073,0.13664,1184.041516,70.031977,2.97576921 4/12/2017,79.020928,0.6404,0.6254,0.9376,0.82134,0.86012,0.13669,1206.484928,66.485216,2.80726816 4/13/2017,78.993009,0.7131,0.6738,0.9423,0.83399,0.86374,0.13652,1213.607016,62.691219,2.81700585 4/18/2017,77.62727,0.7045,0.6677,0.9319,0.81581,0.85954,0.13581,1201.927344,56.10038,2.85245271 4/19/2017,77.67552,0.7,0.6675,0.9336,0.81881,0.85763,0.13556,1195.204056,55.941312,2.91600624 4/20/2017,77.35399,0.7023,0.6676,0.9331,0.81865,0.85355,0.13491,1196.14089,56.536529,2.89764874 4/21/2017,77.183025,0.7038,0.6673,0.9325,0.82188,0.85438,0.13576,1197.7403,59.260375,2.8338675 4/24/2017,73.911633,0.6966,0.6607,0.9201,0.81426,0.83831,0.13375,1174.332831,57.248622,2.74217403 4/25/2017,73.26176,0.6896,0.6566,0.9152,0.81317,0.82388,0.13286,1156.931776,57.56608,2.70697856 4/26/2017,73.138725,0.6855,0.657,0.9171,0.81498,0.82579,0.13339,1164.001662,59.473935,2.77010055 4/27/2017,73.456439,0.6866,0.6584,0.9197,0.81384,0.82666,0.13344,1162.77671,59.017149,2.82605416 4/28/2017,73.267974,0.6873,0.6568,0.9178,0.80672,0.82286,0.13312,1164.027384,60.125078,2.90630548 5/4/2017,70.82912,0.7099,0.6693,0.9104,0.80368,0.80948,0.13252,1118.116864,56.317344,2.79383552 5/5/2017,70.390264,0.6748,0.6472,0.9092,0.79743,0.80657,0.13182,1116.506692,53.270028,2.800336 5/9/2017,67.40668,0.6711,0.6205,0.9196,0.80721,0.80676,0.13302,1123.043108,54.008108,2.7896066 5/10/2017,67.321832,0.6656,0.6258,0.9202,0.81018,0.80518,0.13334,1121.81582,55.02796,2.86163796 5/12/2017,66.242574,0.6433,0.6277,0.9147,0.81136,0.80708,0.13269,1123.644921,52.485486,2.97030531 5/15/2017,64.87032,0.6754,0.6517,0.9111,0.81092,0.80071,0.13212,1121.400102,52.032921,2.9765637 5/16/2017,64.081346,0.6701,0.6468,0.9023,0.80856,0.79763,0.13119,1116.361652,52.387538,2.91226348 5/17/2017,64.69842,0.6659,0.6444,0.8961,0.80142,0.80857,0.13045,1130.304696,53.58678,2.8334682 5/18/2017,65.886205,0.6683,0.6467,0.9007,0.80099,0.80788,0.13048,1123.235949,52.654922,2.82117254 5/19/2017,65.539435,0.6657,0.6439,0.8923,0.79186,0.8021,0.12976,1120.666339,53.35954,2.75426241 5/22/2017,67.258642,0.6654,0.642,0.8899,0.79554,0.79958,0.1293,1121.834637,55.253891,2.85417627 5/23/2017,67.351144,0.6687,0.6431,0.8942,0.79553,0.79994,0.12917,1118.840924,54.912822,2.86126116 5/24/2017,66.756946,0.6689,0.6438,0.8914,0.7914,0.79947,0.12986,1122.031922,52.111244,2.76815356 5/25/2017,65.80284,0.665,0.6433,0.892,0.79889,0.79759,0.12982,1120.05764,51.78952,2.7324636 5/26/2017,65.881504,0.6661,0.6473,0.8944,0.79801,0.80329,0.13046,1132.990144,51.11496,2.77389216 5/31/2017,66.206936,0.6609,0.643,0.8894,0.79437,0.80291,0.13054,1128.577448,49.868658,2.6682 6/1/2017,66.134385,0.6931,0.6599,0.8919,0.79491,0.80086,0.13094,1129.109724,48.804768,2.61585351 6/2/2017,65.905268,0.7126,0.6605,0.8863,0.79002,0.80266,0.13021,1133.728371,49.083294,2.534818 6/6/2017,68.391171,0.6656,0.6429,0.8867,0.7937,0.81045,0.13056,1147.735613,49.362589,2.62126254 6/7/2017,69.7394,0.664,0.6333,0.8884,0.79036,0.80895,0.13076,1143.50406,49.119636,2.65960308 6/9/2017,72.169707,0.6713,0.6217,0.8933,0.79525,0.8096,0.13145,1131.596708,48.854577,2.65863946 6/12/2017,75.64785,0.6412,0.6284,0.8926,0.79178,0.81178,0.13135,1130.192268,49.191186,2.749208 6/13/2017,75.374,0.6724,0.6459,0.892,0.79059,0.81047,0.1312,1129.7626,48.4356,2.6850092 6/14/2017,74.681492,0.6765,0.6481,0.8914,0.79313,0.81369,0.13055,1123.930604,48.643698,2.58541656 6/15/2017,75.068118,0.68,0.6484,0.8973,0.79814,0.80879,0.13173,1125.196254,49.333554,2.62164141 6/16/2017,74.716746,0.6806,0.6456,0.8931,0.78739,0.80551,0.13117,1119.706263,49.334844,2.6516139 6/19/2017,76.245,0.6817,0.6467,0.897,0.79193,0.80426,0.13133,1115.72448,49.7835,2.5640745 6/20/2017,75.88945,0.6808,0.6465,0.8981,0.79103,0.80581,0.13168,1116.347281,49.242823,2.5739546 6/21/2017,75.330002,0.6763,0.6445,0.8954,0.78269,0.80388,0.13141,1116.098192,49.094782,2.57982648 6/22/2017,75.42088,0.6763,0.645,0.8968,0.78597,0.80547,0.13118,1121.457368,48.929408,2.55623872 6/23/2017,75.197994,0.6762,0.6438,0.8933,0.78443,0.80281,0.1306,1122.619043,48.979639,2.55474867 6/26/2017,72.778134,0.6784,0.6442,0.8943,0.78653,0.79944,0.13049,1113.153096,48.506832,2.66242053 6/27/2017,71.380986,0.6687,0.6357,0.8819,0.77601,0.78495,0.12995,1099.879223,49.439314,2.6271801 6/28/2017,72.04284,0.6715,0.6359,0.879,0.76835,0.78252,0.12953,1098.10833,51.19296,2.66337 6/29/2017,72.121991,0.6716,0.6338,0.8741,0.76589,0.77924,0.12897,1088.700291,54.036862,2.62623345 6/30/2017,72.168992,0.6727,0.6359,0.8752,0.76499,0.77877,0.12926,1086.657072,53.921072,2.57650128 7/3/2017,70.0744,0.7181,0.6706,0.88,0.76732,0.77616,0.12948,1073.776,54.8944,2.546104 7/6/2017,72.08919,0.6707,0.6426,0.8754,0.75636,0.77321,0.1289,1072.557588,52.61154,2.51791302 7/7/2017,72.474264,0.6668,0.6345,0.8772,0.75987,0.77015,0.12901,1063.569912,53.237268,2.53405536 7/11/2017,72.802908,0.6598,0.6327,0.8721,0.75749,0.76537,0.12863,1061.973612,54.9423,2.60714295 7/12/2017,73.372599,0.6381,0.6285,0.8763,0.76531,0.77434,0.12904,1069.532913,55.916703,2.60778117 7/13/2017,73.596312,0.6783,0.6385,0.8774,0.77207,0.77444,0.12945,1068.304692,54.846274,2.57850312 7/14/2017,73.265757,0.6827,0.6358,0.8719,0.76931,0.77474,0.12881,1071.30353,54.110114,2.5537951 7/17/2017,73.3986,0.6795,0.6363,0.8712,0.7721,0.77353,0.12881,1075.156632,55.721952,2.63137248 7/18/2017,75.116745,0.6852,0.6334,0.8655,0.77053,0.77234,0.12805,1075.357785,58.326045,2.67067335 7/19/2017,76.358412,0.6906,0.6345,0.8684,0.77487,0.77576,0.12853,1077.9015,59.242248,2.69308208 7/20/2017,76.659768,0.6842,0.6291,0.8598,0.76374,0.76829,0.12704,1070.012502,59.145642,2.66701362 7/21/2017,78.039488,0.6786,0.6291,0.8572,0.76659,0.77128,0.12685,1075.768856,58.152448,2.5943158 7/24/2017,78.1599,0.6806,0.6307,0.8589,0.77107,0.77318,0.12721,1078.17717,57.322986,2.54354646 7/25/2017,78.492655,0.6814,0.6303,0.8585,0.76976,0.76734,0.12707,1073.17651,58.369415,2.54261945 7/26/2017,77.9763,0.6822,0.6279,0.8522,0.75963,0.76653,0.12725,1074.223666,58.495008,2.49191802 7/27/2017,78.454804,0.6823,0.6299,0.8564,0.76957,0.76974,0.12712,1078.33606,57.986844,2.502829 7/28/2017,78.539508,0.6795,0.6273,0.8511,0.75844,0.76905,0.12627,1080.590604,58.21524,2.48393535 7/31/2017,81.283125,0.6758,0.6233,0.8445,0.75445,0.76592,0.12615,1072.04208,61.69917,2.39508645 8/2/2017,81.75202,0.7145,0.6599,0.8435,0.75045,0.76165,0.12538,1068.419275,61.69359,2.3366637 8/3/2017,81.8236,0.7141,0.6693,0.8425,0.74651,0.7656,0.12528,1068.7955,61.85635,2.339454 8/8/2017,81.354549,0.6734,0.6241,0.8509,0.7562,0.77114,0.12705,1072.950864,65.315084,2.36099223 8/9/2017,81.08564,0.6689,0.6192,0.8504,0.74916,0.77254,0.12761,1086.21592,66.705376,2.42772192 8/11/2017,80.69886,0.6621,0.6333,0.8459,0.73957,0.77462,0.12723,1090.627329,65.117382,2.46546014 8/14/2017,81.4848,0.6665,0.6229,0.8488,0.74467,0.77434,0.12725,1088.28892,64.542752,2.5158432 8/15/2017,82.356608,0.6664,0.6232,0.8522,0.75075,0.76997,0.12753,1083.597866,64.375188,2.49421896 8/16/2017,82.549572,0.6735,0.6239,0.8498,0.74436,0.77123,0.12766,1090.386878,64.49982,2.45651686 8/17/2017,83.69636,0.6727,0.6241,0.853,0.74994,0.77845,0.12757,1098.79195,66.86667,2.4525456 8/18/2017,85.11503,0.6743,0.6239,0.8503,0.74504,0.77861,0.12776,1091.895739,66.969628,2.45430592 8/21/2017,86.1212,0.672,0.622,0.8464,0.74313,0.77668,0.12695,1093.447232,68.482224,2.51947888 8/22/2017,86.567364,0.6727,0.6241,0.8502,0.74989,0.77591,0.12755,1092.575016,68.194542,2.55723156 8/23/2017,86.14837,0.6694,0.6223,0.847,0.74831,0.77681,0.12713,1093.44312,65.06654,2.4762892 8/24/2017,86.622975,0.6695,0.6223,0.8475,0.75143,0.77355,0.12718,1090.224,66.86775,2.51292225 8/25/2017,85.394638,0.6654,0.6186,0.8386,0.74317,0.76682,0.12669,1082.92611,66.173926,2.45785274 8/29/2017,83.737152,0.6641,0.6164,0.8352,0.74171,0.76104,0.12604,1093.468896,64.844928,2.40938496 8/30/2017,83.99853,0.6652,0.6192,0.8415,0.7485,0.76329,0.12738,1101.1869,64.517805,2.4122439 8/31/2017,82.760832,0.6673,0.6193,0.8397,0.74463,0.7635,0.12776,1109.604771,65.992023,2.43042768 9/1/2017,82.768512,0.6956,0.6586,0.8432,0.75096,0.76477,0.12844,1117.433936,66.882624,2.44831552 9/5/2017,81.346254,0.6754,0.6514,0.8394,0.7422,0.77137,0.12834,1124.552574,65.607504,2.40387372 9/6/2017,81.585693,0.6715,0.6453,0.8391,0.73898,0.76829,0.12834,1119.544002,65.273589,2.45889864 9/8/2017,81.54302,0.6707,0.6235,0.8308,0.73698,0.77052,0.12798,1118.746972,64.353768,2.34775772 9/11/2017,82.304708,0.6597,0.6321,0.8366,0.73911,0.7647,0.12785,1110.619964,63.640162,2.3818002 9/13/2017,83.776654,0.6718,0.623,0.8413,0.74563,0.76153,0.12851,1112.509881,64.662318,2.51355201 9/14/2017,83.47211,0.6716,0.6231,0.839,0.7408,0.76107,0.12843,1115.65186,63.14314,2.5473718 9/15/2017,83.23128,0.6695,0.6221,0.837,0.73953,0.75517,0.12756,1104.99066,62.11377,2.4990309 9/18/2017,82.34506,0.6659,0.6207,0.8365,0.74242,0.74978,0.12726,1093.67356,62.05157,2.5958268 9/19/2017,80.968944,0.6678,0.6192,0.8337,0.73696,0.74706,0.1269,1093.105755,60.843426,2.61498342 9/20/2017,80.943816,0.6753,0.6234,0.8408,0.74516,0.74939,0.12681,1093.96488,60.638496,2.6405324 9/21/2017,80.315034,0.6642,0.6205,0.8374,0.73924,0.74452,0.12718,1081.25088,58.651496,2.60046196 9/22/2017,79.939504,0.666,0.6219,0.8368,0.73637,0.74737,0.12681,1085.58064,55.697408,2.46420864 9/25/2017,76.997436,0.6699,0.6246,0.8439,0.74571,0.75536,0.12737,1106.167242,55.098231,2.50266984 9/26/2017,79.34736,0.6687,0.626,0.848,0.74583,0.75546,0.12792,1097.29504,54.40768,2.5021088 9/27/2017,80.533926,0.6683,0.6262,0.8514,0.74637,0.75462,0.12814,1092.158892,54.74502,2.51478018 9/28/2017,80.665872,0.6666,0.6248,0.8484,0.73804,0.75514,0.12727,1092.14532,54.229728,2.47919448 9/29/2017,80.721168,0.6631,0.6235,0.8464,0.73863,0.75228,0.12711,1083.1804,53.49248,2.44279504 10/10/2017,79.94736,0.6587,0.6245,0.8469,0.74582,0.75311,0.12882,1090.832607,53.913654,2.45473965 10/11/2017,79.80888,0.6567,0.6302,0.8432,0.74282,0.74961,0.12806,1089.178304,53.028848,2.46813072 10/13/2017,80.233615,0.6673,0.6269,0.8459,0.74927,0.7565,0.12835,1102.901338,52.048227,2.54835834 10/16/2017,82.777905,0.6655,0.627,0.8477,0.75164,0.75561,0.12849,1098.441183,52.752371,2.43476394 10/17/2017,83.154216,0.6668,0.6267,0.8499,0.75042,0.75748,0.12846,1092.223488,53.135748,2.45604102 10/18/2017,83.474076,0.6657,0.6252,0.8484,0.7507,0.75122,0.1282,1086.868272,51.939048,2.38748244 10/19/2017,83.129761,0.6648,0.6219,0.8437,0.74513,0.74972,0.12767,1088.482681,50.70637,2.37273751 10/20/2017,83.384775,0.6634,0.6234,0.8487,0.75006,0.74789,0.12818,1086.734889,51.482142,2.34741933 10/23/2017,82.990761,0.6644,0.625,0.8511,0.75297,0.75035,0.12825,1091.339997,51.840501,2.50044669 10/24/2017,82.683172,0.6612,0.624,0.8503,0.7541,0.74642,0.12811,1085.475974,51.910815,2.48644726 10/25/2017,82.34752,0.6521,0.6222,0.8465,0.75053,0.74421,0.12753,1081.429145,51.560315,2.48354635 10/26/2017,83.56524,0.6575,0.6278,0.8584,0.7633,0.75294,0.12873,1087.584216,52.044792,2.47717072 10/27/2017,83.952044,0.6614,0.6311,0.8614,0.76211,0.75782,0.12983,1096.86369,51.16716,2.39658708 10/30/2017,84.66143,0.6599,0.6307,0.8582,0.76304,0.75837,0.12944,1095.312078,50.427832,2.46354892 10/31/2017,84.882495,0.6574,0.6301,0.8587,0.76645,0.75561,0.12928,1091.794115,50.113732,2.40436 11/1/2017,85.484724,0.7032,0.6623,0.8607,0.77237,0.75367,0.13024,1097.099862,50.936226,2.27551866 11/7/2017,85.498686,0.6661,0.631,0.8631,0.77619,0.75697,0.13007,1100.71143,53.097912,2.65584501 11/8/2017,85.37025,0.6678,0.6216,0.8625,0.77319,0.75739,0.13016,1105.173,53.18175,2.7184275 11/9/2017,84.9551,0.6717,0.6211,0.859,0.77002,0.75702,0.1295,1103.87513,52.45054,2.7337675 11/10/2017,84.581218,0.6568,0.6226,0.8573,0.76748,0.75508,0.12898,1093.117511,52.200997,2.69569412 11/13/2017,83.301549,0.6534,0.6294,0.8571,0.7648,0.75434,0.12908,1095.639501,52.531659,2.67269493 11/14/2017,82.157868,0.6469,0.6237,0.8476,0.75806,0.74707,0.1282,1085.1399,52.67834,2.61340508 11/15/2017,81.705954,0.6436,0.6251,0.8481,0.76231,0.75135,0.1278,1083.990534,51.259164,2.64089859 11/16/2017,81.528715,0.6446,0.6265,0.8497,0.77141,0.75148,0.12821,1086.409426,51.925167,2.59464392 11/17/2017,80.747601,0.6416,0.6253,0.8481,0.77282,0.75646,0.12803,1096.101402,52.175112,2.58874044 11/20/2017,77.5593,0.6435,0.6282,0.8523,0.77437,0.75676,0.12828,1088.318916,53.064198,2.59977069 11/21/2017,77.94885,0.6456,0.629,0.8519,0.77738,0.75764,0.12851,1090.951659,53.831561,2.5957393 11/22/2017,77.543653,0.6443,0.6279,0.8459,0.77659,0.7604,0.12829,1093.004308,53.951502,2.47569553 11/27/2017,80.0156,0.6389,0.6241,0.8405,0.77203,0.75641,0.12702,1088.04406,56.120185,2.3673523 11/28/2017,81.064708,0.6415,0.6275,0.8446,0.77894,0.75761,0.12738,1092.895508,56.072994,2.4569414 11/29/2017,81.438768,0.639,0.6266,0.8441,0.78393,0.75414,0.1276,1083.520524,56.343675,2.608269 11/30/2017,81.23767,0.6356,0.6229,0.8401,0.77209,0.74647,0.12699,1071.135901,57.740073,2.47132217 12/1/2017,81.423072,0.7052,0.6602,0.8408,0.77369,0.7488,0.12738,1076.745296,57.821816,2.38820832 12/4/2017,81.760028,0.7054,0.672,0.8428,0.77399,0.74975,0.1276,1075.564504,60.234916,2.44504708 12/5/2017,81.887904,0.6756,0.6515,0.8456,0.77874,0.75097,0.12764,1070.335112,60.468856,2.42044544 12/6/2017,81.98226,0.6731,0.6446,0.8478,0.77536,0.75497,0.12817,1071.085086,58.83732,2.47396518 12/7/2017,82.128486,0.6728,0.6361,0.8494,0.77683,0.75112,0.12814,1059.388668,56.926788,2.38120796 12/12/2017,84.708652,0.6438,0.6296,0.8516,0.7798,0.75004,0.12867,1059.807684,57.01462,2.38984508 12/13/2017,85.617,0.6458,0.628,0.8456,0.77534,0.75137,0.12848,1061.6508,56.384608,2.2602888 12/14/2017,86.871421,0.6509,0.6309,0.8491,0.77981,0.75541,0.1284,1063.888336,57.203867,2.26353078 12/15/2017,87.314349,0.6508,0.6311,0.8511,0.78134,0.75585,0.1285,1069.356084,57.568404,2.23005222 12/18/2017,88.546816,0.6505,0.63,0.8488,0.77972,0.75417,0.12787,1071.406288,59.475416,2.29778648 12/19/2017,87.948198,0.6472,0.6272,0.8446,0.7786,0.74816,0.12809,1065.63182,58.927742,2.31471076 12/20/2017,87.752808,0.6458,0.6266,0.8424,0.77936,0.74289,0.12798,1066.116168,58.42044,2.2719528 12/21/2017,87.664598,0.6487,0.6268,0.8422,0.77788,0.74318,0.12798,1066.73052,59.274036,2.19148862 12/22/2017,87.64671,0.6506,0.6274,0.843,0.78076,0.74429,0.12852,1074.11688,60.05532,2.2018317 12/27/2017,87.434328,0.6534,0.6279,0.8412,0.78307,0.7421,0.12812,1082.775816,57.91662,2.31691716 12/28/2017,87.012216,0.6527,0.6258,0.8373,0.78209,0.74175,0.12812,1084.336992,57.974652,2.48217585 12/29/2017,86.53204,0.6506,0.6231,0.833,0.78044,0.73924,0.12817,1085.2324,58.95974,2.9484868 1/2/2018,87.026742,0.6427,0.6112,0.8293,0.78129,0.73849,0.128,1092.652508,60.356454,5.91672378 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7/19/2018,105.56251,0.6321,0.6267,0.859,0.75803,0.76376,0.12724,1050.53123,50.49202,2.3328722 7/20/2018,104.564467,0.6328,0.6259,0.8531,0.75228,0.76553,0.12617,1048.912043,50.170811,2.363087 7/23/2018,103.277475,0.6313,0.6264,0.8553,0.75608,0.76814,0.12569,1047.31485,50.881797,2.31341544 7/24/2018,103.286502,0.6352,0.6274,0.8558,0.75393,0.76962,0.12591,1047.944216,50.860194,2.32589324 7/25/2018,102.670092,0.6356,0.6277,0.8526,0.75704,0.7683,0.12655,1050.087738,51.079266,2.36417454 7/26/2018,103.660641,0.6336,0.6299,0.8589,0.76722,0.77215,0.12623,1050.168441,51.224796,2.38387695 7/27/2018,103.54853,0.635,0.6299,0.8579,0.76731,0.77252,0.12595,1050.258338,52.657902,2.384962 7/30/2018,104.463804,0.6327,0.6275,0.8543,0.76253,0.76917,0.12525,1043.484735,52.240445,2.323696 7/31/2018,104.504218,0.6351,0.6283,0.8554,0.76458,0.76459,0.12535,1047.13791,52.068198,2.40872086 8/1/2018,103.786752,0.6552,0.6271,0.8576,0.76512,0.76763,0.12561,1042.807296,51.387392,2.4021376 8/2/2018,104.136448,0.6353,0.6134,0.8632,0.76651,0.7731,0.12583,1042.598856,51.602096,2.40772376 8/3/2018,104.094445,0.6325,0.6165,0.8645,0.76658,0.77706,0.12628,1050.28105,52.501085,2.4562174 8/6/2018,100.4096,0.6457,0.6362,0.8656,0.77018,0.77694,0.12613,1045.333184,54.299088,2.47674128 8/16/2018,103.44951,0.6383,0.6389,0.879,0.77788,0.79268,0.12748,1032.08664,54.79686,2.65458 8/17/2018,102.875856,0.6395,0.6376,0.8742,0.77715,0.79113,0.12739,1035.27135,55.03089,2.631342 8/20/2018,101.72409,0.6392,0.6361,0.871,0.77544,0.7913,0.1275,1036.90808,55.27366,2.63913 8/21/2018,102.117045,0.6367,0.6328,0.8643,0.77259,0.78348,0.12671,1033.694157,54.373113,2.601543 8/22/2018,102.26878,0.6337,0.631,0.8623,0.77052,0.77998,0.12606,1031.13834,53.755782,2.604146 8/23/2018,102.053256,0.6281,0.6307,0.8664,0.77267,0.77854,0.12562,1027.169184,53.89008,2.573208 8/24/2018,101.014095,0.6305,0.6301,0.8605,0.76901,0.77357,0.12634,1037.203675,53.351,2.572895 8/28/2018,99.832925,0.6275,0.6268,0.8551,0.77052,0.769,0.12546,1026.9751,52.092692,2.548198 8/29/2018,100.676012,0.6244,0.6259,0.8542,0.7693,0.76481,0.12535,1030.67772,52.268498,2.545516 8/30/2018,101.54593,0.6224,0.6266,0.857,0.77283,0.77201,0.12545,1028.38286,53.15114,2.52815 8/31/2018,102.34526,0.6197,0.6282,0.862,0.77435,0.77598,0.12611,1035.3913,53.43538,2.55152 9/4/2018,98.669352,0.6248,0.6188,0.8634,0.77431,0.77484,0.12646,1028.758368,53.755284,2.555664 9/5/2018,98.171964,0.6295,0.627,0.8598,0.76696,0.77095,0.12607,1028.948454,53.900862,2.5794 ================================================ FILE: Ore Money project/iron ore brlaud.csv ================================================ Date,BRLAUD BGN Curncy (R1),soybean,sugar,brent,iron ore,CNYAUD BGN Curncy (R1),USDAUD Curncy (L3),EURAUD Curncy (L2),JPYAUD Curncy (R3),KRWAUD Curncy (L1),INRAUD Curncy (R2) 10/31/2013,0.47200000000000003,19.3734,1353.864375,115.0983,141.282,0.1735,1.0575,1.43644,1.0753,0.000997,0.017 11/1/2013,0.4695,19.3377,1341.4536,112.22223600000001,142.5162,0.1737,1.0596,1.42903,1.0742,0.000999,0.0171 11/4/2013,0.4683,19.261648,1328.9696,111.69022199999999,142.9904,0.1724,1.0514,1.42099,1.0662,0.00099,0.017 11/5/2013,0.4602,19.205868,1324.47915,110.78609399999999,143.78106,0.1724,1.0518,1.41727,1.0678,0.00099,0.0169 11/6/2013,0.4593,18.999570000000002,1325.7711,110.470428,144.43872,0.1723,1.0497,1.41842,1.0639,0.00099,0.0168 11/7/2013,0.4586,19.080907999999997,1352.533875,109.42964199999999,146.06837,0.1736,1.0577,1.4193,1.0782,0.000995,0.0168 11/8/2013,0.4604,19.26424,1391.543,112.00536000000001,147.16686,0.1749,1.0655,1.42419,1.0757,0.000999,0.0168 11/11/2013,0.4583,19.200945,1397.598,113.6884,147.04697,0.1754,1.0685,1.4324700000000001,1.0776,0.0009960000000000001,0.0168 11/12/2013,0.4607,19.212037,1418.325675,113.756331,147.944511,0.1765,1.0751,1.44438,1.0788,0.0010019999999999999,0.0168 11/13/2013,0.4575,19.01752,1410.0209,114.44700800000001,147.022524,0.1754,1.0684,1.44103,1.0766,0.000998,0.0169 11/14/2013,0.4639,18.934776,1413.93615,116.506836,147.10947,0.1762,1.0734,1.4448299999999998,1.0733,0.001004,0.017 11/15/2013,0.4603,18.732870000000002,1366.8057,115.8129,145.155726,0.1752,1.0674,1.44052,1.0655,0.001004,0.017 11/18/2013,0.4711,18.9286,1372.99,115.672408,144.166616,0.175,1.0664,1.44023,1.0663,0.001008,0.0172 11/19/2013,0.4668,18.710765,1352.952625,113.34589199999999,142.710662,0.174,1.0601,1.43516,1.0588,0.001005,0.017 11/20/2013,0.4717,18.854879999999998,1364.568375,115.764678,143.98272,0.1758,1.0713,1.43965,1.0709,0.0010140000000000001,0.0171 11/21/2013,0.4695,18.96333,1398.6945,119.21663999999998,145.5552,0.1777,1.083,1.46003,1.0705,0.001019,0.0172 11/22/2013,0.4783,18.9486,1436.9355,120.93345,146.3616,0.1788,1.089,1.47698,1.0763,0.001027,0.0174 11/25/2013,0.478,18.906512,1451.0093,121.1676,147.191344,0.1791,1.0916,1.4754399999999999,1.0736,0.00103,0.0175 11/26/2013,0.47700000000000004,18.95561,1456.459225,121.491216,148.072898,0.1799,1.0957,1.48712,1.0819,0.001033,0.0175 11/27/2013,0.4727,18.966108,1453.848,122.59683400000002,148.85421000000002,0.1808,1.1014,1.49573,1.0782,0.001034,0.0176 11/29/2013,0.4703,18.8307,1467.477,120.43961999999999,149.28408000000002,0.1802,1.0979999999999999,1.4922,1.0719,0.001037,0.0176 12/2/2013,0.4662,18.636454,1450.99675,122.39438999999999,148.8061,0.1802,1.0982,1.48715,1.0668,0.001038,0.0176 12/3/2013,0.4606,18.398545000000002,1444.466375,123.26258999999999,147.899785,0.1796,1.0945,1.48725,1.0676,0.001031,0.0175 12/4/2013,0.4655,18.4731,1472.42125,123.9071,151.760725,0.1818,1.1075,1.5054,1.0821,0.0010429999999999999,0.0179 12/5/2013,0.4674,18.415746,1465.3152,122.45533200000001,151.739568,0.1811,1.1034,1.50804,1.0839,0.001042,0.0179 12/6/2013,0.4718,18.225773999999998,1456.1943,122.614746,150.486228,0.1807,1.0986,1.50589,1.0686,0.001042,0.0179 12/9/2013,0.4729,18.163625,1474.765625,120.055525,149.2161,0.1807,1.0975,1.5078200000000002,1.0629,0.0010429999999999999,0.018000000000000002 12/10/2013,0.4734,18.163998,1462.573425,119.541402,148.6344,0.18,1.0929,1.50384,1.0627,0.001039,0.0179 12/11/2013,0.4733,18.246852,1485.3888,121.24043999999999,150.296148,0.182,1.1052,1.5235,1.0791,0.00105,0.0179 12/12/2013,0.4795,18.23807,1481.143875,121.59086299999998,151.968998,0.1843,1.1189,1.5388700000000002,1.0824,0.0010630000000000001,0.018000000000000002 12/13/2013,0.4784,18.149185,1480.82625,121.39986499999999,151.250645,0.1838,1.1155,1.53315,1.0806,0.001058,0.018000000000000002 12/16/2013,0.4801,18.183352,1495.0694,123.461272,150.909528,0.184,1.1176,1.5378399999999999,1.0849,0.0010609999999999999,0.0181 12/17/2013,0.4842,17.935848,1513.1967,121.86487199999999,150.600438,0.1851,1.1238,1.5471700000000002,1.0946,0.001067,0.0182 12/18/2013,0.4815,17.931865,1494.134,123.717455,151.15129,0.1859,1.1285,1.54429,1.0822,0.001073,0.0182 12/19/2013,0.4789,18.21397,1496.5906,124.385062,150.11018,0.1858,1.1278,1.5407,1.0821,0.001062,0.0181 12/20/2013,0.4706,18.433870000000002,1500.4834,125.24946200000001,148.81568000000001,0.1846,1.1206,1.53253,1.0766,0.001053,0.0181 12/23/2013,0.475,18.166239,1486.99005,124.86910800000001,147.714021,0.1844,1.1193,1.53301,1.0753,0.0010550000000000002,0.0181 12/24/2013,0.4754,18.169789,1495.000375,125.42871000000001,147.375932,0.1846,1.1209,1.53348,1.0752,0.001057,0.0181 12/26/2013,0.478,18.313218,1482.53875,125.88791599999999,147.450072,0.1851,1.1242,1.53908,1.0726,0.0010609999999999999,0.0182 12/27/2013,0.4822,18.524825,1501.26625,126.48295,147.803975,0.1858,1.1275,1.55017,1.0725,0.0010689999999999999,0.0182 12/30/2013,0.4755,18.396378,1491.757575,124.899951,148.46258899999998,0.1853,1.1231,1.55009,1.0685,0.001064,0.0181 12/31/2013,0.4748,18.407097,1472.23125,124.28436,149.645997,0.1853,1.1217,1.54116,1.0653,0.001064,0.0181 1/2/2014,0.47,18.280638,1444.2714,120.95071599999999,151.182784,0.1855,1.1222,1.5342799999999999,1.0709,0.001068,0.018000000000000002 1/3/2014,0.4695,17.975832,1441.252575,119.49233100000001,150.603488,0.1847,1.1179,1.5190000000000001,1.0659999999999998,0.001059,0.0179 1/6/2014,0.4692,17.932416,1446.1356,119.025296,149.581776,0.1842,1.1152,1.5198,1.07,0.001047,0.0179 1/7/2014,0.4722,17.990412,1455.6999,120.25347,150.207618,0.1851,1.1202,1.52521,1.071,0.001047,0.018000000000000002 1/8/2014,0.4692,17.683889999999998,1461.392625,120.383025,150.549,0.1857,1.1235,1.5251299999999999,1.0712,0.001052,0.0181 1/9/2014,0.4691,17.394876,1456.596125,119.55044299999999,150.497141,0.1856,1.1237,1.5291,1.072,0.001057,0.0181 1/10/2014,0.4694,17.310726000000003,1449.50925,119.24055,148.87001999999998,0.1837,1.1118,1.5196,1.0673,0.001047,0.0181 1/13/2014,0.4686,17.2302,1465.395375,117.905375,147.1194,0.1827,1.1045,1.51003,1.0723,0.001044,0.0179 1/14/2014,0.4738,17.275997,1493.3867,118.65676699999999,148.3349,0.1846,1.1153,1.52566,1.0702,0.001053,0.0181 1/15/2014,0.4754,17.081968,1478.2688,120.157008,147.71472,0.1855,1.1216,1.52598,1.0728,0.001053,0.0182 1/16/2014,0.4796,17.515665,1490.8155,121.40793300000001,148.17459,0.1872,1.1337,1.5441,1.0864,0.001066,0.0185 1/17/2014,0.486,17.332535999999998,1499.2302,121.259424,148.04399999999998,0.1882,1.1388,1.54215,1.0916,0.001073,0.0185 1/21/2014,0.4814,17.283832,1454.1358,121.20258799999999,144.67543999999998,0.1877,1.1356,1.54005,1.0888,0.00106,0.0183 1/22/2014,0.47600000000000003,16.979391,1445.45115,122.312619,141.09953000000002,0.1867,1.1297,1.53045,1.0808,0.001058,0.0183 1/23/2014,0.47600000000000003,17.151616,1456.2908,122.68423200000001,143.80444,0.1884,1.1404,1.5619399999999999,1.1041,0.001059,0.0184 1/24/2014,0.4801,17.402186999999998,1479.646575,124.245396,145.92039,0.1904,1.1517,1.57528,1.1256,0.00106,0.0184 1/27/2014,0.4725,16.93564,1473.572325,122.08536699999999,144.75395,0.1892,1.1443,1.56467,1.1158,0.001056,0.018000000000000002 1/28/2014,0.4694,17.109282,1464.31305,122.35073100000001,143.07096,0.1882,1.1391,1.5573700000000001,1.1065,0.001057,0.0182 1/29/2014,0.4698,16.866982,1452.402775,123.412755,143.60965,0.1891,1.1443,1.56342,1.1187,0.001062,0.0182 1/30/2014,0.4719,17.045129,1449.8025,122.749945,142.59233999999998,0.1877,1.1371,1.54126,1.107,0.001052,0.0182 2/7/2014,0.4687,17.559399,1486.35345,122.312991,139.87239,0.1841,1.1163,1.52203,1.0906,0.001039,0.018000000000000002 2/10/2014,0.4641,17.4777,1481.24625,121.394025,139.017,0.1844,1.1175,1.52481,1.0928,0.0010400000000000001,0.0179 2/11/2014,0.4609,17.10649,1476.900875,120.25442,136.5421,0.1826,1.1065,1.50894,1.0781,0.001038,0.0178 2/12/2014,0.4573,17.515898999999997,1465.7517,120.52844099999999,136.16091,0.1827,1.1079,1.50591,1.0805,0.0010429999999999999,0.0179 2/13/2014,0.4632,17.440542,1497.091225,121.092601,136.76236,0.1837,1.1137,1.5236,1.0901,0.001046,0.0179 2/14/2014,0.4635,17.300847,1480.47875,120.740652,136.1487,0.1825,1.1069,1.51562,1.0873,0.001042,0.0179 2/18/2014,0.4626,17.902048,1507.7158,122.36758799999998,137.47798,0.1826,1.1078,1.52416,1.0823,0.0010400000000000001,0.0178 2/19/2014,0.4642,18.288706,1504.707175,122.74321699999999,137.66529,0.1828,1.1111,1.52593,1.0859,0.0010400000000000001,0.0178 2/20/2014,0.4683,18.132832,1508.2008,122.47712,136.5792,0.1825,1.1104,1.52322,1.0857,0.001036,0.0179 2/21/2014,0.475,18.626079999999998,1527.0155,122.3729,135.351,0.1829,1.114,1.53073,1.0872,0.001038,0.018000000000000002 2/24/2014,0.4728,19.267647,1534.43955,122.44528799999999,133.46802,0.1815,1.1067,1.51968,1.0797,0.00103,0.0179 2/25/2014,0.4736,19.226592,1551.2112,121.42468799999999,131.3928,0.1811,1.1088,1.524,1.0845,0.001033,0.0179 2/26/2014,0.4745,19.27835,1569.08375,122.1148,131.2355,0.1821,1.115,1.52605,1.0892,0.001042,0.018000000000000002 2/27/2014,0.4804,19.452576,1554.3099,121.533984,130.39026,0.182,1.1154,1.52925,1.0922,0.001046,0.018000000000000002 2/28/2014,0.4781,18.454635,1584.667125,122.21293500000002,129.7539,0.1823,1.1205,1.54619,1.1008,0.00105,0.0181 3/3/2014,0.4769,19.91464,1574.4313,124.41056,129.55704,0.1821,1.1188,1.5366799999999998,1.103,0.0010429999999999999,0.018000000000000002 3/4/2014,0.47700000000000004,19.820902,1584.3314,122.12088999999999,127.70738999999999,0.1819,1.1173,1.53552,1.0931,0.0010429999999999999,0.018000000000000002 3/5/2014,0.4801,20.28999,1580.46,119.93688,126.1029,0.1816,1.113,1.52843,1.0879,0.001039,0.0181 3/6/2014,0.4734,20.153832,1581.39375,118.92081,123.54123,0.1798,1.1001,1.52483,1.0674,0.001033,0.0181 3/7/2014,0.4709,19.861428,1607.3310000000001,120.2052,121.63883999999999,0.18,1.1028,1.53013,1.068,0.001035,0.018000000000000002 3/10/2014,0.4719,20.200514000000002,1573.522475,119.828296,116.85698000000001,0.1806,1.1087,1.53844,1.0733,0.001039,0.0182 3/11/2014,0.4713,20.085420000000003,1572.411,120.9247,115.4104,0.1814,1.114,1.544,1.0813,0.001041,0.0182 3/12/2014,0.4722,19.659642,1537.33505,120.183052,115.7104,0.18100000000000002,1.1126,1.54692,1.0828,0.001039,0.0182 3/13/2014,0.4681,19.732086,1539.977475,118.912947,116.2665,0.1804,1.1073,1.53554,1.0873,0.001034,0.018000000000000002 3/14/2014,0.4714,19.1061,1524.0576,120.252132,116.07648,0.1801,1.1076,1.54134,1.0925,0.001033,0.018000000000000002 3/17/2014,0.4686,18.76182,1531.4817,116.90649599999999,115.542,0.1781,1.1004,1.53211,1.0815,0.001031,0.018000000000000002 3/18/2014,0.4683,18.780298000000002,1553.976525,117.009803,114.39108,0.1769,1.0957,1.52672,1.0802,0.001024,0.018000000000000002 3/19/2014,0.4706,19.154188,1582.819375,117.05951499999999,114.12888000000001,0.1785,1.1059,1.52983,1.081,0.001029,0.018000000000000002 3/20/2014,0.4754,18.862415,1586.157625,117.765635,112.73196999999999,0.1776,1.1063,1.52433,1.0803,0.001024,0.018000000000000002 3/21/2014,0.4734,18.531513,1551.174625,117.72961200000002,112.09198,0.1769,1.1011,1.51892,1.0769,0.001019,0.018000000000000002 3/24/2014,0.4717,18.4398,1560.9225,116.95695,112.4565,0.1768,1.095,1.5154100000000001,1.071,0.001016,0.0181 3/25/2014,0.4722,18.51427,1557.9479999999999,116.72608999999999,113.9004,0.1759,1.091,1.50847,1.0669,0.0010119999999999999,0.0181 3/26/2014,0.4707,18.816504000000002,1560.816,116.009817,114.02628,0.1746,1.0839,1.49371,1.0622,0.001007,0.018000000000000002 3/27/2014,0.4779,19.2996,1551.42,116.4564,113.616,0.1738,1.08,1.4839799999999999,1.0571,0.001011,0.018000000000000002 3/28/2014,0.4783,19.443572,1553.4311,116.86689799999999,114.73653999999999,0.174,1.0814,1.48706,1.0515,0.001011,0.0181 4/1/2014,0.4778,18.578452,1605.3383,114.217468,119.06213999999999,0.1742,1.0814,1.49165,1.0433,0.001023,0.0181 4/2/2014,0.4761,18.349660999999998,1581.130925,113.309427,118.943,0.1742,1.0813,1.4886700000000002,1.0409,0.0010220000000000001,0.0181 4/3/2014,0.4744,18.609376,1597.9908,114.98168000000001,119.04368000000001,0.1744,1.0832,1.48617,1.0421,0.001023,0.0179 4/4/2014,0.4806,18.67207,1586.04975,114.85206399999998,118.16676000000001,0.1732,1.0762,1.4749700000000001,1.0418,0.001023,0.018000000000000002 4/8/2014,0.4852,18.332028,1583.75475,115.02386100000001,120.7179,0.1724,1.0683,1.47394,1.0493,0.001018,0.0178 4/9/2014,0.4859,18.145896,1592.291725,114.987902,120.44018999999999,0.1718,1.0649,1.47545,1.0441,0.001029,0.0178 4/10/2014,0.4814,18.144084,1574.594175,114.154758,120.14613,0.171,1.0623,1.47518,1.0463,0.0010220000000000001,0.0176 4/11/2014,0.4801,17.87856,1556.9246,114.22058600000001,120.2546,0.1714,1.0642,1.47765,1.0476,0.001024,0.0176 4/14/2014,0.479,17.603649,1566.448875,115.734177,120.32874,0.1706,1.0611,1.46652,1.0418,0.001019,0.0176 4/15/2014,0.4781,17.689392,1603.63525,116.15606799999999,120.49296000000001,0.1717,1.0682,1.47567,1.0481,0.001025,0.0177 4/16/2014,0.4759,18.055332,1620.658125,116.95416000000002,119.30178000000001,0.1715,1.0671,1.47431,1.0438,0.0010279999999999998,0.0177 4/17/2014,0.4793,17.857854,1622.8566,117.405207,119.19528000000001,0.1723,1.0719,1.48071,1.0468,0.001032,0.0178 4/21/2014,0.4792,18.054164,1606.809875,117.87739499999999,116.64448,0.1721,1.0721,1.47866,1.045,0.001031,0.0177 4/22/2014,0.4766,18.138524,1579.7811,116.65665200000001,116.04812,0.1712,1.0676,1.4738200000000001,1.0404,0.001027,0.0175 4/23/2014,0.484,18.749146,1580.54655,117.435093,116.88618000000001,0.1725,1.0763,1.48709,1.0498,0.001035,0.0176 4/24/2014,0.4871,18.479328,1588.8768,119.090202,116.5752,0.1727,1.0794,1.49295,1.0552,0.0010400000000000001,0.0177 4/25/2014,0.4804,18.548479999999998,1615.4432,118.171072,116.35936000000001,0.1725,1.0784,1.49066,1.0549,0.001035,0.0178 4/28/2014,0.4856,18.296894,1629.060825,116.78041200000001,114.92263999999999,0.1728,1.0801,1.4961799999999998,1.0539,0.001044,0.0178 4/29/2014,0.4831,18.38616,1644.396,117.58941999999999,113.1871,0.1725,1.079,1.4903600000000001,1.0512,0.001047,0.0179 4/30/2014,0.4831,18.564032,1648.3116,116.369776,111.87952,0.1721,1.0768,1.49337,1.053,0.001042,0.0179 5/5/2014,0.4807,18.837901000000002,1587.2576,116.154476,110.31008999999999,0.1727,1.0783,1.49614,1.0558,0.001049,0.0179 5/6/2014,0.4796,18.39368,1565.6016,114.48996399999999,109.18574,0.1717,1.0694,1.48977,1.0516,0.001042,0.0178 5/7/2014,0.4837,18.500994,1555.3269,115.904547,107.94033,0.1719,1.0719,1.49137,1.0522,0.001048,0.0179 5/8/2014,0.4828,18.389908,1572.582475,115.24626799999999,105.92331000000001,0.1713,1.0667,1.4762899999999999,1.0492,0.0010429999999999999,0.0178 5/9/2014,0.4827,18.37304,1603.3682,115.248098,105.53816,0.1715,1.0682,1.4696200000000001,1.0489,0.001041,0.0178 5/12/2014,0.4813,18.467449,1584.793375,115.792721,105.31466,0.1713,1.0681,1.4696,1.046,0.001042,0.0179 5/13/2014,0.4823,19.0193,1605.154125,116.72294,105.3541,0.1715,1.0685,1.46399,1.045,0.001045,0.018000000000000002 5/14/2014,0.4842,19.45815,1595.30175,117.484578,105.44718,0.1712,1.0662,1.4623,1.0464,0.001037,0.0179 5/15/2014,0.4816,19.45216,1571.4032,118.03827199999999,105.8112,0.1716,1.0688,1.4652399999999999,1.0522,0.001039,0.018000000000000002 5/16/2014,0.4823,19.122507000000002,1564.1805,117.180075,105.59553000000001,0.1714,1.0677,1.46317,1.0522,0.0010429999999999999,0.0183 5/19/2014,0.4855,19.047663,1592.039475,117.233703,104.40306,0.1718,1.0719,1.4694,1.056,0.001049,0.0183 5/20/2014,0.4882,19.019802,1590.122525,118.67361100000001,104.61973,0.1734,1.0819,1.48243,1.0677,0.001056,0.0184 5/21/2014,0.4893,18.849152,1626.8742,119.48244,103.86488,0.1734,1.0808,1.4794399999999999,1.0663,0.001053,0.0184 5/22/2014,0.4892,18.838182,1646.173125,119.61920400000001,104.0544,0.1738,1.0839,1.48021,1.0655,0.001058,0.0186 5/23/2014,0.4873,18.816921,1641.74115,119.74798200000001,103.13016,0.1737,1.0833,1.4764899999999999,1.0624,0.001057,0.0185 5/27/2014,0.4823,18.3816,1607.85,118.8216,102.6,0.1729,1.08,1.47252,1.0591,0.0010539999999999998,0.0183 5/28/2014,0.485,18.524997,1621.613925,118.891287,102.09861,0.1731,1.0827,1.4715200000000002,1.063,0.001058,0.0184 5/29/2014,0.4832,18.78226,1610.6755,118.162765,101.4328,0.1722,1.0745,1.46141,1.0557,0.0010550000000000002,0.0182 5/30/2014,0.4791,18.667858,1603.899825,117.51728100000001,99.03201999999999,0.1719,1.0741,1.46438,1.0555,0.001052,0.0181 6/3/2014,0.4733,18.553167000000002,1598.713125,117.449426,98.43216,0.1726,1.0793,1.4708,1.0528,0.0010550000000000002,0.0182 6/4/2014,0.4723,18.364008,1597.69025,116.82268,98.93285999999999,0.1724,1.0777,1.46585,1.0490000000000002,0.00105,0.0182 6/5/2014,0.4726,18.018198,1563.6113,116.470574,97.85284,0.1712,1.0706,1.46251,1.0454,0.00105,0.0181 6/6/2014,0.4766,18.128088,1561.0298,116.364754,97.92596,0.1714,1.0714,1.46176,1.0454,0.00105,0.0182 6/9/2014,0.4798,18.148224,1557.2416,117.55731200000001,97.15392,0.1713,1.0688,1.45295,1.0425,0.001051,0.0181 6/10/2014,0.4792,18.105293,1560.34125,116.84688799999999,96.98121,0.1714,1.0669,1.44534,1.0423,0.001049,0.018000000000000002 6/11/2014,0.4767,17.914417,1540.46935,117.17371499999999,96.12614,0.1711,1.0657,1.44225,1.0441,0.001047,0.018000000000000002 6/12/2014,0.4754,17.717029999999998,1501.438725,119.902918,94.20792,0.1706,1.0609,1.4376200000000001,1.0431,0.001042,0.0179 6/13/2014,0.4782,18.123744,1516.4277,120.622876,93.38408000000001,0.1712,1.0636,1.4400700000000002,1.0423,0.001042,0.0178 6/16/2014,0.47600000000000003,18.18927,1512.315475,120.13427800000001,91.58457,0.1709,1.0637,1.44387,1.0446,0.001042,0.0177 6/17/2014,0.4735,18.27126,1497.52575,121.50495,92.10600000000001,0.172,1.071,1.4509,1.0484,0.001048,0.0178 6/18/2014,0.4771,18.630884,1497.4852,121.435528,92.03848,0.1706,1.0628,1.44507,1.0428,0.001044,0.0178 6/19/2014,0.4787,19.084572,1511.39385,122.400828,91.69955999999999,0.1708,1.0638,1.4478799999999998,1.0435,0.001044,0.0177 6/20/2014,0.4774,19.090176,1508.198475,122.307093,91.40274000000001,0.1711,1.0653,1.4486,1.0436,0.001045,0.0177 6/23/2014,0.4786,18.947775,1512.372125,121.13838,92.5628,0.1705,1.0615,1.44395,1.0412,0.001042,0.0177 6/24/2014,0.4801,19.012175,1508.91125,122.18605,93.086,0.1713,1.0675,1.45242,1.0469,0.001048,0.0177 6/25/2014,0.4815,18.83636,1504.94225,121.182,93.3314,0.1705,1.063,1.4486700000000001,1.0435,0.0010429999999999999,0.0177 6/26/2014,0.4837,18.662854,1526.3814,120.25166200000001,95.0669,0.1706,1.0622,1.44577,1.0442,0.001045,0.0177 6/27/2014,0.4833,17.87785,1519.352,120.2113,95.7022,0.1706,1.061,1.4474200000000002,1.046,0.001046,0.0177 6/30/2014,0.479,17.618862,1484.67005,119.11283600000002,95.83304,0.1709,1.0601,1.45156,1.0462,0.001048,0.0177 7/1/2014,0.4783,18.7434,1474.2,118.24136999999999,94.4541,0.1698,1.053,1.44034,1.0371,0.001041,0.0176 7/2/2014,0.4765,18.922543,1474.51825,117.79203600000001,95.19511,0.1705,1.0589,1.44646,1.0405,0.001049,0.0178 7/3/2014,0.4837,19.054919,1484.753725,118.7589,97.14692,0.1722,1.0699,1.4561,1.0469,0.00106,0.018000000000000002 7/7/2014,0.4796,18.681419,1454.1847,117.61505600000001,98.68825,0.172,1.0669,1.4515799999999999,1.0473,0.0010550000000000002,0.0178 7/8/2014,0.4803,18.809752,1414.721025,115.90126599999999,98.51714,0.1715,1.0639,1.44821,1.0475,0.001051,0.0178 7/9/2014,0.4801,18.505266,1417.63935,115.02584399999999,99.43128,0.1714,1.0623,1.44917,1.0452,0.001052,0.0178 7/10/2014,0.4796,18.403476,1415.3859,115.668348,99.62784,0.1716,1.0644,1.4485299999999999,1.0503,0.00105,0.0177 7/11/2014,0.4792,18.176136,1379.7146,113.571568,99.5588,0.1717,1.0648,1.44886,1.0503,0.0010429999999999999,0.0177 7/14/2014,0.4809,18.300473999999998,1378.6570000000002,113.89090800000001,99.5401,0.1715,1.0646,1.44984,1.0485,0.001044,0.0177 7/15/2014,0.4809,18.366512,1259.8296,113.144544,100.3168,0.1719,1.0672,1.44793,1.0495,0.001039,0.0177 7/16/2014,0.4796,18.220518,1267.27065,112.98428999999999,101.18952,0.172,1.0674,1.44374,1.0498,0.001036,0.0178 7/17/2014,0.4739,18.094248,1256.27765,115.37756599999999,101.48606,0.1724,1.0694,1.4464299999999999,1.057,0.001035,0.0176 7/18/2014,0.4783,18.062867999999998,1252.5327,114.14625600000001,100.37292,0.1715,1.0644,1.44016,1.0503,0.001034,0.0177 7/21/2014,0.48,18.42912,1253.937375,114.84071999999999,99.6111,0.1718,1.0665,1.44276,1.0521,0.001038,0.0177 7/22/2014,0.4808,18.266820000000003,1260.368,114.252785,98.5727,0.1716,1.0645,1.43346,1.0492,0.001039,0.0177 7/23/2014,0.4762,17.9352,1270.0575,114.241725,97.81875,0.1706,1.0575,1.4237799999999998,1.042,0.001033,0.0176 7/24/2014,0.4779,18.101985,1282.00275,113.67621899999999,97.78256999999999,0.1714,1.0617,1.42941,1.0428,0.001031,0.0177 7/25/2014,0.4775,18.242102,1290.197675,115.359477,97.17059,0.1719,1.0643,1.42933,1.045,0.001037,0.0177 7/28/2014,0.4781,18.008914,1314.52315,114.35766699999999,97.91150999999999,0.1718,1.0631,1.42886,1.0436,0.001036,0.0177 7/29/2014,0.4778,17.711934,1307.08105,114.79720400000001,98.36411,0.1724,1.0657,1.42897,1.0435,0.001038,0.0177 7/30/2014,0.4769,17.824034,1308.1319,114.15741799999999,98.92714000000001,0.1737,1.0718,1.43575,1.0426,0.001042,0.0177 7/31/2014,0.4753,17.707667999999998,1317.3171,114.056316,99.29634,0.1743,1.0758,1.44056,1.0466,0.001042,0.0177 8/1/2014,0.4752,17.55663,1304.667,112.577192,99.54126,0.1738,1.0738,1.4418,1.0465,0.001041,0.0177 8/4/2014,0.4742,17.485248000000002,1320.5005,112.936274,99.21164,0.1734,1.0714,1.43798,1.0443,0.001037,0.0176 8/5/2014,0.4703,17.334910999999998,1314.089425,112.42436699999999,100.05457,0.1742,1.0747,1.4375799999999999,1.0476,0.001038,0.0176 8/6/2014,0.47,17.44608,1322.3529999999998,111.80671000000001,99.7377,0.1734,1.069,1.43064,1.047,0.001034,0.0175 8/7/2014,0.4702,17.311529999999998,1348.25,113.72758400000001,100.95696,0.1751,1.0786,1.44144,1.0565,0.0010400000000000001,0.0175 8/8/2014,0.4722,17.397306,1384.832025,113.201058,100.67586,0.1751,1.0779,1.44565,1.0566,0.001045,0.0176 8/11/2014,0.4744,17.532704000000003,1419.4041,113.012528,100.51076,0.1754,1.0796,1.44505,1.0566,0.001048,0.0177 8/12/2014,0.4742,17.316345000000002,1391.781,111.148278,99.36669,0.1752,1.0789,1.44235,1.055,0.00105,0.0176 8/13/2014,0.4711,17.216694,1358.95815,112.06971599999999,98.44252,0.1746,1.0747,1.43635,1.0494,0.0010429999999999999,0.0176 8/14/2014,0.4722,17.073021,1314.01095,109.466931,97.00824,0.1744,1.0731,1.43413,1.0474,0.001052,0.0176 8/15/2014,0.4747,17.077384,1182.65175,111.05663100000001,96.97208,0.1745,1.0727,1.43767,1.048,0.0010539999999999998,0.0176 8/18/2014,0.4748,16.815232,1196.2622,108.95584,96.62324,0.1746,1.0724,1.43317,1.0455,0.0010539999999999998,0.0176 8/19/2014,0.4775,16.628703,1204.156725,109.166844,96.63351,0.175,1.0749,1.43187,1.0444,0.0010539999999999998,0.0177 8/20/2014,0.47600000000000003,16.902620000000002,1205.52285,110.114648,95.8174,0.1753,1.0766,1.4277,1.0377,0.001052,0.0177 8/21/2014,0.4737,17.18925,1221.46875,110.32725,95.03,0.1747,1.075,1.4276200000000001,1.0352,0.00105,0.0178 8/22/2014,0.4709,16.787976,1251.5844,109.79808600000001,94.13718,0.1745,1.0734,1.42131,1.033,0.0010539999999999998,0.0178 8/25/2014,0.4704,16.521216,1210.8567,110.41033999999999,94.22256,0.1748,1.0756,1.4188399999999999,1.0337,0.0010539999999999998,0.0178 8/26/2014,0.4746,16.880395,1155.62475,110.13625,93.80385,0.1746,1.0745,1.41487,1.0326,0.001057,0.0178 8/27/2014,0.4767,16.68618,1162.83825,110.01312,93.0699,0.1743,1.071,1.41299,1.0311,0.001056,0.0178 8/28/2014,0.4771,16.630527999999998,1147.624,109.509248,92.13056,0.174,1.0688,1.40893,1.0304,0.001052,0.0176 8/29/2014,0.4788,16.585143,1166.52765,110.485533,92.29434,0.1743,1.0707,1.40622,1.0287,0.0010550000000000002,0.0177 9/2/2014,0.4806,17.057123999999998,1183.05495,108.18658799999999,92.50956,0.1754,1.0782,1.41609,1.0258,0.001059,0.0178 9/3/2014,0.4784,16.7134,1156.4025,109.9639,91.164,0.1742,1.07,1.40698,1.0209,0.001049,0.0177 9/4/2014,0.47700000000000004,16.183048,1138.3218,108.917368,90.59512,0.1742,1.0696,1.38456,1.0161,0.001047,0.0177 9/5/2014,0.4759,15.999,1157.7943,107.53461200000001,88.42114000000001,0.1737,1.0666,1.38095,1.0149,0.001041,0.0177 9/9/2014,0.4753,16.168608,1169.7249,107.74725600000001,89.53584000000001,0.1771,1.0866,1.40577,1.0231,0.00105,0.0178 9/10/2014,0.4768,15.861648,1169.9604,107.098896,89.24908,0.1782,1.0924,1.4107100000000001,1.0221,0.001058,0.018000000000000002 9/11/2014,0.4785,15.780204000000001,1166.48235,107.78011200000002,89.78013,0.1793,1.0989,1.42031,1.0262,0.00106,0.018000000000000002 9/12/2014,0.4731,15.247570000000001,1207.1915,107.452215,90.2904,0.1804,1.1065,1.43441,1.0309,0.0010689999999999999,0.0181 9/15/2014,0.473,15.140892000000001,1095.9702,107.04954,92.04156,0.1804,1.1076,1.43333,1.0334,0.001067,0.0181 9/16/2014,0.4718,14.900935,1078.530775,108.925285,91.82495,0.1789,1.0997,1.4250399999999999,1.0265,0.001065,0.018000000000000002 9/17/2014,0.4736,15.487304,1096.2735,110.430726,93.1693,0.1817,1.1158,1.43603,1.0295,0.0010710000000000001,0.0183 9/18/2014,0.4703,15.339996,1080.6966,108.68148000000001,92.77416,0.1811,1.1124,1.43737,1.0233,0.001065,0.0183 9/19/2014,0.4728,15.1254,1072.2228,110.23615600000001,92.88116,0.1824,1.1204,1.43721,1.0273,0.001073,0.0184 9/22/2014,0.4704,15.868160000000001,1057.40775,109.28518999999999,92.6394,0.1835,1.127,1.4481600000000001,1.0355,0.001083,0.0185 9/23/2014,0.4689,16.00648,1059.086,109.55672,92.41904,0.1843,1.1312,1.4532100000000001,1.0387,0.0010869999999999999,0.0185 9/24/2014,0.4722,16.453348000000002,1054.21845,109.10753000000001,91.7201,0.1835,1.1254,1.4384700000000001,1.0321,0.001082,0.0185 9/25/2014,0.4691,16.7286,1050.0895,110.38600000000001,92.6332,0.1854,1.138,1.4510100000000001,1.0463,0.00109,0.0185 9/26/2014,0.4723,17.581269,1038.504225,110.6673,93.09744,0.1862,1.1409,1.44712,1.0438,0.0010869999999999999,0.0186 9/29/2014,0.4681,17.962020000000003,1059.2545,111.4884,92.7923,0.1865,1.147,1.45505,1.0474,0.001086,0.0186 9/30/2014,0.4666,17.695188,1043.936075,108.217277,92.36248,0.1863,1.1431,1.4441700000000002,1.0426,0.00108,0.0185 10/8/2014,0.4757,19.138212,1057.5785,103.35991800000001,91.39288,0.1843,1.1311,1.44031,1.0466,0.001058,0.0185 10/9/2014,0.4754,19.01462,1072.5612,102.53093,92.68204,0.1857,1.1386,1.4450100000000001,1.0559,0.001065,0.0186 10/10/2014,0.4739,19.054015,1062.07425,103.858773,93.71582,0.1878,1.1513,1.45394,1.0698,0.001073,0.0188 10/13/2014,0.4762,19.0038,1077.585,101.3346,94.848,0.1861,1.14,1.45374,1.067,0.0010689999999999999,0.0187 10/14/2014,0.478,19.292837,1107.243575,97.600408,96.29203000000001,0.1874,1.1477,1.45272,1.0721,0.001077,0.0187 10/15/2014,0.4609,18.68955,1078.89675,94.89760600000001,94.12737,0.1849,1.1327,1.45402,1.0694,0.001068,0.0184 10/16/2014,0.4618,19.038807000000002,1103.83965,96.473187,94.10904000000001,0.1865,1.1421,1.4627700000000001,1.074,0.001076,0.0185 10/17/2014,0.4696,18.993336,1087.6599,98.46364799999999,93.93816,0.1867,1.1428,1.45926,1.0698,0.001075,0.0186 10/20/2014,0.4625,18.988512,1074.9342,97.21936,93.57648,0.1859,1.1384,1.4573399999999999,1.0646,0.001078,0.0186 10/21/2014,0.4605,18.720228,1097.991475,98.178714,92.91792,0.18600000000000003,1.1387,1.44846,1.0642,0.0010789999999999999,0.0186 10/22/2014,0.4584,18.79845,1096.861075,96.510103,92.96688,0.1862,1.1393,1.44085,1.0632,0.0010810000000000001,0.0186 10/24/2014,0.4598,18.61587,1110.92875,97.88674499999999,91.8292,0.1858,1.1365,1.4415200000000001,1.0503,0.001075,0.0186 10/27/2014,0.4505,18.211682999999997,1142.9166,97.511463,91.22883,0.1857,1.1361,1.44265,1.0537,0.00108,0.0185 10/28/2014,0.45799999999999996,18.212383,1138.1328,97.136473,90.21509,0.1847,1.1291,1.4380000000000002,1.0439,0.001078,0.0184 10/29/2014,0.4616,18.531470000000002,1185.7867,99.046728,90.04248,0.18600000000000003,1.1369,1.43587,1.0438,0.0010789999999999999,0.0185 10/30/2014,0.4713,18.44997,1159.348575,97.61505600000001,88.96734000000001,0.1851,1.1319,1.42769,1.0366,0.001074,0.0184 10/31/2014,0.4593,18.231064,1189.4519,97.588476,88.0865,0.18600000000000003,1.1366,1.42364,1.012,0.001059,0.0185 11/3/2014,0.4615,18.346581,1184.811375,97.641126,88.56573,0.1882,1.1517,1.43783,1.0101,0.0010630000000000001,0.0187 11/4/2014,0.4559,17.942624,1155.743,94.770926,87.42452,0.1871,1.1443,1.4357600000000001,1.0073,0.0010609999999999999,0.0187 11/5/2014,0.4645,18.047435999999998,1187.4538,96.52062,88.54996,0.1903,1.1636,1.4529,1.0149,0.001067,0.019 11/6/2014,0.4546,18.085283999999998,1204.5173,96.805338,88.44031,0.1911,1.1683,1.44584,1.0141,0.00107,0.019 11/7/2014,0.4525,18.16902,1204.6095,96.56562,86.7342,0.1892,1.158,1.4419600000000001,1.0103,0.001065,0.0189 11/10/2014,0.4544,18.1656,1191.9,95.5144,86.884,0.1895,1.16,1.4406299999999999,1.0099,0.001064,0.0189 11/11/2014,0.4501,18.688845,1228.07475,94.04300500000001,86.1322,0.188,1.1515,1.43622,0.9944,0.001052,0.0187 11/12/2014,0.4469,18.76492,1202.34275,92.19586,85.7956,0.1872,1.147,1.42661,0.9935,0.001047,0.0187 11/13/2014,0.4424,18.365071,1205.02855,89.382032,85.80308000000001,0.1872,1.1471,1.43049,0.9907,0.001045,0.0186 11/14/2014,0.4394,18.1737,1167.003,90.76563,85.4964,0.1865,1.143,1.4313799999999999,0.9827,0.001039,0.0185 11/17/2014,0.4402,18.107114000000003,1189.82225,91.063742,85.65572,0.1874,1.1482,1.4296,0.9843,0.0010429999999999999,0.0186 11/18/2014,0.444,18.014657,1173.360775,89.981549,83.7091,0.1873,1.1467,1.4377,0.9814,0.001042,0.0186 11/19/2014,0.4511,18.412374,1165.71095,90.61162,84.1145,0.1895,1.1602,1.45666,0.9835,0.001041,0.0187 11/20/2014,0.4509,18.67278,1183.5759,92.006934,82.57776,0.1893,1.1598,1.4548,0.9813,0.0010429999999999999,0.0187 11/21/2014,0.4584,18.563032999999997,1198.6943,92.711332,82.14344,0.1883,1.1537,1.42903,0.9790000000000001,0.001038,0.0187 11/24/2014,0.4554,18.5648,1199.460125,92.452704,82.3813,0.1889,1.1603,1.44377,0.981,0.001042,0.0187 11/25/2014,0.4632,18.7584,1232.1924,91.834092,82.18524000000001,0.1911,1.1724,1.46232,0.9937,0.001056,0.019 11/26/2014,0.4677,18.852339999999998,1224.4665,90.928625,81.1633,0.1905,1.1695,1.4630100000000001,0.9934,0.001059,0.0189 11/28/2014,0.4582,18.326045,1194.308,82.461325,82.7552,0.1913,1.1755,1.4638799999999998,0.9914,0.001056,0.0189 12/1/2014,0.4606,18.355666,1197.4158,85.408596,83.24218,0.1915,1.1774,1.46862,0.9951,0.0010609999999999999,0.019 12/2/2014,0.4609,18.047207999999998,1179.16715,83.533468,83.72294000000001,0.1926,1.1842,1.4663,0.9933,0.0010609999999999999,0.0192 12/3/2014,0.466,17.952573,1187.618025,83.183824,83.16003,0.1934,1.1897,1.46468,0.9932,0.001066,0.0192 12/4/2014,0.4604,18.140967,1205.22335,83.059628,84.20461999999999,0.1938,1.1927,1.4763700000000002,0.9958,0.001072,0.0194 12/5/2014,0.4642,18.186168,1244.4432,82.966884,85.2852,0.1954,1.2012,1.47671,0.9886,0.00107,0.0194 12/8/2014,0.4637,18.447210000000002,1258.449375,79.805283,85.6047,0.1954,1.2057,1.4851299999999998,0.9990000000000001,0.001084,0.0195 12/9/2014,0.465,18.593435999999997,1265.18565,80.595672,84.52658000000001,0.1949,1.2058,1.49213,1.0073,0.001091,0.0194 12/10/2014,0.4596,18.591846,1240.2576,77.203632,84.24618000000001,0.1946,1.2018,1.4965,1.0204,0.001091,0.0193 12/11/2014,0.4562,18.311805,1259.767575,76.970016,84.609,0.1952,1.2087,1.50082,1.0183,0.0010960000000000002,0.0193 12/12/2014,0.4568,18.166245999999997,1270.000075,75.005495,84.28265,0.1959,1.2127,1.5111700000000001,1.0211,0.001099,0.0194 12/15/2014,0.4517,18.212304,1265.4873,74.33444399999999,84.6093,0.1966,1.2174,1.5144,1.0336,0.001109,0.0191 12/16/2014,0.4443,17.896186,1245.1901,72.825676,83.9454,0.1965,1.2166,1.52229,1.0452,0.001125,0.0191 12/17/2014,0.4534,18.114432,1263.8262,75.288108,84.2961,0.1987,1.2306,1.51946,1.0377,0.0011220000000000002,0.0194 12/18/2014,0.46,18.352257,1267.1505,72.564261,82.88511,0.19699999999999998,1.2243,1.50475,1.0307,0.001113,0.0194 12/19/2014,0.4617,18.390946,1265.14485,75.356226,82.99252,0.1973,1.2277,1.50481,1.0273,0.001116,0.0194 12/22/2014,0.4616,18.271856,1276.6322,73.91125600000001,83.12096,0.1975,1.2296,1.50338,1.0244,0.001118,0.0194 12/23/2014,0.4577,18.295771,1281.19745,76.106953,82.53453,0.1982,1.2337,1.50183,1.0224,0.001115,0.0194 12/24/2014,0.4575,18.196128,1268.243,74.26387199999999,82.5976,0.1983,1.2328,1.50396,1.0234,0.001117,0.0194 12/26/2014,0.4617,18.10158,1289.8915,73.20673000000001,81.64182,0.1982,1.2314,1.49999,1.023,0.001113,0.0193 12/29/2014,0.4545,17.94632,1280.5191,71.146096,82.11055999999999,0.1975,1.2292,1.49437,1.0195,0.001117,0.0193 12/30/2014,0.4599,17.850498,1267.92295,70.74221999999999,84.67074000000001,0.19699999999999998,1.2218,1.48555,1.0231,0.001114,0.0193 12/31/2014,0.4609,17.771028,1247.460075,70.166187,84.81626999999999,0.1973,1.2239,1.47995,1.0229,0.001119,0.0194 1/5/2015,0.4568,17.638194,1286.066775,65.69175899999999,86.33561999999999,0.1989,1.2369,1.47622,1.0341,0.001115,0.0195 1/6/2015,0.4576,18.391216,1299.8768,63.200480000000006,87.31808000000001,0.1991,1.2368,1.47076,1.0449,0.001125,0.0195 1/7/2015,0.462,18.297639999999998,1303.3045,63.3237,87.4028,0.1993,1.238,1.46555,1.0379,0.001127,0.0196 1/8/2015,0.4631,18.318768,1286.4995,62.736856,86.91566,0.1981,1.2311,1.4517200000000001,1.0291,0.001123,0.0197 1/9/2015,0.4631,18.173799,1281.67335,61.07907900000001,86.05434,0.1963,1.2189,1.44345,1.0284,0.001123,0.0196 1/12/2015,0.4586,18.095760000000002,1242.5510000000002,58.14918,86.0652,0.1976,1.226,1.45072,1.036,0.001132,0.0197 1/13/2015,0.4635,18.208315,1224.5,57.049455,85.4701,0.1975,1.2245,1.4417200000000001,1.0385,0.001135,0.0198 1/14/2015,0.4689,18.323589000000002,1218.09525,59.757236999999996,85.17461999999999,0.198,1.2273,1.4465700000000001,1.0458,0.0011330000000000001,0.0197 1/15/2015,0.4606,18.668670000000002,1205.2542,57.976254000000004,84.40428,0.1966,1.2162,1.4156799999999998,1.0475,0.001131,0.0196 1/16/2015,0.4638,18.636681,1205.670475,60.991668999999995,83.64016,0.1959,1.2157,1.4068100000000001,1.0334,0.001126,0.0197 1/20/2015,0.4682,19.372754,1201.7716,58.730162,83.09602,0.1969,1.2238,1.41346,1.0303,0.001125,0.0198 1/21/2015,0.4747,19.673935999999998,1215.4093,60.591274,83.54008,0.1991,1.2358,1.43603,1.0484,0.001142,0.0201 1/22/2015,0.4848,19.825451,1217.128175,60.460772,83.36409,0.2006,1.2461,1.4159700000000002,1.0514,0.001149,0.0203 1/23/2015,0.4893,19.176397,1229.653275,61.675439000000004,83.30419,0.2029,1.2641,1.41583,1.0731,0.001173,0.0206 1/26/2015,0.4884,19.3717,1241.177,60.777919999999995,82.661,0.2018,1.262,1.41814,1.0655,0.001168,0.0205 1/27/2015,0.4896,19.100084,1226.827625,62.491040000000005,81.51553,0.2018,1.2599,1.4339600000000001,1.069,0.001169,0.0205 1/28/2015,0.4911,19.219848000000002,1230.08295,61.450266000000006,81.39276,0.2029,1.2678,1.43089,1.0784,0.001167,0.0207 1/29/2015,0.4945,19.128285,1247.202825,63.284353,82.69601999999999,0.2062,1.2881,1.45845,1.089,0.0011710000000000002,0.0209 1/30/2015,0.4789,19.03473,1236.807,68.19813,82.6254,0.20600000000000002,1.287,1.45464,1.0953,0.001168,0.0207 2/2/2015,0.4697,18.225773999999998,1229.79115,70.173075,81.77246,0.2047,1.2817,1.45347,1.0898,0.001166,0.0208 2/3/2015,0.4755,18.572245000000002,1266.8145,74.327485,81.8873,0.2051,1.2835,1.47329,1.0918,0.001174,0.0208 2/4/2015,0.4689,18.63472,1253.4912,69.844736,82.5344,0.2064,1.2896,1.46338,1.0998,0.001185,0.0209 2/5/2015,0.4665,18.479384,1258.355,72.54536800000001,81.94536,0.2051,1.2824,1.47183,1.0911,0.00118,0.0208 2/6/2015,0.4607,18.609075,1248.51375,74.1285,82.08,0.2054,1.2825,1.45125,1.0767,0.001168,0.0207 2/9/2015,0.4621,18.994794,1254.14345,74.774378,82.0288,0.2052,1.2817,1.4514,1.0804,0.00117,0.0206 2/10/2015,0.4547,18.928828,1246.9092,72.614124,81.96916,0.2062,1.2868,1.4569,1.0776,0.0011710000000000002,0.0206 2/11/2015,0.4521,19.056804999999997,1266.675125,70.81203000000001,82.912,0.2075,1.2955,1.46859,1.0756,0.001169,0.0208 2/12/2015,0.4568,19.443711999999998,1271.792,73.75424,82.7392,0.207,1.2928,1.47425,1.0854,0.001174,0.0208 2/13/2015,0.4543,19.169904000000002,1276.06115,79.25621600000001,83.48184,0.2064,1.2883,1.46793,1.0854,0.001174,0.0207 2/17/2015,0.452,19.365574,1289.013025,79.982123,82.62986,0.2046,1.2791,1.45943,1.0726,0.001153,0.0206 2/25/2015,0.4419,17.48572,1277.827,78.14684,81.9128,0.2026,1.268,1.44054,1.0669,0.001152,0.0205 2/26/2015,0.4412,18.05056,1312.7679999999998,76.9841,82.4326,0.2049,1.2819999999999998,1.4356799999999998,1.0737,0.0011619999999999998,0.0208 2/27/2015,0.4505,17.833185999999998,1319.56615,80.11491600000001,82.18884,0.2042,1.2802,1.43351,1.0706,0.001163,0.0208 3/2/2015,0.4448,17.565592000000002,1302.28775,76.675612,82.54798000000001,0.2053,1.2878,1.44012,1.072,0.001167,0.0208 3/3/2015,0.4363,17.206585,1290.493875,78.06288599999999,81.49141,0.2039,1.2793,1.42964,1.0684,0.001166,0.0207 3/4/2015,0.4293,17.064528,1265.1288,77.45555999999999,81.2292,0.204,1.2792,1.4171200000000002,1.0688,0.001161,0.0205 3/5/2015,0.4279,17.2704,1258.33625,77.7168,79.7985,0.2051,1.285,1.4173,1.0697,0.001166,0.0207 3/6/2015,0.4228,17.41824,1269.108,77.41008000000001,80.4816,0.2069,1.296,1.40524,1.0726,0.001166,0.0207 3/9/2015,0.4158,17.228441,1283.044975,75.989499,80.10511,0.2072,1.2983,1.40888,1.0716,0.001165,0.0207 3/10/2015,0.4226,17.074428,1285.172,73.949846,79.9954,0.2094,1.3114,1.40291,1.0826,0.001163,0.0209 3/11/2015,0.42100000000000004,17.29881,1302.0185,75.75140999999999,79.38495,0.2102,1.3165,1.3886399999999999,1.0839,0.001163,0.021 3/12/2015,0.4098,17.138654000000002,1279.8851,74.055592,78.23321999999999,0.2072,1.2974,1.37976,1.0697,0.001152,0.0208 3/13/2015,0.4029,16.63065,1267.923375,71.590365,79.0938,0.2092,1.3095,1.37437,1.0787,0.00115,0.0208 3/16/2015,0.4033,16.8861,1268.74825,69.95296,79.0636,0.2091,1.3090000000000002,1.38295,1.0792,0.0011560000000000001,0.0208 3/17/2015,0.4053,16.830095999999998,1253.0676,70.247928,79.16184,0.2101,1.3128,1.39119,1.0815,0.0011619999999999998,0.021 3/18/2015,0.4006,16.373326000000002,1241.183,71.91144200000001,77.172,0.2064,1.2862,1.39717,1.0708,0.001157,0.0207 3/19/2015,0.3972,16.496864000000002,1257.1996,71.150896,77.90912,0.21100000000000002,1.3072,1.39363,1.0824,0.001165,0.0209 3/20/2015,0.3981,16.310284,1252.534625,71.158116,75.37718000000001,0.2072,1.2863,1.39192,1.0713,0.001155,0.0206 3/23/2015,0.4049,16.165785999999997,1247.96315,70.956888,74.23065,0.2042,1.2689,1.3889200000000002,1.06,0.00115,0.0204 3/24/2015,0.4044,15.802785,1246.135275,69.951123,73.23861,0.2046,1.2693,1.38687,1.06,0.00115,0.0204 3/25/2015,0.3981,15.960496,1247.7105,72.000704,73.42848000000001,0.2052,1.2748,1.39835,1.0669,0.001158,0.0204 3/26/2015,0.4013,15.763116,1244.8263,75.609306,73.19502,0.2056,1.2774,1.39037,1.0717,0.0011560000000000001,0.0203 3/27/2015,0.3972,15.656191,1248.429575,72.808387,73.05362,0.2076,1.2907,1.40462,1.0835,0.001169,0.0206 3/30/2015,0.4046,15.666134,1264.46215,73.548514,73.03894,0.2105,1.3066,1.4154,1.0882,0.001179,0.0209 3/31/2015,0.4113,15.684370999999999,1279.531775,72.453117,72.04556,0.212,1.3147,1.4108,1.0943,0.001185,0.0211 4/7/2015,0.4186,16.726146,1271.8158,77.40918,66.27588,0.2113,1.3098,1.4167299999999998,1.0889,0.001196,0.021 4/8/2015,0.4268,16.877861,1264.21295,72.287215,65.71565,0.2098,1.3013,1.40295,1.0834,0.001191,0.0209 4/9/2015,0.425,16.64,1239.55,73.541,65.65,0.2095,1.3,1.3856700000000002,1.0782,0.001185,0.0209 4/10/2015,0.4233,16.708509,1239.13845,75.364101,65.76615,0.2097,1.3023,1.38038,1.0831,0.001191,0.0209 4/13/2015,0.4219,17.141976,1250.073,76.328568,66.40704000000001,0.212,1.3176,1.39235,1.0968,0.001196,0.0211 4/14/2015,0.4281,17.294728,1259.0798,76.613416,68.1824,0.2111,1.3112,1.39723,1.0982,0.001201,0.0211 4/15/2015,0.4298,16.9234,1256.237,78.524576,67.82378,0.2098,1.3018,1.39125,1.0926,0.001192,0.0209 4/16/2015,0.4243,17.210545,1237.9289999999999,81.99037,66.8943,0.2068,1.2815,1.3790799999999999,1.0769,0.001182,0.0206 4/17/2015,0.4226,17.012076,1244.746875,81.526905,67.07178,0.2073,1.2849,1.38847,1.0806,0.001186,0.0206 4/20/2015,0.4271,16.427204999999997,1265.37375,82.136025,67.44345,0.2087,1.2945,1.39,1.0863,0.0011949999999999999,0.0205 4/21/2015,0.4279,16.094529,1264.801725,80.51155200000001,67.56849,0.2091,1.2969,1.39224,1.0837,0.0011970000000000001,0.0206 4/22/2015,0.4284,16.32507,1251.45975,80.890335,69.1172,0.2082,1.2895,1.3829200000000001,1.0753,0.00119,0.0205 4/23/2015,0.4328,16.829813,1257.736025,83.377645,69.68494,0.2074,1.2857,1.39152,1.075,0.001189,0.0203 4/24/2015,0.4332,16.911909,1239.631425,83.447424,72.22395,0.2063,1.2783,1.39002,1.0744,0.001187,0.02 4/27/2015,0.4362,16.935644,1238.0452,82.489692,73.54472,0.2046,1.2724,1.38582,1.0689,0.00119,0.0201 4/28/2015,0.424,16.417722,1218.5515,80.580224,73.92338000000001,0.2009,1.2466,1.36853,1.0487,0.0011710000000000002,0.0198 4/29/2015,0.4217,16.342865,1234.14225,82.20124,72.28815,0.2014,1.2485,1.38986,1.0490000000000002,0.001167,0.0197 4/30/2015,0.4197,16.4197,1237.8025,84.4767,73.2435,0.2039,1.265,1.41982,1.0599,0.001174,0.0199 5/4/2015,0.4135,15.961509,1254.2097,84.783555,73.74701999999999,0.2055,1.2759,1.4222,1.0623,0.00118,0.0201 5/5/2015,0.4121,16.053525,1250.91585,85.014432,73.65735,0.2029,1.2591,1.40842,1.0504,0.001165,0.0199 5/6/2015,0.4137,16.154424,1243.2756,85.064904,74.43336,0.2024,1.2552,1.4239600000000001,1.0506,0.001161,0.0197 5/7/2015,0.418,16.390512,1241.30305,82.888438,74.87024,0.2038,1.2647,1.4249,1.0562,0.0011560000000000001,0.0197 5/8/2015,0.4236,16.914568,1240.8638,82.417556,73.85944,0.203,1.2604,1.41266,1.0526,0.001159,0.0198 5/11/2015,0.4139,17.083204000000002,1245.7559,82.26044300000001,75.15089,0.2041,1.2673,1.41369,1.0554,0.001155,0.0198 5/12/2015,0.4151,17.023888,1212.2312,83.815696,76.09352,0.2019,1.2536,1.40575,1.0459,0.001147,0.0195 5/13/2015,0.4056,15.974495999999998,1201.785,82.35000600000001,74.5723,0.1987,1.2326,1.3995799999999998,1.0344,0.0011279999999999999,0.0193 5/14/2015,0.4133,15.8895,1191.7125,82.405125,73.5075,0.1996,1.2375,1.41201,1.0385,0.001137,0.0195 5/15/2015,0.4153,16.042894,1186.41495,83.151726,73.80478000000001,0.2005,1.2446,1.42408,1.0428,0.001147,0.0196 5/18/2015,0.4162,15.99417,1194.55675,82.93690500000001,74.21395,0.2017,1.2515,1.41602,1.0431,0.0011480000000000001,0.0196 5/19/2015,0.4159,16.24861,1195.586875,80.88927,74.92555,0.2036,1.2635,1.40889,1.0469,0.0011539999999999999,0.0198 5/20/2015,0.4229,15.986782,1195.19925,82.57509399999999,74.66424,0.2047,1.2698,1.40872,1.0465,0.001158,0.02 5/21/2015,0.4168,15.818585,1188.61025,84.27291,74.59685,0.2044,1.2665,1.40745,1.0465,0.001158,0.0199 5/22/2015,0.4132,15.728487,1180.914225,83.52324899999999,75.51207,0.20600000000000002,1.2777,1.40777,1.0507,0.001165,0.0201 5/26/2015,0.41,15.617023999999999,1192.608,82.377216,78.60224000000001,0.2084,1.2928,1.40575,1.05,0.001167,0.0202 5/27/2015,0.41200000000000003,15.358592999999999,1199.4453,80.29943399999999,79.57485,0.2086,1.2939,1.4107100000000001,1.0462,0.001166,0.0202 5/28/2015,0.4134,15.607968,1210.4672,81.804576,80.3928,0.2108,1.3072,1.4314,1.0546,0.001179,0.0205 5/29/2015,0.4117,15.671038000000001,1221.7654,85.759036,79.92491,0.2111,1.3081,1.43671,1.0539,0.001173,0.0205 6/1/2015,0.4147,16.105075,1217.4122,85.297736,81.24846,0.2121,1.3147,1.4367299999999998,1.0537,0.001178,0.0207 6/2/2015,0.4108,15.850912,1210.36895,84.259434,79.51188,0.2076,1.2866,1.43471,1.0366,0.0011619999999999998,0.0202 6/3/2015,0.4096,15.475814999999999,1201.141575,81.93834,80.39718,0.2072,1.2843,1.4479799999999998,1.0338,0.00116,0.0201 6/4/2015,0.4152,15.764484,1231.11255,80.68242099999999,82.33431,0.2098,1.3007,1.4617200000000001,1.0458,0.001168,0.0203 6/5/2015,0.4172,15.801165,1229.671575,83.018403,83.13642,0.2114,1.3113,1.4580799999999998,1.0452,0.001167,0.0205 6/8/2015,0.4169,15.788544,1226.0142,81.39669599999999,82.18871999999999,0.2092,1.2984,1.4659200000000001,1.043,0.001161,0.0203 6/9/2015,0.4197,15.694621,1237.23545,84.36346400000001,82.30899000000001,0.2095,1.3003,1.46698,1.0457,0.001159,0.0203 6/10/2015,0.4132,15.470081,1223.05095,84.62817,82.56721,0.2076,1.2881,1.4598,1.05,0.00116,0.0202 6/11/2015,0.4173,15.00978,1212.13,83.959345,83.5596,0.2078,1.2895,1.4516799999999999,1.0447,0.001158,0.0202 6/12/2015,0.4146,15.160992000000002,1215.984,82.622232,83.82528,0.2083,1.2936,1.45729,1.0482,0.001163,0.0202 6/15/2015,0.4118,14.757042000000002,1207.540675,80.622897,83.44296,0.2074,1.2877,1.4530399999999999,1.0435,0.001153,0.0201 6/16/2015,0.4175,14.588769000000001,1235.07925,82.16663,82.68259,0.2078,1.2899,1.45096,1.0456,0.001153,0.0201 6/17/2015,0.4226,14.644905,1250.3007,82.411461,81.67599,0.2078,1.2903,1.46302,1.0454,0.001157,0.0202 6/18/2015,0.419,14.423625,1253.573275,82.38774599999999,80.25946,0.2065,1.2821,1.45655,1.0427,0.00116,0.0201 6/19/2015,0.4155,14.309216000000001,1250.1262,81.09413599999999,79.52424,0.2072,1.2868,1.4622,1.0489,0.001166,0.0203 6/23/2015,0.4204,14.540625,1276.34375,83.301625,80.52275,0.2083,1.2925,1.44346,1.0429,0.001168,0.0203 6/24/2015,0.4189,14.939979999999998,1274.3115,82.41001999999999,81.5144,0.2091,1.298,1.45441,1.048,0.001169,0.0204 6/25/2015,0.4132,14.887296,1292.623075,81.67336,81.15644,0.2081,1.2923,1.44779,1.0452,0.0011619999999999998,0.0203 6/26/2015,0.4174,15.244520999999999,1308.9126,82.636538,81.38249,0.2103,1.3063,1.4586,1.0546,0.001163,0.0206 6/29/2015,0.4178,15.392004,1305.4555,80.749422,80.0853,0.2097,1.3022,1.46317,1.0626,0.001163,0.0204 6/30/2015,0.4182,15.9333,1370.484375,82.508025,79.79625,0.2093,1.2975,1.44605,1.0594,0.001159,0.0204 7/1/2015,0.4153,16.271520000000002,1365.5520000000001,81.10908,79.5264,0.2109,1.308,1.44585,1.0619,0.0011619999999999998,0.0206 7/2/2015,0.4231,16.11669,1369.591075,81.330321,78.618,0.2112,1.3103,1.45218,1.0646,0.001166,0.0207 7/6/2015,0.425,16.640832,1378.40225,75.390436,76.93718,0.2148,1.3334,1.4741799999999998,1.088,0.001184,0.0211 7/7/2015,0.4212,16.545627,1344.5838,76.287015,74.47545,0.2161,1.3419,1.47769,1.0951,0.001182,0.0211 7/8/2015,0.4158,16.56926,1354.4125,76.7893,71.7418,0.2168,1.3459999999999999,1.49091,1.1151,0.001185,0.0212 7/9/2015,0.4169,15.98051,1393.594475,78.707369,72.5166,0.2163,1.3429,1.48189,1.1068,0.001186,0.0212 7/10/2015,0.4251,16.667870999999998,1401.52485,78.880263,72.5274,0.2163,1.3431,1.4986,1.0939,0.001187,0.0212 7/13/2015,0.4308,16.959768,1411.401075,78.114855,72.9162,0.2175,1.3503,1.4858,1.094,0.001188,0.0213 7/14/2015,0.4273,16.96288,1394.338,78.52042,71.9312,0.2161,1.3419999999999999,1.47714,1.0874,0.001174,0.0212 7/15/2015,0.4317,16.885792000000002,1389.08,77.31416,72.23216,0.2182,1.3552,1.4839200000000001,1.0946,0.001181,0.0213 7/16/2015,0.4279,16.569408,1376.0576,77.66150400000001,71.97632,0.2175,1.3504,1.46879,1.0879,0.001178,0.0213 7/17/2015,0.4254,16.218956,1376.102475,77.43330999999999,72.28013,0.2184,1.3561,1.46943,1.0928,0.001179,0.0214 7/20/2015,0.424,15.518360000000001,1367.012875,76.845725,73.251,0.2184,1.3565,1.46853,1.0915,0.001173,0.0213 7/21/2015,0.425,15.391876000000002,1373.07125,76.878512,74.8029,0.217,1.3478,1.47383,1.088,0.001173,0.0212 7/22/2015,0.4207,15.426728,1383.7287,76.089828,72.25348000000001,0.2183,1.3556,1.4815399999999999,1.0936,0.001172,0.0213 7/23/2015,0.4137,15.646694,1372.994,75.134038,71.3685,0.2189,1.3594,1.4934,1.0971,0.00117,0.0213 7/24/2015,0.4096,15.435892,1361.283625,75.00964599999999,72.09825,0.2211,1.3733,1.50784,1.1092,0.001173,0.0214 7/27/2015,0.409,15.461744,1322.2955,73.553332,71.80632,0.2215,1.3756,1.52535,1.1161,0.001178,0.0214 7/28/2015,0.406,15.22471,1328.58425,72.6479,72.1027,0.2195,1.3630000000000002,1.50757,1.1033,0.001175,0.0214 7/29/2015,0.4115,15.708222,1347.3981,73.167966,73.60659,0.2208,1.3707,1.5056399999999999,1.1059999999999999,0.00118,0.0215 7/30/2015,0.4066,15.454551,1357.929825,73.104003,75.69575999999999,0.2208,1.3713,1.4990700000000001,1.1047,0.001169,0.0214 7/31/2015,0.3999,15.247318,1342.352525,71.459827,75.14163,0.2205,1.3687,1.5028700000000002,1.1052,0.001173,0.0214 8/3/2015,0.3977,14.947614000000002,1341.7165,67.971152,77.68916,0.221,1.3726,1.5029299999999999,1.1066,0.001172,0.0214 8/4/2015,0.3905,14.921853,1322.7728,67.751447,75.76127,0.2182,1.3553,1.47451,1.0899,0.001159,0.0212 8/5/2015,0.39,14.62822,1348.284125,67.41760500000001,77.89935,0.2189,1.3595,1.4825700000000002,1.0888,0.001158,0.0213 8/6/2015,0.3849,14.5627,1341.2655,67.39672,79.0741,0.2192,1.361,1.48718,1.0911,0.001169,0.0214 8/7/2015,0.3841,14.368614,1360.0311,65.521419,78.31299,0.2171,1.3479,1.47832,1.0849,0.001157,0.0211 8/10/2015,0.3924,14.25893,1409.36775,68.00309,77.7024,0.2172,1.349,1.48641,1.0824,0.001164,0.0212 8/11/2015,0.3941,14.53878,1388.1660000000002,67.32741999999999,78.4437,0.2164,1.369,1.51185,1.0942,0.001161,0.0213 8/12/2015,0.3892,14.283807999999999,1288.7952,67.29923199999999,76.29776,0.2122,1.3552,1.51235,1.091,0.001155,0.0209 8/13/2015,0.3861,14.251714000000002,1349.0898,66.870292,76.62504,0.2124,1.3586,1.51486,1.0921,0.001153,0.0208 8/14/2015,0.3891,14.4714,1325.8675,66.43565,77.506,0.2121,1.355,1.50581,1.09,0.00115,0.0208 8/17/2015,0.3898,14.419595000000001,1257.4755,66.11581,76.64225,0.2121,1.3565,1.50273,1.0906,0.001146,0.0207 8/18/2015,0.3929,14.616406,1244.02915,66.488982,76.55564,0.213,1.3622,1.50166,1.095,0.0011480000000000001,0.0208 8/19/2015,0.3897,14.411931,1229.57315,64.180044,75.52995,0.2128,1.3609,1.51334,1.0992,0.001149,0.0209 8/20/2015,0.3938,14.472935999999999,1255.8202,63.533736,75.6354,0.2133,1.3628,1.5322,1.1041,0.00115,0.0208 8/21/2015,0.3905,14.267304000000001,1237.11465,62.125636,75.8463,0.214,1.3666,1.55664,1.1198,0.001143,0.0206 8/24/2015,0.3931,14.520025,1247.618125,59.659275,76.44325,0.2182,1.3975,1.6236,1.18,0.001173,0.0208 8/25/2015,0.3878,14.868620000000002,1254.364475,60.61066700000001,76.58742,0.2187,1.4027,1.6154700000000002,1.1799,0.001178,0.0211 8/26/2015,0.3905,14.785173,1232.448775,60.572874,76.66386,0.2191,1.4041,1.58844,1.1707,0.001186,0.0213 8/27/2015,0.3927,15.433124,1236.67325,66.365224,76.0493,0.2179,1.3954,1.56939,1.1531,0.001189,0.0212 8/28/2015,0.3892,15.289985999999999,1245.01185,69.75969,78.33156,0.2182,1.3938,1.5594,1.146,0.001181,0.0211 8/31/2015,0.3882,15.026932999999998,1261.61575,76.118655,79.14090999999999,0.2204,1.4057,1.57607,1.1595,0.001188,0.0212 9/1/2015,0.385,15.259607999999998,1260.5918,70.613088,81.2136,0.2239,1.4248,1.6122299999999998,1.1938,0.001207,0.0215 9/2/2015,0.37799999999999995,15.244110999999998,1255.543625,71.74535,80.9799,0.2236,1.4207,1.59503,1.1808,0.0012,0.0215 9/8/2015,0.3731,15.775857,1269.407825,70.570952,83.65337,0.2238,1.4251,1.5964200000000002,1.1894,0.001193,0.0215 9/9/2015,0.3769,16.285464,1257.7422,67.791984,84.63311999999999,0.2234,1.4248,1.5969799999999998,1.1821,0.001196,0.0214 9/10/2015,0.3673,16.019486999999998,1250.59455,69.125571,84.97539,0.2217,1.4139,1.5950600000000001,1.1721,0.001196,0.0213 9/11/2015,0.3643,16.444098,1251.993825,67.89184200000001,84.75903000000001,0.2212,1.4103,1.59877,1.1696,0.001192,0.0213 9/14/2015,0.3671,16.11035,1236.644475,64.959733,84.19409,0.22,1.4009,1.58556,1.1652,0.001184,0.0211 9/15/2015,0.3627,15.963420000000001,1244.8667,65.295989,83.03779,0.2198,1.4003,1.578,1.1629,0.001188,0.0211 9/16/2015,0.3627,15.937565,1232.833875,69.127625,81.4247,0.2181,1.3895,1.56861,1.1525,0.001188,0.021 9/17/2015,0.3576,15.943928,1232.72765,68.402796,81.67081999999999,0.21899999999999997,1.3937,1.5939,1.1615,0.001194,0.0211 9/18/2015,0.3526,15.23988,1205.911125,66.007035,81.62235,0.2186,1.3905,1.56734,1.16,0.001185,0.0211 9/21/2015,0.3519,15.326046,1225.87335,68.595624,82.16892,0.2201,1.4022,1.56908,1.1631,0.00119,0.0213 9/22/2015,0.3483,15.34624,1215.498375,69.22734,82.6553,0.2212,1.4105,1.5684,1.1739,0.00119,0.0214 9/23/2015,0.3418,15.635504999999998,1233.348625,68.182225,82.53262,0.2236,1.4279,1.59725,1.1871,0.0011949999999999999,0.0215 9/24/2015,0.3605,15.930083999999999,1235.6848,68.574812,82.28408,0.223,1.4236,1.59854,1.1857,0.0011949999999999999,0.0215 9/25/2015,0.3582,16.707194,1265.491675,69.16266,82.25518000000001,0.2233,1.4231,1.5938,1.1801,0.001193,0.0215 9/28/2015,0.348,16.810725,1254.366225,67.729338,82.69445999999999,0.2246,1.4307,1.60877,1.1931,0.001196,0.0216 9/29/2015,0.3525,16.837968,1266.06915,69.055714,82.18531999999999,0.2251,1.4318,1.61043,1.1957,0.0011970000000000001,0.0217 9/30/2015,0.361,17.343467,1271.1892,68.932087,81.51572,0.2243,1.4251,1.5927,1.1886,0.001202,0.0217 10/8/2015,0.364,19.30578,1214.3625,73.1029,78.8216,0.2169,1.3780000000000001,1.55325,1.1488,0.001196,0.0213 10/9/2015,0.3625,19.551156,1207.63155,71.78301,78.66818,0.2148,1.3634,1.54795,1.1338,0.001188,0.021 10/12/2015,0.3608,19.340768,1205.4025,67.719852,78.63978,0.2148,1.3582,1.54282,1.1316,0.001187,0.021 10/13/2015,0.3546,19.090932000000002,1261.6856,67.970896,79.64908,0.2177,1.3804,1.5707,1.1528,0.0012,0.0212 10/14/2015,0.3593,19.299073,1247.11185,67.320755,77.93593,0.2158,1.3697,1.5716700000000001,1.1527,0.0012050000000000001,0.0211 10/15/2015,0.3591,19.280385,1235.213625,66.464795,76.6849,0.215,1.3645,1.5537100000000001,1.1475,0.001215,0.0211 10/16/2015,0.3506,19.644082,1236.53095,69.463236,76.81428000000001,0.2166,1.3766,1.56264,1.1519,0.001217,0.0213 10/19/2015,0.355,19.673095999999997,1229.2236,67.06235600000001,76.98168000000001,0.2169,1.3796,1.56274,1.1544,0.001219,0.0213 10/20/2015,0.3528,19.366244000000002,1234.1504,67.093154,76.4457,0.217,1.3774,1.5626799999999998,1.1494,0.001217,0.0212 10/21/2015,0.3521,19.66766,1255.58175,66.36795,75.0367,0.2185,1.3869999999999998,1.57253,1.1566,0.001217,0.0213 10/22/2015,0.3551,20.254579999999997,1246.835875,66.70138399999999,74.49801,0.2182,1.3873,1.5411,1.1496,0.001227,0.0214 10/23/2015,0.3575,19.787796,1240.89435,66.49974300000001,74.13495,0.2182,1.3857,1.5267600000000001,1.141,0.001219,0.0213 10/26/2015,0.3534,20.19588,1220.8575,65.58143000000001,73.80325,0.2172,1.3795,1.52545,1.1394,0.001221,0.0212 10/27/2015,0.3575,20.049568,1239.194,65.084624,73.27408,0.2188,1.3904,1.53653,1.1542,0.001224,0.0214 10/28/2015,0.36,20.60083,1239.5653,68.97411,72.98178,0.2212,1.4062,1.5351700000000001,1.1613,0.001228,0.0216 10/29/2015,0.3673,20.584928,1242.37675,68.99344,72.1038,0.2224,1.4138,1.55185,1.1672,0.0012380000000000002,0.0216 10/30/2015,0.3634,20.34252,1238.13375,69.43356,70.8906,0.2218,1.401,1.54198,1.1616,0.001228,0.0214 11/2/2015,0.3629,21.143423000000002,1228.235575,68.271847,70.10493000000001,0.2208,1.3993,1.54149,1.1589,0.00123,0.0213 11/3/2015,0.3689,21.555884,1222.5206,70.331464,67.77091999999999,0.2197,1.3916,1.52581,1.1494,0.001231,0.0212 11/4/2015,0.3681,20.479896,1233.8298,67.958562,67.00731,0.2208,1.3989,1.51997,1.1512,0.001232,0.0213 11/5/2015,0.3704,20.661048,1214.67645,67.16240400000001,67.05041999999999,0.2206,1.3998,1.52358,1.1498,0.00123,0.0212 11/6/2015,0.3765,20.528862,1236.913625,67.322174,67.00984,0.2235,1.4197,1.52199,1.1529,0.001232,0.0215 11/9/2015,0.3735,19.85181,1239.4965,66.96261,66.1254,0.223,1.419,1.52585,1.1520000000000001,0.001225,0.0214 11/10/2015,0.3795,20.920562,1229.4919,67.46916800000001,66.27452,0.2235,1.4222,1.52528,1.1549,0.001227,0.0215 11/12/2015,0.37200000000000005,21.008898000000002,1219.90545,61.833804,65.2581,0.2204,1.4034,1.51746,1.1445,0.00121,0.0212 11/13/2015,0.3645,21.087584,1204.4039,61.14558100000001,65.19765,0.2202,1.4021,1.51187,1.1442,0.001199,0.0212 11/16/2015,0.3688,21.390138,1211.12145,62.789496,65.66405999999999,0.2212,1.4091,1.50583,1.1440000000000001,0.0012050000000000001,0.0214 11/17/2015,0.3686,20.785114,1215.0432,61.272491,65.53358,0.2205,1.4063,1.4963899999999999,1.1393,0.001202,0.0213 11/18/2015,0.3735,20.350607999999998,1206.3396,62.078495999999994,64.27248,0.2203,1.4064,1.4991,1.1374,0.0012050000000000001,0.0213 11/19/2015,0.3738,20.77751,1195.228,61.401364,62.95794,0.2178,1.3898,1.4920799999999999,1.1312,0.001202,0.021 11/20/2015,0.3729,21.13695,1184.63625,61.697790000000005,62.1675,0.2164,1.3815,1.4706,1.1251,0.001196,0.0209 11/23/2015,0.3726,21.424523,1201.566775,62.327149,62.5635,0.2176,1.3903,1.47894,1.1319,0.0012,0.0209 11/24/2015,0.373,20.67,1190.2475,63.55336,61.5966,0.2158,1.3780000000000001,1.46689,1.1251,0.001202,0.0208 11/25/2015,0.3681,20.56089,1206.96975,63.66843000000001,60.9518,0.2158,1.379,1.46509,1.1239,0.0012050000000000001,0.0208 11/27/2015,0.3614,20.811294,1213.6446,62.364371999999996,61.30781999999999,0.2174,1.3902,1.4725,1.1321,0.001202,0.0208 11/30/2015,0.3576,20.658641,1219.0397,61.726856999999995,59.91421,0.2163,1.3837,1.4618,1.1239,0.001193,0.0208 12/1/2015,0.3543,21.084864000000003,1214.3598,60.687264,58.17456,0.2134,1.3656,1.45185,1.1113,0.001182,0.0206 12/2/2015,0.3568,20.985120000000002,1220.598,58.12631999999999,55.9512,0.2138,1.368,1.45234,1.11,0.001176,0.0205 12/3/2015,0.3619,21.223076000000002,1222.5745,59.718848,55.71398000000001,0.2129,1.3622,1.49017,1.111,0.00118,0.0204 12/4/2015,0.363,21.096144,1234.6968,58.6004,54.78456,0.2128,1.3628,1.48195,1.1069,0.0011710000000000002,0.0204 12/7/2015,0.3652,21.051270000000002,1213.887775,56.040406999999995,54.485640000000004,0.2147,1.3759,1.4912100000000001,1.1153,0.00117,0.0206 12/8/2015,0.3651,20.784000000000002,1214.8248,55.784256000000006,54.31551999999999,0.2159,1.3856,1.50968,1.1271,0.001174,0.0207 12/9/2015,0.3683,20.870979000000002,1212.632925,55.476141000000005,53.9409,0.2152,1.3831,1.52501,1.1387,0.00117,0.0207 12/10/2015,0.3604,19.984425,1206.276375,54.569155,53.15445,0.2133,1.3735,1.50268,1.1293,0.001165,0.0206 12/11/2015,0.3592,20.282238,1211.300325,52.764423,52.72269,0.2155,1.3911,1.5283799999999998,1.1495,0.001172,0.0207 12/14/2015,0.3566,20.035408,1207.1644,52.359936,52.33232,0.2138,1.3808,1.51749,1.1408,0.001166,0.0206 12/15/2015,0.3589,20.285936,1205.8244,53.46088,52.69616,0.2151,1.3904,1.51973,1.1425,0.001184,0.0208 12/16/2015,0.3564,20.169216,1192.32,51.411456,51.84,0.2136,1.3824,1.50871,1.1312,0.001179,0.0208 12/17/2015,0.3618,20.62116,1230.2556,51.987768,52.605,0.2164,1.4028,1.5186899999999999,1.1447,0.001184,0.0211 12/18/2015,0.35,21.04487,1243.528825,51.399656,53.93619,0.2151,1.3937,1.51421,1.1507,0.001178,0.021 12/21/2015,0.3469,20.821773,1239.639625,50.559215,54.94055,0.2146,1.3909,1.51817,1.1476,0.001184,0.021 12/22/2015,0.3467,20.78528,1223.4155,49.90402,55.0036,0.2133,1.382,1.51419,1.1417,0.00118,0.0209 12/23/2015,0.3505,20.943360000000002,1218.9312,51.646464,55.01951999999999,0.2134,1.3824,1.50852,1.1434,0.001178,0.0209 12/28/2015,0.3573,20.361420000000003,1193.2675,50.51729,56.14565,0.2126,1.3795,1.51295,1.1458,0.00118,0.0209 12/29/2015,0.3546,20.257468,1192.422,51.794973999999996,56.8799,0.2113,1.3706,1.49668,1.1379,0.00117,0.0207 12/30/2015,0.3468,20.790345000000002,1201.44865,50.034058,59.0089,0.2114,1.3723,1.5002799999999998,1.1386,0.001165,0.0206 12/31/2015,0.3464,20.913852,1195.616375,51.159344,59.55781999999999,0.2112,1.3723,1.4915100000000001,1.1414,0.001166,0.0207 1/4/2016,0.3443,20.818779,1202.26015,51.761854,61.051730000000006,0.2129,1.3907,1.5062799999999998,1.1643,0.001168,0.0209 1/5/2016,0.3485,20.344091,1211.639325,50.853246,62.414609999999996,0.2143,1.3963,1.5008700000000001,1.1726,0.001174,0.021 1/6/2016,0.3512,20.391322,1238.398075,48.404643,62.078990000000005,0.2157,1.4141,1.52451,1.1934,0.001178,0.0212 1/7/2016,0.3528,21.034975,1250.6897,48.130875,61.3223,0.2163,1.4261,1.55926,1.2123,0.001191,0.0213 1/8/2016,0.3565,20.796372,1264.8969,48.25161,61.26732,0.2181,1.4382,1.56939,1.2268,0.001191,0.0215 1/11/2016,0.3527,20.233085,1259.7419,45.113345,60.19879,0.2176,1.4299,1.55235,1.2143,0.001186,0.0214 1/12/2016,0.3554,20.11117,1275.01955,44.173004,59.97566,0.2178,1.4314,1.55427,1.2165,0.001183,0.0214 1/13/2016,0.3579,20.804966,1292.5822,43.579718,59.237359999999995,0.2187,1.4378,1.56361,1.2215,0.001189,0.0215 1/14/2016,0.358,21.30816,1283.072,44.43496,58.1392,0.2173,1.432,1.55561,1.213,0.001186,0.0213 1/15/2016,0.3594,21.742916,1280.9667,42.174262,59.457840000000004,0.2205,1.4573,1.5911600000000001,1.2453,0.001201,0.0215 1/19/2016,0.3558,21.3521,1278.9546,41.632976,60.94396,0.2193,1.4476,1.57904,1.2304,0.001199,0.0214 1/20/2016,0.353,20.528385999999998,1265.2898,40.361876,60.94817,0.2213,1.4477,1.57646,1.2378,0.0011970000000000001,0.0213 1/21/2016,0.3436,20.646160000000002,1255.2008,41.7924,59.152319999999996,0.21899999999999997,1.4288,1.55377,1.2139,0.001187,0.0211 1/22/2016,0.3485,20.593201999999998,1251.72965,45.956258,59.12334,0.2162,1.4281,1.54182,1.2023,0.001192,0.0211 1/25/2016,0.3508,20.27298,1265.9829,43.8529,59.524919999999995,0.2176,1.4378,1.55985,1.2155,0.001198,0.0212 1/26/2016,0.3522,20.016354,1251.37905,45.400859999999994,58.5357,0.2171,1.4277,1.55193,1.2056,0.001191,0.0211 1/27/2016,0.3464,19.327056,1256.6856,47.10792,59.34744,0.2161,1.4232,1.55024,1.1992,0.001178,0.0209 1/28/2016,0.3469,18.705025,1225.002675,47.842513000000004,58.58555,0.2144,1.4117,1.5444,1.1881,0.001169,0.0207 1/29/2016,0.3532,18.549738,1245.472325,49.042458,58.44438,0.2148,1.4117,1.52898,1.1654,0.001169,0.0208 2/1/2016,0.3545,18.033848000000003,1237.9822,48.127744,58.19184,0.2147,1.4056,1.5307600000000001,1.1618,0.001169,0.0207 2/2/2016,0.3553,18.456192,1259.184,46.488576,59.10528000000001,0.2156,1.4208,1.55131,1.1842,0.001172,0.0209 2/3/2016,0.3576,17.982839000000002,1223.153925,48.884304,58.45469,0.2146,1.3951,1.54915,1.1835,0.0011619999999999998,0.0206 2/4/2016,0.3573,17.899054,1214.3307,47.851156,58.18234,0.2107,1.3886,1.5566200000000001,1.1891,0.001164,0.0206 2/5/2016,0.3622,18.77705,1227.5125,48.1949,59.43,0.2142,1.415,1.57863,1.2112,0.001172,0.0208 2/16/2016,0.3461,18.589964000000002,1237.10445,45.251515999999995,61.45094,0.2161,1.4062,1.56711,1.2325,0.0011539999999999999,0.0205 2/17/2016,0.3488,18.316088,1228.2635,48.0171,61.9351,0.2148,1.3918,1.54879,1.22,0.001137,0.0204 2/18/2016,0.3467,17.857494,1229.274675,47.899444,62.59904,0.2145,1.3973,1.55179,1.2336,0.001137,0.0204 2/19/2016,0.3478,17.514228,1228.583925,46.177689,63.09039,0.2164,1.3989,1.55681,1.242,0.001134,0.0203 2/22/2016,0.3505,17.448457,1219.0397,48.000553000000004,67.52456,0.2121,1.3837,1.52613,1.2254,0.001131,0.0202 2/23/2016,0.3503,19.439,1206.953625,46.195395,67.06455,0.212,1.3885,1.5300200000000002,1.2385,0.001127,0.0202 2/24/2016,0.3507,19.412712,1205.478,47.816136,65.58912,0.2135,1.3896,1.5303799999999999,1.2387,0.001127,0.0203 2/25/2016,0.3494,19.679679999999998,1187.138,48.77078,64.954,0.2124,1.382,1.52272,1.2229,0.001119,0.0201 2/26/2016,0.3506,19.512948,1199.394,49.238279999999996,65.2302,0.2133,1.4028,1.53376,1.2311,0.001129,0.0204 2/29/2016,0.3486,20.389824,1194.5412,50.372388,64.97856,0.2139,1.4004,1.52251,1.2427,0.001131,0.0205 3/1/2016,0.354,20.058221,1185.860425,51.309459000000004,65.65269,0.214,1.3939,1.51473,1.2225,0.001134,0.0206 3/2/2016,0.35200000000000004,20.109636,1171.0059,50.623644,65.66131999999999,0.2106,1.3708,1.4899,1.2079,0.001119,0.0204 3/3/2016,0.3578,20.185368,1164.67125,50.422614,67.3299,0.2081,1.3602,1.4903899999999999,1.1964,0.0011220000000000002,0.0203 3/4/2016,0.3584,19.933003,1170.03905,52.043552000000005,66.66736,0.2074,1.3441,1.4796,1.1817,0.001121,0.0201 3/7/2016,0.3537,19.631206,1169.70385,54.688843999999996,83.96157,0.20600000000000002,1.3391,1.47478,1.1803,0.001115,0.02 3/8/2016,0.358,19.977784,1179.711,53.30546,86.44492,0.2066,1.3444,1.48019,1.1937,0.001111,0.02 3/9/2016,0.3619,19.544217,1175.5919999999999,54.865413000000004,76.41348,0.2049,1.3359,1.46937,1.1788,0.001105,0.0199 3/10/2016,0.3701,19.88103,1182.867625,53.727075,80.08755,0.20600000000000002,1.3415,1.49946,1.1848,0.001114,0.0199 3/11/2016,0.3686,20.00186,1173.9360000000001,53.39558,76.2794,0.2032,1.3219999999999998,1.47451,1.1612,0.001113,0.0197 3/14/2016,0.3636,20.522478,1181.8392,52.610477,75.99439,0.2049,1.3309,1.4777200000000001,1.1691,0.001119,0.0198 3/15/2016,0.3559,20.542588000000002,1196.0828,51.946466,72.27450999999999,0.2058,1.3409,1.48991,1.1847,0.0011220000000000002,0.0199 3/16/2016,0.3537,20.483826999999998,1184.40745,53.400953,70.97176,0.2062,1.3241,1.48634,1.1761,0.001123,0.0198 3/17/2016,0.3604,20.905326000000002,1173.71835,54.309396,71.77626,0.2026,1.3074,1.47969,1.1736,0.001132,0.0197 3/18/2016,0.3629,20.989371,1179.58425,54.149159999999995,74.12652,0.203,1.3143,1.48206,1.179,0.001129,0.0198 3/21/2016,0.3646,21.497913,1190.3694,54.820338,75.35486999999999,0.2031,1.3197,1.4833100000000001,1.1788,0.0011359999999999999,0.0198 3/22/2016,0.3664,21.754618,1194.339025,54.832659,74.13365,0.2019,1.3121,1.47174,1.1678,0.001134,0.0197 3/23/2016,0.3603,22.185867000000002,1201.900425,53.732018999999994,75.81166999999999,0.2038,1.3277,1.48451,1.1815,0.0011359999999999999,0.0198 3/28/2016,0.3655,21.130064,1204.9704,53.381912,71.98008,0.2036,1.3256,1.48403,1.1683,0.001137,0.0199 3/29/2016,0.3601,20.790874,1200.7844,51.308626000000004,68.95334,0.2032,1.3109,1.4802600000000001,1.1625,0.001134,0.0198 3/30/2016,0.3621,20.688132,1184.9724,51.179336,68.56936,0.2015,1.3036,1.47796,1.1595,0.00114,0.0197 3/31/2016,0.3636,20.045565,1189.348425,51.713640000000005,69.47388000000001,0.2017,1.3059,1.48624,1.1601,0.001141,0.0197 4/1/2016,0.3668,19.765878,1195.653325,50.352207,69.53214,0.2015,1.3021,1.48434,1.1667,0.001137,0.0197 4/5/2016,0.3602,19.406784,1199.3366,50.200472,72.2452,0.205,1.3256,1.5091299999999999,1.2014,0.001142,0.02 4/6/2016,0.3613,19.23992,1194.928,52.42944,71.1956,0.2037,1.3159999999999998,1.50011,1.1987,0.001139,0.0198 4/7/2016,0.3614,19.226532000000002,1205.1558,52.536531999999994,72.21608,0.2062,1.3324,1.51596,1.2312,0.0011480000000000001,0.02 4/8/2016,0.369,19.452498000000002,1213.96035,55.536947999999995,72.1689,0.2043,1.3242,1.50888,1.2251,0.00115,0.0199 4/11/2016,0.3766,18.62706,1221.9483,56.381412,73.58676,0.2036,1.3164,1.50166,1.2195,0.001152,0.0198 4/12/2016,0.373,18.313512,1218.623,58.168504000000006,74.71184000000001,0.20199999999999999,1.3016,1.4816200000000002,1.1988,0.0011380000000000001,0.0196 4/13/2016,0.3733,18.308267999999998,1248.9741,57.734424,77.88528000000001,0.2018,1.3068,1.47328,1.1951,0.00114,0.0196 4/15/2016,0.3665,19.470784,1237.6376,55.797259999999994,75.60464,0.2004,1.2946,1.46133,1.1903,0.001129,0.0194 4/18/2016,0.3568,19.806105,1231.268775,55.366772999999995,78.32121,0.1992,1.2903,1.4596799999999999,1.1858,0.001127,0.0194 4/19/2016,0.3622,19.416083,1261.34145,56.353997,79.60978,0.1982,1.2799,1.4537200000000001,1.1719,0.001134,0.0193 4/20/2016,0.3635,19.97631,1295.50925,58.7614,82.2403,0.1977,1.2830000000000001,1.4494200000000002,1.1681,0.001132,0.0194 4/21/2016,0.3659,20.134034,1316.530625,57.546119,90.07330999999999,0.1987,1.2923,1.45878,1.1806,0.001132,0.0194 4/22/2016,0.3634,19.79222,1280.139,58.50767,89.1039,0.1995,1.297,1.45592,1.1607,0.0011279999999999999,0.0195 4/25/2016,0.3644,20.259605999999998,1295.87595,57.654976,87.88235999999999,0.1995,1.2962,1.46038,1.1657,0.001126,0.0194 4/26/2016,0.3657,20.354339000000003,1313.609925,59.036618000000004,84.79899,0.1989,1.2907,1.45789,1.1595,0.001125,0.0194 4/27/2016,0.3735,20.485570000000003,1342.4306,62.154931999999995,82.86446,0.2029,1.3174,1.49129,1.1821,0.001147,0.0199 4/28/2016,0.3759,20.090648,1335.0052,63.130796,84.5853,0.2021,1.3114,1.48856,1.2133,0.001153,0.0197 4/29/2016,0.3827,21.247168,1342.4108,63.281324,86.51384,0.2027,1.3148,1.50537,1.2372,0.001149,0.0198 5/3/2016,0.3755,21.711625,1364.82615,60.084417,87.11372,0.2052,1.3361,1.53607,1.2535,0.00116,0.0201 5/4/2016,0.3778,22.329315,1373.95695,59.839881999999996,85.02574,0.2058,1.3411,1.54049,1.2534,0.001149,0.0201 5/5/2016,0.3787,21.219264000000003,1344.2886,60.295396,82.92124,0.2055,1.3396,1.5277,1.249,0.001147,0.0201 5/6/2016,0.3876,21.365476,1393.03175,61.585238000000004,82.1227,0.2091,1.3574,1.54774,1.2672,0.001161,0.0204 5/9/2016,0.3888,21.70796,1392.63125,59.64221,79.1493,0.2096,1.367,1.55593,1.2618,0.001163,0.0205 5/10/2016,0.3907,21.756762,1461.3156,61.820712,75.37455,0.2086,1.3581,1.5444200000000001,1.2429,0.00116,0.0204 5/11/2016,0.3929,22.738443,1450.474025,64.54084,75.38804,0.2081,1.3559,1.5492700000000001,1.2507,0.001163,0.0204 5/12/2016,0.3922,23.182794,1453.36185,65.643624,75.22803,0.2093,1.3653,1.5530700000000002,1.2527,0.001167,0.0205 5/13/2016,0.3895,23.029218,1451.3635,65.79973100000001,74.15023000000001,0.2105,1.3757,1.55482,1.266,0.001169,0.0205 5/16/2016,0.3917,23.169701999999997,1460.2811,67.17704599999999,73.66566,0.2102,1.3718,1.55301,1.2583,0.001165,0.0205 5/17/2016,0.3913,22.9593,1474.54125,67.2672,73.8465,0.209,1.365,1.5447,1.2506,0.00116,0.0204 5/18/2016,0.3881,23.251592000000002,1487.2858,67.679976,75.52271999999999,0.2099,1.3832,1.5514299999999999,1.2552,0.0011619999999999998,0.0206 5/19/2016,0.3882,23.10612,1482.5274,67.533516,73.46916,0.2121,1.3836,1.54997,1.2582,0.001166,0.0205 5/20/2016,0.3932,23.635122,1487.40655,67.457712,73.52226,0.2115,1.3846,1.55386,1.2571,0.001164,0.0205 5/23/2016,0.3874,23.25624,1465.28155,66.93090500000001,72.53732,0.2113,1.3843,1.55329,1.2674,0.00117,0.0205 5/24/2016,0.3898,23.122781,1468.317475,67.669981,70.71868,0.2121,1.3921,1.5509,1.2657,0.001172,0.0206 5/25/2016,0.38799999999999996,23.836956,1507.86805,69.093834,69.03827,0.2121,1.3891,1.54964,1.2607,0.001175,0.0206 5/26/2016,0.3864,24.107538,1494.266025,68.627601,67.53432,0.2112,1.3839,1.5490700000000002,1.2609,0.001173,0.0207 5/27/2016,0.3852,24.384335999999998,1512.1907,68.643576,68.05901999999999,0.2116,1.3918,1.54662,1.2625,0.001173,0.0207 5/31/2016,0.3827,24.181673999999997,1491.1341,68.701394,65.25872,0.2097,1.3826,1.53891,1.2486,0.001161,0.0206 6/1/2016,0.3825,23.99098,1515.4555,68.51416,65.0416,0.2095,1.3780000000000001,1.54155,1.2579,0.0011560000000000001,0.0204 6/2/2016,0.3849,25.010064,1582.841025,69.220332,65.29176,0.2101,1.3833,1.54245,1.2706,0.001166,0.0206 6/3/2016,0.3849,25.45125,1536.5768,67.381336,63.52632,0.2083,1.3574,1.54291,1.2742,0.001167,0.0203 6/6/2016,0.3891,25.49385,1545.174375,68.621625,65.16,0.2067,1.3575,1.54176,1.2623,0.001167,0.0203 6/7/2016,0.3894,25.4714,1529.95975,68.960464,66.09158000000001,0.2042,1.3406,1.52286,1.2484,0.001159,0.0201 6/8/2016,0.3981,26.247984999999996,1576.418375,70.284635,66.1219,0.204,1.3385,1.52516,1.251,0.00116,0.0201 6/13/2016,0.3888,26.451297999999998,1582.4753,68.158795,66.73741,0.205,1.3537,1.52863,1.2737,0.001155,0.0201 6/14/2016,0.3902,26.28306,1589.3505,67.71897,66.9987,0.2061,1.359,1.5230700000000001,1.2809,0.001155,0.0202 6/15/2016,0.3885,26.676,1560.6,66.1095,65.61,0.205,1.35,1.51997,1.2734,0.001155,0.0201 6/16/2016,0.3919,26.731344,1540.99135,64.098177,66.5567,0.2073,1.3583,1.5244799999999998,1.3028,0.001158,0.0202 6/17/2016,0.3963,26.723423999999998,1568.1078,66.497508,66.80856,0.2057,1.3524,1.52556,1.2981,0.001155,0.0202 6/20/2016,0.395,26.408228,1533.6622,67.93178,65.98704000000001,0.2037,1.3412,1.5167700000000002,1.2903,0.001155,0.0198 6/21/2016,0.3932,25.825851999999998,1521.161475,67.947226,66.04115999999999,0.2033,1.3423,1.5090000000000001,1.2811,0.001164,0.0198 6/22/2016,0.3947,25.382224,1516.40125,66.495028,66.38838,0.2027,1.3331,1.50606,1.2764,0.001161,0.0198 6/23/2016,0.3934,25.012848,1477.25565,66.88046700000001,65.81636999999999,0.2004,1.3137,1.49569,1.2376,0.001151,0.0195 6/24/2016,0.3963,25.4429,1477.0273,64.82583100000001,66.55327,0.2027,1.3391,1.48825,1.3084,0.001141,0.0197 6/27/2016,0.4021,26.572668,1545.5253,64.330956,72.02448000000001,0.2048,1.3641,1.50338,1.3378,0.0011560000000000001,0.0201 6/28/2016,0.41,26.812834999999996,1557.20175,65.75303000000001,72.0062,0.2046,1.3535,1.4980200000000001,1.3176,0.00116,0.02 6/29/2016,0.4168,27.940440000000002,1535.9189999999999,67.91861999999999,70.8576,0.2025,1.3419999999999999,1.493,1.3052,0.001163,0.0199 6/30/2016,0.4176,27.04533,1577.085,66.68049599999999,71.94192,0.20199999999999999,1.3422,1.49064,1.3006,0.001164,0.0199 7/1/2016,0.4121,27.735065999999996,1559.930625,67.202145,72.34074,0.2006,1.3347,1.48629,1.3005,0.001159,0.0198 7/5/2016,0.4056,27.963713000000002,1496.6683,64.261604,73.42652,0.2003,1.3399,1.48431,1.3171,0.0011560000000000001,0.0199 7/6/2016,0.3993,27.351929,1470.980625,64.88936,72.73459,0.1992,1.3297,1.4761799999999998,1.3125,0.001147,0.0197 7/7/2016,0.397,26.380983,1409.637675,62.04144,73.13937,0.1998,1.3371,1.47825,1.3267,0.0011539999999999999,0.0198 7/8/2016,0.4003,25.855884,1439.7777,61.779312,72.26964,0.1978,1.3212,1.4598200000000001,1.314,0.001149,0.0197 7/11/2016,0.4012,26.925756,1437.567175,61.406125,72.62519,0.1983,1.3277,1.4681899999999999,1.2915,0.0011539999999999999,0.0198 7/12/2016,0.3979,25.870668,1452.601275,63.587793000000005,73.59759,0.1961,1.3119,1.4510100000000001,1.2531,0.001147,0.0196 7/13/2016,0.4025,25.606460000000002,1482.756,60.808769999999996,76.37245,0.1962,1.3145,1.45774,1.2581,0.001147,0.0196 7/14/2016,0.4029,26.088073,1456.39845,62.068911,75.34225,0.1959,1.3103,1.4569999999999999,1.2439,0.001157,0.0196 7/15/2016,0.4025,25.485338,1415.4855,62.835678,74.96464,0.1969,1.3198,1.45587,1.2584,0.001158,0.0197 7/18/2016,0.4049,25.516101000000003,1420.378725,61.86040799999999,74.03226,0.1964,1.3173,1.4589299999999998,1.2409,0.00116,0.0196 7/19/2016,0.4101,25.799135999999997,1391.2344,62.179116,73.15974,0.1994,1.3326,1.4687299999999999,1.2557,0.001168,0.0198 7/20/2016,0.4102,25.785072,1373.5098,63.08515799999999,71.68464,0.2001,1.3374,1.47183,1.2512,0.00117,0.0199 7/21/2016,0.4079,26.10282,1377.87125,61.6539,74.4651,0.1998,1.3345,1.47119,1.2611,0.001173,0.0199 7/22/2016,0.4115,26.231009999999998,1347.7035,61.178909999999995,74.8501,0.201,1.339,1.47086,1.2626,0.001179,0.02 7/25/2016,0.4071,26.626742999999998,1316.946125,59.866664,74.56559,0.2007,1.3387,1.47204,1.2653,0.001172,0.0199 7/26/2016,0.4068,26.016256,1324.1368,59.802735999999996,74.6368,0.1994,1.3328,1.4643899999999999,1.2738,0.001172,0.0198 7/27/2016,0.4092,25.496589999999998,1348.91645,58.028103,75.95581,0.2008,1.3349,1.47627,1.2666,0.00118,0.0199 7/28/2016,0.4047,25.05288,1337.2641,56.90201999999999,77.9571,0.2001,1.3326,1.47622,1.266,0.001185,0.0199 7/29/2016,0.4047,25.071704999999998,1358.87325,55.881606000000005,76.72863000000001,0.1984,1.3161,1.47066,1.2892,0.001184,0.0197 8/1/2016,0.4064,24.962751,1321.7916,55.92399399999999,79.36058,0.1991,1.3271,1.4807299999999999,1.296,0.0011970000000000001,0.0199 8/2/2016,0.4032,25.035510000000002,1294.81555,54.93356,79.24625999999999,0.1982,1.3142,1.47465,1.3027,0.001182,0.0197 8/3/2016,0.4069,25.092816,1305.37995,56.80149,79.33758,0.1986,1.3179,1.46928,1.3017,0.00118,0.0197 8/4/2016,0.4106,25.8267,1298.5455,58.06419,77.34899999999999,0.1972,1.311,1.45899,1.2952,0.0011769999999999999,0.0196 8/5/2016,0.4146,26.709375,1317.421875,58.104375,77.9625,0.1973,1.3125,1.45505,1.2893,0.0011769999999999999,0.0196 8/8/2016,0.4121,26.860905,1331.608125,59.329269,79.60239,0.196,1.3071,1.44927,1.2758,0.00118,0.0196 8/9/2016,0.4144,26.574286999999998,1331.9726,58.622434,79.11031,0.1958,1.3033,1.44896,1.2792,0.001182,0.0195 8/10/2016,0.415,25.496648,1320.2694,57.18571,77.76218,0.1954,1.2982,1.45134,1.2819999999999998,0.001183,0.0194 8/11/2016,0.413,25.45648,1327.6983,59.796752000000005,77.01884,0.1953,1.2988,1.44651,1.2738,0.001183,0.0195 8/12/2016,0.4095,25.762941,1311.348075,61.394487,76.59606,0.196,1.3071,1.45825,1.2901,0.001184,0.0195 8/15/2016,0.409,26.037936,1334.151,63.009719999999994,75.97655999999999,0.196,1.3032,1.4574200000000002,1.287,0.001187,0.0195 8/16/2016,0.4058,26.329896,1324.9422,63.979307999999996,76.41648,0.1961,1.2996,1.46563,1.2956,0.001186,0.0194 8/17/2016,0.4074,25.756292000000002,1345.93605,65.109085,77.19051,0.1976,1.3061,1.47453,1.3025,0.001179,0.0195 8/18/2016,0.4017,25.99398,1342.95725,66.20789,76.3687,0.1963,1.301,1.47715,1.3025,0.001174,0.0195 8/19/2016,0.409,25.924401,1346.7051,66.718944,76.71105,0.1972,1.3113,1.48492,1.3083,0.001175,0.0195 8/22/2016,0.4097,26.774703999999996,1357.4198,64.45859200000001,77.22968,0.1972,1.3112,1.48579,1.3068,0.001167,0.0195 8/23/2016,0.406,27.222635999999998,1358.1771,65.607472,78.39804000000001,0.19699999999999998,1.3132,1.48458,1.31,0.001172,0.0196 8/24/2016,0.4073,26.558970000000002,1353.890125,64.427175,78.2846,0.1975,1.3135,1.47933,1.3076,0.001172,0.0196 8/25/2016,0.4059,26.975984999999998,1310.402775,65.201809,77.58057,0.1973,1.3127,1.48128,1.3058,0.0011769999999999999,0.0196 8/26/2016,0.4046,27.254664000000002,1310.1678,66.014208,77.88936,0.1961,1.3224,1.48006,1.2985,0.001178,0.0197 8/29/2016,0.4089,27.309203999999998,1299.0699,65.082312,77.02596,0.1977,1.3212,1.47817,1.2963,0.00118,0.0197 8/30/2016,0.4111,27.324432,1285.6598,64.409492,77.2328,0.1993,1.3316,1.48373,1.2934,0.001189,0.0198 8/31/2016,0.4119,26.683812,1276.992,62.572607999999995,76.22046,0.1992,1.3302,1.48423,1.2862,0.001192,0.0199 9/1/2016,0.4066,25.941078,1269.9078,60.18489,75.61182,0.1985,1.3242,1.48274,1.2828,0.001184,0.0198 9/2/2016,0.4054,26.649708,1279.0011,61.843697999999996,75.9345,0.1983,1.3206,1.4743700000000002,1.2706,0.001183,0.0198 9/6/2016,0.4069,26.304198,1267.401825,61.480534,74.54157,0.1955,1.3009,1.46412,1.2752,0.001188,0.0196 9/7/2016,0.4079,26.443957,1292.547775,62.532334,73.89711,0.1956,1.3033,1.46482,1.281,0.0011949999999999999,0.0196 9/8/2016,0.4071,26.453826,1297.8336,65.401917,73.91895,0.1953,1.3083,1.4730299999999998,1.2766,0.001191,0.0196 9/9/2016,0.4053,26.510738,1322.55295,63.670862,74.2672,0.1977,1.3262,1.48971,1.2913,0.001196,0.0198 9/12/2016,0.4068,26.751208000000002,1301.21365,63.864543999999995,73.22218000000001,0.1989,1.3217,1.4849700000000001,1.2979,0.001193,0.0198 9/13/2016,0.4044,27.374157,1297.358175,63.10929,73.6945,0.2001,1.3399,1.50311,1.3065,0.001188,0.02 9/14/2016,0.4003,26.956083000000003,1301.6052,61.397735,73.6505,0.2002,1.3391,1.50613,1.3073,0.001189,0.02 9/19/2016,0.4057,29.33554,1290.8965,60.99403,72.74152,0.1985,1.3274,1.48324,1.3024,0.001186,0.0198 9/20/2016,0.4062,29.291268,1310.0331,60.72676800000001,73.19508,0.1984,1.3236,1.4758200000000001,1.3014,0.001185,0.0198 9/21/2016,0.4088,29.119740000000004,1279.56335,61.426911,73.06169,0.1977,1.3117,1.46774,1.3076,0.001188,0.0197 9/22/2016,0.4062,29.005011,1277.55495,62.340495,73.91895,0.1962,1.3083,1.46634,1.2983,0.001185,0.0196 9/23/2016,0.4044,29.021282,1252.387,60.18014599999999,74.35638,0.1966,1.3114,1.4723600000000001,1.2989,0.001189,0.0197 9/26/2016,0.4038,29.518384,1237.8994,62.00956,74.59481600000001,0.1962,1.3096,1.47374,1.3052,0.001181,0.0197 9/27/2016,0.4033,30.024986,1242.34575,59.958670999999995,74.292928,0.1959,1.3043,1.4625299999999999,1.2987,0.001189,0.0196 9/28/2016,0.4041,30.250999999999998,1229.15,63.297,74.36,0.1956,1.3,1.4582600000000001,1.2911,0.00119,0.0196 9/29/2016,0.4017,29.806496000000003,1244.4474,64.48470400000001,75.69488,0.1955,1.3096,1.4697200000000001,1.2962,0.001188,0.0196 9/30/2016,0.3999,29.412915,1245.447,64.04783,75.418735,0.1956,1.3055,1.4659799999999998,1.2883,0.001185,0.0196 10/10/2016,0.41,30.406698,1254.7857,69.857844,75.037368,0.1959,1.3146,1.4642700000000002,1.2688,0.001186,0.0198 10/12/2016,0.4136,30.613559999999996,1250.3292,68.513544,77.532312,0.1968,1.3224,1.45556,1.2691,0.001175,0.0198 10/13/2016,0.4157,30.281903999999997,1263.3975,68.742036,76.920264,0.1967,1.3212,1.46061,1.274,0.001169,0.0198 10/14/2016,0.4096,30.083121000000002,1263.85875,68.21554499999999,76.882005,0.1952,1.3131,1.4406,1.2599,0.0011560000000000001,0.0197 10/17/2016,0.409,30.360444,1282.387925,67.53756800000001,77.133356,0.1947,1.3109,1.44194,1.2618,0.001153,0.0196 10/18/2016,0.4092,30.029590000000002,1268.62625,67.41656,76.743735,0.1936,1.3045,1.43239,1.256,0.001159,0.0195 10/19/2016,0.4086,29.722545,1271.14065,68.212917,76.566312,0.1926,1.2951,1.42116,1.2518,0.0011560000000000001,0.0194 10/20/2016,0.4173,29.657082,1278.97805,67.36431800000001,78.40378,0.1942,1.3111,1.433,1.2612,0.001158,0.0196 10/21/2016,0.4166,29.852295,1292.1535,68.06481,77.96299499999999,0.1947,1.3145,1.4300899999999999,1.2659,0.001157,0.0196 10/24/2016,0.4207,30.480159999999998,1303.2896,67.608148,77.829512,0.1942,1.3138,1.4297799999999998,1.261,0.001157,0.0197 10/25/2016,0.4202,29.985560999999997,1295.603775,66.418083,80.070471,0.1929,1.3077,1.42414,1.2548,0.001157,0.0196 10/26/2016,0.4162,29.631957,1320.171,65.328858,80.491218,0.1929,1.3071,1.42584,1.2511,0.0011480000000000001,0.0195 10/27/2016,0.4161,29.769102,1336.57865,66.509366,81.216014,0.1939,1.3178,1.43602,1.2513,0.0011480000000000001,0.0197 10/28/2016,0.4112,29.164776,1317.745125,65.423331,81.46659,0.1948,1.3161,1.44487,1.2566,0.001147,0.0197 10/31/2016,0.4116,28.347294,1317.15695,63.47586,81.979796,0.1943,1.3142,1.4430399999999999,1.2538,0.001149,0.0197 11/1/2016,0.4043,27.691091999999998,1286.2179,62.909352,81.857952,0.1931,1.3068,1.44474,1.2547,0.00114,0.0196 11/2/2016,0.4043,28.32501,1274.951775,61.166357999999995,83.186769,0.1929,1.3053,1.44864,1.2638,0.00114,0.0196 11/3/2016,0.4014,27.960516,1275.340575,60.333794999999995,82.957341,0.1925,1.3017,1.44559,1.2639,0.0011380000000000001,0.0195 11/4/2016,0.4026,28.320709,1279.18895,59.404414,83.424233,0.193,1.3033,1.45139,1.2638,0.001142,0.0195 11/7/2016,0.4036,28.819607,1280.188425,59.722715,85.48824599999999,0.1918,1.2941,1.42861,1.2387,0.001134,0.0194 11/8/2016,0.4065,28.308345000000003,1290.754875,59.322540000000004,85.99449,0.1911,1.2885,1.42055,1.2251,0.001141,0.0195 11/9/2016,0.406,28.953045,1285.9289999999999,60.70842,91.87451999999999,0.1922,1.3095,1.42885,1.2392,0.001131,0.0197 11/10/2016,0.3875,28.437275,1299.0515,60.210840000000005,96.4109,0.1932,1.3135,1.4308100000000001,1.2296,0.001126,0.0195 11/11/2016,0.3895,28.750329999999998,1296.41465,59.289275,101.44759300000001,0.1945,1.3249,1.43862,1.2422,0.0011380000000000001,0.0196 11/14/2016,0.3855,28.629468,1285.2156,58.807548,105.35856000000001,0.1933,1.3236,1.42151,1.2208,0.001132,0.0195 11/15/2016,0.3853,27.979335,1309.00955,62.110155000000006,103.50369599999999,0.193,1.3229,1.41849,1.2115,0.0011330000000000001,0.0195 11/16/2016,0.3903,27.217247999999998,1317.7506,62.334984,99.685176,0.1944,1.3368,1.4291399999999999,1.2253,0.001142,0.0197 11/17/2016,0.3941,27.294978000000004,1335.72605,62.756851,99.744111,0.1947,1.3499,1.43495,1.2257,0.001144,0.0198 11/18/2016,0.4031,27.466465000000003,1354.580625,63.874866000000004,99.54719300000001,0.1972,1.3631,1.4429100000000001,1.2287,0.0011539999999999999,0.02 11/21/2016,0.4051,27.621055,1384.785325,66.37196999999999,99.02860799999999,0.1968,1.3573,1.4426,1.2247,0.00115,0.0199 11/22/2016,0.4026,26.68225,1391.53,66.36112,100.50089,0.1967,1.351,1.4356200000000001,1.2156,0.001155,0.0198 11/23/2016,0.3993,26.513278000000003,1400.477925,66.28319499999999,103.344912,0.1955,1.3541,1.42898,1.2035,0.001146,0.0197 11/25/2016,0.3937,26.664959999999997,1405.8239999999998,63.490559999999995,107.64096,0.1945,1.344,1.42214,1.1865,0.00114,0.0196 11/28/2016,0.3944,26.653798,1411.5552,64.48240799999999,108.152397,0.1932,1.3367,1.41854,1.1939,0.001141,0.0195 11/29/2016,0.3939,26.269692,1392.9885,61.972956,108.27228600000001,0.19399999999999998,1.3362,1.42303,1.189,0.001144,0.0195 11/30/2016,0.4,26.828683,1397.976175,68.35152099999999,107.179302,0.1958,1.3543,1.4338,1.1832,0.00115,0.0197 12/1/2016,0.3892,26.110832000000002,1388.823825,72.748878,107.450929,0.1965,1.3487,1.43784,1.182,0.001155,0.0198 12/2/2016,0.3859,25.624624,1377.0555,72.98729200000001,106.59950800000001,0.1949,1.3402,1.43032,1.1814,0.0011480000000000001,0.0197 12/5/2016,0.3909,25.347402,1396.51605,73.526202,108.201555,0.195,1.3383,1.44058,1.1755,0.001147,0.0197 12/6/2016,0.39299999999999996,26.149253,1404.299325,72.282379,107.572478,0.1948,1.3403,1.43661,1.1755,0.001144,0.0198 12/7/2016,0.3941,26.235495,1401.9885,70.8345,108.964845,0.1946,1.3365,1.4372,1.1749,0.0011539999999999999,0.0198 12/8/2016,0.3972,26.061055,1376.0773,72.207211,108.70608700000001,0.1951,1.3399,1.42235,1.1751,0.0011560000000000001,0.0198 12/9/2016,0.397,25.825851999999998,1392.63625,72.927159,108.04172700000001,0.19399999999999998,1.3423,1.4178,1.1642,0.001149,0.0199 12/12/2016,0.3997,25.681425,1375.4571,74.296029,111.66417,0.1932,1.3341,1.41856,1.1598,0.001146,0.0198 12/13/2016,0.3999,24.80124,1370.7352,74.297048,109.97883200000001,0.1934,1.3334,1.4168,1.1578,0.001145,0.0198 12/14/2016,0.4004,24.345909,1382.369625,72.78116999999999,111.372744,0.1928,1.3503,1.42258,1.1536,0.001145,0.0199 12/15/2016,0.40399999999999997,25.224895999999998,1398.5139,73.418582,110.712286,0.1957,1.3591,1.41524,1.1501,0.001149,0.02 12/16/2016,0.4044,24.943179999999998,1419.31075,75.58249,111.21756,0.1969,1.369,1.43042,1.1609,0.0011539999999999999,0.0202 12/19/2016,0.4093,25.168338000000002,1410.2829,75.822552,110.42038799999999,0.1979,1.3806,1.4356799999999998,1.1788,0.0011619999999999998,0.0203 12/20/2016,0.4112,25.139375,1384.731875,76.244625,108.79495,0.1988,1.3775,1.43099,1.1688,0.001155,0.0203 12/21/2016,0.4148,25.145120000000002,1390.9258,75.241936,109.104952,0.1985,1.3816,1.4401700000000002,1.1755,0.001157,0.0204 12/22/2016,0.42100000000000004,25.162496,1377.9792,76.27728,109.060576,0.19899999999999998,1.3856,1.4461600000000001,1.1788,0.00115,0.0204 12/23/2016,0.4259,25.29384,1378.2704,76.870976,109.174624,0.2008,1.3936,1.45718,1.188,0.00116,0.0205 12/27/2016,0.4251,25.802118,1412.227575,78.06045300000001,107.71758,0.2,1.3917,1.45575,1.1852,0.001153,0.0205 12/28/2016,0.4249,26.458766999999998,1402.704775,78.331326,109.053591,0.2004,1.3933,1.45089,1.1882,0.00115,0.0204 12/29/2016,0.4263,26.997548,1389.7019,77.765128,108.973684,0.1997,1.3852,1.4530299999999998,1.1885,0.0011480000000000001,0.0204 12/30/2016,0.4257,27.093536999999998,1383.83955,78.905934,108.401922,0.1993,1.3887,1.45969,1.1871,0.001149,0.0204 1/3/2017,0.4241,28.408401,1366.747425,76.831497,108.010098,0.1992,1.3851,1.44129,1.1764,0.0011480000000000001,0.0203 1/4/2017,0.4261,28.68197,1381.58125,77.51958,106.62718000000001,0.1985,1.3730000000000002,1.44004,1.171,0.0011480000000000001,0.0202 1/5/2017,0.4257,28.316906,1367.46945,77.52400300000001,107.36713300000001,0.1981,1.3627,1.44544,1.181,0.001151,0.0201 1/6/2017,0.4254,28.43165,1351.0172,78.23841999999999,107.382574,0.1973,1.3702,1.44223,1.171,0.001139,0.0201 1/9/2017,0.4249,27.767115999999998,1355.0407,74.707412,107.301818,0.1964,1.3598,1.43802,1.1715,0.0011300000000000001,0.02 1/10/2017,0.4248,27.791359999999997,1364.4635,72.78948000000001,107.63723999999999,0.1962,1.357,1.4324700000000001,1.172,0.001129,0.0199 1/11/2017,0.4203,27.628528000000003,1347.8314,74.04338,106.56334,0.1959,1.3438,1.42212,1.1644,0.001131,0.0197 1/12/2017,0.4193,27.735359999999996,1378.7520000000002,74.82936,107.26744,0.1934,1.3359999999999999,1.41813,1.1648,0.001137,0.0196 1/13/2017,0.4144,27.355211999999998,1389.75675,73.920395,107.00793700000001,0.1939,1.3331,1.41798,1.1642,0.001135,0.0196 1/17/2017,0.4114,27.394695000000002,1413.013875,73.303605,110.66241000000001,0.1936,1.3215,1.41583,1.1735,0.001139,0.0195 1/18/2017,0.4133,27.953752,1432.33,71.843008,111.2554,0.1932,1.3324,1.41631,1.1622,0.001131,0.0195 1/19/2017,0.4132,26.68805,1415.405625,71.6266,109.2385,0.1929,1.3225,1.4103,1.1514,0.001125,0.0194 1/20/2017,0.4173,26.710247999999996,1412.943,73.446564,108.46902,0.1927,1.3236,1.4166299999999998,1.1544,0.001126,0.0194 1/23/2017,0.4168,27.220032,1394.9607,72.837324,108.036096,0.1925,1.3188,1.41943,1.1701,0.001132,0.0194 1/24/2017,0.4158,27.142962,1396.05565,73.119816,110.049016,0.192,1.3189,1.41588,1.1591,0.0011279999999999999,0.0194 1/25/2017,0.41600000000000004,26.858970000000003,1393.457625,72.73314,110.18252,0.1924,1.3205,1.41967,1.1658,0.0011359999999999999,0.0194 1/26/2017,0.4182,27.023828,1393.00135,74.647352,110.74991200000001,0.1927,1.3273,1.4176600000000001,1.1588,0.001132,0.0195 2/3/2017,0.4168,27.478887,1336.8459,73.949577,108.43161,0.1894,1.3017,1.40432,1.1559,0.001143,0.0194 2/6/2017,0.4186,27.65049,1352.4979999999998,72.74246,107.168495,0.1908,1.3055,1.40343,1.1683,0.00115,0.0194 2/7/2017,0.4202,27.165992,1367.149525,72.176055,107.890419,0.1905,1.3111,1.4006399999999999,1.1666,0.001147,0.0195 2/8/2017,0.4201,27.156156,1384.950875,72.10247199999999,109.801914,0.1905,1.3081,1.39941,1.1687,0.001142,0.0195 2/9/2017,0.4193,27.082475,1377.73075,72.958745,110.79552,0.1909,1.3115,1.39749,1.1582,0.001139,0.0196 2/10/2017,0.4183,26.599092,1379.4534,73.85741999999999,111.88031399999998,0.1896,1.3026,1.38721,1.1506,0.001137,0.0195 2/13/2017,0.4208,26.178,1379.907825,72.761751,120.4188,0.1902,1.3089,1.38739,1.1507,0.0011380000000000001,0.0195 2/14/2017,0.4229,26.71335,1363.725,73.04085,120.28185,0.1903,1.305,1.38024,1.1421,0.001146,0.0195 2/15/2017,0.424,26.562559999999998,1376.44125,72.30775,119.54449,0.1894,1.297,1.3748200000000002,1.1362,0.001142,0.0194 2/16/2017,0.4207,26.459856,1356.4575,72.32274,119.784132,0.1895,1.2996,1.3874600000000001,1.1475,0.0011380000000000001,0.0193 2/17/2017,0.4209,26.48135,1346.89625,72.80414499999999,120.496665,0.1899,1.3045,1.3849,1.156,0.001134,0.0195 2/21/2017,0.4206,27.10032,1337.101125,73.822314,123.658239,0.1894,1.3029,1.37286,1.1461,0.001139,0.0195 2/22/2017,0.4235,26.885721999999998,1327.73405,72.491488,121.45959199999999,0.1892,1.2982,1.3706399999999999,1.1457,0.001139,0.0194 2/23/2017,0.4231,26.129376,1311.00515,73.333338,120.04478200000001,0.1888,1.2961,1.37153,1.151,0.001144,0.0195 2/24/2017,0.4193,25.80534,1320.89455,72.971767,117.27093400000001,0.1895,1.3033,1.37604,1.1626,0.001153,0.0195 2/27/2017,0.4187,24.878088,1317.5352,72.887976,119.920464,0.1893,1.3032,1.37979,1.1564,0.0011480000000000001,0.0195 2/28/2017,0.4199,25.21886,1338.65,72.60054000000001,120.75276000000001,0.1893,1.306,1.38129,1.1582,0.001149,0.0196 3/1/2017,0.4211,25.376596,1356.436375,73.420172,119.379428,0.1898,1.3027,1.37391,1.1454,0.001143,0.0195 3/2/2017,0.4189,25.962996,1355.92605,72.738648,120.478338,0.1916,1.3206,1.38749,1.1542,0.0011480000000000001,0.0198 3/3/2017,0.4226,25.698079999999997,1352.0455,73.59235,118.840455,0.1916,1.3165,1.3982299999999999,1.1545,0.001143,0.0197 3/6/2017,0.4204,25.26268,1354.4886,73.88839200000001,115.720224,0.191,1.3192,1.39621,1.1581,0.001142,0.0198 3/7/2017,0.4226,24.2512,1337.4405,73.70255999999999,114.62646000000001,0.1909,1.318,1.3925,1.1563,0.001145,0.0198 3/8/2017,0.419,24.44256,1343.0124,70.551324,114.48151200000001,0.1918,1.3284,1.40035,1.1614,0.00115,0.0199 3/9/2017,0.4173,23.9832,1332.7331,69.53795600000001,113.866904,0.1928,1.3324,1.40916,1.1591,0.001149,0.02 3/10/2017,0.4216,24.15972,1321.0275,68.11662,112.33872,0.1919,1.3259999999999998,1.41523,1.1552,0.001155,0.0199 3/13/2017,0.4189,24.012144,1315.8470000000002,67.82308,113.45671999999999,0.1906,1.3208,1.40716,1.1497,0.001151,0.02 3/14/2017,0.4173,24.025679999999998,1306.13175,67.36716,113.6457,0.1912,1.3230000000000002,1.40278,1.153,0.001151,0.0201 3/15/2017,0.4179,23.646133,1294.5058,67.202751,114.91008899999999,0.1905,1.2971,1.3924299999999998,1.1441,0.001149,0.0199 3/16/2017,0.4175,23.7688,1304.3536,67.386176,114.84563200000001,0.1891,1.3024,1.40221,1.1495,0.0011539999999999999,0.0199 3/17/2017,0.4197,23.577392,1297.6,67.163776,115.35663999999998,0.1881,1.2976,1.39371,1.1520000000000001,0.001146,0.0198 3/20/2017,0.4211,22.90026,1293.1531,66.785956,114.17785,0.1874,1.2938,1.3890799999999999,1.1495,0.001161,0.0198 3/21/2017,0.4212,22.482187,1302.25045,66.263288,114.03631000000001,0.1882,1.3003,1.40559,1.1639,0.001158,0.0198 3/22/2017,0.4218,22.53325,1302.174375,65.9586,110.84275,0.1891,1.3025,1.40624,1.1717,0.001166,0.0199 3/23/2017,0.4175,23.07536,1299.3001,66.28921600000001,111.22061299999999,0.1902,1.3111,1.4137,1.182,0.001168,0.02 3/24/2017,0.4221,23.231978,1279.98885,66.63944000000001,109.850132,0.1905,1.3118,1.41675,1.1783,0.001174,0.0201 3/27/2017,0.4199,23.23479,1275.28805,66.619525,106.564986,0.1909,1.3127,1.42626,1.1863,0.001181,0.0202 3/28/2017,0.4169,23.001844000000002,1273.2228,67.237167,104.438327,0.19,1.3099,1.4166,1.1787,0.001173,0.0201 3/29/2017,0.4178,22.321056,1263.3822,68.345196,104.773368,0.1894,1.3038,1.4036600000000001,1.1742,0.001173,0.0201 3/30/2017,0.4154,21.999247,1260.2781,69.308752,104.82687,0.1892,1.3087,1.39711,1.1693,0.00117,0.0202 3/31/2017,0.4198,21.969008,1240.0168,69.249564,105.13926799999999,0.1901,1.3108,1.3963700000000001,1.1767,0.001173,0.0202 4/5/2017,0.4236,21.27293,1247.637525,71.825868,105.53223100000001,0.1915,1.3213,1.40866,1.1935,0.0011710000000000002,0.0203 4/6/2017,0.4216,21.801185,1247.76995,72.745717,104.89749499999999,0.192,1.3253,1.41083,1.1961,0.0011710000000000002,0.0205 4/7/2017,0.4238,22.359441,1255.9686,73.651492,101.984117,0.1929,1.3333,1.4127,1.2003,0.001175,0.0207 4/10/2017,0.4256,22.169453,1255.446925,74.626938,98.929351,0.1931,1.3331,1.4127299999999998,1.2017,0.001166,0.0206 4/11/2017,0.425,22.296120000000002,1252.489875,74.98270500000001,97.65220500000001,0.1937,1.3335,1.41415,1.2165,0.001164,0.0206 4/12/2017,0.4253,22.200979999999998,1259.93885,74.260284,94.26775400000001,0.1936,1.3294,1.41761,1.2195,0.0011710000000000002,0.0206 4/13/2017,0.4197,21.93358,1262.50215,73.84745699999999,87.906089,0.1913,1.3213,1.40235,1.2112,0.001163,0.0205 4/17/2017,0.4249,21.700872,1256.0022,72.942336,83.73348,0.1911,1.3176,1.40246,1.2098,0.001163,0.0205 4/18/2017,0.4255,22.08909,1251.2742,72.603003,79.62654,0.1925,1.3227,1.41936,1.2199,0.001158,0.0205 4/19/2017,0.423,21.900996,1267.44345,70.598034,79.921296,0.1935,1.3338,1.4287299999999998,1.2254,0.001166,0.0206 4/20/2017,0.4219,21.696038,1257.85205,70.402514,80.499874,0.1926,1.3286,1.42391,1.2153,0.001167,0.0205 4/21/2017,0.4215,21.762942000000002,1261.2162,68.909352,84.28001,0.1929,1.3262,1.4227100000000001,1.2154,0.001168,0.0205 4/24/2017,0.4223,21.453039999999998,1269.81125,68.1636,82.19261999999999,0.1921,1.321,1.43556,1.2034,0.001164,0.0205 4/25/2017,0.4217,21.474096,1266.8124,69.14712,83.48088,0.1926,1.3272,1.4498799999999998,1.1945,0.001176,0.0206 4/26/2017,0.4216,20.57844,1265.4135,69.33516,86.7693,0.1943,1.338,1.45875,1.2048,0.001181,0.0209 4/27/2017,0.4206,20.330574,1266.642975,68.893592,85.942881,0.1946,1.3393,1.4566700000000001,1.2039,0.001184,0.0209 4/28/2017,0.4204,21.418212,1262.192325,69.075069,87.475503,0.1941,1.3353,1.45509,1.1973,0.001174,0.0208 5/2/2017,0.4211,21.07276,1271.266,66.96042,90.12984,0.1929,1.327,1.45039,1.1849,0.001175,0.0207 5/3/2017,0.4255,21.245344,1300.7216,68.424288,89.18464,0.1946,1.3472,1.46656,1.1949,0.001188,0.021 5/4/2017,0.4233,20.746426,1302.89445,65.303324,83.498628,0.1962,1.3498,1.48271,1.2002,0.001189,0.021 5/5/2017,0.4241,20.628694,1297.5462,66.15734,78.94416600000001,0.1955,1.3474,1.48171,1.1956,0.001186,0.0209 5/8/2017,0.4233,20.819906,1294.475625,66.791558,79.502801,0.1962,1.3537,1.47882,1.1953,0.001194,0.021 5/9/2017,0.42700000000000005,21.02156,1314.187875,66.345895,79.960895,0.1969,1.3615,1.48061,1.1945,0.001196,0.021 5/10/2017,0.4286,21.501216,1305.47945,68.168628,81.17251999999999,0.1962,1.3574,1.4751299999999998,1.1877,0.0012,0.021 5/11/2017,0.4316,21.181776,1295.5712,68.803504,77.761376,0.1965,1.3552,1.4719200000000001,1.1902,0.001204,0.021 5/12/2017,0.4334,20.995887,1291.4298,68.822108,77.675306,0.1959,1.3537,1.48011,1.1943,0.0012,0.0211 5/15/2017,0.434,21.056329,1302.025725,69.899998,77.035679,0.1954,1.3489,1.4805,1.1855,0.001206,0.0211 5/16/2017,0.4349,21.38242,1314.520625,69.546725,78.17779,0.1954,1.3465,1.4924,1.1903,0.001207,0.0211 5/17/2017,0.4287,21.93328,1312.9692,70.253776,80.46688,0.1958,1.3456,1.50148,1.2141,0.001198,0.0209 5/18/2017,0.3992,21.605234,1273.33405,70.77297800000001,78.792388,0.1953,1.3478,1.49651,1.2089,0.001194,0.0208 5/19/2017,0.4121,21.967218,1278.0683,71.896371,80.19778000000001,0.1949,1.3411,1.50183,1.2055,0.001199,0.0208 5/22/2017,0.4093,22.082125,1279.31875,72.051125,83.045375,0.1942,1.3375,1.50295,1.2019,0.001198,0.0207 5/23/2017,0.409,21.222951000000002,1268.094725,72.414795,82.123593,0.1937,1.3373,1.4955200000000002,1.1963,0.001188,0.0206 5/24/2017,0.4067,20.881842000000002,1263.63795,71.907096,77.903796,0.1943,1.3326,1.4950700000000001,1.1952,0.001191,0.0206 5/25/2017,0.4096,21.006324,1260.2453,69.028444,77.88168399999999,0.1951,1.3414,1.50383,1.1994,0.0011970000000000001,0.0208 5/26/2017,0.4119,20.209139999999998,1244.1042,70.02702,76.74101999999999,0.196,1.3428,1.50158,1.2061,0.0012,0.0208 5/31/2017,0.4171,20.012045999999998,1232.7528,67.70719799999999,75.459006,0.1973,1.3458,1.51324,1.2149,0.001202,0.0209 6/1/2017,0.4173,19.29588,1237.011,68.65428,74.20031999999999,0.1988,1.3559999999999999,1.52051,1.2175,0.001209,0.0211 6/2/2017,0.4137,18.45969,1237.699375,67.107825,74.40303,0.1974,1.3435,1.51529,1.2167,0.001201,0.0209 6/5/2017,0.4052,18.554261999999998,1231.6076,66.082026,74.631146,0.1965,1.3358,1.50329,1.2091,0.001194,0.0208 6/6/2017,0.4064,18.624156,1230.2867,66.769864,74.163574,0.1958,1.3322,1.50224,1.2177,0.001191,0.0207 6/7/2017,0.4051,18.72843,1232.778375,63.655469999999994,73.231605,0.1948,1.3245,1.49132,1.206,0.001178,0.0206 6/8/2017,0.4061,19.003368,1243.0376,63.424071999999995,72.88600000000001,0.1951,1.3252,1.48603,1.2044,0.001181,0.0206 6/9/2017,0.40299999999999997,18.957695,1250.78275,63.967275,72.655665,0.1952,1.3285,1.48749,1.2042,0.00118,0.0206 6/12/2017,0.3995,18.59052,1234.8375,64.03254,73.07585999999999,0.1952,1.3259999999999998,1.48558,1.206,0.001172,0.0206 6/13/2017,0.4004,18.296572,1237.241,64.641696,72.04524,0.1951,1.3268,1.48736,1.2055,0.0011769999999999999,0.0206 6/14/2017,0.4023,17.945712,1227.6738,61.9272,71.901432,0.1933,1.3176,1.47886,1.2025,0.0011769999999999999,0.0205 6/15/2017,0.4029,17.773665,1233.402625,61.910940000000004,72.54611,0.1937,1.3195,1.47053,1.1892,0.001167,0.0204 6/16/2017,0.3986,17.638656,1232.3436,62.168388,72.496976,0.1926,1.3124,1.4693200000000002,1.1838,0.001158,0.0204 6/19/2017,0.4007,17.71336,1234.079,61.73356,73.038,0.1929,1.3159999999999998,1.46671,1.1798,0.001158,0.0204 6/20/2017,0.3965,17.954311999999998,1223.8878,60.709584,72.33173599999999,0.1933,1.3192,1.46886,1.1838,0.0011560000000000001,0.0204 6/21/2017,0.3968,17.290134,1216.333125,59.337198,72.589437,0.1939,1.3239,1.47869,1.1886,0.001158,0.0205 6/22/2017,0.3967,17.024556,1198.6136,59.957198,72.341104,0.1939,1.3259,1.4786,1.1909,0.001164,0.0205 6/23/2017,0.3952,17.142449,1195.47765,60.19021800000001,72.468811,0.1931,1.3217,1.4788700000000001,1.1876,0.001164,0.0205 6/26/2017,0.4,16.625024,1195.4592,60.422272,71.51001600000001,0.1926,1.3184,1.4741799999999998,1.1784,0.001163,0.0205 6/27/2017,0.3979,16.681555,1201.665375,61.517355,73.926322,0.1935,1.3187,1.49534,1.1738,0.0011560000000000001,0.0204 6/28/2017,0.3992,16.426695000000002,1196.3346,61.924059,76.230336,0.193,1.3089,1.48929,1.1657,0.001149,0.0203 6/29/2017,0.3941,17.30995,1191.52325,61.717130000000004,80.45873,0.1919,1.3015,1.48904,1.1603,0.001134,0.0201 6/30/2017,0.3931,17.793576,1225.584575,62.32954399999999,80.136127,0.1922,1.3007,1.48584,1.1572,0.001135,0.0202 7/3/2017,0.3952,18.171167999999998,1259.38465,64.852272,81.430852,0.1922,1.3054,1.4835200000000002,1.1513,0.001135,0.0201 7/5/2017,0.3999,18.044544000000002,1283.964,62.853407999999995,80.371872,0.1939,1.3152,1.49301,1.1612,0.00114,0.0203 7/6/2017,0.3997,18.350735999999998,1292.922725,63.423413000000004,79.22983,0.1939,1.3183,1.50584,1.1645,0.001139,0.0204 7/7/2017,0.4008,18.61008,1309.9392,61.432992000000006,79.819488,0.1934,1.3152,1.50039,1.1547,0.00114,0.0203 7/10/2017,0.4038,17.825976,1341.22065,61.628448,80.821608,0.1934,1.3146,1.49866,1.1529,0.001144,0.0204 7/11/2017,0.4023,17.596992,1342.359825,62.217936,82.4859,0.1932,1.3093,1.5013299999999998,1.149,0.001139,0.0203 7/12/2017,0.406,17.569376000000002,1324.2152,62.176576000000004,83.106144,0.192,1.3024,1.48629,1.151,0.001144,0.0202 7/13/2017,0.4028,18.295745999999998,1258.31775,62.650638,80.881689,0.1908,1.2939,1.47419,1.1419,0.001137,0.0201 7/14/2017,0.4017,18.262529999999998,1258.262775,62.462961,79.256826,0.1889,1.2771,1.4646299999999999,1.1354,0.001131,0.0199 7/17/2017,0.4029,18.066198,1262.9669999999999,62.084123999999996,82.009512,0.18899999999999997,1.2822,1.47133,1.1385,0.0011359999999999999,0.0199 7/18/2017,0.4002,17.811120000000003,1249.9364,61.694688,85.127048,0.1871,1.2632,1.45955,1.1272,0.001123,0.0196 7/19/2017,0.3994,18.2352,1257.2856,62.50272,85.793472,0.1864,1.2576,1.44812,1.1233,0.001118,0.0196 7/20/2017,0.4026,18.107606,1273.24995,61.95038,86.441514,0.1859,1.2566,1.46154,1.123,0.001121,0.0195 7/21/2017,0.4019,18.19296,1274.7706,60.719004000000005,85.709056,0.1867,1.2634,1.47327,1.1367,0.001129,0.0196 7/24/2017,0.4011,18.1728,1258.845,61.3332,84.22588,0.1869,1.262,1.4693,1.1359,0.001131,0.0196 7/25/2017,0.3972,17.512610000000002,1236.59185,63.24698000000001,85.660601,0.1864,1.2599,1.4674200000000002,1.1261,0.001125,0.0195 7/26/2017,0.39799999999999996,17.776116000000002,1235.1465,63.671724,85.745088,0.187,1.2492,1.46584,1.1236,0.001123,0.0195 7/27/2017,0.3984,18.111093,1248.510725,64.625099,84.982821,0.18600000000000003,1.2551,1.46557,1.1282,0.001123,0.0196 7/28/2017,0.3999,17.995551000000003,1253.239225,65.77079599999999,85.65732,0.1858,1.2523,1.4714200000000002,1.1315,0.001113,0.0195 7/31/2017,0.3999,18.628554,1242.5283,65.78090999999999,91.281164,0.1863,1.2494,1.47976,1.1333,0.001116,0.0195 8/1/2017,0.4014,18.672912,1204.07655,64.97872199999999,92.64926700000001,0.1867,1.2549,1.48108,1.1371,0.001119,0.0196 8/2/2017,0.4031,18.562929,1213.05415,65.717036,91.798014,0.1864,1.2551,1.48781,1.1333,0.001118,0.0197 8/3/2017,0.4039,18.004842,1195.9191,65.438982,92.377044,0.1874,1.2582,1.4932,1.1434,0.001114,0.0197 8/4/2017,0.4026,17.836195999999997,1197.38395,66.12258800000001,93.84816,0.1876,1.2614,1.48727,1.1396,0.001117,0.0198 8/7/2017,0.4042,17.528906,1212.93205,66.18520600000001,99.77701,0.1882,1.2638,1.49074,1.1409,0.001121,0.0198 8/8/2017,0.4042,17.41103,1216.7505,65.87889,96.98626,0.1887,1.2635,1.4847700000000001,1.1453,0.001119,0.0198 8/9/2017,0.4017,17.29552,1221.0839999999998,66.8236,99.46191999999999,0.1903,1.268,1.4908299999999999,1.1521,0.001113,0.0198 8/10/2017,0.3997,16.809504,1181.6802,65.89224,101.65687199999999,0.1907,1.2696,1.4948299999999999,1.1627,0.0011099999999999999,0.0198 8/11/2017,0.3966,16.72044,1184.99785,65.99507,97.510566,0.1906,1.2667,1.49785,1.1603,0.001108,0.0198 8/14/2017,0.3991,17.1936,1178.7168,64.609728,96.844544,0.1906,1.2736,1.50037,1.1618,0.001118,0.0199 8/15/2017,0.4033,16.789331,1178.641725,64.95796,96.592998,0.1913,1.2787,1.50037,1.1553,0.001125,0.0199 8/16/2017,0.4003,16.327692000000003,1163.06415,63.430686,95.77062,0.1896,1.2618,1.48478,1.1451,0.001111,0.0197 8/17/2017,0.3993,16.854378,1179.74305,64.716246,99.414198,0.1891,1.2682,1.48658,1.1574,0.0011099999999999999,0.0197 8/18/2017,0.4009,16.911351,1182.28125,66.485192,99.324236,0.1895,1.2611,1.4831299999999998,1.1546,0.0011070000000000001,0.0197 8/21/2017,0.3979,17.027088,1174.3905,65.060604,101.898054,0.1889,1.2594,1.48822,1.1556,0.001106,0.0196 8/22/2017,0.3996,17.075289,1180.166625,65.558493,101.37741899999999,0.1895,1.2639,1.48662,1.1535,0.001117,0.0197 8/23/2017,0.4026,17.293917,1182.8685,66.50630699999999,97.18498199999999,0.19,1.2651,1.49379,1.1603,0.001123,0.0198 8/24/2017,0.4021,17.743712,1191.246,65.861824,99.85584,0.1899,1.2656,1.49247,1.1551,0.0011220000000000002,0.0197 8/25/2017,0.3989,17.684815,1183.6095,66.06280500000001,99.46605500000001,0.1897,1.2605,1.50371,1.1525,0.001124,0.0197 8/28/2017,0.3965,17.969067000000003,1174.393425,65.158273,97.844144,0.1899,1.2557,1.5043,1.1493,0.001123,0.0197 8/29/2017,0.3975,17.37865,1170.418125,65.39,97.6323,0.1903,1.2575,1.5057399999999999,1.1458,0.001118,0.0196 8/30/2017,0.4006,17.59615,1167.595,64.3379,96.98755,0.1921,1.265,1.50328,1.148,0.001125,0.0198 8/31/2017,0.3997,18.123839999999998,1178.36425,65.92546800000001,98.913374,0.1915,1.2586,1.49865,1.1444,0.001119,0.0197 9/1/2017,0.3995,17.254875,1182.1158,66.195975,99.538668,0.1912,1.2549,1.48671,1.138,0.001118,0.0197 9/5/2017,0.4013,17.545918,1201.2013,66.757028,97.74689599999999,0.1908,1.2506,1.49001,1.1494,0.001104,0.0195 9/6/2017,0.4032,17.861071,1205.52855,67.74458,97.229721,0.1917,1.2499,1.48958,1.1443,0.001104,0.0195 9/7/2017,0.4008,17.435081,1197.030775,67.71472299999999,97.35311800000001,0.1918,1.2427,1.4940799999999999,1.1458,0.001102,0.0194 9/8/2017,0.4021,17.485689999999998,1187.0165,66.74098000000001,96.12786,0.1909,1.2409999999999999,1.4932,1.1507,0.001097,0.0194 9/11/2017,0.4014,17.798195,1189.141125,67.05771999999999,94.74518499999999,0.1908,1.2455,1.48874,1.1384,0.001102,0.0195 9/12/2017,0.3988,17.484342,1177.574175,67.68011700000001,95.764809,0.1905,1.2471,1.4922600000000001,1.1318,0.001105,0.0195 9/13/2017,0.3993,17.942593,1193.2513,69.065836,96.236406,0.1915,1.2521,1.48851,1.1334,0.001106,0.0195 9/14/2017,0.4002,17.826083999999998,1208.2887,69.293124,94.014792,0.1912,1.2492,1.48892,1.1332,0.001101,0.0195 9/15/2017,0.4018,18.183135,1210.646875,69.508314,92.740237,0.1907,1.2497,1.49263,1.1276,0.001103,0.0195 9/18/2017,0.4003,17.976222,1215.68755,69.693976,93.184916,0.1907,1.2562,1.5025700000000002,1.1259,0.001112,0.0196 9/19/2017,0.3982,17.180736,1205.5233,68.84780400000001,91.122828,0.1898,1.2486,1.49732,1.1189,0.001104,0.0194 9/20/2017,0.3972,17.518557,1207.747,70.086679,89.796612,0.1886,1.2451,1.48086,1.1097,0.0011,0.0193 9/21/2017,0.4016,17.71986,1224.3099,71.169516,88.334448,0.1912,1.2612,1.5059799999999999,1.1207,0.001113,0.0194 9/22/2017,0.4019,17.55888,1236.218,71.41615999999999,83.59936,0.1903,1.256,1.50165,1.1215,0.001108,0.0193 9/25/2017,0.3986,17.3124,1223.775,74.3652,82.2654,0.1899,1.26,1.49284,1.1277,0.0011099999999999999,0.0193 9/26/2017,0.4004,16.748959,1221.62165,74.096076,81.348464,0.1911,1.2679,1.49546,1.1297,0.001114,0.0194 9/27/2017,0.3989,16.665228,1230.14355,73.77039,81.92463000000001,0.1913,1.2741,1.4963,1.1292,0.001112,0.0194 9/28/2017,0.3999,16.837820999999998,1221.15565,73.06570699999999,81.350984,0.1916,1.2727,1.5003799999999998,1.1329,0.0011099999999999999,0.0195 9/29/2017,0.4035,17.28381,1235.971125,73.44981,80.6748,0.1916,1.2765,1.50823,1.1346,0.001115,0.0195 10/9/2017,0.4045,18.0558,1246.817475,71.952363,83.05668,0.1945,1.2897,1.51434,1.1445,0.001127,0.0197 10/10/2017,0.4042,18.218369,1241.9862,72.783477,81.847662,0.1953,1.2857,1.51819,1.1434,0.001132,0.0197 10/11/2017,0.4044,18.3612,1239.381,73.11095999999999,80.75076,0.1951,1.284,1.5225799999999998,1.1413,0.0011330000000000001,0.0197 10/12/2017,0.4029,18.259836,1268.4704,71.926875,78.25644,0.19399999999999998,1.2787,1.51273,1.1388,0.001129,0.0197 10/13/2017,0.4029,18.267557,1268.016925,72.474409,78.001581,0.1928,1.2677,1.49905,1.1336,0.001125,0.0196 10/16/2017,0.4019,18.062484,1262.3358,73.651116,79.268574,0.193,1.2738,1.50266,1.1353,0.001129,0.0197 10/17/2017,0.4033,17.884041,1255.260825,73.779636,79.694244,0.1928,1.2747,1.49971,1.136,0.001127,0.0196 10/18/2017,0.402,17.944960000000002,1254.426625,74.112175,78.02489,0.1927,1.2745,1.50227,1.1285,0.001125,0.0196 10/20/2017,0.4006,17.9102,1252.114875,73.879575,77.602338,0.1932,1.2793,1.5078,1.1269,0.0011300000000000001,0.0196 10/23/2017,0.3959,17.780279999999998,1256.34075,73.49096999999999,78.02571,0.1931,1.281,1.5049700000000001,1.1293,0.0011330000000000001,0.0197 10/24/2017,0.396,18.364079999999998,1254.493,75.01238000000001,78.5103,0.1938,1.286,1.51242,1.1289,0.001137,0.0197 10/25/2017,0.4013,18.407058,1266.29655,75.860964,79.06727099999999,0.1956,1.2981,1.53347,1.1413,0.001151,0.02 10/26/2017,0.3959,18.41355,1267.48125,77.3865,79.12215,0.196,1.305,1.52099,1.1452,0.0011560000000000001,0.0201 10/27/2017,0.4025,19.054112,1270.1656,78.717056,77.36256,0.1962,1.3024,1.51209,1.1458,0.001157,0.0201 10/30/2017,0.3965,19.159311,1265.255925,79.21263,76.429132,0.1963,1.3007,1.51539,1.1493,0.0011560000000000001,0.0201 10/31/2017,0.3993,19.253388,1271.91225,80.16149399999999,76.229832,0.1969,1.3062,1.5211,1.1494,0.001168,0.0202 11/1/2017,0.3988,19.033908,1278.0468,78.806372,77.099704,0.1972,1.3028,1.51376,1.141,0.001172,0.0202 11/2/2017,0.397,18.447772,1282.1396,78.58776800000001,77.693252,0.196,1.2964,1.51149,1.1365,0.001166,0.0201 11/3/2017,0.3944,18.797535999999997,1277.1344,81.137904,79.033312,0.19699999999999998,1.3072,1.51725,1.146,0.0011710000000000002,0.0202 11/6/2017,0.3998,18.930912,1279.3968,83.563854,80.040312,0.1968,1.3002,1.50959,1.1434,0.001168,0.0201 11/7/2017,0.3997,19.25376,1289.688,83.30651999999999,80.46816,0.1973,1.308,1.51552,1.1475,0.001174,0.0201 11/8/2017,0.4007,19.327616,1286.7712,82.689376,80.305984,0.1966,1.3024,1.51015,1.1441,0.001169,0.02 11/9/2017,0.4006,19.375248000000003,1269.873025,83.243253,79.506226,0.1966,1.3021,1.51586,1.1476,0.001165,0.02 11/10/2017,0.3975,19.528783999999998,1275.70215,82.91900799999999,79.48580600000001,0.1961,1.3054,1.5227899999999999,1.1499,0.001164,0.02 11/13/2017,0.4,19.846021,1263.82295,82.846972,80.394093,0.1971,1.3117,1.53061,1.1544,0.001172,0.0201 11/14/2017,0.3952,19.785529999999998,1256.5777,81.513763,81.43514499999999,0.1978,1.3103,1.5460399999999999,1.1549,0.001174,0.02 11/15/2017,0.3975,19.882584,1286.307,81.519912,79.63574399999999,0.19899999999999998,1.3176,1.55376,1.1674,0.001192,0.0202 11/16/2017,0.4021,20.111154,1280.9988,80.866344,80.536869,0.1986,1.3179,1.55128,1.1658,0.001199,0.0202 11/17/2017,0.4056,20.317603,1309.34195,82.90956800000001,81.323288,0.2,1.3219,1.5589600000000001,1.179,0.001207,0.0204 11/20/2017,0.4067,19.84101,1311.255,82.41039,82.46337,0.1996,1.3245,1.55397,1.1761,0.001206,0.0204 11/21/2017,0.4056,19.635648,1305.0844,82.56737199999999,83.385524,0.19899999999999998,1.3196,1.54892,1.1736,0.001209,0.0204 11/22/2017,0.4072,20.053472,1308.7909,83.101168,83.704872,0.1993,1.3124,1.55205,1.1805,0.001209,0.0203 11/24/2017,0.4062,20.284305,1304.037925,83.841794,86.638271,0.1988,1.3129,1.56657,1.1772,0.00121,0.0203 11/27/2017,0.4078,20.244006,1310.1384,83.97513599999999,87.829258,0.1991,1.3154,1.56515,1.1839,0.0012050000000000001,0.0204 11/28/2017,0.4097,19.801664000000002,1307.3838,83.748926,87.409074,0.19899999999999998,1.3166,1.55892,1.181,0.001215,0.0204 11/29/2017,0.4072,19.905963,1310.99325,83.361999,88.170075,0.1997,1.3209,1.56518,1.1801,0.001221,0.0205 11/30/2017,0.4043,19.931236,1302.865775,84.02046899999999,90.840441,0.1994,1.3217,1.57328,1.1744,0.001215,0.0205 12/1/2017,0.4032,19.677728,1306.0468,83.715728,90.336272,0.19899999999999998,1.3136,1.56243,1.1703,0.001213,0.0204 12/4/2017,0.4056,19.820466,1314.12585,82.190445,94.061667,0.1989,1.3161,1.56162,1.1708,0.0012109999999999998,0.0205 12/5/2017,0.4054,19.58605,1325.67325,82.62947,93.999895,0.1983,1.3145,1.55459,1.1675,0.001209,0.0204 12/6/2017,0.4086,19.104345000000002,1325.735775,80.938962,91.75374000000001,0.1998,1.3221,1.55952,1.1774,0.001209,0.0205 12/7/2017,0.4042,19.050902999999998,1320.6496,82.80686,89.223726,0.2009,1.3313,1.56738,1.1772,0.001218,0.0206 12/8/2017,0.4044,18.710385000000002,1318.050075,84.42978000000001,87.905517,0.2011,1.3317,1.56788,1.1736,0.001219,0.0207 12/11/2017,0.4022,18.535365,1305.44775,85.953603,88.823595,0.2005,1.3287,1.56374,1.17,0.00122,0.0206 12/12/2017,0.3985,18.216333,1290.819675,83.792486,88.568155,0.2,1.3229,1.5535700000000001,1.1651,0.0012109999999999998,0.0205 12/13/2017,0.3947,18.135189999999998,1282.22995,81.758936,87.310792,0.1986,1.3094,1.54851,1.1635,0.001207,0.0204 12/14/2017,0.3911,17.961588,1262.3331,82.581564,87.87742800000001,0.1976,1.3044,1.5364,1.1606,0.001198,0.0203 12/15/2017,0.3961,17.868646,1265.259725,82.711163,88.479884,0.1974,1.3081,1.53661,1.1615,0.001201,0.0204 12/18/2017,0.3967,17.949920000000002,1254.27675,82.718345,91.406315,0.1971,1.3045,1.53741,1.1591,0.001201,0.0203 12/19/2017,0.3965,18.80505,1247.58,83.259,91.04985,0.1978,1.305,1.54505,1.156,0.001202,0.0204 12/20/2017,0.3957,19.003651,1244.3022,84.205608,90.45320500000001,0.1984,1.3043,1.54844,1.1503,0.001207,0.0204 12/21/2017,0.3927,19.177367999999998,1231.857,84.26616,91.381392,0.1975,1.2984,1.54159,1.1458,0.001202,0.0203 12/22/2017,0.3885,18.93036,1231.1217,84.60315,92.369784,0.1971,1.2966,1.53922,1.1449,0.001204,0.0203 12/26/2017,0.3909,19.020329999999998,1241.173575,86.717178,89.22734399999999,0.1978,1.2939,1.53463,1.1427,0.001202,0.0202 12/27/2017,0.3881,19.217896,1229.9196,85.521568,88.62371999999999,0.1962,1.2872,1.53044,1.1355,0.0011970000000000001,0.0201 12/28/2017,0.3873,19.242,1213.2081,85.58841600000001,88.821072,0.1965,1.2828,1.53234,1.1366,0.001199,0.02 12/29/2017,0.3867,19.41996,1219.19175,85.66046999999999,90.66918000000001,0.1968,1.281,1.53722,1.1367,0.0012,0.0201 1/2/2018,0.3916,19.581008999999998,1219.8215,85.029861,92.961894,0.1969,1.2773,1.54006,1.1374,0.001201,0.0201 1/3/2018,0.3942,19.540153,1224.928925,86.584192,93.731472,0.1965,1.2763,1.53346,1.1343,0.001199,0.0201 1/4/2018,0.3936,19.390375,1219.686375,86.551005,92.85764499999999,0.1961,1.2715,1.53475,1.1278,0.0011970000000000001,0.0201 1/5/2018,0.3939,19.178744000000002,1222.8357,85.999116,93.044888,0.1963,1.2718,1.52973,1.1251,0.0011970000000000001,0.0201 1/8/2018,0.39399999999999996,18.848934,1222.056225,86.43983399999999,93.16066500000001,0.1964,1.2753,1.52606,1.1276,0.001193,0.0201 1/9/2018,0.3934,18.827886,1221.63965,87.965724,95.41763,0.196,1.2782,1.52575,1.1346,0.001192,0.0201 1/10/2018,0.3941,18.680215,1207.5197,88.23692,95.645251,0.1956,1.2751,1.52344,1.1442,0.001192,0.02 1/11/2018,0.3943,17.968896,1191.8016,87.766272,94.96396800000001,0.1952,1.2672,1.52473,1.1391,0.001189,0.0199 1/12/2018,0.3941,17.910757999999998,1192.3664,88.252797,93.519924,0.1961,1.2631,1.54118,1.1374,0.001192,0.0199 1/16/2018,0.3896,17.071758,1216.0016,86.86623,91.740286,0.1953,1.2562,1.54015,1.1373,0.00118,0.0196 1/17/2018,0.3893,16.836732,1215.39375,87.04414799999999,90.58211999999999,0.1949,1.2546,1.5289700000000002,1.1275,0.001175,0.0197 1/18/2018,0.3893,16.35,1216.25,86.6375,91.275,0.1948,1.25,1.5295,1.125,0.001167,0.0196 1/19/2018,0.3915,16.577075,1222.637475,85.837971,92.443779,0.1949,1.2511,1.5284200000000001,1.129,0.001172,0.0196 1/22/2018,0.3893,16.428258,1227.75345,86.10802199999999,92.831508,0.1947,1.2474,1.5295100000000001,1.1246,0.001167,0.0195 1/23/2018,0.3859,16.4875,1232.8125,87.45,90.4875,0.1953,1.25,1.53724,1.1332,0.001164,0.0196 1/24/2018,0.3946,16.315768,1230.19155,87.44309399999999,89.2656,0.1947,1.2398,1.53934,1.1356,0.001165,0.0194 1/25/2018,0.3957,16.49704,1236.3435,87.74332,91.92988000000001,0.1954,1.246,1.54484,1.1389,0.001168,0.0195 1/26/2018,0.3917,16.471544,1215.02295,86.944108,89.681146,0.1954,1.2329,1.53246,1.1356,0.001158,0.0194 1/29/2018,0.3915,16.887918,1224.8991,85.810884,89.282358,0.1948,1.2354,1.52977,1.1339,0.0011539999999999999,0.0194 1/30/2018,0.3889,16.970268,1237.209225,85.370838,89.489715,0.1955,1.2369,1.53454,1.1373,0.001153,0.0194 1/31/2018,0.3895,16.422399,1236.024475,85.711765,88.889493,0.1961,1.2413,1.54103,1.137,0.00116,0.0195 2/1/2018,0.3924,16.630943,1225.2415,86.637635,89.772263,0.1982,1.2439,1.55609,1.137,0.0011619999999999998,0.0195 2/2/2018,0.392,17.199697,1235.084625,86.541102,92.711793,0.2,1.2619,1.57172,1.1455,0.001157,0.0196 2/5/2018,0.3902,17.64327,1230.903675,85.830066,93.712419,0.2002,1.2693,1.5699100000000001,1.1633,0.001159,0.0197 2/6/2018,0.391,17.506216000000002,1247.507625,84.571214,93.248428,0.2022,1.2649,1.5654700000000001,1.1545,0.0011710000000000002,0.0197 2/7/2018,0.3907,17.8976,1256.6672,83.747984,95.58596800000001,0.2024,1.2784,1.56778,1.1692,0.001173,0.0199 2/8/2018,0.3912,17.451658,1269.357525,83.28733100000001,95.431526,0.2027,1.2851,1.57402,1.1819,0.0011710000000000002,0.0199 2/9/2018,0.3878,17.498967,1258.3383,80.37747900000001,95.149833,0.203,1.2801,1.56813,1.1764,0.00118,0.0199 2/12/2018,0.3853,17.461814,1274.02565,79.601962,93.909712,0.2018,1.2718,1.56352,1.1706,0.001175,0.0198 2/13/2018,0.3855,17.151951999999998,1287.3507,79.804928,94.89559200000001,0.2008,1.2724,1.57149,1.1801,0.001172,0.0198 2/14/2018,0.3913,16.906779999999998,1283.464325,81.203012,94.059735,0.2009,1.2617,1.57077,1.179,0.001178,0.0197 2/22/2018,0.392,17.474766,1315.3872,84.620694,94.21843199999999,0.2004,1.2746,1.57158,1.194,0.001179,0.0196 2/23/2018,0.3938,17.447472,1321.63325,85.847174,96.330962,0.2019,1.2754,1.56746,1.1933,0.001185,0.0197 2/26/2018,0.3948,17.391911999999998,1316.8071,85.941,97.488924,0.2021,1.2732,1.56807,1.1906,0.001189,0.0196 2/27/2018,0.395,16.702238,1332.5844,85.539594,98.698544,0.2023,1.2838,1.5704799999999999,1.1961,0.001187,0.0197 2/28/2018,0.3968,17.367632,1346.378,84.750952,97.390156,0.2026,1.2884,1.57093,1.2077,0.001187,0.0197 3/1/2018,0.3965,17.677674,1363.5405,82.302402,97.92993,0.2032,1.2894,1.5815299999999999,1.2137,0.001191,0.0198 3/2/2018,0.3959,17.293012,1366.88245,82.947182,97.379502,0.2035,1.2886,1.5883200000000002,1.2185,0.001193,0.0198 3/5/2018,0.397,17.462568,1373.76065,84.402412,95.15554200000001,0.2034,1.2878,1.5885200000000002,1.2125,0.001194,0.0198 3/6/2018,0.3978,17.179685,1359.68585,84.033567,93.945415,0.2023,1.2773,1.5844799999999999,1.2037,0.0012,0.0197 3/7/2018,0.3941,16.344341,1348.1845,82.220086,92.813877,0.2024,1.2779,1.58609,1.2048,0.001198,0.0197 3/8/2018,0.3934,16.555916,1353.4365,81.700684,91.616252,0.2023,1.2844,1.58056,1.2091,0.001196,0.0197 3/9/2018,0.3914,16.362012,1311.573275,83.453907,86.537713,0.2014,1.2743,1.56913,1.193,0.001196,0.0196 3/12/2018,0.3895,16.423686,1312.43415,82.49949000000001,83.655372,0.2009,1.2702,1.56671,1.1937,0.001193,0.0196 3/13/2018,0.3902,16.056426000000002,1323.82815,82.241472,84.467997,0.2006,1.2723,1.57636,1.1938,0.001193,0.0196 3/14/2018,0.3892,16.197544,1305.5779,82.37136600000001,85.760664,0.2011,1.2694,1.5700399999999999,1.1939,0.001193,0.0195 3/15/2018,0.3902,16.337776,1334.6578,83.509888,86.959544,0.2021,1.2824,1.57785,1.2059,0.001199,0.0197 3/16/2018,0.3952,16.39946,1360.5718,85.834644,87.45514399999999,0.2042,1.2964,1.59302,1.2231,0.0012109999999999998,0.0199 3/19/2018,0.3943,16.700284,1324.751,85.57438,83.48846400000001,0.205,1.2956,1.59825,1.2212,0.001207,0.0198 3/20/2018,0.3931,16.348095999999998,1338.3702,87.753872,82.013816,0.2051,1.3016,1.5932899999999999,1.2217,0.001214,0.02 3/21/2018,0.3934,16.316426,1326.11205,89.463466,81.29881400000001,0.2052,1.2878,1.58886,1.2143,0.00121,0.0198 3/22/2018,0.3922,16.599723,1338.572025,89.576109,83.77855500000001,0.2049,1.2999,1.59912,1.2347,0.001202,0.0199 3/23/2018,0.3923,16.329687,1335.799575,91.52159499999999,79.336037,0.2048,1.2991,1.60466,1.2403,0.001199,0.02 3/26/2018,0.3895,16.030494,1323.61285,90.503884,79.390957,0.2064,1.2907,1.60619,1.2245,0.0012,0.0199 3/27/2018,0.3914,16.329588,1327.5929,91.297242,81.06195,0.2065,1.3022,1.61516,1.2363,0.0012109999999999998,0.0201 3/28/2018,0.3928,15.935270999999998,1328.5918,90.74360300000001,79.85906899999999,0.2068,1.3051,1.60656,1.2216,0.0012259999999999999,0.02 4/2/2018,0.3939,16.342356,1351.63815,88.290492,81.13744799999999,0.2078,1.3053,1.60535,1.2326,0.001235,0.02 4/3/2018,0.3895,16.225964,1350.6456,88.637744,80.882592,0.2071,1.3012,1.59666,1.2208,0.001234,0.02 4/4/2018,0.3891,15.90192,1315.764,88.15392,78.70608,0.20600000000000002,1.296,1.5911899999999999,1.2138,0.001225,0.0199 4/9/2018,0.3796,16.05564,1360.0529999999999,89.17635,79.40786999999999,0.2059,1.2990000000000002,1.60063,1.2165,0.001214,0.02 4/10/2018,0.3778,15.627079,1352.715,91.520832,80.08072800000001,0.2053,1.2883,1.5920100000000001,1.2019,0.00121,0.0198 4/11/2018,0.3821,15.547752,1350.7593,92.899752,80.072212,0.2055,1.2892,1.59495,1.2072,0.001209,0.0198 4/12/2018,0.3778,15.538475,1367.837125,92.86979000000001,79.56215,0.205,1.2895,1.5896,1.2015,0.001204,0.0198 4/13/2018,0.3762,15.560248000000001,1357.979425,93.490298,80.441845,0.2051,1.2881,1.58785,1.1996,0.001201,0.0198 4/16/2018,0.376,15.3943,1338.97,91.7747,78.9247,0.205,1.285,1.5910600000000001,1.1998,0.0012,0.0196 4/17/2018,0.3778,14.999375,1346.725,92.15925,78.898,0.2049,1.2875,1.59293,1.2031,0.001206,0.0196 4/18/2018,0.3801,15.082378,1338.336225,94.39975600000001,79.240296,0.2047,1.2847,1.58966,1.198,0.001206,0.0195 4/19/2018,0.3823,15.20215,1341.99405,95.456564,83.139588,0.205,1.2938,1.59709,1.205,0.001212,0.0196 4/20/2018,0.3819,15.176232,1341.28425,96.559428,83.83434,0.2069,1.3038,1.60152,1.2109,0.001217,0.0197 4/23/2018,0.3809,14.74115,1342.28625,98.24365,85.1068,0.2079,1.315,1.60548,1.2097,0.001216,0.0198 4/24/2018,0.3788,14.650214000000002,1344.360975,97.133286,85.573557,0.2086,1.3151,1.60881,1.2086,0.001221,0.0198 4/25/2018,0.3794,14.35692,1358.355,97.82799999999999,85.12358,0.2089,1.3219999999999998,1.6075700000000002,1.2081,0.001222,0.0198 4/26/2018,0.381,14.522085999999998,1360.8664,98.940812,84.352536,0.2089,1.3238,1.6022100000000001,1.2111,0.001228,0.0198 4/27/2018,0.3814,14.800301999999999,1378.4595,98.457624,83.525412,0.2087,1.3191,1.6002100000000001,1.2095,0.001235,0.0198 5/2/2018,0.3757,15.682725,1378.411425,97.91359200000001,85.247289,0.2094,1.3347,1.59487,1.2152,0.001236,0.02 5/3/2018,0.3763,15.519644,1385.0187,97.737912,85.802788,0.2096,1.3276,1.59174,1.2159,0.001234,0.0199 5/4/2018,0.3759,15.268015,1362.647125,99.315055,86.288825,0.209,1.3265,1.58669,1.2158,0.001235,0.0198 5/7/2018,0.3748,15.06126,1333.493625,101.344185,86.469195,0.2088,1.3305,1.58595,1.2195,0.001231,0.0198 5/8/2018,0.3765,15.510051999999998,1356.794125,100.426245,87.170249,0.2109,1.3417,1.59146,1.2295,0.0012439999999999999,0.02 5/9/2018,0.3731,15.134245000000002,1350.218625,103.500005,86.14053,0.2107,1.3405,1.5881100000000001,1.2211,0.001242,0.0199 5/10/2018,0.374,14.959798000000001,1344.98805,102.833678,85.497834,0.2096,1.3274,1.5820299999999998,1.2136,0.0012460000000000001,0.0198 5/11/2018,0.3684,14.878842,1319.137975,102.26883199999999,86.806506,0.2095,1.3261,1.58318,1.2124,0.001242,0.0197 5/14/2018,0.3669,14.962288000000001,1346.0744,103.952024,86.956672,0.2091,1.3288,1.58465,1.2116,0.001241,0.0196 5/15/2018,0.3662,15.417216,1363.393125,104.962869,87.966459,0.2098,1.3383,1.58431,1.2129,0.0012380000000000002,0.0196 5/16/2018,0.36200000000000004,15.447104999999999,1330.167375,105.48203999999998,86.66877,0.2092,1.3305,1.5710600000000001,1.2054,0.001235,0.0197 5/17/2018,0.3601,15.388672,1324.5439999999999,105.56416000000002,87.300096,0.209,1.3312,1.57023,1.2019,0.00123,0.0196 5/18/2018,0.3562,15.527622000000001,1329.70245,104.551767,86.16099,0.2087,1.3317,1.56725,1.2021,0.001232,0.0196 5/21/2018,0.3589,15.9599,1352.30475,104.49118,83.59822,0.2072,1.319,1.55526,1.1877,0.001224,0.0193 5/22/2018,0.3618,16.036785000000002,1360.15695,105.02444299999999,81.715009,0.207,1.3199,1.55485,1.1902,0.0012259999999999999,0.0194 5/23/2018,0.3645,16.337815,1374.823825,105.56742,81.702304,0.2075,1.3229,1.5470700000000002,1.2018,0.001228,0.0194 5/24/2018,0.3618,16.3416,1367.19,104.0028,81.3384,0.2072,1.32,1.5469700000000002,1.208,0.00122,0.0193 5/25/2018,0.3626,16.508254,1379.88335,101.275356,82.024559,0.2071,1.3249,1.54367,1.2112,0.001228,0.0196 5/29/2018,0.3574,16.600458,1372.93515,100.442097,81.616698,0.2073,1.3323,1.53754,1.225,0.0012289999999999998,0.0196 5/30/2018,0.3542,16.629479999999997,1350.1554,102.2845,81.048918,0.2061,1.3198,1.53999,1.2119,0.001225,0.0196 5/31/2018,0.3548,16.900706,1345.8459,102.527426,81.358598,0.2063,1.3214,1.54498,1.2143,0.0012230000000000001,0.0196 6/1/2018,0.35100000000000003,16.541424,1349.2755,101.454948,81.148104,0.20600000000000002,1.3212,1.54031,1.2062,0.001232,0.0197 6/4/2018,0.3491,15.564010000000001,1310.188825,98.47179100000001,80.527403,0.2042,1.3079,1.52962,1.1907,0.001221,0.0195 6/5/2018,0.3446,15.781057999999998,1314.541125,98.966402,81.3998,0.2052,1.3129,1.5384799999999998,1.1958,0.001225,0.0196 6/6/2018,0.3386,15.91124,1296.70085,98.284512,82.086348,0.2041,1.3042,1.53555,1.1837,0.001222,0.0195 6/7/2018,0.3356,15.385067999999999,1277.8263,101.412912,82.932468,0.2048,1.3116,1.5478299999999998,1.1957,0.0012230000000000001,0.0195 6/8/2018,0.3548,16.117325,1275.242225,100.598422,81.862854,0.2054,1.3157,1.5482200000000002,1.2014,0.001225,0.0195 6/11/2018,0.354,16.2279,1253.2275,100.46844,81.19206,0.2051,1.314,1.54871,1.1941,0.00122,0.0195 6/12/2018,0.3549,16.30694,1259.6616,100.191952,81.58751600000001,0.2054,1.3204,1.5509899999999999,1.1962,0.00122,0.0195 6/13/2018,0.3546,16.508195999999998,1235.1456,101.266104,81.92076800000001,0.2057,1.3196,1.55598,1.1958,0.001215,0.0196 6/14/2018,0.3514,16.352732999999997,1239.825975,101.539374,84.223929,0.2074,1.3371,1.54694,1.2086,0.001228,0.0197 6/15/2018,0.3603,16.153678,1216.90145,98.696016,84.370042,0.2084,1.3439,1.56005,1.2144,0.001218,0.0197 6/19/2018,0.3616,16.040832,1204.4172,101.718384,82.114428,0.2091,1.3548,1.57016,1.2308,0.001218,0.0199 6/20/2018,0.3597,16.138297,1207.31835,101.444602,81.872336,0.2095,1.3573,1.57063,1.2299,0.001222,0.0199 6/21/2018,0.3596,16.092159,1193.69385,99.033885,80.908176,0.2089,1.3557,1.5726799999999999,1.2322,0.00122,0.02 6/22/2018,0.3551,16.193995,1202.11855,101.531645,80.109879,0.207,1.3439,1.5661,1.2222,0.001209,0.0198 6/25/2018,0.3575,16.1844,1179.43815,100.788351,80.719695,0.2064,1.3487,1.57856,1.2287,0.001209,0.0198 6/26/2018,0.3557,16.395936,1173.2158,103.232168,80.680992,0.2055,1.3528,1.57535,1.2293,0.001209,0.0198 6/27/2018,0.3529,15.967328,1181.882,105.74948799999999,81.253536,0.2053,1.3624,1.57395,1.2355,0.001213,0.0198 6/28/2018,0.3521,16.159176000000002,1171.47225,105.89157,81.31275600000001,0.2052,1.3602,1.5735700000000001,1.2311,0.001213,0.0198 6/29/2018,0.3482,16.014557999999997,1159.23255,107.26783200000001,81.61213199999999,0.2042,1.3503,1.57865,1.2193,0.0012109999999999998,0.0197 7/2/2018,0.3483,15.751656,1156.1661,105.32898,80.81580600000001,0.2049,1.3626,1.58581,1.2287,0.001218,0.0198 7/3/2018,0.3475,15.42206,1142.776,105.28703999999999,80.0891,0.2039,1.354,1.5784799999999999,1.2243,0.001214,0.0198 7/5/2018,0.3443,15.539328,1130.9328,104.755104,78.30575999999999,0.2039,1.3536,1.5825,1.2233,0.001209,0.0197 7/6/2018,0.3484,15.495913,1176.6662,103.813193,78.745087,0.2026,1.3463,1.58099,1.2187,0.001207,0.0196 7/9/2018,0.3458,15.268020000000002,1140.748775,104.559151,79.206202,0.2024,1.3393,1.57375,1.2084,0.0012029999999999999,0.0195 7/10/2018,0.3515,15.297386999999999,1142.611575,105.727602,79.329219,0.2019,1.3407,1.57467,1.2079,0.0012029999999999999,0.0195 7/11/2018,0.3503,15.326175,1126.385625,99.6405,79.943175,0.2024,1.3575,1.58465,1.2119,0.0012029999999999999,0.0197 7/12/2018,0.3478,14.956892000000002,1120.417,100.500055,78.672172,0.2024,1.3499,1.57559,1.1997,0.0012,0.0198 7/13/2018,0.35,14.771888,1097.1092,101.529774,78.158922,0.2016,1.3478,1.57399,1.1995,0.001192,0.0197 7/16/2018,0.3491,15.012264000000002,1117.8342,96.811584,79.090644,0.2015,1.3476,1.5784799999999999,1.2001,0.001194,0.0197 7/17/2018,0.3525,15.063342,1136.1793,97.661344,79.877668,0.2016,1.3534,1.57825,1.199,0.001201,0.0198 7/18/2018,0.3512,14.977944,1138.55355,98.54621999999999,79.972488,0.2015,1.3518,1.5732,1.198,0.0011949999999999999,0.0197 7/19/2018,0.3548,14.914812,1150.2216,98.67976800000001,79.917288,0.2014,1.3596,1.58189,1.2087,0.0011970000000000001,0.0197 7/20/2018,0.3575,14.98976,1145.463,98.49835999999999,79.27588,0.1993,1.348,1.5813700000000002,1.21,0.0011949999999999999,0.0196 7/23/2018,0.358,15.012292,1148.616475,98.98899399999999,80.603001,0.1994,1.3549,1.58398,1.2168,0.001194,0.0197 7/24/2018,0.3593,15.086357999999999,1156.7556,99.011808,80.123526,0.1984,1.3482,1.57434,1.2123,0.001196,0.0196 7/25/2018,0.3634,15.010266,1154.61005,99.169702,80.363274,0.1994,1.3414,1.57328,1.2089,0.0012,0.0196 7/26/2018,0.3618,14.952268,1167.5105,101.046424,80.847984,0.1992,1.3556,1.57827,1.2188,0.001206,0.0197 7/27/2018,0.3641,14.699968,1176.13255,100.37321899999999,82.930518,0.1982,1.3511,1.5753,1.217,0.0012109999999999998,0.0197 7/30/2018,0.3618,14.608082000000001,1181.3375,101.21699699999999,82.558615,0.198,1.3501,1.58038,1.2156,0.001208,0.0197 7/31/2018,0.3584,14.203465,1216.718625,99.962775,81.949281,0.1973,1.3463,1.57477,1.2035,0.001209,0.0197 8/1/2018,0.3601,14.154288000000001,1197.64455,97.76993399999999,80.927952,0.198,1.3506,1.57475,1.2089,0.001206,0.0198 8/2/2018,0.3622,14.385456,1198.788,99.77448000000001,81.205152,0.1981,1.3584,1.57408,1.217,0.001204,0.0198 8/3/2018,0.3644,14.659435,1197.412375,98.91403100000001,82.05230300000001,0.1977,1.3511,1.56237,1.2142,0.0012029999999999999,0.0197 8/6/2018,0.3624,14.864723999999999,1187.62105,99.84275,84.923874,0.1974,1.3538,1.5641399999999999,1.2152,0.001202,0.0197 8/7/2018,0.3591,14.661888000000001,1198.3533,100.59834000000001,85.478268,0.1972,1.3476,1.5629600000000001,1.2099,0.0012050000000000001,0.0196 8/8/2018,0.3568,14.545936,1202.63,97.259968,85.71472,0.1972,1.3456,1.56236,1.2125,0.0012050000000000001,0.0197 8/9/2018,0.3568,14.701208,1203.96655,97.741334,87.027354,0.1981,1.3562,1.56348,1.2208,0.001207,0.0197 8/10/2018,0.3544,14.437692000000002,1158.8508,99.735138,87.708294,0.1998,1.3698,1.56293,1.2357,0.001213,0.0198 8/13/2018,0.354,14.16765,1173.98925,99.875055,88.82979,0.1994,1.3755,1.56959,1.2419,0.001209,0.0197 8/14/2018,0.3571,14.28471,1194.30675,100.10349000000001,88.84426500000001,0.2005,1.3815,1.5662,1.2426,0.001224,0.0197 8/15/2018,0.3537,14.131722,1184.5505,97.747864,88.078064,0.1996,1.3814,1.5672,1.2474,0.001218,0.0197 8/16/2018,0.3527,14.18516,1219.5106,98.373396,85.854648,0.1995,1.3772,1.5668,1.2419,0.001222,0.0197 8/17/2018,0.3496,13.920132,1205.3631,98.220342,86.07783,0.1996,1.3674,1.56402,1.2375,0.001221,0.0196 8/20/2018,0.3432,13.749642999999999,1201.560725,98.40056700000001,86.47694200000001,0.1995,1.3627,1.56457,1.238,0.001219,0.0195 8/21/2018,0.3353,13.807808999999999,1187.30865,98.609751,85.41290699999999,0.1987,1.3577,1.57043,1.2308,0.001216,0.0194 8/22/2018,0.3365,13.850907999999999,1167.73495,101.74566800000001,84.819804,0.1989,1.3606,1.57794,1.2306,0.001216,0.0195 8/23/2018,0.3352,13.963576000000002,1161.7916,103.112454,85.82356,0.2,1.3798,1.5921,1.2398,0.001227,0.0196 8/24/2018,0.3325,13.964973,1149.4142,103.501882,84.6362,0.2003,1.3651,1.58578,1.2274,0.001224,0.0196 8/27/2018,0.3332,14.305160999999998,1136.178225,103.729431,83.476263,0.1998,1.3611,1.58864,1.2253,0.0012259999999999999,0.0195 8/28/2018,0.3293,14.048406,1118.0133,103.48947,83.009592,0.2,1.3626,1.59359,1.2255,0.0012289999999999998,0.0194 8/29/2018,0.3331,14.186160000000001,1126.2060000000001,105.52752,83.70792,0.201,1.368,1.60151,1.2249,0.001232,0.0194 8/30/2018,0.3317,14.550661999999999,1128.1237,107.058182,85.37673199999999,0.201,1.3766,1.60686,1.2403,0.001234,0.0194 8/31/2018,0.34299999999999997,14.74036,1158.3698,107.660252,86.203294,0.2031,1.3906,1.6136700000000002,1.2519,0.001247,0.0196 9/4/2018,0.3349,14.821520000000001,1158.976,108.89081000000002,86.72818000000001,0.2037,1.393,1.61332,1.2501,0.0012460000000000001,0.0195 9/5/2018,0.3353,15.139278,1147.6101,107.420754,87.151638,0.2037,1.3902,1.61699,1.2465,0.001241,0.0194 9/6/2018,0.3426,14.999039999999999,1148.1904,106.2432,88.008256,0.2033,1.3888,1.61428,1.2544,0.0012380000000000002,0.0193 9/7/2018,0.3469,15.494373000000001,1170.8736,108.122859,91.08045600000001,0.2047,1.4073,1.62568,1.2678,0.001247,0.0195 9/10/2018,0.3441,15.743839999999999,1171.65095,108.759009,90.217826,0.2048,1.4057,1.62952,1.2648,0.0012439999999999999,0.0194 9/11/2018,0.3382,15.698955999999999,1151.79505,111.016052,89.335204,0.205,1.4042,1.63022,1.2584,0.0012490000000000001,0.0194 9/12/2018,0.3352,16.273815,1156.0405,111.19743000000001,88.1324,0.2034,1.3945,1.6217,1.2535,0.001245,0.0194 9/13/2018,0.3306,16.242207999999998,1144.11615,108.71710800000001,89.01230600000001,0.2032,1.3906,1.62496,1.2419,0.00124,0.0194 9/14/2018,0.335,15.599448,1148.2927,109.154202,89.82262800000001,0.2028,1.3978,1.6251799999999998,1.2474,0.0012460000000000001,0.0194 9/17/2018,0.3371,14.808653,1147.21785,108.73145500000001,89.520606,0.2031,1.3931,1.62683,1.2456,0.0012369999999999998,0.0192 9/18/2018,0.3328,14.571252,1127.4714,109.464453,89.24199300000001,0.2022,1.3851,1.61592,1.2327,0.001233,0.0191 9/19/2018,0.3337,14.814368,1142.744,109.31792,89.257944,0.2009,1.3768,1.60704,1.2263,0.00123,0.0191 9/20/2018,0.3364,14.81112,1166.03285,107.92918,88.537584,0.2008,1.3714,1.61505,1.2192,0.001228,0.0191 9/21/2018,0.3388,14.874648,1162.59645,108.12936,89.069502,0.2003,1.3722,1.61155,1.2187,0.001231,0.019 9/25/2018,0.3386,14.289548000000002,1166.542975,112.92329099999999,89.723465,0.2008,1.3793,1.62296,1.2209,0.001234,0.019 9/26/2018,0.3417,13.640220000000001,1171.13,112.070252,89.97034000000001,0.2003,1.3778,1.61741,1.2223,0.001235,0.019 9/27/2018,0.3458,13.944375,1186.3125,113.3865,90.60375,0.2012,1.3875,1.6151200000000001,1.2237,0.001245,0.0191 9/28/2018,0.3417,14.425448000000001,1170.5102,114.517568,91.398088,0.2011,1.3844,1.60689,1.2175,0.001247,0.0191 10/8/2018,0.3738,18.281632000000002,1228.7828,118.548048,94.23376,0.2042,1.4128,1.62352,1.2477,0.001245,0.0191 10/9/2018,0.3792,18.259166,1214.9314,119.663,95.322138,0.2038,1.4078,1.61776,1.2464,0.0012439999999999999,0.019 10/10/2018,0.3773,18.209735000000002,1207.723475,117.746839,96.91546899999999,0.2036,1.4171,1.63286,1.2621,0.00124,0.019 10/11/2018,0.3713,18.138388,1204.897175,112.67701399999999,94.524587,0.2043,1.4039,1.62741,1.2516,0.001236,0.019 10/12/2018,0.3719,18.377727,1219.79175,113.092623,94.700835,0.203,1.4061,1.6250200000000001,1.2528,0.001242,0.0191 10/15/2018,0.3753,18.834232,1250.2396,113.285872,94.830288,0.2024,1.4024,1.62401,1.2548,0.001239,0.019 10/16/2018,0.376,18.553975,1238.915425,113.998423,94.31020500000001,0.2026,1.4003,1.62073,1.2475,0.001247,0.0191 10/17/2018,0.3815,19.313991,1245.984525,112.60633500000002,96.049476,0.2025,1.4067,1.61781,1.2488,0.0012460000000000001,0.0191 10/18/2018,0.3783,19.537282,1216.3261,111.687894,97.34834599999999,0.2021,1.4086,1.61329,1.2556,0.0012369999999999998,0.0191 10/19/2018,0.3786,19.511283,1203.476725,112.066966,96.713595,0.2026,1.4047,1.6175700000000002,1.2483,0.001241,0.0191 10/22/2018,0.3832,19.516604,1212.3737,112.735926,99.10819599999999,0.2032,1.4122,1.61907,1.2517,0.0012460000000000001,0.0192 10/23/2018,0.3819,19.490053,1210.18975,107.879772,99.045034,0.2038,1.4113,1.6188799999999999,1.2551,0.001242,0.0193 10/24/2018,0.3792,19.838160000000002,1203.954,107.85672,100.70591999999999,0.2037,1.416,1.61371,1.2612,0.001243,0.0193 ================================================ FILE: Ore Money project/iron ore production/iron ore production bubble map.csv ================================================ region,iron ore production,latitude,longitude Australia,817000,-24.15,133.08 Brazil,397000,-10.47,-52.55 China,375000,31.55,108.2 India,156000,22.37,79.13 Russia,101000,65.45,97.35 South Africa,73000,-30.44,25.12 Ukraine,67000,49.3,32.28 United States,46000,37.91,-97.02 Canada,46000,58.27,-105.42 Iran,27000,32.44,53.3 Sweden,25000,64.2,18.03 Kazakhstan,21000,47.1,67.3 Mexico,18840,20.2,-100.1 Chile,17109,-33.24,-70.9 Venezuela,16800,7.3,-65.55 Sierra Leone,11895,7.3,-11.17 Malaysia,11588,3.59,101.91 Peru,10126,-11,-75 Turkey,8589,39.57,35.54 Mongolia,6736,46,105 Vietnam,4708,17.05,107.55 Indonesia,4000,-1.09,115.49 Norway,3409,60.55,7.45 Egypt,3320,26.01,30.14 North Korea,3054,39.09,126.3 Algeria,1067,29.42,3.08 Philippines,1057,11.4,124.03 ================================================ FILE: Ore Money project/iron ore production/iron ore production bubble map.py ================================================ # coding: utf-8 # In[1]: #installing basemap is pretty painful for anaconda #try conda install -c conda-forge basemap #if there is filenotfounderror #try conda install -c conda-forge proj4 import pandas as pd import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.basemap import Basemap import os os.chdir('d:/') # In[2]: #need data with value and coordinates to plot #the iron ore production data of 2015 comes from wikipedia # https://en.wikipedia.org/wiki/List_of_countries_by_iron_ore_production #the coordinates of each country's capital come from someone's personal blog # https://lab.lmnixon.org/4th/worldcapitals.html #note that the capital doesnt necessarily locate at the centre of a country #to make the figure look better, i slightly change the coordinates df=pd.read_csv('iron ore production bubble map.csv') # In[3]: ax=plt.figure(figsize=(50,20)).add_subplot(111) #draw up a world map #fill continents, lakes and country boundaries m = Basemap() m.drawmapboundary(fill_color='white', linewidth=0) m.fillcontinents(color='#c0c0c0',alpha=0.5, lake_color='white') m.drawcountries(linewidth=1,color='#a79c93') size=df['iron ore production']/max(df['iron ore production'])*40000 #this is crucial if we use a different map projection x,y=m(df['longitude'].tolist(),df['latitude'].tolist()) m.scatter(x,y, s=size, linewidths=2, edgecolors="#6c6b74", alpha=0.8,c=df['iron ore production'],cmap='autumn_r') for i in range(len(x)): plt.text(x[i],y[i], '%s '%(df['region'][i]), horizontalalignment='center', verticalalignment='center', size=25) cb=plt.colorbar(ticks=[10000,800000]) cb.ax.set_yticklabels(cb.ax.get_yticklabels(), fontsize=20) cb.ax.set_ylabel('Iron Ore Production 1000 Tonnes per Year',fontsize=20,rotation=270) plt.title('Iron Ore Production by Countries', fontsize=42) plt.show() ================================================ FILE: Ore Money project/iron ore uahusd.csv ================================================ Date,iron ore 62,UAHUSD,RUBUSD,EURUSD,TRYUSD,PLNUSD,CNYUSD,INRUSD 21/10/2013,135.4,0.1222,0.03127,1.3681,0.50494,0.3278,0.16412,0.016232 22/10/2013,135.4,0.1222,0.03155,1.3781,0.5083,0.3308,0.16413,0.016357 23/10/2013,135.4,0.1223,0.0315,1.3776,0.50588,0.3293,0.1644,0.016228 24/10/2013,135,0.1223,0.03155,1.3801,0.50508,0.3301,0.16444,0.016267 25/10/2013,134.5,0.1223,0.03144,1.3802,0.50403,0.3301,0.1644,0.016273 28/10/2013,134,0.1224,0.03133,1.3785,0.50407,0.3297,0.1643,0.016251 29/10/2013,133.9,0.1224,0.03116,1.3745,0.50207,0.3283,0.16422,0.016281 30/10/2013,133.6,0.122,0.03126,1.3736,0.50127,0.3285,0.16409,0.016308 31/10/2013,133.6,0.1221,0.03119,1.3584,0.50079,0.3248,0.16413,0.016094 1/11/2013,134.5,0.1223,0.03086,1.3487,0.49581,0.3212,0.16395,0.016071 4/11/2013,136,0.1219,0.03095,1.3514,0.49603,0.3232,0.16398,0.016131 5/11/2013,136.7,0.1218,0.03072,1.3474,0.49274,0.3219,0.16402,0.016077 6/11/2013,137.6,0.1221,0.0309,1.3513,0.4913,0.3238,0.16408,0.016026 7/11/2013,138.1,0.1221,0.03083,1.3419,0.49128,0.3199,0.16418,0.015916 8/11/2013,138.12,0.1219,0.0306,1.3367,0.49069,0.3199,0.16419,0.015782 11/11/2013,137.62,0.1219,0.03045,1.3407,0.48934,0.3181,0.16414,0.015743 12/11/2013,137.61,0.1217,0.03043,1.3436,0.48679,0.3195,0.16414,0.015633 13/11/2013,137.61,0.122,0.03053,1.3487,0.48926,0.3214,0.16403,0.015809 14/11/2013,137.05,0.1219,0.03062,1.3461,0.49183,0.3211,0.16408,0.015855 15/11/2013,135.99,0.1219,0.03069,1.3496,0.4927,0.3224,0.16413,0.01593 18/11/2013,135.19,0.1222,0.03068,1.3506,0.49458,0.3236,0.16414,0.016082 19/11/2013,134.62,0.1217,0.03054,1.3538,0.4972,0.3237,0.16413,0.016055 20/11/2013,134.4,0.1217,0.03039,1.3439,0.49619,0.3206,0.16419,0.01598 21/11/2013,134.4,0.1216,0.03029,1.3482,0.49599,0.3214,0.1641,0.015877 22/11/2013,134.4,0.1217,0.03053,1.3558,0.49851,0.3232,0.1641,0.016001 25/11/2013,134.84,0.1219,0.03037,1.3517,0.49822,0.322,0.16414,0.015999 26/11/2013,135.14,0.1219,0.03036,1.3572,0.49695,0.3229,0.16413,0.015999 27/11/2013,135.15,0.1215,0.03014,1.3579,0.49368,0.3229,0.16414,0.016002 28/11/2013,135.15,0.1218,0.03015,1.3606,0.49628,0.3243,0.16414,0.016066 29/11/2013,135.96,0.1216,0.03017,1.3591,0.49526,0.3232,0.16416,0.016007 2/12/2013,135.5,0.1214,0.0301,1.3542,0.49061,0.3223,0.16411,0.016048 3/12/2013,135.13,0.1217,0.03006,1.3588,0.48922,0.3233,0.16415,0.016025 4/12/2013,137.03,0.1213,0.03013,1.3593,0.48813,0.3236,0.16417,0.01621 5/12/2013,137.52,0.1217,0.03035,1.3667,0.49094,0.3262,0.16416,0.01623 6/12/2013,136.98,0.1217,0.0305,1.3706,0.49369,0.3275,0.16448,0.016352 9/12/2013,135.96,0.1224,0.03061,1.3739,0.49211,0.3281,0.16467,0.016433 10/12/2013,136,0.1212,0.03055,1.3761,0.49329,0.3293,0.16471,0.016367 11/12/2013,135.99,0.121,0.0305,1.3786,0.48939,0.3296,0.1647,0.016325 12/12/2013,135.82,0.1207,0.03047,1.3753,0.48957,0.3291,0.16469,0.016081 13/12/2013,135.59,0.1209,0.03038,1.3742,0.49044,0.3289,0.16474,0.016095 16/12/2013,135.03,0.1206,0.03038,1.3761,0.4934,0.3296,0.1647,0.0162 17/12/2013,134.01,0.1206,0.03034,1.3768,0.49121,0.3293,0.16471,0.016188 18/12/2013,133.94,0.1206,0.03042,1.3685,0.48596,0.3282,0.16462,0.016115 19/12/2013,133.1,0.1208,0.03031,1.3661,0.48246,0.3285,0.16478,0.016008 20/12/2013,132.8,0.1215,0.03026,1.3673,0.47814,0.329,0.16468,0.016125 23/12/2013,131.97,0.1214,0.03057,1.3696,0.47675,0.3292,0.16474,0.016187 24/12/2013,131.48,0.1223,0.03065,1.368,0.48161,0.3305,0.16471,0.016175 25/12/2013,131.2,0.1223,0.03058,1.3681,0.4773,0.3301,0.16474, 26/12/2013,131.16,0.1217,0.03062,1.3691,0.47007,0.3308,0.16474,0.016152 27/12/2013,131.09,0.1214,0.0307,1.3749,0.46423,0.3315,0.16483,0.016139 30/12/2013,132.19,0.1214,0.03047,1.3801,0.47098,0.3329,0.16496,0.016152 31/12/2013,133.41,0.1214,0.03039,1.3743,0.46557,0.3308,0.16513,0.016165 2/1/2014,134.72,0.1214,0.03021,1.3672,0.46069,0.328,0.16528,0.016046 3/1/2014,134.72,0.1214,0.03014,1.3589,0.45917,0.3261,0.16524,0.016056 6/1/2014,134.13,0.1214,0.03014,1.3629,0.46056,0.3264,0.16515,0.016048 7/1/2014,134.09,0.1215,0.03018,1.3616,0.46145,0.3261,0.16526,0.016102 8/1/2014,134,0.1213,0.0301,1.3576,0.45756,0.325,0.16523,0.016098 9/1/2014,133.93,0.121,0.03013,1.3608,0.4593,0.3259,0.16516,0.01613 10/1/2014,133.9,0.1207,0.03027,1.367,0.46177,0.3297,0.16525,0.016259 13/01/2014,133.2,0.1203,0.03005,1.3671,0.45884,0.3291,0.16545,0.016263 14/01/2014,133,0.1202,0.03003,1.3679,0.45794,0.3302,0.16554,0.016263 15/01/2014,131.7,0.12,0.02994,1.3605,0.45639,0.3272,0.16538,0.016254 16/01/2014,130.7,0.1199,0.02994,1.362,0.45313,0.3269,0.16514,0.016291 17/01/2014,130,0.1195,0.02978,1.3541,0.44771,0.3252,0.16528,0.016226 20/01/2014,129.2,0.1194,0.02957,1.3552,0.44633,0.3258,0.16521,0.016251 21/01/2014,127.4,0.119,0.02943,1.3561,0.44417,0.3256,0.16528,0.016107 22/01/2014,124.9,0.1193,0.02947,1.3547,0.44274,0.3255,0.16523,0.016174 23/01/2014,126.1,0.1185,0.0293,1.3696,0.43618,0.3275,0.16522,0.016087 24/01/2014,126.7,0.1186,0.02902,1.3678,0.42799,0.326,0.16534,0.015943 27/01/2014,126.5,0.1178,0.02891,1.3673,0.43798,0.3253,0.16533,0.015767 28/01/2014,125.6,0.1179,0.02877,1.3671,0.44399,0.3255,0.16526,0.015934 29/01/2014,125.5,0.1179,0.02847,1.3663,0.44224,0.3233,0.16511,0.015886 30/01/2014,125.4,0.1181,0.02859,1.3555,0.44068,0.3203,0.165,0.01601 7/2/2014,125.3,0.117,0.02877,1.3635,0.45095,0.3266,0.16489,0.0161 10/2/2014,124.4,0.1186,0.02877,1.3646,0.45124,0.3265,0.16502,0.016047 11/2/2014,123.4,0.1159,0.02878,1.3638,0.45593,0.3269,0.16501,0.016121 12/2/2014,122.9,0.1151,0.02872,1.3593,0.45608,0.3269,0.16493,0.016161 13/02/2014,122.8,0.1138,0.0285,1.3681,0.45766,0.3289,0.16494,0.016087 14/02/2014,123,0.1138,0.0285,1.3693,0.45767,0.3302,0.16483,0.016167 17/02/2014,123.5,0.1129,0.02838,1.3707,0.45936,0.3308,0.1649,0.016191 18/02/2014,124.1,0.113,0.02819,1.3759,0.45873,0.3317,0.16481,0.016086 19/02/2014,123.9,0.1117,0.02793,1.3733,0.45161,0.3292,0.16457,0.016028 20/02/2014,123,0.1117,0.02796,1.3719,0.45456,0.3292,0.16435,0.016103 21/02/2014,121.5,0.1117,0.02815,1.3746,0.45931,0.3308,0.16417,0.016119 24/02/2014,120.6,0.1091,0.02814,1.3735,0.45428,0.33,0.16399,0.016165 25/02/2014,118.5,0.1028,0.02798,1.3745,0.45198,0.3309,0.16329,0.016146 26/02/2014,117.7,0.0985,0.02774,1.3687,0.44882,0.3274,0.16329,0.016095 27/02/2014,116.9,0.0935,0.02776,1.371,0.45185,0.3297,0.16316,0.016136 28/02/2014,115.8,0.1006,0.02768,1.3802,0.45301,0.3318,0.1627,0.016165 3/3/2014,115.8,0.1026,0.02741,1.3735,0.44784,0.3249,0.1627,0.016075 4/3/2014,114.3,0.1101,0.02774,1.3743,0.45339,0.3285,0.16284,0.016151 5/3/2014,113.3,0.107,0.02774,1.3733,0.45387,0.3281,0.16318,0.016296 6/3/2014,112.3,0.1084,0.02767,1.3861,0.45869,0.3317,0.16343,0.016415 7/3/2014,110.3,0.1083,0.02745,1.3875,0.45356,0.3301,0.16326,0.016338 10/3/2014,105.4,0.1083,0.02752,1.3877,0.45075,0.3294,0.16293,0.016395 11/3/2014,103.6,0.1083,0.02742,1.386,0.44514,0.3281,0.16288,0.016373 12/3/2014,104,0.1067,0.0274,1.3903,0.44798,0.3291,0.16268,0.016397 13/03/2014,105,0.1032,0.02729,1.3868,0.4478,0.3274,0.16299,0.016269 14/03/2014,104.8,0.1031,0.02735,1.3914,0.45189,0.3294,0.1626,0.016321 17/03/2014,105,0.1026,0.02755,1.3922,0.45056,0.3293,0.16183,0.016379 18/03/2014,104.4,0.0998,0.02759,1.3934,0.45079,0.3311,0.1615,0.016389 19/03/2014,103.2,0.0986,0.02765,1.3833,0.44654,0.3284,0.16142,0.016273 20/03/2014,101.9,0.0953,0.02753,1.3779,0.4485,0.3283,0.16057,0.01633 21/03/2014,101.8,0.0948,0.0276,1.3794,0.44778,0.329,0.16063,0.016393 24/03/2014,102.7,0.0928,0.02771,1.3839,0.44707,0.3295,0.16139,0.016494 25/03/2014,104.4,0.0914,0.02819,1.3826,0.45112,0.3299,0.16124,0.016597 26/03/2014,105.2,0.0898,0.02812,1.3781,0.45631,0.3296,0.16101,0.01661 27/03/2014,105.2,0.09,0.02807,1.374,0.45758,0.33,0.16095,0.016615 28/03/2014,106.1,0.0902,0.02798,1.3752,0.45637,0.3297,0.16098,0.0167 31/03/2014,108.1,0.0907,0.02852,1.3769,0.46713,0.3305,0.16084, 1/4/2014,110.1,0.0882,0.02849,1.3793,0.4678,0.3306,0.16111,0.016724 2/4/2014,110,0.0881,0.0282,1.3767,0.46988,0.3304,0.16115,0.016713 3/4/2014,109.9,0.0874,0.02808,1.372,0.46907,0.3293,0.16102,0.016558 4/4/2014,109.8,0.0863,0.02835,1.3705,0.47305,0.3293,0.16103,0.016719 8/4/2014,113,0.0838,0.02799,1.3797,0.47696,0.331,0.16139,0.016635 9/4/2014,113.1,0.0823,0.02811,1.3855,0.47532,0.3328,0.16128,0.016685 10/4/2014,113.1,0.0794,0.02811,1.3886,0.47405,0.3326,0.16097,0.016554 11/4/2014,113,0.0795,0.02805,1.3885,0.47338,0.3322,0.161,0.016575 14/04/2014,113.4,0.0769,0.02781,1.3821,0.47154,0.3306,0.1608,0.016566 15/04/2014,112.8,0.084,0.02758,1.3815,0.46676,0.3298,0.16075,0.016555 16/04/2014,111.8,0.0886,0.02781,1.3816,0.46802,0.3298,0.16073,0.016587 17/04/2014,111.2,0.0897,0.02818,1.3814,0.47021,0.3303,0.16078,0.016568 18/04/2014,108.9,0.0886,0.02809,1.3813,0.46984,0.3305,0.16066,0.016562 21/04/2014,108.8,0.0885,0.028,1.3793,0.46865,0.3301,0.16013,0.016528 22/04/2014,108.7,0.0852,0.02806,1.3805,0.46699,0.3295,0.16033,0.016416 23/04/2014,108.6,0.0866,0.02803,1.3817,0.46492,0.3299,0.16032,0.016355 24/04/2014,108,0.0885,0.02795,1.3831,0.4683,0.3296,0.16004,0.016363 25/04/2014,107.9,0.087,0.02778,1.3834,0.46855,0.3286,0.1599,0.016483 28/04/2014,106.4,0.0866,0.02788,1.3851,0.47044,0.3292,0.15991,0.016509 29/04/2014,104.9,0.0866,0.02807,1.3812,0.47177,0.3293,0.1598,0.01659 30/04/2014,103.9,0.0862,0.02807,1.3867,0.4734,0.3299,0.15974,0.016581 5/5/2014,102.3,0.0859,0.02799,1.3875,0.47613,0.33,0.1601,0.016637 6/5/2014,102.1,0.0847,0.02822,1.3928,0.47851,0.3317,0.16061,0.016662 7/5/2014,100.7,0.086,0.02863,1.391,0.48046,0.3321,0.16038,0.016695 8/5/2014,99.3,0.0858,0.02852,1.384,0.48231,0.3312,0.16056,0.016685 9/5/2014,98.8,0.0859,0.0284,1.3758,0.48164,0.3291,0.16057,0.016711 12/5/2014,98.6,0.0849,0.02855,1.3757,0.48057,0.329,0.16031,0.016788 13/05/2014,98.6,0.0845,0.02865,1.3704,0.48348,0.3273,0.16053,0.016817 14/05/2014,98.9,0.0838,0.02885,1.3715,0.48307,0.3273,0.16053,0.016813 15/05/2014,99,0.0846,0.02876,1.371,0.47656,0.327,0.1605,0.016817 16/05/2014,98.9,0.0836,0.02882,1.3694,0.47633,0.3267,0.16041,0.017081 19/05/2014,97.4,0.0837,0.02892,1.3709,0.47689,0.3273,0.16033,0.017112 20/05/2014,96.7,0.0837,0.02896,1.3702,0.47314,0.3271,0.16033,0.017057 21/05/2014,96.1,0.084,0.02917,1.3687,0.47753,0.3276,0.16042,0.017053 22/05/2014,96,0.0837,0.02915,1.3656,0.48056,0.3282,0.16038,0.017133 23/05/2014,95.2,0.0837,0.0293,1.3629,0.48035,0.3281,0.16038,0.017115 26/05/2014,95.2,0.0839,0.02922,1.3646,0.47993,0.3278,0.16027,0.017038 27/05/2014,95,0.084,0.02905,1.3635,0.4758,0.3274,0.16006,0.016963 28/05/2014,94.3,0.084,0.02893,1.3591,0.47633,0.3274,0.15985,0.016975 29/05/2014,94.4,0.0845,0.02883,1.3602,0.47928,0.3286,0.1603,0.016971 30/05/2014,92.2,0.0848,0.02865,1.3635,0.47686,0.329,0.16006,0.016862 3/6/2014,91.2,0.0837,0.02852,1.3628,0.47234,0.3279,0.15988,0.01686 4/6/2014,91.8,0.0839,0.02856,1.3599,0.47269,0.3293,0.16,0.016872 5/6/2014,91.4,0.0843,0.02883,1.366,0.47703,0.3305,0.15979,0.016935 6/6/2014,91.4,0.085,0.02907,1.3643,0.48112,0.3331,0.15998,0.016958 9/6/2014,90.9,0.0851,0.02911,1.3594,0.47925,0.3313,0.16025,0.016893 10/6/2014,90.9,0.0859,0.02913,1.3547,0.48084,0.3299,0.16066,0.016896 11/6/2014,90.2,0.0865,0.02908,1.3532,0.47247,0.3294,0.16057,0.016838 12/6/2014,88.8,0.0855,0.02909,1.3552,0.47355,0.3293,0.16081,0.016863 13/06/2014,87.8,0.0848,0.02907,1.354,0.47081,0.3287,0.16105,0.016748 16/06/2014,86.1,0.0843,0.02889,1.3574,0.4665,0.3278,0.16077,0.016605 17/06/2014,86,0.0843,0.02872,1.3547,0.46533,0.327,0.1606,0.01659 18/06/2014,86.6,0.0845,0.0291,1.3595,0.47052,0.3293,0.16048,0.016721 19/06/2014,86.2,0.0843,0.02907,1.3608,0.46668,0.3279,0.16055,0.016617 20/06/2014,85.8,0.0842,0.02903,1.36,0.46681,0.3262,0.16067,0.016622 23/06/2014,87.2,0.0844,0.02936,1.3605,0.46778,0.3269,0.16062,0.016648 24/06/2014,87.2,0.0841,0.02958,1.3606,0.46711,0.3277,0.16051,0.016616 25/06/2014,87.8,0.0838,0.02962,1.3629,0.46888,0.3294,0.16038,0.016651 26/06/2014,89.5,0.0841,0.02969,1.3612,0.47026,0.3279,0.16066,0.016619 27/06/2014,90.2,0.0852,0.02963,1.3649,0.47098,0.3287,0.16082,0.016669 30/06/2014,90.4,0.0851,0.02942,1.3692,0.47206,0.3293,0.16117,0.016655 1/7/2014,89.7,0.0846,0.02914,1.3679,0.46981,0.3288,0.16127,0.016688 2/7/2014,89.9,0.0843,0.02917,1.366,0.46946,0.3295,0.16102,0.016789 3/7/2014,90.8,0.0845,0.02917,1.361,0.4698,0.3286,0.161,0.016791 4/7/2014,92.4,0.0852,0.02907,1.3595,0.4688,0.3275,0.1612,0.016729 7/7/2014,92.5,0.0854,0.02902,1.3605,0.46963,0.3284,0.16119,0.016671 8/7/2014,92.6,0.0857,0.0292,1.3612,0.47067,0.3299,0.16125,0.016705 9/7/2014,93.6,0.0853,0.02948,1.3642,0.47258,0.3307,0.16129,0.01676 10/7/2014,93.6,0.0857,0.02941,1.3609,0.47088,0.3284,0.16123,0.016647 11/7/2014,93.5,0.0854,0.02925,1.3608,0.47227,0.3286,0.16118,0.016631 14/07/2014,93.5,0.0853,0.02911,1.3619,0.47256,0.3291,0.16113,0.016643 15/07/2014,94,0.0856,0.02908,1.3568,0.47101,0.328,0.16108,0.016616 16/07/2014,94.8,0.0862,0.0289,1.3525,0.47194,0.3272,0.16119,0.016644 17/07/2014,94.9,0.0854,0.02835,1.3526,0.46702,0.3254,0.16119,0.016484 18/07/2014,94.3,0.0859,0.02843,1.3524,0.47093,0.326,0.16097,0.016574 21/07/2014,93.4,0.0855,0.02842,1.3524,0.4721,0.3262,0.16105,0.016585 22/07/2014,92.6,0.0866,0.0286,1.3466,0.47462,0.3254,0.16116,0.016633 23/07/2014,92.5,0.0856,0.02866,1.3464,0.47829,0.3256,0.16133,0.016675 24/07/2014,92.1,0.0853,0.02851,1.3464,0.47812,0.3253,0.16141,0.016645 25/07/2014,91.3,0.0841,0.02847,1.343,0.47748,0.3239,0.1615,0.016649 28/07/2014,92.1,0.0823,0.02811,1.344,0.47638,0.3243,0.16163,0.016644 29/07/2014,92.3,0.0825,0.02797,1.3409,0.47248,0.3229,0.16179,0.016599 30/07/2014,92.3,0.0818,0.02811,1.3397,0.46881,0.3223,0.16204,0.016565 31/07/2014,92.3,0.0815,0.02799,1.339,0.46692,0.3205,0.16198,0.016414 1/8/2014,92.7,0.0821,0.02797,1.3427,0.46842,0.3209,0.16185,0.016449 4/8/2014,92.6,0.0809,0.02786,1.3422,0.46896,0.3216,0.16183,0.016419 5/8/2014,93.1,0.0818,0.02771,1.3376,0.46603,0.3194,0.16206,0.016369 6/8/2014,93.3,0.0809,0.02763,1.3383,0.46326,0.3185,0.16226,0.016331 7/8/2014,93.6,0.08,0.02755,1.3364,0.46148,0.317,0.16229,0.01626 8/8/2014,93.4,0.0806,0.02765,1.341,0.46635,0.3193,0.16244,0.016361 11/8/2014,93.1,0.078,0.02784,1.3385,0.46507,0.319,0.1625,0.016359 12/8/2014,92.1,0.0765,0.02764,1.3369,0.46271,0.3183,0.16241,0.016328 13/08/2014,91.6,0.0761,0.02778,1.3364,0.46368,0.3191,0.16247,0.016363 14/08/2014,90.4,0.0772,0.02776,1.3365,0.46468,0.3198,0.16254,0.01643 15/08/2014,90.4,0.0762,0.02769,1.3401,0.46149,0.3185,0.16249,0.016413 18/08/2014,90.1,0.0768,0.02772,1.3364,0.4622,0.3195,0.16277,0.016453 19/08/2014,89.9,0.0763,0.02765,1.332,0.46249,0.3184,0.16282,0.016465 20/08/2014,89,0.0753,0.02754,1.3259,0.45778,0.3165,0.16283,0.016476 21/08/2014,88.4,0.0749,0.02777,1.3281,0.45916,0.3172,0.16255,0.016513 22/08/2014,87.7,0.0739,0.02767,1.3242,0.45983,0.3159,0.16244,0.016549 25/08/2014,87.6,0.0738,0.02766,1.3192,0.45916,0.3152,0.16246,0.016523 26/08/2014,87.3,0.0738,0.02766,1.3167,0.46183,0.3145,0.16252,0.016531 27/08/2014,86.9,0.0736,0.02764,1.3193,0.46392,0.3141,0.16275,0.016573 28/08/2014,86.2,0.0741,0.0272,1.3182,0.46338,0.3122,0.16279,0.016491 29/08/2014,86.2,0.0758,0.02699,1.3132,0.46248,0.3118,0.16269,0.016498 1/9/2014,86.3,0.0798,0.02679,1.3128,0.46289,0.3123,0.16281,0.016521 2/9/2014,85.8,0.0804,0.02671,1.3133,0.4603,0.3121,0.16263,0.016498 3/9/2014,85.2,0.081,0.02714,1.315,0.46355,0.3135,0.16283,0.016547 4/9/2014,84.7,0.0788,0.02704,1.2944,0.46228,0.3088,0.16293,0.016531 5/9/2014,82.9,0.0781,0.02707,1.2951,0.46316,0.31,0.16287,0.0166 9/9/2014,82.4,0.0792,0.02696,1.2937,0.45525,0.3078,0.16294,0.016431 10/9/2014,81.7,0.0769,0.02681,1.2917,0.45612,0.3079,0.16315,0.016454 11/9/2014,81.7,0.0771,0.02663,1.2925,0.45434,0.3079,0.16312,0.016409 12/9/2014,81.6,0.0778,0.02647,1.2963,0.44974,0.3083,0.16309,0.016382 15/09/2014,83.1,0.0772,0.02607,1.294,0.45149,0.3084,0.16282,0.016358 16/09/2014,83.5,0.0776,0.0261,1.296,0.45388,0.3095,0.16272,0.016399 17/09/2014,83.5,0.0786,0.02598,1.2865,0.44968,0.3072,0.16285,0.016382 18/09/2014,83.4,0.0778,0.02602,1.2923,0.44933,0.3076,0.16279,0.016456 19/09/2014,82.9,0.0711,0.02602,1.2829,0.44751,0.3066,0.16282,0.016416 22/09/2014,82.2,0.0706,0.02582,1.2849,0.44625,0.3072,0.16286,0.016385 23/09/2014,81.7,0.0763,0.02591,1.2847,0.44656,0.3078,0.16285,0.016377 24/09/2014,81.5,0.0755,0.02618,1.278,0.44713,0.3062,0.16298,0.016442 25/09/2014,81.4,0.0773,0.02599,1.2751,0.44227,0.3049,0.16298,0.016262 26/09/2014,81.6,0.0776,0.02554,1.2684,0.44218,0.3032,0.1632,0.016292 29/09/2014,80.9,0.0772,0.02534,1.2685,0.43891,0.3033,0.16261,0.016216 30/09/2014,80.8,0.0772,0.02526,1.2631,0.43896,0.302,0.1629,0.016151 8/10/2014,80.8,0.0774,0.02502,1.2734,0.44207,0.3049,0.16282,0.016387 9/10/2014,81.4,0.0772,0.02493,1.2691,0.44063,0.3034,0.16312,0.016362 10/10/2014,81.4,0.0772,0.02479,1.2628,0.43698,0.3017,0.16313,0.016325 13/10/2014,83.2,0.0775,0.02469,1.2752,0.44068,0.3042,0.16328,0.016387 14/10/2014,83.9,0.0775,0.02444,1.2658,0.43993,0.3011,0.16323,0.016292 15/10/2014,83.1,0.0776,0.02476,1.2838,0.44072,0.3041,0.16329,0.016235 16/10/2014,82.4,0.0775,0.02448,1.2809,0.442,0.3028,0.16332,0.016225 17/10/2014,82.2,0.0776,0.02455,1.2761,0.44536,0.3025,0.16328,0.016315 20/10/2014,82.2,0.0769,0.02437,1.28,0.44563,0.3031,0.16329,0.016352 21/10/2014,81.6,0.0777,0.02442,1.2716,0.44549,0.3013,0.16335,0.016367 22/10/2014,81.6,0.0761,0.02417,1.2649,0.44524,0.2988,0.1635,0.016341 23/10/2014,81.1,0.0769,0.02398,1.2646,0.4472,0.2991,0.16341, 24/10/2014,80.8,0.0769,0.02387,1.2671,0.44826,0.3007,0.16345,0.016364 27/10/2014,80.3,0.0769,0.02367,1.2698,0.44849,0.3005,0.16346,0.016304 28/10/2014,79.9,0.077,0.02356,1.2734,0.45328,0.3021,0.16355,0.016348 29/10/2014,79.2,0.077,0.02316,1.2632,0.45135,0.299,0.16354,0.016262 30/10/2014,78.6,0.0769,0.02405,1.2613,0.4549,0.2995,0.16355,0.016303 31/10/2014,77.5,0.0769,0.02325,1.2525,0.44996,0.2964,0.16359,0.016284 3/11/2014,76.9,0.0769,0.02294,1.2482,0.44765,0.2955,0.16333,0.016277 4/11/2014,76.4,0.0769,0.02295,1.2546,0.45017,0.2968,0.16353,0.016308 5/11/2014,76.1,0.0738,0.02228,1.2486,0.44553,0.2953,0.16357,0.016286 6/11/2014,75.7,0.0714,0.02137,1.2375,0.44178,0.2932,0.16371,0.01625 7/11/2014,74.9,0.0689,0.02142,1.2455,0.44276,0.2947,0.16331,0.016288 10/11/2014,74.9,0.0673,0.0218,1.2421,0.4426,0.2944,0.1634,0.016254 11/11/2014,74.8,0.0632,0.02158,1.2475,0.44313,0.2957,0.16323,0.016263 12/11/2014,74.8,0.0631,0.02218,1.2438,0.4442,0.2949,0.16325,0.016288 13/11/2014,74.8,0.0644,0.02138,1.2477,0.44602,0.2944,0.16328,0.016265 14/11/2014,74.8,0.0644,0.02119,1.2525,0.44839,0.2961,0.16312,0.016219 17/11/2014,74.6,0.0644,0.02119,1.245,0.44819,0.2949,0.16325,0.016183 18/11/2014,73,0.0644,0.02132,1.2536,0.45023,0.2973,0.16338,0.016196 19/11/2014,72.5,0.0665,0.02134,1.2554,0.44799,0.2975,0.16349,0.016111 20/11/2014,71.2,0.0658,0.02167,1.2539,0.45061,0.2976,0.1633,0.016151 21/11/2014,71.2,0.0658,0.02188,1.2391,0.45009,0.295,0.1633,0.016209 24/11/2014,71,0.0662,0.02223,1.2442,0.44843,0.2965,0.16282,0.016162 25/11/2014,70.1,0.0663,0.02161,1.2474,0.45075,0.2987,0.16296,0.016175 26/11/2014,69.4,0.0662,0.02109,1.2506,0.45236,0.2993,0.16286,0.016185 27/11/2014,69.4,0.0666,0.02056,1.2467,0.45308,0.2984,0.16289,0.016169 28/11/2014,70.4,0.066,0.01983,1.2452,0.45042,0.2976,0.16283,0.016065 1/12/2014,70.7,0.0662,0.01954,1.247,0.4516,0.2985,0.16255,0.01615 2/12/2014,70.7,0.0654,0.01856,1.2383,0.44826,0.2974,0.16265,0.016173 3/12/2014,69.9,0.0656,0.01878,1.2311,0.44642,0.2964,0.16261,0.016143 4/12/2014,70.6,0.0652,0.01839,1.2379,0.44769,0.2978,0.16255,0.016232 5/12/2014,71,0.0647,0.01898,1.2283,0.44235,0.2954,0.16259,0.016132 8/12/2014,71,0.0642,0.01861,1.2317,0.44069,0.296,0.16199,0.016171 9/12/2014,70.1,0.0645,0.0185,1.2374,0.44115,0.2976,0.16164,0.016116 10/12/2014,70.1,0.0637,0.01822,1.2448,0.44138,0.298,0.16193,0.016065 11/12/2014,70,0.0636,0.01772,1.2411,0.43898,0.2974,0.1616,0.015991 12/12/2014,69.5,0.0635,0.01718,1.2462,0.43505,0.2978,0.16168,0.015966 15/12/2014,69.5,0.0639,0.01528,1.2437,0.42098,0.2971,0.16156,0.015723 16/12/2014,69,0.0633,0.01465,1.2511,0.42351,0.2968,0.16156,0.01567 17/12/2014,68.5,0.0632,0.01651,1.2342,0.42764,0.2916,0.16142,0.015788 18/12/2014,67.7,0.0632,0.01614,1.2286,0.43048,0.2891,0.16089,0.015872 19/12/2014,67.6,0.0632,0.0168,1.2229,0.43224,0.2868,0.16073,0.015783 22/12/2014,67.6,0.0624,0.01792,1.223,0.43196,0.287,0.16074,0.015806 23/12/2014,66.9,0.0636,0.0183,1.2172,0.43079,0.283,0.16065,0.015762 24/12/2014,67,0.0634,0.01876,1.2196,0.43178,0.2808,0.16082,0.015742 25/12/2014,66.4,0.0632,0.01889,1.2225,0.43261,0.2817,0.16114, 26/12/2014,66.3,0.0633,0.01852,1.2183,0.43148,0.2777,0.16058,0.015708 29/12/2014,66.8,0.0632,0.01693,1.2152,0.43132,0.2819,0.16076,0.015707 30/12/2014,69.3,0.0633,0.01803,1.2156,0.42953,0.2842,0.16124,0.015789 31/12/2014,69.3,0.0633,0.01723,1.2098,0.42873,0.2823,0.16113,0.015813 5/1/2015,69.8,0.0632,0.01652,1.1933,0.42909,0.2782,0.16072,0.015755 6/1/2015,70.6,0.0632,0.01584,1.189,0.43056,0.2753,0.16088,0.015759 7/1/2015,70.6,0.0632,0.01594,1.1839,0.43142,0.2757,0.16099,0.015833 8/1/2015,70.6,0.0633,0.01661,1.1793,0.43501,0.2754,0.16099,0.016007 9/1/2015,70.6,0.0628,0.01614,1.1842,0.43567,0.2776,0.16101,0.016109 12/1/2015,70.2,0.0628,0.01584,1.1834,0.43757,0.2768,0.16118,0.016111 13/01/2015,69.8,0.0632,0.01529,1.1773,0.43744,0.2748,0.16142,0.016136 14/01/2015,69.4,0.0627,0.01547,1.1789,0.43834,0.2769,0.16142,0.016082 15/01/2015,69.4,0.0632,0.01533,1.1633,0.43262,0.2696,0.16167,0.016149 16/01/2015,68.8,0.0643,0.01532,1.1567,0.42951,0.2687,0.16114,0.016228 19/01/2015,67.9,0.0631,0.0154,1.1606,0.42762,0.2681,0.16075,0.016212 20/01/2015,67.9,0.0632,0.01533,1.155,0.42633,0.2667,0.16085,0.016199 21/01/2015,67.6,0.0633,0.01534,1.161,0.42541,0.27,0.16108,0.016251 22/01/2015,66.9,0.0632,0.01557,1.1366,0.43005,0.2671,0.16118,0.016288 23/01/2015,65.9,0.0632,0.01545,1.1204,0.42547,0.2664,0.16047,0.016277 26/01/2015,65.5,0.0631,0.01509,1.1238,0.42474,0.2666,0.15994,0.01628 27/01/2015,64.7,0.0627,0.01477,1.1381,0.42294,0.2684,0.16025,0.016272 28/01/2015,64.2,0.0628,0.01475,1.1287,0.41895,0.2658,0.1601,0.016295 29/01/2015,64.2,0.0628,0.01453,1.132,0.41387,0.2686,0.16003,0.016181 30/01/2015,64.2,0.0617,0.01442,1.1291,0.40928,0.2696,0.15989,0.016096 2/2/2015,63.8,0.0617,0.01464,1.1341,0.41128,0.2706,0.15978,0.016208 3/2/2015,63.8,0.0614,0.01534,1.1481,0.41641,0.2751,0.15974,0.016232 4/2/2015,64,0.0597,0.01468,1.1345,0.40537,0.2719,0.16006,0.016173 5/2/2015,63.9,0.0411,0.01502,1.1477,0.41039,0.2754,0.15996,0.016201 6/2/2015,64,0.0396,0.01501,1.1316,0.4039,0.2722,0.16014,0.016129 9/2/2015,64,0.04,0.01521,1.1325,0.40372,0.2707,0.15999,0.016093 10/2/2015,63.7,0.039,0.01528,1.1321,0.40059,0.2695,0.16025,0.016044 11/2/2015,64,0.0385,0.01533,1.1336,0.39977,0.2693,0.16017,0.01603 12/2/2015,64,0.0375,0.01532,1.1403,0.40539,0.2737,0.1601,0.01609 13/02/2015,64.8,0.0383,0.01595,1.1394,0.407,0.272,0.16014,0.016107 16/02/2015,64.7,0.0379,0.01583,1.1355,0.40708,0.272,0.16002,0.016079 17/02/2015,64.6,0.0379,0.016,1.1411,0.40777,0.2723,0.15975,0.016085 25/02/2015,64.6,0.0406,0.01629,1.1361,0.40191,0.2732,0.15975,0.016165 26/02/2015,64.3,0.0297,0.01637,1.1198,0.39888,0.2698,0.15979,0.016197 27/02/2015,64.2,0.0367,0.01586,1.1196,0.39875,0.2697,0.15958,0.016235 2/3/2015,64.1,0.0378,0.01601,1.1184,0.39727,0.2689,0.1594,0.016165 3/3/2015,63.7,0.0413,0.01616,1.1176,0.39434,0.2683,0.15931,0.016173 4/3/2015,63.5,0.0444,0.01616,1.1078,0.38989,0.2669,0.15954,0.016049 5/3/2015,62.1,0.0426,0.0164,1.103,0.38353,0.2661,0.15968,0.016026 6/3/2015,62.1,0.044,0.01657,1.0844,0.38105,0.2625,0.15963,0.015926 9/3/2015,61.7,0.0428,0.01652,1.0852,0.38441,0.2637,0.15972,0.015966 10/3/2015,61,0.0463,0.01607,1.0698,0.37893,0.2571,0.15974,0.015913 11/3/2015,60.3,0.0455,0.01628,1.0547,0.38312,0.2558,0.1597,0.015929 12/3/2015,60.3,0.0463,0.01636,1.0635,0.3869,0.2568,0.15962,0.016004 13/03/2015,60.4,0.0462,0.0161,1.0496,0.37882,0.2529,0.15976,0.015853 16/03/2015,60.4,0.0457,0.01605,1.0568,0.38073,0.2559,0.15969,0.015929 17/03/2015,60.3,0.0447,0.01629,1.0597,0.38298,0.2562,0.16,0.015966 18/03/2015,60,0.0427,0.01689,1.0864,0.38906,0.2629,0.16052,0.016074 19/03/2015,59.6,0.0432,0.01666,1.066,0.3843,0.258,0.16144,0.016004 20/03/2015,58.6,0.0453,0.01686,1.0821,0.38853,0.2617,0.16117,0.01605 23/03/2015,58.5,0.0442,0.01703,1.0946,0.39349,0.2665,0.1609,0.016087 24/03/2015,57.7,0.0431,0.01731,1.0924,0.39185,0.267,0.16111,0.016038 25/03/2015,57.6,0.0449,0.01744,1.097,0.38653,0.2685,0.16092,0.016021 26/03/2015,57.3,0.0427,0.01745,1.0884,0.38442,0.2665,0.16105,0.015892 27/03/2015,56.6,0.0427,0.01729,1.0889,0.3831,0.2657,0.16086,0.015985 30/03/2015,55.9,0.0424,0.01736,1.0833,0.38337,0.2651,0.1611,0.015998 31/03/2015,54.8,0.0427,0.01718,1.0731,0.38506,0.2632,0.16129,0.016048 1/4/2015,54,0.0418,0.01736,1.0763,0.38489,0.2652,0.16141, 2/4/2015,51.8,0.0426,0.01771,1.088,0.38674,0.2672,0.16128, 3/4/2015,50.6,0.0441,0.01769,1.0969,0.38877,0.2705,0.16269,0.016138 7/4/2015,50.6,0.0421,0.01817,1.0814,0.38431,0.2676,0.16139,0.016052 8/4/2015,50.5,0.0425,0.01864,1.0781,0.38479,0.2691,0.16122,0.016074 9/4/2015,50.5,0.0429,0.01928,1.0659,0.38168,0.2647,0.16124,0.016049 10/4/2015,50.5,0.0431,0.01866,1.0604,0.3804,0.2635,0.16106,0.016058 13/04/2015,50.4,0.0444,0.01918,1.0567,0.37456,0.2637,0.16084,0.016019 14/04/2015,52,0.0455,0.01962,1.0655,0.37189,0.2654,0.16099,0.016058 15/04/2015,52.1,0.0446,0.02015,1.0684,0.37045,0.2657,0.16118,0.01603 16/04/2015,52.2,0.0478,0.02008,1.0761,0.37332,0.2673,0.16131,0.016046 17/04/2015,52.2,0.0477,0.01925,1.0806,0.3734,0.2684,0.16138,0.01599 20/04/2015,52.1,0.0438,0.01875,1.0738,0.37058,0.2691,0.16131,0.015833 21/04/2015,52.1,0.044,0.0186,1.0736,0.37238,0.2693,0.16126,0.015906 22/04/2015,53.6,0.0443,0.0192,1.0725,0.3688,0.2689,0.16143,0.015875 23/04/2015,54.2,0.0444,0.0197,1.0824,0.37016,0.2705,0.16134,0.015804 24/04/2015,56.5,0.0436,0.01965,1.0873,0.36839,0.2695,0.16146,0.015678 27/04/2015,57.8,0.0436,0.01928,1.0891,0.37379,0.273,0.16085,0.015802 28/04/2015,59.3,0.0442,0.01947,1.0981,0.37614,0.275,0.1612,0.015859 29/04/2015,57.9,0.0483,0.0196,1.1128,0.3752,0.2774,0.16138,0.015757 30/04/2015,57.9,0.0471,0.01937,1.1224,0.37423,0.2775,0.16127,0.01574 4/5/2015,57.8,0.0471,0.01919,1.1146,0.36853,0.2767,0.16105,0.015718 5/5/2015,58.5,0.0479,0.01979,1.1185,0.36976,0.2776,0.16109,0.015785 6/5/2015,59.3,0.0476,0.01973,1.1347,0.37145,0.2805,0.16126,0.015727 7/5/2015,59.2,0.0487,0.01991,1.1267,0.37244,0.2785,0.16114,0.015589 8/5/2015,58.6,0.0474,0.01959,1.1199,0.37099,0.2769,0.16113,0.015704 11/5/2015,59.3,0.0474,0.0195,1.1155,0.3713,0.2733,0.16107,0.015607 12/5/2015,60.7,0.0478,0.02002,1.1213,0.37546,0.2734,0.16106,0.015566 13/05/2015,60.5,0.0483,0.02028,1.1354,0.38028,0.2772,0.16124,0.01562 14/05/2015,59.4,0.0488,0.02,1.141,0.38597,0.2805,0.16125,0.015764 15/05/2015,59.3,0.0476,0.0202,1.1451,0.38818,0.2835,0.16115,0.015763 18/05/2015,59.3,0.0463,0.02035,1.1315,0.38749,0.2776,0.16117,0.015689 19/05/2015,59.3,0.0474,0.02018,1.115,0.38555,0.2752,0.16113,0.015683 20/05/2015,58.8,0.0483,0.02011,1.1094,0.38782,0.2721,0.16125,0.015723 21/05/2015,58.9,0.0482,0.02001,1.1112,0.38633,0.2712,0.16135,0.015721 22/05/2015,59.1,0.0482,0.02,1.1013,0.38476,0.268,0.16136,0.015738 25/05/2015,59.6,0.0485,0.02002,1.0978,0.38234,0.2674,0.16124,0.015723 26/05/2015,60.8,0.0464,0.01964,1.0873,0.37857,0.2621,0.16118,0.015632 27/05/2015,61.5,0.0474,0.01932,1.0904,0.37847,0.2642,0.16131,0.015646 28/05/2015,61.5,0.0477,0.01899,1.0949,0.37671,0.2643,0.16119,0.01568 29/05/2015,61.1,0.0475,0.01911,1.0986,0.3755,0.2673,0.16133,0.015677 1/6/2015,61.8,0.0475,0.01867,1.0927,0.37257,0.2655,0.16127,0.015723 2/6/2015,61.8,0.0475,0.01894,1.1151,0.37393,0.2707,0.16135,0.015702 3/6/2015,62.6,0.0478,0.01841,1.1275,0.37234,0.2709,0.16133,0.015622 4/6/2015,63.3,0.0475,0.01774,1.1238,0.37488,0.2695,0.16125,0.015631 5/6/2015,63.4,0.0475,0.01778,1.1114,0.37564,0.2672,0.16125,0.015594 8/6/2015,63.3,0.0473,0.01792,1.1291,0.36343,0.2705,0.16116,0.015639 9/6/2015,63.3,0.0472,0.01804,1.1283,0.36323,0.2701,0.16117,0.015619 10/6/2015,64.1,0.0474,0.01842,1.1324,0.3655,0.2734,0.16112,0.015679 11/6/2015,64.8,0.0476,0.01828,1.1258,0.37003,0.2724,0.16108,0.015633 12/6/2015,64.8,0.0475,0.01812,1.1266,0.36854,0.272,0.16111,0.015595 15/06/2015,64.8,0.0466,0.01834,1.1283,0.36553,0.2716,0.16107,0.015604 16/06/2015,64.1,0.046,0.01856,1.1248,0.36578,0.2714,0.16105,0.015573 17/06/2015,63.3,0.046,0.01864,1.1337,0.36951,0.2729,0.16104,0.015646 18/06/2015,62.6,0.0473,0.01871,1.1359,0.3686,0.2723,0.16106,0.01571 19/06/2015,61.8,0.0461,0.01848,1.1352,0.37104,0.2716,0.16103,0.015747 23/06/2015,62.3,0.0465,0.01858,1.1167,0.37334,0.2683,0.16109,0.015722 24/06/2015,62.8,0.0474,0.01836,1.1205,0.37348,0.2686,0.16114,0.015742 25/06/2015,62.8,0.0476,0.01827,1.1205,0.37663,0.2686,0.16106,0.015735 26/06/2015,62.3,0.0477,0.01825,1.1167,0.3752,0.2677,0.16105,0.01576 29/06/2015,61.5,0.0474,0.01796,1.1236,0.37003,0.2678,0.16107,0.015698 30/06/2015,61.5,0.0476,0.01807,1.1147,0.37295,0.2658,0.16108,0.015722 1/7/2015,60.8,0.0476,0.01791,1.1053,0.37154,0.2639,0.16128,0.015734 2/7/2015,60,0.0476,0.01802,1.1084,0.37245,0.2644,0.1612,0.015796 3/7/2015,59.3,0.0473,0.01787,1.1114,0.37182,0.265,0.16117,0.015769 6/7/2015,57.7,0.0471,0.01759,1.1056,0.37338,0.263,0.16107,0.015807 7/7/2015,55.5,0.0464,0.01764,1.1011,0.3724,0.2617,0.1613,0.015753 8/7/2015,53.3,0.0463,0.01741,1.1077,0.37197,0.2614,0.16106,0.015758 9/7/2015,54,0.0456,0.0175,1.1036,0.37332,0.2618,0.16098,0.015792 10/7/2015,54,0.0456,0.01775,1.1162,0.37499,0.2668,0.16099,0.015785 13/07/2015,54,0.045,0.01768,1.1002,0.37794,0.2659,0.1611,0.015761 14/07/2015,53.6,0.045,0.01773,1.1009,0.37997,0.2666,0.16105,0.015803 15/07/2015,53.3,0.0446,0.01758,1.095,0.37795,0.2652,0.16106,0.015746 16/07/2015,53.3,0.0453,0.01756,1.0875,0.37645,0.2645,0.16099,0.015753 17/07/2015,53.3,0.0458,0.01755,1.083,0.37699,0.2637,0.161,0.015755 20/07/2015,54,0.0439,0.01754,1.0825,0.37062,0.2625,0.161,0.015713 21/07/2015,55.5,0.0453,0.01755,1.0935,0.37249,0.2646,0.161,0.015728 22/07/2015,53.3,0.0453,0.01741,1.0929,0.36941,0.2654,0.16108,0.01573 23/07/2015,52.5,0.045,0.01731,1.0984,0.3657,0.2665,0.16094,0.015645 24/07/2015,52.5,0.0455,0.01711,1.0984,0.36534,0.2648,0.16107,0.015593 27/07/2015,52.2,0.0452,0.01668,1.1088,0.36079,0.2691,0.16106,0.015576 28/07/2015,52.9,0.0447,0.01669,1.106,0.3623,0.2686,0.16106,0.015673 29/07/2015,53.7,0.0454,0.01705,1.0984,0.36149,0.266,0.1613,0.015667 30/07/2015,55.2,0.0474,0.01672,1.0932,0.35932,0.2638,0.16104,0.01559 31/07/2015,54.9,0.0471,0.0162,1.0984,0.36095,0.2652,0.16109,0.015611 3/8/2015,56.6,0.0452,0.01574,1.095,0.35962,0.2642,0.16105,0.015582 4/8/2015,55.9,0.0464,0.01587,1.0881,0.3593,0.2602,0.16097,0.015674 5/8/2015,57.3,0.0463,0.01575,1.0906,0.35887,0.2612,0.161,0.015701 6/8/2015,58.1,0.047,0.01551,1.0925,0.36026,0.2608,0.16103,0.015693 7/8/2015,58.1,0.0473,0.01562,1.0967,0.35962,0.2621,0.16106,0.015679 10/8/2015,57.6,0.0466,0.01588,1.1019,0.35973,0.2624,0.16102,0.01568 11/8/2015,57.3,0.0463,0.01556,1.1042,0.3597,0.2633,0.15809,0.015544 12/8/2015,56.3,0.0468,0.01557,1.1159,0.36003,0.2666,0.15659,0.015398 13/08/2015,56.4,0.046,0.01546,1.115,0.35469,0.2668,0.15626,0.015335 14/08/2015,57.2,0.0454,0.01541,1.1109,0.35307,0.2657,0.15648,0.015365 17/08/2015,56.5,0.0448,0.01529,1.1078,0.34866,0.2659,0.15635,0.015288 18/08/2015,56.2,0.0469,0.01518,1.1024,0.34542,0.2648,0.1564,0.015262 19/08/2015,55.5,0.0466,0.01502,1.112,0.34183,0.2663,0.15631,0.015369 20/08/2015,55.5,0.0451,0.0147,1.1242,0.34294,0.2683,0.15654,0.015283 21/08/2015,55.5,0.0454,0.01448,1.1386,0.34258,0.2692,0.15657,0.015101 24/08/2015,54.7,0.0451,0.01411,1.1619,0.33985,0.2728,0.15615,0.014921 25/08/2015,54.6,0.0443,0.01448,1.1517,0.34008,0.2707,0.15595,0.015077 26/08/2015,54.6,0.0459,0.01451,1.1314,0.34095,0.2673,0.15597,0.015149 27/08/2015,54.5,0.047,0.01512,1.1246,0.34374,0.2657,0.15616,0.015159 28/08/2015,56.2,0.0472,0.01528,1.1185,0.34201,0.2654,0.15656,0.015117 31/08/2015,56.3,0.0449,0.01559,1.1211,0.3431,0.2649,0.15684,0.015057 1/9/2015,57,0.0458,0.01498,1.1315,0.34122,0.2661,0.15713,0.015064 2/9/2015,57,0.0452,0.01492,1.1227,0.33998,0.2649,0.15734,0.015105 7/9/2015,57.9,0.0455,0.01447,1.117,0.32983,0.2637,0.15702,0.01495 8/9/2015,58.7,0.045,0.0147,1.1203,0.33219,0.265,0.15705,0.015086 9/9/2015,59.4,0.0453,0.01461,1.1207,0.32937,0.2659,0.1568,0.015011 10/9/2015,60.1,0.0466,0.01476,1.128,0.33088,0.2678,0.15656,0.015088 11/9/2015,60.1,0.0459,0.01475,1.1338,0.32826,0.2694,0.15688,0.015096 14/09/2015,60.1,0.0455,0.01477,1.1317,0.32722,0.2689,0.15702,0.015083 15/09/2015,59.3,0.0454,0.01497,1.1269,0.32998,0.2682,0.15701,0.015049 16/09/2015,58.6,0.046,0.01527,1.129,0.33352,0.2684,0.15695,0.015094 17/09/2015,58.6,0.0465,0.01528,1.1435,0.332,0.2718,0.15709,0.015135 18/09/2015,58.7,0.0459,0.01504,1.1298,0.3328,0.2689,0.15714,0.01518 21/09/2015,58.6,0.0461,0.01508,1.119,0.33262,0.2673,0.15696,0.015221 22/09/2015,58.6,0.046,0.01515,1.112,0.33041,0.2645,0.15689,0.015175 23/09/2015,57.8,0.0472,0.01508,1.1186,0.32912,0.2649,0.15665,0.015086 24/09/2015,57.8,0.0467,0.01513,1.123,0.32887,0.2661,0.15673,0.015102 25/09/2015,57.8,0.0464,0.01527,1.1195,0.32874,0.265,0.15685,0.015114 28/09/2015,57.8,0.0465,0.01505,1.1244,0.327,0.265,0.15709,0.015063 29/09/2015,57.4,0.0466,0.0152,1.1249,0.32926,0.2656,0.15718,0.015167 30/09/2015,57.2,0.0472,0.01529,1.1177,0.33046,0.2632,0.15732,0.015253 8/10/2015,57.2,0.047,0.01628,1.1276,0.34558,0.267,0.15741,0.015428 9/10/2015,57.7,0.0458,0.01618,1.1358,0.34344,0.269,0.15761,0.015437 12/10/2015,57.9,0.0461,0.01606,1.1358,0.34165,0.2688,0.15816,0.015449 13/10/2015,57.7,0.0465,0.01586,1.1379,0.338,0.2689,0.15766,0.01536 14/10/2015,56.9,0.0465,0.01597,1.1474,0.34324,0.2712,0.15755,0.01543 15/10/2015,56.2,0.046,0.01628,1.1386,0.34717,0.2689,0.15757,0.015437 16/10/2015,55.8,0.047,0.01632,1.1348,0.34567,0.2679,0.15741,0.015454 19/10/2015,55.8,0.0463,0.01604,1.1327,0.34415,0.2667,0.15726,0.015404 20/10/2015,55.5,0.045,0.01612,1.1346,0.34469,0.2663,0.15753,0.015379 21/10/2015,54.1,0.0449,0.01597,1.1339,0.34527,0.2642,0.15748,0.015353 22/10/2015,53.7,0.0447,0.01596,1.1109,0.34813,0.2613,0.15733,0.015418 23/10/2015,53.5,0.044,0.01604,1.1018,0.3439,0.2592,0.15739,0.015379 26/10/2015,53.5,0.0441,0.01586,1.1058,0.34598,0.2586,0.15735,0.015403 27/10/2015,52.7,0.0437,0.01528,1.1051,0.34441,0.2579,0.1574,0.015358 28/10/2015,51.9,0.0435,0.01564,1.0923,0.34184,0.255,0.1572,0.015344 29/10/2015,51,0.0428,0.01553,1.0977,0.34037,0.2565,0.15737,0.015284 30/10/2015,50.6,0.0436,0.01561,1.1006,0.34305,0.259,0.15833,0.015285 2/11/2015,50.1,0.0434,0.01571,1.1016,0.35413,0.2586,0.15785,0.015252 3/11/2015,48.7,0.043,0.01598,1.0964,0.35343,0.2579,0.15779,0.01525 4/11/2015,47.9,0.0434,0.01583,1.0866,0.34929,0.256,0.15784,0.015241 5/11/2015,47.9,0.044,0.01579,1.0884,0.34955,0.256,0.1576,0.015177 6/11/2015,47.2,0.0445,0.0155,1.0741,0.34268,0.2515,0.15746,0.015133 9/11/2015,46.6,0.0439,0.01548,1.0752,0.34236,0.2526,0.15715,0.015054 10/11/2015,46.6,0.0442,0.0155,1.0724,0.34293,0.2531,0.15717,0.015101 11/11/2015,46.6,0.0437,0.01528,1.0743,0.34792,0.2549,0.15701, 12/11/2015,46.5,0.0435,0.01497,1.0814,0.34904,0.2554,0.15701,0.015138 13/11/2015,46.5,0.0432,0.01498,1.0773,0.34957,0.2538,0.15689,0.015129 16/11/2015,46.6,0.0428,0.01531,1.0686,0.34687,0.2518,0.15695,0.015164 17/11/2015,46.6,0.0428,0.01534,1.0642,0.34861,0.2507,0.15675,0.015148 18/11/2015,45.7,0.042,0.01543,1.066,0.34936,0.251,0.15662,0.015149 19/11/2015,45.3,0.0421,0.0155,1.0734,0.35173,0.2524,0.15669,0.015128 20/11/2015,45,0.0415,0.01546,1.0646,0.35349,0.2512,0.15653,0.015127 23/11/2015,45,0.0418,0.01519,1.0636,0.35077,0.2501,0.15659,0.01506 24/11/2015,44.7,0.042,0.01528,1.0643,0.34755,0.2497,0.15652,0.015083 25/11/2015,44.2,0.0424,0.01525,1.0624,0.34613,0.2488,0.15656,0.015068 26/11/2015,44.1,0.0426,0.01518,1.061,0.34218,0.2483,0.15651,0.015008 27/11/2015,44.1,0.0425,0.01505,1.0593,0.34194,0.248,0.15634,0.014959 30/11/2015,43.3,0.0421,0.01506,1.0565,0.34329,0.2474,0.15632,0.015034 1/12/2015,42.6,0.0419,0.01498,1.0633,0.34576,0.2484,0.15637,0.015051 2/12/2015,40.9,0.0427,0.01484,1.0615,0.34614,0.2481,0.15632,0.015019 3/12/2015,40.9,0.0433,0.0148,1.094,0.3467,0.2525,0.15657,0.014968 4/12/2015,40.2,0.0422,0.01468,1.0881,0.34558,0.2521,0.15623,0.014999 7/12/2015,39.6,0.0432,0.01445,1.0837,0.34324,0.2507,0.15603,0.014976 8/12/2015,39.2,0.0437,0.01442,1.0892,0.34365,0.2508,0.15583,0.014957 9/12/2015,39,0.0435,0.01435,1.1025,0.34286,0.2536,0.15554,0.014956 10/12/2015,38.7,0.0425,0.01453,1.0941,0.342,0.2517,0.1553,0.014978 11/12/2015,37.9,0.042,0.01421,1.0986,0.33527,0.2517,0.1549,0.014891 14/12/2015,37.9,0.0421,0.01417,1.0992,0.33566,0.2518,0.15487,0.014908 15/12/2015,37.9,0.0418,0.0143,1.0931,0.33725,0.2534,0.15455,0.014956 16/12/2015,37.5,0.0424,0.01421,1.0912,0.3405,0.2537,0.15444,0.015057 17/12/2015,37.5,0.0427,0.01404,1.0826,0.34138,0.2517,0.15419,0.015055 18/12/2015,38.7,0.0422,0.01409,1.0868,0.3439,0.2544,0.15426,0.015075 21/12/2015,39.5,0.043,0.01404,1.0915,0.34324,0.2566,0.15431,0.015091 22/12/2015,39.8,0.0437,0.01404,1.0957,0.34129,0.2577,0.15441,0.015095 23/12/2015,39.8,0.0438,0.01434,1.0912,0.34279,0.2571,0.15435,0.015134 24/12/2015,40.1,0.0437,0.01422,1.0963,0.34264,0.2587,0.15433, 25/12/2015,40.8,0.0437,0.01421,1.096,0.3426,0.259,0.15473, 28/12/2015,40.7,0.0426,0.01382,1.0968,0.34411,0.2584,0.15412,0.015119 29/12/2015,41.5,0.042,0.01383,1.092,0.34412,0.2581,0.15421,0.015096 30/12/2015,43,0.0416,0.01359,1.0933,0.34262,0.2568,0.15408,0.015042 31/12/2015,43.4,0.0416,0.0137,1.0862,0.34258,0.2548,0.154,0.015102 4/1/2016,43.9,0.0414,0.01373,1.0831,0.33739,0.252,0.15296,0.01502 5/1/2016,44.7,0.0415,0.01363,1.0748,0.33495,0.2495,0.15323,0.015041 6/1/2016,43.9,0.0428,0.01337,1.0781,0.33296,0.2477,0.15246,0.014993 7/1/2016,43,0.0428,0.01336,1.0932,0.33358,0.2515,0.15166,0.014948 8/1/2016,42.6,0.0428,0.01337,1.0922,0.33105,0.2502,0.15167,0.014956 11/1/2016,42.1,0.0427,0.01313,1.0859,0.3292,0.2495,0.15228,0.014975 12/1/2016,41.9,0.0431,0.01299,1.0858,0.32965,0.2491,0.15217,0.014937 13/01/2016,41.2,0.0429,0.01305,1.0877,0.33039,0.25,0.15205,0.014944 14/01/2016,40.6,0.0415,0.01313,1.0865,0.33067,0.2473,0.15172,0.014854 15/01/2016,40.8,0.041,0.01286,1.0916,0.32809,0.2436,0.15189,0.014753 18/01/2016,42,0.0407,0.0126,1.0892,0.3294,0.2443,0.15202,0.014778 19/01/2016,42.1,0.0405,0.0127,1.0908,0.32895,0.2452,0.15194,0.014763 20/01/2016,42.1,0.0409,0.01229,1.089,0.32866,0.2426,0.15188,0.01471 21/01/2016,41.4,0.0402,0.01214,1.0874,0.33193,0.2421,0.15195,0.014748 22/01/2016,41.4,0.0407,0.01282,1.0796,0.33321,0.2421,0.15201,0.014798 25/01/2016,41.4,0.0403,0.01249,1.0849,0.33091,0.2424,0.15194,0.014765 26/01/2016,41,0.0402,0.01269,1.087,0.33242,0.2443,0.15198,0.01476 27/01/2016,41.7,0.0401,0.01282,1.0893,0.33314,0.2433,0.15202,0.014674 28/01/2016,41.5,0.0398,0.01309,1.094,0.33679,0.2453,0.15208,0.014693 29/01/2016,41.4,0.039,0.01321,1.0831,0.33848,0.245,0.15209,0.014732 1/2/2016,41.4,0.0391,0.01293,1.0888,0.33947,0.2475,0.15201,0.014743 2/2/2016,41.6,0.0386,0.01253,1.0919,0.33871,0.2478,0.15186,0.01471 3/2/2016,41.9,0.0388,0.01303,1.1105,0.34314,0.251,0.15205,0.014759 4/2/2016,41.9,0.0387,0.01302,1.1209,0.34336,0.2535,0.1523,0.014804 5/2/2016,42,0.0386,0.013,1.1158,0.34272,0.2531,0.15213,0.014732 15/02/2016,43.6,0.0371,0.01299,1.1156,0.33943,0.2537,0.15386,0.014677 16/02/2016,43.7,0.0373,0.01284,1.1144,0.33574,0.2529,0.15343,0.014603 17/02/2016,44.5,0.0372,0.01331,1.1128,0.33832,0.253,0.15328,0.014635 18/02/2016,44.8,0.0379,0.01313,1.1107,0.33694,0.2528,0.15348,0.014592 19/02/2016,45.1,0.0371,0.01299,1.113,0.33877,0.2546,0.15335,0.014546 22/02/2016,48.8,0.0369,0.01332,1.103,0.34051,0.253,0.15329,0.014589 23/02/2016,48.3,0.0367,0.0131,1.102,0.3397,0.2516,0.15322,0.014584 24/02/2016,47.2,0.0366,0.01319,1.1013,0.34053,0.2516,0.15317,0.014613 25/02/2016,47,0.0369,0.01328,1.1018,0.34146,0.253,0.15296,0.014546 26/02/2016,46.5,0.0366,0.01311,1.0934,0.33427,0.2498,0.15285,0.014545 29/02/2016,46.4,0.0372,0.01341,1.0873,0.33718,0.2501,0.15258,0.014664 1/3/2016,47.1,0.0368,0.01365,1.0868,0.34057,0.2509,0.15262,0.01479 2/3/2016,47.9,0.0376,0.01363,1.0868,0.34,,, ================================================ FILE: Pair trading backtest.py ================================================ # -*- coding: utf-8 -*- """ Created on Tue Feb 6 11:57:46 2018 @author: Administrator """ # In[1]: #grazie a my mentor Prof Giampiero M Gallo #ex-professor in statistics currently a governor in Italy #neither Lega Nord nor Movimento 5 Stelle but Partito Democratico #and his mentor Robert Engle, the nobel laureate! #for their tremendous contributions to VECM # In[2]: #pair trading is also called mean reversion trading #we find two cointegrated assets, normally a stock and an ETF index #or two stocks in the same industry or any pair that passes the test #we run an cointegration test on the historical data #we set the trigger condition for both stocks #theoretically these two stocks cannot drift too far from each other #its like a drunk man with a dog #the invisible dog leash would keep both assets in check #when one stock is getting too bullish #we short the bullish one and long the bearish one, vice versa #sooner or later, the dog would converge to the drunk man #nevertheless, the backtest is based on historical datasets #in real stock market, market conditions are dynamic #two assets may seem cointegrated for the past two years #they can completely diverge after one company launch a new product or whatsoever #i am talking about nvidia and amd, two gpu companies #after bitcoin mining boom and machine learning hype #stock price of nvidia went skyrocketing #on the contrary amd didnt change much #the cointegrated relationship just broke up #so be extremely cautious with cointegration #there is no such thing as riskless statistical arbitrage #always check the cointegration status before trading execution import matplotlib.pyplot as plt import numpy as np import pandas as pd import yfinance as yf import statsmodels.api as sm # In[3]: #use Engle-Granger two-step method to test cointegration #the underlying method is straight forward and easy to implement #a more important thing is the method is invented by the mentor of my mentor!!! #the latest statsmodels package should ve included johansen test which is more common #check sm.tsa.var.vecm.coint_johansen #the malaise of two-step is the order of the cointegration #unlike johansen test, two-step method can only detect the first order #check the following material for further details # https://warwick.ac.uk/fac/soc/economics/staff/gboero/personal/hand2_cointeg.pdf def EG_method(X,Y,show_summary=False): #step 1 #estimate long run equilibrium model1=sm.OLS(Y,sm.add_constant(X)).fit() epsilon=model1.resid if show_summary: print('\nStep 1\n') print(model1.summary()) #check p value of augmented dickey fuller test #if p value is no larger than 5%, stationary test is passed if sm.tsa.stattools.adfuller(epsilon)[1]>0.05: return False,model1 #take first order difference of X and Y plus the lagged residual from step 1 X_dif=sm.add_constant(pd.concat([X.diff(),epsilon.shift(1)],axis=1).dropna()) Y_dif=Y.diff().dropna() #step 2 #estimate error correction model model2=sm.OLS(Y_dif,X_dif).fit() if show_summary: print('\nStep 2\n') print(model2.summary()) #adjustment coefficient must be negative if list(model2.params)[-1]>0: return False,model1 else: return True,model1 # In[4]: #first we verify the status of cointegration by checking historical datasets #bandwidth determines the number of data points for consideration #bandwidth is 250 by default, around one year's data points #if the status is valid, we check the signals #when z stat gets above the upper bound #we long the bearish one and short the bullish one, vice versa def signal_generation(asset1,asset2,method,bandwidth=250): signals=pd.DataFrame() signals['asset1']=asset1['Close'] signals['asset2']=asset2['Close'] #signals only imply holding signals['signals1']=0 signals['signals2']=0 #initialize prev_status=False signals['z']=np.nan signals['z upper limit']=np.nan signals['z lower limit']=np.nan signals['fitted']=np.nan signals['residual']=np.nan #signal processing for i in range(bandwidth,len(signals)): #cointegration test coint_status,model=method(signals['asset1'].iloc[i-bandwidth:i], signals['asset2'].iloc[i-bandwidth:i]) #cointegration breaks #clear existing positions if prev_status and not coint_status: if signals.at[signals.index[i-1],'signals1']!=0: signals.at[signals.index[i],'signals1']=0 signals.at[signals.index[i],'signals2']=0 signals['z'].iloc[i:]=np.nan signals['z upper limit'].iloc[i:]=np.nan signals['z lower limit'].iloc[i:]=np.nan signals['fitted'].iloc[i:]=np.nan signals['residual'].iloc[i:]=np.nan #cointegration starts #set the trigger conditions #this is no forward bias #just to minimize the calculation done in pandas if not prev_status and coint_status: #predict the price to compute the residual signals['fitted'].iloc[i:]=model.predict(sm.add_constant(signals['asset1'].iloc[i:])) signals['residual'].iloc[i:]=signals['asset2'].iloc[i:]-signals['fitted'].iloc[i:] #normalize the residual to get z stat #z should be a white noise following N(0,1) signals['z'].iloc[i:]=(signals['residual'].iloc[i:]-np.mean(model.resid))/np.std(model.resid) #create thresholds #conventionally one sigma is the threshold #two sigma reaches 95% which is relatively difficult to trigger signals['z upper limit'].iloc[i:]=signals['z'].iloc[i]+np.std(model.resid) signals['z lower limit'].iloc[i:]=signals['z'].iloc[i]-np.std(model.resid) #as z stat cannot exceed both upper and lower bounds at the same time #the lines below hold if coint_status and signals['z'].iloc[i]>signals['z upper limit'].iloc[i]: signals.at[signals.index[i],'signals1']=1 if coint_status and signals['z'].iloc[i]new['Close'][0] else -1 new['sar'][1]=new['High'][0] if new['trend'][1]>0 else new['Low'][0] new.at[1,'real sar']=new['sar'][1] new['ep'][1]=new['High'][1] if new['trend'][1]>0 else new['Low'][1] new['af'][1]=initial_af #calculation for i in range(2,len(new)): temp=new['sar'][i-1]+new['af'][i-1]*(new['ep'][i-1]-new['sar'][i-1]) if new['trend'][i-1]<0: new.at[i,'sar']=max(temp,new['High'][i-1],new['High'][i-2]) temp=1 if new['sar'][i]new['Low'][i] else new['trend'][i-1]+1 new.at[i,'trend']=temp if new['trend'][i]<0: temp=min(new['Low'][i],new['ep'][i-1]) if new['trend'][i]!=-1 else new['Low'][i] else: temp=max(new['High'][i],new['ep'][i-1]) if new['trend'][i]!=1 else new['High'][i] new.at[i,'ep']=temp if np.abs(new['trend'][i])==1: temp=new['ep'][i-1] new.at[i,'af']=initial_af else: temp=new['sar'][i] if new['ep'][i]==new['ep'][i-1]: new.at[i,'af']=new['af'][i-1] else: new.at[i,'af']=min(end_af,new['af'][i-1]+step_af) new.at[i,'real sar']=temp return new # In[3]: #generating signals #idea is the same as macd oscillator #check the website below to learn more # https://github.com/je-suis-tm/quant-trading/blob/master/MACD%20oscillator%20backtest.py def signal_generation(df,method): new=method(df) new['positions'],new['signals']=0,0 new['positions']=np.where(new['real sar'] We’re right 50.75 percent of the time... but we’re 100 percent right 50.75 percent of the time, you can make billions that way.

> --- Robert Mercer, co-CEO of Renaissance Technologies > If you trade a lot, you only need to be right 51 percent of the time, we need a smaller edge on each trade.

> --- Elwyn Berlekamp, co-Founder of Combinatorial Game Theory ###### *The quotes above come from a book by Gregory Zuckerman, a book every quant must read, THE MAN WHO SOLVED THE MARKET.*   Most scripts inside this repository are technical indicator automated trading. These scripts include various types of momentum trading, opening range breakout, reversal of support & resistance and statistical arbitrage strategies. Yet, quantitative trading is not only about technical analysis. It can refer to computational finance to exploit derivative price mismatch, pattern recognition on alternative datasets to generate alphas or low latency order execution in the market microstructure. Hence, there are a few ongoing projects inside this repository. These projects are mostly quantamental analysis on some strange ideas I come up with to beat the market (or so I thought). There is no HFT strategy simply because ultra high frequency data are very expensive to acquire (even consider platforms like Quantopian or Quandl). Additionally, please note that, all scripts are historical data backtesting/forward testing (basically via Python, not C++, maybe Julia in the near future). The assumption is that all trades are frictionless. No slippage, no surcharge, no illiquidity. Last but not least, all scripts contain a global function named main so that you can embed the scripts directly into you trading system (although too lazy to write docstring). ### Table of Contents   #### Options Strategy * Options Straddle * VIX Calculator   #### Quantamental Analysis * Monte Carlo Project * Oil Money Project * Pair Trading * Portfolio Optimization Project * Smart Farmers Project * Wisdom of Crowd Project   #### Technical Indicators * Awesome Oscillator * Bollinger Bands Pattern Recognition * Dual Thrust * Heikin-Ashi Candlestick * London Breakout * MACD Oscillator * Parabolic SAR * Relative Strength Index Pattern Recognition * Shooting Star   ### Data Source * Bloomberg/Eikon * CME/LME * Histdata/FX Historical Data * Macrotrends * Stooq/Quandl * Reddit WallStreetBets * Web Scraping * Yahoo Finance/fix_yahoo_finance package/yfinance package
## Strategies: ### 1. MACD oscillator MACD oscillator is trading strategy 101. MACD refers to Moving Average Convergence/Divergence. It is a momentum trading strategy which holds the belief that upward/downward momentum has more impact on short term moving average than long term moving average. It only takes 5 minutes for any bloke with no background in finance to trade with MACD signals. Regarding the simplicity of MACD oscillator, it is the most common strategy among the non-professionals in the market. In behavioral economics, the more people believe in the strategy, the more effective the strategy becomes (not always true, e.g. 2008). Therefore, we should not underestimate the power of MACD oscillator. For the strategy itself, we compute long term moving average and short term moving average on the close price of a given stock. To generate the trading signal, we implement a comparison between the moving averages of different time horizons. When short term moving average is above long term moving average, we long the given stock accordingly. Vice versa. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/macd%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/macd%20oscillator.png) ### 2. Pair trading Pair trading is the basic form of statistics arbitrage. It relies on the assumption that two cointegrated stocks would not drift too far away from each other. First step, we select two stocks and run Engle-Granger two step analysis. Once the criteria of cointegration is met, we standardize the residual and set one sigma away (two tailed) as the threshold. After that, we compute the current standardized residual of the selected stocks accordingly. When the standardized residual exceeds the threshold, it generates the trading signal. The simple rule is we always long the cheap stock and short the expensive stock. The core idea of pair trading is cointegration. Metaphorically speaking, cointegration is like a couple in a clingy relationship where two parties are crazy-glued together. Yet, most relationships break sooner or later, and only the very few can make it to the marriage (from a statistics perspective, not being pessimistic). Hence, it is important to frequently check on the status quo of cointegration before any pair trading order execution (the same applies to relationships). *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/pair%20trading%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/pair%20trading%20asset.png) ### 3. Heikin-Ashi candlestick Heikin-Ashi, the exotic name actually referring to 'Average Bar' in Japanese, is an alternative style of candlestick chart. The sophisticated rules of Heiki-Ashi are designed to filter out the noise for momentum trading. Hence, Heikin-Ashi shows more consecutive bars in contrast to the standard candlestick, which makes price momentum and reverse points more distinguishable in figures. Arguably it should outperform the standard candlestick in sideways and choppy markets. For the strategy itself, initially we make a few transformations on four vital benchmarks - Open, Close, High, Low. The next step is to apply unique Heikin-Ashi rules on Heikin-Ashi Open, Close, High, Low to generate trading signals. The downside of Heikin-Ashi (or any momentum trading strategies) is the slow response. Thus, we should set up the stop loss position accordingly so that we don't get caught up in any flash crash. The rules of Heikin-Ashi can be found in Quantiacs. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/heikin-ashi%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/heikin-ashi%20asset%20value.png) ### 4. London Breakout To one of my favourite cities in the world! Proud to be a Londoner! London Breakout is an intra daily opening range breakout strategy. Basically, it is a fascinating information arbitrage across different markets in different time zones. FX market runs 24/7 globally. For instance, you cannot long the stock of Ford in ASX simply because Ford is listed in NYSE. As FX market is decentralised, you can long any currency pair in any market as long as the market is open. That leaves a door to take a peek at the activity in a closed foreign FX market before the opening of domestic FX market. Back to London Breakout, London and Tokyo are two of the largest FX markets in the world. Tokyo FX trading hour is GMT 0:00 a.m. - GMT 8:59am. London FX trading hour (no summer daylight saving) begins at GMT 8:00 a.m. Even though there is an hour of overlap, the crucial timeframe of London Breakout is GMT 7:00 a.m. - GMT 7:59 a.m. a.k.a. the last trading hour before the opening of London market. The price movement of the crucial timeframe incorporates the information of all the overnight activities of financial market (from the perspective of the current time zone). For the strategy itself, we establish upper and lower thresholds prior to the high and low of the crucial timeframe. Once London FX market opens, we spend the first couple of minutes to check if the price would breach the preset boundaries. If it is above threshold, we long the currency pair accordingly. Vice versa. Nevertheless, we should set up a limit to prevent us from trading in the case of abnormal opening volatility. Normally, we clear our positions based on our target stop loss or stop profit respectively. By the end of the trading hour (still from the perspective of the current time zone), if there are any open positions, we clear them out. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/london%20breakout%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/london%20breakout%20thresholds.png) ### 5. Awesome oscillator Awesome oscillator is an upgraded version of MACD oscillator. It is one of those momentum strategies focusing on the game of moving average. Instead of taking simple moving average on close price, awesome moving average is derived from the mean of high and low price. Similar to MACD oscillator, it takes both short term and long term moving averages to construct the oscillator. There are various strategies for awesome oscillator to generate signals, such as traditional moving average divergence, twin peaks and saucer. Twin peaks is just one of the many names of bottom W pattern. The pattern recognition will be covered in another chapter so the main focus of this chapter is saucer. Saucer is slightly more complex to implement than the traditional divergence. In return, saucer has the power to beat the slow response of the traditional divergence. Generally speaking, a faster response may sound awesome, but it does not guarantee a less risky outcome or a more profitable outcome. Hence, we will take MACD oscillator as a control group, to test if awesome oscillator can actually outperform MACD oscillator. The rules of awesome oscillator could be found in TradingView. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/awesome%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/awesome%20oscillator.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/awesome%20ma.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/awesome%20asset.png) ### 6. Oil Money project This project is inspired by an article on oil-backed foreign exchange. Amid the bullish outlook for crude oil, the currency exchange of oil producing countries would also bounce back. Does this statement really hold? According to the article by Bloomberg (or many other similar research), researchers examine the correlation between petrocurrency and oil price, instead of the causality. But correlation does not equal to causality. Correlation could be a coincidence of a math game. We simply cannot draw the conclusion that oil price moves the currency. Some researchers even use bootstrapping which greatly destroys the autocorrelation of a time series. Thus, it is vital to apply academic analysis and computer simulation on some petrocurrencies to test the causality of oil. *For more details, please refer to the read me page of a separate directory or quant trading section on my personal blog.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Oil%20Money%20project/preview/oil%20production%20bubble%20map.png) ### 7. Dual Thrust If you search dual thrust on google, you will end up with results of rocket engine. Don't panic yet, you can rest assured that dual thrust strategy is nowhere near rocket science. It is just an opening range breakout strategy developed by the founder of Universal Technical Systems. The mathematics involved in this strategy is merely primary school level. Initially we establish upper and lower thresholds based on previous days' open, close, high and low. When the market opens and the price exceeds certain thresholds, we would take long/short positions prior to upper/lower thresholds. The strategy is quite useful in intra daily trading. However, there is no stop loss/profit position in this strategy. We reverse our positions when the price goes from one threshold to the other. We need to clear all positions by the end of the day. Rules of dual thrust can be found in QuantConnect. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/dual%20thrust%20positions.png) ### 8. Parabolic SAR Parabolic SAR is an indicator to identify stop and reverse of a trend. Usually, Parabolic SAR is presented as dotted line either above or below the price in charts. When the price is an uptrend, SAR curve would sit below the price. When the price is downtrend, SAR curve would rise above the price. Parabolic SAR is always considered as a symbol of resistance to the price momentum. When SAR curve and the price curve cross over, it is when trade orders are supposed to be executed. The building of this strategy seems very simple, but the construction of the indicator is extremely painful due to the involvement of recursive calculation. Illustration on how to compute Parabolic SAR can be found in Wikipedia but it is not very well explained. To get a clear idea of the calculation, my personal recommendation is to take a look at the spreadsheet made by joeu2004. It is worth mentioning that SAR and RSI (which will be featured in a later chapter) shares the same founder, Welles Wilder. The guy is a real legend who used to work as mechanical engineer and real estate developer and later became a technical analyst. His book on technical trading system is a must-read for anyone that wants to elevate quant trading system to the next level. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/parabolic%20sar%20positions.png) ### 9. Bollinger Bands Pattern Recognition Bollinger Bands is a very simple but powerful indicator. There are three bands of this indicator. The mid band is the moving average on the price series (usually takes 20 lags). The upper and lower bands are two moving standard deviations away from the mid band. Bollinger Bands can be used to test for various types of strategies. For volatility trading, contraction and expansion of the band width are crucial elements. Any distinct momentum clustering (it can take form of either upward or downward) would result in a Bollinger Bands expansion. And the oscillation in a horizontal channel would result in a Bollinger Bands contraction. For momentum trading, the phenomenon of 'walking the band' indicates the resistance and support level of the underlying asset. In a strong trend, the price constantly attempts to touch or break through the upper/lower band along with Bollinger Bands moving towards the same direction. For pattern recognition, Bollinger Bands has the capability of testing bottom W, top M, head-shoulder patterns, etc. With upper and lower bands served as an interval, it is easier to identify the hidden pattern in the historical data. More details of Bollinger Bands can be found in TradingView. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/bollinger%20bands%20positions.png) ### 10. Relative Strength Index Pattern Recognition RSI (Relative Strength Index) is also a popular indicator. It reflects the current strength/weakness of the stock price momentum. The calculation is pretty straight forward. We use 14 days of smoothed moving average (or other moving average methods) to separately calculate the intra daily uptrend and downtrend. We denote uptrend moving average divided by downtrend moving average as the relative strength. We normalize the relative strength by 100 which becomes an index called RSI. It is commonly believed that RSI above 70 is overbought and RSI below 30 is oversold. This is the simplest way to trade on RSI (as shown in the pictures below). Nonetheless, there could be divergence between RSI momentum and price momentum which will not be covered in the script. The effectiveness of any divergence strategy on RSI is rather debatable. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/rsi%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/rsi%20oscillator.png) If you are looking for something slightly more complex, well, we can apply pattern recognition technique to RSI as well. Unlike strategy No.9 Bollinger Bands, we can directly look at the patterns of RSI itself instead of the price. Since we have tested double bottom pattern in Bollinger Bands, we would test head-shoulder pattern on RSI this time. For details of head-shoulder pattern, please refer to Investopedia. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/rsi%20pattern%20positions.png) ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/rsi%20pattern%20oscillator.png) ### 11. Monte Carlo project Monte Carlo, my first thought on these two words is the grand casino, where you meet Famke Janssen in tuxedo and introduce yourself, 'Bond, James Bond'. Indeed, the simulation is named after the infamous casino. It actually refers to the computer simulation of massive amount of random events. This unconventional mathematical method is extremely powerful in the study of stochastic process. Here comes the argument on Linkedin that caught my eyes the other day. "Stock price can be seemed as a Wiener Process. Hence, we can use Monte Carlo simulation to predict the stock price." said a data science blog. Well, in order to be a Wiener Process, we have to assume the stock price is continuous in time. In reality, the market closes. The overnight volatility exists. But that is not the biggest issue here. The biggest issue is, can we really use Monte Carlo simulation to predict the stock price, even a range or its direction? *For more details, please refer to the read me page of a separate directory or quant trading section on my personal blog.* ![alt text](https://raw.githubusercontent.com/je-suis-tm/quant-trading/master/Monte%20Carlo%20project/preview/ge%20simulation2.png) ### 12. Options Straddle Here marks the debut of options strategy in this repository. Straddle refers to the shape of compasses in the payoff diagram of the strategy. A long straddle involves buying a call option and a put option at the same strike price, the same expiration date and preferably the same price. In reality, the same price is not always feasible (call options price higher implies higher upside risk, vice versa). It is recommended to trade when the price disparity between call and put options is converging. Long straddle is commonly seen in event driven strategy, e.g. political referendum, company earning release. It profits from the uncertainty of both-side risk. For upside risk, the potential profit is unlimited. The potential loss does not come from the downside risk (there is limited gain from downside risk). Instead, it comes from the stagnant price due to insufficient volatility. In this case, short straddle is more suitable for sideways choppy market. The crucial element of options straddle is the selection of the strike price. As the price of options contains the market consensus, the only way to maximize the profit is to find the optimal strike price to shrink the loss bandwidth. This is where the economists kick in and offer base case outlook plus best/worst scenarios. In contrast to the common misunderstanding of quantitative trading, Option Greeks are no silver bullet. Quantitative combined with fundamental in one, so-called quantamental, makes the portfolio impeccable. *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/options%20straddle%20payoff%20diagram.png) ### 13. Portfolio Optimization project Modern portfolio theory was introduced in 1952 by Nobel laureate Harry Markowitz. It is part of investment class 101. But I watched a video by Wolfram recently. It challenged the traditional approach and introduced graph theory to asset diversification. There are plenty of quant shops deploying fancy mathematic tools to solve the market. The real question for us is, as fancy as it sounds, does graph theory work on portfolio optimization? ![alt text](https://github.com/je-suis-tm/graph-theory/blob/master/Portfolio%20Optimization%20project/preview/outta%20sample%20mean%20variance.png) *This project is documented in the repository of Graph Theory. For more details, please refer to the read me page of a separate directory or graph theory section on my personal blog.* ### 14. Smart Farmers project I know a lot of you have complained that this repository isn’t quantitative enough. You are yelling for the ultimate weapon of math destruction such as Poisson process or Jensen’s inequality. Well, the objective of quantitative trading is churning out more :euro: rather than deploying an elegant closed form equation. If you crave for intellectual challenge in mathematics, you are always welcome to check out my Graph Theory repository. Nevertheless, I believe the birth of this project will meet your picky demand. Buon appetito :yum: :tangerine: :pineapple: :melon: :corn: and :sweet_potato: are something we have been taking for granted. Up until COVID-19, we finally come to senses that farmers are one of our low-paid essential workers. This project is dedicated to the optimal allocation of agricultural resources. By trading agricultural market, we are able to eliminate the inefficiency in the crop market. Ideally no food will be wasted and farmers will be fairly compensated. The project per se intends to leverage convex optimization to approximate farmers’ plantation planning for different crops. Assuming farmers are Homo Economicus, their end game is to maximize the profit regarding the price impact from supply and demand. Their decision is constrained by arable land area and biological features of crops. We develop this smart model accordingly to acquire a head start in trading :rice: :coffee: and :chocolate_bar: ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/oil%20palm%20vs%20palm%20oil.png) *For more details, please refer to the read me page of a separate directory or quant trading section on my personal blog.* ### 15. VIX Calculator VIX is the fear gauge of S&P 500 index. By using Riemann sum and Taylor series expansion, we are able to convert a continuous fair price variance swap to a discrete options volatility index, which is called VIX. VIX is determined by two components, 3-week-ahead weekly S&P 500 options and one-month-ahead monthly S&P 500 options. It is de facto market anticipated volatility of S&P 500 index in 30 days. So far it has been applied to some stock exchange indices and some forex pairs. Since VIX is such a great risk management tool, why don’t we apply it to any asset with options contract? The objective of this script is to create a VIX calculator for any commodity options within any given length of forecast time horizon. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/vix%20calculator.PNG) *Click here to be redirected to the script.* ### 16. Wisdom of Crowds Project Every now and then, we read some bulge brackets hit the headline, “XXX will reach 99999€ in 20YY”. Some forecasts hit the bull’s eye but most projections are as accurate as astrology. Price prediction can be easily influenced by the cognitive bias. In the financial market, there is merit to the idea that consensus estimate is the best oracle. By harnessing the power of ensemble learning, we are about to leverage Dawid-Skene model and Platt-Burges model to eliminate the idiosyncratic noise associate with each individual judgement. The end game is to reveal the underlying intrinsic value generated by the collective knowledge of research analysts from different investment banks. Is wisdom of crowds a crystal ball for trading? ![alt text](https://github.com/je-suis-tm/machine-learning/blob/master/Wisdom%20of%20Crowds%20project/preview/y1%20forecast%20bias.png) *This project is documented in the repository of Machine Learning. For more details, please refer to the read me page of a separate directory or machine learning section on my personal blog.* ### 17. Shooting Star > Can we pretend that airplanes in the night sky are like shooting stars? I could really use a wish right now!

> --- Hayley Williams, Lead Vocalist of Paramore Shooting star, such a poetic name, is merely a simple candlestick pattern. It has a long upper shadow, little lower shadow and a small real body, which resonates the shape of a shooting star. Similar to a real comet, shooting star is a jinxed signal. It indicates the beginning of a bearish momentum after a price uptrend. However, the definition of a shooting star in mathematics is sophisticated. Not many candlesticks can suffice the rigid criteria of shooting star. In practice, people relax the constraint on shooting star in order to trigger the signal. A sibling of shooting star is called hammer which is effectively a vertical flipped shooting star with bullish outlook. The close price of a hammer is supposed to be higher than the open price. Another sibling of shooting star is called inverted hammer. Inverted hammer shares the same shape with shooting star, but inverted hammer comes with higher close price than open price and usually is an omen of price hike. Nonetheless, there is no "inverted shooting star". As malicious as it sounds, the official name is called hanging man... *Click here to be redirected to the script.* ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/preview/shooting%20star%20positions.png)
#### STAY TUNED ================================================ FILE: RSI Pattern Recognition backtest.py ================================================ # coding: utf-8 # In[1]: #relative strength index(rsi) is another popular indicator for technical analysis #actually i believe its kinda bull shit #normally i read stuff on trading view wiki #its not like i work there and try to promote it #trading view wiki is a very detailed encyclopedia for different indicators #plz refer to the following link for more details # https://www.tradingview.com/wiki/Relative_Strength_Index_(RSI) #on trading view wiki, there are a couple of strategies to use rsi #the simplest one is overbought/oversold #that is what this script is about #we just set upper/lower boundaries capped at 30/70 for rsi #if rsi exceeds the bound, we bet the stock would go under price correction #another one is called divergence #rsi goes up and price actually goes down #the inventor of rsi called wilder believes bearish rsi divergence creates a selling opportunity #but his protege cardwell believes bearish divergence only occurs in a bullish trend #so their ideas basically contradict to each other #i would undoubtedly give up on this bs divergence strategy #the last one is called failure swing #its kinda like a double bottom pattern in price itself #except this strategy is a pattern recognition on rsi #since i have written bottom w pattern for bollinger bands #i would not do it here import pandas as pd import numpy as np import matplotlib.pyplot as plt import fix_yahoo_finance as yf # In[2]: #smoothed moving average #for details plz refer to wikipedia # https://en.wikipedia.org/wiki/Moving_average#Modified_moving_average def smma(series,n): output=[series[0]] for i in range(1,len(series)): temp=output[-1]*(n-1)+series[i] output.append(temp/n) return output # In[3]: #calculating rsi is very simple #except there are several versions of moving average for rsi #simple moving average, exponentially weighted moving average, etc #in this script, we use smoothed moving average(the authentic way) def rsi(data,n=14): delta=data.diff().dropna() up=np.where(delta>0,delta,0) down=np.where(delta<0,-delta,0) rs=np.divide(smma(up,n),smma(down,n)) output=100-100/(1+rs) return output[n-1:] # In[4]: #signal generation #it is really easy #when rsi goes above 70, we short the stock #we bet the stock price would fall #vice versa def signal_generation(df,method,n=14): df['rsi']=0.0 df['rsi'][n:]=method(df['Close'],n=14) df['positions']=np.select([df['rsi']<30,df['rsi']>70], \ [1,-1],default=0) df['signals']=df['positions'].diff() return df[n:] # In[5]: #plotting def plot(new,ticker): #the first plot is the actual close price with long/short positions fig=plt.figure(figsize=(10,10)) ax=fig.add_subplot(211) new['Close'].plot(label=ticker) ax.plot(new.loc[new['signals']==1].index, new['Close'][new['signals']==1], label='LONG',lw=0,marker='^',c='g') ax.plot(new.loc[new['signals']==-1].index, new['Close'][new['signals']==-1], label='SHORT',lw=0,marker='v',c='r') plt.legend(loc='best') plt.grid(True) plt.title('Positions') plt.xlabel('Date') plt.ylabel('price') plt.show() #the second plot is rsi with overbought/oversold interval capped at 30/70 bx=plt.figure(figsize=(10,10)).add_subplot(212,sharex=ax) new['rsi'].plot(label='relative strength index',c='#522e75') bx.fill_between(new.index,30,70,alpha=0.5,color='#f22f08') bx.text(new.index[-45],75,'overbought',color='#594346',size=12.5) bx.text(new.index[-45],25,'oversold',color='#594346',size=12.5) plt.xlabel('Date') plt.ylabel('value') plt.title('RSI') plt.legend(loc='best') plt.grid(True) plt.show() # In[6]: #pattern recognition #do u really think i would write such an easy script? #dont be naive, here is another way of using rsi #unlike double bottom pattern for bollinger bands #this is head-shoulder pattern directly on rsi instead of price #well, it is actually named head and shoulders #but i refused to do free marketing for the shampoo #cuz that shampoo doesnt work at all! #the details of head-shoulder pattern could be found in this link # https://www.investopedia.com/terms/h/head-shoulders.asp #any way, this pattern recognition is similar to the one in bollinger bands #plz refer to bollinger bands for a detailed explanation # https://github.com/je-suis-tm/quant-trading/blob/master/Bollinger%20Bands%20Pattern%20Recognition%20backtest.py def pattern_recognition(df,method,lag=14): df['rsi']=0.0 df['rsi'][lag:]=method(df['Close'],lag) #as usual, period is defined as the horizon for finding the pattern period=25 #delta is the threshold of the difference between two prices #if the difference is smaller than delta #we can conclude two prices are not significantly different from each other #the significant level is defined as delta delta=0.2 #these are the multipliers of delta #we wanna make sure there is head and shoulders are significantly larger than other nodes #the significant level is defined as head/shoulder multiplier*delta head=1.1 shoulder=1.1 df['signals']=0 df['cumsum']=0 df['coordinates']='' #now these are the parameters set by us based on experience #entry_rsi is the rsi when we enter a trade #we would exit the trade based on two conditions #one is that we hold the stock for more than five days #the variable for five days is called exit_days #we use a variable called counter to keep track of it #two is that rsi has increased more than 4 since the entry #the variable for 4 is called exit_rsi #when either condition is triggered, we exit the trade #this is a lazy way to exit the trade #cuz i dont wanna import indicators from other scripts #i would suggest people to use other indicators such as macd or bollinger bands #exiting trades based on rsi is definitely inefficient and unprofitable entry_rsi=0.0 counter=0 exit_rsi=4 exit_days=5 #signal generation #plz refer to the following link for pattern visualization # https://github.com/je-suis-tm/quant-trading/blob/master/preview/rsi%20head-shoulder%20pattern.png #the idea is to start with the first node i #we look backwards and find the head node j with maximum value in pattern finding period #between node i and node j, we find a node k with its value almost the same as node i #started from node j to left, we find a node l with its value almost the same as node i #between the left beginning and node l, we find a node m with its value almost the same as node i #after that, we find the shoulder node n with maximum value between node m and node l #finally, we find the shoulder node o with its value almost the same as node n for i in range(period+lag,len(df)): #this is pretty much the same idea as in bollinger bands #except we have two variables #one for shoulder and one for the bottom nodes moveon=False top=0.0 bottom=0.0 #we have to make sure no holding positions #and the close price is not the maximum point of pattern finding horizon if (df['cumsum'][i]==0) and \ (df['Close'][i]!=max(df['Close'][i-period:i])): #get the head node j with maximum value in pattern finding period #note that dataframe is in datetime index #we wanna convert the result of idxmax to a numerical index number j=df.index.get_loc(df['Close'][i-period:i].idxmax()) #if the head node j is significantly larger than node i #we would move on to the next phrase if (np.abs(df['Close'][j]-df['Close'][i])>head*delta): bottom=df['Close'][i] moveon=True #we try to find node k between node j and node i #if node k is not significantly different from node i #we would move on to the next phrase if moveon==True: moveon=False for k in range(j,i): if (np.abs(df['Close'][k]-bottom)shoulder*delta) and \ (df['Close'][j]-df['Close'][n]>shoulder*delta): top=df['Close'][n] moveon=True #we try to find shoulder node o between node k and node i #if node o is not significantly different from node n #we would set up the signals and coordinates for visualization #we also need to refresh cumsum and entry_rsi for exiting the trade #note that moveon is still set as True #it would help the algo to ignore this round of iteration for exiting the trade if moveon==True: for o in range(k,i): if (np.abs(df['Close'][o]-top)exit_rsi) or \ (counter>exit_days): df.at[df.index[i],'signals']=1 df['cumsum']=df['signals'].cumsum() counter=0 entry_rsi=0 return df #visualize the pattern def pattern_plot(new,ticker): #this part is to get a small slice of dataframe #so we can get a clear view of head-shoulder pattern a,b=list(new[new['signals']!=0].iloc[2:4].index) #extract coordinates for head-shoulder pattern visualization temp=list(map(int,new['coordinates'][a].split(','))) indexlist=list(map(lambda x:new.index[x],temp)) #slicing c=new.index.get_loc(b) newbie=new[temp[0]-30:c+20] #first plot is always price with positions ax=plt.figure(figsize=(10,10)).add_subplot(211) newbie['Close'].plot(label=ticker) ax.plot(newbie['Close'][newbie['signals']==1],marker='^',markersize=12, \ lw=0,c='g',label='LONG') ax.plot(newbie['Close'][newbie['signals']==-1],marker='v',markersize=12, \ lw=0,c='r',label='SHORT') plt.legend(loc=0) plt.title('Positions') plt.xlabel('Date') plt.ylabel('price') plt.grid(True) plt.show() #second plot is head-shoulder pattern on rsi bx=plt.figure(figsize=(10,10)).add_subplot(212,sharex=ax) newbie['rsi'].plot(label='relative strength index',c='#f4ed71') #we plot the overbought/oversold interval, positions and pattern bx.fill_between(newbie.index,30,70,alpha=0.6,label='overbought/oversold range',color='#000d29') bx.plot(newbie['rsi'][indexlist], \ lw=3,alpha=0.7,marker='o', \ markersize=6,c='#8d2f23',label='head-shoulder pattern') bx.plot(newbie['rsi'][newbie['signals']==1],marker='^',markersize=12, \ lw=0,c='g',label='LONG') bx.plot(newbie['rsi'][newbie['signals']==-1],marker='v',markersize=12, \ lw=0,c='r',label='SHORT') #put some captions on head and shoulders for i in [(1,'Shoulder'),(3,'Head'),(5,'Shoulder')]: plt.text(indexlist[i[0]], newbie['rsi'][indexlist[i[0]]]+2, \ '%s'%i[1],fontsize=10,color='#e4ebf2', \ horizontalalignment='center', \ verticalalignment='center') plt.title('RSI') plt.legend(loc=1) plt.xlabel('Date') plt.ylabel('value') plt.grid(True) plt.show() # In[7]: def main(): ticker='FCAU' startdate='2016-01-01' enddate='2018-01-01' df=yf.download(ticker,start=startdate,end=enddate) new=signal_generation(df,rsi,n=14) plot(new,ticker) #how to calculate stats could be found from my other code called Heikin-Ashi # https://github.com/je-suis-tm/quant-trading/blob/master/heikin%20ashi%20backtest.py if __name__ == '__main__': main() ================================================ FILE: Shooting Star backtest.py ================================================ # coding: utf-8 # In[1]: #shooting star is my friend's fav indicator #the name is poetic and romantic #it is merely a vertical flipped hammer #hammer and shooting star could be confusing #since both of them can be inverted #i memorize them via a simple tune #if u see thor (with hammer),price shall soar #if u see star (shooting star),price shall fall #details of shooting star can be found in investopedia # https://www.investopedia.com/terms/s/shootingstar.asp import pandas as pd import matplotlib.pyplot as plt import numpy as np import yfinance # In[2]: #criteria of shooting star def shooting_star(data,lower_bound,body_size): df=data.copy() #open>close,red color df['condition1']=np.where(df['Open']>=df['Close'],1,0) #a candle with little or no lower wick df['condition2']=np.where( (df['Close']-df['Low'])=2*( df['Open']-df['Close']),1,0) #price uptrend df['condition5']=np.where( df['Close']>=df['Close'].shift(1),1,0) df['condition6']=np.where( df['Close'].shift(1)>=df['Close'].shift(2),1,0) #the next candle's high must stay #below the high of the shooting star df['condition7']=np.where( df['High'].shift(-1)<=df['High'],1,0) #the next candle's close below #the close of the shooting star df['condition8']=np.where( df['Close'].shift(-1)<=df['Close'],1,0) return df # In[3]: #signal generation #there are eight criteria according to investopedia def signal_generation(df,method, lower_bound=0.2,body_size=0.5, stop_threshold=0.05, holding_period=7): #get shooting star conditions data=method(df,lower_bound,body_size) #shooting star should suffice all conditions #in practise,you may find the definition too rigid #its important to relax a bit on the body size data['signals']=data['condition1']*data[ 'condition2']*data['condition3']*data[ 'condition4']*data['condition5']*data[ 'condition6']*data['condition7']*data[ 'condition8'] #shooting star is a short signal data['signals']=-data['signals'] #find exit position idxlist=data[data['signals']==-1].index for ind in idxlist: #entry point entry_pos=data['Close'].loc[ind] stop=False counter=0 while not stop: ind+=1 counter+=1 #set stop loss/profit at +-5% if abs(data['Close'].loc[ ind]/entry_pos-1)>stop_threshold: stop=True data['signals'].loc[ind]=1 #set maximum holding period at 7 workdays if counter>=holding_period: stop=True data['signals'].loc[ind]=1 #create positions data['positions']=data['signals'].cumsum() return data # In[4]: #since matplotlib remove the candlestick #plus we dont wanna install mpl_finance #we implement our own version #simply use fill_between to construct the bar #use line plot to construct high and low def candlestick(df,ax=None,highlight=None,titlename='', highcol='High',lowcol='Low', opencol='Open',closecol='Close',xcol='Date', colorup='r',colordown='g',highlightcolor='y', **kwargs): #bar width #use 0.6 by default dif=[(-3+i)/10 for i in range(7)] if not ax: ax=plt.figure(figsize=(10,5)).add_subplot(111) #construct the bars one by one for i in range(len(df)): #width is 0.6 by default #so 7 data points required for each bar x=[i+j for j in dif] y1=[df[opencol].iloc[i]]*7 y2=[df[closecol].iloc[i]]*7 barcolor=colorup if y1[0]>y2[0] else colordown #no high line plot if open/close is high if df[highcol].iloc[i]!=max(df[opencol].iloc[i],df[closecol].iloc[i]): #use generic plot to viz high and low #use 1.001 as a scaling factor #to prevent high line from crossing into the bar plt.plot([i,i], [df[highcol].iloc[i], max(df[opencol].iloc[i], df[closecol].iloc[i])*1.001],c='k',**kwargs) #same as high if df[lowcol].iloc[i]!=min(df[opencol].iloc[i],df[closecol].iloc[i]): plt.plot([i,i], [df[lowcol].iloc[i], min(df[opencol].iloc[i], df[closecol].iloc[i])*0.999],c='k',**kwargs) #treat the bar as fill between plt.fill_between(x,y1,y2, edgecolor='k', facecolor=barcolor,**kwargs) if highlight: if df[highlight].iloc[i]==-1: plt.fill_between(x,y1,y2, edgecolor='k', facecolor=highlightcolor,**kwargs) #only show 5 xticks plt.xticks([]) plt.grid(True) plt.title(titlename) # In[5]: #plotting the backtesting result def plot(data,name): #first plot is candlestick to showcase ax1=plt.subplot2grid((250,1),(0,0), rowspan=120, ylabel='Candlestick') candlestick(data,ax1, highlight='signals', highlightcolor='#FFFF00') #the second plot is the actual price #with long/short positions as up/down arrows ax2=plt.subplot2grid((250,1),(130,0), rowspan=120, ylabel='£ per share', xlabel='Date') ax2.plot(data.index, data['Close'], label=name) #long/short positions are attached to #the real close price of the stock #set the line width to zero #thats why we only observe markers ax2.plot(data.loc[data['signals']==-1].index, data['Close'].loc[data['signals']==-1], marker='v',lw=0,c='r',label='short', markersize=10) ax2.plot(data.loc[data['signals']==1].index, data['Close'].loc[data['signals']==1], marker='^',lw=0,c='g',label='long', markersize=10) #only show five tickers plt.xticks(range(0,len(data),len(data)//5), data['Date'][0::len(data)//5].dt.date) plt.grid(True) plt.legend(loc='lower left') plt.tight_layout(pad=0.1) plt.show() # In[6]: def main(): #initializing stdate='2000-01-01' eddate='2021-11-04' name='Vodafone' ticker='VOD.L' df=yfinance.download(ticker,start=stdate,end=eddate) df.reset_index(inplace=True) df['Date']=pd.to_datetime(df['Date']) #signal generation new=signal_generation(df,shooting_star) #get subset for better viz to highlight shooting star subset=new.loc[5268:5283].copy() subset.reset_index(inplace=True,drop=True) #viz plot(subset,name) # In[7]: if __name__ == '__main__': main() ================================================ FILE: Smart Farmers project/README.md ================================================ # Smart Farmers   ----------------------------------------- ### Table of Contents * Intro * Assumption * Theoretical Framework * Data Specification * Empirical Result * Discussion * Further Reading ------------------------------------------------   ### Intro :tangerine: :pineapple: :melon: :corn: and :sweet_potato: are something we have been taking for granted. Up until COVID-19, we finally come to senses that farmers are one of the low-paid essential workers. This project is dedicated to the optimal allocation of agricultural resources. By trading agricultural market, we are able to eliminate the inefficiency in the crop market. Ideally no food will be wasted and farmers will be fairly compensated. The project per se intends to leverage convex optimization to approximate farmers’ plantation planning for different crops. Assuming farmers are Homo Economicus, their end game is to maximize the profit regarding the price impact from supply and demand. Their decision is constrained by arable land area and biological features of crops. We develop this smart model accordingly to acquire a head start in trading :rice: :coffee: and :chocolate_bar: ### Assumption The core of this project is Efficient Market Hypothesis. As faulty as it sounds, there is only one way to be rational (call it Pareto Optimal as you may) but one thousand ways to be irrational. Efficient Market Hypothesis allows us to convert head-scratching individual decisions into the simplest form of supply and demand. We aggregate all farmers inside one country into a big farmer union to study their collective behavior. The farmers in the union are presumed to be Homo Economicus. They have one simple but elegant objective, to maximize their margin. To make the ultimate result more robust, we slightly expand the assumptions. * No extreme weather prior to farm planning. No flood/drought, volcano eruption, locust invasion, El Niño or La Niña is expected. Agricultural market is predominantly supply-driven. Weather is the biggest factor that leads to supply shock and price spike. Even if future climate condition may impact the choice of crops, as we have witnessed how global warming encourages farmers to grow grains in Siberia, we can easily modify the list of crops we are monitoring with the assistance of agronomists. In reality, big farms normally implement protection measures in advance, e.g. better irrigation system to fight against drought. This can be easily embedded into the cost of planting certain type of crops. * No sudden surge and plunge of domestic demand. This assumption eradicates the demand side in the model so we can derive an analytical solution from the supply side. The domestic demand for each type of crops is determined by the population and the disposable income. Beyond Meat and Impossible Whopper are absolutely overhyped. The rise of veganism will merely increase the plantation of soybeans in the long run. Moreover, crops are primarily for culinary consumption. Some crops such as corn and sugar cane are the raw material to generate ethanol for biofuel. Other crops such as acorn and oat are essential feed for livestock (cereals for your favorite prosciutto di Parma). They are relatively niche compared to culinary consumption. Nonetheless, we can always use multiple layers to prove that both industrial and livestock demands are fundamentally driven by the population and the disposable income. * No major upgrades of agricultural technology. AgriTech covers a lot of topics including satellite image monitoring, drone pesticide spreading, robotic fruit picking, crop gene engineering, etc. To be honest, IoT sensors, AI management or automated machinery do not really matter to the model. This assumption just focuses on the expected yield of crops. Any technology progress that improves the adaptability of seeds and the fertility of soil should be our concerns. In the next chapter, the scarcity of arable land will be one of the constraints that make farmers rational. Advancements like vertical farming can easily distort the model since the expected yield of crops fully depend on the number of storeys. * No arbitrage between domestic and international market. Oui, oui, we all know international trade is a big deal. Here, we are creating a utopian closed-system where self-sufficiency is achieved. Later in the discussion, we will expand the naïve model to a more general form to somewhat relax the assumption. Apparently, the pain point is data availability. To map out the arbitrage, the freight cost and the tariff should be taken into consideration. Given the complexity of tax systems and the variety of trade routes, this assumption makes our life easier. * No logistic bottleneck and liquidity issue. First of all, all crops are shipped to the nearest buyers to preserve the freshness so the low cost of the cargo can be ignored. Second, probably one of the most controversial assumptions, all crops will be absorbed by the market. Those who cannot be consumed locally will be shipped to the nearest available market. Those who cannot be consumed domestically will be shipped to the international market. According to my business intelligence, the undersupply caused by weather disruption is the common phenomenon. However, most of the farmers disced excess crops back into the ground during COVID-19. The commies will be like, ‘this is the inherent evilness of capitalism, why not donate surplus load to the food bank before rotting?’ The raison d’être is always the cost, the cost of harvest and transportation. * No premium and penalty for heterogenous crop quality. We are assuming all crops within the defined category is identical and sells at the same market price. There is no Michelin-restaurant grade Basmati rice, Charlotte potato or blood orange. This is another assumption caused by data availability. Agricultural products have far more sophisticated grades than other commodities. Different origins usually refer to different percentages of nutrients (like Brent or WTI). Different varieties lead to different tastes (blueberry/blackberry/raspberry). Then you have labels of organic, conventional or gene-modified. Even brand premiums! See that Zespri on your sungold kiwis? Homogeneity greatly reduces the workload of price collection. ### Theoretical Framework   **Objective Function** Maximize total profit regarding supply and demand for each type of crop **Constraints** * Government intervention * Annual crop rotation * Perennial crop lifespan * Limited arable land **Workflow** ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/workflow.png)   ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/naive%20model.PNG) As we have mentioned in the assumptions, the objective of the farmers is straight forward, profit maximization. The profit equals to unit revenue minus unit cost then times the quantity. Inevitably farmers would love to increase as much output as possible since they gain no control over the unit cost. There is only one small faux pas, too much supply can damage the crop price which ultimately leads to the decrease of the total revenue. Hence, farmers have to strike a delicate balance to plant each type of crop. When facing oversupply of one type of crop, farmers need to decide whether the greater market share can compensate the loss from the crop price, or it is wise to switch to another type of crop. Translated to mathematics, the entire decision on choice of crops becomes the pricing mechanism of each type of crop. We will expand on the topic of pricing later. For the moment, let’s just quickly scan over the main equation. The objective function can be broken down into four parts. The first one is the declaration of maximization. Next, Σ denotes a sum over each type of crop. The first term after Σ is price (everything inside the parenthesis) times production of crop i. The second term after Σ is cost times production of crop i. For the cost, it is tricky. If you read FAO handbook, you will be astonished by the overloaded dimension of the cost data, how are you supposed to collect so much data? According to US farm production expenditure summary, the biggest cost is labor (what happened to illegal immigrants?), land, fertilizer and seed. Rents, tractors, trucks, repairs and other fixed costs are always there in spite of the crop choice. The same applies to the labor. Unless the farmers decide to switch crops, they should have plenty of seeds produced by the existing crops. The good news is we are only left with fertilizers and pesticides. There are plenty of free data on the website of IFA. It’s still a pain in the ass given that each type of crop requires a unique intensity of NPK compound fertilizers. After weeks of brainstorming with my friend, it suddenly came to my mind that cost doesn’t have much impact mathematically when we study the aggregated farmer behavior (for individual farmer it’s a huge one). Later, you will see that both inequality and equality constraints are the major factors. At this point, the cost can be simply calculated via production-weighted profit. Nevertheless, the game isn’t this simple. We cannot ignore the intervention of government policies. Farmers may be entitled to subsidies if they grow specific types of crops. We all know at least one-third of EU budget goes to every EU farmer who meets the requirement of environment, sustainability and biodiversity (375 € per hectare, younger gets more). Some of the governments in the world maintain food stockpiles in case of a famine. To suffice the government requirement, there must be mandatory minimum production of grains to avoid the food crisis. After all, Hannibal the Cannibal is a real nightmare. These non-market behaviors can influence farmers’ choice of crops. Therefore, this creates our first inequality constraint, the government intervention. It can take the form of either non-negative production or minimum required production of crop i. Moreover, Farmers need to consider the biological features of the crops. Crops are categorized as annual, biennial and perennial plants. Annual plants grow and die within a year. They are the prime target for crop rotation to improve soil structure and organic matter. Biennial plants grow and die within two years. To make our life easier, we consider biennial plants as annual plants which is a common practice in farms. Perennial plants take years to grow and mature and their lifespan can be longer than Homo Sapiens. Farmers are unlikely to replace perennial plants which can still bear fruits for the next few years. They have fewer incentives to grow perennial plants which take years to bear fruits. What if this year’s price rally of :apple: turns to a price freefall next year? Thus, the second inequality constraint is born. For both annual and perennial plants, they are bounded by upper and lower thresholds. The lower threshold of annual plants is determined by the inertia. Even though the farmers have free wills to choose commercially viable crops, their decision will be limited by their knowledge domain and soil suitability. Different crops require different level of soil acidity and other measures. Needless to say, the knowledge takes time to learn. Furthermore, the drainage condition may affect the choice of crops. That’s why we introduce the inertia coefficient ψ, which controls how much hectare of crop i will remain intact. The inertia coefficient ψ is set at 0.8 by default. As observed throughout the dataset, farmers hardly ever experiment new crops above 20% of their plantation area in a single year. The upper threshold of annual plants is determined by the crop rotation. Monoculture ends up with the same pest and weed community each year. Crop rotation creates a diverse environment and utilizes the ecosystem service to build up the resilience of the farm. With crop rotation, the theoretical largest plantation area of crop i next year equals to this year’s maximum arable land minus this year’s plantation area of crop i. In another word, the theoretical maximum plantation area of crop i equals to sum of this year’s plantation area of any crops apart from crop i. The lower threshold of perennial plants is its long economic lifespan. The biggest issue is that nobody knows the exact age distribution of crop i aside from the actual owner of the farm. At this time, we assume a uniform distribution. Each year only a fraction of crop i reaches the end of their economic lifespan and the rest keeps nourishing. The farmers merely need to decide on the choice of that fraction, replace the old with the new or cut off and try others. To be more precise, that fraction equals to one over ωL where ω denotes the economic lifecycle coefficient (I consulted my agronomist friend and she suggested 0.7) and L denotes the average lifespan of crop i. The upper threshold of perennial plants is its long growth period. Some trees take years to bear fruits. Even if we plan to increase the plantation of perennial plants ridiculously, we will only be capable of harvesting so many fruits next year. To be more precise, we can only harvest (ωL+1)/ωL at maximum. Assuming no perennial plants exceed their economic lifespan this year, the plantation increment of crop i should be the same as the fraction that we would’ve chopped off (the fraction in the lower threshold), since the age of crop i is uniformly distributed. Last but not least, there is limited supply of arable land inside the system. For the sake of ESG, deforestation requires approval from the local government (didn’t stop the notorious palm oil apartheid between EU and Malaysia). Farmers do not have the luxury to grow infinite number of plants. Additionally, each type of crop requires different amount of plantation area. Social distancing is a must for planting trees to prevent competition for sunlight and water. On the contrary, the field of roots and tubers can have higher density. We will take the historic average of the inverse of the yield to get the required hectare per each expected tonne of crop i. This computation allows us to take discount from weather risk, which indicates no bias towards a good year or a bad year. Hence, we derive the equality constraint, the total available land area for plantation. It is rather difficult to predict how much land area will increase by the issued permits or decrease by the natural disasters. We can only do two things to get around the trouble, take the last available number or create scenarios with inputs from agricultural experts. However, the big malaise of the equality constraint is the life cycle of some annual plants. Some of the crops grow and mature within several months even several weeks. Yet, the time horizon of the whole model is on an annual basis due to the classification of annual and perennial plants, which implies harvest area of some plants is repeatedly taken into account. The sum of cropland is inevitably larger than the maximum arable land. It is something worth exploring. With no solutions in sight, we have to turn a blind eye for now. After we set things straight at the objective function and the constraints, we can move onto the core part of the model, the pricing mechanism. Let’s borrow the concept of market equilibrium from microeconomics. Alfred Marshall introduced the idea of supply demand model into economics. Where supply curve with negative slope and demand curve with positive slope intercepts denotes the equilibrium price. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/pricing%20mechanism.PNG) By using linear approximation, we obtain the equation above. Price of crop i equals to the equilibrium price plus the mismatch between supply and demand. When supply exceeds demand, the market condition is oversupply. The difference between demand and supply is undisputedly negative. After multiplied by pricing coefficient α, the difference converts from several hundred tonnes to the scale of US dollar per tonne. The equation easily generates a downward pressure on the equilibrium price, and vice versa. With some random disturbance ε (force majeure), the linear regression emerges. Now that we obtain the pricing mechanism, we shove it back into the original objective function. Because the income per crop is estimated via last available price, the expected unit revenue equals to the latest price plus the change of the price caused by supply fluctuation through the pricing mechanism. The price change can be easily derived via the first order difference of price at time t and t-1. We already know the number of this year’s supply but want to get the answer of next year’s, so we use next year’s supply minus this year’s supply instead of the abbreviation of ∆Q. What is ∆D though? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/price%20change%20derivation.PNG) Let’s solve the final piece of the puzzle. Prior to our assumptions of demand, demand is driven by the population and the disposable income. Disposable income is slightly complicated to compute but we can easily find its substitute, GDP per capita. Intuitively we can create a regression model like the pricing mechanism. The only problem is we cannot directly observe the value of demand which bridges the gap between two regression models. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/demand%20model.PNG) Fortunately, there is an econometric tool called instrumental variable. By using 2-Stage Least Square, it creates the possibility of making causal inferences with observational data. A valid instrumental variable has a causal effect on unobserved variable but no confounding for the direct effect on the dependent variable. Both population and GDP per capita make brilliant instrumental variables. In layman’s terms, population and GDP per capita have no direct power over the crop price. They can only influence the crop price indirectly through the change of demand. Voila, the only unknown variable inside the framework is expected production of each type of crop. In order to get the optimal production of each type of crop, we steal something called quadratic programming from the toolbox of convex optimization. We have to transform the equations above into the matrix form below. While using `CVXOPT`, a couple of things are moderately modified. First, we will minimize the negative version of the objective function rather than maximize the objective function. Then, the inequality constraint must follow the form of not-larger-than. Many smaller-than inequalities are converted to the negative version of not-larger-than. At last, we ought to construct block matrix to satisfy the requirement of a single inequality constraint. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/naive%20model%20matrix.PNG) Splendid, all :raised_hands: on deck, it’s about time to move towards the next chapter! ### Data Specification As you can see in the methodology, this model consumes an insane amount of data and workload. The silver lining is, we can find most of the data with consistent format from one source, Food and Agriculture Organization. FAO is an organization under United Nations and it provides a database with absurd level of details. The metadata consists of production, yield, land area, price, GDP per capita, population and so much more that we don’t need. The database is about 14 gigabytes after decompression. The csv of international trade alone takes up 4 gigabytes :astonished: Unfortunately, I cannot upload the full data to GitHub so you will have to download it from the source. The time horizon of the model is set from 2013 to 2018. The FAO data of 2019 hasn’t been released at the beginning of this project (June 2020). You can trace the record further back to 1975 if needed. The target country is handpicked as Malaysia because I am a big fan of Nasi Lemak. Lol no, I am not. The actual justification is its low variety of crops. For Malaysia, we only need to examine 61 categories of crops but for Italy the number becomes 111 :sweat_smile: After removing crops which takes less than 1% of the land use, we end up with 30 categories. Even inside 30 categories of crops, the issue of missing price data persists. There are a couple of ways to fill the missing data, use the previous value, the latter value, arithmetic average or Kalman Filter. Here, we propose an unconventional way, synthetic control method. Synthetic control method is widely used in political science to evaluate the effect of a policy. It was populated by the study of how terrorism casts shadow over the economic growth of Basque (Abadie and Gardeazabal 2003). The idea of synthetic control unit is to assign weights to control groups to create a synthetic group equivalent to the treatment group before the policy. In our case, control groups are countries with price data of certain crops. The treatment group is Malaysia without price data of certain crops. The policy is simply missing price data. The raison d’être is clearly the market efficiency. In fact, the agricultural market isn’t as domestic as in the model. The price deviation of the same crops between two countries creates an opportunity of arbitrage. In one way or another, the price disparity of two countries will eventually converge to zero. Of course, some nasty governments use tariff, quota or other “ESG” reasons to stop it at the living cost of ordinary people. Luckily, it’s not the case of Malaysia. Thus, we can obtain the missing price data by synthetic control method. Now all the price data can be standardized into annual average producer price in US dollar. Regardless of the numerous dimensions of FAO, FAO still lacks in one type of data, the lifespan of each crop. This is the biggest hurdle of data collection. As mentioned in the theoretical framework, we create the preference towards annual plants to create more flexibility for farmers to switch crops. Yet, figuring out the lifespan of perennial plants is not a walk in the park. If you search the lifespan of an apple tree, you will end up with multiple answers from 60 to 150 years. Let’s define a tidy structure for this challenge. We only collect the information of the first page of google organic results and take the mean of different numbers. After that, we create `mapping.csv` and upload to GitHub. You are welcome to raise an issue when you disagree with any number inside this file. ### Empirical Result How does the model perform against the reality? Let’s run a backtest. Unlike traditional regression, the convex optimization doesn’t allow us to do in-sample and out-of-sample analysis. The backtest is purely based upon one step ahead forecast for each year. For each crop, we examine both price and production to determine the accuracy. In general, the model is a useful tool on around 65% of the crops which we should be really grateful. In quantitative trading, we can churn out a Gulfstream G6 from a factor with odds at 55%. Obviously, we cannot present the backtest result of 30 types of agricultural products. We will only select 25% of the outcome to conduct analytics. Each crop listed below demonstrates a unique challenge. The first target is cabbage. Honestly, I don’t recall eating cabbage in a Malay restaurant, probably in a Peranakan restaurant? The estimated price of cabbage looks like an AR1 model. The lime line seems to be a replication of the green line with one-year lag. I wouldn’t be surprised given that the estimated price equals to the last available price plus the pricing mechanism. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/cabbage%20price.png) The same can be said to the production backtesting. The red line always lags the violet line by one year. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/cabbage%20production.png) In the actual regression stage, the in-sample data is a nice fit. The purple line captures the overall trend but has a smaller volatility than the yellow line. There is a valid causal relationship between price and supply plus demand. Cabbage is apparently for domestic consumption. Seriously, besides Singapore, why would anyone import cabbage from Malaysia? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/cabbage%20regression.png) The second one is cocoa. Who doesn’t like chocolates? Although Malaysian cocoa beans isn’t known for its top-notch quality, the cocoa tree occupies quite a large area of plantation area. I suspect it has something to do with the popular drink, Milo Dinosaur. The price forecast shows similar traits as the cabbage, AR1 model. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/cocoa%20price.png) Yet, the production backtest is a different case. It’s a flawless forecast on the production side. Since our model is centered around the expected production, it kind of makes sense. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/cocoa%20production.png) The regression result sounds worrisome. The demand of cocoa beans does not appear to count on GDP per capita or population. I suppose, you buy iced Milo when you are broke and you buy one more spoon on top when you are rich? ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/cocoa%20regression.png) The third one is coconut. Nobody loves coconut rice like Malays. Nothing tastes as delicious as coconut rice with pandan leaves. The estimated coconut price looks the part. The prediction successfully simulates the V-shaped recovery of coconut price. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/coconut%20price.png) But the production is severely overestimated. At first, the downhill production of coconut coincides with the collapse of the price. The production hasn’t kept up with the price rebound ever since. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/coconut%20production.png) For the regression, supply and demand do not have the explanatory power over the coconut price at the beginning. Gradually, the relationship starts to reveal itself. As Malaysia exports coconut oil for cosmetics products, the domestic demand isn’t sufficient for the model. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/coconut%20regression.png) The fourth one is another tropical fruit, mango. You can put it in chicken curry or chendol, either way, so yummy. The price forecast is a disaster. The actual price moves completely opposite to the projection. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/mango%20price.png) The estimated production follows the trend but with a larger magnitude of fluctuation. Especially in 2015, the model expects a price peak for some unknown reason. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/mango%20production.png) Supply and demand work to certain extent – at least the overall trend is captured. People usually buy imported mango from Thailand. Domestic demand should be able to cover the model. There may be some other hidden factors influence mango demand. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/mango%20regression.png) The fifth one is rubber. Rubber is a public traded commodity in SGX with RSS3 and TSR20. It used to play a giant role in Malaysia’s export business before the bonanza of oil palm. Many rubber end products are big industries in Malaysia, such as tyre and condom. The plunge of the rubber price prompts the farmers to switch crops. However, the price prediction works spectacularly well. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/rubber%20price.png) Despite the overestimation of rubber production, the model provides a clear picture of the underlying trend. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/rubber%20production.png) Supply and demand have limited explanatory power on rubber. Since rubber is an export business, the model must take in consideration of international demand. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/rubber%20regression.png) At the first glance, the model works well on the overall production of all 30 crops. If you break down the actual volume of each crop, you will realize oil palm is actually the predominant driver. The total production is merely a reflection of oil palm. Oil palm fruit is the raw material for palm oil. Malaysia is the second largest palm oil producer trailing after Indonesia. The oil palm industry is a pillar of the Malaysian economy. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/overall%20production.png) The prediction of oil palm looks a bit weird. In some parts, it shows some features of AR1 model. In other parts, the model appears to be accurate. Oil palm is perhaps the most commercialized commodity among 30 crops in the model. It is rather difficult if not impossible to speculate the price movement of oil palm. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/oil%20palm%20price.png) Though the price projection is gibberish, the model yields a convincing outcome on the production. Oil palm possibly has the smallest mean error compared to other crops. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/oil%20palm%20production.png) Supply and demand explain the price in the earlier period. Throughout the recent years, the relationship begins to cool down. Palm oil is a lucrative export business in Malaysia. The external business environment should have a bigger influence than local population or GDP per capita. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/oil%20palm%20regression.png) ### Discussion > I’ve never seen a bad backtest.

> --- Dimitris Melas, Head of Research at MSCI To be fair, the excellent result of backtesting occurs because we are using God's eye view. Since we are in 2020, we already know the historical population and GDP per capita of Malaysia. When it comes to trading, the forward-looking capability is what we care the most. To make a price or production forecast, there are many variables to be plugged in. In order to obtain price and production, the framework requires a projection of demand (population and GDP per capita), agricultural land and crop yield. Attributable to the variety of the input, this model is more like a scenario analysis tool. We can adjust each input variable to see how the price and the production of each crop are responding accordingly. A comparison with futures market is the best way to test the forward-looking accuracy of the model. Bear in mind that not all crops are commoditized in the financial market. Here we select palm oil, for its immense liquidity, to make a forward testing. In Malaysia, there are two types of price associated with palm oil, Fresh Fruit Bunches (FFB) and Crude Palm Oil (CPO). The model per se gives out the raw material price which is oil palm fruit FFB price in US dollar per tonne. The historical benchmark we are using for comparison is Bursa Malaysia Ringgit denominated CPO futures generic first contract. The benchmark requires some computations of annual average and US dollar conversion before plotting. The contract size of the futures is 25 metric tonnes. As a consequence of unit mismatch and other fees involved in the oil extraction, we would visualize both prices in separate axis. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/oil%20palm%20vs%20palm%20oil.png) Oil palm FFB price forecast is based upon a few assumptions. The demand consists of UN population forecast and IMF GDP per capita forecast before COVID-19. We assume a 5% Year-on-Year increase in agricultural land. As for the crop yield, we are taking the historic average to eliminate the influence of weather. Palm oil CPO futures price is collected from Bloomberg on the 8th of July. As you can see, the forward testing isn’t as fantastic as the back testing. The model suggests a backwardation from 2018 to 2020 and a contango from 2021 onwards. Apparently, the actual forward curve is more like a W-shaped recovery thanks to fucking coronavirus. If we create a short position in 2018 and keep rolling over the contracts, not sure how many investors have pulled out their money from our hedge fund in 2020 :expressionless: Why is there a huge price divergence? Well, first of all, we are using an outdated population and GDP per capita forecast. The damn virus in 2020 has slashed GDP per capita growth for every country in the world (thank you for concealing information). The virus has severely disrupted the population growth as well. I mean, does anyone want to get pregnant during pandemic? Second, the area of agricultural land is another issue. The arable land is impractical to forecast. The last but not least, the crop yield is stagnant in our model. Now we have a hike of the demand. Yet, the supply cannot keep up due to the stagnant growth from total plantation area and crop yield. An increasingly undersupply market will certainly push the crop price through the roof. The solution is simple. We can send our enquiries to the economist friends and grab the latest population and GDP per capita forecast with COVID-19 taken into consideration. As for the crop yield, we should go to our agronomist friends to get a sense of the future fertilizer usage and climate change. Alternatively, if we have no economist or agronomist friend, we will just create scenarios, e.g. 2%/5%/7% increase in crop yield. One thing about forward testing we didn’t mention is the export nature of palm oil. The convex optimization model is no panacea. It works fine with peppers or lettuce given their scale of domestic consumption. To estimate the demand of palm oil, perhaps its biggest buyer India should be counted in. Truth be told, the customers of Malay palm oil are so fragmented. Top 20 does not even cover more than 75% of the market share (calculation based upon Global Trade Atlas data). Thus, we propose a more generalized model. For a closed-system that craves for self-sufficiency, e.g. EU, the naïve form works alright. When it comes to powerful agricultural exporters such as US or Canada, we will need a Ricardian model. David Ricardo created this model by demonstrating an international trade of wine and clothes between England and Portugal. In our case, Ricardian model is a Ricardian international trading system where different countries produce each crop proportionally to its cost and plantation area which are considered as comparative advantage. To preserve the robustness of the model, the assumptions of the naïve form stay the same. We only need to fortify two of the original assumptions. * Data availability assumption Although FAO provides a detailed list of crop price in each country, Ricardian model only uses single price for one type of crop regardless of the origin, ideally from CME or ICE futures. The arbitrage cost is the major cause. The logistic and warehouse cost could take enormous amount of time to find. The same applies to the tariff or the quota which are buried inside government documents and updated frequently due to trade frictions. In this sense, Ricardian model removes all trade barrier. The market share of each crop for each country is determined by the cost and the plantation area. Ricardian model also removes the heterogeneity in the agriculture technology and natural condition. The universal crop yield is applied to each country. * Homo Economicus assumption The naïve form is centered around the idea of Pareto Optimal. The generalized form also ensures Pareto Optimal equals to Nash Equilibrium. In another phrase, the illicit market behaviors such as competition and collusion do not take place among different countries. We have heard of the infamous oil price war between Russia and Saudi Arabia. Their competition of the market share led to the plummeting oil price. Their collusion also led to the bankruptcy of many shale oil producers in Permian basin. In this zero-sum game, the slice may be larger for some players but the cake is definitely smaller. In our Ricardian model, the end game is to maximize the total profit sum of all countries. It’s a bigger cake for everyone although the slice for individual player is not guaranteed to be bigger. ![alt text](https://github.com/je-suis-tm/quant-trading/blob/master/Smart%20Farmers%20project/preview/ricardian%20model.PNG) The generalized form looks like the cousin of the naïve form. There are only minor changes in the mathematics form. We have one more sum function Σ to capture each country with subscript j in the system. The list of countries should include importers and exporters for each type of crop to cover ideally 90% of the market activity. Well, given the data complexity of Ricardian model, it is likely to take a decade for me to collect everything and simulate the model. Since we have talked about the smart farmers, let’s be smart researchers for once. Amid the decent performance of the naïve form, why bother fixing it when it’s not broken? The bottom line is, as long as we collect good forecast of population, GDP per capita, arable land & crop yield, we are able to make one year ahead forecast for both crop production and price. In that way, we can adjust our futures contracts accordingly and switch from the front month to a further-out month. ### Further Reading 1. Abadie A, Gardeazabal J (2003) The Economic Costs of Conflict: A Case Study of the Basque Country *This paper populated the concept of synthetic control method by investigating the economic effects of terrorist conflict in Basque. Besides a difference-in-difference approach on GDP, the author also used event study to compute the cumulated abnormal return of Basque-exposed portfolio and non-Basque-exposed portfolio.* 2. Angrist JD, Krueger AB (2001) Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments *This paper summarized the previous literatures using instrumental variables to analyze data from natural and randomized experiments. The author discussed the advantage of instrumental variables in combating measurement errors and omitted variables.* 3. Komareka AM et al. (2017) Agricultural Household Effects of Fertilizer Price Changes for Smallholder Farmers in Central Malawi *This paper applied a farm system simulator to Malawi to study the impact of fertilizer price. For those who want to explore different scenarios of crop yield, you can check out the computation of nitrogen-limited and water-limited yield in this paper.* 4. Louhichi K et al. (2010) FSSIM, A Bio-economic Farm Model for Simulating the Response of EU Farming Systems to Agricultural and Environmental Policies *This paper created a farm system simulator to estimate the impact of EU policies. The objective function of FSSIM is similar to Markowitz portfolio optimization which is a tradeoff between return and risk.* 5. Louhichi K, Gomez y Paloma S (2013) Modelling Agri-Food Policy Impact at Farm-household Level in Developing Countries (FSSIM-Dev) *This paper extended the application of FSSIM to developing countries. The constraint of perennial plants was inspired by the net present value of the profitability of tree-crop in this paper.* 6. Marshall A (1890) Principles of Economics *This book is the origin of supply and demand model. You will find the detailed explanation of market equilibrium in book 5 chapter 3.* 7. Ricardo D (1817) On the Principles of Political Economy and Taxation *This book is the origin of Ricardian model. You will find the detailed explanation of comparative advantage in chapter 7.* ================================================ FILE: Smart Farmers project/check consistency.py ================================================ # coding: utf-8 # In[1]: import os os.chdir('H:/') import pandas as pd # In[2]: prod=pd.read_csv('Production_Crops_E_All_Data_(Normalized).csv', encoding='latin-1') prix=pd.read_csv('Prices_E_All_Data_(Normalized).csv', encoding='latin-1') land=pd.read_csv('Inputs_LandUse_E_All_Data_(Normalized).csv', encoding='latin-1') # In[3]: global beginyear,endyear beginyear=2012; endyear=2019 # In[4]: mapping=pd.read_csv('mapping.csv') # In[5]: #select malaysia from 2012-2018 malay_land=land[land['Year'].isin(range(beginyear,endyear))][land['Area']=='Malaysia'][land['Element'].isin(['Area'])][land['Item'].isin(['Cropland'])] malay_prod=prod[prod['Year'].isin(range(beginyear,endyear))][prod['Area']=='Malaysia'][prod['Element'].isin(['Area harvested','Production'])] malay_prod=malay_prod.merge(mapping,on=['Item Code', 'Item'],how='left') # In[6]: #remove redundant cols for i in ['Area Code','Element Code','Year Code', 'Flag','COMMODITY','Item Code', 'subclass code','class code', 'DEFINITIONS, COVERAGE, REMARKS',]: del malay_prod[i] # In[7]: #select crops with available data a=set(malay_prod['Item'][malay_prod['Element']=='Area harvested']) b=set(malay_prod['Item'][malay_prod['Element']=='Production']) target_crops=a.intersection(b) # In[8]: #exclude land usage<1% without price data exclude=['Areca nuts', 'Bastfibres, other', 'Cashew nuts, with shell', 'Cereals, Total', 'Chillies and peppers, dry', 'Citrus Fruit, Total', 'Cloves', 'Coarse Grain, Total', 'Coffee, green', 'Coir', 'Fibre Crops Primary', 'Fruit Primary', 'Fruit, citrus nes', 'Fruit, fresh nes', 'Fruit, tropical fresh nes', 'Groundnuts, with shell', 'Manila fibre (abaca)', 'Nutmeg, mace and cardamoms', 'Oilcrops', 'Oilcrops, Cake Equivalent', 'Oilcrops, Oil Equivalent', 'Roots and Tubers, Total', 'Roots and tubers nes', 'Soybeans', 'Spices nes', 'Tea', 'Treenuts, Total', 'Vegetables Primary', 'Vegetables, fresh nes'] # In[9]: #finalize the target targets=[i for i in target_crops if i not in exclude] # In[10]: #cleanse malay_crops=malay_prod[malay_prod['Item'].isin(targets)] # In[11]: #subtotal total=malay_prod[malay_prod['class'].isnull()] # In[12]: #compare sum of area by crops with sum of area by subclass sss=total[total['Element']=='Area harvested'].groupby(['Item','Year']).sum() ttt=malay_crops[malay_crops['Element']=='Area harvested'].groupby(['class','Year']).sum() # In[13]: #compare sum of area by crops malay_crops[malay_crops['Element']=='Area harvested'].groupby(['Year']).sum() # In[14]: #with cropland malay_land ================================================ FILE: Smart Farmers project/cleanse data.py ================================================ # coding: utf-8 # In[1]: import os os.chdir('H:/') import pandas as pd import numpy as np # ### define functions # In[2]: #etl def prepare(target_land,target_prod,target_prix): #land clean up target_land=target_land[['Year','Value']].copy() #prix clean up target_prix=target_prix[['Item','Year','Value']].copy() #create area and clean up target_area=target_prod[target_prod['Element']=='Area harvested'].copy() target_area=target_area[['Item','Year','Value','type','lifespan']].copy() #production clean up target_prod=target_prod[target_prod['Element']=='Production'].copy() target_prod=target_prod[['Item','Year','Value','class']].copy() #compute yield inverse and clean up target_yield_inverse=target_prod.merge(target_area,on=['Item','Year'],how='left') target_yield_inverse['Value']=np.divide(target_yield_inverse['Value_y'],target_yield_inverse['Value_x']) target_yield_inverse=target_yield_inverse[['Item', 'Year','Value','type', 'lifespan']] #sort by item and year for data in [target_prod,target_area,target_prix,target_yield_inverse]: data.sort_values(['Item','Year'],inplace=True) #concatenate global D D={} for currentyear in range(beginyear,endyear): temp1=target_prod[target_prod['Year']==currentyear].merge( target_area[target_area['Year']==currentyear],on=['Item', 'Year'],how='outer') temp2=target_prix[target_prix['Year']==currentyear].merge( target_yield_inverse[target_yield_inverse['Year']==currentyear],on=['Item', 'Year'],how='outer') temp1.columns=temp1.columns.str.replace('Value_x','production') temp1.columns=temp1.columns.str.replace('Value_y','area') temp2.columns=temp2.columns.str.replace('Value_x','price') temp2.columns=temp2.columns.str.replace('Value_y','yield_i') data=temp1.merge(temp2,on=['Item', 'Year', 'type', 'lifespan'],how='outer') D[currentyear]=data #compute eco lifespan for perennials for currentyear in range(beginyear,endyear): eco_lifespan=[default_discount for _ in range(len(D[currentyear]))] indices=D[currentyear]['lifespan'].dropna().index perennial=D[currentyear]['lifespan'].dropna().apply(lambda x:(x*eco_coeff-1)/(x*eco_coeff)) for i in indices: eco_lifespan[i]=round(perennial.loc[i],4) D[currentyear]['eco lifespan']=eco_lifespan return D # ### execution # In[3]: global beginyear,endyear beginyear=2012 endyear=2019 # In[4]: global eco_coeff,default_discount eco_coeff=0.7 default_discount=0.8 # In[5]: prod=pd.read_csv('Production_Crops_E_All_Data_(Normalized).csv', encoding='latin-1') prix=pd.read_csv('Prices_E_All_Data_(Normalized).csv', encoding='latin-1') land=pd.read_csv('Inputs_LandUse_E_All_Data_(Normalized).csv', encoding='latin-1') population=pd.read_csv('Population_E_All_Data_(Normalized).csv', encoding='latin-1') gdp=pd.read_csv('Macro-Statistics_Key_Indicators_E_All_Data_(Normalized).csv', encoding='latin-1') # In[6]: os.chdir('H:/data') # In[7]: mapping=pd.read_csv('mapping.csv') # In[8]: #select malaysia from beginyear-endyear malay_land=land[land['Year'].isin(range(beginyear,endyear))][land['Area']=='Malaysia'][land['Element'].isin(['Area'])][land['Item'].isin(['Cropland'])] malay_prix=prix[prix['Year'].isin(range(beginyear,endyear))][prix['Area']=='Malaysia'][prix['Element']=='Producer Price (USD/tonne)'][prix['Months']=='Annual value'] malay_prod=prod[prod['Year'].isin(range(beginyear,endyear))][prod['Area']=='Malaysia'][prod['Element'].isin(['Area harvested','Production'])] malay_pop=population[population['Element']=='Total Population - Both sexes'][population['Area']=='Malaysia'][population['Year']>=beginyear] malay_gdp=gdp[gdp['Element']=='Value US$'][gdp['Item']=='Gross Domestic Product per capita'][gdp['Area']=='Malaysia'][gdp['Year'].isin(range(beginyear,endyear))] # In[9]: #exclude land usage<1% exclude=[813,236,809,1717, 512, 782, 656, 149, 667, 809, 813, 689, 698, 702, 723, 217, 226, 236, 242,463, 603, 619, 1720, 1729, 1731, 1732, 1735, 1738, 1753, 1804, 1841,1814] # In[10]: #find items without price a=set(malay_prod['Item Code'][malay_prod['Element']=='Area harvested']) b=set(malay_prod['Item Code'][malay_prod['Element']=='Production']) c=set(malay_prix['Item Code']) sans_prix=[i for i in a.intersection(b) if i not in c] sans_prix=[i for i in sans_prix if i not in exclude] print(sans_prix) # In[11]: #use austria oilseeds to replace oilseeds_prix=prix[prix['Area']=='Austria'][prix['Element']=='Producer Price (USD/tonne)'][prix['Item Code']==339][prix['Year'].isin(range(beginyear,endyear))] # In[12]: #use avg of maize and rice to replace cereals cereal_mean=malay_prix[malay_prix['Item'].isin(['Maize','Rice, paddy'])].groupby('Year').mean()['Value'].tolist() cereal_prix=oilseeds_prix.copy() cereal_prix['Value']=cereal_mean cereal_prix['Item']='Cereals (Rice Milled Eqv)' cereal_prix['Item Code']=1817 # In[13]: #add missing malay_prix=malay_prix.append(oilseeds_prix).append(cereal_prix) malay_prix.reset_index(inplace=True,drop=True) # In[14]: #concat malay_prod=malay_prod.merge(mapping,on=['Item Code', 'Item'],how='left') # In[15]: #find inner join of crops a=set(malay_prod['Item Code'][malay_prod['Element']=='Area harvested']) b=set(malay_prod['Item Code'][malay_prod['Element']=='Production']) c=set(malay_prix['Item Code']) target_crops=a.intersection(b).intersection(c) targets=[i for i in target_crops if i not in exclude] # In[16]: #select crops malay_prod=malay_prod[malay_prod['Item Code'].isin(targets)] malay_prix=malay_prix[malay_prix['Item Code'].isin(targets)] # In[17]: #add 2018 land land_2018=malay_land.iloc[-1:].copy() land_2018.reset_index(inplace=True,drop=True) land_2018.at[0,'Year']=2018 land_2018.at[0,'Year Code']=2018 malay_land=malay_land.append(land_2018) # In[18]: #export to csv malay_land.to_csv('malay_land.csv',index=False) malay_prod.to_csv('malay_prod.csv',index=False) malay_prix.to_csv('malay_prix.csv',index=False) malay_pop.to_csv('malay_pop.csv',index=False) malay_gdp.to_csv('malay_gdp.csv',index=False) # In[19]: #concat D=prepare(malay_land,malay_prod,malay_prix) grand=pd.concat([D[i] for i in D]) grand.reset_index(inplace=True,drop=True) # In[20]: #create from synthetic control unit malay_ginger=[1711.631924118213, 1918.0617150999785, 1926.352662122375, 1904.0526853161766] malay_lettuce=[808.9104313117714, 809.2907573824596, 880.0718990821069, 801.194381901839] malay_maize=[176.02653721679235, 181.61446377135653, 185.21444467527138] malay_orange=[385.20868947337976, 303.6319254759596, 277.51641822220614, 376.92771860265077] malay_sugarcane=[246.78089608441445] malay_tobacco=[4345.956117624693, 4091.368210599639, 3638.8980233955585, 3829.529414768218, 3758.1754705530975, 3889.6001454970665] # In[21]: #fill price fillnull=dict(zip(grand['Item'][grand['price'].isnull()].unique(), [malay_tobacco,malay_ginger,malay_lettuce, malay_orange,malay_maize,malay_sugarcane,])) for i in fillnull: indices=grand[grand['Item']==i][grand['price'].isnull()].index.tolist() for j in indices: grand.at[j,'price']=fillnull[i][indices.index(j)] # In[22]: grand.to_csv('grand.csv',index=False) # ### synthetic control unit # In[23]: # import statsmodels.api as sm # #show missing items # null=set(grand['Item'][grand['price'].isnull()]) # ss=grand[grand['Item'].isin(null)].sort_values(['Item','Year']) # ss # #split here # #create synthetic control unit # for ii in ss['Item'].unique(): # print(ii) # #cleanse data # temp=prix[prix['Item']==ii][prix['Year'].isin(range(beginyear,endyear))][prix['Element']=='Producer Price (USD/tonne)'][prix['Months']=='Annual value'] # temp=temp.pivot(index='Year',columns='Area',values='Value') # #delete null data # for i in temp: # if temp[i].isnull().any() and i!='Malaysia': # del temp[i] # #train # x=temp.loc[temp['Malaysia'].dropna().index] # del x['Malaysia'] # y=temp['Malaysia'].dropna() # x.reset_index(inplace=True,drop=True) # y.reset_index(inplace=True,drop=True) # m=sm.OLS(y,x).fit() # #train result # print(m.predict(),y.tolist()) # #test result # test=temp[temp['Malaysia'].isnull()] # test=test[[i for i in test.columns if i!='Malaysia']] # print(m.predict(test).tolist()) ================================================ FILE: Smart Farmers project/country selection.py ================================================ # coding: utf-8 # In[1]: target_country=['Australia','Spain', 'Morocco', 'United Kingdom', 'Poland', 'France', 'Mexico', 'Bangladesh', 'Canada', 'Viet Nam', 'Thailand', 'Guatemala', 'Colombia', 'Germany', 'China', 'Brazil', 'India', 'United States of America', 'Malaysia', 'Indonesia'] # In[2]: target_year=[2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017] # In[3]: import pandas as pd import numpy as np import os os.chdir('H:/') # In[4]: prod=pd.read_csv('Production_Crops_E_All_Data_(Normalized).csv',encoding='latin-1') # In[5]: prix=pd.read_csv('Prices_E_All_Data_(Normalized).csv',encoding='latin-1') # In[6]: echanger=pd.read_csv('Trade_Crops_Livestock_E_All_Data_(Normalized).csv',encoding='latin-1') # In[7]: #only compare crops with available data target_crops=set(prod['Item']).intersection(set(prix['Item'])).intersection(set(echanger['Item'])) # # volume # In[8]: #extract export volume trade=echanger[echanger['Element']=='Export Quantity'] # In[9]: #cleanse trade=trade[trade['Item'].isin(target_crops)] trade=trade[trade['Area'].isin(target_country)] trade=trade[trade['Year'].isin(target_year)] trade=trade[['Area','Year','Item','Value']] # In[10]: #extract production data prod=prod[prod['Element']=='Production'] # In[11]: #cleanse prod=prod[prod['Item'].isin(target_crops)] prod=prod[prod['Area'].isin(target_country)] prod=prod[prod['Year'].isin(target_year)] prod=prod[['Area','Year','Item','Value']] # In[12]: #group by sum export=trade.groupby(['Area','Year']).sum() # In[13]: #group by sum supply=prod.groupby(['Area','Year']).sum() # In[14]: #create new dataframe to compute export volume percentage pourcent=pd.DataFrame(index=export.index) # In[15]: #compute percentage pourcent['value']=np.divide(export['Value'].tolist(),supply['Value'].tolist()) # In[16]: #clean up index pourcent.reset_index(inplace=True) # In[17]: #historical average mean_pourcent=pourcent[['Area','value']].groupby('Area').mean() # In[18]: #sort by percentage mean_pourcent=mean_pourcent.sort_values('value') # In[19]: #export percentage for a particular year pourcent[pourcent['Year'].isin([2017])].sort_values('value') # # price # In[20]: #get usd price prix=prix[prix['Element']=='Producer Price (USD/tonne)'] # In[21]: #cleanse prix=prix[prix['Item'].isin(target_crops)] prix=prix[prix['Area'].isin(target_country)] prix=prix[prix['Year'].isin(target_year)] prix=prix[['Area','Year','Item','Value']] # In[22]: #previously we examine the volume #now we focus on value value=prod.merge(prix,on=['Area','Year','Item'],how='inner') # In[23]: #volume times unit price equals to total value value['Value']=np.multiply(value['Value_x'],value['Value_y']) # In[24]: #cleanse value=value[['Area','Year','Item','Value']] # In[25]: #get export price exchange=echanger[echanger['Element']=='Export Value'] # In[26]: #cleanse exchange=exchange[exchange['Item'].isin(target_crops)] exchange=exchange[exchange['Area'].isin(target_country)] exchange=exchange[exchange['Year'].isin(target_year)] exchange=exchange[['Area','Year','Item','Value']] # In[27]: #group by sum temp1=exchange.groupby(['Area','Year']).sum() # In[28]: #group by sum temp2=value.groupby(['Area','Year']).sum() # In[29]: #inner join temp=temp1.merge(temp2,on=['Area','Year'],how='inner') # In[30]: #create dataframe to compute export value percentage percentage=pd.DataFrame(index=temp.index) # In[31]: #compute export value percentage percentage['value']=np.divide(temp['Value_x'],temp['Value_y']) # In[32]: #clean up percentage.reset_index(inplace=True) # In[33]: #historical average mean_percentage=percentage[['Area','value']].groupby('Area').mean() # In[34]: #sort by percentage mean_percentage=mean_percentage.sort_values('value') # In[35]: #export percentage for a particular year percentage[percentage['Year'].isin([2016])].sort_values('value') ================================================ FILE: Smart Farmers project/data/capita.csv ================================================ Date,Mid Price 12/31/1980,1926.963 12/31/1981,1920.127 12/31/1982,2006.4821 12/31/1983,2189.553 12/31/1984,2419.501 12/31/1985,2154.458 12/31/1986,1864.031 12/31/1987,2070.009 12/31/1988,2213.866 12/31/1989,2380.512 12/31/1990,2585.824 12/31/1991,2885.3059 12/31/1992,3378.7209 12/31/1993,3716.9519 12/31/1994,4027.509 12/31/1995,4678.0239 12/31/1996,5175.5562 12/31/1997,5011.5601 12/31/1998,3519.7661 12/31/1999,3762.769 12/31/2000,4347.73 12/31/2001,4189.0571 12/31/2002,4441.8472 12/31/2003,4740.3159 12/31/2004,5244.874 12/31/2005,5678.5972 12/31/2006,6353.4141 12/31/2007,7483.4092 12/31/2008,8769.3945 12/31/2009,7545.1118 12/31/2010,9047.2021 12/31/2011,10398.2363 12/31/2012,10806.8398 12/31/2013,10851.6641 12/31/2014,11165.2588 12/31/2015,9663.1113 12/31/2016,9523.2949 12/31/2017,9960.3232 12/31/2018,11072.3867 12/31/2019,11136.8115 12/31/2020,11484.5049 12/31/2021,12172.1621 12/31/2022,12875.417 12/31/2023,13629.3301 12/31/2024,14468.3174 ================================================ FILE: Smart Farmers project/data/cme.csv ================================================ product_id,date,expiration_date,last,change,prior_settle,open,high,low,volume,last_update 2457,7/1/2020,7/31/2020,,,534.75,,,,0,7/1/2020 20:15 2457,7/1/2020,8/31/2020,,,532,,,,0,7/1/2020 20:15 2457,7/1/2020,9/30/2020,,,532,,,,0,7/1/2020 20:15 2457,7/1/2020,10/31/2020,,,533.75,,,,0,7/1/2020 20:15 2457,7/1/2020,11/30/2020,,,535.25,,,,0,7/1/2020 20:15 2457,7/1/2020,12/31/2020,,,536.5,,,,0,7/1/2020 20:15 2457,7/1/2020,1/31/2021,,,538,,,,0,7/1/2020 20:15 2457,7/1/2020,2/28/2021,,,539,,,,0,7/1/2020 20:15 2457,7/1/2020,3/31/2021,,,538.25,,,,0,7/1/2020 20:15 2457,7/1/2020,4/30/2021,,,536.75,,,,0,7/1/2020 20:15 2457,7/1/2020,5/31/2021,,,537.75,,,,0,7/1/2020 20:15 2457,7/1/2020,6/30/2021,,,540.25,,,,0,7/1/2020 20:15 2457,7/1/2020,7/31/2021,,,541.5,,,,0,7/1/2020 20:15 2457,7/1/2020,8/31/2021,,,539,,,,0,7/1/2020 20:15 2457,7/1/2020,9/30/2021,,,537.5,,,,0,7/1/2020 20:15 2457,7/1/2020,10/31/2021,,,537,,,,0,7/1/2020 20:15 2457,7/1/2020,11/30/2021,,,533.75,,,,0,7/1/2020 20:15 2457,7/1/2020,12/31/2021,,,527.75,,,,0,7/1/2020 20:15 2457,7/1/2020,1/31/2022,,,521.5,,,,0,7/1/2020 17:57 2457,7/1/2020,2/28/2022,,,520.5,,,,0,7/1/2020 17:57 2457,7/1/2020,3/31/2022,,,519.25,,,,0,7/1/2020 17:56 2457,7/1/2020,4/30/2022,,,518.75,,,,0,7/1/2020 17:56 2457,7/1/2020,5/31/2022,,,518,,,,0,7/1/2020 17:57 2457,7/1/2020,6/30/2022,,,517.25,,,,0,7/1/2020 17:57 2457,7/1/2020,7/31/2022,,,516.25,,,,0,7/1/2020 17:56 2457,7/1/2020,8/31/2022,,,515,,,,0,7/1/2020 17:56 2457,7/1/2020,9/30/2022,,,514.25,,,,0,7/1/2020 17:57 2457,7/1/2020,10/31/2022,,,513.75,,,,0,7/1/2020 17:57 2457,7/1/2020,11/30/2022,,,512.75,,,,0,7/1/2020 17:55 2457,7/1/2020,12/31/2022,,,511.75,,,,0,7/1/2020 17:56 2457,7/1/2020,1/31/2023,,,511,,,,0,7/1/2020 17:56 2457,7/1/2020,2/28/2023,,,509.75,,,,0,7/1/2020 17:57 2457,7/1/2020,3/31/2023,,,509,,,,0,7/1/2020 17:56 2457,7/1/2020,4/30/2023,,,508.25,,,,0,7/1/2020 17:57 2457,7/1/2020,5/31/2023,,,507.5,,,,0,7/1/2020 17:55 2457,7/1/2020,6/30/2023,,,506.75,,,,0,7/1/2020 17:57 2457,7/1/2020,7/31/2023,,,506,,,,0,7/1/2020 17:56 2457,7/1/2020,8/31/2023,,,505.25,,,,0,7/1/2020 17:56 2457,7/1/2020,9/30/2023,,,539.25,,,,0,7/1/2020 17:56 2457,7/1/2020,10/31/2023,,,547,,,,0,7/1/2020 17:57 2457,7/1/2020,11/30/2023,,,508.25,,,,0,7/1/2020 17:56 2457,7/1/2020,12/31/2023,,,508.75,,,,0,7/1/2020 17:55 2457,7/1/2020,1/31/2024,,,541.25,,,,0,7/1/2020 17:56 2457,7/1/2020,2/29/2024,,,546.5,,,,0,7/1/2020 17:57 2457,7/1/2020,3/31/2024,,,573.75,,,,0,7/1/2020 17:57 2457,7/1/2020,4/30/2024,,,562.5,,,,0,7/1/2020 17:57 2457,7/1/2020,5/31/2024,,,560,,,,0,7/1/2020 17:57 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8074,7/8/2020,12/31/2020,,,578,,,,0,7/8/2020 17:43 8074,7/8/2020,1/31/2021,,,578,,,,0,7/8/2020 17:42 8074,7/8/2020,2/28/2021,,,580.5,,,,0,7/8/2020 17:42 8074,7/8/2020,3/31/2021,,,580.5,,,,0,7/8/2020 17:42 8074,7/8/2020,4/30/2021,,,580.5,,,,0,7/8/2020 17:44 8074,7/8/2020,5/31/2021,,,578,,,,0,7/8/2020 17:42 8074,7/8/2020,6/30/2021,,,578,,,,0,7/8/2020 17:44 8074,7/8/2020,7/31/2021,,,578,,,,0,7/8/2020 17:42 8074,7/8/2020,8/31/2021,,,578,,,,0,7/8/2020 17:43 8074,7/8/2020,9/30/2021,,,578,,,,0,7/8/2020 17:44 8074,7/8/2020,10/31/2021,,,578,,,,0,7/8/2020 17:42 8074,7/8/2020,11/30/2021,,,578,,,,0,7/8/2020 17:43 8074,7/8/2020,12/31/2021,,,578,,,,0,7/8/2020 17:43 8074,7/8/2020,1/31/2022,,,578,,,,0,7/8/2020 17:44 8074,7/8/2020,2/28/2022,,,578,,,,0,7/8/2020 17:42 8074,7/8/2020,3/31/2022,,,578,,,,0,7/8/2020 17:43 8074,7/8/2020,4/30/2022,,,578,,,,0,7/8/2020 17:44 8074,7/8/2020,5/31/2022,,,578,,,,0,7/8/2020 17:42 8076,7/1/2020,7/31/2020,,,180.5,,,,0,7/1/2020 17:57 8076,7/1/2020,8/31/2020,,,174.25,,,,0,7/1/2020 17:56 8076,7/1/2020,9/30/2020,,,170,,,,0,7/1/2020 17:57 8076,7/1/2020,10/31/2020,,,168.75,,,,0,7/1/2020 17:56 8076,7/1/2020,11/30/2020,,,168.5,,,,0,7/1/2020 17:56 8076,7/1/2020,12/31/2020,,,167,,,,0,7/1/2020 17:56 8076,7/1/2020,1/31/2021,,,165,,,,0,7/1/2020 17:57 8076,7/1/2020,2/28/2021,,,163,,,,0,7/1/2020 17:55 8076,7/1/2020,3/31/2021,,,159.25,,,,0,7/1/2020 17:57 8076,7/1/2020,4/30/2021,,,155,,,,0,7/1/2020 17:57 8076,7/1/2020,5/31/2021,,,154,,,,0,7/1/2020 17:57 8076,7/1/2020,6/30/2021,,,153.75,,,,0,7/1/2020 17:57 8076,7/2/2020,7/31/2020,,,182.75,,,,0,7/2/2020 18:09 8076,7/2/2020,8/31/2020,,,178,,,,0,7/2/2020 18:08 8076,7/2/2020,9/30/2020,,,173.75,,,,0,7/2/2020 18:09 8076,7/2/2020,10/31/2020,,,173.5,,,,0,7/2/2020 18:08 8076,7/2/2020,11/30/2020,,,174,,,,0,7/2/2020 18:08 8076,7/2/2020,12/31/2020,,,174.25,,,,0,7/2/2020 18:08 8076,7/2/2020,1/31/2021,,,172.75,,,,0,7/2/2020 18:09 8076,7/2/2020,2/28/2021,,,170,,,,0,7/2/2020 18:08 8076,7/2/2020,3/31/2021,,,166.75,,,,0,7/2/2020 18:09 8076,7/2/2020,4/30/2021,,,163.25,,,,0,7/2/2020 18:10 8076,7/2/2020,5/31/2021,,,161.5,,,,0,7/2/2020 18:09 8076,7/2/2020,6/30/2021,,,159.25,,,,0,7/2/2020 18:09 8076,7/5/2020,7/31/2020,,,185,,,,0,7/5/2020 13:06 8076,7/5/2020,8/31/2020,,,181.25,,,,0,7/5/2020 13:05 8076,7/5/2020,9/30/2020,,,177.5,,,,0,7/5/2020 13:07 8076,7/5/2020,10/31/2020,,,177.25,,,,0,7/5/2020 13:06 8076,7/5/2020,11/30/2020,,,178.25,,,,0,7/5/2020 13:06 8076,7/5/2020,12/31/2020,,,178,,,,0,7/5/2020 13:06 8076,7/5/2020,1/31/2021,,,175.25,,,,0,7/5/2020 13:07 8076,7/5/2020,2/28/2021,,,172.25,,,,0,7/5/2020 13:05 8076,7/5/2020,3/31/2021,,,168,,,,0,7/5/2020 13:07 8076,7/5/2020,4/30/2021,,,164,,,,0,7/5/2020 13:07 8076,7/5/2020,5/31/2021,,,162.5,,,,0,7/5/2020 13:07 8076,7/5/2020,6/30/2021,,,160.25,,,,0,7/5/2020 13:07 8076,7/6/2020,7/31/2020,,,185,,,,0,7/6/2020 18:29 8076,7/6/2020,8/31/2020,,,181.25,,,,0,7/6/2020 18:28 8076,7/6/2020,9/30/2020,,,177.5,,,,0,7/6/2020 18:29 8076,7/6/2020,10/31/2020,,,177.25,,,,0,7/6/2020 18:28 8076,7/6/2020,11/30/2020,,,178.25,,,,0,7/6/2020 18:28 8076,7/6/2020,12/31/2020,,,178,,,,0,7/6/2020 18:28 8076,7/6/2020,1/31/2021,,,175.25,,,,0,7/6/2020 18:30 8076,7/6/2020,2/28/2021,,,172.25,,,,0,7/6/2020 18:28 8076,7/6/2020,3/31/2021,,,168,,,,0,7/6/2020 18:30 8076,7/6/2020,4/30/2021,,,164,,,,0,7/6/2020 18:30 8076,7/6/2020,5/31/2021,,,162.5,,,,0,7/6/2020 18:29 8076,7/6/2020,6/30/2021,,,160.25,,,,0,7/6/2020 18:29 8076,7/7/2020,7/31/2020,,,183,,,,0,7/7/2020 18:00 8076,7/7/2020,8/31/2020,,,178.75,,,,0,7/7/2020 17:59 8076,7/7/2020,9/30/2020,,,175,,,,0,7/7/2020 18:00 8076,7/7/2020,10/31/2020,,,174,,,,0,7/7/2020 17:59 8076,7/7/2020,11/30/2020,,,174.25,,,,0,7/7/2020 17:59 8076,7/7/2020,12/31/2020,,,174,,,,0,7/7/2020 17:59 8076,7/7/2020,1/31/2021,,,171.75,,,,0,7/7/2020 18:00 8076,7/7/2020,2/28/2021,,,169.25,,,,0,7/7/2020 17:58 8076,7/7/2020,3/31/2021,,,166.5,,,,0,7/7/2020 18:00 8076,7/7/2020,4/30/2021,,,163,,,,0,7/7/2020 18:00 8076,7/7/2020,5/31/2021,,,161.75,,,,0,7/7/2020 18:00 8076,7/7/2020,6/30/2021,,,160.75,,,,0,7/7/2020 18:00 8076,7/8/2020,7/31/2020,,,179.75,,,,0,7/8/2020 17:43 8076,7/8/2020,8/31/2020,,,174.75,,,,0,7/8/2020 17:42 8076,7/8/2020,9/30/2020,,,171.5,,,,0,7/8/2020 17:43 8076,7/8/2020,10/31/2020,,,170.5,,,,0,7/8/2020 17:42 8076,7/8/2020,11/30/2020,,,170.25,,,,0,7/8/2020 17:43 8076,7/8/2020,12/31/2020,,,170,,,,0,7/8/2020 17:42 8076,7/8/2020,1/31/2021,,,168,,,,0,7/8/2020 17:44 8076,7/8/2020,2/28/2021,,,165,,,,0,7/8/2020 17:42 8076,7/8/2020,3/31/2021,,,161.5,,,,0,7/8/2020 17:44 8076,7/8/2020,4/30/2021,,,159,,,,0,7/8/2020 17:44 8076,7/8/2020,5/31/2021,,,157.25,,,,0,7/8/2020 17:43 8076,7/8/2020,6/30/2021,,,154,,,,0,7/8/2020 17:43 ================================================ FILE: Smart Farmers project/data/forecast.csv ================================================ Item,Year,production,class,area,type,lifespan,price,yield_i,eco lifespan,constant,gamma,beta,alpha Bananas,2019,451906.74695550837,Fruit Primary,37419.59560771456,Perennial,6.0,471.5596971059776,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2019,182320.67094121707,Vegetables Primary,6513.595389240896,Annual,,368.27928607869205,0.035726038937959906,0.8,5.081663891103838,0.002839710029201975,0.011502973679406305,0.00014088930766170443 Cassava,2019,47714.34497578723,"Roots and Tubers, Total",2589.5970136750875,Annual,,223.00012589252748,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.4143175380316643e-08 Cereals (Rice Milled Eqv),2019,2267911.1792598995,"Cereals, Total",812595.5925687944,Annual,,318.42385079437463,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224205e-06,0.011127306605191636,4.320552572277093e-05 "Chillies and peppers, green",2019,42697.157918263016,Vegetables Primary,3469.196580807127,Annual,,1464.2315782066657,0.0812512295888255,0.8,1035.7086425867562,0.01757105733617474,0.0070643248709759765,9.625527915760374e-09 "Cocoa, beans",2019,1805.9997798951633,stimulant,21599.997367516902,Annual,,1518.6372429942046,11.960132890365449,0.8,705.4388994711712,0.11980808648112415,-1.2139759647537153e-08,-1.0307794008680998e-08 Coconuts,2019,622983.5624643781,"Oilcrops, Oil Equivalent",85622.3948411322,Perennial,70.0,295.90202151575204,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506827e-08,2.8201595519240104e-08 Cucumbers and gherkins,2019,107275.10603533332,Vegetables Primary,5498.395183832579,Annual,,308.9837587585943,0.05125508971318627,0.8,166.22483946655962,0.015133662343010813,1.634150404204424e-07,2.100576073161531e-09 Ginger,2019,11933.96016271514,spice,1190.3960262859148,Annual,,1929.2530171628098,0.09974861739567624,0.8,0.0096566813169251,0.00020003396941839675,0.05977776316267956,1.0519745505094401e-07 Grapefruit (inc. pomelos),2019,15352.745539246192,Fruit Primary,1004.3964371071646,Perennial,50.0,641.0197096703362,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.031263403500663416,0.03720816717256728 Lemons and limes,2019,8396.366802922068,Fruit Primary,1237.1951084482853,Perennial,50.0,739.907305540065,0.1473488637987709,0.9714,5.0130500510485945,0.08952707223765867,9.68994647153527e-07,0.018605709180711458 Lettuce and chicory,2019,68653.1323714551,Vegetables Primary,3517.1965352945217,Annual,,846.5413291849304,0.05123140654769188,0.8,218.41581513200146,5.844932375604774e-06,0.025102616503896343,0.0030379289060933306 Maize,2019,91634.3675786914,"Cereals, Total",12284.395653637464,Annual,,184.66753669202512,0.13405882507006106,0.8,75.46003640087406,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2019,80504.37079912922,Fruit Primary,12773.995366564768,Perennial,300.0,1539.135785965185,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.1375158952859415e-09,0.04167946149358704,0.0025830487546855763 Oil palm fruit,2019,93901293.38429418,"Oilcrops, Oil Equivalent",4995232.926823739,Perennial,30.0,105.91176910791293,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518925,1.5001406584727444e-08,2.04633913640054e-06 Oilseeds nes,2019,243309.59395136448,"Oilcrops, Oil Equivalent",188800.79530644405,Annual,,6093.13251765217,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768398,0.07754978969801597 Okra,2019,61508.342531471324,Vegetables Primary,3862.7963909086793,Annual,,877.0574339924931,0.0628011783756365,0.8,25.81426809649961,0.06410322892582927,0.014089847348207726,0.005538105300982748 Oranges,2019,16124.362333287541,Fruit Primary,2000.3953270514498,Perennial,50.0,374.36025398315434,0.12406043015554068,0.9714,0.002341882933738424,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2019,60622.730092441525,Fruit Primary,3448.7960229948526,Perennial,5.0,362.6177399619028,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.0002290699875014984 Pepper (piper spp.),2019,36548.39306628454,spice,20009.99620383802,Annual,,5524.709048713003,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.4882468743433912 Pineapples,2019,395237.8630774801,Fruit Primary,12667.195611694871,Perennial,7.0,360.57992325469223,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.0002000215044559888 "Pumpkins, squash and gourds",2019,35481.55174012174,Vegetables Primary,2283.5968939884897,Annual,,334.1786517162297,0.06436011904761904,0.8,245.52573260861217,0.007813270275751892,1.8478048929440495e-07,6.965075806266524e-09 "Rice, paddy",2019,3262784.370198072,"Cereals, Total",800311.1926900418,Annual,,363.9806270595695,0.2452847328802969,0.8,2.382524503379601e-07,1.2207150148941924e-08,0.01877159509645604,0.00010787808718958384 "Rubber, natural",2019,938395.194747595,tobacco,1324655.992585608,Perennial,32.0,1337.5910110954972,1.4116184737517838,0.9554,0.0004869510671906789,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2019,69743.93932176496,Vegetables Primary,5389.195311322203,Annual,,474.479571014367,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.002287435784800093 Sugar cane,2019,35319.42673971392,sugar,973.195225967723,Perennial,15.0,245.51395612302778,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240212e-08 Sweet potatoes,2019,46396.746522391084,"Roots and Tubers, Total",2732.396850597054,Annual,,401.48333193238216,0.05889199255121042,0.8,3.603685012975389e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676242 "Tobacco, unmanufactured",2019,2547.5974010058617,tobacco,3334.7965979252426,Annual,,3945.785492030747,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2019,131163.4169515169,Vegetables Primary,2276.396823115812,Annual,,633.08226469097,0.017355424828229785,0.8,-1.5684319280144374e-08,0.060972796177440676,-1.1066421462337259e-08,0.00020453841180799237 Watermelons,2019,222347.92542939386,Vegetables Primary,12956.395654709728,Annual,,296.04415270484776,0.0582708187166064,0.8,36.80612043021051,0.025112082291921238,4.2861419032304196e-08,-3.3910334787244814e-08 Bananas,2020,542286.7807502913,Fruit Primary,44903.405792883845,Perennial,6.0,606.6930472597131,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2020,218783.7209908257,Vegetables Primary,7816.275735109995,Annual,,379.1916791012727,0.035726038937959906,0.8,5.081663891103838,0.002839710029201975,0.011502973679406305,0.00014088930766170443 Cassava,2020,57255.93878235474,"Roots and Tubers, Total",3107.447208196809,Annual,,223.00029141250084,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.4143175380316643e-08 Cereals (Rice Milled Eqv),2020,2443392.051855348,"Cereals, Total",875470.6226648679,Annual,,330.6374905442997,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224205e-06,0.011127306605191636,4.320552572277093e-05 "Chillies and peppers, green",2020,51236.334645512776,Vegetables Primary,4163.015189572453,Annual,,1473.2813284940064,0.0812512295888255,0.8,1035.7086425867562,0.01757105733617474,0.0070643248709759765,9.625527915760374e-09 "Cocoa, beans",2020,1445.9345061275699,stimulant,17293.56884405067,Annual,,1560.293722588964,11.960132890365449,0.8,705.4388994711712,0.11980808648112415,-1.2139759647537153e-08,-1.0307794008680998e-08 Coconuts,2020,747578.4462348856,"Oilcrops, Oil Equivalent",102746.62247112422,Perennial,70.0,305.5798614582143,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506827e-08,2.8201595519240104e-08 Cucumbers and gherkins,2020,128728.87118266294,Vegetables Primary,6598.009841144588,Annual,,314.2457463552884,0.05125508971318627,0.8,166.22483946655962,0.015133662343010813,1.634150404204424e-07,2.100576073161531e-09 Ginger,2020,14320.564261157195,spice,1428.456485376364,Annual,,1954.2036388575264,0.09974861739567624,0.8,0.0096566813169251,0.00020003396941839675,0.05977776316267956,1.0519745505094401e-07 Grapefruit (inc. pomelos),2020,18422.549468943704,Fruit Primary,1205.226974011715,Perennial,50.0,769.3605568533475,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.031263403500663416,0.03720816717256728 Lemons and limes,2020,10075.290748500356,Fruit Primary,1484.5826442337955,Perennial,50.0,802.2732516632743,0.1473488637987709,0.9714,5.0130500510485945,0.08952707223765867,9.68994647153527e-07,0.018605709180711458 Lettuce and chicory,2020,82383.29143351287,Vegetables Primary,4220.61189616728,Annual,,898.7028697757102,0.05123140654769188,0.8,218.41581513200146,5.844932375604774e-06,0.025102616503896343,0.0030379289060933306 Maize,2020,109959.13695055201,"Cereals, Total",14740.99270530894,Annual,,188.20830264711907,0.13405882507006106,0.8,75.46003640087406,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2020,96604.99771798092,Fruit Primary,15328.755209025698,Perennial,300.0,1598.0723976607787,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.1375158952859415e-09,0.04167946149358704,0.0025830487546855763 Oil palm fruit,2020,89431591.84819624,"Oilcrops, Oil Equivalent",4757459.841049337,Perennial,30.0,102.19671634843945,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518925,1.5001406584727444e-08,2.04633913640054e-06 Oilseeds nes,2020,291971.276955907,"Oilcrops, Oil Equivalent",226560.77140522533,Annual,,9870.811864306837,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768398,0.07754978969801597 Okra,2020,73809.55644562456,Vegetables Primary,4635.327120168278,Annual,,973.3356260381536,0.0628011783756365,0.8,25.81426809649961,0.06410322892582927,0.014089847348207726,0.005538105300982748 Oranges,2020,19348.85641785374,Fruit Primary,2400.427450216729,Perennial,50.0,390.9102078046001,0.12406043015554068,0.9714,0.002341882933738424,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2020,72746.2177456652,Fruit Primary,4138.495017736728,Perennial,5.0,374.3962632912153,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.0002290699875014984 Pepper (piper spp.),2020,43857.84829735077,spice,24011.87314437811,Annual,,9093.533666071558,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.4882468743433912 Pineapples,2020,474284.1814959083,Fruit Primary,15200.594537582347,Perennial,7.0,387.3375014438976,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.0002000215044559888 "Pumpkins, squash and gourds",2020,42577.057771470296,Vegetables Primary,2740.264506869182,Annual,,336.895400553967,0.06436011904761904,0.8,245.52573260861217,0.007813270275751892,1.8478048929440495e-07,6.965075806266524e-09 "Rice, paddy",2020,2901518.9340197267,"Cereals, Total",711698.2966781524,Annual,,332.8211579355216,0.2452847328802969,0.8,2.382524503379601e-07,1.2207150148941924e-08,0.01877159509645604,0.00010787808718958384 "Rubber, natural",2020,1126073.7633523045,tobacco,1589586.5271553074,Perennial,32.0,1398.8807786460043,1.4116184737517838,0.9554,0.0004869510671906789,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2020,83691.87716940971,Vegetables Primary,6466.968691806934,Annual,,520.1218012669976,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.002287435784800093 Sugar cane,2020,42381.8144664602,sugar,1167.793005548168,Perennial,15.0,253.68070251812762,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240212e-08 Sweet potatoes,2020,55675.21591684725,"Roots and Tubers, Total",3278.824401062,Annual,,419.82008557540723,0.05889199255121042,0.8,3.603685012975389e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676242 "Tobacco, unmanufactured",2020,3057.043447183243,tobacco,4001.659792615277,Annual,,4120.821878339001,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2020,157395.4898929091,Vegetables Primary,2731.6655931387845,Annual,,659.6475654331871,0.017355424828229785,0.8,-1.5684319280144374e-08,0.060972796177440676,-1.1066421462337259e-08,0.00020453841180799237 Watermelons,2020,266816.1720087724,Vegetables Primary,15547.596789782046,Annual,,304.7739678847423,0.0582708187166064,0.8,36.80612043021051,0.025112082291921238,4.2861419032304196e-08,-3.3910334787244814e-08 Bananas,2021,650743.3435148337,Fruit Primary,53884.02125612554,Perennial,6.0,768.349443648161,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2021,262539.6509653518,Vegetables Primary,9379.50179314656,Annual,,392.02763111739466,0.035726038937959906,0.8,5.081663891103838,0.002839710029201975,0.011502973679406305,0.00014088930766170443 Cassava,2021,68706.31732560173,"Roots and Tubers, Total",3728.8927314684506,Annual,,223.00049839515452,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.4143175380316643e-08 Cereals (Rice Milled Eqv),2021,2540853.4618247277,"Cereals, Total",910391.1755114318,Annual,,339.4136503305741,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224205e-06,0.011127306605191636,4.320552572277093e-05 "Chillies and peppers, green",2021,61483.40585831059,Vegetables Primary,4995.602325296532,Annual,,1488.2620419567597,0.0812512295888255,0.8,1035.7086425867562,0.01757105733617474,0.0070643248709759765,9.625527915760374e-09 "Cocoa, beans",2021,1157.302555128252,stimulant,13841.492353693378,Annual,,1642.6806138714219,11.960132890365449,0.8,705.4388994711712,0.11980808648112415,-1.2139759647537153e-08,-1.0307794008680998e-08 Coconuts,2021,897092.8144094899,"Oilcrops, Oil Equivalent",123295.7653981503,Perennial,70.0,324.717654526376,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506827e-08,2.8201595519240104e-08 Cucumbers and gherkins,2021,154473.73037201204,Vegetables Primary,7917.564908548024,Annual,,324.65263933889645,0.05125508971318627,0.8,166.22483946655962,0.015133662343010813,1.634150404204424e-07,2.100576073161531e-09 Ginger,2021,17184.532657116797,spice,1714.133373138247,Annual,,1978.8620344995434,0.09974861739567624,0.8,0.0096566813169251,0.00020003396941839675,0.05977776316267956,1.0519745505094401e-07 Grapefruit (inc. pomelos),2021,22106.529130324205,Fruit Primary,1446.2376803252587,Perennial,50.0,921.447285979225,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.031263403500663416,0.03720816717256728 Lemons and limes,2021,12090.063096434533,Fruit Primary,1781.4570605150784,Perennial,50.0,901.3238533301821,0.1473488637987709,0.9714,5.0130500510485945,0.08952707223765867,9.68994647153527e-07,0.018605709180711458 Lettuce and chicory,2021,98859.60486130982,Vegetables Primary,5064.71660779394,Annual,,959.0577256905156,0.05123140654769188,0.8,218.41581513200146,5.844932375604774e-06,0.025102616503896343,0.0030379289060933306 Maize,2021,131949.49871387813,"Cereals, Total",17688.994766166034,Annual,,195.20918948629296,0.13405882507006106,0.8,75.46003640087406,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2021,115925.81212042013,Fruit Primary,18394.476873639785,Perennial,300.0,1665.0757071046799,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.1375158952859415e-09,0.04167946149358704,0.0025830487546855763 Oil palm fruit,2021,85174648.09926526,"Oilcrops, Oil Equivalent",4531004.753841207,Perennial,30.0,104.22775690057779,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518925,1.5001406584727444e-08,2.04633913640054e-06 Oilseeds nes,2021,350365.45199119527,"Oilcrops, Oil Equivalent",271872.8633325576,Annual,,14406.80735916222,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768398,0.07754978969801597 Okra,2021,88571.15285461319,Vegetables Primary,5562.372769358328,Annual,,1104.947533208834,0.0628011783756365,0.8,25.81426809649961,0.06410322892582927,0.014089847348207726,0.005538105300982748 Oranges,2021,23218.391980322467,Fruit Primary,2880.483696598761,Perennial,50.0,423.64206590878024,0.12406043015554068,0.9714,0.002341882933738424,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2021,87294.67988583363,Fruit Primary,4966.149567328844,Perennial,5.0,393.493587744174,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.0002290699875014984 Pepper (piper spp.),2021,52629.349399988,spice,28814.210238854776,Annual,,13376.198036199341,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.4882468743433912 Pineapples,2021,569140.1017787191,Fruit Primary,18240.684087186437,Perennial,7.0,426.1753196136196,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.0002000215044559888 "Pumpkins, squash and gourds",2021,51091.901557012796,Vegetables Primary,3288.280866578576,Annual,,342.2683872171991,0.06436011904761904,0.8,245.52573260861217,0.007813270275751892,1.8478048929440495e-07,6.965075806266524e-09 "Rice, paddy",2021,2321243.534931531,"Cereals, Total",569365.6004157967,Annual,,277.9221806836401,0.2452847328802969,0.8,2.382524503379601e-07,1.2207150148941924e-08,0.01877159509645604,0.00010787808718958384 "Rubber, natural",2021,1351288.1124483559,tobacco,1907503.262893277,Perennial,32.0,1520.0979769344215,1.4116184737517838,0.9554,0.0004869510671906789,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2021,100429.6634898578,Vegetables Primary,7760.3169086880835,Annual,,582.2469451719958,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.002287435784800093 Sugar cane,2021,50857.06292420314,sugar,1401.3208993826233,Perennial,15.0,269.8325758512632,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240212e-08 Sweet potatoes,2021,66809.60371500466,"Roots and Tubers, Total",3934.5506843333746,Annual,,449.845716163145,0.05889199255121042,0.8,3.603685012975389e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676242 "Tobacco, unmanufactured",2021,3668.406236946504,tobacco,4801.93166861721,Annual,,4401.439848108871,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2021,188874.14394891472,Vegetables Primary,3277.991007301641,Annual,,708.0145370958146,0.017355424828229785,0.8,-1.5684319280144374e-08,0.060972796177440676,-1.1066421462337259e-08,0.00020453841180799237 Watermelons,2021,320178.4374135834,Vegetables Primary,18657.059683493226,Annual,,322.04068012902934,0.0582708187166064,0.8,36.80612043021051,0.025112082291921238,4.2861419032304196e-08,-3.3910334787244814e-08 Bananas,2022,780891.3549785271,Fruit Primary,64660.77108544171,Perennial,6.0,959.2761875476223,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2022,315046.75116279203,Vegetables Primary,11255.372499319674,Annual,,406.0796610815219,0.035726038937959906,0.8,5.081663891103838,0.002839710029201975,0.011502973679406305,0.00014088930766170443 Cassava,2022,82446.98638169935,"Roots and Tubers, Total",4474.639017446486,Annual,,223.00073824525091,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.4143175380316643e-08 Cereals (Rice Milled Eqv),2022,2293663.85649407,"Cereals, Total",821822.8110810127,Annual,,333.239838851955,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224205e-06,0.011127306605191636,4.320552572277093e-05 "Chillies and peppers, green",2022,73779.88251062954,Vegetables Primary,5994.706172907731,Annual,,1503.4792822117959,0.0812512295888255,0.8,1035.7086425867562,0.01757105733617474,0.0070643248709759765,9.625527915760374e-09 "Cocoa, beans",2022,926.2051866841529,stimulant,11077.537116488207,Annual,,1726.9362352158787,11.960132890365449,0.8,705.4388994711712,0.11980808648112415,-1.2139759647537153e-08,-1.0307794008680998e-08 Coconuts,2022,1076510.072950425,"Oilcrops, Oil Equivalent",147954.73921013408,Perennial,70.0,344.2902857237345,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506827e-08,2.8201595519240104e-08 Cucumbers and gherkins,2022,185367.5457033154,Vegetables Primary,9501.030184936588,Annual,,335.29559259452833,0.05125508971318627,0.8,166.22483946655962,0.015133662343010813,1.634150404204424e-07,2.100576073161531e-09 Ginger,2022,20621.293984891498,spice,2056.945563902702,Annual,,2003.2057721010283,0.09974861739567624,0.8,0.0096566813169251,0.00020003396941839675,0.05977776316267956,1.0519745505094401e-07 Grapefruit (inc. pomelos),2022,26527.36896222478,Fruit Primary,1735.4547304503785,Perennial,50.0,1100.834644519945,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.031263403500663416,0.03720816717256728 Lemons and limes,2022,14507.683200241003,Fruit Primary,2137.6906359080285,Perennial,50.0,1009.2661344494488,0.1473488637987709,0.9714,5.0130500510485945,0.08952707223765867,9.68994647153527e-07,0.018605709180711458 Lettuce and chicory,2022,118631.17919228192,Vegetables Primary,6077.642170431881,Annual,,1029.2899705117466,0.05123140654769188,0.8,218.41581513200146,5.844932375604774e-06,0.025102616503896343,0.0030379289060933306 Maize,2022,158338.53060549346,"Cereals, Total",21226.67737629236,Annual,,202.36929225281736,0.13405882507006106,0.8,75.46003640087406,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2022,139110.7865374713,Fruit Primary,22073.342416435105,Perennial,300.0,1741.838720500933,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.1375158952859415e-09,0.04167946149358704,0.0025830487546855763 Oil palm fruit,2022,81120334.87488434,"Oilcrops, Oil Equivalent",4315328.9288959475,Perennial,30.0,106.91710643762806,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518925,1.5001406584727444e-08,2.04633913640054e-06 Oilseeds nes,2022,420438.49337036296,"Oilcrops, Oil Equivalent",326247.39796177065,Annual,,19848.65601795932,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768398,0.07754978969801597 Okra,2022,106285.08389174574,Vegetables Primary,6674.828512155013,Annual,,1253.8347276493796,0.0628011783756365,0.8,25.81426809649961,0.06410322892582927,0.014089847348207726,0.005538105300982748 Oranges,2022,27861.520637221038,Fruit Primary,3456.5122350411157,Perennial,50.0,457.11639263065393,0.12406043015554068,0.9714,0.002341882933738424,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2022,104752.83634979039,Fruit Primary,5959.335134687892,Perennial,5.0,413.54286701928913,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.0002290699875014984 Pepper (piper spp.),2022,63155.17648991405,spice,34577.02885935308,Annual,,18515.40653995934,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.4882468743433912 Pineapples,2022,682967.2219404688,Fruit Primary,21888.792053811394,Perennial,7.0,469.1951580999007,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.0002000215044559888 "Pumpkins, squash and gourds",2022,61309.84975080444,Vegetables Primary,3945.9092287534104,Annual,,347.7632538059847,0.06436011904761904,0.8,245.52573260861217,0.007813270275751892,1.8478048929440495e-07,6.965075806266524e-09 "Rice, paddy",2022,1856998.3040624703,"Cereals, Total",455493.3329711274,Annual,,235.44050765480026,0.2452847328802969,0.8,2.382524503379601e-07,1.2207150148941924e-08,0.01877159509645604,0.00010787808718958384 "Rubber, natural",2022,1621545.374744175,tobacco,2289003.4070156366,Perennial,32.0,1644.0646140112528,1.4116184737517838,0.9554,0.0004869510671906789,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2022,120515.04110957719,Vegetables Primary,9312.337398883536,Annual,,652.4522945174949,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.002287435784800093 Sugar cane,2022,61027.37285774509,sugar,1681.5546966884542,Perennial,15.0,286.35082861904255,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240212e-08 Sweet potatoes,2022,80170.8995695769,"Roots and Tubers, Total",4721.424020275362,Annual,,481.91779916188756,0.05889199255121042,0.8,3.603685012975389e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676242 "Tobacco, unmanufactured",2022,4402.05967691385,tobacco,5762.281602517,Annual,,4706.364719646253,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2022,226648.53018373292,Vegetables Primary,3933.581528032546,Annual,,758.6202632612418,0.017355424828229785,0.8,-1.5684319280144374e-08,0.060972796177440676,-1.1066421462337259e-08,0.00020453841180799237 Watermelons,2022,384213.109911738,Vegetables Primary,22388.412476210455,Annual,,339.69872096648936,0.0582708187166064,0.8,36.80612043021051,0.025112082291921238,4.2861419032304196e-08,-3.3910334787244814e-08 Bananas,2023,937068.8186445624,Fruit Primary,77592.85845256603,Perennial,6.0,1185.5312720621553,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2023,378054.5729132708,Vegetables Primary,13506.392392573314,Annual,,421.67808765475957,0.035726038937959906,0.8,5.081663891103838,0.002839710029201975,0.011502973679406305,0.00014088930766170443 Cassava,2023,98933.66953206142,"Roots and Tubers, Total",5369.419517383143,Annual,,223.00101887221064,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.4143175380316643e-08 Cereals (Rice Milled Eqv),2023,1834932.6200346616,"Cereals, Total",657458.798799811,Annual,,317.85194192401406,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224205e-06,0.011127306605191636,4.320552572277093e-05 "Chillies and peppers, green",2023,88535.50773008486,Vegetables Primary,7193.61886534036,Annual,,1519.53943926242,0.0812512295888255,0.8,1035.7086425867562,0.01757105733617474,0.0070643248709759765,9.625527915760374e-09 "Cocoa, beans",2023,740.9955589094802,stimulant,8862.405355728002,Annual,,1817.2611181750665,11.960132890365449,0.8,705.4388994711712,0.11980808648112415,-1.2139759647537153e-08,-1.0307794008680998e-08 Coconuts,2023,1291808.0641501546,"Oilcrops, Oil Equivalent",177545.13408039988,Perennial,70.0,365.27345704176605,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506827e-08,2.8201595519240104e-08 Cucumbers and gherkins,2023,222439.3916784578,Vegetables Primary,11401.150976225934,Annual,,346.7052018288587,0.05125508971318627,0.8,166.22483946655962,0.015133662343010813,1.634150404204424e-07,2.100576073161531e-09 Ginger,2023,24745.326933740744,spice,2468.3121486446275,Annual,,2027.1601010158254,0.09974861739567624,0.8,0.0096566813169251,0.00020003396941839675,0.05977776316267956,1.0519745505094401e-07 Grapefruit (inc. pomelos),2023,31832.341276951574,Fruit Primary,2082.512869220609,Perennial,50.0,1313.071178892938,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.031263403500663416,0.03720816717256728 Lemons and limes,2023,17408.794434501273,Fruit Primary,2565.1660800301293,Perennial,50.0,1130.7393847864928,0.1473488637987709,0.9714,5.0130500510485945,0.08952707223765867,9.68994647153527e-07,0.018605709180711458 Lettuce and chicory,2023,142356.87474405853,Vegetables Primary,7293.142924871712,Annual,,1111.367039590281,0.05123140654769188,0.8,218.41581513200146,5.844932375604774e-06,0.025102616503896343,0.0030379289060933306 Maize,2023,190000.11759534976,"Cereals, Total",25471.192528006024,Annual,,210.04550779804168,0.13405882507006106,0.8,75.46003640087406,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2023,166932.598034789,Fruit Primary,26487.956028445584,Perennial,300.0,1830.3002827333648,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.1375158952859415e-09,0.04167946149358704,0.0025830487546855763 Oil palm fruit,2023,77259006.96933286,"Oilcrops, Oil Equivalent",4109919.2737154127,Perennial,30.0,110.79272252886068,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518925,1.5001406584727444e-08,2.04633913640054e-06 Oilseeds nes,2023,504526.14399212727,"Oilcrops, Oil Equivalent",391496.8402670048,Annual,,26377.861122982133,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768398,0.07754978969801597 Okra,2023,127541.66351856697,Vegetables Primary,8009.766760954934,Annual,,1425.4946465860467,0.0628011783756365,0.8,25.81426809649961,0.06410322892582927,0.014089847348207726,0.005538105300982748 Oranges,2023,33433.57418392632,Fruit Primary,4147.78359489508,Perennial,50.0,493.00203354251124,0.12406043015554068,0.9714,0.002341882933738424,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2023,125702.15683537853,Fruit Primary,7151.1312327021105,Perennial,5.0,435.37111606391517,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.0002290699875014984 Pepper (piper spp.),2023,75786.17041748686,spice,41492.411981206074,Annual,,24682.456160105532,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.4882468743433912 Pineapples,2023,819559.5408846624,Fruit Primary,26266.514394603248,Perennial,7.0,518.0723837296613,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.0002000215044559888 "Pumpkins, squash and gourds",2023,73570.25905806651,Vegetables Primary,4734.990631341334,Annual,,353.65393959369226,0.06436011904761904,0.8,245.52573260861217,0.007813270275751892,1.8478048929440495e-07,6.965075806266524e-09 "Rice, paddy",2023,1485600.1029021933,"Cereals, Total",364395.02440730605,Annual,,202.84950709735085,0.2452847328802969,0.8,2.382524503379601e-07,1.2207150148941924e-08,0.01877159509645604,0.00010787808718958384 "Rubber, natural",2023,1904606.5825087822,tobacco,2688577.837098648,Perennial,32.0,1776.9610617491555,1.4116184737517838,0.9554,0.0004869510671906789,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2023,144617.12251234686,Vegetables Primary,11174.733262266858,Annual,,733.3041312367563,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.002287435784800093 Sugar cane,2023,73231.34068745628,sugar,2017.824119101928,Perennial,15.0,304.0589698773846,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240212e-08 Sweet potatoes,2023,96204.02121788138,"Roots and Tubers, Total",5665.64650095996,Annual,,517.4201638004195,0.05889199255121042,0.8,3.603685012975389e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676242 "Tobacco, unmanufactured",2023,5282.336135964642,tobacco,6914.560584948536,Annual,,5048.7723320180985,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2023,271977.6164123256,Vegetables Primary,4720.287076605232,Annual,,813.8599879423767,0.017355424828229785,0.8,-1.5684319280144374e-08,0.060972796177440676,-1.1066421462337259e-08,0.00020453841180799237 Watermelons,2023,461053.7836095019,Vegetables Primary,26865.981443314762,Annual,,358.62846014879347,0.0582708187166064,0.8,36.80612043021051,0.025112082291921238,4.2861419032304196e-08,-3.3910334787244814e-08 Bananas,2024,1124475.8829901381,Fruit Primary,93110.87540868553,Perennial,6.0,1454.3301486867033,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2024,453651.9494094282,Vegetables Primary,16207.18720888265,Annual,,439.1978776498379,0.035726038937959906,0.8,5.081663891103838,0.002839710029201975,0.011502973679406305,0.00014088930766170443 Cassava,2024,118699.73116509084,"Roots and Tubers, Total",6442.181476139682,Annual,,223.00134925139446,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.4143175380316643e-08 Cereals (Rice Milled Eqv),2024,1467956.8204673312,"Cereals, Total",525970.881620825,Annual,,306.3376132094401,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224205e-06,0.011127306605191636,4.320552572277093e-05 "Chillies and peppers, green",2024,106239.39040212151,Vegetables Primary,8632.081100939638,Annual,,1537.0367669320617,0.0812512295888255,0.8,1035.7086425867562,0.01757105733617474,0.0070643248709759765,9.625527915760374e-09 "Cocoa, beans",2024,593.12630192291,stimulant,7093.869391769023,Annual,,1917.7785779594274,11.960132890365449,0.8,705.4388994711712,0.11980808648112415,-1.2139759647537153e-08,-1.0307794008680998e-08 Coconuts,2024,1550136.091244085,"Oilcrops, Oil Equivalent",213049.5448980319,Perennial,70.0,388.6249707544566,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506827e-08,2.8201595519240104e-08 Cucumbers and gherkins,2024,266916.0630811672,Vegetables Primary,13680.806759115709,Annual,,359.4023094997159,0.05125508971318627,0.8,166.22483946655962,0.015133662343010813,1.634150404204424e-07,2.100576073161531e-09 Ginger,2024,29692.180187541413,spice,2961.7539211705466,Annual,,2050.643269449633,0.09974861739567624,0.8,0.0096566813169251,0.00020003396941839675,0.05977776316267956,1.0519745505094401e-07 Grapefruit (inc. pomelos),2024,38194.183892723115,Fruit Primary,2498.7128277481042,Perennial,50.0,1564.6473138692518,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.031263403500663416,0.03720816717256728 Lemons and limes,2024,20885.478166464905,Fruit Primary,3077.451477722641,Perennial,50.0,1270.5380057624343,0.1473488637987709,0.9714,5.0130500510485945,0.08952707223765867,9.68994647153527e-07,0.018605709180711458 Lettuce and chicory,2024,170823.43919888328,Vegetables Primary,8751.525061472914,Annual,,1207.6419904307268,0.05123140654769188,0.8,218.41581513200146,5.844932375604774e-06,0.025102616503896343,0.0030379289060933306 Maize,2024,227826.18308556665,"Cereals, Total",30542.110424647683,Annual,,218.58817596826077,0.13405882507006106,0.8,75.46003640087406,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2024,200316.08084745827,Fruit Primary,31785.065372146517,Perennial,300.0,1932.7874749374107,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.1375158952859415e-09,0.04167946149358704,0.0025830487546855763 Oil palm fruit,2024,73581478.66822666,"Oilcrops, Oil Equivalent",3914287.1391948415,Perennial,30.0,116.37343500887098,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518925,1.5001406584727444e-08,2.04633913640054e-06 Oilseeds nes,2024,605431.0025075249,"Oilcrops, Oil Equivalent",469795.9209921134,Annual,,34212.123667142005,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768398,0.07754978969801597 Okra,2024,153046.30902792254,Vegetables Primary,9611.48855299535,Annual,,1626.0192467508427,0.0628011783756365,0.8,25.81426809649961,0.06410322892582927,0.014089847348207726,0.005538105300982748 Oranges,2024,40109.63444643609,Fruit Primary,4976.018502806352,Perennial,50.0,532.9371577153445,0.12406043015554068,0.9714,0.002341882933738424,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2024,150832.83574923887,Fruit Primary,8580.802667180913,Perennial,5.0,459.8168097103938,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.0002290699875014984 Pepper (piper spp.),2024,90943.10583580418,spice,49790.73086029598,Annual,,32082.788837533393,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.4882468743433912 Pineapples,2024,983460.2596317468,Fruit Primary,31519.458657333726,Perennial,7.0,574.6147667388474,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.0002000215044559888 "Pumpkins, squash and gourds",2024,88268.9812420883,Vegetables Primary,5681.0021409528545,Annual,,360.2093485732402,0.06436011904761904,0.8,245.52573260861217,0.007813270275751892,1.8478048929440495e-07,6.965075806266524e-09 "Rice, paddy",2024,1188490.4593323783,"Cereals, Total",291518.56484812376,Annual,,178.1192886825994,0.2452847328802969,0.8,2.382524503379601e-07,1.2207150148941924e-08,0.01877159509645604,0.00010787808718958384 "Rubber, natural",2024,2123623.0194230983,tobacco,2997745.485502189,Perennial,32.0,1924.854143951322,1.4116184737517838,0.9554,0.0004869510671906789,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2024,173532.87810457902,Vegetables Primary,13409.087329106407,Annual,,827.6410345462252,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.002287435784800093 Sugar cane,2024,87862.9325264705,sugar,2420.9845506393362,Perennial,15.0,323.7653712002321,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240212e-08 Sweet potatoes,2024,115435.11989039135,"Roots and Tubers, Total",6798.20422073301,Annual,,557.774434212949,0.05889199255121042,0.8,3.603685012975389e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676242 "Tobacco, unmanufactured",2024,6337.521123869176,tobacco,8295.794254937562,Annual,,5442.3244986684285,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2024,326367.5332488671,Vegetables Primary,5664.247189675498,Annual,,876.1402124726719,0.017355424828229785,0.8,-1.5684319280144374e-08,0.060972796177440676,-1.1066421462337259e-08,0.00020453841180799237 Watermelons,2024,553247.3898296951,Vegetables Primary,32238.178358201836,Annual,,379.69406866924305,0.0582708187166064,0.8,36.80612043021051,0.025112082291921238,4.2861419032304196e-08,-3.3910334787244814e-08 ================================================ FILE: Smart Farmers project/data/grand.csv ================================================ Item,Year,production,class,area,type,lifespan,price,yield_i,eco lifespan Bananas,2012,289034.0,Fruit Primary,29193.0,Perennial,6.0,372.3,0.10100195824712664,0.7619 Cabbages and other brassicas,2012,94886.0,Vegetables Primary,3528.0,Annual,,372.3,0.03718145985709167,0.8 Cassava,2012,77854.0,"Roots and Tubers, Total",2825.0,Annual,,291.4,0.0362858684203766,0.8 Cereals (Rice Milled Eqv),2012,1817389.0,"Cereals, Total",693867.0,Annual,,218.55,0.3817933309819747,0.8 "Chillies and peppers, green",2012,40097.0,Vegetables Primary,2856.0,Annual,,1392.1,0.07122727386088734,0.8 "Cocoa, beans",2012,3645.0,stimulant,11748.0,Annual,,2107.9,3.223045267489712,0.8 Coconuts,2012,624152.0,"Oilcrops, Oil Equivalent",100996.0,Perennial,70.0,372.3,0.16181314807931402,0.9796 Cucumbers and gherkins,2012,93114.0,Vegetables Primary,4607.0,Annual,,323.8,0.049476985200936484,0.8 Ginger,2012,8727.0,spice,903.0,Annual,,1699.7,0.10347198349948436,0.8 Grapefruit (inc. pomelos),2012,11357.0,Fruit Primary,1123.0,Perennial,50.0,615.1,0.09888174694021308,0.9714 Lemons and limes,2012,6086.0,Fruit Primary,967.0,Perennial,50.0,906.5,0.1588892540256326,0.9714 Lettuce and chicory,2012,39817.0,Vegetables Primary,2069.0,Annual,,841.8,0.05196272948740488,0.8 Maize,2012,83601.0,"Cereals, Total",9322.0,Annual,,194.3,0.1115058432315403,0.8 "Mangoes, mangosteens, guavas",2012,78676.0,Fruit Primary,12862.0,Perennial,300.0,841.8,0.16348060399613606,0.9952 Oil palm fruit,2012,94917736.0,"Oilcrops, Oil Equivalent",5076929.0,Perennial,30.0,199.1,0.053487674842981926,0.9524 Oilseeds nes,2012,180000.0,"Oilcrops, Oil Equivalent",145000.0,Annual,,4229.8,0.8055555555555556,0.8 Okra,2012,27660.0,Vegetables Primary,2157.0,Annual,,971.3,0.0779826464208243,0.8 Oranges,2012,16252.0,Fruit Primary,2993.0,Perennial,50.0,906.5,0.18416194929854787,0.9714 Papayas,2012,35634.0,Fruit Primary,2031.0,Perennial,5.0,323.8,0.05699612729415727,0.7143 Pepper (piper spp.),2012,26000.0,spice,10833.0,Annual,,5293.0,0.41665384615384615,0.8 Pineapples,2012,314405.0,Fruit Primary,13096.0,Perennial,7.0,356.1,0.04165328159539448,0.7959 "Pumpkins, squash and gourds",2012,17382.0,Vegetables Primary,1664.0,Annual,,323.8,0.09573121620066735,0.8 "Rice, paddy",2012,2599382.0,"Cereals, Total",684545.0,Annual,,242.8,0.2633491345250525,0.8 "Rubber, natural",2012,923020.0,tobacco,1041190.0,Perennial,32.0,3083.7,1.1280253948993522,0.9554 Spinach,2012,53038.0,Vegetables Primary,4023.0,Annual,,437.1,0.0758512764433048,0.8 Sugar cane,2012,146164.0,sugar,4346.0,Perennial,15.0,291.4,0.029733723762349142,0.9048 Sweet potatoes,2012,55838.0,"Roots and Tubers, Total",2595.0,Annual,,356.1,0.046473727569039,0.8 "Tobacco, unmanufactured",2012,1972.0,tobacco,2526.0,Annual,,4739.7,1.2809330628803246,0.8 Tomatoes,2012,129572.0,Vegetables Primary,1978.0,Annual,,550.4,0.015265643811934678,0.8 Watermelons,2012,225681.0,Vegetables Primary,11949.0,Annual,,307.6,0.052946415515705794,0.8 Bananas,2013,288677.0,Fruit Primary,27085.0,Perennial,6.0,349.1,0.09382458595592999,0.7619 Cabbages and other brassicas,2013,129148.0,Vegetables Primary,4845.0,Annual,,365.0,0.037515098956236254,0.8 Cassava,2013,62843.0,"Roots and Tubers, Total",4046.0,Annual,,301.5,0.06438266791846348,0.8 Cereals (Rice Milled Eqv),2013,1823136.0,"Cereals, Total",681399.0,Annual,,214.2,0.3737510531304302,0.8 "Chillies and peppers, green",2013,59775.0,Vegetables Primary,4104.0,Annual,,1539.2,0.06865746549560853,0.8 "Cocoa, beans",2013,2809.0,stimulant,13826.0,Annual,,2003.9,4.922036311854753,0.8 Coconuts,2013,624727.0,"Oilcrops, Oil Equivalent",87974.0,Perennial,70.0,333.2,0.14081991013674774,0.9796 Cucumbers and gherkins,2013,119857.0,Vegetables Primary,5161.0,Annual,,333.2,0.04305964607824324,0.8 Ginger,2013,8831.0,spice,893.0,Annual,,1269.5,0.10112105084361907,0.8 Grapefruit (inc. pomelos),2013,11714.0,Fruit Primary,1093.0,Perennial,50.0,460.2,0.09330715383302032,0.9714 Lemons and limes,2013,9293.0,Fruit Primary,1310.0,Perennial,50.0,777.6,0.14096631873453136,0.9714 Lettuce and chicory,2013,64993.0,Vegetables Primary,3346.0,Annual,,666.5,0.0514824673426369,0.8 Maize,2013,86499.0,"Cereals, Total",9720.0,Annual,,190.4,0.11237124128602642,0.8 "Mangoes, mangosteens, guavas",2013,69266.0,Fruit Primary,11138.0,Perennial,300.0,904.5,0.1608003926890538,0.9952 Oil palm fruit,2013,94917736.0,"Oilcrops, Oil Equivalent",5229739.0,Perennial,30.0,153.9,0.05509759524816311,0.9524 Oilseeds nes,2013,183315.0,"Oilcrops, Oil Equivalent",152119.0,Annual,,4579.4,0.8298229822982298,0.8 Okra,2013,34370.0,Vegetables Primary,2703.0,Annual,,952.1,0.07864416642420716,0.8 Oranges,2013,18666.0,Fruit Primary,3108.0,Perennial,50.0,1031.4,0.16650594664095147,0.9714 Papayas,2013,31748.0,Fruit Primary,1934.0,Perennial,5.0,365.0,0.060917223132165806,0.7143 Pepper (piper spp.),2013,26500.0,spice,9835.0,Annual,,5289.9,0.37113207547169813,0.8 Pineapples,2013,244353.0,Fruit Primary,10580.0,Perennial,7.0,380.8,0.04329801557582678,0.7959 "Pumpkins, squash and gourds",2013,32544.0,Vegetables Primary,2323.0,Annual,,333.2,0.07138028515240905,0.8 "Rice, paddy",2013,2603654.0,"Cereals, Total",671679.0,Annual,,238.0,0.25797552209318136,0.8 "Rubber, natural",2013,826424.0,tobacco,1057271.0,Perennial,32.0,2458.6,1.2793324008015257,0.9554 Spinach,2013,56649.0,Vegetables Primary,4288.0,Annual,,444.3,0.07569418701124468,0.8 Sugar cane,2013,98885.0,sugar,2847.0,Perennial,15.0,253.9,0.028791019871567982,0.9048 Sweet potatoes,2013,50748.0,"Roots and Tubers, Total",3042.0,Annual,,365.0,0.05994324899503429,0.8 "Tobacco, unmanufactured",2013,419.0,tobacco,538.0,Annual,,4345.956117624693,1.2840095465393795,0.8 Tomatoes,2013,190977.0,Vegetables Primary,2831.0,Annual,,714.1,0.014823774590657514,0.8 Watermelons,2013,209599.0,Vegetables Primary,11032.0,Annual,,349.1,0.05263383890190316,0.8 Bananas,2014,303107.0,Fruit Primary,28911.0,Perennial,6.0,580.5,0.09538215877561389,0.7619 Cabbages and other brassicas,2014,301518.0,Vegetables Primary,7937.0,Annual,,326.9,0.026323469908927494,0.8 Cassava,2014,51911.0,"Roots and Tubers, Total",3050.0,Annual,,290.3,0.05875440658049354,0.8 Cereals (Rice Milled Eqv),2014,1283020.0,"Cereals, Total",624286.0,Annual,,275.0,0.48657542360992034,0.8 "Chillies and peppers, green",2014,40521.0,Vegetables Primary,3582.0,Annual,,1399.4,0.08839860812911823,0.8 "Cocoa, beans",2014,2665.0,stimulant,16102.0,Annual,,2607.8,6.04202626641651,0.8 Coconuts,2014,595097.0,"Oilcrops, Oil Equivalent",88092.0,Perennial,70.0,275.0,0.14802964894798662,0.9796 Cucumbers and gherkins,2014,97331.0,Vegetables Primary,4661.0,Annual,,369.7,0.04788813430458949,0.8 Ginger,2014,10775.0,spice,1048.0,Annual,,2245.7,0.09726218097447796,0.8 Grapefruit (inc. pomelos),2014,11831.0,Fruit Primary,1009.0,Perennial,50.0,550.0,0.08528442228044966,0.9714 Lemons and limes,2014,7477.0,Fruit Primary,989.0,Perennial,50.0,1038.8,0.1322723017252909,0.9714 Lettuce and chicory,2014,67320.0,Vegetables Primary,3127.0,Annual,,825.0,0.046449792038027335,0.8 Maize,2014,59188.0,"Cereals, Total",9707.0,Annual,,183.3,0.16400283841319185,0.8 "Mangoes, mangosteens, guavas",2014,77198.0,Fruit Primary,11977.0,Perennial,300.0,756.2,0.1551465063861758,0.9952 Oil palm fruit,2014,95380438.0,"Oilcrops, Oil Equivalent",4689321.0,Perennial,30.0,158.6,0.0491643894526884,0.9524 Oilseeds nes,2014,187043.0,"Oilcrops, Oil Equivalent",154320.0,Annual,,4609.1,0.8250509241190528,0.8 Okra,2014,45130.0,Vegetables Primary,3120.0,Annual,,960.9,0.06913361400398847,0.8 Oranges,2014,16622.0,Fruit Primary,2965.0,Perennial,50.0,198.6,0.17837805318252917,0.9714 Papayas,2014,55358.0,Fruit Primary,2771.0,Perennial,5.0,381.9,0.050055999132916654,0.7143 Pepper (piper spp.),2014,27500.0,spice,16021.0,Annual,,6879.6,0.5825818181818182,0.8 Pineapples,2014,335725.0,Fruit Primary,9456.0,Perennial,7.0,359.0,0.028165909598629833,0.7959 "Pumpkins, squash and gourds",2014,44526.0,Vegetables Primary,2333.0,Annual,,336.1,0.0523963526928087,0.8 "Rice, paddy",2014,1834831.0,"Cereals, Total",614579.0,Annual,,366.7,0.33495128434171867,0.8 "Rubber, natural",2014,668613.0,tobacco,1065600.0,Perennial,32.0,1690.1,1.5937470554715507,0.9554 Spinach,2014,51286.0,Vegetables Primary,4386.0,Annual,,458.3,0.08552041492805054,0.8 Sugar cane,2014,9147.0,sugar,237.0,Perennial,15.0,290.3,0.025910134470318136,0.9048 Sweet potatoes,2014,51476.0,"Roots and Tubers, Total",3013.0,Annual,,397.2,0.058532131478747376,0.8 "Tobacco, unmanufactured",2014,1769.0,tobacco,2292.0,Annual,,4091.368210599639,1.295647258338044,0.8 Tomatoes,2014,162384.0,Vegetables Primary,1948.0,Annual,,718.0,0.01199625578874766,0.8 Watermelons,2014,176379.0,Vegetables Primary,10842.0,Annual,,305.5,0.06146990287959451,0.8 Bananas,2015,315500.0,Fruit Primary,24858.0,Perennial,6.0,460.9,0.07878922345483359,0.7619 Cabbages and other brassicas,2015,277202.0,Vegetables Primary,8261.0,Annual,,358.5,0.02980137228447125,0.8 Cassava,2015,67713.0,"Roots and Tubers, Total",3418.0,Annual,,268.9,0.05047775168726833,0.8 Cereals (Rice Milled Eqv),2015,1890976.0,"Cereals, Total",691589.0,Annual,,236.85000000000002,0.36573124143299546,0.8 "Chillies and peppers, green",2015,47015.0,Vegetables Primary,2915.0,Annual,,1331.5,0.062001488886525576,0.8 "Cocoa, beans",2015,1729.0,stimulant,18122.0,Annual,,2055.8,10.481203007518797,0.8 Coconuts,2015,505614.0,"Oilcrops, Oil Equivalent",73167.0,Perennial,70.0,243.2,0.14470920504574636,0.9796 Cucumbers and gherkins,2015,100817.0,Vegetables Primary,4371.0,Annual,,320.1,0.043355783250840635,0.8 Ginger,2015,12924.0,spice,965.0,Annual,,1711.631924118213,0.07466728567007118,0.8 Grapefruit (inc. pomelos),2015,10196.0,Fruit Primary,1044.0,Perennial,50.0,601.7,0.10239309533150255,0.9714 Lemons and limes,2015,7587.0,Fruit Primary,850.0,Perennial,50.0,780.9,0.11203374192698036,0.9714 Lettuce and chicory,2015,66006.0,Vegetables Primary,3182.0,Annual,,808.9104313117714,0.04820773869042208,0.8 Maize,2015,62460.0,"Cereals, Total",10030.0,Annual,,166.4,0.1605827729747038,0.8 "Mangoes, mangosteens, guavas",2015,98315.0,Fruit Primary,8344.0,Perennial,300.0,1024.2,0.08487006051975791,0.9952 Oil palm fruit,2015,98344073.0,"Oilcrops, Oil Equivalent",4859397.0,Perennial,30.0,117.5,0.0494121999604389,0.9524 Oilseeds nes,2015,192347.0,"Oilcrops, Oil Equivalent",155948.0,Annual,,3952.7,0.8107638798629561,0.8 Okra,2015,50778.0,Vegetables Primary,3326.0,Annual,,857.8,0.0655008074362913,0.8 Oranges,2015,15537.0,Fruit Primary,1643.0,Perennial,50.0,385.20868947337976,0.10574757031601982,0.9714 Papayas,2015,60625.0,Fruit Primary,2514.0,Perennial,5.0,345.7,0.0414680412371134,0.7143 Pepper (piper spp.),2015,28300.0,spice,16333.0,Annual,,7177.3,0.5771378091872792,0.8 Pineapples,2015,452021.0,Fruit Primary,10551.0,Perennial,7.0,307.3,0.023341835888155638,0.7959 "Pumpkins, squash and gourds",2015,25652.0,Vegetables Primary,1817.0,Annual,,345.7,0.07083268361141432,0.8 "Rice, paddy",2015,2741404.0,"Cereals, Total",681559.0,Annual,,307.3,0.24861676717477613,0.8 "Rubber, natural",2015,722122.0,tobacco,1074386.0,Perennial,32.0,1336.3,1.48781784795367,0.9554 Spinach,2015,48357.0,Vegetables Primary,3860.0,Annual,,422.5,0.0798229832289017,0.8 Sugar cane,2015,30271.0,sugar,1717.0,Perennial,15.0,217.6,0.05672095404842919,0.9048 Sweet potatoes,2015,50607.0,"Roots and Tubers, Total",2908.0,Annual,,371.3,0.057462406386468275,0.8 "Tobacco, unmanufactured",2015,2139.0,tobacco,2791.0,Annual,,3638.8980233955585,1.3048153342683497,0.8 Tomatoes,2015,165177.0,Vegetables Primary,1984.0,Annual,,601.7,0.012011357513455263,0.8 Watermelons,2015,178928.0,Vegetables Primary,10024.0,Annual,,268.9,0.05602253420370205,0.8 Bananas,2016,309508.0,Fruit Primary,22294.0,Perennial,6.0,433.9,0.07203044832443749,0.7619 Cabbages and other brassicas,2016,101258.0,Vegetables Primary,3774.0,Annual,,361.6,0.037271129194730294,0.8 Cassava,2016,61161.0,"Roots and Tubers, Total",3148.0,Annual,,313.4,0.051470708458004284,0.8 Cereals (Rice Milled Eqv),2016,1892184.0,"Cereals, Total",698812.0,Annual,,289.3,0.36931503490146833,0.8 "Chillies and peppers, green",2016,43738.0,Vegetables Primary,3176.0,Annual,,1518.7,0.07261420275275504,0.8 "Cocoa, beans",2016,1757.0,stimulant,17421.0,Annual,,2017.7,9.915196357427433,0.8 Coconuts,2016,504773.0,"Oilcrops, Oil Equivalent",75151.0,Perennial,70.0,241.1,0.1488807840355962,0.9796 Cucumbers and gherkins,2016,97621.0,Vegetables Primary,4359.0,Annual,,325.4,0.044652277686153596,0.8 Ginger,2016,13362.0,spice,940.0,Annual,,1918.0617150999785,0.07034875018709774,0.8 Grapefruit (inc. pomelos),2016,12858.0,Fruit Primary,910.0,Perennial,50.0,554.4,0.0707730595738062,0.9714 Lemons and limes,2016,7072.0,Fruit Primary,1013.0,Perennial,50.0,771.4,0.14324095022624433,0.9714 Lettuce and chicory,2016,65268.0,Vegetables Primary,3017.0,Annual,,809.2907573824596,0.04622479622479622,0.8 Maize,2016,64867.0,"Cereals, Total",10042.0,Annual,,176.02653721679235,0.15480907086808393,0.8 "Mangoes, mangosteens, guavas",2016,102046.0,Fruit Primary,8379.0,Perennial,300.0,1265.6,0.08211002881053643,0.9952 Oil palm fruit,2016,86325309.0,"Oilcrops, Oil Equivalent",5001438.0,Perennial,30.0,143.2,0.05793709930421448,0.9524 Oilseeds nes,2016,195130.0,"Oilcrops, Oil Equivalent",155334.0,Annual,,3869.3,0.7960539127760979,0.8 Okra,2016,49057.0,Vegetables Primary,3127.0,Annual,,771.4,0.06374217746702815,0.8 Oranges,2016,13448.0,Fruit Primary,1557.0,Perennial,50.0,303.6319254759596,0.1157792980368828,0.9714 Papayas,2016,65967.0,Fruit Primary,3980.0,Perennial,5.0,337.5,0.06033319690148104,0.7143 Pepper (piper spp.),2016,29245.0,spice,16768.0,Annual,,6364.1,0.5733629680287229,0.8 Pineapples,2016,391714.0,Fruit Primary,10354.0,Perennial,7.0,313.4,0.026432550279030107,0.7959 "Pumpkins, squash and gourds",2016,16494.0,Vegetables Primary,1128.0,Annual,,313.4,0.06838850491087668,0.8 "Rice, paddy",2016,2739606.0,"Cereals, Total",688770.0,Annual,,289.3,0.2514120643625397,0.8 "Rubber, natural",2016,673513.0,tobacco,1077993.0,Perennial,32.0,1370.3,1.600552624819417,0.9554 Spinach,2016,54823.0,Vegetables Primary,4276.0,Annual,,421.9,0.07799646133921895,0.8 Sugar cane,2016,28038.0,sugar,1515.0,Perennial,15.0,204.9,0.054033811256152364,0.9048 Sweet potatoes,2016,43212.0,"Roots and Tubers, Total",2592.0,Annual,,301.3,0.05998333796167731,0.8 "Tobacco, unmanufactured",2016,2195.0,tobacco,2864.0,Annual,,3829.529414768218,1.3047835990888383,0.8 Tomatoes,2016,242946.0,Vegetables Primary,2794.0,Annual,,482.1,0.01150049805306529,0.8 Watermelons,2016,192910.0,Vegetables Primary,11058.0,Annual,,277.2,0.05732206728526256,0.8 Bananas,2017,350493.0,Fruit Primary,27565.0,Perennial,6.0,377.9,0.07864636383608231,0.7619 Cabbages and other brassicas,2017,77342.0,Vegetables Primary,3279.0,Annual,,381.4,0.04239611078068837,0.8 Cassava,2017,44229.0,"Roots and Tubers, Total",2566.0,Annual,,305.8,0.05801623369282597,0.8 Cereals (Rice Milled Eqv),2017,2008124.0,"Cereals, Total",699745.0,Annual,,279.0,0.3484570673922527,0.8 "Chillies and peppers, green",2017,27358.0,Vegetables Primary,2835.0,Annual,,1397.5,0.103625996052343,0.8 "Cocoa, beans",2017,1029.0,stimulant,17554.0,Annual,,1436.6,17.059280855199223,0.8 Coconuts,2017,517589.0,"Oilcrops, Oil Equivalent",74008.0,Perennial,70.0,281.4,0.14298603718394323,0.9796 Cucumbers and gherkins,2017,88492.0,Vegetables Primary,4401.0,Annual,,295.3,0.04973330922569272,0.8 Ginger,2017,14279.0,spice,974.0,Annual,,1926.352662122375,0.06821205966804399,0.8 Grapefruit (inc. pomelos),2017,13037.0,Fruit Primary,892.0,Perennial,50.0,512.7,0.06842064892229807,0.9714 Lemons and limes,2017,6961.0,Fruit Primary,1011.0,Perennial,50.0,672.0,0.14523775319637983,0.9714 Lettuce and chicory,2017,40358.0,Vegetables Primary,2323.0,Annual,,880.0718990821069,0.057559839437038504,0.8 Maize,2017,72561.0,"Cereals, Total",10477.0,Annual,,181.61446377135653,0.14438885902895496,0.8 "Mangoes, mangosteens, guavas",2017,113824.0,Fruit Primary,9571.0,Perennial,300.0,959.2,0.08408595726736014,0.9952 Oil palm fruit,2017,101740900.0,"Oilcrops, Oil Equivalent",5110713.0,Perennial,30.0,140.9,0.05023263014186035,0.9524 Oilseeds nes,2017,198944.0,"Oilcrops, Oil Equivalent",156347.0,Annual,,2705.7,0.7858844700016085,0.8 Okra,2017,53937.0,Vegetables Primary,3411.0,Annual,,829.0,0.06324044718838645,0.8 Oranges,2017,13245.0,Fruit Primary,1517.0,Perennial,50.0,277.51641822220614,0.11453378633446584,0.9714 Papayas,2017,83797.0,Fruit Primary,2738.0,Perennial,5.0,317.4,0.03267420074704345,0.7143 Pepper (piper spp.),2017,30433.0,spice,17087.0,Annual,,3784.5,0.5614628856833043,0.8 Pineapples,2017,340722.0,Fruit Primary,10131.0,Perennial,7.0,337.2,0.029733917974184232,0.7959 "Pumpkins, squash and gourds",2017,23859.0,Vegetables Primary,1435.0,Annual,,306.9,0.06014501865124272,0.8 "Rice, paddy",2017,2901894.0,"Cereals, Total",689268.0,Annual,,279.0,0.23752349327714933,0.8 "Rubber, natural",2017,740138.0,tobacco,1081889.0,Perennial,32.0,1636.4,1.4617395674860634,0.9554 Spinach,2017,71180.0,Vegetables Primary,5485.0,Annual,,387.2,0.07705816240517,0.8 Sugar cane,2017,29990.0,sugar,1668.0,Perennial,15.0,218.6,0.055618539513171056,0.9048 Sweet potatoes,2017,41245.0,"Roots and Tubers, Total",2441.0,Annual,,391.8,0.05918293126439569,0.8 "Tobacco, unmanufactured",2017,2034.0,tobacco,2659.0,Annual,,3758.1754705530975,1.3072763028515242,0.8 Tomatoes,2017,188185.0,Vegetables Primary,1941.0,Annual,,538.3,0.010314318356935994,0.8 Watermelons,2017,172275.0,Vegetables Primary,9595.0,Annual,,300.0,0.05569583514729357,0.8 Bananas,2018,376589.0,Fruit Primary,31183.0,Perennial,6.0,359.3,0.0828037993674802,0.7619 Cabbages and other brassicas,2018,151934.0,Vegetables Primary,5428.0,Annual,,359.3,0.035726038937959906,0.8 Cassava,2018,39762.0,"Roots and Tubers, Total",2158.0,Annual,,223.0,0.05427292389718827,0.8 Cereals (Rice Milled Eqv),2018,1889926.0,"Cereals, Total",677163.0,Annual,,297.4,0.35830133031663675,0.8 "Chillies and peppers, green",2018,35581.0,Vegetables Primary,2891.0,Annual,,1462.2,0.0812512295888255,0.8 "Cocoa, beans",2018,1505.0,stimulant,18000.0,Annual,,1525.1,11.960132890365449,0.8 Coconuts,2018,519153.0,"Oilcrops, Oil Equivalent",71352.0,Perennial,70.0,297.4,0.13743925201241253,0.9796 Cucumbers and gherkins,2018,89396.0,Vegetables Primary,4582.0,Annual,,309.8,0.05125508971318627,0.8 Ginger,2018,9945.0,spice,992.0,Annual,,1904.0526853161766,0.09974861739567623,0.8 Grapefruit (inc. pomelos),2018,12794.0,Fruit Primary,837.0,Perennial,50.0,532.8,0.06542129123026419,0.9714 Lemons and limes,2018,6997.0,Fruit Primary,1031.0,Perennial,50.0,718.7,0.1473488637987709,0.9714 Lettuce and chicory,2018,57211.0,Vegetables Primary,2931.0,Annual,,801.194381901839,0.05123140654769188,0.8 Maize,2018,76362.0,"Cereals, Total",10237.0,Annual,,185.21444467527138,0.13405882507006103,0.8 "Mangoes, mangosteens, guavas",2018,67087.0,Fruit Primary,10645.0,Perennial,300.0,1486.9,0.15867455691862806,0.9952 Oil palm fruit,2018,98419400.0,"Oilcrops, Oil Equivalent",5235581.0,Perennial,30.0,116.0,0.05319663602907557,0.9524 Oilseeds nes,2018,202758.0,"Oilcrops, Oil Equivalent",157334.0,Annual,,2948.6,0.7759693822191973,0.8 Okra,2018,51257.0,Vegetables Primary,3219.0,Annual,,817.8,0.0628011783756365,0.8 Oranges,2018,13437.0,Fruit Primary,1667.0,Perennial,50.0,376.92771860265077,0.12406043015554068,0.9714 Papayas,2018,50519.0,Fruit Primary,2874.0,Perennial,5.0,359.3,0.05688948712365645,0.7143 Pepper (piper spp.),2018,30457.0,spice,16675.0,Annual,,2550.6,0.5474931871162623,0.8 Pineapples,2018,329365.0,Fruit Primary,10556.0,Perennial,7.0,347.0,0.03204954989145781,0.7959 "Pumpkins, squash and gourds",2018,29568.0,Vegetables Primary,1903.0,Annual,,334.6,0.06436011904761904,0.8 "Rice, paddy",2018,2718987.0,"Cereals, Total",666926.0,Annual,,297.4,0.24528473288029695,0.8 "Rubber, natural",2018,781996.0,tobacco,1103880.0,Perennial,32.0,1347.1,1.4116184737517838,0.9554 Spinach,2018,58120.0,Vegetables Primary,4491.0,Annual,,446.1,0.07727116311080523,0.8 Sugar cane,2018,29433.0,sugar,811.0,Perennial,15.0,246.78089608441445,0.027554105935514557,0.9048 Sweet potatoes,2018,38664.0,"Roots and Tubers, Total",2277.0,Annual,,396.5,0.05889199255121043,0.8 "Tobacco, unmanufactured",2018,2123.0,tobacco,2779.0,Annual,,3889.6001454970665,1.3089967027790863,0.8 Tomatoes,2018,109303.0,Vegetables Primary,1897.0,Annual,,631.9,0.017355424828229785,0.8 Watermelons,2018,185290.0,Vegetables Primary,10797.0,Annual,,297.4,0.0582708187166064,0.8 ================================================ FILE: Smart Farmers project/data/malay_gdp.csv ================================================ Area Code,Area,Item Code,Item,Element Code,Element,Year Code,Year,Unit,Value,Flag,Note 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2012,2012,,10779.504483,Fc, 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2013,2013,,10882.259575,Fc, 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2014,2014,,11183.869684000001,Fc, 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2015,2015,,9808.7171,Fc, 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2016,2016,,9659.564758,Fc, 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2017,2017,,10085.774790000001,Fc, 131,Malaysia,22014,Gross Domestic Product per capita,6119,Value US$,2018,2018,,11190.754009,Fc, ================================================ FILE: Smart Farmers project/data/malay_land.csv ================================================ Area Code,Area,Item Code,Item,Element Code,Element,Year Code,Year,Unit,Value,Flag 131,Malaysia,6620,Cropland,5110,Area,2012,2012,1000 ha,7544.2,Fm 131,Malaysia,6620,Cropland,5110,Area,2013,2013,1000 ha,7774.3,Q 131,Malaysia,6620,Cropland,5110,Area,2014,2014,1000 ha,7804.0,Fm 131,Malaysia,6620,Cropland,5110,Area,2015,2015,1000 ha,8284.97,Q 131,Malaysia,6620,Cropland,5110,Area,2016,2016,1000 ha,8305.7,Fm 131,Malaysia,6620,Cropland,5110,Area,2017,2017,1000 ha,8305.2,Fm 131,Malaysia,6620,Cropland,5110,Area,2018,2018,1000 ha,8305.2,Fm ================================================ FILE: Smart Farmers project/data/malay_pop.csv ================================================ Area Code,Area,Item Code,Item,Element Code,Element,Year Code,Year,Unit,Value,Flag,Note 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2012,2012,1000 persons,29068.189,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2013,2013,1000 persons,29468.923,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2014,2014,1000 persons,29866.603,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2015,2015,1000 persons,30270.962,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2016,2016,1000 persons,30684.654,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2017,2017,1000 persons,31104.646,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2018,2018,1000 persons,31528.033,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2019,2019,1000 persons,31949.777,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2020,2020,1000 persons,32365.999,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2021,2021,1000 persons,32776.194,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2022,2022,1000 persons,33181.072,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2023,2023,1000 persons,33579.265,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2024,2024,1000 persons,33969.29,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2025,2025,1000 persons,34349.936,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2026,2026,1000 persons,34720.347,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2027,2027,1000 persons,35080.112,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2028,2028,1000 persons,35429.087,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2029,2029,1000 persons,35767.388,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2030,2030,1000 persons,36095.054,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2031,2031,1000 persons,36411.996,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2032,2032,1000 persons,36717.9,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2033,2033,1000 persons,37012.445,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2034,2034,1000 persons,37295.251,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2035,2035,1000 persons,37566.148,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2036,2036,1000 persons,37825.112,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2037,2037,1000 persons,38072.527,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2038,2038,1000 persons,38309.22,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2039,2039,1000 persons,38536.264,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2040,2040,1000 persons,38754.574,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2041,2041,1000 persons,38964.542,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2042,2042,1000 persons,39166.396,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2043,2043,1000 persons,39360.773,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2044,2044,1000 persons,39548.354,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2045,2045,1000 persons,39729.699,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2046,2046,1000 persons,39905.062,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2047,2047,1000 persons,40074.631,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2048,2048,1000 persons,40238.61,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2049,2049,1000 persons,40397.168,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2050,2050,1000 persons,40550.365,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2051,2051,1000 persons,40698.294,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2052,2052,1000 persons,40840.8,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2053,2053,1000 persons,40977.445,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2054,2054,1000 persons,41107.613,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2055,2055,1000 persons,41230.759,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2056,2056,1000 persons,41346.675,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2057,2057,1000 persons,41455.194,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2058,2058,1000 persons,41555.888,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2059,2059,1000 persons,41648.244,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2060,2060,1000 persons,41731.877,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2061,2061,1000 persons,41806.614,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2062,2062,1000 persons,41872.362,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2063,2063,1000 persons,41928.871,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2064,2064,1000 persons,41975.9,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2065,2065,1000 persons,42013.361,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2066,2066,1000 persons,42041.225,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2067,2067,1000 persons,42059.669,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2068,2068,1000 persons,42068.988,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2069,2069,1000 persons,42069.605,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2070,2070,1000 persons,42061.944,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2071,2071,1000 persons,42046.292,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2072,2072,1000 persons,42022.971,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2073,2073,1000 persons,41992.517,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2074,2074,1000 persons,41955.499,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2075,2075,1000 persons,41912.491,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2076,2076,1000 persons,41863.892,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2077,2077,1000 persons,41810.176,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2078,2078,1000 persons,41752.0,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2079,2079,1000 persons,41690.087,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2080,2080,1000 persons,41625.092,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2081,2081,1000 persons,41557.426,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2082,2082,1000 persons,41487.446,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2083,2083,1000 persons,41415.604,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2084,2084,1000 persons,41342.328,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2085,2085,1000 persons,41267.997,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2086,2086,1000 persons,41192.896,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2087,2087,1000 persons,41117.199,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2088,2088,1000 persons,41040.987,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2089,2089,1000 persons,40964.235,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2090,2090,1000 persons,40886.939,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2091,2091,1000 persons,40809.104,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2092,2092,1000 persons,40730.761,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2093,2093,1000 persons,40651.951,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2094,2094,1000 persons,40572.639,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2095,2095,1000 persons,40492.785,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2096,2096,1000 persons,40412.247,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2097,2097,1000 persons,40330.825,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2098,2098,1000 persons,40248.246,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2099,2099,1000 persons,40164.17,X, 131,Malaysia,3010,Population - Est. & Proj.,511,Total Population - Both sexes,2100,2100,1000 persons,40078.168,X, ================================================ FILE: Smart Farmers project/data/malay_prix.csv ================================================ Area Code,Area,Item Code,Item,Element Code,Element,Year Code,Year,Months Code,Months,Unit,Value,Flag 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,372.3, 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,349.1, 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,580.5, 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,460.9, 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,433.9, 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,377.9, 131,Malaysia,486,Bananas,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,359.3, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,372.3, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,365.0, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,326.9, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,358.5, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,361.6, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,381.4, 131,Malaysia,358,Cabbages and other brassicas,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,359.3, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,291.4, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,301.5, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,290.3, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,268.9, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,313.4, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,305.8, 131,Malaysia,125,Cassava,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,223.0, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,1392.1, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,1539.2, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,1399.4, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,1331.5, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,1518.7, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,1397.5, 131,Malaysia,401,"Chillies and peppers, green",5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,1462.2, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,2107.9, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,2003.9, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,2607.8, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,2055.8, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,2017.7, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,1436.6, 131,Malaysia,661,"Cocoa, beans",5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,1525.1, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,372.3, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,333.2, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,275.0, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,243.2, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,241.1, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,281.4, 131,Malaysia,249,Coconuts,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,297.4, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,323.8, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,333.2, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,369.7, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,320.1, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,325.4, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,295.3, 131,Malaysia,397,Cucumbers and gherkins,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,309.8, 131,Malaysia,720,Ginger,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,1699.7, 131,Malaysia,720,Ginger,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,1269.5, 131,Malaysia,720,Ginger,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,2245.7, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,615.1, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,460.2, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,550.0, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,601.7, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,554.4, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,512.7, 131,Malaysia,507,Grapefruit (inc. pomelos),5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,532.8, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,906.5, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,777.6, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,1038.8, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,780.9, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,771.4, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,672.0, 131,Malaysia,497,Lemons and limes,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,718.7, 131,Malaysia,372,Lettuce and chicory,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,841.8, 131,Malaysia,372,Lettuce and chicory,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,666.5, 131,Malaysia,372,Lettuce and chicory,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,825.0, 131,Malaysia,56,Maize,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,194.3, 131,Malaysia,56,Maize,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,190.4, 131,Malaysia,56,Maize,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,183.3, 131,Malaysia,56,Maize,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,166.4, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,841.8, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,904.5, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,756.2, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,1024.2, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,1265.6, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,959.2, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,1486.9, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,199.1, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,153.9, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,158.6, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,117.5, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,143.2, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,140.9, 131,Malaysia,254,Oil palm fruit,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,116.0, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,971.3, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,952.1, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,960.9, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,857.8, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,771.4, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,829.0, 131,Malaysia,430,Okra,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,817.8, 131,Malaysia,490,Oranges,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,906.5, 131,Malaysia,490,Oranges,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,1031.4, 131,Malaysia,490,Oranges,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,198.6, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,323.8, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,365.0, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,381.9, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,345.7, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,337.5, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,317.4, 131,Malaysia,600,Papayas,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,359.3, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,5293.0, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,5289.9, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,6879.6, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,7177.3, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,6364.1, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,3784.5, 131,Malaysia,687,Pepper (piper spp.),5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,2550.6, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,356.1, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,380.8, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,359.0, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,307.3, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,313.4, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,337.2, 131,Malaysia,574,Pineapples,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,347.0, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,323.8, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,333.2, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,336.1, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,345.7, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,313.4, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,306.9, 131,Malaysia,394,"Pumpkins, squash and gourds",5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,334.6, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,242.8, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,238.0, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,366.7, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,307.3, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,289.3, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,279.0, 131,Malaysia,27,"Rice, paddy",5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,297.4, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,3083.7, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,2458.6, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,1690.1, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,1336.3, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,1370.3, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,1636.4, 131,Malaysia,836,"Rubber, natural",5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,1347.1, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,437.1, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,444.3, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,458.3, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,422.5, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,421.9, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,387.2, 131,Malaysia,373,Spinach,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,446.1, 131,Malaysia,156,Sugar cane,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,291.4, 131,Malaysia,156,Sugar cane,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,253.9, 131,Malaysia,156,Sugar cane,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,290.3, 131,Malaysia,156,Sugar cane,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,217.6, 131,Malaysia,156,Sugar cane,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,204.9, 131,Malaysia,156,Sugar cane,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,218.6, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,356.1, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,365.0, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,397.2, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,371.3, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,301.3, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,391.8, 131,Malaysia,122,Sweet potatoes,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,396.5, 131,Malaysia,826,"Tobacco, unmanufactured",5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,4739.7, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,550.4, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,714.1, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,718.0, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,601.7, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,482.1, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,538.3, 131,Malaysia,388,Tomatoes,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,631.9, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,307.6, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,349.1, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,305.5, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,268.9, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,277.2, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,300.0, 131,Malaysia,567,Watermelons,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,297.4, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,4229.8, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,4579.4, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,4609.1, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,3952.7, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,3869.3, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,2705.7, 11,Austria,339,Oilseeds nes,5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,2948.6, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2012,2012,7021,Annual value,USD,218.55, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2013,2013,7021,Annual value,USD,214.2, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2014,2014,7021,Annual value,USD,275.0, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2015,2015,7021,Annual value,USD,236.85000000000002, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2016,2016,7021,Annual value,USD,289.3, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2017,2017,7021,Annual value,USD,279.0, 11,Austria,1817,Cereals (Rice Milled Eqv),5532,Producer Price (USD/tonne),2018,2018,7021,Annual value,USD,297.4, ================================================ FILE: Smart Farmers project/data/malay_prod.csv ================================================ Area Code,Area,Item Code,Item,Element Code,Element,Year Code,Year,Unit,Value,Flag,COMMODITY,"DEFINITIONS, COVERAGE, REMARKS",subclass,subclass code,class,class code,type,lifespan 131,Malaysia,486,Bananas,5312,Area harvested,2012,2012,ha,29193.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5312,Area harvested,2013,2013,ha,27085.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5312,Area harvested,2014,2014,ha,28911.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5312,Area harvested,2015,2015,ha,24858.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5312,Area harvested,2016,2016,ha,22294.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5312,Area harvested,2017,2017,ha,27565.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5312,Area harvested,2018,2018,ha,31183.0,Im,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2012,2012,tonnes,289034.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2013,2013,tonnes,288677.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2014,2014,tonnes,303107.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2015,2015,tonnes,315500.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2016,2016,tonnes,309508.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2017,2017,tonnes,350493.0,,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,486,Bananas,5510,Production,2018,2018,tonnes,376589.0,Im,"BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",,,Fruit Primary,1738.0,Perennial,6.0 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2012,2012,ha,3528.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2013,2013,ha,4845.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2014,2014,ha,7937.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2015,2015,ha,8261.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2016,2016,ha,3774.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2017,2017,ha,3279.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5312,Area harvested,2018,2018,ha,5428.0,Im,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2012,2012,tonnes,94886.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2013,2013,tonnes,129148.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2014,2014,tonnes,301518.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2015,2015,tonnes,277202.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2016,2016,tonnes,101258.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2017,2017,tonnes,77342.0,,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,358,Cabbages and other brassicas,5510,Production,2018,2018,tonnes,151934.0,Im,"CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2012,2012,ha,2825.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2013,2013,ha,4046.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2014,2014,ha,3050.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2015,2015,ha,3418.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2016,2016,ha,3148.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2017,2017,ha,2566.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5312,Area harvested,2018,2018,ha,2158.0,Im,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2012,2012,tonnes,77854.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2013,2013,tonnes,62843.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2014,2014,tonnes,51911.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2015,2015,tonnes,67713.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2016,2016,tonnes,61161.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2017,2017,tonnes,44229.0,,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,125,Cassava,5510,Production,2018,2018,tonnes,39762.0,Im,"CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2012,2012,ha,2856.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2013,2013,ha,4104.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2014,2014,ha,3582.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2015,2015,ha,2915.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2016,2016,ha,3176.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2017,2017,ha,2835.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5312,Area harvested,2018,2018,ha,2891.0,Im,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2012,2012,tonnes,40097.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2013,2013,tonnes,59775.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2014,2014,tonnes,40521.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2015,2015,tonnes,47015.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2016,2016,tonnes,43738.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2017,2017,tonnes,27358.0,,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,401,"Chillies and peppers, green",5510,Production,2018,2018,tonnes,35581.0,Im,"CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2012,2012,ha,11748.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2013,2013,ha,13826.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2014,2014,ha,16102.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2015,2015,ha,18122.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2016,2016,ha,17421.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2017,2017,ha,17554.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5312,Area harvested,2018,2018,ha,18000.0,F,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2012,2012,tonnes,3645.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2013,2013,tonnes,2809.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2014,2014,tonnes,2665.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2015,2015,tonnes,1729.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2016,2016,tonnes,1757.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2017,2017,tonnes,1029.0,,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,661,"Cocoa, beans",5510,Production,2018,2018,tonnes,1505.0,Im,"COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.",,,stimulant,,Annual, 131,Malaysia,249,Coconuts,5312,Area harvested,2012,2012,ha,100996.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5312,Area harvested,2013,2013,ha,87974.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5312,Area harvested,2014,2014,ha,88092.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5312,Area harvested,2015,2015,ha,73167.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5312,Area harvested,2016,2016,ha,75151.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5312,Area harvested,2017,2017,ha,74008.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5312,Area harvested,2018,2018,ha,71352.0,Im,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2012,2012,tonnes,624152.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2013,2013,tonnes,624727.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2014,2014,tonnes,595097.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2015,2015,tonnes,505614.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2016,2016,tonnes,504773.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2017,2017,tonnes,517589.0,,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,249,Coconuts,5510,Production,2018,2018,tonnes,519153.0,Im,"COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2012,2012,ha,4607.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2013,2013,ha,5161.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2014,2014,ha,4661.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2015,2015,ha,4371.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2016,2016,ha,4359.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2017,2017,ha,4401.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5312,Area harvested,2018,2018,ha,4582.0,Im,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2012,2012,tonnes,93114.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2013,2013,tonnes,119857.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2014,2014,tonnes,97331.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2015,2015,tonnes,100817.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2016,2016,tonnes,97621.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2017,2017,tonnes,88492.0,,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,397,Cucumbers and gherkins,5510,Production,2018,2018,tonnes,89396.0,Im,"CUCUMBERS, GHERKINS Cucumis sativus",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2012,2012,ha,903.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2013,2013,ha,893.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2014,2014,ha,1048.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2015,2015,ha,965.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2016,2016,ha,940.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2017,2017,ha,974.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5312,Area harvested,2018,2018,ha,992.0,Im,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2012,2012,tonnes,8727.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2013,2013,tonnes,8831.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2014,2014,tonnes,10775.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2015,2015,tonnes,12924.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2016,2016,tonnes,13362.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2017,2017,tonnes,14279.0,,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,720,Ginger,5510,Production,2018,2018,tonnes,9945.0,Im,"GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",,,spice,,Annual, 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2012,2012,ha,1123.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2013,2013,ha,1093.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2014,2014,ha,1009.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2015,2015,ha,1044.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2016,2016,ha,910.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2017,2017,ha,892.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5312,Area harvested,2018,2018,ha,837.0,Im,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2012,2012,tonnes,11357.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2013,2013,tonnes,11714.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2014,2014,tonnes,11831.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2015,2015,tonnes,10196.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2016,2016,tonnes,12858.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2017,2017,tonnes,13037.0,,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,507,Grapefruit (inc. pomelos),5510,Production,2018,2018,tonnes,12794.0,Im,"GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2012,2012,ha,967.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2013,2013,ha,1310.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2014,2014,ha,989.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2015,2015,ha,850.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2016,2016,ha,1013.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2017,2017,ha,1011.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5312,Area harvested,2018,2018,ha,1031.0,Im,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2012,2012,tonnes,6086.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2013,2013,tonnes,9293.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2014,2014,tonnes,7477.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2015,2015,tonnes,7587.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2016,2016,tonnes,7072.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2017,2017,tonnes,6961.0,,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,497,Lemons and limes,5510,Production,2018,2018,tonnes,6997.0,Im,"LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2012,2012,ha,2069.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2013,2013,ha,3346.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2014,2014,ha,3127.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2015,2015,ha,3182.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2016,2016,ha,3017.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2017,2017,ha,2323.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5312,Area harvested,2018,2018,ha,2931.0,Im,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2012,2012,tonnes,39817.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2013,2013,tonnes,64993.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2014,2014,tonnes,67320.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2015,2015,tonnes,66006.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2016,2016,tonnes,65268.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2017,2017,tonnes,40358.0,,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,372,Lettuce and chicory,5510,Production,2018,2018,tonnes,57211.0,Im,"LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2012,2012,ha,9322.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2013,2013,ha,9720.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2014,2014,ha,9707.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2015,2015,ha,10030.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2016,2016,ha,10042.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2017,2017,ha,10477.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5312,Area harvested,2018,2018,ha,10237.0,Im,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2012,2012,tonnes,83601.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2013,2013,tonnes,86499.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2014,2014,tonnes,59188.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2015,2015,tonnes,62460.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2016,2016,tonnes,64867.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2017,2017,tonnes,72561.0,,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,56,Maize,5510,Production,2018,2018,tonnes,76362.0,Im,"MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2012,2012,ha,12862.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2013,2013,ha,11138.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2014,2014,ha,11977.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2015,2015,ha,8344.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2016,2016,ha,8379.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2017,2017,ha,9571.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5312,Area harvested,2018,2018,ha,10645.0,Im,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2012,2012,tonnes,78676.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2013,2013,tonnes,69266.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2014,2014,tonnes,77198.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2015,2015,tonnes,98315.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2016,2016,tonnes,102046.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2017,2017,tonnes,113824.0,,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,571,"Mangoes, mangosteens, guavas",5510,Production,2018,2018,tonnes,67087.0,Im,"MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.",,,Fruit Primary,1738.0,Perennial,300.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2012,2012,ha,5076929.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2013,2013,ha,5229739.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2014,2014,ha,4689321.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2015,2015,ha,4859397.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2016,2016,ha,5001438.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2017,2017,ha,5110713.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5312,Area harvested,2018,2018,ha,5235581.0,Im,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2012,2012,tonnes,94917736.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2013,2013,tonnes,94917736.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2014,2014,tonnes,95380438.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2015,2015,tonnes,98344073.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2016,2016,tonnes,86325309.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2017,2017,tonnes,101740900.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,254,Oil palm fruit,5510,Production,2018,2018,tonnes,98419400.0,,"[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2012,2012,ha,145000.0,F,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2013,2013,ha,152119.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2014,2014,ha,154320.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2015,2015,ha,155948.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2016,2016,ha,155334.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2017,2017,ha,156347.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5312,Area harvested,2018,2018,ha,157334.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2012,2012,tonnes,180000.0,F,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2013,2013,tonnes,183315.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2014,2014,tonnes,187043.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2015,2015,tonnes,192347.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2016,2016,tonnes,195130.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2017,2017,tonnes,198944.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,339,Oilseeds nes,5510,Production,2018,2018,tonnes,202758.0,Im,"OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",,,"Oilcrops, Oil Equivalent",1732.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2012,2012,ha,2157.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2013,2013,ha,2703.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2014,2014,ha,3120.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2015,2015,ha,3326.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2016,2016,ha,3127.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2017,2017,ha,3411.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5312,Area harvested,2018,2018,ha,3219.0,Im,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2012,2012,tonnes,27660.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2013,2013,tonnes,34370.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2014,2014,tonnes,45130.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2015,2015,tonnes,50778.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2016,2016,tonnes,49057.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2017,2017,tonnes,53937.0,,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,430,Okra,5510,Production,2018,2018,tonnes,51257.0,Im,"OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,490,Oranges,5312,Area harvested,2012,2012,ha,2993.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5312,Area harvested,2013,2013,ha,3108.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5312,Area harvested,2014,2014,ha,2965.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5312,Area harvested,2015,2015,ha,1643.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5312,Area harvested,2016,2016,ha,1557.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5312,Area harvested,2017,2017,ha,1517.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5312,Area harvested,2018,2018,ha,1667.0,Im,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2012,2012,tonnes,16252.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2013,2013,tonnes,18666.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2014,2014,tonnes,16622.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2015,2015,tonnes,15537.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2016,2016,tonnes,13448.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2017,2017,tonnes,13245.0,,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,490,Oranges,5510,Production,2018,2018,tonnes,13437.0,Im,"ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 131,Malaysia,600,Papayas,5312,Area harvested,2012,2012,ha,2031.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5312,Area harvested,2013,2013,ha,1934.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5312,Area harvested,2014,2014,ha,2771.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5312,Area harvested,2015,2015,ha,2514.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5312,Area harvested,2016,2016,ha,3980.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5312,Area harvested,2017,2017,ha,2738.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5312,Area harvested,2018,2018,ha,2874.0,Im,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2012,2012,tonnes,35634.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2013,2013,tonnes,31748.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2014,2014,tonnes,55358.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2015,2015,tonnes,60625.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2016,2016,tonnes,65967.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2017,2017,tonnes,83797.0,,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,600,Papayas,5510,Production,2018,2018,tonnes,50519.0,Im,"PAPAYAS Carica papaya",,,,Fruit Primary,1738.0,Perennial,5.0 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2012,2012,ha,10833.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2013,2013,ha,9835.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2014,2014,ha,16021.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2015,2015,ha,16333.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2016,2016,ha,16768.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2017,2017,ha,17087.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5312,Area harvested,2018,2018,ha,16675.0,Im,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2012,2012,tonnes,26000.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2013,2013,tonnes,26500.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2014,2014,tonnes,27500.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2015,2015,tonnes,28300.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2016,2016,tonnes,29245.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2017,2017,tonnes,30433.0,,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,687,Pepper (piper spp.),5510,Production,2018,2018,tonnes,30457.0,Im,"PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",,,spice,,Annual, 131,Malaysia,574,Pineapples,5312,Area harvested,2012,2012,ha,13096.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5312,Area harvested,2013,2013,ha,10580.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5312,Area harvested,2014,2014,ha,9456.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5312,Area harvested,2015,2015,ha,10551.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5312,Area harvested,2016,2016,ha,10354.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5312,Area harvested,2017,2017,ha,10131.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5312,Area harvested,2018,2018,ha,10556.0,Im,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2012,2012,tonnes,314405.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2013,2013,tonnes,244353.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2014,2014,tonnes,335725.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2015,2015,tonnes,452021.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2016,2016,tonnes,391714.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2017,2017,tonnes,340722.0,,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,574,Pineapples,5510,Production,2018,2018,tonnes,329365.0,Im,"PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,,,Fruit Primary,1738.0,Perennial,7.0 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2012,2012,ha,1664.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2013,2013,ha,2323.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2014,2014,ha,2333.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2015,2015,ha,1817.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2016,2016,ha,1128.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2017,2017,ha,1435.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5312,Area harvested,2018,2018,ha,1903.0,Im,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2012,2012,tonnes,17382.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2013,2013,tonnes,32544.0,Im,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2014,2014,tonnes,44526.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2015,2015,tonnes,25652.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2016,2016,tonnes,16494.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2017,2017,tonnes,23859.0,,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,394,"Pumpkins, squash and gourds",5510,Production,2018,2018,tonnes,29568.0,Im,"PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2012,2012,ha,684545.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2013,2013,ha,671679.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2014,2014,ha,614579.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2015,2015,ha,681559.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2016,2016,ha,688770.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2017,2017,ha,689268.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5312,Area harvested,2018,2018,ha,666926.0,Im,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2012,2012,tonnes,2599382.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2013,2013,tonnes,2603654.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2014,2014,tonnes,1834831.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2015,2015,tonnes,2741404.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2016,2016,tonnes,2739606.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2017,2017,tonnes,2901894.0,,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,27,"Rice, paddy",5510,Production,2018,2018,tonnes,2718987.0,Im,"RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.",,,"Cereals, Total",1717.0,Annual, 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2012,2012,ha,1041190.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2013,2013,ha,1057271.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2014,2014,ha,1065600.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2015,2015,ha,1074386.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2016,2016,ha,1077993.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2017,2017,ha,1081889.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5312,Area harvested,2018,2018,ha,1103880.0,Im,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2012,2012,tonnes,923020.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2013,2013,tonnes,826424.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2014,2014,tonnes,668613.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2015,2015,tonnes,722122.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2016,2016,tonnes,673513.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2017,2017,tonnes,740138.0,,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,836,"Rubber, natural",5510,Production,2018,2018,tonnes,781996.0,Im,"NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.",,,tobacco,,Perennial,32.0 131,Malaysia,373,Spinach,5312,Area harvested,2012,2012,ha,4023.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5312,Area harvested,2013,2013,ha,4288.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5312,Area harvested,2014,2014,ha,4386.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5312,Area harvested,2015,2015,ha,3860.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5312,Area harvested,2016,2016,ha,4276.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5312,Area harvested,2017,2017,ha,5485.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5312,Area harvested,2018,2018,ha,4491.0,Im,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2012,2012,tonnes,53038.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2013,2013,tonnes,56649.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2014,2014,tonnes,51286.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2015,2015,tonnes,48357.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2016,2016,tonnes,54823.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2017,2017,tonnes,71180.0,,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,373,Spinach,5510,Production,2018,2018,tonnes,58120.0,Im,"SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",,,Vegetables Primary,1735.0,Annual, 131,Malaysia,156,Sugar cane,5312,Area harvested,2012,2012,ha,4346.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5312,Area harvested,2013,2013,ha,2847.0,Im,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5312,Area harvested,2014,2014,ha,237.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5312,Area harvested,2015,2015,ha,1717.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5312,Area harvested,2016,2016,ha,1515.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5312,Area harvested,2017,2017,ha,1668.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5312,Area harvested,2018,2018,ha,811.0,Im,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2012,2012,tonnes,146164.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2013,2013,tonnes,98885.0,Im,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2014,2014,tonnes,9147.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2015,2015,tonnes,30271.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2016,2016,tonnes,28038.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2017,2017,tonnes,29990.0,,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,156,Sugar cane,5510,Production,2018,2018,tonnes,29433.0,Im,"SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",,,sugar,,Perennial,15.0 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2012,2012,ha,2595.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2013,2013,ha,3042.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2014,2014,ha,3013.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2015,2015,ha,2908.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2016,2016,ha,2592.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2017,2017,ha,2441.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5312,Area harvested,2018,2018,ha,2277.0,Im,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2012,2012,tonnes,55838.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2013,2013,tonnes,50748.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2014,2014,tonnes,51476.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2015,2015,tonnes,50607.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2016,2016,tonnes,43212.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2017,2017,tonnes,41245.0,,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,122,Sweet potatoes,5510,Production,2018,2018,tonnes,38664.0,Im,"SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",,,"Roots and Tubers, Total",1720.0,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2012,2012,ha,2526.0,,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2013,2013,ha,538.0,,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2014,2014,ha,2292.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2015,2015,ha,2791.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2016,2016,ha,2864.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2017,2017,ha,2659.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5312,Area harvested,2018,2018,ha,2779.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2012,2012,tonnes,1972.0,,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2013,2013,tonnes,419.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2014,2014,tonnes,1769.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2015,2015,tonnes,2139.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2016,2016,tonnes,2195.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2017,2017,tonnes,2034.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,826,"Tobacco, unmanufactured",5510,Production,2018,2018,tonnes,2123.0,Im,"TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.",,,tobacco,,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2012,2012,ha,1978.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2013,2013,ha,2831.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2014,2014,ha,1948.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2015,2015,ha,1984.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2016,2016,ha,2794.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2017,2017,ha,1941.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5312,Area harvested,2018,2018,ha,1897.0,Im,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2012,2012,tonnes,129572.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2013,2013,tonnes,190977.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2014,2014,tonnes,162384.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2015,2015,tonnes,165177.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2016,2016,tonnes,242946.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2017,2017,tonnes,188185.0,,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,388,Tomatoes,5510,Production,2018,2018,tonnes,109303.0,Im,"TOMATOES, FRESH Lycopersicon esculentum",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2012,2012,ha,11949.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2013,2013,ha,11032.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2014,2014,ha,10842.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2015,2015,ha,10024.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2016,2016,ha,11058.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2017,2017,ha,9595.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5312,Area harvested,2018,2018,ha,10797.0,Im,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2012,2012,tonnes,225681.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2013,2013,tonnes,209599.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2014,2014,tonnes,176379.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2015,2015,tonnes,178928.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2016,2016,tonnes,192910.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2017,2017,tonnes,172275.0,,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,567,Watermelons,5510,Production,2018,2018,tonnes,185290.0,Im,"WATERMELONS Citrullus vulgaris",,,,Vegetables Primary,1735.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2012,2012,ha,693867.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2013,2013,ha,681399.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2014,2014,ha,624286.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2015,2015,ha,691589.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2016,2016,ha,698812.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2017,2017,ha,699745.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5312,Area harvested,2018,2018,ha,677163.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2012,2012,tonnes,1817389.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2013,2013,tonnes,1823136.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2014,2014,tonnes,1283020.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2015,2015,tonnes,1890976.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2016,2016,tonnes,1892184.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2017,2017,tonnes,2008124.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, 131,Malaysia,1817,Cereals (Rice Milled Eqv),5510,Production,2018,2018,tonnes,1889926.0,A,Cereals (Rice Milled Eqv),,,,"Cereals, Total",1717.0,Annual, ================================================ FILE: Smart Farmers project/data/mapping.csv ================================================ COMMODITY,"DEFINITIONS, COVERAGE, REMARKS",Item,Item Code,subclass,subclass code,class,class code,type,lifespan Cereals (Rice Milled Eqv),,Cereals (Rice Milled Eqv),1817,,,"Cereals, Total",1717.0,Annual, "WHEAT Triticum spp.: common (T. aestivum) durum (T. durum) spelt (T. spelta)","Common and durum wheat are the main types. Among common wheat, the main varieties are spring and winter, hard and soft, and red and white. At the national level, different varieties should be reported separately, reflecting their different uses. Used mainly for human food.",Wheat,15,,,"Cereals, Total",1717.0,Annual, Flour of Wheat,"Defined broadly to include meal, groats and pellets. Strong flours from hard wheat are used for bread, while durum wheat flour is used primarily for pasta. Weaker flours from soft wheat are mainly used in cakes, pastries, biscuits and certain noodles.",,16,,,"Cereals, Total",1717.0,, Bran of Wheat,See Chapter 11.,,17,,,"Cereals, Total",1717.0,, Bran of Wheat,"Defined broadly to include sharps and other residue from the milling, sifting or other working of the grain. Contains a little flour.",,17,,,fodder,,, Macaroni,"Pasta made from semolina, or flour, that is mixed with water and kneaded into a dough. Other ingredients may be included as well. The dough is then shaped into various forms. This heading is limited to macaroni that is not cooked, stuffed or otherwise prepared.",,18,,,"Cereals, Total",1717.0,, Germ of Wheat,"The seed embryo. Whole or rolled germ is used for oil extraction by solvents. Flaked or ground germ is used in bakers' wares, dietetic preparations, feed supplements and in pharmaceutical preparations.",,19,,,"Cereals, Total",1717.0,, Bread,"A baked product of flour or meal of cereals, especially wheat. Includes ordinary, unleavened, crackers, rusks, etc.",,20,,,"Cereals, Total",1717.0,, Bulgur,"Whole wheat grains that are boiled, dried and cracked, either between stones or in a hand mill. Very popular in the Near East.",,21,,,"Cereals, Total",1717.0,, Pastry,"All baked products excluding those listed under bread. Pastry products may contain ingredients other than wheat flour, such as milk, eggs, sugar, honey, starch, fats, fruit, seeds, etc.",,22,,,"Cereals, Total",1717.0,, Starch of Wheat,"Starch is the carbohydrate component in many plant cells. A white, odourless powder that is insoluble in cold water, it forms a paste in hot water. Wheat starch is used for human consumption and animal feed, and is processed into glucose and dextrine for industrial use. It is usually obtained from low-quality flour.",,23,,,"Cereals, Total",1717.0,, Wheat Gluten,"A by-product of the industrial production of starch, wheat gluten is the preferred cereal gluten for food purposes. Uses include enriching protein in flours for bread, pasta, etc.",,24,,,"Cereals, Total",1717.0,, Wheat-Fermented Beverages,"Low-alcohol beverages from fermented flour, e.g. Korean jakju and takju.",,26,,,beverage,,, Wheat-Fermented Beverages,See Chapter 15.,,26,,,"Cereals, Total",1717.0,, "RICE PADDY Oryza spp., mainly oryza sativa","Rice grain after threshing and winnowing.Also known as rice in the husk and rough rice. Used mainly for human food.","Rice, paddy",27,,,"Cereals, Total",1717.0,Annual, "Rice, Husked",Rice grain without hulls or husks. Also known as brown or cargo rice.,,28,,,"Cereals, Total",1717.0,Annual, "Rice, Milled (Husked)","White rice milled from imported husked rice. Includes semi-milled, whole-milled and parboiled rice.",,29,,,"Cereals, Total",1717.0,Annual, "Rice, Milled","White rice milled from locally grown paddy. Includes semi-milled, whole-milled and parboiled rice.",,31,,,"Cereals, Total",1717.0,Annual, "Rice, Broken","Residues from the selection of whole-grain, milled rice.",,32,,,"Cereals, Total",1717.0,Annual, "Rice, Gluten","A by-product of the industrial production of starch. Not suitable for food use.",,33,,,"Cereals, Total",1717.0,Annual, Starch of Rice,"See 0023 Rice starch is usually obtained from broken rice. Use primarily in the photographic industry to prepare ""matt"" paper.",,34,,,"Cereals, Total",1717.0,Annual, Bran of Rice,"A by-product of polishing brown rice, comprising the pericarp, aleurone layer, embryo and some endosperm.",,35,,,fodder,,Annual, Bran of Rice,See Chapter 11.,,35,,,"Cereals, Total",1717.0,Annual, Oil of Rice Bran,"Extracted from bran by pressure or, more frequently, by solvents.",,36,,,fat,,, Oil of Rice,See Chapter 6.,,36,,,"Cereals, Total",1717.0,, Oil of Rice Bran,See Chapter 14.,,36,,,"Oilcrops, Oil Equivalent",1732.0,, Cake of Rice Bran,A residue of the extraction of oil. Also known as de-oiled rice bran.,,37,,,fodder,,, Cake of Rice Bran,See Chapter 11.,,37,,,"Cereals, Total",1717.0,, Flour of Rice,"Produced by milling broken or milled rice. Finely ground rice flour is widely used in infant foods and in noodles. It is not used in bread because it lacks the necessary gluten-forming protein.",,38,,,"Cereals, Total",1717.0,, Rice-Fermented Beverages,"Low-alcohol beverages, such as rice wine and sake.",,39,,,beverage,,, Rice-Fermented Beverages,See Chapter 15.,,39,,,"Cereals, Total",1717.0,, Breakfast Cereals,"Foods prepared by swelling and roasting cereals or cereal products, e.g. corn flakes, puffed rice; cereals o/t maize, in grain form, precooked or otherwise prepared.",,41,,,"Cereals, Total",1717.0,, "BARLEY Hordeum spp.: two-row barley (H. disticum) six-row barley",,Barley,44,,,"Cereals, Total",1717.0,Annual, Pot Barley,"Whole-seed barley with the husks, hulls and bran removed.",,45,,,"Cereals, Total",1717.0,Annual, "Barley, Pearled","Small, round pellets obtained by the further milling of pot barley. This definition also includes kibbled, rolled or flaked grains.",,46,,,"Cereals, Total",1717.0,Annual, Bran of Barley,See Chapter 11.,,47,,,"Cereals, Total",1717.0,Annual, Bran of Barley,A by-product of the production of pot barley.,,47,,,fodder,,Annual, Barley Flour and Grits,"Fine flour and course meal obtained as milling by-products of pearled barley.",,48,,,"Cereals, Total",1717.0,Annual, Malt,"A grain - usually barley - that has been germinated through a soaking process and then dried. Malt is used in brewing and distilling, and as a nutrient additive. Includes whole, ground, flour, and roasted malt, but excludes extracts and preparations.",,49,,,"Cereals, Total",1717.0,, Malt Extract,"A concentrated solution from water-macerated malt, which is used in infant and dietetic foods and in bread baking.",,50,,,"Cereals, Total",1717.0,, Beer of Barley,See Chapter 15.,,51,,,"Cereals, Total",1717.0,, Beer of Barley,"Beverage that may be alcoholic or non-alcoholic that is made from fermented malted cereals (mainly barley), water and hops. Non-malted cereals may also be used. The FAO definition differs from the main international classifications in that it includes non-alcoholic beer.",,51,,,beverage,,, "MAIZE Zea mays Corn, Indian corn, mealies","A grain with a high germ content. At the national level, hybrid and ordinary maize should be reported separately owing to widely different yields and uses. Used largely for animal feed and commercial starch production.",Maize,56,,,"Cereals, Total",1717.0,Annual, Germ of Maize,"The seed embryo that is separated during processing and is valued mainly for its oil.",,57,,,"Cereals, Total",1717.0,Annual, Flour of Maize,"Broadly defined to include meal, groats and pellets.",,58,,,"Cereals, Total",1717.0,Annual, Bran of Maize,A by-product of the milling of shelled maize.,,59,,,fodder,,Annual, Bran of Maize,See Chapter 11.,,59,,,"Cereals, Total",1717.0,Annual, Oil of Maize,See Chapter 6.,,60,,,"Cereals, Total",1717.0,Annual, Oil of Maize,Extracted from germ by pressure or by solvents.,,60,,,fat,,Annual, Cake of Maize,See Chapter 11.,,61,,,"Cereals, Total",1717.0,Annual, Cake of Maize,A residue of the extraction of oil from germ.,,61,,,fodder,,Annual, Maize Gluten,"Maize protein is often called gluten, although it lacks the quality characteristics of wheat gluten. It is separated from maize during commercial wet milling and used to enrich animal feeds.",,63,,,"Cereals, Total",1717.0,Annual, Starch of Maize,"See 0023. The primary product of the large- scale industrial wet-milling process. Used mainly for the production of glucose, dextrin and alcohol.",,64,,,"Cereals, Total",1717.0,Annual, Beer of Maize,Prepared either from malted or unmalted cereal.,,66,,,beverage,,Annual, Beer of Maize,See Chapter 15.,,66,,,"Cereals, Total",1717.0,Annual, WHITE MAIZE,"Although separate data are reported for white maize production owing to its regional importance, its production is also included in 0056.",,67,,,"Cereals, Total",1717.0,Annual, "POPCORN Zea mays var. everta","A variety of maize that is eaten after the kernels have been heated and have ""popped"".",,68,,,"Cereals, Total",1717.0,Annual, "RYE Secale cereale","A grain that is tolerant of poor soils, high latitudes and altitudes. Mainly used in making bread, whisky and beer. When fed to livestock, it is generally mixed with other grains.",Rye,71,,,"Cereals, Total",1717.0,, Flour of Rye,"Broadly defined to include meal, groats and pellets. In northern countries, rye flour is used primarily in bread.",,72,,,"Cereals, Total",1717.0,, Bran of Rye,See Chapter 11.,,73,,,"Cereals, Total",1717.0,, Bran of Rye,A milling by-product.,,73,,,fodder,,, "OATS Avena spp., mainly Avena sativa","A plant with open, spreading panicle-bearing large spikelets. Used primarily in breakfast foods. Makes excellent fodder for horses.",Oats,75,,,"Cereals, Total",1717.0,, "Oats, Rolled","Obtained by crushing or rolling the whole or broken grain; includes grains flaked, hulled or otherwise worked for human consumption.",,76,,,"Cereals, Total",1717.0,, "Bran of Oats See Chapter 11.",See Chapter 11.,,77,,,"Cereals, Total",1717.0,, Bran of Oats,"By-product of milling oats for human consumption, containing mainly hulls and fragments of the endosperm (oat millfeed), as well as residues from hulling, rolling, flaking, etc.",,77,,,fodder,,, "MILLETS Including inter alia: barnyard or Japanese millet (Echinocloa frumentacea); ragi, finger or African millet (Eleusine coracana); teff (Eragrostis abyssinica); common, golden or proso millet (Panicum miliaceum); koda or ditch millet (Paspalum scrobiculatum); pearl or cattail millet (Pennisetum glaucum); foxtail millet (Setaria italica)","Small-grained cereals that include a large number of different botanical species. Originated by the domestication of wild African grasses in the Nile valley and the Sahel zone, millets were subsequently taken to China and India. These cereals tolerate arid conditions and possess a small, highly nutritious grain that stores well. Used locally, both as a food and as a livestock feed. In all areas where they are cultivated, millets are used in traditional beer brewing. Also used as a feed for birds.",Millet,79,,,"Cereals, Total",1717.0,, Flour of Millet,"Broadly defined to include meal, groats and pellets.",,80,,,"Cereals, Total",1717.0,, Bran of Millet,See Chapter 11.,,81,,,"Cereals, Total",1717.0,, Bran of Millet,A milling by-product.,,81,,,fodder,,, Beer of Millet,See Chapter 15.,,82,,,"Cereals, Total",1717.0,, Beer of Millet,"A traditional beer prepared in African countries in which millets are cultivated. It is normally consumed while still fermenting.",,82,,,beverage,,, "SORGHUM Sorghum spp.: guinea corn (S. guineense); common, milo, feterita, kaffir corn (S. vulgare); durra, jowar, kaoliang (S. dura)","A cereal that has both food and feed uses. Sorghum is a major food grain in most of Africa, where it is also used in traditional beer brewing. It is desirable to report hybrid and other varieties separately.",Sorghum,83,,,"Cereals, Total",1717.0,, Flour of Sorghum,"Broadly defined to include meal, groats and pellets.",,84,,,"Cereals, Total",1717.0,, Bran of Sorghum,A milling by-product.,,85,,,fodder,,, Bran of Sorghum,See Chapter 11.,,85,,,"Cereals, Total",1717.0,, Beer of Sorghum,"A traditional beer prepared in African countries in which sorghum is cultivated. It is normally consumed while still fermenting.",,86,,,beverage,,, Beer of Sorghum,See Chapter 15.,,86,,,"Cereals, Total",1717.0,, "BUCKWHEAT Fagopyrum esculentum (Polygonaceae)","A minor cereal cultivated primarily in northern regions. Buckwheat is considered a cereal, although it does not belong to the gramineous family.",Buckwheat,89,,,"Cereals, Total",1717.0,Annual, Flour of Buckwheat,"Broadly defined to include meal, groats and pellets. The flour is normally used in bread and crackers, and is also mixed with wheat flour. Meal and groats are normally used for soups.",,90,,,"Cereals, Total",1717.0,Annual, Bran of Buckwheat,A milling by-product.,,91,,,fodder,,Annual, Bran of Buckwheat,See Chapter 11.,,91,,,"Cereals, Total",1717.0,Annual, "QUINOA Chenopodium quinoa (Chenopodiaceae)","A minor cereal, which tolerates high altitudes, quinoa is cultivated primarily in Andean countries. Used for food and to make chicha, a fermented beverage.",Quinoa,92,,,"Cereals, Total",1717.0,, "FONIO Digitaria spp.: fonio or findi (D. exilis); black fonio or hungry rice (D. iburua)","A minor cereal of importance only in West Africa where it is eaten in place of rice during famines. The seeds are cooked by steaming the whole grain.",Fonio,94,,,"Cereals, Total",1717.0,, Flour of Fonio,"Broadly defined to include meal, groats and pellets.",,95,,,"Cereals, Total",1717.0,, Bran of Fonio,See Chapter 11.,,96,,,"Cereals, Total",1717.0,, Bran of Fonio,A milling by-product.,,96,,,fodder,,, TRITICALE,"A minor cereal that is a cross between wheat and rye, combining the quality and yield of wheat with the hardiness of rye.",Triticale,97,,,"Cereals, Total",1717.0,, Flour of Triticale,"Broadly defined to include meal, groats and pellets.",,98,,,"Cereals, Total",1717.0,, Bran of Triticale,See Chapter 11.,,99,,,"Cereals, Total",1717.0,, Bran of Triticale,A milling by-product.,,99,,,fodder,,, "CANARY SEED Phalaris canariensis",Minor cereal normally used as bird feed.,Canary seed,101,,,"Cereals, Total",1717.0,Annual, MIXED GRAIN,"A mixture of cereal species that are sown and harvested together. The mixture wheat/rye is known as meslin, but in trade is usually classified with wheat.","Grain, mixed",103,,,"Cereals, Total",1717.0,, Flour of Mixed Grain,"Broadly defined to include meal, groats and pellets.",,104,,,"Cereals, Total",1717.0,, Bran of Mixed Grain,A milling by-product.,,105,,,fodder,,, Bran of Mixed Grain,See Chapter 11.,,105,,,"Cereals, Total",1717.0,, "CEREALS NES Including inter alia: canagua or coaihua (Chenopodium pallidicaule); quihuicha or Inca wheat (Amaranthus caudatus); adlay or Job's tears (Coix lacryma-jobi); wild rice (Zizania aquatica)","Other cereal crops that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report cereals under this commodity heading that are classified individually by FAO.",Cereals nes,108,,,"Cereals, Total",1717.0,, Infant Food,"Preparations for infant consumption, usually containing some non-cereal ingredients.",,109,,,"Cereals, Total",1717.0,, Wafers,"Communion wafers, empty cachets for pharmaceutical use and sealing wafers.",,110,,,"Cereals, Total",1717.0,, Flour of Cereals nes,"Broadly defined to include meal, groats and pellets.",,111,,,"Cereals, Total",1717.0,, Bran of Cereals nes,See Chapter 11.,,112,,,"Cereals, Total",1717.0,, Bran of Cereals nes,A milling by-product.,,112,,,fodder,,, Cereal Preparations,"Cereal grains, excluding barley and oats, that are either rolled, flaked, pearled, sliced or kibbled.",,113,,,"Cereals, Total",1717.0,, Mixes and Doughs,Used in the preparation of bakers' wares.,,114,,,"Cereals, Total",1717.0,, "Food Preparations of Flour, Meal or Malt Extract","Food preparations of flour, meal, starch or malt extracts, that either do not contain, or contain less than 50%, cocoa powder. Also, food preparations of milk that either do not contain, or contain less than 10%, cocoa powder.",,115,,,"Cereals, Total",1717.0,, "POTATOES Solanum tuberosum Irish potato","A seasonal crop grown in temperate zones all over the world, but primarily in the northern hemisphere.",Potatoes,116,,,"Roots and Tubers, Total",1720.0,Annual, Flour of Potatoes,"Produced from tubers that have been peeled, dried and milled. Includes flour, meal, flakes, granules and pellets.",,117,,,"Roots and Tubers, Total",1720.0,Annual, Frozen Potatoes,"Peeled potatoes that are either cooked or uncooked, sliced or unsliced, and then frozen.",,118,,,"Roots and Tubers, Total",1720.0,Annual, Starch of Potatoes,"A carbohydrate found in many plant cells. A white odourless powder that is insoluble in cold water, but forms a paste in hot water. Has wide food and non-food uses.",,119,,,"Roots and Tubers, Total",1720.0,Annual, Potato Offals,The residue and waste from the preparation of potatoes.,,120,,,fodder,,Annual, Potato Offals,See Chapter 11.,,120,,,"Roots and Tubers, Total",1720.0,Annual, Tapioca of Potatoes,"A product obtained by heating potato starch mixed with water. Tapioca may be in the form of flakes, grains, pearls, siftings, seeds or other similar forms. Used in the preparation of soups and puddings or in foods for invalids.",,121,,,"Roots and Tubers, Total",1720.0,, "SWEET POTATOES Ipomoea batatas","A seasonal crop grown in tropical and subtropical regions. Used mainly for human food. Trade data cover fresh and dried tubers, whether or not sliced or in the form or pellets.",Sweet potatoes,122,,,"Roots and Tubers, Total",1720.0,Annual, "CASSAVA Manioc, mandioca, yuca (Manihot esculenta, syn. M. utilissima); yuca dulce (M. palmata, syn. M. dulcis)","A semi-permanent crop grown in tropical and subtropical regions. Sometimes bitter and sweet cassavas are referred to as separate species, the former being M. esculenta and the latter M. palmata, but this is incorrect since the toxicity varies according to location. Cassava is the staple food in many tropical countries. It is not traded internationally in its fresh state because tubers deteriorate very rapidly.",Cassava,125,,,"Roots and Tubers, Total",1720.0,Annual, Flour of Cassava,"A product of tubers that have been peeled, dried and milled; mainly for human consumption. Includes flour, meal and flakes.",,126,,,"Roots and Tubers, Total",1720.0,Annual, Tapioca of Cassava,"See 0121. Obtained from cassava starch and used in the preparation of puddings and in infant foods.",,127,,,"Roots and Tubers, Total",1720.0,Annual, "Cassava, Dried","Includes peeled, sliced and sun-dried (cassava chips), as well as ground and compressed cassava (pellets). Used mainly as livestock feed.",,128,,,"Roots and Tubers, Total",1720.0,Annual, Starch of Cassava,"See 0119. The principal industrial outlet for cassava. Cassava starch is used in the foodstuffs, textile and paper industries for the manufacture of plywood and veneer, adhesives, glucose and dextrine.",,129,,,"Roots and Tubers, Total",1720.0,Annual, "YAUTIA (COCOYAM) Xanthosoma spp.; malanga, new cocoyam, ocumo, tannia (X. sagittifolium)","Several plants are included in this group, some with edible tubers and others with edible stems (also called aroids). Yautia is grown mainly in the Caribbean and is used for food. Trade data cover both fresh and dried yautia.",Yautia (cocoyam),135,,,"Roots and Tubers, Total",1720.0,, "TARO (COCOYAM) Dasheen, eddoe, taro, old cocoyam(Colocasia esculenta)","Aroids cultivated for their edible starchy corms or underground stems. Taro is grown throughout the tropics for food. Trade data cover both fresh and dried taro.",Taro (cocoyam),136,,,"Roots and Tubers, Total",1720.0,Perennial, "YAMS Dioscorea spp.","The principal edible yams are widely grown throughout the tropics. A starchy staple foodstuff, normally eaten as a vegetable, boiled, baked or fried. In West Africa they are consumed mainly as ""fufu"", a stiff glutinous dough. Trade data cover both fresh and dried yams.",Yams,137,,,"Roots and Tubers, Total",1720.0,, "ROOTS AND TUBERS NES Including inter alia: arracacha (Arracacoa xanthorrhiza); arrowroot (Maranta arundinacea); chufa (Cyperus esculentus); sago palm (Metroxylon spp.); oca and ullucu (Oxalis tuberosa and Ullucus tuberosus); yam bean, jicama (Pachyrxhizus erosus, P. angulatus); mashua (Tropaeolum tuberosum); Jerusalem artichoke, topinambur (Helianthus tuberosus)","Other tubers, roots or rhizomes, fresh, that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report roots and tubers under this commodity heading that are classified individually by FAO.",Roots and tubers nes,149,,,"Roots and Tubers, Total",1720.0,, Flour of Roots and Tubers nes,"Flour and meal produced from roots and tubers o/t potatoes and cassava.",,150,,,"Roots and Tubers, Total",1720.0,, "Roots and Tubers, Dried nes","Other tubers, roots or rizhomes, dried, o/t potatoes and cassava.",,151,,,"Roots and Tubers, Total",1720.0,, "Fructose, Chemically Pure","Or levulose, monosaccharide, present with glucose in sweet fruits and honey.",,154,,,sugar,,, "Maltose, Chemically Pure","Produced industrially from starch by hydrolysis with malt diastase. Used in the brewing industry.",,155,,,sugar,,, "Maltose, Chemically Pure",See Chapter 3.,,155,,,"Cereals, Total",1717.0,, "SUGAR CANE Saccharum officinarum","In some producing countries, marginal quantities of sugar cane are consumed, either directly as food or in the form of juice.",Sugar cane,156,,,sugar,,Perennial,15.0 "SUGAR BEET Beta vulgaris var. altissima","In some producing countries, marginal quantities are consumed, either directly as food or in the preparation of jams.",Sugar beet,157,,,sugar,,Perennial,15.0 Cane Sugar,"A non-refined, crystallized material derived from the juices of sugar-cane stalk and consisting either wholly or essentially of sucrose.",,158,,,sugar,,Perennial,15.0 Cane Sugar,"A non-refined, crystallized material derived from the juices of sugar-cane stalk and consisting either wholly or essentially of sucrose.",,158,,,sugar,,Perennial,15.0 Beet Sugar,"A non-refined, crystallized material derived from the juices extracted from the root of the sugar beet and consisting either wholly or essentially of sucrose.",,159,,,sugar,,Perennial,15.0 Beet Sugar,"A non-refined, crystallized material derived from the juices extracted from the root of the sugar beet and consisting either wholly or essentially of sucrose.",,159,,,sugar,,Perennial,15.0 Maple Sugar and Syrups,"Maple syrup is produced by atmospheric boiling of maple sap in an open-pan evaporator. Continuing the evaporation process until the syrup crystalizes yields maple sugar.",,160,,,sugar,,Perennial,15.0 "SUGAR CROPS NES Including inter alia: sugar maple (Acer saccharum); sweet sorghum (Sorghum saccharatum); sugar palm (Arenga saccharifera)","Includes minor sugar crops of local importance. In the case of saps, production is to be expressed in liquid equivalent.",Sugar crops nes,161,,,sugar,,Perennial,15.0 "Sugar, Raw Centrifugal","The sum of codes 0158 and 0159. Processed further to obtain refined sugar.",,162,,,sugar,,Perennial,15.0 "Sugar, Raw Centrifugal","The sum of codes 0158 and 0159. Processed further to obtain refined sugar.",,162,,,sugar,,Perennial,15.0 "Sugar, Non-Centrifugal","Generally derived from sugar cane through traditional methods without centrifugation.",,163,,,sugar,,Perennial,15.0 "Sugar, Non-Centrifugal","Generally derived from sugar cane through traditional methods without centrifugation.",,163,,,sugar,,Perennial,15.0 "Sugar, Refined","Production covers domestic production, plus or minus imports and/or exports of raw centrifugal sugar in terms of refined sugar.",,164,,,sugar,,Perennial,15.0 "Sugar, Refined","Production covers domestic production, plus or minus imports and/or exports of raw centrifugal sugar in terms of refined sugar.",,164,,,sugar,,Perennial,15.0 Molasses,"A by-product of the extraction or refining of beet or cane sugar or of the production of fructose from maize. Used for feed, food, industrial alcohol, alcoholic beverages and ethanol.",,165,,,sugar,,, Molasses,"A by-product of the extraction or refining of beet or cane sugar or of the production of fructose from maize. Used for feed, food, industrial alcohol, alcoholic beverages and ethanol.",,165,,,sugar,,, Other Fructose and Syrup,"Monosaccharide found in fruits and honey, commercially produced from glucose, sucrose or by hydrolysis of inulin (polysaccharide found mainly in the tubers of the dahlia and the Jerusalem artichoke). Especially suitable for use by diabetics.",,166,,,sugar,,, Other Fructose and Syrup,See Chapter 3.,,166,,,"Cereals, Total",1717.0,, Sugar and Syrups nes,"Includes invert sugar, caramel, golden syrup, artificial honey, maltose other than chemically pure, sorghum and palm sugars. See also the general note in the introduction.",,167,,,sugar,,, Sugar Confectionery,"Sugar confectionery, including chewing gum, that does not contain cocoa. Includes white chocolate.",,168,,,sugar,,, Beet Pulp,See Chapter 11.,,169,,,sugar,,, Beet Pulp,See Chapter 11.,,169,,,sugar,,, Beet Pulp,"Residue from the extraction of sugar from the root of sugar beets. Used for animal feed.",,169,,,fodder,,, Bagasse,See Chapter 11.,,170,,,sugar,,, Bagasse,See Chapter 11.,,170,,,sugar,,, Bagasse,"Residue consisting of the fibrous portion of the sugar cane after the juice has been extracted. Used as a fuel in sugar mills, as an animal feed, and in paper production.",,170,,,fodder,,, Glucose and Dextrose,See Chapter 3.,,172,,,"Cereals, Total",1717.0,, Glucose and Dextrose,"Glucose is a monosaccharide produced by hydrolysing starch with acids and/or enzymes. Dextrose is chemically pure glucose. Used in the food industry, in brewing, in tobacco fermentation and in pharmaceutical products.",,172,,,sugar,,, Lactose,Also known as milk sugar. Produced commercially from whey.,,173,,,sugar,,, Lactose,See Chapter 3.,,173,,,animal,,, Artificial Sweeteners,"High-intensity or low-caloric sweetening agents that are produced chemically.",,174,,,sugar,,, Isoglucose,"Also known as HFCS (high-fructose corn syrup), HFSS (high-fructose starch syrup), HFGS (high-fructose glucose syrup). Isoglucose is a new type of starch syrup where glucose has been isomerized to fructose by using one or more isomerizing enzymes. Most important of the sweeteners manufactured from maize starch. Widely used in the production of food and soft drinks.",,175,,,sugar,,, Isoglucose,See Chapter 3.,,175,,,"Cereals, Total",1717.0,, "BEANS, DRY Phaseolus spp.: kidney, haricot bean (Ph. vulgaris); lima, butter bean (Ph. lunatus); adzuki bean (Ph. angularis); mungo bean, golden, green gram (Ph. aureus); black gram, urd (Ph. mungo); scarlet runner bean (Ph. coccineus); rice bean (Ph. calcaratus); moth bean (Ph. aconitifolius); tepary bean (Ph. acutifolius)","Only species of Phaseolus should be included, though several countries also include certain types of beans. Commonly classified as Vigna (angularis, mungo, radiata, aconitifolia). In the past, these species were also classified as Phaseolus.","Beans, dry",176,,,"Pulses, Total",1726.0,Annual, "BROAD BEANS, DRY Vicia faba: horse-bean (var. equina); broad bean (var. major); field bean (var. minor)",,"Broad beans, horse beans, dry",181,,,"Pulses, Total",1726.0,Annual, "PEAS, DRY garden pea (Pisum sativum); field pea (P. arvense)",,"Peas, dry",187,,,"Pulses, Total",1726.0,Annual, "CHICK-PEAS chickpea, Bengal gram, garbanzos (Cicer arietinum)",,Chick peas,191,,,"Pulses, Total",1726.0,Annual, "COW PEAS, DRY cowpea, blackeye pea/bean (Vigna sinensis; Dolichos sinensis)",,"Cow peas, dry",195,,,"Pulses, Total",1726.0,Annual, "PIGEON PEAS pigeon pea, cajan pea, Congo bean (Cajanus cajan)",,Pigeon peas,197,,,"Pulses, Total",1726.0,Annual, "PIGEON PEAS pigeon pea, cajan pea, Congo bean (Cajanus cajan)",,Pigeon peas,197,,,"Pulses, Total",1726.0,Annual, "LENTILS (Lens esculenta; Ervum lens)",,Lentils,201,,,"Pulses, Total",1726.0,, "BAMBARA BEANS bambara groundnut, earth pea (Voandzeia subterranea)",These beand are grown underground in a similar way to groundnuts.,Bambara beans,203,,,"Pulses, Total",1726.0,Annual, "VETCHES spring/common vetch (Vicia sativa)",Used mainly for animal feed.,Vetches,205,,,"Pulses, Total",1726.0,, "LUPINS (Lupinus spp.)","Used primarily for feed, though in some parts of Africa and in Latin America some varieties are cultivated for human food.",Lupins,210,,,"Pulses, Total",1726.0,, "PULSES NES Including inter alia: lablab or hyacinth bean (Dolichos spp.); jack or sword bean (Canavalia spp.); winged bean (Psophocarpus tetragonolobus); guar bean (Cyamopsis tetragonoloba); velvet bean (Stizolobium spp.); yam bean (Pachyrrhizus erosus);","Vigna spp. other than those included in 0176 and 0195 Other pulses that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report pulses under this heading that are classified individually by FAO.",Pulses nes,211,,,"Pulses, Total",1726.0,, Flour of Pulses,"Produced through milling or grinding of pulses. This heading also includes meal.",,212,,,"Pulses, Total",1726.0,, Bran of Pulses,"Bran, sharps and other residues from the milling or working of pulses.",,213,,,fodder,,, Bran of Pulses,See Chapter 11.,,213,,,"Pulses, Total",1726.0,, "BRAZIL NUTS Brazil, Para or cream nut (Bertholletia excelsa)",,"Brazil nuts, with shell",216,,,"Treenuts, Total",1729.0,Perennial, "CASHEW NUTS Anacardium occidentale","Produced mainly in East Africa, India and Brazil.","Cashew nuts, with shell",217,,,"Treenuts, Total",1729.0,Perennial,50.0 "CHESTNUTS Castanea spp.: C. vesca; C. vulgaris; C. sativa Produced mainly in Europe and Asia.",Produced mainly in Europe and Asia.,Chestnut,220,,,"Treenuts, Total",1729.0,Perennial, "ALMONDS Prunus amygdalus; P. communis; Amygdalus communis Produced mainly in Mediterranean countries, the United States and Asia.","Produced mainly in Mediterranean countries, the United States and Asia.","Almonds, with shell",221,,,"Treenuts, Total",1729.0,Perennial, "WALNUTS Jugland spp.: J. regia","Produced in temperate zones of the Northern Hemisphere, particularly in the United States.","Walnuts, with shell",222,,,"Treenuts, Total",1729.0,Perennial,250.0 "PISTACHIOS Pistacia vera",Produced mainly in the Near East and the United States.,Pistachios,223,,,"Treenuts, Total",1729.0,Perennial, "KOLA NUTS kola, cola, Sudan cola nut (Cola nitida; C. vera; C. acuminata)","Produced mainly in Africa. Kola nuts, containing 2.4 to 2.6% caffeine, are commonly chewed by the local population. Much used in Europe and America in the production of beverages.",Kola nuts,224,,,"Treenuts, Total",1729.0,Perennial, "HAZELNUTS (FILBERTS) Corylus avellana",Produced mainly in Mediterranean countries and the United States.,"Hazelnuts, with shell",225,,,"Treenuts, Total",1729.0,Perennial, "ARECA NUTS areca, betel nut (Areca catechu)","Produced mainly in the Far East. Areca nuts are used mainly as masticatory. These nuts contain alkaloids (arecoline and arecaidine).",Areca nuts,226,,,"Treenuts, Total",1729.0,Perennial,60.0 "Brazil Nuts, Shelled",Around 55% of the weight in shell.,,229,,,"Treenuts, Total",1729.0,Perennial, "Cashew Nuts, Shelled",Around 25% of the weight in shell.,,230,,,"Treenuts, Total",1729.0,Perennial,50.0 "Almonds, Shelled",Around 55% of the weight in shell.,,231,,,"Treenuts, Total",1729.0,Perennial, "Walnuts, Shelled",Around 53% of the weight in shell.,,232,,,"Treenuts, Total",1729.0,Perennial,250.0 "Hazelnuts, Shelled",Around 50% of the weight in shell.,,233,,,"Treenuts, Total",1729.0,Perennial, "NUTS NES Including inter alia: pecan nut (Carya illinoensis); butter or swarri nut (Caryocar nuciferum); pili nut, Java almond, Chinese olives (Canarium spp.); paradise or sapucaia nut (Lecythis zabucajo); Queensland, macadamia nut (Macadamia ternifolia); pignolia nut (Pinus pinea)","Other nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report nuts under this heading that are classified individually by FAO.",Nuts nes,234,,,"Treenuts, Total",1729.0,Perennial, Prepared Nuts,"Mainly roasted, whether or not containing vegetable oils, salt, flavours, spices or other additives. Excludes prepared groundnuts, except when mixed with other nuts.",,235,,,"Treenuts, Total",1729.0,Perennial, "SOYBEANS Glycine soja","The most important oil crop. Also widely consumed as a bean and in the form of various derived products because of its high protein content, e.g. soya milk, meat, etc.",Soybeans,236,,,"Oilcrops, Oil Equivalent",1732.0,Annual, "SOYBEANS Glycine soja","The most important oil crop. Also widely consumed as a bean and in the form of various derived products because of its high protein content, e.g. soya milk, meat, etc.",Soybeans,236,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Soybeans,See Chapter 11.,,237,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Soybeans,Obtained by solvent extraction from the beans. Used mainly for food.,,237,,,fat,,Annual, Cake of Soybeans,"Oilcake and other solid residues (except dregs), whether or not ground, or in the form of pellets, resulting from the extraction of fats or oils.",,238,,,fodder,,Annual, Soya Sauce,"A fermented soya product from defatted soybeand and wheat or other cereals that is filtered and pasteurized.",,239,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Soya Paste,"A fermented, salty condiment. Soya paste can be produced through brine fermentation of low- moisture soya curd.",,240,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Soya Curd,"Obtained by precipitating proteins from soya milk and removing the fluid. Can be fermented or non-fermented.",,241,,,"Oilcrops, Oil Equivalent",1732.0,Annual, "GROUNDNUTS IN SHELL Arachis hypogaea","For trade data, groundnuts in shell are converted at 70% and reported on a shelled basis.","Groundnuts, with shell",242,,,"Oilcrops, Oil Equivalent",1732.0,Annual, "Groundnuts, Shelled",Used as direct food and for extracting oil.,,243,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Groundnuts,See Chapter 11.,,244,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Groundnuts,Obtained by pressure or solvent extraction. Used mainly for food.,,244,,,fat,,Annual, Cake of Groundnuts,Residue from oil extraction.,,245,,,fodder,,Annual, Prepared Groundnuts,"Roasted, salted, flavoured, etc.",,246,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Peanut Butter,"Obtained by grinding roasted peanuts. In addition to fat, at 40-46%, peanut butter contains all other components of the nuts.",,247,,,"Oilcrops, Oil Equivalent",1732.0,Annual, "COCONUTS Cocos nucifera Husked coconut","In shell, covered by the endocarp, while exocarp (the smooth outer skin) and mesocarp (the fibrous covering) are removed. Immature nuts contain a milky juice that is consumed as a refreshing drink. Mature nuts are consumed as such, or processed for copra or desiccated coconut. The flesh, from which copra/oil is extracted, constitutes 40-70% of the weight of the husked coconut. The oil content is about 36% of the flesh.",Coconuts,249,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 "Coconuts, Desiccated","Dried, shredded flesh of coconut processed for human consumption. It retains most of the oil and proteins of the fresh nut and is mainly used in confectionery and baking.",,250,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 Copra,The dried flesh of coconut from which the oil is extracted.,,251,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 Oil of Coconuts,"Obtained by pressure from copra and by solvent from the residues of pressure extraction. Has both food and industrial uses.",,252,,,fat,,Perennial,70.0 Oil of Coconut,See Chapter 11.,,252,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,70.0 Cake of Copra,Residue from oil extraction.,,253,,,fodder,,Perennial,70.0 "[OIL PALM FRUIT] Elaeis guineensis","The oil palm produces bunches containing a large number of fruits with the fleshy mesocarp enclosing a kernel that is covered by a very hard shell. FAO considers palm oil (coming from the pulp) and palm kernels to be primary products. The oil extraction rate from a bunch varies from 17 to 27% for palm oil, and from 4 to 10% for palm kernels.",Oil palm fruit,254,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 PALM KERNELS,"Seeds of the oil palm. Babassu kernels (Orbignya speciosa) are often reported as palm kernels.",Palm kernels,256,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 OIL OF PALM,See Chapter 14.,"Oil, palm",257,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 OIL OF PALM,"Obtained from the mesocarp of the fruit of the oil palm by pressure, and also by solvent from the residues of the pressure extraction.","Oil, palm",257,,,fat,,Perennial,30.0 Oil of Palm Kernel,"Obtained from the kernel of the nut of the fruits of the oil palm by pressure in two or three stages at different temperatures. Including oil of babassu kernels.",,258,,,fat,,Perennial,30.0 Cake of Palm Kernel,Residue from oil extraction.,,259,,,fodder,,Perennial,30.0 Cake of Palm Kernel,,,259,,,"Oilcrops, Oil Equivalent",1732.0,Perennial,30.0 OLIVES Olea europaea,Includes table olives and olives for oil.,Olives,260,,,"Oilcrops, Oil Equivalent",1732.0,, "Oil of Olives, Virgin",See Chapter 11.,,261,,,"Oilcrops, Oil Equivalent",1732.0,, "Oil of Olives, Virgin","Obtained from olives by mechanical or other physical means. Olive oil is the only vegetable oil that can be consumed without refining.",,261,,,fat,,, KARITE NUTS (SHEANUTS) Butyrospermum parkii,"Production data refer only to the nut contained in the fruit although the pulp around the nut is also edible.",Karite nuts (sheanuts),263,,,"Oilcrops, Oil Equivalent",1732.0,, Butter of Karite Nuts,,,264,,,"Oilcrops, Oil Equivalent",1732.0,, Butter of Karite Nuts,"A very important vegetable oil in West Africa. Used as a substitute for cocoa butter and in cosmetics.",,264,,,fat,,, CASTOR BEANS Ricinus communis,"Valued mainly for their oil, which is used in pharmaceutical products. Ground seedcakes are used as fertilizers (castor oil pomace).",Castor oil seed,265,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Castor Beans,See Chapter 14.,,266,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Castor Beans,"Obtained by pressure or by solvent. Uses include mainly industrial ones, in pharmaceuticals and cosmetics.",,266,,,fat,,, SUNFLOWER SEED Helianthus annuus,"Valued mainly for its oil. Minor uses include as a human food and as feed for birds.",Sunflower seed,267,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Sunflower Seed,Obtained by pressure extraction. Mainly for food use.,,268,,,fat,,, Oil of Sunflower Seed,See Chapter 11.,,268,,,"Oilcrops, Oil Equivalent",1732.0,, Cake of Sunflower Seed,"Residue from oil extraction. The cake is used for feed if it is from decorticated seeds, or for fertilizer if it comes from undecorticated seeds.",,269,,,fodder,,, RAPESEED Brassica napus var. oleifera,"Valued mainly for its oil. Older varieties are rich in Erucic acid, which is considered unhealthy.",Rapeseed,270,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Rapeseed Canola oil,See Chapter 11.,,271,,,"Oilcrops, Oil Equivalent",1732.0,, "Oil of Rapeseed Canola oil","Obtained by pressure extraction for food use. Oil recovered with solvent from the residues of the pressure extraction is used for industrial purposes. Canola oil is produced from new varieties of rapeseed.",,271,,,fat,,, Cake of Rapeseed,Residue from oil extraction.,,272,,,fodder,,, Olive Residues,"Residues make up about 40% of the olives crushed for oil, but account for about 5% of the oil.",,273,,,fodder,,, Oil of Olive Residues,Oil extracted from olive residues with solvents.,,274,,,fat,,, Oil of Olive Residues,,,274,,,"Oilcrops, Oil Equivalent",1732.0,, TUNG NUTS Aleurites cordata; A. fordii,Valued mainly for their oil.,Tung nuts,275,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Tung Nuts,,,276,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Tung Nuts,"Obtained by pressure and used exclusively for industrial purposes. The resulting cake contains a toxic protein and thus cannot be used for feed.",,276,,,fat,,, JOJOBA SEEDS Simmondsia californica (syn. S. chinensis),From the shrub or small tree of the Buxaceae family.,,277,,,"Oilcrops, Oil Equivalent",1732.0,, Jojoba Oil,"© FAO 1994 Return to top",,278,,,"Oilcrops, Oil Equivalent",1732.0,, Jojoba Oil,"Obtained by cold pressure. Its peculiar chemical properties make it the only vegetable oil in nature having the same characteristics as spermaceti. Below 15øC it solidifies and assumes the characteristics of wax. It is used as a lubricant, in cosmetics and in pharmaceuticals, and is considered a product with good growth prospects.",,278,,,fat,,, SAFFLOWER SEED Carthamus tinctorius,"Valued mainly for its oil. Minor uses include as a human food and as poultry feed.",Safflower seed,280,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Safflower Seed,See Chapter 11.,,281,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Safflower Seed,"Obtained either by pressure or by solvent. Has both food and industrial uses.",,281,,,fat,,, Cake of Safflower Seed,Residue from oil extraction.,,282,,,fodder,,, SESAME SEED Sesamum indicum,"Valued for its oil, but also as a food, either raw or roasted, as well as in bakery products and other food preparations.",Sesame seed,289,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Sesame Seed,See Chapter 11.,,290,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Sesame Seed,"Obtained by pressure extraction in two or three stages at different temperatures. Sometimes the oil is also extracted by solvent from the residue of the pressure extraction. Used mainly for food.",,290,,,fat,,, Cake of Sesame Seed,Residue from oil extraction.,,291,,,fodder,,, MUSTARD SEED white mustard (Brassica alba; B. hirta; Sinapis alba); black mustard (Brassica nigra; Sinapis nigra),"In addition to the oil extracted from them, white mustard seeds, may be processed into flour for food use. Black mustard seeds also yield oil and are processed into flour that is used mainly in pharmaceutical products.",Mustard seed,292,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Mustard Seed,See Chapter 11.,,293,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Mustard Seed,"Obtained by dry pressure extraction. Has both food and industrial uses.",,293,,,fat,,, Cake of Mustard Seed,Residue from oil extraction.,,294,,,fodder,,, Flour of Mustard Seed,"Includes flour, meal and prepared mustard.",,295,,,"Oilcrops, Oil Equivalent",1732.0,, POPPY SEED Papaver somniferum,"The source of opium, poppy seeds are also used in baking and confectionery.",Poppy seed,296,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Poppy Seed,See Chapter 11.,,297,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Poppy Seed,Obtained by pressure extraction. Has both food and industrial uses.,,297,,,fat,,, Cake of Poppy Seed,Residue from oil extraction.,,298,,,fodder,,, MELONSEED Cucumis melo,Includes seeds of other Cucurbitaceae.,Melonseed,299,,,"Oilcrops, Oil Equivalent",1732.0,, [TALLOWTREE SEEDS] Borneo tallow tree (Shorea aptera; S. stenocarpa); Chinese tallow tree (Sapium sebiferum; Stillingia sebifera),"Grown wild and cultivated. FAO considers vegetable tallow and stillingia oil to be primary products (see below).",Tallowtree seed,305,,,"Oilcrops, Oil Equivalent",1732.0,, VEGETABLE TALLOW,"Obtained by pressure extraction or by solvent from the kernels of the fruit of the Borneo tallow tree and from the outer coating that surrounds the seeds of the fruit of the Chinese tallow tree. Used as a substitute for cocoa butter. Also used in soap, candles, medicines and cosmetics.",,306,,,fat,,, VEGETABLE TALLOW,See Chapter 14.,,306,,,"Oilcrops, Oil Equivalent",1732.0,, STILLINGIA OIL,"Obtained by solvent from the seeds of Stillingia sebifera. Used as a drying agent in paints and varnishes.",,307,,,fat,,, "[KAPOK FRUIT] Ceiba pentandra, Bombacaceae",The fruit of kapok contains fibre (see Chapter 14.,Kapok fruit,310,,,"Oilcrops, Oil Equivalent",1732.0,Perennial, Oil of Kapok,Obtained from shelled seeds by pressure. Used for food and soap.,,313,,,fat,,Perennial, Cake of Kapok,See Chapter,,314,,,"Oilcrops, Oil Equivalent",1732.0,Perennial, Cake of Kapok,Residue from oil extraction.,,314,,,fodder,,Perennial, [SEED COTTON] Gossypium spp.: Unginned cotton,"Grown for both seed and for fibre. FAO considers cottonseed, cotton lint and linters to be primary products. Lint content ranges from 30 to 40%, seed 55 to 65%, and linters 2 to 5% though they are not always separated.",Seed cotton,328,,,"Oilcrops, Oil Equivalent",1732.0,Annual, COTTONSEED,Used for extracting oil.,Cottonseed,329,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Cottonseed,See Chapter 11.,,331,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Cottonseed,"Obtained first by pressure extraction from the kernels of cotton seeds. The residue from this process is then exposed to a solvent. Used mainly as a food.",,331,,,fat,,Annual, Cake of Cottonseed,Residue from oil extraction.,,332,,,fodder,,Annual, LINSEED Linum usitatissimum Flaxseed,"An annual herbaceous that is cultivated for its fibre as well as its oil.",Linseed,333,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Linseed,Obtained by pressure extraction. Used mainly in non-food items.,,334,,,fat,,, Oil of Linseed,See Chapter 11.,,334,,,"Oilcrops, Oil Equivalent",1732.0,, Cake of Linseed,Residue from oil extraction.,,335,,,fodder,,, HEMPSEED Cannabis sativa,"An annual herbaceous that is cultivated for its fibre as well as its oil. In major producing countries oil is extracted from the seeds.",Hempseed,336,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Hempseed,See Chapter 11.,,337,,,"Oilcrops, Oil Equivalent",1732.0,, Oil of Hempseed,"Obtained either by pressure extraction or by solvent. Used mainly in non-food items.",,337,,,fat,,, Cake of Hempseed,Residue from oil extraction.,,338,,,fodder,,, "OILSEEDS NES Includes inter alia: beech nut (Fagus sylvatica);(Aleurites moluccana);(Carapa guineensis);(Croton tiglium);(Bassia latifolia);(Guizotia abyssinica);(Licania rigida);(Perilla frutescens);(Jatropha curcas);(Shorea robusta);(Pongamia glabra);(Astrocaryum spp.)","Other oilseeds, oleaginous fruits and nuts that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report commodities under this heading that are classified individually by FAO. Also included under this code are tea seeds, grape pips and tomato seeds from which oil is extracted.",Oilseeds nes,339,,,"Oilcrops, Oil Equivalent",1732.0,Annual, Oil of Vegetable Origin nes,"Includes, inter alia, myrtle wax and Japan wax.",,340,,,fat,,, Oil of Vegetable Origin nes,See Chapter 11.,,340,,,"Oilcrops, Oil Equivalent",1732.0,, Cake of Oilseeds nes,Residue from oil extraction.,,341,,,fodder,,, Flour of Oilseeds,"Flours and meals of oilseeds and oleaginous fruits (excluding mustard), non defatted or partially defatted.",,343,,,"Oilcrops, Oil Equivalent",1732.0,, "CABBAGES Chinese, mustard cabbage, pak-choi (Brassica chinensis); white, red, savoy cabbage, Brussels sprouts, collards, kale and kohlrabi (Brassica oleracea all var. except botrytis)",,Cabbages and other brassicas,358,,,Vegetables Primary,1735.0,Annual, "ARTICHOKES Cynara scolymus",,Artichokes,366,,,Vegetables Primary,1735.0,Perennial, "ASPARAGUS Asparagus officinalis",,Asparagus,367,,,Vegetables Primary,1735.0,Perennial, "LETTUCE Lactuca sativa; witloof chicory (Cichorium intybus var. foliosum); endive (C. endivia var. crispa); escarole chicory (C. endivia var. latifolia)",,Lettuce and chicory,372,,,Vegetables Primary,1735.0,Annual, "SPINACH Spinacia oleracea","Trade figures may include New Zealand spinach (Tetragonia espansa) and orache (garden) spinach (Atriplex hortensis).",Spinach,373,,,Vegetables Primary,1735.0,Annual, "CASSAVA LEAVES Manihot esculenta; M. utilissima",Young cassava leaves are eaten in some areas of Africa as a vegetable.,,378,,,Vegetables Primary,1735.0,, "TOMATOES, FRESH Lycopersicon esculentum",,Tomatoes,388,,,Vegetables Primary,1735.0,Annual, Juice of Tomatoes,"Juice is obtained by treating tomatoes with cold or hot water or with steam. The juice then undergoes various processes, such as clarification, homogenization, sterilization, etc.",,390,,,Vegetables Primary,1735.0,Annual, Paste of Tomatoes,"Tomatoes prepared or preserved o/t by vinegar, in the form of paste, pur‚e or concentrate. Includes juice of dry weight content of 7% or more.",,391,,,Vegetables Primary,1735.0,Annual, "Tomatoes, Peeled",Prepared or preserved o/t by vinegar; either whole or in pieces.,,392,,,Vegetables Primary,1735.0,Annual, "CAULIFLOWER Brassica oleracea var. botrytis, subvariety cauliflora and cymosa",Includes headed broccoli.,Cauliflowers and broccoli,393,,,Vegetables Primary,1735.0,Annual, "PUMPKINS, SQUASH, GOURDS Cucurbita spp",Includes marrows.,"Pumpkins, squash and gourds",394,,,Vegetables Primary,1735.0,Annual, "CUCUMBERS, GHERKINS Cucumis sativus",,Cucumbers and gherkins,397,,,Vegetables Primary,1735.0,Annual, "EGGPLANTS Solanum melongena",Also called aubergines.,Eggplants (aubergines),399,,,Vegetables Primary,1735.0,, "CHILLIES, PEPPERS (GREEN) Capsicum annuum; C. fructescens; Pimenta officinalis","Production data exclude crops cultivated explicitly as spices. In contrast, trade data include these crops, provided they are fresh, uncrushed and unground.","Chillies and peppers, green",401,,,Vegetables Primary,1735.0,Annual, "ONIONS, SHALLOTS (GREEN) shallots (Allium ascalonicum); onions (A. cepa); welsh onions (A. fistulosum)","Young onions pulled before the bulb has enlarged; used especially in salads. Includes onion sets.","Onions, shallots, green",402,,,Vegetables Primary,1735.0,Annual, "ONIONS, DRY Allium cepa","Includes onions at a mature stage, but not dehydrated onions.","Onions, dry",403,,,Vegetables Primary,1735.0,Annual, "GARLIC Allium sativum",,Garlic,406,,,Vegetables Primary,1735.0,Annual, "LEEKS AND OTHER ALLIACEOUS VEGETAB leeks (Allium porrum); chives (A. schoenoprasum); other alliac. (Allium varieties except those of 0402, 0403 and 0406)",,"Leeks, other alliaceous vegetables",407,,,Vegetables Primary,1735.0,Annual, "BEANS, GREEN Phaseolus and Vigna spp.",For shelling.,"Beans, green",414,,,Vegetables Primary,1735.0,Annual, "PEAS, GREEN Pisum sativum","Mostly for shelling, but including edible- podded peas or sugar peas.","Peas, green",417,,,Vegetables Primary,1735.0,Annual, "BROAD BEANS, GREEN Vicia faba",For shelling.,"Vegetables, leguminous nes",420,,,Vegetables Primary,1735.0,, "STRING BEANS Phaseolus vulgaris; Vigna spp",Not for shelling,String beans,423,,,Vegetables Primary,1735.0,Annual, "CARROTS Daucus carota",Trade data may include turnips (Brassica rapa var. rapifera).,Carrots and turnips,426,,,Vegetables Primary,1735.0,Annual, "OKRA Abelmoschus esculentus; Hibiscus esculentus",Also called gombo.,Okra,430,,,Vegetables Primary,1735.0,Annual, "GREEN CORN (MAIZE) Zea mays, particularly var. saccharata","Maize harvested green for food. Saccharata variety is commonly known as sweet corn.","Maize, green",446,,,Vegetables Primary,1735.0,Annual, "Sweet Corn, Frozen","Either uncooked, or cooked by steaming or boiling in water, and then frozen.",,447,,,Vegetables Primary,1735.0,, "Sweet Corn, Prepared or Preserved","Prepared or preserved other than by vinegar or acetic acid; not frozen.",,448,,,Vegetables Primary,1735.0,, "MUSHROOMS Including inter alia: Boletus edulis; Agaricus campestris; Morchella spp. and Tuber magnatum",Cultivated or spontaneous. Includes truffles.,Mushrooms and truffles,449,,,Vegetables Primary,1735.0,, Dried Mushrooms,"Mushrooms and truffles, whether dried, dehydrated, evaporated or freeze-dried.",,450,,,Vegetables Primary,1735.0,, Canned Mushrooms,"Mushrooms and truffles, prepared or preserved o/t by vinegar or acetic acid; either whole, in pieces, or homogenized.",,451,,,Vegetables Primary,1735.0,, "CHICORY ROOTS horium intybus; C. sativum",Unroasted chicory roots.,Chicory roots,459,,,tobacco,,, "VEGETABLE PRODUCTS, FRESH OR DRY NE","Fruit stones, kernels and other vegetable products used primarily for human food that are not specified or included elsewhere.",,460,,,tobacco,,, "CAROBS (Ceratonia siliqua) Carob-tree, locust bean","Includes also seeds. Mainly used as an animal feed and for industrial purposes. Rich in pectin.",Carobs,461,,,tobacco,,Perennial, "VEGETABLES, FRESH NES> Including inter alia: bamboo shoots (Bambusa spp.); beets, chards (Beta vulgaris); capers (Capparis spinosa); cardoons (Cynara cardunculus); celery (Apium graveolens); chervil (Anthriscus cerefolium); cress (Lepidium sativum); fennel (Foeniculum vulgare); horseradish (Cochlearia armoracia); marjoram, sweet (Majorana hortensis); oyster plant (Tragopogon porrifolius); parsley (Petroselinum crispum); parsnips (Pastinaca sativa); radish (Raphanus sativus); rhubarb (Rheum spp.); rutabagas, swedes (Brassica napus); savory (Satureja hortensis); scorzonera (Scorzonera hispanica); sorrel (Rumex acetosa); soybean sprouts tarragon (Artemisia dracunculus); watercress (Nasturtium officinale)","Other vegetables that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report vegetables under this heading that are classified individually by FAO.","Vegetables, fresh nes",463,,,Vegetables Primary,1735.0,Annual, Juice of Vegetables nes,"Juice obtained by pressing, or by treatment with water or with steam, then submitted to various processes. Vegetable juice may contain added salt, spices or flavouring substances.",,466,,,Vegetables Primary,1735.0,Annual, "Vegetables, Dehydrated","Vegetables that are dried, dehydrated, evaporated or freeze-dried. Includes dried vegetables that are broken or powdered.",,469,,,Vegetables Primary,1735.0,, Vegetables in Vinegar,"Vegetables, fruit, nuts and other edible parts of plants, prepared or preserved with vinegar or acetic acid, with or without added sugar, salt, spices, etc. Includes pickles.",,471,,,Vegetables Primary,1735.0,, "Vegetables, Preserved nes","Vegetables prepared or preserved o/t by vinegar and which have not been frozen.",,472,,,Vegetables Primary,1735.0,, "Vegetables, Frozen","Vegetables, either uncooked, or cooked by steaming or boiling in water, and then frozen.",,473,,,Vegetables Primary,1735.0,, "Vegetables, Temporarily preserved","Vegetables preserved with SO2, brine, etc., but which are unsuitable for consumption in that state.",,474,,,Vegetables Primary,1735.0,, "Vegetables, Preserved (Frozen)","Vegetables that are prepared or preserved o/t by vinegar, and then frozen.",,475,,,Vegetables Primary,1735.0,, Homogenized Vegetable,"Preparations Vegetables prepared for dietetic and infant food.",,476,,,Vegetables Primary,1735.0,, "BANANAS Musa sapientum; M. cavendishii; M. nana","Bananas are normally eaten raw. Trade figures may include dried bananas. Data should be reported excluding the weight of the central stalk.",Bananas,486,,,Fruit Primary,1738.0,Perennial,6.0 "PLANTAINS Musa paradisiaca","Generally known as a cooking banana. Data should be reported excluding the weight of the central stalk",Plantains and others,489,,,Fruit Primary,1738.0,Perennial, "ORANGES common, sweet orange (Citrus sinensis); bitter orange (C. aurantium)",Bitter oranges are used primarily in the preparation of marmalade.,Oranges,490,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 Juice of Orange,"Juice is obtained by mechanical extractors, or by pressing, and is then submitted to various processes. Unfermented, it may or may not be frozen. For direct consumption.",,491,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "Orange Juice, Concentrated","Juice that is obtained by a concentration process in which the water is physically removed from the juice until it has not less than 20% of solids by weight. It is then reconstituted with water before consumption. Unfermented, it may or may not be frozen.",,492,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "TANGERINES, MANDARINS, CLEMENTINES, SATSUMAS mandarin, tangerine (Citrus reticulata); clementine, satsuma (C. unshiu)",,"Tangerines, mandarins, clementines, satsumas",495,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 Juice of Tangerine,See 0491.,,496,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "LEMONS AND LIMES lemon (Citrus limon); sour lime (C. aurantifolia); sweet lime (C. limetta)",,Lemons and limes,497,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 Juice of Lemon,See 0491.,,498,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "Lemon Juice, Concentrated",See 0492.,,499,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "GRAPEFRUIT AND POMELO Citrus maxima; C. grandis; C. paradisi",,Grapefruit (inc. pomelos),507,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 Juice of Grapefruit,See 0491.,,509,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "Grapefruit Juice, Concentrated",See 0492.,,510,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "CITRUS FRUIT NES Including inter alia: bergamot (Citrus bergamia); citron (C. medica var. cedrata); chinotto (C. myrtifolia); kumquat (Fortunella japonica)","Some minor varieties of citrus are used primarily in the preparation of perfumes and soft drinks.","Fruit, citrus nes",512,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 Juice of Citrus Fruit nes,See 0491.,,513,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 "Citrus Juice, Concentrated nes",See 0492.,,514,"Citrus fruit, total",1804.0,Fruit Primary,1738.0,Perennial,50.0 APPLES,,Apples,515,,,Fruit Primary,1738.0,Perennial,100.0 "Cider, etc.","Fermented beverages nes (e.g. cider, perry, mead), including alcoholic beverages (that are not distilled) made from cereals, roots and fruits, that are not included under other headings, e.g. beer from plantains and ginger.",,517,,,beverage,,Perennial,100.0 "Cider, etc.",See Chapter 15.,,517,,,Fruit Primary,1738.0,Perennial,100.0 Apple Juice,See 0491.,,518,,,Fruit Primary,1738.0,Perennial,100.0 "Apple Juice, Concentrated",See 0492.,,519,,,Fruit Primary,1738.0,Perennial,100.0 "PEARS Pyrus communis",,Pears,521,,,Fruit Primary,1738.0,Perennial, "QUINCES Cydonia oblonga; C. vulgaris; C. japonica",,Quinces,523,,,Fruit Primary,1738.0,, "APRICOTS Prunus armeniaca",,Apricots,526,,,Fruit Primary,1738.0,Perennial, "Apricots, Dried","Prepared either by direct drying in the sun or by industrial processes. May be marketed as slices or blocks of pulp, either dried or evaporated.",,527,,,Fruit Primary,1738.0,Perennial, "SOUR CHERRIES Prunus cerasus; Cerasus acida",&NBsp,"Cherries, sour",530,,,Fruit Primary,1738.0,, "CHERRIES mazzard, sweet cherry (Prunus avium; Cerasus avium); hard-fleshed cherry (var. duracina); heart cherry (var. juliana)",,Cherries,531,,,Fruit Primary,1738.0,, "PEACHES AND NECTARINES Prunus persica; Amygdalus persica; Persica laevis",,Peaches and nectarines,534,,,Fruit Primary,1738.0,, "PLUMS greengage, mirabelle, damson (Prunus domestica); sloe (P. spinosa)",,Plums and sloes,536,,,Fruit Primary,1738.0,Perennial, "Plums, Dried",See 0527. Known as prunes.,,537,,,Fruit Primary,1738.0,Perennial, Juice of Plum,See 0491.,,538,,,Fruit Primary,1738.0,Perennial, "Juice of Plum, Concentrated",See 0492.,,539,,,Fruit Primary,1738.0,Perennial, "STONE FRUIT, FRESH NES","Other stone fruit not separately identified. In some countries, apricots, cherries, peaches, nectarines and plums are reported under this general category.","Fruit, stone nes",541,,,Fruit Primary,1738.0,, POME FRUIT NES,"Other pome fruit not separately identified. In some countries apples, pears and quinces are reported under this general category.","Fruit, pome nes",542,,,Fruit Primary,1738.0,, "STRAWBERRIES Fragaria spp.",,Strawberries,544,,,Fruit Primary,1738.0,Perennial, "RASPBERRIES ubus idaeus","Trade data may include blackberries, mulberries and loganberries (a cross between the raspberry and blackberry).",Raspberries,547,,,Fruit Primary,1738.0,Perennial, "GOOSEBERRIES Ribes grossularia","Trade data may sometimes include black, white or red currants.",Gooseberries,549,,,Fruit Primary,1738.0,Perennial, "CURRANTS black (Ribes nigrum); red and white",,Currants,550,,,Fruit Primary,1738.0,Perennial, "BLUEBERRIES European blueberry, wild bilberry, whortleberry (Vaccinium myrtillus); American blueberry (V. corymbosum)","Trade data may include cranberries, myrtle berries and other fruits of the genus Vaccinium.",Blueberries,552,,,Fruit Primary,1738.0,Perennial, "CRANBERRIES American cranberry (Vaccinium macrocarpon); European cranberry (V. oxycoccus)","Trade data may include blueberries, myrtle berries and other fruits of the genus Vaccinium.",Cranberries,554,,,Fruit Primary,1738.0,Perennial, "BERRIES NES Including inter alia: blackberry (Morus nigra); loganberry; white, red mulberry (M. alba; M. rubra); myrtle berry (Myrtus communis) huckleberry, dangleberry (Gaylussacia spp.)","Other berries not separately identified. In some countries, some or all of the berries listed previously are reported under this general category.",Berries nes,558,,,Fruit Primary,1738.0,Perennial, "GRAPES Vitis vinifera",Includes both table and wine grapes.,Grapes,560,,,Fruit Primary,1738.0,Perennial, Raisins,Dried grapes. Includes sultanas and currants.,,561,,,Fruit Primary,1738.0,Perennial, Juice of Grape,See 0491. Includes unfermented grape must.,,562,,,Fruit Primary,1738.0,Perennial, Must of Grape,See Chapter 15.,,563,,,Fruit Primary,1738.0,Perennial, Must of Grape,"Grape must that has partially fermented, whether or not fermentation has been arrested, as well as unfermented grape must to which alcohol has been added.",,563,,,beverage,,Perennial, Wine,"Wines of fresh grapes of all qualities, including sparkling, fortified and dessert wines.",,564,,,beverage,,Perennial, "Vermouths, etc.",See Chapter 11.,,565,,,Fruit Primary,1738.0,Perennial, "Vermouths, etc.","Beverages made with wine of fresh grapes and flavoured with aromatic substances.",,565,,,beverage,,Perennial, Marc of Grape,Residues from the pressing of grapes. Used also for distilling.,,566,,,fodder,,Perennial, "WATERMELONS Citrullus vulgaris",,Watermelons,567,,,Vegetables Primary,1735.0,Annual, "MELONS, CANTALOUPES",,"Melons, other (inc.cantaloupes)",568,,,Vegetables Primary,1735.0,Annual, "FIGS Ficus carica",,Figs,569,,,Fruit Primary,1738.0,Perennial, "Figs, Dried",See 0527.,,570,,,Fruit Primary,1738.0,Perennial, "MANGOES Mangifera indica","Trade figures may include dried mangoes, guavas and mangosteens, including both fresh and dried.","Mangoes, mangosteens, guavas",571,,,Fruit Primary,1738.0,Perennial,300.0 "AVOCADOS Persea americana",,Avocados,572,,,Fruit Primary,1738.0,Perennial, "PINEAPPLES Ananas comosus; A. sativ",Trade figures may include dried pineapples.,Pineapples,574,,,Fruit Primary,1738.0,Perennial,7.0 "Pineapples, Canned","Fruit pulp prepared in water, syrup, etc.",,575,,,Fruit Primary,1738.0,Perennial,7.0 Juice of Pineapples,See 0491.,,576,,,Fruit Primary,1738.0,Perennial,7.0 "DATES Phoenix dactylifera",Includes fresh and dried fruit.,Dates,577,,,Fruit Primary,1738.0,Perennial,150.0 "Juice of Pineapples, Concentrated",See 0492. Soluble fruit solids of not less than 27% by weight.,,580,,,Fruit Primary,1738.0,Perennial,7.0 Juice of Mango,See 0491.,,583,,,Fruit Primary,1738.0,Perennial,300.0 Mango Pulp,"Fruit pulp prepared in water, syrup, etc.",,584,,,Fruit Primary,1738.0,Perennial,300.0 "PERSIMONS Diospyros kaki: D. virginiana",,Persimmons,587,,,Fruit Primary,1738.0,Perennial, "CASHEWAPPLE Anacardium occidentale","The thickened, fleshy stem below the cashew nut. When soft it is used for jam.",Cashewapple,591,,,Fruit Primary,1738.0,Perennial, "KIWI FRUIT Actinidia chinensis",,Kiwi fruit,592,,,Fruit Primary,1738.0,Perennial, "PAPAYAS Carica papaya",,Papayas,600,,,Fruit Primary,1738.0,Perennial,5.0 "FRUIT, TROPICAL (FRESH) NES Including inter alia: breadfruit (Artocarpus incisa); carambola (Averrhoa carambola); cherimoya, custard apple (Annona spp.); durian (Durio zibethinus); feijoa (Feijoa sellowiana); guava (Psidium guajava); hog plum, mombin (Spondias spp.); jackfruit (Artocarpus integrifolia); longan (Nephelium longan); mammee (Mammea americana); mangosteen (Garcinia mangostana); naranjillo (Solanum quitoense); passion fruit (Passiflora edulis); rambutan (Nephelium lappaceum); sapote, mamey colorado (Calocarpum mammosum); sapodilla (Achras sapota); star apple, cainito (Chrysophyllum spp.)","Other tropical fresh fruit that are not identified separately because of their minor relevance at the international level. In some countries mangoes, avocados, pineapples, dates and papayas are reported under this general category.","Fruit, tropical fresh nes",603,,,Fruit Primary,1738.0,Perennial, "Fruit, Tropical (Dried) nes","Including, whenever possible, dried bananas, plantains and pineapples as well as other unlisted tropical fruits.",,604,,,Fruit Primary,1738.0,Perennial, "FRUIT, FRESH NES Including inter alia: azarole (Crataegus azarolus); babaco (Carica pentagona); elderberry (Sambucus nigra); jujube (Zizyphus jujuba); litchi (Nephelium litchi); loquat (Eriobotrya japonica); medlar (Mespilus germanica); pawpaw (Asimina triloba); pomegranate (Punica granatum); prickly pear (Opuntia ficus-indica); rose hips (Rosa spp.); rowanberry (Sorbus aucuparia); service-apple (Sorbus domestica); tamarind (Tamarindus indica); tree-strawberry (Arbutus unedo)","Other fresh fruit that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report fresh fruit under this heading that are classified separately by FAO.","Fruit, fresh nes",619,,,Fruit Primary,1738.0,Perennial, "Fruit, Dried nes","Dried fruit other than apricots, dates, citrus, figs, grapes, nuts and plums.",,620,,,Fruit Primary,1738.0,, Juice of Fruits nes,See 0491.,,622,,,Fruit Primary,1738.0,, "Fruit, Prepared nes","Fruit, nuts and peel, including frozen, prepared or preserved, jam, paste, marmalade, purF and cooked fruits, other than those listed separately.",,623,,,Fruit Primary,1738.0,, Flour of Fruits,"Includes the flour, meal, powder, nuts and peel of fruits.",,624,,,Fruit Primary,1738.0,, "Fruit, Nuts, Peel, Sugar Preserved","Fruit, nuts, fruit peel, and other parts of plants preserved with sugar (either drained, glazed or crystallized).",,625,,,Fruit Primary,1738.0,, "Homogenized Cooked Fruit, Prepared","Cooked fruit preparations, homogenized for dietetic and infant foods.",,626,,,Fruit Primary,1738.0,, "Pulp, Waste of Fruit for Feed",See Chapter 3.,,628,,,Fruit Primary,1738.0,, "Pulp, Waste of Fruit for Feed","Waste of fruit, fruit pomace and marc, excluding marc of grapes.",,628,,,fodder,,, Beet Tops,"Beet tops, consisting of the leaves and upper part of the root, are used for feed. They account for about 25% of plant weight, though it is uncertain how much, if any, of this is included in national production statistics.",,629,,,fodder,,, Beet Tops,See Chapter 11.,,629,,,sugar,,, Beet Tops,See Chapter 11.,,629,,,sugar,,, Cane Tops,"The leaves and upper part of the stalks, which are used for feed. The tops represent about 10% of the weight of the plant.",,630,,,fodder,,, Cane Tops,See Chapter 11.,,630,,,sugar,,, Cane Tops,See Chapter 11.,,630,,,sugar,,, "Waters, Ice and Snow","Includes natural or artificial mineral waters without added sugar, sweeteners or flavourings.",,631,,,beverage,,, "Alcohol, Non-Food Purposes","Includes undenatured ethyl alcohol (strength by volume of > 80%) and denatured (any strength).",,632,,,beverage,,, "Beverages, Non-Alcoholic","Includes sweetened or flavoured mineral waters and other non-alcoholic beverages, such as lemonade, orangeade, cola, etc. Excludes fruit and vegetable juices.",,633,,,beverage,,, "Beverages, Distilled Alcoholic","Includes undenatured ethyl alcohol (strength by volume < 80%); spirits, liqueurs and other spirituous beverages and preparations.",,634,,,beverage,,, Straw and Husks,"Cereal straw and husks, unprepared, whether or not chopped, ground, pressed, or in the form of pellets.",,635,,,fodder,,, Straw and Husks,See Chapter 11.,,635,,,"Cereals, Total",1717.0,, MAIZE FOR FORAGE,Maize cut green as grass.,,636,,,fodder,,Annual, SORGHUM FOR FORAGE,"Usually sweet sorghum, so called for the sweet juice in the stem, which is cut green as grass.",,637,,,fodder,,, "RYE GRASS FOR FORAGE Italian ryegrass (Lolium multiflorum); English, perennial ryegrass (L. perenne)",Quick-growing grasses.,,638,,,fodder,,, "GRASSES NES FOR FORAGE Including inter alia: bent, redtop, fiorin grass (Agrostis spp.); bluegrass (Poa spp.); Columbus grass (Sorghum almum); fescue (Festuca spp.); Napier, elephant grass (Pennisetum purpureum); orchard grass (Dactylis glomerata); Rhodes grass (Chloris gayana); Sudan grass (Sorghum vulgare var. sudanense); Timothy grass (Phleum pratense)","Includes species used for cereal production, if cut green for fodder.",,639,,,fodder,,, "CLOVER FOR FORAGE Trifolium spp.","Various species grown for pasture, green fodder or silage.",,640,,,fodder,,Annual, "ALFALFA FOR FORAGE Medicago sativa","A deep-rooted perennial herb used for green fodder, for hay or silage, and for pasture.",,641,,,fodder,,, GREEN OILSEEDS FOR SILAGE,Cut green as grass.,,642,,,fodder,,, "LEGUMES FOR SILAGE Including inter alia: birdsfoot, trefoil (Lotus corniculatus); lespedeza (Lespedeza spp.); kudzu (Pueraria lobata); sesbania (Sesbania spp.); sainfoin, esparcette (Onobrychis sativa); sulla (Hedysarum coronarium)","Includes species of pulses, if harvested for fodder.",,643,,,fodder,,, "CABBAGE FOR FODDER Brassica chinensis; B. oleracea",Especially cultivated for fodder.,,644,,,fodder,,, "PUMPKINS FOR FODDER Cucurbita spp. Especially cultivated for fodder.",,,645,,,fodder,,Annual, "TURNIPS FOR FODDER Brassica rapa var. rapifera",Especially cultivated for fodder.,,646,,,fodder,,, "BEETS FOR FODDER beet, beetroot, mangold (Beta vulgaris)",Especially cultivated for fodder.,,647,,,fodder,,, "CARROTS FOR FODDER Daucus carota",Especially cultivated for fodder.,,648,,,fodder,,, "SWEDES FOR FODDER rutabaga, swede, swede turnip (Brassica napus var napobrassica)",Especially cultivated for fodder.,,649,,,fodder,,, "Leaves, Tops and Vines nes","Vegetable products that are not specifically grown for animal feed, but are used for that purpose.",,650,,,fodder,,, Forage Products nes,Plants specifically grown for animal feed.,,651,,,fodder,,, Vegetable Products for Feed nes,"Vegetable products, vegetable waste, residues and by-products from the industrial processing of vegetable materials.",,652,,,fodder,,, Food Wastes,"Sweetened forage and preparations of a kind used for animal feed, e.g. wine lees, argol.",,653,,,fodder,,, "VEGETABLES, ROOTS FODDER NES",Any other crop of the vegetable group that is cultivated for fodder.,,655,,,fodder,,, "COFFEE, GREEN Coffea spp. (arabica, robusta, liberica)",Raw coffee in all forms.,"Coffee, green",656,,,stimulant,,Perennial,20.0 "Coffee, Roasted","With or without caffeine, and whether or not ground.",,657,,,stimulant,,Perennial,20.0 Coffee Substitutes,Coffee substitutes containing coffee in any proportion.,,658,,,stimulant,,Perennial,20.0 Coffee Extracts,"Essences and concentrates, including instant coffee, roasted chicory and other coffee substitutes, extracts and essences thereof.",,659,,,stimulant,,Perennial,20.0 Coffee Husks and Skins,,,660,,,stimulant,,Perennial,20.0 "COCOA BEANS Theobroma cacao","The seeds contained in the fruit of the cacao- tree, including whole or broken, raw or roasted.","Cocoa, beans",661,,,stimulant,,Annual, Cocoa Paste,"Obtained by grinding roasted cocoa beans. Also called liquor. Not defatted.",,662,,,stimulant,,Annual, Cocoa Husks and Shells,Including skins and other cocoa waste.,,663,,,stimulant,,Annual, Cocoa Butter,"Obtained by hot-pressing either cocoa paste or the whole bean. Includes the fat and oil.",,664,,,stimulant,,Annual, Cocoa Powder and Cake,"Wholly or partly defatted paste (cake) and cake reduced to powder, without added sugar or other sweeteners.",,665,,,stimulant,,Annual, Chocolate Products nes,"Includes sweetened cocoa powder, chocolate and other food preparations containing cocoa, as well as sugar confectionery containing cocoa in any amount. Excludes white chocolate (see 0168 in Chapter .).",,666,,,stimulant,,Annual, "TEA Camellia sinensis; Thea sinensis; Thea assaamica","Includes green tea (unfermented), black tea (fermented), and partially fermented tea. Excludes green tea eaten as a vegetable.",Tea,667,,,stimulant,,Perennial,50.0 "MATE Ilex paraguayensis","The dried leaves of certain shrubs of the holly family which grow in South America. Prepared in a way similar to tea.",Maté,671,,,stimulant,,Perennial,2.0 Extracts of Tea and Mate,"Includes essences, concentrates and preparations of tea and mat‚.",,672,,,stimulant,,Perennial, TEA NES,"Various plants used for making infusions like tea, i.e. herbal teas.",,674,,,stimulant,,Perennial,50.0 "HOPS Humulus lupulus","Hop cones, fresh or dried, whether or not ground, powdered or in the form of pellets. Includes lupuline, a yellow resinous powder that covers the hop cones. Mainly used in the brewing industry to give flavour to beer.",Hops,677,,,tobacco,,, "PEPPER black, white pepper (Piper nigrum); long pepper (P. longum)","Perennial climbing vines. Includes whole, crushed or ground berries. Black pepper is produced from partially ripe berries, while white pepper is from fully ripe berries which have had the outer hull removed.",Pepper (piper spp.),687,,,spice,,Annual, "PIMENTO red and cayenne pepper, paprika, chillies (Capsicum frutescens; C. annuum); allspice, Jamaica pepper (Pimenta officinalis)","Uncrushed or unground fresh pimentos are considered to be vegetables. See Chapter 7.","Chillies and peppers, dry",689,,,spice,,Annual, "VANILLA Vanilla planifolia; V. pompona","The fruit (or bean) of a climbing plant of the orchid family. Includes whole, crushed or ground.",Vanilla,692,,,spice,,, "CINNAMON (CANELLA) Ceylon cinnamon (Cinnamomum zeylanicum); Chinese, common cinnamon, cassia (C. cassia)","The inner bark of young branches of certain trees of the Laurus family. Includes cinnamon- tree flowers, cinnamon fruit and cinnamon waste (chips), whether whole, crushed or ground.",Cinnamon (cannella),693,,,spice,,Perennial, "CLOVES Eugenia caryophyllata; Caryophyllus aromaticus","The whole fruit of the clove tree, including the flowers picked before maturity and dried in the sun, and the stems of the clove flowers.",Cloves,698,,,spice,,Annual, "NUTMEG, MACE, CARDAMONS nutmeg, mace (Myristica fragrans); cluster cardamon (Elettaria cardamomum); other cardamons (Aframomum angustifolium; A. hambury; Amomun aromaticum; A. cardamomum); Malaguetta pepper, grains of paradise (Aframomum melegueta)","Nutmeg is the inner brown kernel of the fruit of the nutmeg tree. Mace is the net-like membrane between the outer shell and the kernel. Cardamon seeds are enclosed in the capsule produced by perennial herbs of the Zingiberaceae family.","Nutmeg, mace and cardamoms",702,,,spice,,Perennial,60.0 "ANISE, BADIAN, FENNEL Include: anise (Pimpinella anisum); badian or star anise (Illicium verum); caraway (Carum carvi); coriander (Coriandrum sativum); cumin (Cuminum cyminum); fennel (Foeniculum vulgare); juniper berries (Juniperus communis)","Seeds and berries from the various plants listed. They are normally used as spices, but also have industrial (e.g. in distilleries) and medicinal applications.","Anise, badian, fennel, coriander",711,,,spice,,Perennial, "GINGER Zingiber officinale","Rhizome of a perennial herb. It also is used for making beverages. Includes fresh, provisionally preserved or dried, whereas ginger preserved in sugar or syrup is excluded.",Ginger,720,,,spice,,Annual, "SPICES NES Including inter alia: bay leaves (Laurus nobilis); dill seed (Anethum graveolens); fenugreek seed (Trigonella foenum-graecum); saffron (Crocus sativus); thyme (Thymus vulgaris); turmeric (Curcuma longa)","Other spices that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report spices under this heading that are classified individually by FAO. This heading also includes curry powder and other mixtures of different spices.",Spices nes,723,,,spice,,, OIL OF CITRONELLA,Essential oil extracted from Cymbopogon nardus.,,737,,,tobacco,,, "PEPPERMINT, SPEARMINT Mentha spp.: M. piperita","Leaves and flowers are used in the perfumery, food and other industries.",Peppermint,748,,,tobacco,,Perennial, ESSENTIAL OILS NES,"Extracted from many plants and used mainly in the perfumery, food and other industries.",,753,,,tobacco,,, "PYRETHRUM, DRIED FLOWERS Chrysanthemum cinerariifolium","Includes leaves, stems and flowers. For insecticides, fungicides and similar products.","Pyrethrum, dried",754,,,tobacco,,Perennial, Pyrethrum Extract,Obtained from the flowers by extraction using an organic solvent.,,755,,,tobacco,,, Pyrethrum Marc,The waste from pyrethrum processing.,,756,,,tobacco,,, "COTTON LINT Gossypium spp","Fibres from ginning seed cotton that have not been carded or combed. Trade data also include fibres that have been cleaned, bleached, dyed or rendered absorbent.",Cotton lint,767,,,Fibre Crops Primary,1753.0,Annual, "Cotton, Carded or Combed","Cotton (including garnetted stock and other cotton waste) which has been carded or combed, whether or not further prepared for spinning. May be bleached or dyed.",,768,,,Fibre Crops Primary,1753.0,Annual, Cotton Waste,"Waste is produced when cotton is prepared for spinning, or during spinning operations, weaving, knitting, etc., or from garnetting cotton goods.",,769,,,Fibre Crops Primary,1753.0,Annual, Cotton Linters,"Very short fibres that cover the seeds after ginning and that are very high in cellulose.",,770,,,Fibre Crops Primary,1753.0,Annual, "[FLAX, RAW OR RETTED] Linum usitatissimum Flax Straw","Flax is cultivated for seed as well as for fibre. The fibre is obtained from the stem of the plant. Data are reported in terms of straw.",,771,,,Fibre Crops Primary,1753.0,, FLAX FIBRE AND TOW,"Broken, scutched, hackled etc. but not spun. Traditionally, FAO has used this commodity to identify production in its raw state; in reality, the primary agricultural product is the commodity 0771, which can either be used for the production of fibre or for other purposes.",Flax fibre and tow,773,,,Fibre Crops Primary,1753.0,, Flax Tow and Waste,Includes yarn waste and garnetted stock.,,774,,,Fibre Crops Primary,1753.0,, "HEMP FIBRE AND TOW Cannabis sativa","This plant is cultivated for seed as well as for fibre. The fibre is obtained from the stem of the plant. Trade data include raw, retted, scutched, combed fibre, tow and waste.",Hemp tow waste,777,,,Fibre Crops Primary,1753.0,, "KAPOK FIBRE Ceiba pentandra","This plant is cultivated for seed as well as for fibre. Trade data cover only fibres that have been crushed, carded or combed for spinning.",,778,,,Fibre Crops Primary,1753.0,, "JUTE white jute (Corchorus capsularis); red jute, tossa",,Jute,780,,,Fibre Crops Primary,1753.0,, "JUTE-LIKE FIBRES Including inter alia: China jute (Abutilon avicennae); Congo jute, malva, paka (Urena lobata; U. sinuata); Indian flax (Abroma augusta); kenaf, meshta (Hibiscus cannabinus); rosella hemp (H. sabdariffa); sunn hemp (Crotalaria juncea)","This definition covers all textile fibres extracted from the stems of dicotyledonous plants, o/t flax, ramie, true hemp and true jute. For trade coverage see 0780.","Bastfibres, other",782,,,Fibre Crops Primary,1753.0,, "RAMIE China grass, white ramie (Boehmeria nivea); rhea, green ramie (B. tenacissima)","Ramie fibre is obtained from the bast of the plant. For trade coverage see 0780",Ramie,788,,,Fibre Crops Primary,1753.0,Perennial, "SISAL Agave sisalana","Sisal fibre is obtained from the leaves of the plant. It also is used as an ornamental plant. Trade data cover fibres that are raw, prepared for spinning, and tow and waste, including yarn waste and garnetted stock.",Sisal,789,,,Fibre Crops Primary,1753.0,Perennial, "AGAVE FIBRES NES Including inter alia: Haiti hemp (Agave foetida); henequen (A. fourcroydes); ixtle, tampico (A. lecheguilla); maguey (A. cantala); pita (A. americana); Salvador hemp (A. letonae)","See 0789. The leaves of some agave varieties are used for the production of alcoholic beverages, such as aquamiel, mezcal, pulque and tequila.",Agave fibres nes,800,,,Fibre Crops Primary,1753.0,, "ABACA MANILA HEMP Musa textilis","The fibre is obtained from stalks of certain banana trees. For trade coverage see 0789.",Manila fibre (abaca),809,,,Fibre Crops Primary,1753.0,, "COIR Cocos nucifera","Coir fibre is obtained from the fibrous covering of the mesocarp. For trade coverage see 0789.",Coir,813,,,Fibre Crops Primary,1753.0,Perennial,70.0 "FIBRE CROPS NES Including inter alia: alfa, esparto (Lygeum spartum; Stipa tenacissima); bowstring hemp (Sansevieria spp.); caroa (Neoglaziovia variegata); fuque fibre (Furcraea macrophylla); Mauritius hemp (F. gigantea); New Zealand flax (Phormium tenax); palma ixtle (Samuela carnerosana)","Other fibres that are not identified separately because of their minor relevance at the international level. Because of their limited local importance, some countries report vegetable fibres under this commodity heading that are classified individually by FAO. The fibre is obtained from the leaves, stalks or fruit of the plant. In instances where the fibrous part is normally used for other purposes, data cover only those fibres intended for spinning. For trade coverage see 0789.",Fibre crops nes,821,,,Fibre Crops Primary,1753.0,, "TOBACCO LEAVES Nicotiana tabacum","Unmanufactured dry tobacco, including refuse that is not stemmed or stripped, or is partly or wholly stemmed or stripped.","Tobacco, unmanufactured",826,,,tobacco,,Annual, Cigarettes,Includes cigarettes of tobacco substitutes.,,828,,,tobacco,,Annual, Cigars and Cheroots,"Includes cigars, cheroots and cigarillos of tobacco substitutes.",,829,,,tobacco,,Annual, Tobacco Products nes,"Includes smoking, chewing, snuff tobacco, homogenized or compressed tobacco, manufactured tobacco substitutes, tobacco extracts and essences.",,831,,,tobacco,,Annual, "NATURAL RUBBER Hevea brasiliensis Latex","The liquid secreted by the rubber tree. Includes stabilized or concentrated latex and prevulcanized rubber latex. In trade figures, liquid weight is converted to dry weight at 60%.","Rubber, natural",836,,,tobacco,,Perennial,32.0 "Rubber, Natural (Dry)","In the form of sheets, cr坧es, re-agglomerated granules, free-flowing powders, etc.; includes technically specified natural rubber (TSNR).",,837,,,tobacco,,Perennial,32.0 "NATURAL GUMS Including inter alia: balata (Manilkara bidentata",,"Gums, natural",839,,,tobacco,,, "Compound Feed, Cattle","Prepared animal feed designed to provide a balanced diet (complete feed).",,840,,,fodder,,, "Compound Feed, Poultry",See 0840.,,841,,,fodder,,, "Compound Feed, Pigs",See 0840.,,842,,,fodder,,, Pet Food,"International trade classifications cover only dog and cat food. FAO trade data also cover food for other pets (i.e. fish, birds, etc.), whenever possible.",,843,,,fodder,,, Compound Feed nes,See 0840. See general note in the introduction.,,845,,,fodder,,, Gluten Feed and Meal,See Chapter 11.,,846,,,"Cereals, Total",1717.0,, Gluten Feed and Meal,"Generally, by-products of the wet milling of maize. Gluten feed consists of fibres, spent germ and steep liquor. Gluten meal contains endosperm protein fractions that remain following starch recovery (see Chapter 1.).",,846,,,fodder,,, Feed Yeast,Inactive dried yeast.,,849,,,fodder,,, Feed Supplements,"Prepared animal feed that supplements the basic farm produced feed with organic or inorganic substances.",,850,,,fodder,,, Non-Protein Nitrogens,"A mixture of different nutrients or substances that are used in making complete or supplementary feeds.",,851,,,fodder,,, Other Concentrates nes,See 0851.,,852,,,fodder,,, Vitamins,See 0851,,853,,,fodder,,, Feed Additives,See 0851.,,854,,,fodder,,, Feed Minerals,See 0851.,,855,,,fodder,,, "Hay, Non-Leguminous",Hay that is mainly from grasses.,,857,,,fodder,,, "Hay (Clover, Lucerne, etc.)",Hay from leguminous crops.,,858,,,fodder,,Annual, Hay nes,Hay from unspecified plants.,,859,,,fodder,,, RANGE PASTURES,,,860,,,fodder,,, IMPROVED PASTURES,,,861,,,fodder,,, Alfalfa Meal and Pellets,"Alfalfa (lucerne) dried, whole, cut, chopped, milled, pressed or pelletized.",,862,,,fodder,,, "CATTLE common ox (Bos taurus); zebu, humped ox (Bos indicus); Asiatic ox (subgenus Bibos); Tibetan yak (Poephagus grunniens)","Animals of the genus listed, regardless of age, sex, or purpose raised. Data are expressed in number of heads.",,866,,,livestock,,, MEAT OF CATTLE,"Meat of bovine animals, fresh, chilled or frozen, with bone in. Commontrade names are beef and veal.",,867,,,slaughter,,, "OFFALS OF CATTLE, EDIBLE","Fresh, chilled or frozen.",,868,,,slaughter,,, FAT OF CATTLE,See Chapter 14.,,869,,,slaughter,,, FAT OF CATTLE,"Unrendered slaughter fats from bovine animals, including edible and inedible fats that are removed in the course of dressing the carcass.",,869,,,fat,,, "MEAT OF CATTLE, BONELESS","Boneless meat of bovine animals, whether fresh, chilled or frozen.",,870,,,slaughter,,, "Cattle, Butcher Fat",Unrendered fats that are removed during butchering.,,871,,,fat,,, "Cattle, Butcher Fat",See Chapter 14.,,871,,,slaughter,,, "Beef and Veal, Dried, Salted, Smok","Meat of bovine animals, whether salted, in brine, dried or smoked.Includes edible flours and meals.",,872,,,slaughter,,, Meat Extracts,Extracts obtained by boiling meat under pressure and concentrating theresulting liquid after the fat has been removed. Includes juicesobtained by pressing raw meat. Whenever possible trade data excludefish extracts.,,873,,,slaughter,,, Sausages of Beef and Veal,"Preparations of meat or offal, whether chopped, minced or of blood.They may be raw, cooked or smoked and contain other ingredients, andare then enclosed in natural or artificial casings.",,874,,,slaughter,,, Beef and Veal Preparations nes,"Meat and offal (o/t liver) that are boiled, steamed, grilled, fried,roasted or otherwise cooked. Includes prepared meals that contain morethan 20% of meat and offal by weight.",,875,,,slaughter,,, Homogenized Meat Preparations,Preparations used in infant or dietetic food.,,877,,,slaughter,,, Liver Preparations,"Liver of any animal, excluding fatty livers of code 1060.",,878,,,slaughter,,, "COW MILK, WHOLE (FRESH)","Production data refer to raw milk containing all its constituents. Trade data normally cover milk from any animal, and refer to milk that is not concentrated, pasteurized, sterilized or other-wise preserved, homogenized or peptonized.",,882,,,animal,,, Standardized Milk,"Milk in which the fat content is adjusted to a predetermined value without altering any other constituents.",,883,,,animal,,, "Cream, Fresh","That portion of milk which is rich in milk fat and is separated by skimming or centrifuging.",,885,,,animal,,, Butter of Cow Milk,"Emulsion of milk fat and water that is obtained by churning cream. Trade data cover butter from the milk of any animal.",,886,,,animal,,, Ghee from Cow Milk,"Butter from which the water has been removed. Very common in hot countries. Includes also anhydrous butterfat or butter oil.",,887,,,animal,,, Skim Milk of Cows,Milk from which most of the fat has been removed.,,888,,,animal,,, "Whole Milk, Condensed","Milk and cream from which water has been partly removed after heat-treating and concentrating. Normally sucrose is added to give the product stability and bacteriological safety.",,889,,,animal,,, "Whey, Condensed",Whey paste.,,890,,,animal,,, Yoghurt,A fermented milk food.,,891,,,animal,,, "Yoghurt, Concentrated or Unconcent","Includes additives such as sugar, flavouring materials, fruit or cocoa.",,892,,,animal,,, "Buttermilk, Curdled Milk, Acidifie",Residue from butter making. Includes kephir.,,893,,,animal,,, "Whole Milk, Evaporated","Milk and cream from which the water has been partly removed and which has been heat- treated to render it bacteriologically safe and stable.",,894,,,animal,,, "Skim Milk, Evaporated","Same as 0894, but applied to skim milk.",,895,,,animal,,, "Skim Milk, Condensed","Same as 0889, but applied to skim milk.",,896,,,animal,,, Dry Whole Cow Milk,"Milk and cream from which water has been completely removed by various methods. In form of powder, granules or other solid forms. May contain added sugar or other sweeteners.",,897,,,animal,,, Dry Skim Cow Milk,"Same as 0897, but from skim milk. Normally does not exceed 1.5% fat content.",,898,,,animal,,, Dry Buttermilk,,,899,,,animal,,, Dry Whey,Used in both food and animal feed.,,900,,,animal,,, Cheese from Whole Cow Milk,"Curd of milk that has been coagulated and separated from whey. May include some skimmed milk.",,901,,,animal,,, "Whey, Fresh","The liquid part of the milk that remains after the separation of curd in cheese making. Its main food use is in the preparation of whey cheese, whey drinks and fermented whey drinks. The main industrial uses are in the manufacture of lactose, whey paste and dried whey.",,903,,,animal,,, Cheese from Skimmed Cow Milk,May include some whole milk.,,904,,,animal,,, Whey Cheese,,,905,,,animal,,, Processed Cheese,,,907,,,animal,,, Reconstituted Milk,"Obtained by adding water, fat, etc. to milk powder.",,908,,,animal,,, Products of Natural Milk Constitue,,,909,,,animal,,, Ice Cream and Edible Ice,"A product with a milk or cream base to which sweeteners, eggs, etc. have been added.",,910,,,animal,,, Egg Albumin,The main protein constituent of egg white.,,916,,,animal,,, Casein,"The main protein constituent of milk. Casein is obtained from skimmed milk by precipitation (curdling) with acids or rennet.",,917,,,animal,,, "CATTLE HIDES, FRESH","Green hide or skin as removed from the carcass of the animal (adult bovine). Used for production data only.",,919,,,hides,,, "Hides, Wet-Salted (Cattle)",Approximately 80-85% of green weight.,,920,,,hides,,, "Hides, Dry-Salted (Cattle)","Includes dry and dry-salted, approximately 35% and 55% of green weight, respectively.",,921,,,hides,,, "Hides nes, Cattle","Limed, pickled or otherwise preserved.",,922,,,hides,,, "SKINS, FRESH (CALVES)",See 0919. From young bovine animals.,,927,,,hides,,, "Skins, Wet-Salted (Calves)",See 0920.,,928,,,hides,,, "Skins, Dry-Salted (Calves)",See 0921.,,929,,,hides,,, "Skins nes, Calves",See 0922.,,930,,,hides,,, Indigenous Cattle Meat,,,944,,,slaughter,,, Biological Cattle Meat,,,945,,,slaughter,,, "BUFFALOES Indian, Asiatic, pigmy, water buffalo (Bubalus bubalus; B. arnee; B. depressicornis",,,946,,,livestock,,, BUFFALO MEAT,"Fresh, chilled or frozen, with bone in or boneless.",,947,,,slaughter,,, "OFFALS OF BUFFALO, EDIBLE","Fresh, chilled or frozen.",,948,,,slaughter,,, FAT OF BUFFALO,See 0869.,,949,,,fat,,, FAT OF BUFFALO,See Chapter 14.,,949,,,slaughter,,, BUFFALO MILK,See 0882 and derived products.,,951,,,animal,,, Butter of Buffalo Milk,,,952,,,animal,,, "Ghee, from Buffalo Milk",,,953,,,animal,,, Skim Milk of Buffalo,Cheese of Buffalo Milk,,954,,,animal,,, "BUFFALO HIDES, FRESH",See 0919. Both adult and young animals.,,957,,,hides,,, "Hides, Wet-Salted (Buffalo)",See 0920.,,958,,,hides,,, "Hides, Dry-Salted (Buffalo)",See 0921.,,959,,,hides,,, Indigenous Buffalo Meat,,,972,,,slaughter,,, Biological Buffalo Meat,,,973,,,slaughter,,, "SHEEP Ovis spp.","See 0866. Includes Uriel, Argali, Bighorn, Karakul and Astrakhan.",,976,,,livestock,,, MEAT OF SHEEP,"Meat of sheep and lamb, whether fresh, chilled or frozen, with bone inor boneless.",,977,,,slaughter,,, "OFFALS OF SHEEP, EDIBLE","Fresh, chilled or frozen.",,978,,,slaughter,,, FAT OF SHEEP,See Chapter 14.,,979,,,slaughter,,, FAT OF SHEEP,Unrendered slaughter fats of sheep. See 0869.,,979,,,fat,,, SHEEP MILK,See 0882 and derived products.,,982,,,animal,,, Butter and Ghee of Sheep Milk,,,983,,,animal,,, Cheese of Sheep Milk,,,984,,,animal,,, Skim Sheep Milk,,,985,,,animal,,, "WOOL, GREASY","A natural fibre taken from sheep or lambs. Includes fleece-washed, shorn and pulled wool (from slaughtered animals), but does not include carded or combed wool.",,987,,,Fibre Crops Primary,1753.0,, "Wool, Degreased","Includes scoured and carbonized, but does not include carded or combed wool.",,988,,,Fibre Crops Primary,1753.0,, Wool Grease and Lanolin,"Extracted from the soapy water in which wool has been scoured, or from greasy wool by meand of solvents. Lanolin is obtained by purifying wool grease. Includes wool grease olein and stearin.",,994,,,fat,,, "SHEEPSKINS, FRESH",See 0919. Both adult and young animals.,,995,,,hides,,, "Skins, Wet-Salted (Sheep)",Sheep and lamb skins without wool. See 0920.,,996,,,hides,,, "Skins, Dry-Salted (Sheep)",Sheep and lamb skins without wool. See 0921.,,997,,,hides,,, "Skins nes, Sheep",Sheep and lamb skins without wool. See 0922.,,998,,,hides,,, "Skins with Wool, Sheep","Sheep and lamb skins (excluding 1002), with wool on, salted, dried, limed, pickled or otherwise preserved.",,999,,,hides,,, KARAKUL SKINS,"Raw skins of Astrakhan, Caracul, Persian or similar lambs.",,1002,,,hides,,, "Wool, Shoddy","Garnetted stock of wool or of fine or coarse animal hair obtained by garnetting rags or waste of spinning, weaving, knitting etc.",,1007,,,Fibre Crops Primary,1753.0,, "Hair, Carded, Combed","Wool and fine or coarse animal hair, carded or combed, including combed wool in fragments.",,1008,,,Fibre Crops Primary,1753.0,, "Wool, Hair Waste","Noils of wool or animal hair not garnetted; other waste of wool and animal hair (excluding horsehair) not covered in 1007.",,1009,,,Fibre Crops Primary,1753.0,, Wool Tops,"Slivers consisting of long fibres laid parallel by combing and then wound into balls.",,1010,,,Fibre Crops Primary,1753.0,, Indigenous Sheep Meat,,,1012,,,slaughter,,, Biological Sheep Meat,,,1013,,,slaughter,,, "GOATS Capra spp.","See 0866. Includes Hircus, Ibex, Nubiana, Pyrenaica, Tibetana, Kashmir and Angora.",,1016,,,livestock,,, GOAT MEAT,"Meat of goats and kids, whether fresh, chilled or frozen, with bone inor boneless.",,1017,,,slaughter,,, "OFFALS OF GOATS, EDIBLE","Fresh, chilled or frozen.",,1018,,,slaughter,,, FAT OF GOATS,See Chapter 14.,,1019,,,slaughter,,, FAT OF GOATS,Unrendered slaughter fats of goats. See 0869.,,1019,,,fat,,, GOAT MILK,See 0882 and derived products.,,1020,,,animal,,, "Cheese of Goat Milk",,,1021,,,animal,,, "Butter of Goat Milk",,,1022,,,animal,,, Skim Milk of Goat,,,1023,,,animal,,, "GOATSKINS, FRESH",See 0919. Both adult and young animals.,,1025,,,hides,,, "Skins, Wet-Salted (Goats)",Includes kids. See 0920.,,1026,,,hides,,, "Skins, Dry-Salted (Goats)",Includes kids. See 0921.,,1027,,,hides,,, "Skins nes, Goats",Includes kids. See 0922.,,1028,,,hides,,, FINE GOAT HAIR,"Hair from cashmere, angora (mohair) and similar goats. Excludes carded or combed hair.",,1030,,,Fibre Crops Primary,1753.0,, COARSE GOAT HAIR,Common goat hair. Not carded or combed hair.,,1031,,,Fibre Crops Primary,1753.0,, Indigenous Goat Meat,,,1032,,,slaughter,,, Biological Goat Meat,,,1033,,,slaughter,,, "PIGS domestic pig (Sus domestica); wild boar (Sus scrofa)",See 0866. Excludes non-domesticated wild boars.,,1034,,,livestock,,, PIG MEAT,"Meat, with the bone in, of domestic or wild pigs (e.g. wild boars),whether fresh, chilled or frozen.",,1035,,,slaughter,,, "OFFALS OF PIGS, EDIBLE","Fresh, chilled or frozen.",,1036,,,slaughter,,, FAT OF PIGS,See Chapter 14.,,1037,,,slaughter,,, FAT OF PIGS,Unrendered slaughter fats of pigs. See 0869.,,1037,,,fat,,, PORK,"Pig meat, excluding butcher fat and bones.",,1038,,,slaughter,,, Bacon and Ham,"Meat of pigs, whether salted, in brine, dried or smoked.",,1039,,,slaughter,,, "Pig, Butcher Fat",See Chapter 14.,,1040,,,slaughter,,, "Pig, Butcher Fat",See 0871.,,1040,,,fat,,, Sausages of Pig Meat,See 0874.,,1041,,,slaughter,,, Pig Meat Preparations,See 0875.,,1042,,,slaughter,,, Lard,See Chapter 14.,,1043,,,slaughter,,, Lard,Rendered pig fat.,,1043,,,fat,,, "PIGSKINS, FRESH","See 0919. In many countries, pigskins are not removed from the carcasses.",,1044,,,hides,,, "Skins, Wet-Salted (Pigs)",See 0920.,,1045,,,hides,,, "Skins, Dry-Salted (Pigs)",See 0921.,,1046,,,hides,,, "Skins nes, Pigs",See 0922.,,1047,,,hides,,, Indigenous Pig Meat,,,1055,,,slaughter,,, Biological Pig Meat,,,1056,,,slaughter,,, "CHICKENS fowl (Gallus domesticus); Guinea fowl (Numida meleagris Domesticated birds only. Data are expressed in thousands.",,,1057,,,livestock,,, CHICKEN MEAT,"Fresh, chilled or frozen. May include all types of poultry meat ifnational statistics do not report separate data.",,1058,,,slaughter,,, OFFALS AND LIVER OF CHICKENS,"Fresh, chilled or frozen.",,1059,,,slaughter,,, Fatty Liver Preparations,"Fatty livers of ducks and geese when cooked, prepared or preserved(e.g. pat‚).",,1060,,,slaughter,,, "Meat, Canned (Chicken)",Includes meat and offals of poultry.,,1061,,,slaughter,,, HEN EGGS,Weight in shell.,,1062,,,animal,,, "Eggs, Liquid","Whole eggs, not in the shell, and egg yolks in liquid form that are frozen or otherwise preserved.",,1063,,,animal,,, "Eggs, Dried","Whole eggs and egg yolks, dried or powdered.",,1064,,,animal,,, FAT OF POULTRY,Unrendered poultry fat.,,1065,,,fat,,, FAT OF POULTRY,See Chapter 14.,,1065,,,slaughter,,, "Fat of Poultry, Rendered","Rendered poultry fat, including bone fat and fat obtained from waste.",,1066,,,fat,,, "Fat of Poultry, Rendered",See Chapter 14.,,1066,,,slaughter,,, "HEN EGGS, (NUMBER)",,,1067,,,animal,,, "DUCKS Anas spp.",See 1057.,,1068,,,livestock,,, DUCK MEAT,"Fresh, chilled or frozen.",,1069,,,slaughter,,, Indigenous Duck Meat,,,1070,,,slaughter,,, Biological Duck Meat,,,1071,,,slaughter,,, "GEESE Anser spp.",See 1057.,,1072,,,livestock,,, GOOSE MEAT,"Fresh, chilled or frozen.",,1073,,,slaughter,,, OFFALS AND LIVER OF GEESE,"Fresh, chilled or frozen, salted or in brine.",,1074,,,slaughter,,, OFFALS AND LIVER OF DUCKS,"Fresh, chilled or frozen, salted or in brine.",,1075,,,slaughter,,, Indigenous Goose Meat,,,1077,,,slaughter,,, Biological Goose Meat,,,1078,,,slaughter,,, "TURKEYS Meleagris gallopavo",See 1057.,,1079,,,livestock,,, TURKEY MEAT,"Fresh, chilled or frozen.",,1080,,,slaughter,,, OFFALS AND LIVER OF TURKEYS,,,1081,,,slaughter,,, "PIGEONS AND OTHER BIRDS Including inter alia: partridge (Alectoris rufa); pigeon (Columba livia); quail (Coturnis spp.); turtle dove, pheasant, etc.",See 1057.,,1083,,,livestock,,, "Indigenous Meat, Other Poultry",,,1084,,,slaughter,,, "Biological Meat, Other Poultry",,,1085,,,slaughter,,, Indigenous Turkey Meat,,,1087,,,slaughter,,, Biological Turkey Meat,,,1088,,,slaughter,,, MEAT OF PIGEONS AND OTHER BIRDS NES,"Fresh, chilled or frozen.",,1089,,,slaughter,,, "EGGS, EXCLUDING HEN EGGS",Weight in shell.,,1091,,,animal,,, "EGGS, EXCLUDING HEN EGGS (NUMBER)",,,1092,,,animal,,, Biological Chicken Meat,,,1095,,,slaughter,,, Indigenous Chicken Meat,,,1095,,,slaughter,,, "HORSES Equus caballus",See 0866.,,1096,,,livestock,,, HORSE MEAT,"Fresh, chilled or frozen.",,1097,,,slaughter,,, OFFALS OF HORSES,"Fresh, chilled or frozen.",,1098,,,slaughter,,, HAIR OF HORSES,"Includes hair of the manes and tails of equine and bovine animals and waste therefrom. Hair from flanks included in 1219.",,1100,,,Fibre Crops Primary,1753.0,, "HORSE HIDES, FRESH",See 0919. Both adult and young animals.,,1102,,,hides,,, "Hides, Wet-Salted (Horses)",See 0920. Includes hides of asses and mules.,,1103,,,hides,,, "Hides, Dry-Salted (Horses)",See 0921. Includes hides of asses and mules.,,1104,,,hides,,, "Hides nes, Horses",See 0922. Includes hides of asses and mules.,,1105,,,hides,,, "ASSES Equus asinus",See 0866.,,1107,,,livestock,,, MEAT OF ASSES,"Fresh, chilled or frozen.",,1108,,,slaughter,,, "HIDES OF ASSES, FRESH",See 0919. Both adult and young animals.,,1109,,,hides,,, MULES,"Includes hinnies. Mules are offspring of a male ass and a female horse (mare); a hinny is the offspring of a female ass and a male horse (stallion). Both are sterile. See 0866.",,1110,,,livestock,,, MEAT OF MULES,"Fresh, chilled or frozen.",,1111,,,slaughter,,, "HIDES OF MULES, FRESH",See 0919. Both adult and young animals.,,1112,,,hides,,, Indigenous Horse Meat,,,1120,,,slaughter,,, Biological Horse Meat,,,1121,,,slaughter,,, Indigenous Ass Meat,,,1122,,,slaughter,,, Biological Ass Meat,,,1123,,,slaughter,,, Indigenous Mule Meat,,,1124,,,slaughter,,, Biological Mule Meat,,,1125,,,slaughter,,, "CAMELS Bactrian camel (Camelus bactrianus); Arabian camel (C. dromedarius)",See 0866.,,1126,,,livestock,,, MEAT OF CAMELS,"Fresh, chilled or frozen.",,1127,,,slaughter,,, "OFFALS OF CAMELS, EDIBLE","Fresh, chilled or frozen.",,1128,,,slaughter,,, FAT OF CAMELS,Unrendered slaughter fats.,,1129,,,fat,,, FAT OF CAMELS,See Chapter 14.,,1129,,,slaughter,,, CAMEL MILK,See 0882.,,1130,,,animal,,, "CAMEL HIDES, FRESH",See 0919. Both adult and young animals.,,1133,,,hides,,, "Hides, Wet-Salted (Camels)",See 0920.,,1134,,,hides,,, "Hides, Dry-Salted (Camels)",See 0921.,,1135,,,hides,,, "Hides nes, Camels",See 0922.,,1136,,,hides,,, Indigenous Camel Meat,,,1137,,,slaughter,,, Biological Camel Meat,,,1138,,,slaughter,,, "RABBITS Oryctolagus cuniculus","See 0866. May include domesticated hares (Lepus spp.). Data are expressed in thousands.",,1140,,,livestock,,, RABBIT MEAT,"Fresh, chilled or frozen. May include hare meat.",,1141,,,slaughter,,, Indigenous Rabbit Meat,,,1144,,,slaughter,,, Biological Rabbit Meat,,,1145,,,slaughter,,, RABBIT SKINS,"See 0919. Both adult and young animals. Trade data include processed skins, including angora.",,1146,,,hides,,, OTHER RODENTS,"See 0866. Includes only those used mainly for meat, e.g. Guinea pig. Rodents used mainly for fur skins are included in Code 1169. Data are expressed in thousands.",,1150,,,livestock,,, MEAT OF OTHER DOMESTIC RODENTS,"Fresh, chilled or frozen.",,1151,,,slaughter,,, "Indigenous Meat, Other Rodents",,,1154,,,slaughter,,, "Biological Meat, Other Rodents",,,1155,,,slaughter,,, "OTHER CAMELIDS Various species of Lama: e.g. glama pacos (alpaca); peruana (llama); huanacos (guanaco>); vicugna (vicuå…€)",See 0866.,,1157,,,livestock,,, MEAT OF OTHER DOMESTIC CAMELIDS,"Fresh, chilled or frozen.",,1158,,,slaughter,,, FAT OF OTHER CAMELIDS,Unrendered slaughter fats.,,1160,,,fat,,, FAT OF OTHER CAMELIDS,See Chapter 14.,,1160,,,slaughter,,, "Indigenous Meat, Other Camelids",,,1161,,,slaughter,,, "Biological Meat, Other Camelids",,,1162,,,slaughter,,, GAME MEAT,"Meat and offals of wild animals, whether fresh, chilled or frozen.",,1163,,,slaughter,,, "Meat, Dried nes","Meat, except of bovines and pigs, salted, in brine or smoked.",,1164,,,slaughter,,, MEAT NES,"Including frog legs, marine mammals, etc. Some countries includeunder this heading meats that are listed above, but which are notreported separately. Fresh, chilled or frozen.",,1166,,,slaughter,,, OFFALS NES,"Fresh, chilled or frozen.",,1167,,,slaughter,,, Animal Oils and Fats nes,"Animal oils and fats obtained from other animal species and oils and fats recovered from guts, feet, sweepings, hide trimmings, etc.",,1168,,,fat,,, Animal Oils and Fats nes,See Chapter 14.,,1168,,,slaughter,,, "LIVE ANIMALS, NON- FOOD NES","Any animal not raised for food. External trade data also include wild animals.",,1169,,,livestock,,, LIVE ANIMALS NES,"Any other animal grown for meat, eggs, feathers and skins, e.g. ostrich, antelope, deer, reindeer, chamois.",,1171,,,livestock,,, "Meat, Prepared nes","Excludes poultry, swine or bovine meat preparations.",,1172,,,slaughter,,, Meat Meal,"Flours, meals and pellets of meat and offal (including of marine mammals); greaves and tankage. Used for feed.",,1173,,,fodder,,, Meat Meal,See Chapter 11.,,1173,,,slaughter,,, Fish Meal,"Flours, meals and pellets from fish, crustaceans, molluscs or other aquatic invertebrates. Used for feed.",,1174,,,fodder,,, Blood Meal,"Flours, meals and pellets obtained through dehydration of blood. Used for feed.",,1175,,,fodder,,, Blood Meal,See Chapter 11.,,1175,,,slaughter,,, SNAILS O/T SEA SNAILS,"Fresh, chilled, frozen, dried, salted or in brine.",,1176,,,slaughter,,, "BEEHIVES Apis mellifica; A. dorsata; A. florea; A. indica",A beehive is an artificial habitation for bees.,,1181,,,livestock,,, HONEY,See Chapter 3.,,1182,,,animal,,, HONEY,Honey produced by bees (Apis mellifera) or by other insects.,,1182,,,sugar,,, BEESWAX,"The substance bees use to build the hexagonal cells of the combs of beehives. Includes other insect waxes as well, i.e. lac and Chinese wax.",,1183,,,animal,,, "COCOONS, REELABLE","Silkworm cocoons suitable for reeling. Foreign trade data are expressed in silk equivalent, which is 25% of their weight.",,1185,,,Fibre Crops Primary,1753.0,, "Silk, Raw",Obtained by reeling the filaments from cocoons. Not thrown.,,1186,,,Fibre Crops Primary,1753.0,, "Cocoons Unreelable, Waste","Include cocoons unsuitable for reeling and silk waste of all kinds. Not carded or combed.",,1187,,,Fibre Crops Primary,1753.0,, FUR SKINS,"High-value raw skins, e.g. mink, fox, beaver.",,1195,,,hides,,, "HIDES AND SKINS NES, FRESH","See 0919. Both adult and young animals. Includes, among others, chamois, antelope, crocodile and snake.",,1213,,,hides,,, "Hides, Wet-Salted nes",See 0920.,,1214,,,hides,,, "Hides, Dry-Salted nes",See 0921.,,1215,,,hides,,, Hides nes,See 0922.,,1216,,,hides,,, "Leather, Used and Waste","Parings and other waste of leather, leather dust, powder and flour.",,1217,,,hides,,, "HAIR, FINE","Fine animal hair, mainly from alpaca, llama, vicuå…€, camel and angora rabbit. Excludes carded or combed hair.",,1218,,,Fibre Crops Primary,1753.0,, "HAIR, COARSE NES","Hair from flanks of equines and bovines, as well as hair from other animals, such as dogs and monkeys. Excludes carded or combed hair.",,1219,,,Fibre Crops Primary,1753.0,, Lard Stearine and Lard Oil,See Chapter 14.,,1221,,,slaughter,,, Lard Stearine and Lard Oil,"Obtained by pressing lard or tallow (oleo-oil, tallow oil, tallow stearine).",,1221,,,fat,,, Degras,"A residue from tanning leather that is obtained either by pressing or by extraction with solvents.",,1222,,,fat,,, "Oil from Fish and Marine Mammals","Fats and oils from fish and marine mammals extracted from the body or liver, whether or not refined, but not chemically modified.",,1223,,,fat,,, Tallow,See Chapter 14.,,1225,,,slaughter,,, Tallow,"Rendered fats of animals other than pigs, excluding tallow oil or stearine.",,1225,,,fat,,, Food Preparations nes,Including turtle eggs and birds' nests.,,1232,,,slaughter,,, Food Preparations nes,"Including both crop and livestock products. Inter alia: homogenized composite food preparations; soups and broths; ketchup and other sauces; mixed condiments and seasonings; vinegar and substitutes; yeast and baking powders; stuffed pasta, whether or not cooked; couscous; and protein concentrates.",,1232,,,tobacco,,, Liquid Margarine,See Chapter 14.,,1241,,,"Oilcrops, Oil Equivalent",1732.0,, Liquid Margarine,See commodity code 1242. Fat content varies from 30 to 70%.,,1241,,,fat,,, Margarine and Shortening,"Margarine is made principally from one or more hydrogenated vegetable or animal fats or oils in which is dispersed an aqueous potion containing milk products, salt, flavouring agents and other additives. Shortening is a product similar to margarine, but with a higher animal fat content. Shortening and compound fats are used primarily for baking and frying. The fat content of margarine and shortening varies from 70 to 90%.",,1242,,,fat,,, Fat Preparations nes,"Cooking fats prepared from both vegetable and animal oils and fats. Usually containing 100% fat.",,1243,,,fat,,, Fat Preparations nes,See Chapter 14.,,1243,,,slaughter,,, "Food Waste, Prep. for Feed",Same coverage as 0653.,,1259,,,fodder,,, "Castor Oil, Hydrogenated","Also called ""opal wax"".",,1273,,,fat,,, "Oils Boiled, Dehydrated, etc.","Also includes oxidized and sulphurized oils. Animal and vegetable fats and oils whose chemical structure has been modified to improve viscosity, drying ability or other properties.",,1274,,,fat,,, "Oils Boiled, Dehydrated, etc",See Chapter 14.,,1274,,,"Oilcrops, Oil Equivalent",1732.0,, Hydrogenated Oils and Fats,"Animal and vegetable fats and oils that have been hydrogenated to raise their melting point and increase their consistency by transforming unsaturated glycerides into saturated glycerides.",,1275,,,fat,,, Fatty Acids,"Manufactured by the saponification or hydrolysis of natural fats or oils. Including acid oils from refining.",,1276,,,fat,,, ARABIC GUM,Latex exuded by some acacias.,,1291,,,tobacco,,, "OTHER RESINS Including inter alia: copaiba, copal (Copaifera spp.); gum tragacanth (some Astragalus spp.); incense (Boswellia spp.); myrrh, opopanax, Mecca balsam (Commiphora spp.); tolu balsam, peru balsam (Myroxilon balsamum; M. Pereira)","Including lac (resinous substance produced by an insect on several kinds of tropical trees), gums, gum-resins and balsams (vegetable secretions which may solidify on contact with air).",,1292,,,tobacco,,, Crude Organic Materials nes,"Trade data are expressed in value terms only. Including, of vegetable origin: bulbs, tubers, tuberous roots, corms, crowns and rhizomes; live plants, cuttings and slips; mushroom spawn; cut flowers and flower buds; foliage, branches and grasses, mosses and lichens; plants and parts used primarily in perfumes, pharmaceuticals, insecticides, fungicides, or for similar purposes; seaweeds and other algae; vegetable saps and extracts; materials used for plaiting, stuffing or padding; materials used primarily in brooms or brushes; and materials used primarily in dyeing and tanning.",,1293,,,tobacco,,, Seeds for Planting,"Seeds, fruits and spores used for sowing. Excludes cereals, oilseeds, pulses and spices, even if intended for sowing.",,1294,,,tobacco,,, Spermaceti,"Waxy substance extracted from the fat of sperm whales and similar cetaceans.",,1295,,,fat,,, "VEGETABLE WAXES Including inter alia: candelilla (Euphorbia antisyphilitica; Pedilanthus pavonis); carnauba (Copernicia cerifera); urucury (Attalea excelsa); palm wax (Ceroxylon andicolum)","Vegetable waxes, whether crude or refined, bleached or coloured. Excludes mixtures and chemically modified waxes.",,1296,,,tobacco,,, ================================================ FILE: Smart Farmers project/data/palm.csv ================================================ Date,KO1 Comdty (L1),OR1 Comdty (R1),RG1 Comdty (R1) 12/9/2011,3050,339.5,345.5 12/12/2011,2963,334.6,340 12/13/2011,2990,333.1,337 12/14/2011,3030,334.4,337 12/15/2011,2990,326.7,330.7 12/16/2011,2986,331.3,335.9 12/19/2011,3021,330.1,327.3 12/20/2011,3020,334.4,331 12/21/2011,3074,337.6,338.7 12/22/2011,3095,338,338 12/23/2011,3170,336.9,342.7 12/27/2011,3157,333.7,336 12/28/2011,3157,330.8,333.2 12/29/2011,3120,325.2,328 12/30/2011,3175,327,327.5 1/2/2012,,, 1/3/2012,3233,329.3,330.5 1/4/2012,3223,323.6,329 1/5/2012,3200,326.4,331.2 1/6/2012,3216,327.1,334.1 1/9/2012,3210,326.4,331 1/10/2012,3220,330.7,335 1/11/2012,3224,337.7,343.2 1/12/2012,3207,337,344.7 1/13/2012,3140,336.9,344.9 1/16/2012,3161,340.6,345.9 1/17/2012,3195,354.5,361.5 1/18/2012,3190,358.5,373 1/19/2012,3165,369.7,380 1/20/2012,3163,372.6,388 1/24/2012,,, 1/25/2012,3172,380.5,407 1/26/2012,3138,383.2,409.5 1/27/2012,3137,376,403 1/30/2012,3090,370.5,395 1/31/2012,3075,376,403 2/1/2012,,376.8,400 2/2/2012,3030,373.4,398 2/3/2012,3052,375.7,401.7 2/6/2012,,381.7,406 2/7/2012,,379.5,403 2/8/2012,3110,384.8,408 2/9/2012,3097,380.8,403 2/10/2012,3093,374.9,395.8 2/13/2012,3130,375.1,399 2/14/2012,3160,375.5,398 2/15/2012,3153,377.1,402.3 2/16/2012,3175,373.3,396 2/17/2012,3213,372.5,393.3 2/20/2012,3219,373.7,398.6 2/21/2012,3234,380.6,401.2 2/22/2012,3216,380.3,401.5 2/23/2012,3225,381.6,401 2/24/2012,3232,381.3,400.7 2/27/2012,3235,377.8,398.7 2/28/2012,3248,379,398.5 2/29/2012,3225,380,401 3/1/2012,3255,383,403.5 3/2/2012,3235,383.6,403.3 3/5/2012,3220,379.6,398 3/6/2012,3217,376.7,395 3/7/2012,3255,378.1,392 3/8/2012,3290,379.9,391.8 3/9/2012,3335,381.2,397.3 3/12/2012,3316,381.7,394.9 3/13/2012,3358,381.3,394.6 3/14/2012,3376,379.4,393.4 3/15/2012,3420,377.8,388.9 3/16/2012,3394,375.9,390.4 3/19/2012,3370,375,389 3/20/2012,3364,374.4,388 3/21/2012,3367,375.2,387 3/22/2012,3367,373.4,386.3 3/23/2012,3470,375.9,389 3/26/2012,3482,375.8,390 3/27/2012,3512,378.4,392.5 3/28/2012,3500,379,394 3/29/2012,3483,377.9,392 3/30/2012,3480,376,393 4/2/2012,3572,376.6,397 4/3/2012,3580,375.5,394 4/4/2012,3590,371.8,390 4/5/2012,3600,372,389.8 4/6/2012,3639,, 4/9/2012,3616,371.4,390 4/10/2012,3645,370.6,389 4/11/2012,,364.7,383.5 4/12/2012,3596,365,384 4/13/2012,3568,363.7,380 4/16/2012,3498,362.6,376 4/17/2012,3515,362.4,377 4/18/2012,3500,364.9,378.5 4/19/2012,3495,364.2,379 4/20/2012,3515,364,379.1 4/23/2012,3498,363.5,381 4/24/2012,3473,360.6,378.8 4/25/2012,3513,361,380.2 4/26/2012,3510,364,386 4/27/2012,3486,364.8,386 4/30/2012,3472,366.5,391 5/1/2012,,, 5/2/2012,3461,369.2,393.5 5/3/2012,3385,365,392.5 5/4/2012,3365,363.3,393.9 5/7/2012,3368,358,385 5/8/2012,3355,354.2,383 5/9/2012,3335,348.7,376.8 5/10/2012,3355,350.6,379 5/11/2012,3285,344.4,376.5 5/14/2012,3155,332.9,365.7 5/15/2012,3196,333.1,365.7 5/16/2012,3100,328.1,362.8 5/17/2012,3111,331.4,365.3 5/18/2012,3104,330.7,370 5/21/2012,3100,335.3,374.3 5/22/2012,3110,334.5,372 5/23/2012,3015,325,366.3 5/24/2012,3060,321.4,364.3 5/25/2012,3100,321.4,364.3 5/28/2012,3117,322,369 5/29/2012,3140,324.3,369 5/30/2012,3079,320,358 5/31/2012,3070,314.6,355 6/1/2012,2973,304.5,343 6/4/2012,2945,286.9,325 6/5/2012,2953,281.5,319 6/6/2012,2989,286.9,323.4 6/7/2012,2954,284.7,324 6/8/2012,2944,280,315 6/11/2012,2960,284.9,321.5 6/12/2012,2930,285.4,316.5 6/13/2012,2917,285,322.5 6/14/2012,2810,286.1,326.3 6/15/2012,2810,295.5,330 6/18/2012,2871,298.9,339 6/19/2012,2930,294.5,325.5 6/20/2012,3035,296.6,329 6/21/2012,2984,288.6,320 6/22/2012,2926,276.8,302.5 6/25/2012,3003,278.8,301.9 6/26/2012,3015,278.8,304.2 6/27/2012,3003,279.4,310 6/28/2012,2983,279.4,305 6/29/2012,2992,279,314 7/2/2012,3054,288.5,314 7/3/2012,3098,296,320.8 7/4/2012,3094,296,320 7/5/2012,3134,298.8,320.4 7/6/2012,3094,292.5,317.3 7/9/2012,3126,290.5,309.5 7/10/2012,3110,291.3,309.5 7/11/2012,3053,289.5,305 7/12/2012,2997,288.9,305.7 7/13/2012,3015,293,310 7/16/2012,3100,294.1,312.4 7/17/2012,3042,294.3,312.5 7/18/2012,2970,291,308.5 7/19/2012,3025,293.8,310 7/20/2012,3010,291.9,310.6 7/23/2012,2962,283.2,300 7/24/2012,2898,283.5,297 7/25/2012,2926,284.1,295.8 7/26/2012,2855,284.1,298.6 7/27/2012,2901,284,302 7/30/2012,2980,279.5,297.3 7/31/2012,2955,275.8,295.5 8/1/2012,2922,280.6,303 8/2/2012,2910,280.1,297 8/3/2012,2897,277.3,294.9 8/6/2012,2888,274.3,291 8/7/2012,2874,269.9,286.5 8/8/2012,2811,259.2,274.3 8/9/2012,2817,, 8/10/2012,2830,258,276.6 8/13/2012,2817,247.8,268.9 8/14/2012,2798,240.8,260.4 8/15/2012,2798,242.7,266.2 8/16/2012,2860,253.1,278.3 8/17/2012,2898,256,278 8/21/2012,,254.1,276.8 8/22/2012,3008,251.2,274.5 8/23/2012,3017,254.7,276 8/24/2012,3030,256.8,280.4 8/27/2012,3032,264.5,282 8/28/2012,2974,261,277.8 8/29/2012,2915,256.6,275.4 8/30/2012,2920,257.5,275.5 8/31/2012,,253.5,272 9/3/2012,2961,258.4,279.3 9/4/2012,2940,257.5,279.6 9/5/2012,2888,252.9,278.4 9/6/2012,2840,255.6,283 9/7/2012,2809,257,281 9/10/2012,2824,265.7,292.9 9/11/2012,2832,268.1,293 9/12/2012,2818,275.3,300 9/13/2012,2794,272.8,301 9/14/2012,2715,290.2,317.5 9/17/2012,,291.2,318.5 9/18/2012,2714,289.3,317 9/19/2012,2705,290.5,318 9/20/2012,2675,285.2,314.2 9/21/2012,2593,287.4,319.5 9/24/2012,2512,284.7,313 9/25/2012,2539,285.1,312 9/26/2012,2480,282.5,314.5 9/27/2012,2480,284.1,316.5 9/28/2012,2420,292,328 10/1/2012,2300,298,329.5 10/2/2012,2083,310.7,340 10/3/2012,2183,307.7,336.3 10/4/2012,2189,308,334.5 10/5/2012,2248,305.9,336 10/8/2012,2228,299,326 10/9/2012,2278,305.9,336 10/10/2012,2279,303.6,331 10/11/2012,2380,302.1,329.5 10/12/2012,2407,297.3,323 10/15/2012,2400,294.5,320.1 10/16/2012,2397,294.2,318.8 10/17/2012,2393,294.5,319 10/18/2012,2396,297.3,320.2 10/19/2012,2404,287.7,312.5 10/22/2012,2469,283.4,308.4 10/23/2012,2437,281.5,303.4 10/24/2012,2468,285.7,305 10/25/2012,2500,290.8,310.5 10/29/2012,2425,286.3,305.5 10/30/2012,2392,283.1,302 10/31/2012,2394,281.1,301.5 11/1/2012,2404,285.4,303 11/2/2012,2370,283,301 11/5/2012,2300,276.3,296 11/6/2012,2280,277.1,295.8 11/7/2012,2290,278.1,297 11/8/2012,2257,275.2,291.9 11/9/2012,2249,276.2,295 11/12/2012,2228,276.1,293 11/14/2012,2150,279.3,297.8 11/15/2012,,280.7,300 11/16/2012,2360,278.7,299.1 11/19/2012,2386,280.8,298.9 11/20/2012,2369,280.8,299 11/21/2012,2340,281.7,299.9 11/22/2012,2300,281.3,298.7 11/23/2012,2267,281.8,298 11/26/2012,2265,281.2,299.6 11/27/2012,2178,281.3,295 11/28/2012,2160,280.9,294 11/29/2012,2170,281.9,296 11/30/2012,2145,282.9,297 12/3/2012,2101,283.2,301.1 12/4/2012,2100,282.3,301 12/5/2012,2105,285.9,303.5 12/6/2012,2115,284,301 12/7/2012,2111,283.4,301.5 12/10/2012,2121,285.8,304.5 12/11/2012,2087,284.7,303.5 12/12/2012,2042,286.1,306 12/13/2012,2042,285.7,306 12/14/2012,2100,291.3,310.3 12/17/2012,2197,291.9,311 12/18/2012,2197,293.3,316 12/19/2012,2191,292.8,318 12/20/2012,2201,289,315.8 12/21/2012,2283,290.1,314 12/24/2012,2299,289,314 12/26/2012,2308,294.3,319 12/27/2012,2350,300.3,323 12/28/2012,2367,300.2,326.2 12/31/2012,2320,298.8,324 1/2/2013,2382,306.5,334 1/3/2013,2364,307.4,337.5 1/4/2013,2369,305.5,334.5 1/7/2013,2320,301.3,329 1/8/2013,2293,302.1,331 1/9/2013,2295,304,334 1/10/2013,2275,307.2,337 1/11/2013,2269,304,334.3 1/14/2013,2276,305.9,333 1/15/2013,2330,304.5,331 1/16/2013,2387,299.8,328 1/17/2013,2343,301.8,328.9 1/18/2013,2358,303.7,334.5 1/21/2013,2370,301.5,327.3 1/22/2013,2412,303,328 1/23/2013,2410,304.2,327 1/24/2013,,303,326 1/25/2013,2382,305.1,326.7 1/28/2013,,303.8,325 1/29/2013,2402,307.4,327 1/30/2013,2445,308.5,328.1 1/31/2013,2512,304.8,326.2 2/1/2013,,311.5,334 2/4/2013,2496,312.9,335 2/5/2013,2481,312,335 2/6/2013,2469,311.6,333 2/7/2013,2470,311.3,331 2/8/2013,2480,309.1,328.7 2/13/2013,2445,311.6,328 2/14/2013,2436,311,327 2/15/2013,2428,307.8,323.9 2/18/2013,2474,306.3,322 2/19/2013,2506,302.7,315.5 2/20/2013,2509,299.8,308.5 2/21/2013,2481,294.1,300.9 2/22/2013,2478,298,304.8 2/25/2013,2419,299.8,301.3 2/26/2013,2387,296.7,299 2/27/2013,2390,295.5,304 2/28/2013,2375,288,303 3/1/2013,2350,285.5,300.2 3/4/2013,2400,285.2,298.2 3/5/2013,2384,288.5,301.6 3/6/2013,2386,288.4,302.7 3/7/2013,2422,288,303 3/8/2013,2434,290.5,307.1 3/11/2013,2440,287.4,306 3/12/2013,2400,278.3,296.6 3/13/2013,2382,274.3,289.6 3/14/2013,2348,275.1,292 3/15/2013,2348,277.5,295.5 3/18/2013,2386,271.7,291 3/19/2013,2414,274.8,293 3/20/2013,2426,279.6,297 3/21/2013,2436,277.6,298.5 3/22/2013,2460,276.4,296.3 3/25/2013,2428,279,298.5 3/26/2013,2405,278.1,297 3/27/2013,2410,277.5,296.5 3/28/2013,2372,267,294.3 3/29/2013,2340,, 4/1/2013,2315,261.6,286.5 4/2/2013,2357,263.4,287.3 4/3/2013,2371,262.8,286.8 4/4/2013,2366,256.5,281.5 4/5/2013,2336,248.8,277 4/8/2013,2370,261.4,284.6 4/9/2013,2361,255,285.3 4/10/2013,2338,260.9,291 4/11/2013,2319,258.6,292.2 4/12/2013,2305,256.8,294 4/15/2013,2300,243.3,282 4/16/2013,2284,243.5,284 4/17/2013,2254,235.9,275.9 4/18/2013,2293,237.8,277.2 4/19/2013,2283,242.8,285 4/22/2013,2245,239.4,286 4/23/2013,2265,238.5,285.5 4/24/2013,2285,246,288 4/25/2013,2310,246,290.7 4/26/2013,2301,246.5,292.5 4/29/2013,2248,245.5,297 4/30/2013,2249,246,297 5/2/2013,2235,245.5,291 5/3/2013,2231,251,296 5/6/2013,2229,254.2,302 5/7/2013,2238,251.1,299.4 5/8/2013,2263,258.7,304 5/9/2013,2288,258,302 5/10/2013,2290,266.4,306 5/13/2013,2281,260.5,302.8 5/14/2013,2280,254.4,301.1 5/15/2013,2280,246,299 5/16/2013,2320,246.6,299.5 5/17/2013,2334,254.1,302.1 5/20/2013,2330,252.9,303 5/21/2013,2316,255.6,310.2 5/22/2013,2328,257.6,320 5/23/2013,2340,246.5,310 5/27/2013,2365,245.1,307 5/28/2013,2372,249.1,310 5/29/2013,2359,243,310 5/30/2013,2326,242.2,307 5/31/2013,2360,238.6,297.8 6/3/2013,2360,242,286 6/4/2013,2340,244.4,291.8 6/5/2013,2369,239,289 6/6/2013,2389,236.9,286 6/7/2013,2417,240,286.5 6/10/2013,2411,240.6,286 6/11/2013,2415,235.6,282 6/12/2013,2420,232.8,278 6/13/2013,2389,230,276 6/14/2013,2410,232.9,278 6/17/2013,2459,233.3,278 6/18/2013,2465,233,282 6/19/2013,2466,235.2,283 6/20/2013,2457,230.3,279.3 6/21/2013,2431,228.5,279.3 6/24/2013,2394,224.9,277.5 6/25/2013,2400,223.8,280 6/26/2013,2370,222.9,276 6/27/2013,2348,222.5,277 6/28/2013,2337,223,269 7/1/2013,2337,223.7,267 7/2/2013,2333,225.5,266 7/3/2013,2359,222.5,262 7/4/2013,2365,224.7,265.6 7/5/2013,2376,223.2,265 7/8/2013,2369,217.8,261.1 7/9/2013,2396,217.2,258 7/10/2013,2390,215.9,255 7/11/2013,2390,221.3,260.3 7/12/2013,2330,216.8,255 7/15/2013,2330,216.2,254.5 7/16/2013,2259,218.2,253.5 7/17/2013,2277,220.6,253 7/18/2013,2340,225.4,255 7/19/2013,2326,227.5,255 7/22/2013,2355,228.6,257 7/23/2013,2346,230.1,256.5 7/24/2013,2310,234.1,257 7/25/2013,2271,233.5,255 7/26/2013,2260,233.3,250 7/29/2013,2253,229.2,246.4 7/30/2013,2283,227.1,245 7/31/2013,2293,225.5,242.2 8/1/2013,2300,224,243.7 8/2/2013,2296,224.2,244.3 8/5/2013,2310,223,242.5 8/6/2013,2313,228.4,246.3 8/7/2013,2278,227.9,245 8/12/2013,2280,241,257.5 8/13/2013,2330,242.8,261 8/14/2013,2334,239.5,260 8/15/2013,2365,240,259 8/16/2013,2367,243.4,261.7 8/19/2013,2393,243.3,261 8/20/2013,2380,238.7,257.3 8/21/2013,2393,239,259 8/22/2013,2402,242.5,259.6 8/23/2013,2419,241.5,263 8/26/2013,2483,247,265 8/27/2013,2466,245.2,264 8/28/2013,2489,244.3,264 8/29/2013,2444,240.9,265 8/30/2013,2407,242.7,259 9/2/2013,2430,249.6,269 9/3/2013,2420,249.7,269 9/4/2013,2399,248.8,267 9/5/2013,2400,249.4,268.9 9/6/2013,2432,249.1,268.7 9/9/2013,2401,247,267.5 9/10/2013,2353,247.2,266 9/11/2013,2351,247,266 9/12/2013,2361,241,261 9/13/2013,2360,239.4,259.2 9/16/2013,,238.9,259.2 9/17/2013,2363,240,261 9/18/2013,2329,241.1,263 9/19/2013,2322,245.3,268 9/20/2013,2305,242.6,267 9/23/2013,2316,241.2,266 9/24/2013,2311,237.8,264 9/25/2013,2324,234.8,260.5 9/26/2013,2310,235,258 9/27/2013,2350,231.6,258 9/30/2013,2355,230.6,253 10/1/2013,2368,230.5,252 10/2/2013,2355,230.1,249.2 10/3/2013,2340,232.4,249 10/4/2013,2339,231.3,248.2 10/7/2013,2350,231,248.4 10/8/2013,2350,234.9,252 10/9/2013,2369,231.2,253.1 10/10/2013,2390,232.2,253 10/11/2013,2380,233.9,256 10/14/2013,2375,237.1,260 10/16/2013,2400,237.5,260.5 10/17/2013,2390,234.1,258 10/18/2013,2392,233.8,257 10/21/2013,2431,233.4,256 10/22/2013,2457,232.1,256 10/23/2013,2488,231.5,254.5 10/24/2013,2472,232.1,255 10/25/2013,2458,229.4,251 10/28/2013,2480,228.3,249.5 10/29/2013,2527,229,251.5 10/30/2013,2585,228.2,254.5 10/31/2013,2623,227.1,251.5 11/1/2013,2649,229.4,251.1 11/4/2013,2600,229.5,251 11/5/2013,,227.8,247.4 11/6/2013,2560,227.5,248 11/7/2013,2545,229.2,249.5 11/8/2013,2509,230.7,250 11/11/2013,2532,230.7,249.5 11/12/2013,2589,229,249.1 11/13/2013,2594,229.5,248.4 11/14/2013,2577,231,249 11/15/2013,2585,230.5,249 11/18/2013,2591,231,249 11/19/2013,2562,231.1,249 11/20/2013,2582,232,249.5 11/21/2013,2653,230.8,248 11/22/2013,2640,231.5,248.5 11/25/2013,2622,230,247.3 11/26/2013,2613,228.9,247 11/27/2013,2620,230,246.8 11/28/2013,2620,231.4,249 11/29/2013,2615,233.5,252 12/2/2013,2602,233.3,256 12/3/2013,2571,231.9,253.5 12/4/2013,2606,231.2,253.8 12/5/2013,2602,231,253 12/6/2013,2629,234.8,257 12/9/2013,2614,233.3,258 12/10/2013,2608,232,256.2 12/11/2013,2599,231.8,257.4 12/12/2013,2580,234,261 12/13/2013,2580,234,261.2 12/16/2013,2541,233.9,261 12/17/2013,2532,230.9,258.1 12/18/2013,2502,230.5,257.5 12/19/2013,2524,232.5,257.6 12/20/2013,2546,231,257 12/23/2013,2593,230.5,256.5 12/24/2013,2603,228.6,254 12/26/2013,2612,228.3,253.5 12/27/2013,2611,229.5,253 12/30/2013,2603,226.8,249 12/31/2013,2628,226.5,248.5 1/2/2014,2619,227,247.3 1/3/2014,2606,224,243 1/6/2014,2566,219.8,238.5 1/7/2014,2530,218.5,236 1/8/2014,2517,218.7,236.5 1/9/2014,2510,219.2,237 1/10/2014,2487,220,239 1/13/2014,2460,216.9,235 1/14/2014,,220.7,236.3 1/15/2014,2460,218.1,235.8 1/16/2014,2515,218,236.2 1/17/2014,,218,235.2 1/20/2014,2560,217.3,235.5 1/21/2014,2569,215.2,234 1/22/2014,2557,215.6,232.6 1/23/2014,2586,212.9,231.1 1/24/2014,2577,208.3,227.7 1/27/2014,2545,197.1,218 1/28/2014,2520,193.5,216 1/29/2014,2535,194.9,217.4 1/30/2014,2551,188.6,217 2/3/2014,,189.3,215 2/4/2014,2521,186.9,211 2/5/2014,2540,184.8,208 2/6/2014,2565,181.2,202 2/7/2014,2577,183.1,206 2/10/2014,2626,192.2,212 2/11/2014,2610,194.5,215.5 2/12/2014,2628,195.4,215.5 2/13/2014,2649,191,214.5 2/14/2014,2649,191.1,215 2/17/2014,2683,197.5,223 2/18/2014,2710,197.2,223 2/19/2014,2708,196.4,223.1 2/20/2014,2765,190.8,216.5 2/21/2014,2776,190.5,216.4 2/24/2014,2769,183.4,213.5 2/25/2014,2750,179,213 2/26/2014,2830,179.1,213 2/27/2014,2815,183.6,216 2/28/2014,2825,183,218 3/3/2014,2821,187.6,220.2 3/4/2014,2790,187.9,220.5 3/5/2014,2831,191.5,223.5 3/6/2014,2865,191.3,224 3/7/2014,2890,191,224 3/10/2014,2904,188,221 3/11/2014,2912,192.5,224 3/12/2014,2859,196.2,229.8 3/13/2014,2841,198.3,232.1 3/14/2014,2841,200.6,233.2 3/17/2014,2829,195.3,229.5 3/18/2014,2839,193.4,228.9 3/19/2014,2871,193.7,229.9 3/20/2014,2865,192.9,228.5 3/21/2014,2822,191.9,229.9 3/24/2014,2793,190.8,230.5 3/25/2014,2797,191.7,232.5 3/26/2014,2770,189.9,229.7 3/27/2014,2733,186.8,229.5 3/28/2014,2735,189.3,233.7 3/31/2014,2718,190,235.8 4/1/2014,2689,189.2,233.1 4/2/2014,2713,184.9,228.5 4/3/2014,2675,185.3,223 4/4/2014,2705,183.5,226.5 4/7/2014,2668,181.7,226 4/8/2014,2619,183.5,227 4/9/2014,2650,182.6,226.6 4/10/2014,2655,180.4,225 4/11/2014,2660,179.3,224.8 4/14/2014,2670,179.4,224 4/15/2014,2680,180.4,224.5 4/16/2014,2736,180.7,224.8 4/17/2014,2712,177.8,220.9 4/18/2014,2694,, 4/21/2014,2695,164.6,203.8 4/22/2014,2730,168,206.5 4/23/2014,2698,168.9,205.8 4/24/2014,2701,169.7,207 4/25/2014,2705,168.3,207.1 4/28/2014,2717,170.1,211.6 4/29/2014,2690,174.5,217.2 4/30/2014,2691,176,216.5 5/2/2014,2660,169.8,206 5/5/2014,2640,168.5,204 5/6/2014,2632,165.8,200.5 5/7/2014,2642,166.1,201.2 5/8/2014,2633,166.1,200 5/9/2014,2645,167.4,202.6 5/12/2014,2650,169.6,205.7 5/14/2014,2672,170.5,209.8 5/15/2014,2672,170.2,208 5/16/2014,2629,169.1,208.3 5/19/2014,2590,171.7,213 5/20/2014,2559,170.7,210.5 5/21/2014,2542,171.3,210 5/22/2014,2550,170.3,209.7 5/23/2014,2541,170.2,210.1 5/26/2014,2520,170.8,210.4 5/27/2014,2509,171.1,210.5 5/28/2014,2507,171.7,210.5 5/29/2014,2460,170.7,209.7 5/30/2014,2426,169.5,205 6/2/2014,2422,166.5,199.8 6/3/2014,2400,166.6,198.9 6/4/2014,2440,166.2,202.3 6/5/2014,2423,165.9,201.7 6/6/2014,2420,166.7,203.8 6/9/2014,2410,167.1,205 6/10/2014,2386,167.4,207 6/11/2014,2380,168.3,210.3 6/12/2014,2403,167.4,208 6/13/2014,2403,168,209.2 6/16/2014,2440,167.8,208.5 6/17/2014,2445,168.4,210.2 6/18/2014,2484,170,211.9 6/19/2014,2467,172.1,213 6/20/2014,2460,173.9,214.7 6/23/2014,2489,179.5,217.5 6/24/2014,2491,179.4,215.6 6/25/2014,2497,178.9,214.5 6/26/2014,2487,179.2,211.3 6/27/2014,2468,178.6,209.7 6/30/2014,2448,177.2,209 7/1/2014,2435,173.7,205.3 7/2/2014,2450,174,206.5 7/3/2014,2469,174.2,209 7/4/2014,2458,173.1,207.8 7/7/2014,2466,166.7,198.8 7/8/2014,2453,167.7,200.7 7/9/2014,2440,167.3,200.5 7/10/2014,2450,167.2,200 7/11/2014,2410,167.7,200.5 7/14/2014,2375,166.9,200.5 7/15/2014,,166.1,199 7/16/2014,2378,166.8,202.7 7/17/2014,2381,169.3,205.5 7/18/2014,2386,169,202.9 7/21/2014,2373,167.8,201 7/22/2014,2365,167.9,199.3 7/23/2014,2342,167.9,199.5 7/24/2014,2356,168.8,200 7/25/2014,2335,168.8,199.5 7/29/2014,,171.7,201 7/30/2014,2318,172,201 7/31/2014,2328,171.4,200.5 8/1/2014,2357,171.2,196.9 8/4/2014,2341,170,195.7 8/5/2014,2328,169,193.7 8/6/2014,2318,168,191.3 8/7/2014,2316,168.8,191.3 8/8/2014,2291,168.3,190.1 8/11/2014,2230,168.3,188.1 8/12/2014,2228,167.3,185.5 8/13/2014,2215,165.8,183 8/14/2014,2166,164.7,182 8/15/2014,2166,164.4,180.3 8/18/2014,2099,163.3,180.7 8/19/2014,2074,163.8,181.2 8/20/2014,2054,164.5,180.8 8/21/2014,2055,164.8,181 8/22/2014,2021,167.1,182.8 8/25/2014,2049,166.4,181.7 8/26/2014,2035,164.6,179.8 8/27/2014,1996,165.4,180.5 8/28/2014,1984,164.4,179.5 8/29/2014,1937,160,179 9/1/2014,,161.4,177.3 9/2/2014,1964,162.9,177.9 9/3/2014,1984,162.4,175.6 9/4/2014,2035,162.8,177.3 9/5/2014,2041,160.9,174.6 9/8/2014,2054,159.1,170.3 9/9/2014,2050,152.4,166 9/10/2014,2049,150.9,163.5 9/11/2014,2090,152.2,163.4 9/12/2014,2125,153.4,164 9/15/2014,2160,154,163.7 9/16/2014,,154,165.9 9/17/2014,2156,155.2,165.9 9/18/2014,2170,152.9,165.6 9/19/2014,2136,151,163 9/22/2014,2123,145.9,157.2 9/23/2014,2152,144.8,154.3 9/24/2014,2178,146.4,155.3 9/25/2014,2205,145,151.6 9/26/2014,2189,147.3,156 9/29/2014,2202,147.5,153.3 9/30/2014,2232,148,156 10/1/2014,2210,138.7,150 10/2/2014,2165,139.4,150.2 10/3/2014,2187,139.5,152.7 10/7/2014,2202,141.9,154.9 10/8/2014,2220,143.1,155.3 10/9/2014,2220,144.4,157.2 10/10/2014,2209,143.4,156 10/13/2014,2187,146.2,157.5 10/14/2014,2193,149,159.7 10/15/2014,2178,149.3,159.3 10/16/2014,2135,148.8,159.3 10/17/2014,2165,152.6,163.1 10/20/2014,2147,154.9,165.6 10/21/2014,2159,155.4,166 10/23/2014,2185,160.3,171.8 10/24/2014,2199,161.2,171.5 10/27/2014,2188,158.1,168.9 10/28/2014,2222,158.8,170.2 10/29/2014,2260,160,172.1 10/30/2014,2275,158.3,171 10/31/2014,2295,158,170 11/3/2014,2315,154.4,168 11/4/2014,2285,151.6,165.4 11/5/2014,2228,,161.8 11/6/2014,2219,151.9,163.2 11/7/2014,2192,153.8,164.8 11/10/2014,2205,154.5,164 11/11/2014,2234,153.9,163.8 11/12/2014,2214,155.8,167 11/13/2014,2191,156.5,168 11/14/2014,2191,154.9,166 11/17/2014,2208,153,162.8 11/18/2014,2230,153.7,163.2 11/19/2014,2234,154.7,164 11/20/2014,2213,154.8,164.5 11/21/2014,2215,153.5,160.6 11/24/2014,2195,155.1,164.5 11/25/2014,2201,155.8,162.8 11/26/2014,2205,155.9,160.3 11/27/2014,2165,154.5,160 11/28/2014,2147,151.7,157 12/1/2014,2100,148,154.6 12/2/2014,2129,149.6,156 12/3/2014,2160,147.8,154 12/4/2014,2147,148.9,155 12/5/2014,2135,147.7,155.1 12/8/2014,2148,145.9,153 12/9/2014,2107,143.3,152 12/10/2014,2140,143.5,151.5 12/11/2014,2175,143.1,152.8 12/12/2014,2154,146,158.4 12/15/2014,2154,149.7,162.3 12/16/2014,2113,148.5,162.5 12/17/2014,2123,147.9,163.9 12/18/2014,2146,147.8,164.5 12/19/2014,2160,148.6,165.9 12/22/2014,2171,148,167 12/23/2014,2209,147.3,166 12/24/2014,2217,146.4,162 12/26/2014,2250,147.4,164.5 12/29/2014,2298,148,166.9 12/30/2014,2300,152.8,168.9 12/31/2014,2291,152.2,170 1/2/2015,2315,153.4,171 1/5/2015,2298,151.3,169.7 1/6/2015,2309,149.5,168 1/7/2015,2349,144.3,165 1/8/2015,2384,144.4,164.8 1/9/2015,2359,145.5,166 1/12/2015,2375,144.5,165 1/13/2015,2375,142,163 1/14/2015,2361,139.8,160 1/15/2015,2373,139.9,160.4 1/16/2015,2348,138.2,160 1/19/2015,2342,138,160.9 1/20/2015,2337,138.5,161.5 1/21/2015,2291,138.8,163.5 1/22/2015,2272,140.2,166 1/23/2015,2264,140.3,167.5 1/26/2015,2200,139.6,166 1/27/2015,2188,140.4,168.7 1/28/2015,2221,140.8,170 1/29/2015,2147,139.4,169 1/30/2015,2154,138.7,167.5 2/2/2015,,139.8,172.7 2/3/2015,,140.7,174.7 2/4/2015,2193,140.5,174.5 2/5/2015,2300,141,175.2 2/6/2015,2330,141.2,178.5 2/9/2015,2294,140.6,180.8 2/10/2015,2278,139.6,183.6 2/11/2015,2255,140.2,184 2/12/2015,2265,141,184 2/13/2015,2265,143.2,185.3 2/16/2015,2305,143.4,186.1 2/17/2015,2286,143.2,182.7 2/18/2015,2302,140.7,182 2/23/2015,2247,139.7,181.8 2/24/2015,2273,139.6,182.7 2/25/2015,2258,140.1,181 2/26/2015,2292,145,183.5 2/27/2015,2321,145.8,182 3/2/2015,2381,143.9,183.5 3/3/2015,2389,142.3,181.5 3/4/2015,2378,143.4,180.8 3/5/2015,2350,143.5,179 3/6/2015,2312,140.5,172.2 3/9/2015,2280,141.5,172.2 3/10/2015,2240,141.4,171.5 3/11/2015,2286,141.6,171 3/12/2015,2248,142.7,172 3/13/2015,2270,143.2,171.5 3/16/2015,2209,142.9,172.5 3/17/2015,2149,143.3,173 3/18/2015,2195,142.8,172.3 3/19/2015,2210,142.9,171.7 3/20/2015,2168,142.9,171.3 3/23/2015,2188,143.1,172 3/24/2015,2165,143.3,173 3/25/2015,2160,143.2,172.5 3/26/2015,2174,143.5,173.4 3/27/2015,2151,142.9,171.1 3/30/2015,2156,142.8,170.5 3/31/2015,2136,145,169.4 4/1/2015,2142,141.7,171.7 4/2/2015,2154,141.3,172 4/3/2015,2178,, 4/6/2015,2223,139.9,168.3 4/7/2015,2194,140,168.2 4/8/2015,2153,138.6,167.3 4/9/2015,2108,138.2,165 4/10/2015,2120,138.7,165.3 4/13/2015,2124,139.5,166.5 4/14/2015,2148,138.1,165.3 4/15/2015,2150,138.2,166 4/16/2015,2173,138.4,166.9 4/17/2015,2184,138.7,166.5 4/20/2015,2190,138,166.7 4/21/2015,2203,140.3,169.7 4/22/2015,2179,140.1,170 4/23/2015,2174,140.2,172 4/24/2015,2166,140.8,172.2 4/27/2015,2121,143.8,176.5 4/28/2015,2098,144.5,177.5 4/29/2015,2078,146.6,178.1 4/30/2015,2070,149,179 5/4/2015,,154.8,184.5 5/5/2015,2136,154.7,184.5 5/6/2015,2166,154.8,185.4 5/7/2015,2156,152.4,182 5/8/2015,2146,152.3,183.7 5/11/2015,2178,153.5,184 5/12/2015,2206,152.7,184.2 5/13/2015,2190,152.5,184.2 5/14/2015,2199,151.9,182 5/15/2015,2199,153,182.3 5/18/2015,2189,154.4,184.7 5/19/2015,2166,153.8,183.8 5/20/2015,2150,151.6,181.9 5/21/2015,2154,153.7,182 5/22/2015,2132,156,182 5/25/2015,2137,156.6,184.5 5/26/2015,2167,160,185.1 5/27/2015,2145,161.3,187 5/28/2015,2170,161.6,186 5/29/2015,2170,166,190 6/1/2015,2270,, 6/2/2015,2291,163.5,188.5 6/3/2015,2267,162.3,189.3 6/4/2015,2293,163.4,190.5 6/5/2015,2320,161.4,187.2 6/8/2015,2320,158.4,186.5 6/9/2015,2305,158.8,187 6/10/2015,2279,160.9,188 6/11/2015,2275,162.1,189 6/12/2015,2254,158.7,184.9 6/15/2015,2254,159.1,183.5 6/16/2015,2289,159.8,183.1 6/17/2015,2288,159.2,182.8 6/18/2015,2230,157.4,181.3 6/19/2015,2232,158,182 6/22/2015,2205,158.5,182 6/23/2015,2210,159.4,181.8 6/24/2015,2258,159.5,181.9 6/25/2015,2259,157.7,178.2 6/26/2015,2278,156.6,175.2 6/29/2015,2278,154.8,173 6/30/2015,2224,151,166 7/1/2015,2262,151.5,170 7/2/2015,2259,152.1,171 7/3/2015,2263,152.3,170.7 7/6/2015,2228,149.2,167 7/7/2015,2200,147.4,166.7 7/8/2015,2144,140.2,160 7/9/2015,2182,144.6,164 7/10/2015,2190,144.9,164 7/13/2015,2192,144.3,163.5 7/14/2015,2198,143.5,162 7/15/2015,2198,144.6,163 7/16/2015,2189,146.6,165.5 7/20/2015,2187,147.6,166 7/21/2015,2217,149,168 7/22/2015,2205,147.4,166.5 7/23/2015,2190,147.5,165 7/24/2015,2180,142.4,162.5 7/27/2015,2145,140.1,158 7/28/2015,2138,140.1,158.5 7/29/2015,2119,140.9,158.5 7/30/2015,2124,142.1,158.5 7/31/2015,2120,140,158 8/3/2015,2056,137.4,156 8/4/2015,2055,137.7,155.8 8/5/2015,2033,137.5,155.8 8/6/2015,2035,136.7,155 8/7/2015,2031,, 8/10/2015,2010,, 8/11/2015,2017,135.7,151.3 8/12/2015,1970,134.6,149.2 8/13/2015,1986,135.2,148.1 8/14/2015,1986,134.4,145.7 8/17/2015,1999,132.1,142.3 8/18/2015,1998,129,138 8/19/2015,1971,130.6,140 8/20/2015,1936,129.8,139 8/21/2015,1913,131.7,140.1 8/24/2015,1844,126.1,132.7 8/25/2015,1829,126.9,131.8 8/26/2015,1800,125.6,130.2 8/27/2015,1868,129.1,129.3 8/28/2015,1928,131,129.6 8/31/2015,,126.8,129.1 9/1/2015,1945,125.2,132.3 9/2/2015,1923,123.7,130 9/3/2015,1959,122.2,128.6 9/4/2015,1955,121.9,126.7 9/7/2015,1955,123.6,130.4 9/8/2015,1994,125,130.9 9/9/2015,2012,125.9,132.9 9/10/2015,2056,126.2,133 9/11/2015,2032,, 9/14/2015,2081,126,133.4 9/15/2015,2050,124.3,132 9/16/2015,,125.5,132.8 9/17/2015,2054,125.8,133.9 9/18/2015,2034,125.3,133 9/21/2015,2086,125,131.2 9/22/2015,2116,124.9,131 9/23/2015,2157,124.5,130.5 9/25/2015,2259,125.8,132 9/28/2015,2323,125.5,130.8 9/29/2015,2395,124.1,128.3 9/30/2015,2306,124,130.4 10/1/2015,2344,124.6,133.5 10/2/2015,2319,123.2,132 10/5/2015,2365,124.5,132.2 10/6/2015,2320,125.4,132.6 10/7/2015,2271,125.5,132 10/8/2015,2223,124.5,130.5 10/9/2015,2168,126.9,134 10/12/2015,2209,128.2,133.6 10/13/2015,2269,128,134 10/14/2015,,127.5,133.4 10/15/2015,2269,127.9,134.2 10/16/2015,2235,127.4,133.3 10/19/2015,2210,125.2,130.2 10/20/2015,2262,125.5,129.4 10/21/2015,2294,124,127.7 10/22/2015,2296,124.8,127.7 10/23/2015,2251,125.8,128.7 10/26/2015,2208,123.4,126.1 10/27/2015,2243,122.7,123 10/28/2015,2251,124.4,124.5 10/29/2015,2253,124.6,125.2 10/30/2015,2238,120.7,124 11/2/2015,2230,119.4,123.2 11/3/2015,2208,118.1,123 11/4/2015,2245,117.8,122.3 11/5/2015,2224,117.2,121.4 11/6/2015,2188,117.6,122.3 11/9/2015,2235,117.1,120.9 11/11/2015,2181,118.9,122.5 11/12/2015,2180,119.3,122.9 11/13/2015,2100,119.9,124.3 11/16/2015,2132,117.3,122.1 11/17/2015,2132,117.9,121 11/18/2015,2168,117.4,121.2 11/19/2015,2140,117.1,122 11/20/2015,2159,116.8,122 11/23/2015,2143,114.3,120 11/24/2015,2128,114.5,121.5 11/25/2015,2093,115,123 11/26/2015,2135,115.5,123.7 11/27/2015,2159,116.2,123.5 11/30/2015,2140,115.6,121.7 12/1/2015,2145,116.5,125.5 12/2/2015,2140,117.3,128.5 12/3/2015,2186,117.2,127.5 12/4/2015,2189,116.7,127 12/7/2015,2254,118.3,129.9 12/8/2015,2200,117.3,129.4 12/9/2015,2180,117.3,129 12/10/2015,2160,116.7,127.9 12/11/2015,2222,116.8,127.9 12/14/2015,2186,116.1,126 12/15/2015,2186,115.8,124.1 12/16/2015,2224,115.7,123.2 12/17/2015,2214,116,123.2 12/18/2015,2236,116.1,123 12/21/2015,2272,118.8,124 12/22/2015,2290,118.9,123.8 12/23/2015,2294,118.5,123 12/24/2015,,119.2,123 12/28/2015,2248,117,119.6 12/29/2015,2288,116.3,117.1 12/30/2015,2292,117.8,117.5 12/31/2015,2398,, 1/4/2016,2290,110.8,115.5 1/5/2016,2275,110.5,115 1/6/2016,2268,109.2,114.4 1/7/2016,2253,107,111.7 1/8/2016,2263,108.1,112.5 1/11/2016,2239,107.4,113 1/12/2016,2224,107.8,116.5 1/13/2016,2260,108,123.3 1/14/2016,2262,107.9,128.9 1/15/2016,2200,107.4,128.5 1/18/2016,2351,107.6,128.5 1/19/2016,2372,108.7,130 1/20/2016,2358,109,127.3 1/21/2016,2349,108.8,127 1/22/2016,2382,110.2,127.3 1/25/2016,,110,127.8 1/26/2016,2387,107.8,123.5 1/27/2016,2412,107.8,124.3 1/28/2016,2387,104.2,122 1/29/2016,2349,107.4,122.5 2/1/2016,,108.7,123.6 2/2/2016,2432,108.6,124.5 2/3/2016,2454,108.1,121.8 2/4/2016,2453,109.3,124.4 2/5/2016,2497,108.7,123 2/10/2016,2487,106.3,121.8 2/11/2016,2490,104.9,121.9 2/12/2016,2548,106,124.3 2/15/2016,2510,108.7,128 2/16/2016,2526,109.2,128 2/17/2016,2545,107.8,126 2/18/2016,2522,108.2,125.9 2/19/2016,2522,108.7,127 2/22/2016,2502,110.4,128.4 2/23/2016,2483,110.9,129 2/24/2016,2461,110.5,128 2/25/2016,2471,110.9,128.9 2/26/2016,2462,110.1,128.9 2/29/2016,2479,112,125.9 3/1/2016,2474,114.7,130.8 3/2/2016,2448,118.4,132.9 3/3/2016,2453,123.1,137.5 3/4/2016,2464,132.2,148 3/7/2016,2495,134.6,150 3/8/2016,2491,131.3,145.6 3/9/2016,2518,127.8,140.8 3/10/2016,2489,124.5,139 3/11/2016,2549,124.9,140 3/14/2016,2529,124.1,139.9 3/15/2016,2540,123,138 3/16/2016,2590,125.6,141 3/17/2016,2615,130.2,146.3 3/18/2016,2633,130.5,148.5 3/21/2016,2634,132.5,150 3/22/2016,2652,133.4,151.5 3/23/2016,2639,131.8,151 3/24/2016,2616,129.9,149.5 3/25/2016,2660,, 3/28/2016,2705,131.1,152 3/29/2016,2731,130,151 3/30/2016,2702,130.1,149.8 3/31/2016,2690,132.7,150.5 4/1/2016,2717,133.3,154.2 4/4/2016,2739,136.4,156.8 4/5/2016,2717,139.3,159.9 4/6/2016,2681,138.7,161.8 4/7/2016,2679,139.3,163 4/8/2016,2647,140.4,163.5 4/11/2016,2633,148.1,170.7 4/12/2016,2610,151,173 4/13/2016,2628,150.4,172 4/14/2016,2626,150.5,171.5 4/15/2016,2638,149.4,169.3 4/18/2016,2656,149.1,170.6 4/19/2016,2672,150.2,174 4/20/2016,2692,154.7,178.5 4/21/2016,2712,158.8,182.5 4/22/2016,2677,155.9,179.4 4/25/2016,2635,157.1,180.3 4/26/2016,2654,155.9,181.9 4/27/2016,2615,155.8,185 4/28/2016,2584,152.7,182 4/29/2016,2572,148.5,183 5/3/2016,2520,149.1,180.4 5/4/2016,2600,147.1,180.9 5/5/2016,2615,145.6,180 5/6/2016,2640,147.3,180.3 5/9/2016,2675,145.6,179.5 5/10/2016,2670,146.3,181.5 5/11/2016,2690,146.8,182 5/12/2016,2675,146.2,181.5 5/13/2016,2635,141.7,177.2 5/16/2016,2626,139.5,174 5/17/2016,2632,139.9,174.5 5/18/2016,2591,135.3,172 5/19/2016,2552,129.5,162.9 5/20/2016,2557,129.4,158.6 5/23/2016,2519,123.4,149 5/24/2016,2540,127,150.3 5/25/2016,2574,125.8,148.6 5/26/2016,2618,127.7,149 5/27/2016,2587,126.9,148.9 5/30/2016,2621,126.9,151.9 5/31/2016,2635,126,151.8 6/1/2016,2624,123.9,151 6/2/2016,2660,125.9,151 6/3/2016,2680,127,150.3 6/6/2016,2671,129.1,152.5 6/7/2016,2640,127.9,152.8 6/8/2016,2632,127.1,152.1 6/9/2016,2635,124,149 6/10/2016,2626,123.8,144 6/13/2016,2571,125.1,147 6/14/2016,2520,122.5,145.2 6/15/2016,2399,122.9,146 6/16/2016,2441,123.9,148 6/17/2016,2485,127.9,153 6/20/2016,2443,129.7,157.3 6/21/2016,2431,127.3,158.9 6/22/2016,,130,170 6/23/2016,2466,131.1,170.2 6/24/2016,2470,128.3,169.8 6/27/2016,2467,130.5,174 6/28/2016,2440,134.4,177.3 6/29/2016,2383,134.4,179 6/30/2016,2400,135.9,179 7/1/2016,2406,129.3,164.7 7/4/2016,2451,135.3,168 7/5/2016,2409,131.6,162.5 7/7/2016,,130.2,159.5 7/8/2016,2320,126.5,156.5 7/11/2016,2320,128.4,160.5 7/12/2016,2270,130,166.7 7/13/2016,2298,130.4,171.5 7/14/2016,2280,131.1,179 7/15/2016,2298,130.8,183 7/18/2016,2319,130.1,183.9 7/19/2016,2351,130.8,186.3 7/20/2016,2387,132.7,192 7/21/2016,2394,134.1,198.8 7/22/2016,2362,132.7,194.1 7/25/2016,2322,131.3,189.6 7/26/2016,2352,130.5,181 7/27/2016,2356,131.5,181.2 7/28/2016,2333,132.2,182.8 7/29/2016,2374,129.8,188 8/1/2016,2375,128.8,170.4 8/2/2016,2393,129.6,172.3 8/3/2016,2479,129.6,172.1 8/4/2016,2509,129.1,166.1 8/5/2016,2505,129.5,158.5 8/8/2016,2550,131,162.5 8/9/2016,2561,, 8/10/2016,2630,130.3,164.7 8/11/2016,2612,131.3,164.8 8/12/2016,2620,132.9,169.3 8/15/2016,2620,133.3,169.8 8/16/2016,2741,132.9,169 8/17/2016,2888,132.6,168.7 8/18/2016,2838,131.8,169.2 8/19/2016,2852,131.9,171.5 8/22/2016,2820,129.4,166.2 8/23/2016,2833,127.6,160.9 8/24/2016,2841,126.9,159.9 8/25/2016,2804,126.2,159 8/26/2016,2800,126.3,161 8/29/2016,2790,126.6,161.4 8/30/2016,2789,126.1,162.3 8/31/2016,,127.1,157 9/1/2016,2753,129.5,158.3 9/2/2016,2829,130.1,159.8 9/5/2016,2890,130.9,159 9/6/2016,2880,129,157 9/7/2016,2867,130.7,159.6 9/8/2016,2870,131.4,158.5 9/9/2016,2898,131.6,159 9/13/2016,2852,132.1,158.5 9/14/2016,2833,132.8,160.7 9/15/2016,2833,132.8,160 9/16/2016,,133.6,159 9/19/2016,2831,137.4,160.5 9/20/2016,2887,142.7,163.1 9/21/2016,2873,141.2,162.2 9/22/2016,2909,144.4,165.9 9/23/2016,2863,143.3,166 9/26/2016,2900,139.6,162.5 9/27/2016,2849,135.8,160 9/28/2016,2747,135,160 9/29/2016,2761,135,160 9/30/2016,2775,139.1,160 10/3/2016,,136.1,161 10/4/2016,2743,139.8,162.5 10/5/2016,2700,143,164.3 10/6/2016,2690,144.4,167 10/7/2016,2650,146.3,169.5 10/10/2016,2585,150.3,170.5 10/11/2016,2650,151.7,166.2 10/12/2016,2670,148.6,165.5 10/13/2016,2630,148,164 10/14/2016,2630,152.7,166 10/17/2016,2781,151.6,164 10/18/2016,2723,151,166.2 10/19/2016,2750,146.1,163 10/20/2016,2755,144.4,165.7 10/21/2016,2759,145.4,163.3 10/24/2016,2821,146.8,164.9 10/25/2016,2760,146.5,168 10/26/2016,2792,146.1,169.9 10/27/2016,2790,149.2,172.5 10/28/2016,2790,149.1,172.5 10/31/2016,2764,149.3,173.5 11/1/2016,2740,148.3,173.4 11/2/2016,2780,146.1,170.8 11/3/2016,2791,147.8,170.1 11/4/2016,2752,148.8,173.9 11/7/2016,2803,153.9,176.1 11/8/2016,2854,156.6,178.6 11/9/2016,2857,158.5,179.1 11/10/2016,2892,167.2,187.4 11/11/2016,2975,170.6,189.5 11/14/2016,2856,166,182 11/15/2016,2856,166.4,184.5 11/16/2016,2871,171,190.5 11/17/2016,2883,171,190.5 11/18/2016,2872,168.9,190.5 11/21/2016,2923,173.7,197 11/22/2016,2935,174,197 11/23/2016,2959,174,197 11/24/2016,3010,176.2,201 11/25/2016,3042,171.6,200 11/28/2016,3084,174.8,204 11/29/2016,3060,172.9,202.8 11/30/2016,3082,168,200 12/1/2016,3115,171.3,203 12/2/2016,3120,169.1,203 12/5/2016,3225,171.4,209.3 12/6/2016,3268,172.5,212 12/7/2016,3200,177.4,216 12/8/2016,3168,177.3,214.4 12/9/2016,3123,182.1,217.5 12/12/2016,,189,222 12/13/2016,3160,205.6,234.3 12/14/2016,3189,214.9,240 12/15/2016,3189,203.8,237.2 12/16/2016,3188,197.1,233.6 12/19/2016,3166,193.4,227.5 12/20/2016,3123,194.2,230 12/21/2016,3154,193.4,229.6 12/22/2016,3125,190.5,227.3 12/23/2016,3150,190.3,227.3 12/27/2016,3218,186.5,226 12/28/2016,3213,187.6,219 12/29/2016,3196,192.3,223 12/30/2016,3218,193.5,224.5 1/3/2017,3250,201.1,230 1/4/2017,3234,201.5,236 1/5/2017,3200,196.2,235.8 1/6/2017,3200,193,235 1/9/2017,3231,202.6,242.3 1/10/2017,3220,208.7,251 1/11/2017,3261,211.2,259.4 1/12/2017,3255,212.2,259.5 1/13/2017,3280,208.7,256 1/16/2017,3207,222.1,264.6 1/17/2017,3255,218.8,261.9 1/18/2017,3243,220,262.3 1/19/2017,3241,216.8,259.2 1/20/2017,3234,207.7,252 1/23/2017,3231,209.3,252 1/24/2017,3278,214.6,260 1/25/2017,3256,220.9,270.7 1/26/2017,3238,223.7,282 1/27/2017,3243,, 1/31/2017,3230,227.5,285 2/1/2017,,229,285.5 2/2/2017,3258,229,285.6 2/3/2017,3250,222.4,275 2/6/2017,3262,218.6,275.5 2/7/2017,3278,221.5,276.9 2/8/2017,3301,221.6,279.9 2/9/2017,,218.9,277.8 2/10/2017,3268,223.8,283 2/13/2017,3250,230.2,292.8 2/14/2017,3282,231.6,289.8 2/15/2017,3306,227.9,281.5 2/16/2017,3151,224.5,278.5 2/17/2017,3094,220.5,273.5 2/20/2017,3073,217,269.4 2/21/2017,3024,216.4,263.7 2/22/2017,3022,215.9,257.4 2/23/2017,2945,207.5,252.8 2/24/2017,2977,208.4,244.6 2/27/2017,2920,207.5,241.7 2/28/2017,2898,207.8,238 3/1/2017,2951,210,243.3 3/2/2017,2979,211.3,244.2 3/3/2017,3000,215.3,249.7 3/6/2017,3010,208.9,247 3/7/2017,2974,208,242.4 3/8/2017,3000,199.1,234 3/9/2017,2990,197.6,236 3/10/2017,2990,199.6,237.1 3/13/2017,2950,199.9,238.6 3/14/2017,2985,196.7,232.3 3/15/2017,3020,198.9,237.8 3/16/2017,2963,200.7,242 3/17/2017,2966,204,246.4 3/20/2017,2939,202.3,239.5 3/21/2017,2968,199.1,239 3/22/2017,2975,190.6,230.3 3/23/2017,2933,193.4,234.5 3/24/2017,2895,189.7,233.4 3/27/2017,2843,181.5,224.4 3/28/2017,2859,180.8,227 3/29/2017,2874,180.8,231 3/30/2017,2831,175.9,227.1 3/31/2017,2833,191.8,226.4 4/3/2017,2862,182.8,230.5 4/4/2017,2861,179.9,230.4 4/5/2017,2930,184.8,236.4 4/6/2017,2909,181.2,236 4/7/2017,2885,173.8,229.5 4/10/2017,2832,166.7,227 4/11/2017,2838,164.8,224.2 4/12/2017,2780,160.3,219.1 4/13/2017,2769,161.8,221.5 4/14/2017,2750,, 4/17/2017,2636,160.3,219.3 4/18/2017,2597,151.7,212.5 4/19/2017,2584,151.8,212 4/20/2017,2639,156,214 4/21/2017,2669,156.4,218 4/24/2017,,159.2,222.4 4/25/2017,2634,156.9,222.5 4/26/2017,2664,155.4,224 4/27/2017,2660,157,221.7 4/28/2017,2694,162,220.1 5/2/2017,2730,160.2,223.4 5/3/2017,2705,160.3,224 5/4/2017,2730,152.4,214.7 5/5/2017,2775,148.9,212 5/8/2017,2800,147,209.3 5/9/2017,2850,148,210.4 5/11/2017,2895,150,212 5/12/2017,2860,148.6,211.5 5/15/2017,2920,151.5,216 5/16/2017,2834,156.9,225.2 5/17/2017,2886,155.7,223 5/18/2017,2871,150.4,220.8 5/19/2017,2885,153.3,222 5/22/2017,2900,156.2,226.5 5/23/2017,2877,155.7,229.2 5/24/2017,2861,152.5,222 5/25/2017,2876,154,223.2 5/26/2017,2840,153,219.2 5/29/2017,2787,154,211.2 5/30/2017,2757,153.1,208.6 5/31/2017,2749,152.4,201 6/1/2017,2759,146.8,195.8 6/2/2017,2730,144.1,183.8 6/5/2017,2743,139.8,173.9 6/6/2017,2738,135.3,169 6/7/2017,2707,139.5,170.5 6/8/2017,2670,139.6,170.7 6/9/2017,2680,140.6,170.7 6/12/2017,,142.4,172.6 6/13/2017,2649,138.4,172.6 6/14/2017,2675,144.9,180.2 6/15/2017,2650,146.5,186.9 6/16/2017,2656,145.8,185.6 6/19/2017,2640,141.2,178.9 6/20/2017,2603,139.2,171.5 6/21/2017,2587,139.6,171.4 6/22/2017,2597,137.3,169 6/23/2017,2589,140.2,169 6/27/2017,,142.8,171 6/28/2017,2585,144.4,172.5 6/29/2017,2617,151.5,179.5 6/30/2017,2596,150.2,177.9 7/3/2017,2642,156.1,175.5 7/4/2017,2650,148.6,168.3 7/5/2017,2670,148.6,167.5 7/6/2017,2688,147.6,168.9 7/7/2017,2668,146.7,168.5 7/10/2017,2705,145.8,168.4 7/11/2017,2687,147.1,168.2 7/12/2017,2679,148.4,171.4 7/13/2017,2661,149.2,172.8 7/14/2017,2620,150.2,173.7 7/17/2017,2617,151.2,177.3 7/18/2017,2582,148.7,173.4 7/19/2017,2580,156.7,184.3 7/20/2017,2621,157.3,184.5 7/21/2017,2612,155.7,182.5 7/24/2017,2589,152.1,178.7 7/25/2017,2646,153.4,180 7/26/2017,2652,149.6,180.4 7/27/2017,2692,149.1,180.9 7/28/2017,2666,141.6,173.7 7/31/2017,2672,142.4,174.9 8/1/2017,2659,146.9,175.4 8/2/2017,2630,146.8,173.8 8/3/2017,2588,147,174.8 8/4/2017,2590,148.7,178 8/7/2017,2581,151.5,182.4 8/8/2017,2624,151.2,180.7 8/9/2017,2628,, 8/10/2017,2663,153.3,183.2 8/11/2017,2683,150.6,181 8/14/2017,2668,150.6,182 8/15/2017,2628,152.8,182.6 8/16/2017,2622,153.5,183.1 8/17/2017,2649,153.9,186.3 8/18/2017,2675,155.2,187.9 8/21/2017,2703,154.7,186.7 8/22/2017,2729,156.3,188.2 8/23/2017,2723,153.6,186.5 8/24/2017,2750,153.5,186.1 8/25/2017,2733,155.4,187.7 8/28/2017,2723,154.8,187.3 8/29/2017,2680,154.5,186 8/30/2017,2680,154,185.9 8/31/2017,,155.5,185 9/4/2017,,163.3,193.9 9/5/2017,2740,169.1,197.4 9/6/2017,2720,170.7,199.7 9/7/2017,2768,170.6,198 9/8/2017,2771,168.8,195 9/11/2017,2803,168,193.4 9/12/2017,2830,168.6,193 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11/6/2017,2772,146.5,161.5 11/7/2017,2759,144.8,159.5 11/8/2017,2772,143.8,159.4 11/9/2017,2747,141.7,157.5 11/10/2017,2740,142.3,155.2 11/13/2017,2702,143.7,156.9 11/14/2017,2654,143.9,158 11/15/2017,2695,139.8,151 11/16/2017,2706,139.7,151.6 11/17/2017,2680,139.1,150 11/20/2017,2592,139.2,150.4 11/21/2017,2580,139.1,150.8 11/22/2017,2585,140.6,150.6 11/23/2017,2530,141.8,152.8 11/24/2017,2545,141.9,154 11/27/2017,2495,139.5,152.6 11/28/2017,2470,139.6,154.9 11/29/2017,2468,142,156.5 11/30/2017,2495,145.3,157 12/1/2017,,145.5,159.7 12/4/2017,2480,149.9,165.3 12/5/2017,2456,146.4,163.3 12/6/2017,2435,145.2,162.8 12/7/2017,2410,142.8,159.8 12/8/2017,2379,142.8,159.8 12/11/2017,2350,143.1,159.6 12/12/2017,2365,143.3,159.8 12/13/2017,2349,143,159.7 12/14/2017,2340,144.6,161.1 12/15/2017,2346,145,161.2 12/18/2017,2468,144.8,164 12/19/2017,2469,145.2,163.4 12/20/2017,2450,145.4,163.3 12/21/2017,2411,144.6,163.4 12/22/2017,2407,144.1,161.5 12/26/2017,2438,148.6,168.3 12/27/2017,2474,148.9,166.3 12/28/2017,2459,148.8,163.8 12/29/2017,2444,146.9,160.6 1/2/2018,2472,145.4,166 1/3/2018,2555,145.3,167.7 1/4/2018,2542,145.6,167.3 1/5/2018,2570,145.6,167.3 1/8/2018,2590,146,166.6 1/9/2018,2562,147.8,166.9 1/10/2018,2568,148,167.6 1/11/2018,2509,150.5,168 1/12/2018,2474,150.7,169.6 1/15/2018,2480,153.7,172.6 1/16/2018,2504,152.8,169.1 1/17/2018,2478,152.6,167.9 1/18/2018,2465,152.7,169.6 1/19/2018,2435,153.3,170 1/22/2018,2465,153.6,170.1 1/23/2018,2488,151,169.3 1/24/2018,2512,151.2,170.6 1/25/2018,2490,152.6,173 1/26/2018,2482,152.5,173.9 1/29/2018,2514,151.8,171.1 1/30/2018,2490,148.3,171.5 1/31/2018,,147,170.4 2/1/2018,,149,169.9 2/2/2018,2475,149.1,171 2/5/2018,2500,149.3,171.5 2/6/2018,2481,146.8,169.8 2/7/2018,2482,146.6,168.8 2/8/2018,2501,143.9,165.4 2/9/2018,2495,144.2,166.7 2/12/2018,2550,144.8,169.6 2/13/2018,2510,144.5,167.4 2/14/2018,2506,144.3,167.1 2/15/2018,2505,, 2/19/2018,2530,144.1,170.9 2/20/2018,2509,144.2,173.8 2/21/2018,2510,144.4,171 2/22/2018,2509,144.4,173.4 2/23/2018,2536,147,176.6 2/26/2018,2555,150.2,184.1 2/27/2018,2556,150.9,184.5 2/28/2018,2571,150.7,190 3/1/2018,2564,148.1,176.8 3/2/2018,2496,148,173.7 3/5/2018,2491,148.4,174.8 3/6/2018,2491,148.1,174.5 3/7/2018,2459,146.6,174.9 3/8/2018,2425,147,173.4 3/9/2018,2398,146.1,173.5 3/12/2018,2390,146.4,174.2 3/13/2018,2410,145.9,174 3/14/2018,2441,147,176 3/15/2018,2434,146.5,176 3/16/2018,2438,144.4,174.4 3/19/2018,2433,144.8,175 3/20/2018,2450,143.6,173.3 3/21/2018,2459,143,173.5 3/22/2018,2445,143.1,172.4 3/23/2018,2420,134.1,163.3 3/26/2018,2405,134.2,162.2 3/27/2018,2400,138.4,166.5 3/28/2018,2397,139.2,168.5 3/29/2018,2378,133.7,168 3/30/2018,2380,, 4/2/2018,2430,137.7,175 4/3/2018,2410,136.9,174.5 4/4/2018,2428,134.4,171 4/5/2018,2442,134,170.6 4/6/2018,2479,135.5,170.1 4/9/2018,2436,136.8,171.7 4/10/2018,2403,137.7,171.8 4/11/2018,2399,138,170.3 4/12/2018,2392,138.8,170 4/13/2018,2392,138.8,170.1 4/16/2018,2362,137.2,169 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8/6/2018,2180,132.9,145.9 8/7/2018,2195,134.2,147 8/8/2018,2220,134.5,147.2 8/9/2018,2214,, 8/10/2018,2206,134.1,146.6 8/13/2018,2169,134.4,147.1 8/14/2018,2178,134.5,146.6 8/15/2018,2178,134.6,146.6 8/16/2018,2191,133.8,145.5 8/17/2018,2204,133.5,145.1 8/20/2018,2215,134.8,146.1 8/21/2018,2205,139.2,148.5 8/23/2018,2183,136.8,148.5 8/24/2018,2178,135.6,149.5 8/27/2018,2166,133.7,148.9 8/28/2018,2189,133,146.5 8/29/2018,2177,132.7,146.2 8/30/2018,2200,134,147.2 8/31/2018,,132,147 9/3/2018,2209,131.7,145.1 9/4/2018,2242,132,144.7 9/5/2018,2239,131.9,144.2 9/6/2018,2224,132.2,144.6 9/7/2018,2213,131.7,144.2 9/10/2018,,132,142.9 9/11/2018,,131.2,142.7 9/12/2018,2195,132.6,144.7 9/13/2018,2205,133.6,144.8 9/14/2018,2206,132.7,143.9 9/17/2018,,132.3,143.9 9/18/2018,2168,132.9,143.7 9/19/2018,2127,132.1,143.6 9/20/2018,2118,133.3,144.2 9/21/2018,2116,133.3,141.8 9/24/2018,2137,133.3,141.5 9/25/2018,2148,133.1,141.3 9/26/2018,2145,133.9,140.7 9/27/2018,2117,133.8,140.1 9/28/2018,2118,134.2,141.1 10/1/2018,2094,133.7,142.3 10/2/2018,2085,134,142.5 10/3/2018,2127,133.4,141.5 10/4/2018,2148,133.6,142.1 10/5/2018,2139,133.3,140.5 10/8/2018,2116,133,141 10/9/2018,2125,134.6,142.8 10/10/2018,2118,133.7,142.7 10/11/2018,2096,132.7,142.3 10/12/2018,2113,133,143.1 10/15/2018,2148,132.8,142.1 10/16/2018,2140,132.1,142.6 10/17/2018,2156,132.5,143.6 10/18/2018,2135,131.8,143 10/19/2018,2125,131.8,142.9 10/22/2018,2145,132.7,141.6 10/23/2018,2122,132.4,142.8 10/24/2018,2103,132,142.3 10/25/2018,2071,131.8,142 10/26/2018,2046,130.5,142.3 10/29/2018,2075,126.7,141.1 10/30/2018,2057,124.6,141 10/31/2018,1988,124.5,139 11/1/2018,1976,124.5,139.2 11/2/2018,1985,126.2,139.5 11/5/2018,1950,124.4,136.6 11/7/2018,1950,124.2,136.3 11/8/2018,1929,124.4,136.9 11/9/2018,1880,124,137.6 11/12/2018,1865,124.1,136.3 11/13/2018,1825,123.5,134.6 11/14/2018,1759,123.7,135.8 11/15/2018,1759,123.2,135.7 11/16/2018,1775,122.8,135.8 11/19/2018,1800,122.9,133.8 11/20/2018,,121.5,132.9 11/21/2018,1822,121.2,132.5 11/22/2018,1878,121.4,133 11/23/2018,1866,121.7,132.4 11/26/2018,1785,123,130 11/27/2018,1805,121.4,130.7 11/28/2018,1839,121.2,131.4 11/29/2018,1867,121.3,131.5 11/30/2018,1872,122.4,132.3 12/3/2018,1813,124.3,136.5 12/4/2018,1800,123.9,137.2 12/5/2018,1780,124.3,136.9 12/6/2018,1792,123.5,137.9 12/7/2018,1793,123.4,139.6 12/10/2018,1835,123.1,138.1 12/11/2018,1805,123.3,136.9 12/12/2018,1813,124.2,139.2 12/13/2018,1835,125,140.7 12/14/2018,1835,124.4,141.3 12/17/2018,1964,126.2,144 12/18/2018,2062,126.4,144.5 12/19/2018,2139,126.1,144.2 12/20/2018,2133,128,146.6 12/21/2018,2103,127.7,146.8 12/24/2018,2055,126.9,146.8 12/26/2018,2017,124.4,145.5 12/27/2018,2012,124.5,148 12/28/2018,2013,124.8,148.5 12/31/2018,2004,, 1/2/2019,2070,128.6,150 1/3/2019,2090,132.6,153.3 1/4/2019,2120,140.5,159.4 1/7/2019,2092,138.7,157 1/8/2019,2109,138.4,157.7 1/9/2019,2104,137.1,159.1 1/10/2019,2087,134.8,157.8 1/11/2019,2093,135.1,160.8 1/14/2019,2062,134.1,157.9 1/15/2019,2130,133.1,158.4 1/16/2019,2090,133.8,158.4 1/17/2019,2121,133,158.5 1/18/2019,2142,134.3,159.4 1/21/2019,,137.5,165.5 1/22/2019,2163,134.6,161.3 1/23/2019,2191,133,159.6 1/24/2019,2200,132.8,161 1/25/2019,2190,132.9,160.7 1/28/2019,2222,131.2,158.3 1/29/2019,2194,129.8,156.2 1/30/2019,2204,132.5,157.9 1/31/2019,2200,129.7,158.8 2/1/2019,,133.3,157 2/4/2019,2207,, 2/7/2019,2216,132.3,156.6 2/8/2019,2190,130.9,156.1 2/11/2019,2195,130.8,155.9 2/12/2019,2181,132.5,157.2 2/13/2019,2176,133.3,158.9 2/14/2019,2200,136,160.4 2/15/2019,2200,134.8,159.7 2/18/2019,2206,136.3,162 2/19/2019,2155,141.3,165.1 2/20/2019,2134,143.9,167 2/21/2019,2145,140.9,166.1 2/22/2019,2138,144.6,169.8 2/25/2019,2020,144.8,169 2/26/2019,1982,143.8,167.6 2/27/2019,1920,145.8,168.3 2/28/2019,1915,143,173 3/1/2019,1986,149.4,175.9 3/4/2019,1978,147.4,175.3 3/5/2019,1992,148.3,174.8 3/6/2019,2000,147.8,175.2 3/7/2019,1973,146,172.5 3/8/2019,1971,146.3,172.2 3/11/2019,1962,145.7,172.3 3/12/2019,1980,146.7,172.9 3/13/2019,1956,147.3,171.9 3/14/2019,1950,147.9,172.9 3/15/2019,1950,147.1,171.1 3/18/2019,2025,147.5,171.9 3/19/2019,2060,147.8,172.5 3/20/2019,2095,147.9,172 3/21/2019,2090,148.6,172.2 3/22/2019,2090,148.2,171.3 3/25/2019,2062,146.5,166.8 3/26/2019,2036,145.6,167.1 3/27/2019,2031,144.1,167.4 3/28/2019,2013,145.4,165 3/29/2019,2001,143,166.6 4/1/2019,2009,144.6,165.7 4/2/2019,2037,146.4,166 4/3/2019,2070,148.5,167.3 4/4/2019,2100,149.1,167.8 4/5/2019,2129,149.3,168 4/8/2019,2111,151.6,170.6 4/9/2019,2120,152.2,170.1 4/10/2019,2056,154.3,172.1 4/11/2019,2040,154.3,172.6 4/12/2019,2038,155.2,174.2 4/15/2019,2100,155.1,173.3 4/16/2019,2105,152.9,171.8 4/17/2019,2130,150.7,171.9 4/18/2019,2107,149.8,171.1 4/19/2019,2108,, 4/22/2019,2090,151.2,172.2 4/23/2019,2079,151.1,172.7 4/24/2019,2079,151,171.4 4/25/2019,2050,151.3,172 4/26/2019,2013,150.8,173.3 4/29/2019,1997,152.2,174.7 4/30/2019,1982,151.1,175 5/2/2019,1919,150.3,177.1 5/3/2019,1900,151.3,177.4 5/6/2019,1877,149.2,176 5/7/2019,1931,150.5,175 5/8/2019,1922,149.8,174.8 5/9/2019,1910,148,172.2 5/10/2019,1920,149.4,174.4 5/13/2019,1927,149.5,174.5 5/14/2019,1957,148.1,174.2 5/15/2019,1957,148.1,174.7 5/16/2019,2061,151,178.8 5/17/2019,2049,149.9,178.1 5/21/2019,2008,152.2,180.4 5/22/2019,,151.5,180.8 5/23/2019,1974,151.4,180.5 5/24/2019,1976,153.3,185.5 5/27/2019,1987,155.6,185.9 5/28/2019,2018,155.1,186.9 5/29/2019,2044,155.4,188.7 5/30/2019,2020,155.3,189.2 5/31/2019,2030,157,190.5 6/3/2019,1994,151.5,185.2 6/4/2019,2030,152.2,188.2 6/6/2019,,154.3,194.3 6/7/2019,2003,153.4,192.1 6/10/2019,1971,154.5,197.5 6/11/2019,1986,155.4,198.2 6/12/2019,1951,154.6,197.9 6/13/2019,1989,154.5,199.9 6/14/2019,2000,154,200.4 6/17/2019,2023,152.2,201.1 6/18/2019,2005,151.2,199.4 6/19/2019,2026,148.9,199.5 6/20/2019,2004,148.4,200.9 6/21/2019,1998,147.9,203.5 6/24/2019,1967,146.9,202.3 6/25/2019,1948,149.5,201.2 6/26/2019,1916,149.8,199.7 6/27/2019,1880,150.3,202.3 6/28/2019,1865,149.8,202.8 7/1/2019,1890,147.3,193.6 7/2/2019,1904,146.3,192.5 7/3/2019,1894,144.8,187.7 7/4/2019,1890,144.1,187 7/5/2019,1909,145.5,183.7 7/8/2019,1891,143.2,180.7 7/9/2019,1890,140.2,178.7 7/10/2019,1884,140,174.7 7/11/2019,1888,140,174.4 7/12/2019,1900,139.4,175 7/15/2019,1900,140.9,175.1 7/16/2019,1918,139.6,174.1 7/17/2019,1922,140.1,173.1 7/18/2019,1916,141.1,175.4 7/19/2019,1905,141.9,173.8 7/22/2019,1920,142.1,172.3 7/23/2019,1932,142.3,172.7 7/24/2019,1947,142.1,173 7/25/2019,1985,142.2,172.6 7/26/2019,1996,140.4,169.5 7/29/2019,2008,138.3,162.9 7/30/2019,,134.7,160 7/31/2019,2019,134.5,160 8/1/2019,2015,131.7,151.4 8/2/2019,2013,130.7,149.6 8/5/2019,2027,128.9,147 8/6/2019,2037,130.6,148.4 8/7/2019,2040,130.9,148 8/8/2019,2073,131.2,148 8/9/2019,2141,, 8/13/2019,2172,129.3,148.7 8/14/2019,2174,131,150 8/15/2019,2172,129.8,149 8/16/2019,2143,130.4,152.8 8/19/2019,2105,131.3,152.5 8/20/2019,2129,130.7,151 8/21/2019,2163,130.1,150.1 8/22/2019,2201,129.2,150.8 8/23/2019,2210,128.9,149.2 8/26/2019,2213,128.9,147.4 8/27/2019,2184,129.5,148.7 8/28/2019,2200,129.4,146.6 8/29/2019,2155,128.2,148.2 8/30/2019,2168,128.5,149 9/2/2019,,129.7,147.9 9/3/2019,2106,131.1,149.9 9/4/2019,2100,133.1,152.7 9/5/2019,2090,133.8,153.2 9/6/2019,2116,133.3,151.5 9/9/2019,,133,153.5 9/10/2019,2133,134,155 9/11/2019,2114,133.1,154.2 9/12/2019,2105,133.8,154.5 9/13/2019,2105,133.8,153 9/16/2019,,134.2,152.6 9/17/2019,2213,134.9,151.1 9/18/2019,2199,134,149.5 9/19/2019,2181,132.6,146 9/20/2019,2161,133,146.2 9/23/2019,2124,133.4,146.6 9/24/2019,2079,132.8,147.4 9/25/2019,2084,131.4,148.1 9/26/2019,2107,127.9,147.5 9/27/2019,2090,126.3,145.9 9/30/2019,2078,127.9,148.2 10/1/2019,2108,127.1,143.6 10/2/2019,2085,125.2,141.3 10/3/2019,2086,124.4,139.5 10/4/2019,2096,125.1,139 10/7/2019,2104,125,138.5 10/8/2019,2118,126.2,138.5 10/9/2019,2140,127.7,139.6 10/10/2019,2135,128.7,140.6 10/11/2019,2118,129.2,140.1 10/14/2019,2088,130.1,142.5 10/15/2019,2088,128.9,141.6 10/16/2019,2189,129.2,143.4 10/17/2019,2192,130.7,143.2 10/18/2019,2208,130.8,144.8 10/21/2019,2215,130.9,145 10/22/2019,2236,131.2,144 10/23/2019,2239,131.2,146.2 10/24/2019,2287,131.7,147.7 10/25/2019,2309,131.7,148.5 10/29/2019,2340,130.8,149.3 10/30/2019,2410,131.5,150.8 10/31/2019,2444,131.9,150.8 11/1/2019,2422,132.7,146.2 11/4/2019,2470,132.5,148 11/5/2019,2454,135.4,149.3 11/6/2019,2492,135.4,149.5 11/7/2019,2480,135.7,150.8 11/8/2019,2526,135.1,150.9 11/11/2019,2580,134.7,150 11/12/2019,2555,135.9,151.2 11/13/2019,2534,136.7,151.8 11/14/2019,2560,137.2,153 11/15/2019,2560,135.3,150.8 11/18/2019,2494,136.9,151.3 11/19/2019,2519,136.9,152 11/20/2019,2588,139.5,156.2 11/21/2019,2572,141.1,157.3 11/22/2019,2642,141.3,158.5 11/25/2019,2650,141.7,159.8 11/26/2019,2580,139.7,160 11/27/2019,2600,139.1,159.9 11/28/2019,2637,139.9,161 11/29/2019,2620,138.5,160.5 12/2/2019,2630,140.6,157.7 12/3/2019,2646,141.8,159.4 12/4/2019,2673,142.3,160.3 12/5/2019,2715,145.8,164.7 12/6/2019,2757,148.5,166.1 12/9/2019,2802,147.1,165.9 12/10/2019,2820,146.7,166.4 12/11/2019,2802,147.3,167.7 12/12/2019,2816,147.1,168.2 12/13/2019,2816,147.3,168.2 12/16/2019,2851,146.4,168.8 12/17/2019,2849,147,168.4 12/18/2019,2835,145.4,168.2 12/19/2019,2853,142.7,165.5 12/20/2019,2897,143.3,165.9 12/23/2019,2901,142.7,164.1 12/24/2019,2900,143.9,164.8 12/26/2019,2969,143.6,164.1 12/27/2019,3035,143.2,164 12/30/2019,3097,145.1,166.3 12/31/2019,3041,, 1/2/2020,3125,144.9,162.6 1/3/2020,3110,144.7,162 1/6/2020,3036,148,166 1/7/2020,3038,149.5,165.5 1/8/2020,3038,149.8,168.6 1/9/2020,3108,147.4,167.5 1/10/2020,3131,148.5,167 1/13/2020,3092,152.4,174.3 1/14/2020,3030,152,174.2 1/15/2020,3030,151.6,173.3 1/16/2020,2968,152.4,170.6 1/17/2020,2922,152,171.9 1/20/2020,2973,150.7,169.7 1/21/2020,2960,147.6,166.8 1/22/2020,3038,146.8,164.1 1/23/2020,2985,145.9,164.5 1/24/2020,2925,, 1/28/2020,2640,136,155.8 1/29/2020,2779,137,159.3 1/30/2020,2684,135.8,156.3 1/31/2020,2640,138,156.3 2/3/2020,2670,127.2,149.5 2/4/2020,2717,131.2,152.6 2/5/2020,2853,132.6,153.5 2/6/2020,2898,132.5,151 2/7/2020,2872,132.3,150 2/10/2020,2800,132.3,151.2 2/11/2020,2740,135.2,155.6 2/12/2020,2736,134.7,157 2/13/2020,2665,134.3,157.5 2/14/2020,2660,134.4,157.5 2/17/2020,2725,136.4,163 2/18/2020,2730,135.7,163.4 2/19/2020,2645,135.5,163 2/20/2020,2669,136.2,163.7 2/21/2020,2683,136.3,163.5 2/24/2020,2596,133.2,162 2/25/2020,2480,135.3,163.4 2/26/2020,2460,135,163.1 2/27/2020,2497,135.1,161.5 2/28/2020,2357,130.5,157.7 3/2/2020,2358,131.4,161.9 3/3/2020,2405,131,163.3 3/4/2020,2501,130.8,162.8 3/5/2020,2532,131,161.8 3/6/2020,2448,129.8,159.6 3/9/2020,2336,126.2,157.1 3/10/2020,2339,128.3,160.6 3/11/2020,2370,127.7,160.9 3/12/2020,2302,126.1,159.6 3/13/2020,2302,127.2,158 3/16/2020,2276,125.2,155.5 3/17/2020,2325,126,155.8 3/18/2020,2321,122.4,150.3 3/19/2020,2271,118.4,148 3/20/2020,2338,117.7,146.6 3/23/2020,2348,110.6,139.8 3/24/2020,2401,111.3,134.7 3/25/2020,2483,111.3,136.5 3/26/2020,2420,108.8,135.5 3/27/2020,2487,107,132.6 3/30/2020,2591,103.6,138 3/31/2020,2550,103.8,137.3 4/1/2020,2493,103.4,127.1 4/2/2020,2398,105.9,128 4/3/2020,2320,106.1,131.9 4/6/2020,2333,107.2,130 4/7/2020,2393,108.5,130.5 4/8/2020,2433,111.9,131.5 4/9/2020,2383,111.7,131.5 4/10/2020,2389,, 4/13/2020,2302,110.5,132.3 4/14/2020,2312,111.7,134 4/15/2020,2312,111.3,137 4/16/2020,2249,111.3,136.9 4/17/2020,2285,112.1,138.8 4/20/2020,2290,113.1,139 4/21/2020,2113,107.7,135.2 4/22/2020,2120,108.3,136.9 4/23/2020,2162,110.1,137 4/24/2020,2121,109.5,135.5 4/27/2020,2050,108.8,134.7 4/28/2020,2051,105.2,133.6 4/29/2020,2060,104.8,133.8 4/30/2020,2102,105,135 5/4/2020,2035,106.7,133.3 5/5/2020,2038,106.9,136.7 5/6/2020,2000,110.3,136.9 5/8/2020,2060,109.6,137.5 5/11/2020,,108.7,139 5/12/2020,2036,107.9,137 5/13/2020,2070,108.1,136 5/14/2020,2081,108,135 5/15/2020,2115,109.2,135.8 5/18/2020,2186,108.8,135.7 5/19/2020,2230,109.8,135 5/20/2020,2218,110.7,135.5 5/21/2020,2276,111.3,136.3 5/22/2020,2240,109.5,134.5 5/26/2020,,110.1,135 5/27/2020,2345,109.4,133.5 5/28/2020,2334,108,131.3 5/29/2020,2373,111.2,131.5 6/1/2020,2388,112.4,134.6 6/2/2020,2460,112,136.4 6/3/2020,2474,114,137.1 6/4/2020,2396,112.5,137.7 6/5/2020,2405,116.4,144.9 6/8/2020,,118.3,147 6/9/2020,2415,116.9,145.5 6/10/2020,2380,116.4,145.4 6/11/2020,2403,115.3,144 6/12/2020,2433,114.5,143.5 6/15/2020,2422,112.8,141.5 6/16/2020,2455,113.5,141.5 6/17/2020,2447,113.9,140.9 6/18/2020,2454,114.3,140.8 6/19/2020,2538,116.2,142 6/22/2020,2520,115.5,141.3 6/23/2020,2542,115.3,144.8 6/24/2020,2542,114,146.4 6/25/2020,2512,113.4,146 6/26/2020,2473,112.7,146.5 6/29/2020,2428,111.1,147.9 6/30/2020,2379,109.3,146.5 7/1/2020,2395,114,142 7/2/2020,2423,115.1,149.9 7/3/2020,2421,116,148.4 7/6/2020,2445,117.7,145.1 7/7/2020,2423,116.9,147.2 7/8/2020,2474,117.7,148.1 ================================================ FILE: Smart Farmers project/data/tres_grand.csv ================================================ Item,Year,production,class,area,type,lifespan,price,yield_i,eco lifespan,constant,gamma,beta,alpha Bananas,2012,289034.0,Fruit Primary,29193.0,Perennial,6.0,372.3,0.10100195824712664,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2012,94886.0,Vegetables Primary,3528.0,Annual,,372.3,0.03718145985709167,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2012,77854.0,"Roots and Tubers, Total",2825.0,Annual,,291.4,0.0362858684203766,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2012,1817389.0,"Cereals, Total",693867.0,Annual,,218.55,0.3817933309819747,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2012,40097.0,Vegetables Primary,2856.0,Annual,,1392.1,0.07122727386088734,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2012,3645.0,stimulant,11748.0,Annual,,2107.9,3.2230452674897117,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2012,624152.0,"Oilcrops, Oil Equivalent",100996.0,Perennial,70.0,372.3,0.16181314807931402,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2012,93114.0,Vegetables Primary,4607.0,Annual,,323.8,0.049476985200936484,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2012,8727.0,spice,903.0,Annual,,1699.7,0.10347198349948436,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2012,11357.0,Fruit Primary,1123.0,Perennial,50.0,615.1,0.09888174694021308,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2012,6086.0,Fruit Primary,967.0,Perennial,50.0,906.5,0.1588892540256326,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2012,39817.0,Vegetables Primary,2069.0,Annual,,841.8,0.05196272948740488,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2012,83601.0,"Cereals, Total",9322.0,Annual,,194.3,0.1115058432315403,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2012,78676.0,Fruit Primary,12862.0,Perennial,300.0,841.8,0.16348060399613604,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2012,94917736.0,"Oilcrops, Oil Equivalent",5076929.0,Perennial,30.0,199.1,0.053487674842981926,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2012,180000.0,"Oilcrops, Oil Equivalent",145000.0,Annual,,4229.8,0.8055555555555556,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2012,27660.0,Vegetables Primary,2157.0,Annual,,971.3,0.0779826464208243,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2012,16252.0,Fruit Primary,2993.0,Perennial,50.0,906.5,0.18416194929854787,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2012,35634.0,Fruit Primary,2031.0,Perennial,5.0,323.8,0.056996127294157276,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2012,26000.0,spice,10833.0,Annual,,5293.0,0.41665384615384615,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2012,314405.0,Fruit Primary,13096.0,Perennial,7.0,356.1,0.041653281595394484,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2012,17382.0,Vegetables Primary,1664.0,Annual,,323.8,0.09573121620066737,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2012,2599382.0,"Cereals, Total",684545.0,Annual,,242.8,0.2633491345250525,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2012,923020.0,tobacco,1041190.0,Perennial,32.0,3083.7,1.1280253948993522,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2012,53038.0,Vegetables Primary,4023.0,Annual,,437.1,0.0758512764433048,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2012,146164.0,sugar,4346.0,Perennial,15.0,291.4,0.029733723762349142,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2012,55838.0,"Roots and Tubers, Total",2595.0,Annual,,356.1,0.046473727569038996,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2012,1972.0,tobacco,2526.0,Annual,,4739.7,1.2809330628803246,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2012,129572.0,Vegetables Primary,1978.0,Annual,,550.4,0.015265643811934678,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2012,225681.0,Vegetables Primary,11949.0,Annual,,307.6,0.052946415515705794,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 Bananas,2013,288677.0,Fruit Primary,27085.0,Perennial,6.0,349.1,0.09382458595593,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2013,129148.0,Vegetables Primary,4845.0,Annual,,365.0,0.037515098956236254,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2013,62843.0,"Roots and Tubers, Total",4046.0,Annual,,301.5,0.06438266791846348,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2013,1823136.0,"Cereals, Total",681399.0,Annual,,214.2,0.3737510531304302,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2013,59775.0,Vegetables Primary,4104.0,Annual,,1539.2,0.06865746549560853,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2013,2809.0,stimulant,13826.0,Annual,,2003.9,4.922036311854753,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2013,624727.0,"Oilcrops, Oil Equivalent",87974.0,Perennial,70.0,333.2,0.14081991013674774,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2013,119857.0,Vegetables Primary,5161.0,Annual,,333.2,0.04305964607824324,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2013,8831.0,spice,893.0,Annual,,1269.5,0.10112105084361908,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2013,11714.0,Fruit Primary,1093.0,Perennial,50.0,460.2,0.09330715383302032,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2013,9293.0,Fruit Primary,1310.0,Perennial,50.0,777.6,0.14096631873453136,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2013,64993.0,Vegetables Primary,3346.0,Annual,,666.5,0.0514824673426369,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2013,86499.0,"Cereals, Total",9720.0,Annual,,190.4,0.11237124128602642,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2013,69266.0,Fruit Primary,11138.0,Perennial,300.0,904.5,0.1608003926890538,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2013,94917736.0,"Oilcrops, Oil Equivalent",5229739.0,Perennial,30.0,153.9,0.055097595248163114,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2013,183315.0,"Oilcrops, Oil Equivalent",152119.0,Annual,,4579.4,0.8298229822982298,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2013,34370.0,Vegetables Primary,2703.0,Annual,,952.1,0.07864416642420716,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2013,18666.0,Fruit Primary,3108.0,Perennial,50.0,1031.4,0.16650594664095147,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2013,31748.0,Fruit Primary,1934.0,Perennial,5.0,365.0,0.06091722313216581,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2013,26500.0,spice,9835.0,Annual,,5289.9,0.3711320754716981,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2013,244353.0,Fruit Primary,10580.0,Perennial,7.0,380.8,0.043298015575826784,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2013,32544.0,Vegetables Primary,2323.0,Annual,,333.2,0.07138028515240905,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2013,2603654.0,"Cereals, Total",671679.0,Annual,,238.0,0.25797552209318136,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2013,826424.0,tobacco,1057271.0,Perennial,32.0,2458.6,1.2793324008015257,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2013,56649.0,Vegetables Primary,4288.0,Annual,,444.3,0.07569418701124468,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2013,98885.0,sugar,2847.0,Perennial,15.0,253.9,0.028791019871567982,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2013,50748.0,"Roots and Tubers, Total",3042.0,Annual,,365.0,0.05994324899503429,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2013,419.0,tobacco,538.0,Annual,,4345.956117624693,1.2840095465393797,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2013,190977.0,Vegetables Primary,2831.0,Annual,,714.1,0.014823774590657512,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2013,209599.0,Vegetables Primary,11032.0,Annual,,349.1,0.052633838901903165,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 Bananas,2014,303107.0,Fruit Primary,28911.0,Perennial,6.0,580.5,0.09538215877561387,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2014,301518.0,Vegetables Primary,7937.0,Annual,,326.9,0.02632346990892749,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2014,51911.0,"Roots and Tubers, Total",3050.0,Annual,,290.3,0.05875440658049354,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2014,1283020.0,"Cereals, Total",624286.0,Annual,,275.0,0.4865754236099203,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2014,40521.0,Vegetables Primary,3582.0,Annual,,1399.4,0.08839860812911822,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2014,2665.0,stimulant,16102.0,Annual,,2607.8,6.04202626641651,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2014,595097.0,"Oilcrops, Oil Equivalent",88092.0,Perennial,70.0,275.0,0.14802964894798662,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2014,97331.0,Vegetables Primary,4661.0,Annual,,369.7,0.047888134304589484,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2014,10775.0,spice,1048.0,Annual,,2245.7,0.09726218097447796,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2014,11831.0,Fruit Primary,1009.0,Perennial,50.0,550.0,0.08528442228044966,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2014,7477.0,Fruit Primary,989.0,Perennial,50.0,1038.8,0.1322723017252909,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2014,67320.0,Vegetables Primary,3127.0,Annual,,825.0,0.046449792038027335,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2014,59188.0,"Cereals, Total",9707.0,Annual,,183.3,0.16400283841319185,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2014,77198.0,Fruit Primary,11977.0,Perennial,300.0,756.2,0.1551465063861758,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2014,95380438.0,"Oilcrops, Oil Equivalent",4689321.0,Perennial,30.0,158.6,0.0491643894526884,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2014,187043.0,"Oilcrops, Oil Equivalent",154320.0,Annual,,4609.1,0.8250509241190528,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2014,45130.0,Vegetables Primary,3120.0,Annual,,960.9,0.06913361400398847,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2014,16622.0,Fruit Primary,2965.0,Perennial,50.0,198.6,0.17837805318252914,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2014,55358.0,Fruit Primary,2771.0,Perennial,5.0,381.9,0.050055999132916654,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2014,27500.0,spice,16021.0,Annual,,6879.6,0.5825818181818182,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2014,335725.0,Fruit Primary,9456.0,Perennial,7.0,359.0,0.028165909598629836,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2014,44526.0,Vegetables Primary,2333.0,Annual,,336.1,0.0523963526928087,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2014,1834831.0,"Cereals, Total",614579.0,Annual,,366.7,0.3349512843417187,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2014,668613.0,tobacco,1065600.0,Perennial,32.0,1690.1,1.5937470554715507,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2014,51286.0,Vegetables Primary,4386.0,Annual,,458.3,0.08552041492805054,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2014,9147.0,sugar,237.0,Perennial,15.0,290.3,0.025910134470318136,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2014,51476.0,"Roots and Tubers, Total",3013.0,Annual,,397.2,0.058532131478747376,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2014,1769.0,tobacco,2292.0,Annual,,4091.3682105996395,1.295647258338044,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2014,162384.0,Vegetables Primary,1948.0,Annual,,718.0,0.01199625578874766,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2014,176379.0,Vegetables Primary,10842.0,Annual,,305.5,0.061469902879594515,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 Bananas,2015,315500.0,Fruit Primary,24858.0,Perennial,6.0,460.9,0.07878922345483359,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2015,277202.0,Vegetables Primary,8261.0,Annual,,358.5,0.02980137228447125,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2015,67713.0,"Roots and Tubers, Total",3418.0,Annual,,268.9,0.050477751687268334,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2015,1890976.0,"Cereals, Total",691589.0,Annual,,236.85,0.36573124143299546,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2015,47015.0,Vegetables Primary,2915.0,Annual,,1331.5,0.062001488886525576,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2015,1729.0,stimulant,18122.0,Annual,,2055.8,10.481203007518797,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2015,505614.0,"Oilcrops, Oil Equivalent",73167.0,Perennial,70.0,243.2,0.14470920504574636,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2015,100817.0,Vegetables Primary,4371.0,Annual,,320.1,0.043355783250840635,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2015,12924.0,spice,965.0,Annual,,1711.631924118213,0.07466728567007118,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2015,10196.0,Fruit Primary,1044.0,Perennial,50.0,601.7,0.10239309533150256,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2015,7587.0,Fruit Primary,850.0,Perennial,50.0,780.9,0.11203374192698036,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2015,66006.0,Vegetables Primary,3182.0,Annual,,808.9104313117714,0.04820773869042208,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2015,62460.0,"Cereals, Total",10030.0,Annual,,166.4,0.1605827729747038,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2015,98315.0,Fruit Primary,8344.0,Perennial,300.0,1024.2,0.08487006051975791,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2015,98344073.0,"Oilcrops, Oil Equivalent",4859397.0,Perennial,30.0,117.5,0.0494121999604389,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2015,192347.0,"Oilcrops, Oil Equivalent",155948.0,Annual,,3952.7,0.8107638798629561,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2015,50778.0,Vegetables Primary,3326.0,Annual,,857.8,0.0655008074362913,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2015,15537.0,Fruit Primary,1643.0,Perennial,50.0,385.20868947337976,0.10574757031601982,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2015,60625.0,Fruit Primary,2514.0,Perennial,5.0,345.7,0.0414680412371134,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2015,28300.0,spice,16333.0,Annual,,7177.3,0.5771378091872792,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2015,452021.0,Fruit Primary,10551.0,Perennial,7.0,307.3,0.02334183588815564,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2015,25652.0,Vegetables Primary,1817.0,Annual,,345.7,0.07083268361141433,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2015,2741404.0,"Cereals, Total",681559.0,Annual,,307.3,0.2486167671747761,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2015,722122.0,tobacco,1074386.0,Perennial,32.0,1336.3,1.4878178479536701,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2015,48357.0,Vegetables Primary,3860.0,Annual,,422.5,0.0798229832289017,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2015,30271.0,sugar,1717.0,Perennial,15.0,217.6,0.05672095404842919,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2015,50607.0,"Roots and Tubers, Total",2908.0,Annual,,371.3,0.057462406386468275,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2015,2139.0,tobacco,2791.0,Annual,,3638.898023395559,1.3048153342683495,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2015,165177.0,Vegetables Primary,1984.0,Annual,,601.7,0.012011357513455265,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2015,178928.0,Vegetables Primary,10024.0,Annual,,268.9,0.05602253420370205,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 Bananas,2016,309508.0,Fruit Primary,22294.0,Perennial,6.0,433.9,0.07203044832443749,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2016,101258.0,Vegetables Primary,3774.0,Annual,,361.6,0.03727112919473029,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2016,61161.0,"Roots and Tubers, Total",3148.0,Annual,,313.4,0.051470708458004284,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2016,1892184.0,"Cereals, Total",698812.0,Annual,,289.3,0.3693150349014683,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2016,43738.0,Vegetables Primary,3176.0,Annual,,1518.7,0.07261420275275504,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2016,1757.0,stimulant,17421.0,Annual,,2017.7,9.915196357427432,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2016,504773.0,"Oilcrops, Oil Equivalent",75151.0,Perennial,70.0,241.1,0.1488807840355962,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2016,97621.0,Vegetables Primary,4359.0,Annual,,325.4,0.0446522776861536,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2016,13362.0,spice,940.0,Annual,,1918.0617150999785,0.07034875018709774,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2016,12858.0,Fruit Primary,910.0,Perennial,50.0,554.4,0.0707730595738062,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2016,7072.0,Fruit Primary,1013.0,Perennial,50.0,771.4,0.14324095022624433,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2016,65268.0,Vegetables Primary,3017.0,Annual,,809.2907573824596,0.04622479622479622,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2016,64867.0,"Cereals, Total",10042.0,Annual,,176.02653721679238,0.15480907086808393,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2016,102046.0,Fruit Primary,8379.0,Perennial,300.0,1265.6,0.08211002881053643,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2016,86325309.0,"Oilcrops, Oil Equivalent",5001438.0,Perennial,30.0,143.2,0.05793709930421447,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2016,195130.0,"Oilcrops, Oil Equivalent",155334.0,Annual,,3869.3,0.7960539127760979,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2016,49057.0,Vegetables Primary,3127.0,Annual,,771.4,0.06374217746702815,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2016,13448.0,Fruit Primary,1557.0,Perennial,50.0,303.63192547595963,0.1157792980368828,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2016,65967.0,Fruit Primary,3980.0,Perennial,5.0,337.5,0.060333196901481034,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2016,29245.0,spice,16768.0,Annual,,6364.1,0.5733629680287229,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2016,391714.0,Fruit Primary,10354.0,Perennial,7.0,313.4,0.02643255027903011,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2016,16494.0,Vegetables Primary,1128.0,Annual,,313.4,0.06838850491087667,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2016,2739606.0,"Cereals, Total",688770.0,Annual,,289.3,0.2514120643625397,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2016,673513.0,tobacco,1077993.0,Perennial,32.0,1370.3,1.600552624819417,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2016,54823.0,Vegetables Primary,4276.0,Annual,,421.9,0.07799646133921895,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2016,28038.0,sugar,1515.0,Perennial,15.0,204.9,0.05403381125615237,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2016,43212.0,"Roots and Tubers, Total",2592.0,Annual,,301.3,0.05998333796167731,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2016,2195.0,tobacco,2864.0,Annual,,3829.529414768218,1.3047835990888383,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2016,242946.0,Vegetables Primary,2794.0,Annual,,482.1,0.011500498053065291,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2016,192910.0,Vegetables Primary,11058.0,Annual,,277.2,0.05732206728526256,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 Bananas,2017,350493.0,Fruit Primary,27565.0,Perennial,6.0,377.9,0.07864636383608231,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2017,77342.0,Vegetables Primary,3279.0,Annual,,381.4,0.04239611078068837,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2017,44229.0,"Roots and Tubers, Total",2566.0,Annual,,305.8,0.05801623369282598,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2017,2008124.0,"Cereals, Total",699745.0,Annual,,279.0,0.3484570673922527,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2017,27358.0,Vegetables Primary,2835.0,Annual,,1397.5,0.103625996052343,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2017,1029.0,stimulant,17554.0,Annual,,1436.6,17.059280855199226,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2017,517589.0,"Oilcrops, Oil Equivalent",74008.0,Perennial,70.0,281.4,0.14298603718394326,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2017,88492.0,Vegetables Primary,4401.0,Annual,,295.3,0.04973330922569272,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2017,14279.0,spice,974.0,Annual,,1926.3526621223748,0.06821205966804399,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2017,13037.0,Fruit Primary,892.0,Perennial,50.0,512.7,0.06842064892229807,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2017,6961.0,Fruit Primary,1011.0,Perennial,50.0,672.0,0.14523775319637985,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2017,40358.0,Vegetables Primary,2323.0,Annual,,880.0718990821069,0.0575598394370385,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2017,72561.0,"Cereals, Total",10477.0,Annual,,181.61446377135655,0.14438885902895496,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2017,113824.0,Fruit Primary,9571.0,Perennial,300.0,959.2,0.08408595726736014,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2017,101740900.0,"Oilcrops, Oil Equivalent",5110713.0,Perennial,30.0,140.9,0.05023263014186035,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2017,198944.0,"Oilcrops, Oil Equivalent",156347.0,Annual,,2705.7,0.7858844700016085,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2017,53937.0,Vegetables Primary,3411.0,Annual,,829.0,0.06324044718838645,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2017,13245.0,Fruit Primary,1517.0,Perennial,50.0,277.51641822220614,0.11453378633446586,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2017,83797.0,Fruit Primary,2738.0,Perennial,5.0,317.4,0.03267420074704345,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2017,30433.0,spice,17087.0,Annual,,3784.5,0.5614628856833043,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2017,340722.0,Fruit Primary,10131.0,Perennial,7.0,337.2,0.029733917974184232,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2017,23859.0,Vegetables Primary,1435.0,Annual,,306.9,0.06014501865124273,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2017,2901894.0,"Cereals, Total",689268.0,Annual,,279.0,0.2375234932771493,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2017,740138.0,tobacco,1081889.0,Perennial,32.0,1636.4,1.4617395674860634,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2017,71180.0,Vegetables Primary,5485.0,Annual,,387.2,0.07705816240517,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2017,29990.0,sugar,1668.0,Perennial,15.0,218.6,0.055618539513171056,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2017,41245.0,"Roots and Tubers, Total",2441.0,Annual,,391.8,0.05918293126439569,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2017,2034.0,tobacco,2659.0,Annual,,3758.1754705530975,1.3072763028515242,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2017,188185.0,Vegetables Primary,1941.0,Annual,,538.3,0.010314318356935994,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2017,172275.0,Vegetables Primary,9595.0,Annual,,300.0,0.055695835147293565,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 Bananas,2018,376589.0,Fruit Primary,31183.0,Perennial,6.0,359.3,0.0828037993674802,0.7619,1.4775924043946734e-07,0.0066422536897316475,0.02577042054531402,0.0013509362773830534 Cabbages and other brassicas,2018,151934.0,Vegetables Primary,5428.0,Annual,,359.3,0.035726038937959906,0.8,5.081663891103838,0.0028397100292019747,0.011502973679406303,0.00014088930766170443 Cassava,2018,39762.0,"Roots and Tubers, Total",2158.0,Annual,,223.0,0.05427292389718827,0.8,284.8992339846437,4.321493316516116e-08,3.735024028915422e-08,1.414317538031664e-08 Cereals (Rice Milled Eqv),2018,1889926.0,"Cereals, Total",677163.0,Annual,,297.4,0.35830133031663675,0.8,0.001987345196132716,1.3419447194224203e-06,0.011127306605191635,4.320552572277093e-05 "Chillies and peppers, green",2018,35581.0,Vegetables Primary,2891.0,Annual,,1462.2,0.0812512295888255,0.8,1035.7086425867562,0.017571057336174735,0.007064324870975976,9.625527915760374e-09 "Cocoa, beans",2018,1505.0,stimulant,18000.0,Annual,,1525.1,11.960132890365449,0.8,705.4388994711713,0.11980808648112415,-1.2139759647537151e-08,-1.0307794008680998e-08 Coconuts,2018,519153.0,"Oilcrops, Oil Equivalent",71352.0,Perennial,70.0,297.4,0.13743925201241253,0.9796,0.0006602655391586947,0.02782428726444178,1.2316494451506829e-08,2.8201595519240104e-08 Cucumbers and gherkins,2018,89396.0,Vegetables Primary,4582.0,Annual,,309.8,0.05125508971318627,0.8,166.22483946655964,0.015133662343010812,1.634150404204424e-07,2.100576073161531e-09 Ginger,2018,9945.0,spice,992.0,Annual,,1904.0526853161768,0.09974861739567624,0.8,0.009656681316925098,0.00020003396941839675,0.059777763162679555,1.05197455050944e-07 Grapefruit (inc. pomelos),2018,12794.0,Fruit Primary,837.0,Perennial,50.0,532.8,0.06542129123026419,0.9714,11.436837611149318,0.003182554077728488,0.03126340350066342,0.03720816717256728 Lemons and limes,2018,6997.0,Fruit Primary,1031.0,Perennial,50.0,718.7,0.1473488637987709,0.9714,5.013050051048595,0.08952707223765867,9.689946471535268e-07,0.018605709180711458 Lettuce and chicory,2018,57211.0,Vegetables Primary,2931.0,Annual,,801.1943819018389,0.05123140654769188,0.8,218.41581513200148,5.844932375604774e-06,0.025102616503896346,0.0030379289060933306 Maize,2018,76362.0,"Cereals, Total",10237.0,Annual,,185.21444467527138,0.13405882507006106,0.8,75.46003640087407,0.010176731485581784,8.536979215952399e-07,1.1068385568795221e-07 "Mangoes, mangosteens, guavas",2018,67087.0,Fruit Primary,10645.0,Perennial,300.0,1486.9,0.15867455691862806,0.9952,-5.453422700810914e-09,-4.137515895285942e-09,0.04167946149358704,0.002583048754685576 Oil palm fruit,2018,98419400.0,"Oilcrops, Oil Equivalent",5235581.0,Perennial,30.0,116.0,0.05319663602907557,0.9524,178.6785668519915,0.015621424444518923,1.500140658472744e-08,2.04633913640054e-06 Oilseeds nes,2018,202758.0,"Oilcrops, Oil Equivalent",157334.0,Annual,,2948.6,0.7759693822191973,0.8,18548.08536055455,0.010495734048645749,0.0007850758585768399,0.07754978969801597 Okra,2018,51257.0,Vegetables Primary,3219.0,Annual,,817.8,0.0628011783756365,0.8,25.814268096499607,0.06410322892582927,0.014089847348207724,0.005538105300982748 Oranges,2018,13437.0,Fruit Primary,1667.0,Perennial,50.0,376.9277186026508,0.12406043015554068,0.9714,0.0023418829337384242,0.04759881434460983,1.7579187987519577e-08,4.742113051105619e-08 Papayas,2018,50519.0,Fruit Primary,2874.0,Perennial,5.0,359.3,0.05688948712365645,0.7143,0.24035847219470824,0.019981695498761186,0.004934608258056912,0.00022906998750149836 Pepper (piper spp.),2018,30457.0,spice,16675.0,Annual,,2550.6,0.5474931871162623,0.8,19174.484714066337,1.48392337980803e-06,1.3049976104015312e-05,0.48824687434339115 Pineapples,2018,329365.0,Fruit Primary,10556.0,Perennial,7.0,347.0,0.032049549891457814,0.7959,4.09547136063259,0.026308780143381123,0.004322754298282098,0.00020002150445598877 "Pumpkins, squash and gourds",2018,29568.0,Vegetables Primary,1903.0,Annual,,334.6,0.06436011904761904,0.8,245.5257326086122,0.007813270275751892,1.8478048929440498e-07,6.965075806266524e-09 "Rice, paddy",2018,2718987.0,"Cereals, Total",666926.0,Annual,,297.4,0.2452847328802969,0.8,2.3825245033796008e-07,1.2207150148941924e-08,0.018771595096456036,0.00010787808718958383 "Rubber, natural",2018,781996.0,tobacco,1103880.0,Perennial,32.0,1347.1,1.4116184737517838,0.9554,0.00048695106719067886,0.17627607059488273,3.538065072618974e-09,-1.3866574659630312e-09 Spinach,2018,58120.0,Vegetables Primary,4491.0,Annual,,446.1,0.07727116311080523,0.8,1.434881969414173,0.02985587810532678,0.008064269373876842,0.0022874357848000934 Sugar cane,2018,29433.0,sugar,811.0,Perennial,15.0,246.78089608441445,0.02755410593551456,0.9048,0.0002802732158983135,0.023488122329431104,7.222272810149916e-09,1.1083602062240213e-08 Sweet potatoes,2018,38664.0,"Roots and Tubers, Total",2277.0,Annual,,396.5,0.05889199255121042,0.8,3.6036850129753886e-07,0.030546509519943792,0.0026792121035462235,0.0007114090254676243 "Tobacco, unmanufactured",2018,2123.0,tobacco,2779.0,Annual,,3889.6001454970665,1.3089967027790863,0.8,1597.513293988024,0.2609586448743896,2.578109896401012e-07,0.16547911430158946 Tomatoes,2018,109303.0,Vegetables Primary,1897.0,Annual,,631.9,0.017355424828229785,0.8,-1.5684319280144374e-08,0.06097279617744068,-1.106642146233726e-08,0.00020453841180799234 Watermelons,2018,185290.0,Vegetables Primary,10797.0,Annual,,297.4,0.0582708187166064,0.8,36.80612043021051,0.025112082291921235,4.2861419032304196e-08,-3.391033478724481e-08 ================================================ FILE: Smart Farmers project/estimate demand.py ================================================ # coding: utf-8 # In[1]: import numpy as np import os import pandas as pd import statsmodels.api as sm import matplotlib.pyplot as plt import cvxopt os.chdir('H:/') # ### define functions # In[2]: #create xy for least square def create_xy(target_crop,grande,malay_gdp,malay_pop): y=grande['price'][target_crop] x=pd.concat([malay_gdp['Value'],malay_pop['Value'], grande['production'][target_crop]],axis=1) x=sm.add_constant(x) #set production negative x[target_crop.lower()]=x[target_crop].apply(lambda x:-1*x) del x[target_crop] return x,y # In[3]: #linear regression def lin_reg(crops,grande,malay_gdp,malay_pop,viz=False): D={} #run regression for target_crop in crops: #create xy x,y=create_xy(target_crop,grande,malay_gdp,malay_pop) m=sm.OLS(y,sm.add_constant(x)).fit() D[target_crop]=(m.rsquared,m.params.tolist()) #viz if viz: fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.ylabel('USD/Tonnes') plt.xlabel('Year') plt.plot(range(beginyear,endyear),m.predict(),label='Est',color='#C8C8A9') plt.plot(range(beginyear,endyear),y,label='Act',color='#EDE574') plt.title(target_crop+' Price') plt.legend() plt.show() return D # In[4]: def constrained_ols(x,y): linear_coeff=cvxopt.matrix(-1*np.mat(y.tolist())*np.mat(x)).T quadratic_coeff=cvxopt.matrix(np.mat(x).T*np.mat(x)) #inequality constraint inequality_coeff=cvxopt.matrix(0.0,(len(x.columns),len(x.columns))) #diagonal matrix #use -1 to achieve larger than inequality_coeff[::len(x.columns)+1]=-1 #no constraint for the constant inequality_coeff[0,0]=0 inequality_value=cvxopt.matrix([0.0 for _ in range(len(x.columns))]) cvxopt.solvers.options['show_progress']=False ans=cvxopt.solvers.qp(P=quadratic_coeff,q=linear_coeff, G=inequality_coeff,h=inequality_value)['x'] return ans # In[5]: #create params by using constrained ols def get_params(crops,grande,malay_gdp,malay_pop,viz=False): D={} for target_crop in crops: #create xy x,y=create_xy(target_crop,grande,malay_gdp,malay_pop) #constrained ols ans=constrained_ols(x,y) #viz if viz: #get forecast and convert to list forecast=np.mat(ans).T*np.mat(x).T forecast=forecast.ravel().tolist()[0] fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.ylabel('USD/Tonnes') plt.xlabel('Year') plt.plot(range(beginyear,endyear),forecast,label='Est',color='#C8C8A9',) plt.plot(range(beginyear,endyear),y,label='Act',color='#EDE574') plt.legend() plt.title(target_crop+' Price') plt.show() D[target_crop]=list(ans) return D # ### execution # In[6]: global beginyear,endyear beginyear=2012 endyear=2019 # In[7]: grand=pd.read_csv('grand.csv') malay_pop=pd.read_csv('malay_pop.csv') malay_gdp=pd.read_csv('malay_gdp.csv') # In[8]: #cleanse malay_pop=malay_pop[malay_pop['Year'].isin(range(beginyear,endyear))] malay_pop.reset_index(inplace=True,drop=True) # In[9]: #pivot grande=grand.pivot(index='Year',columns='Item',values=['price','production']) grande.reset_index(inplace=True,drop=True) # In[10]: #find crops crops=grande.columns.levels[1] # ### linear regression # In[11]: D1=lin_reg(crops,grande,malay_gdp,malay_pop,viz=True) # In[12]: D1 # ### constrained regression # In[13]: D2=get_params(crops,grande,malay_gdp,malay_pop,viz=True) # In[14]: # #replace unsuccessful result with ols # for i in D2: # if len([j for j in D2[i] if j<0])>0: # D2[i]=D1[i][1] # In[15]: #create output output=pd.DataFrame(columns=D2.keys()) for i in D2: output[i]=D2[i] output=output.T output.columns=['constant','gamma','beta','alpha'] output.index.name='Item' output.reset_index(inplace=True) # In[16]: #merge with grand tres_grand=grand.merge(output,on='Item',how='left') tres_grand.to_csv('tres_grand.csv',index=False) # ### backtest # In[17]: forecast=pd.read_csv('forecast.csv') # In[18]: #extract historical generic 1st palm=pd.read_csv('palm.csv') palm.set_index('Date',inplace=True,) palm.index=pd.to_datetime(palm.index) palm.columns=['Palm oil','Rubber1','Rubber2'] # In[19]: cme=pd.read_csv('cme.csv') #extract cme palm oil futures palm_futures=cme[cme['date']==cme['date'].iloc[-1]][cme['product_id']==2457] palm_futures=palm_futures[['expiration_date','prior_settle']] palm_futures.columns=['Date','Palm oil'] palm_futures.set_index('Date',inplace=True) palm_futures.index=pd.to_datetime(palm_futures.index) # In[20]: #concat, currency convert and get annual avg temp=palm['Palm oil'][str(beginyear):].apply(lambda x:x*0.23).append(palm_futures['Palm oil'][:str(endyear+5)]) palmoil=temp.resample('1A').mean() #convert datetime index from year end to beginning palmoil.index=[pd.to_datetime(str(i)[:5]+'01-01') for i in palmoil.index] # In[21]: #create oil palm actual and estimated price oilpalm_act=grand['price'][grand['Item']=='Oil palm fruit'] oilpalm_act.reset_index(inplace=True,drop=True) oilpalm_est=oilpalm_act.iloc[-1:].append(forecast['price'][forecast['Item']=='Oil palm fruit']) oilpalm_est.reset_index(inplace=True,drop=True) # In[22]: #dual axis plot fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.set_xlabel('Date') ax.set_ylabel('Palm Oil Generic 1st',color='#45ADA8') ax.plot(palmoil.index,palmoil,color='#45ADA8',label='Palm Oil') ax.tick_params(axis='y',labelcolor='#45ADA8') ax.yaxis.labelpad=15 plt.legend(loc=3) ax2=ax.twinx() ax2.set_ylabel('Oil Palm Fruit Price',color='#EC2049',rotation=270) ax2.plot(palmoil.index[:len(oilpalm_act)],oilpalm_act, color='#EC2049',label='Oil Palm Act') ax2.plot(palmoil.index[len(oilpalm_est)-1:],oilpalm_est, color='#fea5c4',label='Oil Palm Est',linestyle='-.') ax2.tick_params(axis='y',labelcolor='#EC2049') ax2.yaxis.labelpad=15 fig.tight_layout() plt.legend(loc=4) plt.grid(False) plt.title('Palm Oil vs Oil Palm') plt.show() ================================================ FILE: Smart Farmers project/forecast.py ================================================ # coding: utf-8 # In[1]: import numpy as np import os import pandas as pd import scipy.optimize import random as rd import matplotlib.pyplot as plt import cvxopt os.chdir('H:/') # ### define functions # In[2]: #etl def prepare(grand): global D D={} for i in grand['Year'].unique(): D[i]=grand[grand['Year']==i] D[i].reset_index(inplace=True,drop=True) return D # In[3]: #quadratic programming def get_ans(quadratic_coeff,linear_coeff,inequality_coeff, inequality_value,equality_coeff,equality_value): cvxopt.solvers.options['show_progress']=False ans=cvxopt.solvers.qp(P=quadratic_coeff,q=linear_coeff, G=inequality_coeff,h=inequality_value, A=equality_coeff,b=equality_value)['x'] return list(ans) # In[4]: #linear version def get_production(initial_guess): #create profit price=D[currentyear]['price'] linear_coeff=cvxopt.matrix(initial_guess-price) #none quadratic_coeff=cvxopt.matrix(0.0,(len(D[currentyear]),len(D[currentyear]))) #maximum cropland constraint equality_coeff=cvxopt.matrix(D[currentyear]['yield_i']).T equality_value=cvxopt.matrix(malay_land['Value'][malay_land['Year']==currentyear].item()*1000) #crop rotation constraint area_hist=D[currentyear-1]['area'].tolist() eco_lifespan=D[currentyear]['eco lifespan'].tolist() inequality_coeff=cvxopt.matrix(0.0,(len(D[currentyear]),len(D[currentyear]))) #diagonal matrix #use -1 to achieve larger than inequality_coeff[::len(D[currentyear])+1]=D[currentyear]['yield_i'].apply(lambda x:-1*x).tolist() #use -1 to achieve larger than inequality_value=cvxopt.matrix(np.multiply(np.multiply(area_hist,eco_lifespan),-1)) #cvxopt estimate=get_ans(quadratic_coeff,linear_coeff,inequality_coeff, inequality_value,equality_coeff,equality_value) return estimate # In[5]: #quadratic version def get_production(initial_guess): #get historical price price_hist=np.mat(D[currentyear-1]['price']).T #create alpha diagonal alpha=np.diag(D[currentyear]['alpha']) #get historical production #use negative value production_hist=np.mat(D[currentyear-1]['production']).T #get population change delta_pop=malay_pop['Value'][malay_pop['Year']==currentyear].item()-malay_pop['Value'][malay_pop['Year']==currentyear-1].item() #create beta beta=np.mat(D[currentyear]['beta']).T #get gdp per capita change delta_gdp=malay_gdp['Value'][malay_gdp['Year']==currentyear].item()-malay_gdp['Value'][malay_gdp['Year']==currentyear-1].item() #create gamma gamma=np.mat(D[currentyear]['gamma']).T #create linear coefficient #production_hist*-1 to obtain negative production linear_coeff=-price_hist+(alpha*production_hist*-1)-delta_pop*beta-delta_gdp*gamma+np.mat(initial_guess).T linear_coeff=cvxopt.matrix(linear_coeff) #create quadratic coefficient quadratic_coeff=cvxopt.matrix(alpha) #maximum cropland constraint equality_coeff=cvxopt.matrix(D[currentyear]['yield_i']).T equality_value=cvxopt.matrix(malay_land['Value'][malay_land['Year']==currentyear].item()*1000) #crop rotation constraint seems to be too large for upper bound #we use the same upperbound as perennial area_hist=D[currentyear-1]['area'] eco_lifespan=D[currentyear]['eco lifespan'].tolist() #smaller than upperblock=np.diag(D[currentyear]['yield_i']) #larger than #use -1 lowerblock=np.diag(D[currentyear]['yield_i'].apply(lambda x:-1*x)) #concat inequality_coeff=cvxopt.matrix(np.append(upperblock,lowerblock,axis=0)) inequality_value=cvxopt.matrix((area_hist*upperbound).append(np.multiply(np.multiply(area_hist,eco_lifespan),-1))) #cvxopt estimate=get_ans(quadratic_coeff,linear_coeff,inequality_coeff, inequality_value,equality_coeff,equality_value) return estimate # In[6]: #compute sse def costfunction(initial_guess): #cvxopt estimate=get_production(initial_guess) actual=D[currentyear]['production'].tolist() cost=sum(np.power(np.divide(np.subtract(actual,estimate),actual),2)) return cost # In[7]: #least square to estimate the best cost def ls_estimate(initial_guess,diagnosis=True): if diagnosis: #get sse before least square sse_original=costfunction(initial_guess) print(f'Initial SSE: {round(sse_original,2)}') #least square least_square=scipy.optimize.minimize(costfunction, x0=(initial_guess), method='Nelder-Mead') #if successful return result #else print the issue if least_square.success: if diagnosis: sse=costfunction(least_square.x) print(f'Result SSE: {round(sse,2)}') return least_square.x else: print(least_square) return [0] # In[8]: #using random initial value to find the best starting point def find_init(num=10): global currentyear dic={} #try random cost for _ in range(num): initial_guess=pd.Series([i*rd.random() for i in D[currentyear]['price']]) ans=ls_estimate(initial_guess,diagnosis=False) if len(ans)>1: sample=[] #get average sse of all years for currentyear in range(beginyear,endyear): cost=costfunction(ans) sample.append(cost) dic[np.mean(sample)]=initial_guess return dict(sorted(dic.items())) # In[9]: #write init values into txt def write_file(dic): f=open('init.txt','w') for i in dic: f.write('\n\n'+str(i)+'\n\n') for j in dic[i].astype(str): f.write(j+'\n') f.close() return # In[10]: #use production to compute price def compute_price(production): #get historical price price_hist=np.mat(D[currentyear-1]['price']).T #create alpha diagonal alpha=np.diag(D[currentyear]['alpha']) #get historical production #use negative value production_hist=np.mat(D[currentyear-1]['production']).T #get population change delta_pop=malay_pop['Value'][malay_pop['Year']==currentyear].item()-malay_pop['Value'][malay_pop['Year']==currentyear-1].item() #create beta beta=np.mat(D[currentyear]['beta']).T #get gdp per capita change delta_gdp=malay_gdp['Value'][malay_gdp['Year']==currentyear].item()-malay_gdp['Value'][malay_gdp['Year']==currentyear-1].item() #create gamma gamma=np.mat(D[currentyear]['gamma']).T #predict price price_est=price_hist+delta_pop*beta+delta_gdp*gamma-(alpha*production*-1)+(alpha*production_hist*-1) return price_est.ravel().tolist()[0] # ### execution # In[11]: grand=pd.read_csv('tres_grand.csv') capita=pd.read_csv('capita.csv') # In[12]: #create time series capita.set_index('Date',inplace=True,) capita.index=pd.to_datetime(capita.index) # In[13]: global malay_land malay_land=pd.read_csv('malay_land.csv') global malay_pop malay_pop=pd.read_csv('malay_pop.csv') global malay_gdp malay_gdp=pd.read_csv('malay_gdp.csv') # In[14]: #ffill land area for 2018 malay_land.at[6,'Value']=malay_land.at[5,'Value'] # In[15]: global D D=prepare(grand) # In[16]: global beginyear,endyear beginyear=2013 endyear=2019 # In[17]: global currentyear currentyear=2013 # In[18]: global upperbound,lowerbound upperbound=1.2 lowerbound=-0.8 # ### margin weighted cost # In[19]: cost_optimal=[46.45261724887184, 25.771497795481803, 8.04132847940984, 257.7585247333969, 6.2550124573415955, 0.286864009247044, 79.32795295554159, 14.445506332549158, 1.685693777638147, 1.7429878194147876, 1.1023982955265745, 8.870826525406954, 10.129836899368781, 12.685177915888149, 13825.333042426462, 27.911072146085953, 6.803152547546634, 2.218450015909855, 8.289956670382614, 4.143929068809526, 50.592542452998224, 4.215768472073825, 371.2574670551623, 106.12409983634397, 8.127574487076723, 5.49462574257295, 6.734987344270521, 0.25431612106271956, 25.95233336898883, 27.02920135710488] # In[20]: # #cost linear system # def cost_func(x): # temp=[None for _ in range(len(x))] # for i in range(len(x)): # temp[i]=ss[i]*tt-ss[i]*sum(x)-x[i] # return temp # #create margin weighted cost # dick={} # for currentyear in range(beginyear,endyear): # global ss # ss=D[currentyear]['production']/sum(D[currentyear]['production']) # global tt # tt=sum(D[currentyear]['price']) # dick[currentyear]=scipy.optimize.fsolve(cost_func,x0=[1000 for _ in range(len(ss))]) # #get average cost # avgcost=[] # for ii in range(len(ss)): # avgcost.append(np.mean([dick[i][ii] for i in dick])) # ### viz # In[21]: #get predicted production X={} for currentyear in range(beginyear,endyear): x=get_production(cost_optimal) X[currentyear]=x #plot predicted production for ii in range(len(X[currentyear])): Y=[D[i]['production'][ii] for i in range(beginyear,endyear)] fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.plot(range(beginyear,endyear),[X[i][ii] for i in X],label='Est',color='#ef6466') plt.plot(range(beginyear,endyear),Y,label='Act',color='#9f65a2') plt.ylabel('Tonnes') plt.xlabel('Year') plt.legend() plt.title(D[currentyear]['Item'][ii]+' Production') plt.show() #plot overall production fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.plot(range(beginyear,endyear),[sum(X[i]) for i in X], label='Est',color='#ef6466') plt.plot(range(beginyear,endyear),[sum(D[i]['production']) for i in X], label='Act',color='#9f65a2') plt.ylabel('Tonnes') plt.xlabel('Year') plt.legend() plt.title('Overall Production') plt.show() # In[22]: #plot predicted price price_predict={} for currentyear in range(beginyear,endyear): price_predict[currentyear]=compute_price(np.mat(X[currentyear]).T) #plot predicted price for ii in range(len(price_predict[currentyear])): Y=[D[i]['price'][ii] for i in range(beginyear,endyear)] fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.ylabel('USD/Tonnes') plt.xlabel('Year') plt.plot(range(beginyear,endyear),[price_predict[i][ii] for i in price_predict], label='Est',color='#99B800',) plt.plot(range(beginyear,endyear),Y,label='Act',color='#1b5004',) plt.legend() plt.title(D[currentyear]['Item'][ii]+' Price') plt.show() # ### forecast # In[23]: beginyear=2019;endyear=2025 # In[24]: #add gdp per capita forecast from imf gdp_extra=malay_gdp.iloc[:(endyear-beginyear)].copy() gdp_extra['Year']=range(beginyear,endyear) gdp_extra['Year Code']=range(beginyear,endyear) gdp_extra['Value']=capita['Mid Price'][str(beginyear):str(endyear)].tolist() malay_gdp=malay_gdp.append(gdp_extra) # In[25]: #add land per capita forecast #i mean ffill land_extra=malay_land.iloc[:(endyear-beginyear)].copy() land_extra['Year']=range(beginyear,endyear) land_extra['Year Code']=range(beginyear,endyear) # In[26]: #assume land grows 1% per annum temp=[malay_land['Value'].iloc[-1]] for i in range(len(land_extra)): temp.append(temp[-1]*1.01) temp.pop(0) # In[27]: #concat land land_extra['Value']=temp malay_land=malay_land.append(land_extra) # In[28]: #make forecast for currentyear in range(beginyear,endyear): D[currentyear]=D[currentyear-1].copy() D[currentyear]['production']=0.0 D[currentyear]['area']=0.0 D[currentyear]['price']=0.0 D[currentyear]['Year']=currentyear D[currentyear]['production']=get_production(cost_optimal) D[currentyear]['price']=compute_price(np.mat(D[currentyear]['production']).T) D[currentyear]['area']=np.multiply(D[currentyear]['production'],D[currentyear]['yield_i']) # In[29]: #plot predicted production for ii in range(len(D[currentyear])): fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.ylabel('Tonnes') plt.xlabel('Year') plt.plot([D[i]['production'][ii] for i in D],color='#0e3c6b',) plt.title(D[currentyear]['Item'][ii]+' Production') plt.show() #plot overall production fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.ylabel('Tonnes') plt.xlabel('Year') plt.plot([sum(D[i]['production']) for i in D],color='#0e3c6b',) plt.title('Overall Production') plt.show() # In[30]: #plot predicted price for ii in range(len(D[currentyear])): fig=plt.figure(figsize=(10,5)) ax=fig.add_subplot(111) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) plt.ylabel('USD/Tonnes') plt.xlabel('Year') plt.plot([D[i]['price'][ii] for i in D],color='#7d0b02',) plt.title(D[currentyear]['Item'][ii]+' Price') plt.show() # In[31]: #export forecast pd.concat([D[i] for i in range(beginyear,endyear)]).to_csv('forecast.csv',index=False) ================================================ FILE: VIX Calculator.py ================================================ # coding: utf-8 # In[1]: #check cboe white paper on the details of computation # http://www.cboe.com/micro/vix/vixwhite.pdf #check this awesome article on the connection between vix and variance swap # https://berentlunde.netlify.app/post/the-fear-index-vix-and-variance-swaps #check this paper on the variance swap # https://www.researchgate.net/publication/246869706_More_Than_You_Ever_Wanted_to_Know_About_Volatility_Swaps import pandas as pd import datetime as dt import dateutil import decimal import os import numpy as np os.chdir('K:/ecole/github/televerser/données') # In[2]: #fill weekend and holiday missing cmt rate def cmt_rate_fill_date(cmt_rate): #get missing date as well complete_date=pd.date_range(cmt_rate['Date'].min(),cmt_rate['Date'].max()) #reindex to fill missing date cmt_rate=cmt_rate.pivot(index='Date',columns='maturity',values='value') cmt_rate=cmt_rate.reindex(complete_date) #cleanse cmt_rate.index.name='Date' cmt_rate.reset_index(inplace=True) #ffill cmt_rate.fillna(method='ffill',inplace=True) #revert to the original form cmt_rate=cmt_rate.melt(id_vars='Date',value_vars=['1 Mo', '1 Yr', '10 Yr', '2 Mo', '2 Yr', '20 Yr', '3 Mo', '3 Yr', '30 Yr', '5 Yr', '6 Mo', '7 Yr']) return cmt_rate # In[3]: #get settlement day in datetime format #you can scrape the following website of cme instead # f'https://www.cmegroup.com/CmeWS/mvc/ProductCalendar/Options/{futures_id}?optionTypeFilter=&optionTypeFilter=' #however it has some conflicts with cme globex s own holiday calendar # https://www.cmegroup.com/tools-information/holiday-calendar.html def get_settlement_day(current_day,time_horizon, expiration_day,expiration_hour, public_holidays): #get month end at expiration hour month_end=current_day+dateutil.relativedelta.relativedelta(day=31,hour=expiration_hour, minute=0,second=0, microsecond=0, months=+time_horizon-1) #adjust to the nth last day of the month settlement_day=month_end #use loop to skip non trading day correct=False #count the month end if its a weekday counter=1 if dt.datetime.weekday(settlement_day) in range(5) else 0 while not correct: #cannot be a weekend day or a federal holiday if (dt.datetime.weekday(settlement_day) in range(5)) and \ (str(settlement_day)[:10] not in public_holidays) and \ counter>expiration_day-1: correct=True else: settlement_day-=dt.timedelta(days=1) #weekday is counted even if its federal holiday if (dt.datetime.weekday(settlement_day) in range(5)): counter+=1 return settlement_day # In[4]: #get time to expiration #instead of current day+settlement day+other days #we can directly use timedelta to obtain the result in minutes #no need to skip any holidays in this calculation def get_time_to_expiration(current_day,time_horizon, expiration_day,expiration_hour, public_holidays): #get settlement day settlement_day=get_settlement_day(current_day,time_horizon, expiration_day,expiration_hour, public_holidays) #convert seconds to minutes #divided by minutes in a year return (settlement_day-current_day).total_seconds()/60/525600 # In[5]: #get forward level and strike price no larger than forward def get_forward_strike(options, interest_rate, time_to_expiration): #cleanse options=options.sort_values('options-strikePrice') find_forward=options.pivot(index='options-strikePrice', columns='options-optiontype', values='options-priorSettle') #find the forward level with the least put call disparity min_diff_ind=(find_forward['call']-find_forward['put']).apply(abs).idxmin() min_diff=float(decimal.Decimal(find_forward['call'][min_diff_ind].astype(str))-decimal.Decimal(find_forward['put'][min_diff_ind].astype(str))) forward=min_diff_ind+np.e**(interest_rate*time_to_expiration)*(min_diff) #find the strike price no larger than forward level strike=find_forward.index[find_forward.index<=forward][-1] return forward,strike # In[6]: #select out of money call options #with zero prior settle exclusion def get_options_call_inclusion(options,strike): options_call=options[options['options-optiontype']=='call'] #select outta money options #cuz they are usually more liquid options_call_otm=options_call[options_call['options-strikePrice']>strike] #sort by strike price options_call_otm=options_call_otm.sort_values('options-strikePrice') options_call_otm.reset_index(inplace=True,drop=True) #find all zero prior settle options options_call_otm_zeros=options_call_otm[options_call_otm['options-priorSettle']==0] options_call_otm_zeros.reset_index(inplace=True) #as we dont have bid and ask #we use prior settle instead #once options with consecutive strike prices have zero prior settle #any further out of money options would be excluded if options_call_otm_zeros[options_call_otm_zeros['index'].diff()==1].empty: ind=len(options_call_otm) else: ind=options_call_otm_zeros['index'][options_call_otm_zeros['index'].diff()==1].iloc[0] #exclude all zero prior settle options options_call_inclusion=options_call_otm[options_call_otm['options-priorSettle']!=0][:ind] #cleanse options_call_inclusion.reset_index(inplace=True,drop=True) return options_call_inclusion # In[7]: #select out of money put options #with zero prior settle exclusion def get_options_put_inclusion(options,strike): options_put=options[options['options-optiontype']=='put'] #select outta money options #cuz they are usually more liquid options_put_otm=options_put[options_put['options-strikePrice']