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├── Efficient _Frontier_implementation.ipynb
└── README.md
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FILE: Efficient _Frontier_implementation.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Efficient Frontiner from Modern Portfolio Theory implemented in Python"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"My personal interest in finance has led me to take an online course on Coursera. It is a 5-course specialization by the University of Geneva partnered with UBS. It is not specifically for financial modelling, but more for general introduction in investment strategies and the theories surrounding them. As someone who doesn't have any experience in the industry, the course is really helpful to understand the big picture. I am currently on the 3rd course within the specialization, and I learned something very interesting called \"Modern Portfolio Theory\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"While I was going through the course, I thought it would be a very good material to practice my Python skills. Even though the course did not provide any technical details of how to implement it in Python, with some digging I found a couple of very useful blog posts I can refer to."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Series of Medium blog post by Bernard Brenyah (https://medium.com/@bbrenyah)\n",
"- Markowitz’s Efficient Frontier in Python [Part 1/2] (https://medium.com/python-data/effient-frontier-in-python-34b0c3043314)\n",
"- Markowitz’s Efficient Frontier in Python [Part 2/2] (https://medium.com/python-data/efficient-frontier-portfolio-optimization-with-python-part-2-2-2fe23413ad94)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Blog post by Bradford Lynch (http://www.bradfordlynch.com/)\n",
"- Investment Portfolio Optimization (http://www.bradfordlynch.com/blog/2015/12/04/InvestmentPortfolioOptimization.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Based on what I have learned through the course, and also from the above blog posts, I have tried to replicate it in my own way, tweaking bit and pieces along the way."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Modern Portfolio Theory"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Modern Portfolio Theory (MPT) is an investment theory developed by Harry Markowitz and published under the title \"Portfolio Selection\" in the Journal of Finance in 1952.\n",
"\n",
"There are a few underlying concepts that can help anyone to understand MPT. If you are familiar with finance, you might know what the acronym \"TANSTAAFL\" stands for. It is a famous acronym for \"There Ain't No Such Thing As A Free Lunch\". This concept is also closely related to 'risk-return trade-off'.\n",
"\n",
"Higher risk is associated with greater probability of higher return and lower risk with a greater probability of smaller return. MPT assumes that investors are risk-averse, meaning that given two portfolios that offer the same expected return, investors will prefer the less risky one. Thus, an investor will take on increased risk only if compensated by higher expected returns. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another factor comes in to play in MPT is \"diversification\". Modern portfolio theory says that it is not enough to look at the expected risk and return of one particular stock. By investing in more than one stock, an investor can reap the benefits of diversification – chief among them, a reduction in the riskiness of the portfolio.\n",
"\n",
"What you need to understand is \"risk of a portfolio is not equal to average/weighted-average of individual stocks in the portfolio\". In terms of return, yes it is the average/weighted average of individual stock's returns, but that's not the case for risk. The risk is about how volatile the asset is, if you have more than one stock in your portfolio, then you have to take count of how these stocks movement correlates with each other. The beauty of diversification is that you can even get lower risk than a stock with the lowest risk in your portfolio, by optimising the allocation. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I will try to explain as I go along with the actual code. First, let's start by importing some libraries we need. \"Quandl\" is a financial platform which also offers Python library. If you haven't installed it before, of course, you first need to install the package in your command line \"pip install quandl\", and before you can use it, you also need to get an API key on Quandl's website. Sign-up and getting an API key is free but has some limits. As a logged-in free user, you will be able to call 2,000 calls per 10 minutes maximum (speed limit), and 50,000 calls per day (volume limit). https://www.quandl.com/"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd \n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import quandl\n",
"import scipy.optimize as sco\n",
"\n",
"plt.style.use('fivethirtyeight')\n",
"np.random.seed(777)\n",
"\n",
"%matplotlib inline\n",
"%config InlineBackend.figure_format = 'retina'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In order to run the below code block, you will need your own API key. The stocks selected for this post is Apple, Amazon, Google, Facebook. Below code block will get daily adjusted closing price of each stock from 01/01/2016 to 31/12/2017."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>ticker</th>\n",
" <th>adj_close</th>\n",
" </tr>\n",
" <tr>\n",
" <th>None</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2016-01-04</td>\n",
" <td>AAPL</td>\n",
" <td>101.783763</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2016-01-05</td>\n",
" <td>AAPL</td>\n",
" <td>99.233131</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2016-01-06</td>\n",
" <td>AAPL</td>\n",
" <td>97.291172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2016-01-07</td>\n",
" <td>AAPL</td>\n",
" <td>93.185040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2016-01-08</td>\n",
" <td>AAPL</td>\n",
" <td>93.677776</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date ticker adj_close\n",
"None \n",
"0 2016-01-04 AAPL 101.783763\n",
"1 2016-01-05 AAPL 99.233131\n",
"2 2016-01-06 AAPL 97.291172\n",
"3 2016-01-07 AAPL 93.185040\n",
"4 2016-01-08 AAPL 93.677776"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"quandl.ApiConfig.api_key = 'your_api_key_here'\n",
"stocks = ['AAPL','AMZN','GOOGL','FB']\n",
"data = quandl.get_table('WIKI/PRICES', ticker = stocks,\n",
" qopts = { 'columns': ['date', 'ticker', 'adj_close'] },\n",
" date = { 'gte': '2016-1-1', 'lte': '2017-12-31' }, paginate=True)\n",
"data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By looking at the info() of data, it seems like the \"date\" column is already in datetime format."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 2006 entries, 0 to 2005\n",
"Data columns (total 3 columns):\n",
"date 2006 non-null datetime64[ns]\n",
"ticker 2006 non-null object\n",
"adj_close 2006 non-null float64\n",
"dtypes: datetime64[ns](1), float64(1), object(1)\n",
"memory usage: 47.1+ KB\n"
]
}
],
"source": [
"data.info()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ticker</th>\n",
" <th>adj_close</th>\n",
" </tr>\n",
" <tr>\n",
" <th>date</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2016-01-04</th>\n",
" <td>AAPL</td>\n",
" <td>101.783763</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-05</th>\n",
" <td>AAPL</td>\n",
" <td>99.233131</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-06</th>\n",
" <td>AAPL</td>\n",
" <td>97.291172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-07</th>\n",
" <td>AAPL</td>\n",
" <td>93.185040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-08</th>\n",
" <td>AAPL</td>\n",
" <td>93.677776</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" ticker adj_close\n",
"date \n",
"2016-01-04 AAPL 101.783763\n",
"2016-01-05 AAPL 99.233131\n",
"2016-01-06 AAPL 97.291172\n",
"2016-01-07 AAPL 93.185040\n",
"2016-01-08 AAPL 93.677776"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = data.set_index('date')\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>AAPL</th>\n",
" <th>AMZN</th>\n",
" <th>FB</th>\n",
" <th>GOOGL</th>\n",
" </tr>\n",
" <tr>\n",
" <th>date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2016-01-04</th>\n",
" <td>101.783763</td>\n",
" <td>636.99</td>\n",
" <td>102.22</td>\n",
" <td>759.44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-05</th>\n",
" <td>99.233131</td>\n",
" <td>633.79</td>\n",
" <td>102.73</td>\n",
" <td>761.53</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-06</th>\n",
" <td>97.291172</td>\n",
" <td>632.65</td>\n",
" <td>102.97</td>\n",
" <td>759.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-07</th>\n",
" <td>93.185040</td>\n",
" <td>607.94</td>\n",
" <td>97.92</td>\n",
" <td>741.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016-01-08</th>\n",
" <td>93.677776</td>\n",
" <td>607.05</td>\n",
" <td>97.33</td>\n",
" <td>730.91</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" AAPL AMZN FB GOOGL\n",
"date \n",
"2016-01-04 101.783763 636.99 102.22 759.44\n",
"2016-01-05 99.233131 633.79 102.73 761.53\n",
"2016-01-06 97.291172 632.65 102.97 759.33\n",
"2016-01-07 93.185040 607.94 97.92 741.00\n",
"2016-01-08 93.677776 607.05 97.33 730.91"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"table = df.pivot(columns='ticker')\n",
"# By specifying col[1] in below list comprehension\n",
"# You can select the stock names under multi-level column\n",
"table.columns = [col[1] for col in table.columns]\n",
"table.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's first look at how the price of each stock has evolved within give time frame."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x1144be510>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
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RLCu2+Epjbf8d1rLwrFuJuW09yrFRp04mDRtH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\nbjBv0GTOoEnwsqRtz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Cwy0jKH/0wPZJKdkUdxXjke0/0OvVtR32A3H+x+mbbu5Pah+89s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\nIQeoSZpTT0+Gjuxr2L30ynS2bs7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AfB8GgptiGut+qYwIkVk4TyvN\nlBECrdBbWXjmZcG0uWEVsJIQn/4jTOUIwbYfITrxezegJfHGqewQuus2lF9A+UXw8yg/n14Oyksq\nRCntwx/6MGINSAw6gzTOYqZfwMy8hMSVDa1blOYHmQ/z9VerfHustelgUysYzXvsLHnsKvrs6pzv\nLHoUVgjeRIRqvHCy1GKhGllenY758pnWimHfZvRkNP/0nhKPDoUotXRntiLMR8JcZJlrWyqR5e25\nhP90LG2D+wO7nx9E+5c85vdan+E/NmM+kD/Dfd7r3OG9g8/Kgeq4HeQPop/gnIyuePtmPDwY8qO7\nctzdG9CdWfq6fngkQz22TLYsjUTQCrYXPIqd1z+2wqvTMd+90Oap8TbTrbT6VNA0ydGU3Krr7c1o\nfnLP+tuFO1vHhaiO4ziO4ziO4ziO4ziO4zjvU2JaJBf/BjP9/aVtam9mygMdwC3Y2tUK1OI0ZIlt\nGqzElwVWR+OdGDy6201KqkbZaxJoCLUi0IpQQ+ApfAWeUnjFXeiee9Mg7/IWwcpDF3aiS/vTU3Ev\nyssiNoGkBkAy+T2S8SfBLq96XJMO8brvwtZOINHsVe9u516jPffaxtaxEcrH670PFZTSNs7aB+Wj\nlAdYbO0ktnYKsOjSQXRpP8ovpA/NDaOyw8sCvquuUntAOptSFXaiCzvxd/w4tnosDVRnXwGzfKbn\ngsQKs23L77U/zbfGPGD1+64l1IpffajMPX0B4QZavSql6AoVXSGLzwPgo9uy/NzBPP/7y1Wen4w2\ntU0LthU8/vUj3WwrrDzDUytFd0alYWQpve7xUfjbu3L846dnmWyt3Oo5JuBVcwevmjvI0OYu7wgf\n8F7ngHcSQfMDs5dnk/s4Yg9g15gRu8DXcFdvQFegaSTCZMuS8WBn0accKqzAQM7j4cGQvV1rR2qF\nQK8YWgMEWvHAQMgDAyH/6K4iR+YSvnuhzXcvtDlXX/sbF//FwQJZ37XyfTe4ENVxHMdxHMdxHMdx\nHMdxHOd9yDbGiI7+1rqCsM3Qxb2Et/8jQNIga+4NzNxrGw5rVaYXXdiDLu5FF3ejcttQ2kOSBhLN\nkEw81ZlLuo5lhd2Ywn5eqQ9yfD5mr32THeosOV9R9DUbzNLWJKRhWWSEyELbpJV/VpZW+SX4fDt5\nlG/EH2a+nd6WyWQB0BhKqk6JGiVVo0vVKKk6Dclywu5kZmKYnSWP/V0P8fjIj/FAfgwdFNCFnSgd\nMtMyvDAZ89qpmHrcZjDncbA7y129AYPbPoU//DHs/FHQHio7hNIh0p7EtiaQzsm2JpG4is704o/8\nMF5P2u5URJDWOLZ+BjP5NLZ28ppeLxWUUflRJKog7el1hbte7wcIdv8Myste07rXYiUNvEPNmmGr\nUhqv6yBe10Fk909DUgelwctha8ex8+8gcY2WhS+e9HiqcYDzMnJN2/Yr9xR5cDC8pmVcqS/r8a8f\nKfP1c23+7RvVZdWx+8s+rUSIrJDYtM2wEUnPLeQDxSODIb94uLisWnM9thU8fuOD3fyLl+b5wVxa\nZbqn5POP7y4yef4MF1oKv7efiabhYjPkYuN+/rB5L/VmGkTKOoLTnK94dCjkseEMDw+Gqwaf14tW\nisM9AYd7An7hUIHTNcMzF6PFGbhaQaDhaCVhLrL86K7rt387a3MhquM4juM4juM4juM4juM4znuE\n2AhpzyBxBWmMYRtnkfZMOpRQeZ2TjzTHkPbU9dsQv0C47++jVBpOeKX9eKX9BDt+HNu8iDTPI2LR\nmX5QKg3tGuexzTEwLVTYje46hFc+tLSd6mWm4gxfOlHm+cm/xa5mgc9lvspgFrrCS4GICrrQpQO0\n8vs5avbwYqWLvzrWZj5aqHJ7mI/5T/Pp4Ov42jKc9yhcpeIrtsJspJiQQabpY8icoqxrhFohpK15\nI5ueyxqtcxM8nk8+wFeTj1CRrs61S6trLR4V6aJC18pdeEU4Vkk4Vkn46lnYX97BZ3bnOHsm4oXJ\nGifmV58deXu3z0e3ZXli22GOzCW8fDZiqmXpzQwwkBtmKKcZ7PUYzGn6Mhrvit7CSilUbgSdG8Hr\newgz/X3i038MdgMVjMrD63sQf/jj6NzwZU9L0pbI7WnENFF+CTF1zNT3sfWzoDz8ocfx+h7acBXp\n1cy2LS9ORrw4FXGsknC6aoisUAoUB7sD7u0L+Mzu3JL9bNnTUhqC0uJlr3QAr3QAgF9/eZ6v1q+t\niroYKH7l7hIf23Z9wjWlFD+8I8uHhkOem4iYblnu6w/ZV74xkdL2os+/+6EeTlUNVoR9XT5KKY7O\nCLtywoH9y1vbNpK0LXEjEcYbhuPzCZVI6A4VQ3kPX0Ei0J/VHOreWOXu9aSUYnfJZ3dp5dfWWFn2\n3nNuHBeiOo7jOI7jOI7jOI7jOI7j3OLExsRn/hQz9SzI6sHZDaF8wr0/v2r4qXNDkBtael1hF/Q9\nuLHVKPjPJ9I2qKd5mGNmF4fb7/ATu0N6yqO82Rrixfku3jqTBmGpK9umKp5MHuOsHeVvBd/hfLVK\nOV9mtGcQHeTxdIj2fDwvg+8FvD4HXzqT4Ui8g2Tx8Lowqi7ygP8qD3svU1CNJWtoE1KXAtXOaVwG\nOWl2csLupMnqcxA341gl4QuvVtd13yNzCUfmavy7N2tXva9W6ckIDGQ1n92T5/P7cuhOgKmUwu9/\nBF3YQ3Ti/0Ea5666TK/vQYI9P9tpu7uUUgr8wmLb3cXHdILIrRRb4c2ZmOcmIl6YjHinsvL7pxpL\nGq5ORnz5TIvf/FA3g7mVW9Wu5pWpiK+eXV+AGuo0yHxgIOTr51qcqSXsLPo8PpLhsZGQvH/9qyeL\ngb5uQe3VaKWu2j73cnlfk+/cfXfJ55GhzHXashvLBajvLheiOo7jOI7jOI7jOI7jOI7j3MLExkTH\nfhtbeev6r8zLorODqMwAeJm0UrA1mbaDDcqo3Ah+/6Powo51L3I+sjx5vs1Uy3Bbd8CjQyFagWLt\n9qn9WY+9Xf5iteWYDDOWDPPNY5ffa33zPo/avRxt700vtICZdW8+oBiTYf4iHuav4ifoVzPkVJuq\nFKhJgYitbbf6brCSngAmmpb/+60az09E/K/3d9FzWctWnRsic+hXSM79BcnFb6+6PH/44/jbP7Pl\nVaSQVrG2DbSM0DRC26TViWdraXViywj9WU1i4Wgl5pXpmGayesXwSi40DD/1jWl+8XCRQnDpOVze\nqbkSWV6ZjjldTVBAOaM5tkpAu0AreGAg5OPbsjw2fKnN7OOj741A0HFuNS5EdRzHcRzHcRzHcRzH\ncZxbSCWy/Id36nxnrE09EfK+IuspclecZ31F3lMcKPt8eDRD6QbPfFvJXAx/fLxBNRYGc5rtBY9t\nBY/+rF4SplgRTswnvDmb0Iha7JLjDHjz7Bq+jbC47YZvt22cx0w9g0RzEJTRmX5UdgCV6Udl+lA6\nuOHbtECSOtGJ38NW3t6S5ancCF75MCrsSVv/2hi8LCo7iM4Ogl/c0uBrrm35padmOVc3y277wyf6\nGMmvXen3wEC4ZsvaG83iMSEDK7feXcNI3mNH0aNWadC0UPc1E0179Qe+i16aivivvj3DP7u/i3v7\nLwXFSgcEO38SXT5EfPKLSDy/cAu6+w4Y+CjN/H6yFkIvDT2rsRBbIdCKUCtCj8Uq18QKp6oJc53W\nrKMFjz872VycIRl0ZpW2jNBKhJbZ4It/DX7rratX8S6YbK3++zxY9vnRXTkeH8lsao6o4zjXhwtR\nHcdxHMdxHMdxHMdxHOc6kKSOxPNIUkN5OVR2BKU31vpxumWoxkJvRhNoxTfOtfidI3Uq0aWD8Y11\nVFD90YkGX3i0m/7spfW3EmG6bZluGWbalulWepqNLCKQ9xWlQDOU1xQDzVjdMN22ZD3oCjQLnSRF\n0rxIOj8jgiBoJWwrhtzdm86e+8txzfGZk9yb+RbDagKAcwjnAF9BzleEnmKeLt5sjTKZFBjRF7nf\ne528alAHjpxS5HZ+lgMHP7Gh13EtYk06HzSporx0zl4y8V1M5c30CZnGssdcGfepsDetwBz8IXRp\nH2b6BSSaQ3cdQJcObmnoKGKR1kVs/SzSOEMy9RyYK1vUboLSBDs/hz/42Ca2SZhoWsYahoKfBvfr\nfc7/11u1FQNUgNen46uGqDuLG3tP3QyUgkcGQz6xPcuOosdowVtszXr06CQABw700zbChYbhfN0w\nVk/Pz9cN5+qGamxpJLJYHfpumWlbfuWZOX7+tgKf35cnc9mcSa98GH33/4atvE1k4cm5IZ6cCHnl\nSISRKQINvRlNZNM5pFfyFISeIrZCcnPnydekN6P59Q92U7wJvujiOM5SLkR1HMdxHMdxHMdxHMdx\nnGskSRPbOIOtn0bqp7H1M2nV4uV0Bt11AK/rELp8OyozsCxosjbhrckKz12Y5bXpmDfqXSRce5Xj\n6arh556c4fGRDMfmEy420nB2vbpVhQ95z7PXO0OOJlkVoTF4WDwMWlk8LLpzecGMdPMHZi9VChzm\nLT6Sm1qsLlvGpKcc5xnSb7NSB1QrQvPMnzFZ3sbA0B0bfBXSsE/aU5f9nk5j62eveYaoRDNINENU\neXPpDRe+hi7uxR/+GCo7hAq7Ud7G5guKjTGzr2JrJ5HGWWzjXFodupX8EuHen8MrH7rqXZuJcLKa\ncHw+4cR8en58PqF+2f50uCfgfkV8zQAAIABJREFUf7mvi9HC2gHn2VrCN8+tPh/y9ZmYT+xY+/W6\nWsi6lr1dPnlf8fZszPUqXsz5ip1Fj51Ff/H8zl6fvuzVtzvjKXaXfHaXVj6MvxBe//GJBn96srlq\noLqt4HFff0hvRjMfW753MeJiY+XgejOswO8eqfPHxxt8cDjDaN5jJO8xlNeM5j3Om9v4Vy/Pdypr\no8XHxRYurlFta4QNt9m9Ff3yXUUXoDrOTcqFqI7jOI7jOI7jOI7jOI6zCbYxRjLxHWz1GNK6uI4H\ntLFzb2Dn3kgv+wV0dhjE0GrXmG3M02g1SKxwH3AfIDnFrHQzL0WakqVJlpZkyKiIAg18ZbAorGgM\nGkFhO/FmVQrMSZnTdjsn7E6aiearZ1cPrFaSpcUTwXf5iP8MPhsPGnvVHA/7L6VPX7YmDLEijB/5\nffrK/wSV6UWpNIwSEcz08yQXn0Tas6igmLbaDXtROsC2p7C1k5DUt2Q71r29tRNEx04sXlb5bXil\n/ejiPnRpPyoopdtvI2z1BHb+CLZ5IZ0vGpYxk88gcWVT6/Z67kblt6PzO0Bn0rBYDNgEEQNiEC/L\nhLeX1+Y8Xjo+z0zbUgoU+8s+g1kPpWCsbhbD0rGG4Wq/yrdmY/7b78zwy3eV+Pi2zKrB+e8fbaxZ\nSfnGzNXD4vsHQvaUfE5Wr75/juQ97ugNuLMn4N7+YDGcPDmf8D89V9lwsNif1Xx+X55tBY+jlYTx\npiHnqUuBacmjL6Ovy9xPSFvYDuU9funOEh8ZzfLv367x2kxMKdDc2xfwwEDIg4PhsqD5l+8U3p5L\n+OrZFt8811qsZt9V8rinL6Q/q5luWSaaholmer6eL11UY+FrG/yMuVkN5T0eGgh5YCDkUI9Pd6j5\nly/N850L65uxu14fHc3w+Iibd+o4NyslW/SPF2drVSqVVX8xR48eBeDAgQM3bHsc51bh3h+Oc3Xu\nfeI46+PeK46zOvf+cJzl3Pvi/UXEklz4Gsn5r7DhwYdLlgO12FKJhXp8fXtVHrN7+PftnyHBo1fN\n0aMq5FUzrSLlUhVpWlGaBkk79BiH9VHyagtaxXIpRF21EnWDdhR98r5GhWXwckjzwpYs90ZT2UFU\n0IWtnbrmitgFurSf8MA/oGp8nhpvL1aKNhKhadLzViLUE2G6Zbieu1851IzkNaVAUwgUxUBT8BXv\nVGJenrp6SPoXn+ynK1y7Si8ywi9+d3bZbNSsp/jhHVkeGAi5szegZ41Zk43E8s1zbU7MJ0y2LHOR\nJTJCbCGyQmyEWNJ1FQPFR0ez/L3b8otteLfKtf49EZENhbZtk84fLgSKHQVv1cdGRhDg99+p88Vj\njasG6beanK+4ty/gocE0ON2+wmshInzhtRp/dfraPxOH8x6f2pnlp/flCb3rE7K/F7l/bzlboVwu\nr/tN5ypRHcdxHMdxHMdxHMdxHGcVIoK0xpHmBcRGSHsaM/Mi0ppc5+PTAEaAQIPXOShfiSyTTYu5\nQUnEfn2S/yP3q9QlT0Etn/F5KzpXMxQCS1c8Q8HX6MsOiQpwq8QS0ppAWhNbtjyv935OdP8kX3yp\nyTMX2+/6LMlKZJfM8N2IjKc4UzPc2bt2UBl6ii882s0/f6HCq9MxoVY8NhLyi4eLDObW1+4372s+\nvTu3qe28mWy06jXjKQ71XL1l+ELQ918fKnJ3X8CvvlTd9O/1Rgi1IuOl4WjWU2R9RTnQ7Cp5FAPN\nVMvSMsJQTvPgQMgdvQGBXvu1U0rxT+4u8oH+gGcuRjQSS97XhHrp583C70ABI3nN4Z4AXyvO1hIC\nrTjY7a8ZWDuOc/NwIarjOI7jOI7jOI7jOI7jkAamxBVs8wLSHMc2x7DzP0Ci2Q0tJzJphV+jc7q8\nja1Wasva2mY8RX9Wk/EUVtLg0Epa8SkCM+00JLjczRSgZj2FAJHtvPZXUEDWV6vORBSEWizUYtDK\nslCsmAgkVsh6inKo6QrVqtWvIlBLLPOREFkh1Iqcr/DUpco7rRRGhPkk5JjdTUUPUFZ1+vUMPUxT\noI5WaWhTDBRaQT0WIgt5X5H3r19QYgWMCImF+exBjhU+wdcnh3nuza2pHn433NMX8Nk9OYZyHgfK\nPv5Vgq0FPRnNb36oh1ps0YotrxB1LnloMMNvP+7zL1+a59XprZnPqxR0h5rYXqr+vfxjoRgoAq2o\nRHaxBfTBss/n9+c53BNgBXJe+rmY81d/z1/7dio+vi3Lx7dtbLYxwJ291z7f2nGcG8uFqI7jOI7j\nOI7jOI7jOM6GGCvMRZbYQiFQFNZxwHq8YXhpKqISCT0Zxe3dATsKHt46A5KtJHEVM/0CtnEOsIBG\n2pPY5jiYpeGTCLSMkIjgqbSi6cpNNpKGpQvtUuPOEX4hnWca49Or5giIrzlAVUAxSIPBQqBXqbZM\nrw09xelqsmbDYV8rfAVe53zhMioN6JJOoGElraQNdBp8rlZBu7A9Qho8NhMh6bweHhBqoZzP07ft\ngwR994PyEYG5yDLesFRaLcrJGQbkAiVf8MISsd/Nt95+hZ1yfNXnYUVoXTHOsmWEVtMw0UzD2IKv\nKYcKXyvaRqhEaXhqRGiRYc6WyaoW3fE8VSnynLmX18whskSAcNLuJCJctu5+Nc1/Gf4nRvVFJq7I\nLqc7v4dSoPFU+vpolQZGWin0wmXS8NeIYGy6VwYaCr4isVBLhMgIpnOfhg05bUY4ZUY4Z0c5aXcw\nLb2dtUZr/MZvbr6G//m+rnVXj66kGLjw9EYYyHn8nx/s5rmJiD852eS5ifXtd12h5pfuKPLRbRmO\nzydMNi0ZDw71BJQu+92JpPt7ZAUr6XtBKUUttpyqGgq+YnfJVXM6jnN9uRDVcRzHcRzHcRzHcRzH\nuarICP/xyCRjF15lIDnObn2WPE0a5KhJgZYqkugCoPBI8NTCrM0EsYaG0UxLL1O2F5TwDIaKdFH1\nt6Ey/fRkPUqBwlNpFaDXCfQ8lYZQ+7p8PjQcbqi6TGySVpEqhQq6kcYZkslnMNMvgCRpxSagUSSS\nhoULVVDpeRrMXVkl6V1x0H4hUJyRbs7YbZyx2zhtt3POjtAmA4BPwh59htu9Y9ymTzCqx9Gs3Aqz\nITnwi4zmEvp0FV+ngaRIuu71ZgYZTzGU9xhvLE0Xu0JNb0YTemrDLW919134/Y+ickMoHYDyAJ2e\nKw+UBqVRSiNJHVP5Aa36eZRY5mZmMF4vI4efQPmFJcvtA/oWMkAOL7ktBHLJw5w88m/Yo89ucIvT\nCt1mIjQTw1QLEjzO22HO2O2ctts5bbcxJb0I6b6lsAidJHkdpqSPX2//Aj8WfIvH/OfQWF43t/Pd\n5GFu845z0J4gjCMKqkmXqm54+xfUJc+3ksd43dy+ZHvfDYM5zd4un32d096utD3py9Mx/+LF+U23\nef25A4VrClCdG0spxcNDGR4eyjDVMhyZSxhvGC40DOMNy3jDMNYwi9XkHx7J8A/vLDLQ+R3f3h1w\ne/fqy174YsflioG+antnx3GcreJCVMdxHMdxHMdxHMdxnFuE2ARQKO11LhtIqkhcwcZ1lPZROkzL\n3EQw1jLTTphsGiabCaiAwd5tHO4rcqZmOF5p00gMozmPUT1BKTlNYGqIkFa8kVYgVqOEl86e5k5z\nlHtJ0pLCjgINBtR0ZwMv39grNn6NXCSJfWajMm3J4JHgK4OHwSc9VwgT0s+/feM2ksJBdFBCBUX2\nlPPsKipsNINtTUJrEi+eJIinyMST5OwsVtKoKfTSdquBTtvDVmJLZDZXFXplFeZxu5s/jn6UcRla\n/Tnic9Tu5ajdy18CHgkDaoYeVaFNQF0KKL/AY9u6+eSuAvvLadtHSRpINIeYJpgmkjTAtEAHqKAE\nOgCx6QsuFsSACJLUiE9/iXKoCXRavQVpgJr1Nl65pQu78Xd8Fq+0d92PUX4Bv+8+in33ATAWHV28\nfqOe2FniN2Z+gVcuPM1BfZIeVaFbVcir5W1rE3y+kzzMq+YwZVWlT81SVHUakuOk3cEZu51kjcOi\nmwknEwL+3/iT/Hn8CTQW01n+MbuH/++yJfeqOfbqM+zTp9jvnbr03ulokuW02U6oYnrVLN1qHovm\nVXOYP41+hCqlDW/behQDxfaCx+GegG0Fj8jCuVpC26aV58VAs6fksbcTmHaFK79GDwyEfPHjvXzl\nTIvvXWzz6nS82Hp1LbtLPp/bm+NHdm68Rapzc+jPejw2vPyDXiRtbx5oRWYTnz2O4zjvJheiOo7j\nOI7jOI7jOI7jXINjlZi/mfbIe0J30zAXWd6ZS2gaIeOl7V8XT74i1OkMyFYi5H3F9qJHly9IPIu0\nJrDNcaLmDJLUkaQOSQ2SOpgamDZKgfJyVGKot+q0jSzOwfS1IuxU7SSdSsqF/KKnc94+rfmeZGkT\n0q3m6e1UQ453TqvZeb1eQNIqzQE1vWbh3251lt2chdY3oZVel8x4aGTFis4EWFLztzVj+5aYkR6e\nTD7I08mDGw7eDD7jMsi4DLK3y+e/O5jn0aEM4RUhg/LzKD+/qe3ThV203/4Ced+Q968IN5SHLt/R\nqSZdWkmqlE4DettGBV3oroPorkPvattMpRT/w739vLT9U3z1bIs/GG/TTIQMbcpqnh41T7eqYPA4\nYvZRo/iubKegMavuC4oZ6WHG9PCCuQdiKFFlt3cOn4QZ6eas3Ya97PE5mmgsdTYePC8uw1f80EiG\nO3oCuoJ0XmSuM6s15ylKoaYrUFv2+y0Gms/ty/O5fXmaiXCxaajFQj221JJ0jm01tjRioSejeXAw\nZHfJHaZ+r1IqnRXsOI5zK3J/nRzHcRzHcRzHcRzHcTZAJA3sIqv4N69OUh3/HqP2LOOS4zcmRrBo\nymqejIoWKyl9DF6nutLDkOBj0XSpKhfVLH26QqAEFMQGZM0plnBFPLgosZfmT65GYymoBgUam3n6\nNxUfc/U7bQFBccaOMin9JOIxIz28ZQ5wTkZYT8vXUCt6s5qJpllSlecp+Py+PD9/W2FZeLoVdGEH\nwa7PE5/6Qy4vDfa3fxp/+IlbbpagUor7B0LuHwhpG+HZi22+db7NsxezTNiBd3vzNqVKidfNoVVv\nb5Lb9LK1gs/uyfH3DhZWrRy93nK+cgGp4ziOc8tyf8Ecx3Ecx3Ecx3Ecx3nPEhGaRqhEQiWyVNr2\n0s+dy+Xm6+xtP0OGBkkwAPmdWB0gJsYzVXxTJbBVAlsjY6uEto4RRTMxPAEQpFWgAHqToZQIRJvr\nLOtssQSPi3YgrRK1A1ywQ5yy2zdc2Xig7HP/QMiDAyF39QaEniKxwnjDcL5uiCzc3u0vzga8XvyB\nR1HZIezc64DF638UnRu+ruu8ETKe4vHRLI+PZqnHlqfHI56bjGgb4a7egO5Q88zFNi9MRlTjq3yx\nQMEH+kN6MppqZDk+n1AKNHf2BgzkNJERPKXY0+Wxp+QjQD1OP1vqsTDdMvzNhbR17Y2mFXSHmp5M\neurunI/mNR8cyjCUd/NFHcdxHGezXIjqOI7jOI7jOM57npgWKB+l3X+BHOdGELEotbGqJ4mrJBNP\nIa0LgErbi6IX24uivHSZl10GxemacKoG43GOs+0SPjG93jyxsVyM8kzEGYy1qE7LV09d+rmo6jzi\nvcQ2fVkT23gMGq+uup1R5+SkfK0WWwmvR9CZSSoIbbP+x10PCR6vmcOctttpS0iDHBfsINPSu6Sd\nKqTVdEOhTtuRrhLI9Wc1DwyEPDgYcl8nkLuSrxXbiz7bizf275FX2ruhWaa3mkKg+cSOLJ/YsXSe\n5id2ZLEi/GAu4XeO1Hlhcum7dyTv8amdWT65I3vNYfZP7M3zylTEd8fb1GPh0aGQ27sD/vPJJifm\nE3KeWtwnmonQMDY975wSC12hojvUlALNRMtwZDYh6pQul0PNE9syHOoJ6M1oerOa7lDTFapNf3nD\ncRzHcZy1uSMIjuM4juM4juO8J9j2DLZ6FIlmkWgOiWY657Ng0uF5KjeKVz6E7r4bXdxzy7UxdJwb\nxbYmMdPPI80xxCbo3BAqO4zK9KKCblTYg/LCJY8R0yI+++eYqWcB8PoeINj+aVRQWno/sRBXkbiC\nxPMgBjP/Dmbq+2Dba26XCCQixBbaJq0mbRuhH+gH7lzpQcHmXwdnZQk+pnwv9+1/EC8/AjYhieZp\ntmq0o1o6G1R7KOWB8hdD7yxNcskEElfT68WQNM6TNC6QJBGJCCKXms4u5KtG6FT8LZ97uh41KSAo\nSqqGRTNmh3ne3MOLyd3UOnMmlYKCrxgpehzKewznPUbyunPusaPg4WmFFWG6ZTGSVkICtIwQaujN\naPd35SakleJQT8CvPVLm1emYp8bbZD3FAwMhd/cFWxpA3tsfcm//0s/G//6Ozc9mnY8sb8/GZDzF\n4Z7gurR8dhzHcRxndS5EdRzHcRzHcZxrJFEFM/MCtnYa/Dy6sAtd2ofODt64bRADNk5Pfj49cH0T\nEZsgcSWtIgvKG65QW3mZBpJqWr124WuY2dUrxxYf0xwjaY7B+LdQmX68vofwyrdhKm9j599Bklqn\nYjVID/BrP73sZVD5Hfj9D6GCrmvedse5WdnaKeJzf4GtHl16feXN5Xf2C6gwDVRBY+deW3KzmXoW\nM/UsurATgi6I55GoE5yuMO/TiBCZNJCqJ0Js0vmgnkrDtNim93m/ExTqitevLnnmpUiVIh6WgBiF\nsFBz62tF1vfIqjbFZBzkUhipUIRe+lPNZjllRjhlt2Hw8ABPg6cUnkrDKJ3t54F99/DwSO+SbQjz\noyyNjtYnJG25jGkg0RxI0gle08/gNIj1kPY0c1NvUJk5jkpqBFLHxHWiJMaKEOk8DW+AttdHFAxg\nMgMQDqCzA4Rhntm25fX5BidqitM1Sw3h8EDA5/fleHAg3fL1BKBaqevefte5PpRSK4acN7OuUPPw\nUObd3gzHcRzHed9yIarjOI7jOI7jbJCYFrZ2Cls7ga0dx84f5fJAwEw+DYDXcy/Brp9aUoUlIpDU\nkKTWqeRa2nZOxCCtCWxjDIlm04PHeuFgcoDqnKPTCh5bP42ZeQVpjl1aiJfFH/ww/sgnUN7KB97E\nxtj6GaR1EWnPoPwcurQfld+5eBBZbAw2SlvhmjbYNmIjlA5R2SGUn0dMBKaOJJ1TXIOk3qkCnU1P\n7Rkkrly2fXm8nrvRuVEAVKYP3XVw2Wux4naLYKvvkFz8NrZyJD3YvknSniIZ+zLJ2JeX37bSA2Ze\nIjn/V3g99+KPfvI9MU/OufWIyJZVuolI+l5tjCHtSUzlLez8D9a/gIX3feP8mnez9TMrP9wKkYVq\npz1qYt87AalWiqyXhpMiYOmcC1jSakulQAOJZbFdZ13yTEsPE9LPtAxQ1yWakqdBjiZFmuRoqRyR\nEVRSp+BbdnV388ldRR7tDwk9ODGfztv0NYzmPbYVPLrCS19cMXGN46dfoFI5Sz7fy/7tdxMWty/u\nVw+IIGx+tutmKKXSUN4vrH6foERvcTe9uy9dJyKL1cvr+RsCuWvbUMdxHMdxHOd9xYWojuM4juM4\njrOGhZDB1k5gqyew9ZNIY4xVYrYlzOwrmNlX8PofgYVwtDUBprl4H13YicoOAWCbY0hzHMRc20ab\nFsmFr5Nc+Aa6fDvKL6H8PHi5tJqneQFTeXOxxe0SSoPOpgelr7Ydyt9ciGkaaYXa5dfpAJ3bBn7n\nALcK0vmlOlj8WZI6tnociWY2vs6tIgYz8yJm9hX8bZ/CH/74TVf167z3SFInufhtzMzLSOvipS9V\n6LDzpYowrZ5e8nO45GcV9qD8IpJU0y9pNM9jmxdW/hy4lm0FIiMYAd2pII2sENu0BW9i0/A0lk4A\n9h6hlaIQZOjKDdLTNwh4qEwP+MXOl186X4bpVFUq5SGSgI1RXg7J9FFVvczEGfpF+KGcR3eo1gzM\nrQiK5dWTd/Zq7uxdvYexFxQ5uP8jq96ulOJWaRiqlIJ1haeO4ziO4ziOs3EuRHUcx3Ecx3HWRUTS\nwEwEsFecy6WD91vQpnWrpfP3KtjWBNI52U4FJtpH50ZRmT4kaaQBp1i65ibRtk771Sid3XYNFuYD\nrsTWz8AqVVrXTrCVtzf4EAumsc77br4KdBkbY+untm5515sYknN/ia0cITz4D9KgynG2iIhg59/G\nzL2BNC9gayeXfqlBEjAJctkXMm6GODKxwvm6oWVuhq1ZSgGeTlvSekp1WtRealPrqfT2VjjKGX2I\nJK6i0GjtYbwC1i8hfgnxu1B+FzoskJEGxdYJclJloG8vF6cs80oxtP/Apraxp3NarxtZKeo4juM4\njuM470cuRHUcx3Ecx3mPWjgIn0x8F2mcQ4V96PLt6OwQIJ1WrelJJEYpD5XfnrZ07VTW2eZFzMyL\naRVm/fT6KpZ0Jm2pp0OuLGVRXgGCLlRQQgVdnVMJFZRRueG0yq9yBGlPpS1jO7P2VNgD2u+0lW2l\nwcHiebNzfYQKutClvaiwB2lPYSpHsJU3sY1z6XNdhVmhFWXYSp+raFfh4qzOVo8Sn/kTwt0/veb9\nxLSwlbcQMenM3Bs4L9e5+UjSRNqT2NYk0p5C2pNIaxIxDUAjzQvcHLHoxow37ZYEqFUp8py5lwt2\nCA+DxqKxeMpe+rlzvYdFK0tvYLi3q8FQUEXrgJYuo5VHQdXJqQjf89JKe+UBKv3Cj9JAeq78Il7f\ng+jCDrave0tLwNDipYvTR1e/q+M4juM4juM4txwXojqO4ziO47wHmcpbxOf+EmmcW7xOojls7fjV\nH+wX0YVdSOtCWqm5UbaNdOaTXUmY3PjyHGcjlEaX78Ar7e+E8L2osBuCLqQ9jZ17g2T6eaRxdstW\naSa/hx15Ap3pX3ab2AQz+RTx+a8sqfBV2QG8vgfxhz66zjl+zq1OkgbJ+LcwU99fOiP4Zubl8Xo/\ngAp7wTTS+antWSSeQ6IKlwe9zUSox3bdi25KjoqUqEiJBI+caiMo3jIH+JvkERJWr+7uyWgGc5qB\nrMdgTnNPX8iHhkN87SozHcdxHMdxHMfZOi5EdRzHcZwNkqTRmUPmWjc614fYBFt5CzP9PKZ6FNB4\n5dvRxd3prMqkdqkCM1mowmwutnW8PDjdlKSGrbx5zc/jfcfLo4u70nbB7el3e2veX7wsys+jSwfx\nh59A54ZWvJvKDqCHP4o//FFs8wJm6vuYmReRaA50gNd7P1733WnoKjFiTXqe1LHz72BmXlylolmI\nj/8e/vDHsO3pTmXhFNL5eSXSmiQ5/2XM1PcJ9vxdvNL+LXxBwNZOkEw8hW2cBTEov5hWdedG0blh\n8PMor9CZlbtCiNtp0y1JLd2fxaKLu1F+YUu3cyNEJP38s2nV+a30d9g2zhEd++1b6LNBofofxYz8\nWNrKVsB2ZpzmfEWgFWINEleQaA5pT/K1I8eomikakuNvkocZl0EO6aN0q3liAiICqlJkTrqYlyIx\n4fK1KhjNe9zX63F7d8CdvT5doaYWC4GGwZxHf1YTuLDUcRzHcRzHcZwbwIWojuM4jtMh0Rxm/h0k\nmgXlobQPyu+0fQNpT2LmXkea44BC5UdROkSiWcS0UWEZFfZ1Wo92XzoF3eltW1xptLi98XzaelX7\n6UxK1Ql4OyfVuW7hZ2WbgEoPeopZ9UD04vxLpRdbuzrXj9gIWzuNmXkJM/PSspmUZvp5zPTz79LW\nOStRYTe6uLdz2oPKb1t8ryTjTxKf/bPNL9zLofPbUNlhlPbT1suSpK2XbQKy0Io5SWe6FnambSjz\n29Mq5LN/jjTH1vEkNLrrNpSXQ9pT6XzWpXdIA0ov02nTnAEddkKTqUv38YuooJC2a/bTYO5SK+be\nxZbMyksfa2ZewjYvAJdVSK/RbnklurATr/9hvL6H0+3aIJ0bQe/4cfztn4GkBl4epdf4rOt7EDv6\nSdpv/Rok9WU32/opouO/u+HtkPY00ZHfxOt7AH/0R66pza+Ixc6+SjL+5LL5smkV+EngpU0vHx0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Gxu95fkxSxzpb66yKUpTkQuTXEiMj3Fh8yHzs7OljsrGokqskSE/V+k/uI/zHk7rnqa6nN/\nSG7Pu5fEHG+uPkY88WJS1tbPgZfHMiUs03nBaMfw9FeoH/4H2stJMigMp5zQMx+vYzd+981Jwinb\n29KJnWh4H/Wj/z9u4ti8Pq6FFLlk1FDsOHeidPJ+587/3ige+vYFc69OcsBE3TFSj6lGjskqi1l/\nmJ7KIxRaLIs4E1c+3jT1GB7/9Izr+b13JO+TTAkyHVimA/NyxJVTxCPP4urDyUi+wjrAIKpg+dVJ\nadkWR+55bZsuvCO3atoyxC4cT0aFD+3F1YYwP5+MGCyfTJKfkMxL6eLzvzfdaQavY3eSzM6vwe+6\nEcu0t3S8k45M+YfTRdVkVJJ5mAXgBelcmQFguPKJ5DkLR7GgPUlsZzqIhvcRnfr3WSXFrzRXG2q9\nvOZ8CNqSzyQvB34+TfanSX/PT99v+89f/GJB+vom72rL9uCVtuG1b8crbU9GsE2ThFnO4vRzaXKU\n40pzeDTkF746vOgTqJCUwB2rL/7jvJKOjEV84Nnz1SPaM8Y9a3PcvabOtV0BA5WYF8dCjoxFvDgW\n8eJYyPHxiKjJ09ad8/jFm0vcvfmNBBtfTzy0l3DgEeKhvTS78MY5GKrFlEOXzJntoG4ZPBdRj+Gp\ncDufq7+MA/FWktGkF1d7eHJgujoUM/s093KPn+VN2X8i50MWwwMsTr6zklG7ls5bm4zerQa9jNaN\n4Wqd47Uix+K1HIvX8my8nQHXc9E+stRY551ivZ2k1xuk7PJ8PbyFEUoXLTvsOhh2rV9o0s44dwdf\nZ5f/PB02RoY6YFRcjgo5qi5LhRwVl6Oa/p6zGtd4R7jGu/z/A/tdH5+uv4InoutxTP/5nveN3rxH\nT86jEBg531hd8NjUlnTZT5YjhqpJwrseO0oZj1LGKGU82jNGRza5LaU/T5b+rqdzsVYjRyEw2gK7\naA7gc3O5njsW6M1PXwnEzMj6kPUNXeojIiIiIiLLmUaiLlIaiSqNouGnqT33R/O6Ta+0g+yun1vQ\nk9XOxbiJY8SjB5KRnFEZr7Qdv/dO4tH9RAOPEY88y7Sj97wclmm7YD7MVkdFWLYbr7QTr2Nncpvr\nxUVVojOPEA08Slw+3rTM7GIWxskJMi8dNVKNYCKKqcfJ38I4KcE29XPfAMzO3V8MPFYXvBnn3Ytc\nUqpxqBpfMEfYVB1Zj66sR96/cJ6zKy27++fwS0vjM9JFNVw4kiThgnaSM+LpiNbqGVx1ILmNKnht\n1xCsvueispCzNZ/fIy6OiEefJR55jnh0P/H4Ea7IiNtFwmvfmlyUUdyEv+ouvOL6S66TzHc8nJRS\nz3QmifJwBCwz6wT4YlIOHWercdIqMYPpz4PVmEJgXNsZcG1XQMFPxpWN1R2D1Zj+ckT/RMzJckT/\nRMTJcsyZSkQYJ5VD876R9Yx8eoI+5xvj6cUaHtCZ9ejMeXRmk5F8nVmPtiAZVTdai+nKeezpynBd\nd8CqvDen77nZxEo9drw4GnG6EtGb99jZ2Vrp/JMTET/75UFOz2Fuz+UoSHNN5+dBnb/thov0qX75\nuhwdGePG3gy3dlbpnXiccOCRcxdy1b0i/zj6Ur4x1scq7yzDroN90bXUyAIOD0c8Q5Juvtzif5uH\nMp+kQJJI9syI8DkZ93E0Xs9Rt5aj8XqOx2uoMn8luufKs9beS2ZQ8JNkYz4wzlZj4voE67xTbPRO\ncKv/FFu9IxesM+6KDLhuzrouBlw3A3Hy82nXy4Dr5nyZ5GT7t6/Kct/6HBuKPr15j1V5j2JgK/Ii\nkuVGfXWRS1OciFya4kRkeooPmQ8aiSqyzESnv9zSclbcmMzDmekknjhCdPab045oi0cPEA/vTeba\nuwJcVCUa+DquPpKURi1dC8S48SNEoweSZMvYQTg3B1d6XCPPEh77VGs7iau46uXNdehqg0QDjxIN\nPJrcYcEVm4/sSqsVtvHR6v08cmqc7d5B1topVtkgZfJ8LbyNx6Mb2Okd5Nbg29zoP0uOC5+zZPTo\n+bOKE2HModGYwDMCL/mTc+k8qeduWzujPVKLGanFGEY+SJIjhcDI+0kpwCvBa9uM177jimz7SjA/\ni/mrGu+BbBd+tgtKzUe1Libm+fid1+F3Xgck89TGaYxHI/uTuX6DAl779qTkcVzDheO4Sn8yJ+5M\no27P7wTLdODiMElAzqXcZVDCyyUntJ2LgXTkr4vPN2JcHJ37mwUl/FV3Eqx9APOmH5kz/eFnsXzD\n3HfmQ7b78h/DAqjHjs8fq/K54xVeHIsYrMYzztt5uZxLkrNlHMPTLDNajzg63tpcm4XA2NTus7kt\nYEObT9Y/P+eiB+mIOaMrZ+zqyrC2kCRdJ8KYF0Yi/rXf56lRj1MHTlNNdzmZ47CGnwFqabnUSS9d\nneWXb+2gOzd9UuvERMQvfHVoxSVQC4HRm/MoZT22dwTc3JuhJ+cxVnfkfNhaClhdOJ8Ady6pdBC5\n80nVyDlGao6BasxEPT43QnZytF57xjs3qq8379GbS+aQzfpG7Bx/e2CCv9o/cUXex5frSyeS7+d/\nejH532hd8SZuXXU7N/WMM14e5q+PdXO2mr7pLnrLGDFXJwH3RHQDT0c76awfB6Ca7WXUtREz+8/H\ny9GZ9dha8unOeeSDZK7eUia5mKItY7RnPNoDoz39uS1jtAfJxRwvjIa8MBIROkdbkPytmG5jcv28\nb3gNwe2cY7TuGA83Ejs4NPpdfP3UacbHzxJ7WSp+D87LJ2WPPSPrwWbP2GbJZ0Q1St6vaws+15R8\nru3M0DXD54KIiIiIiIgsHhqJukhpJOr8ci6CsIyLK0l5T6+10SGLgXMxlSd+JUlENOH33IrXdVOa\nPL2w1FlcPUP9xQ83LcMKYPk15Pa8e05zhTYTV05Te+4PcdWBed1uK2Y7P9eVEDlH7JIRD8b5xGMz\njmSeskrkcM7DZToIcl0UCj20F7vxguK5eUDxc5iXBT+PeVkisvzj0YA/P+BRa3GYTkDILu8AtwZ7\nucY7SoeNkaPKiCuxL9rJk9F13B48xR3+lZ9L0ktLwRlQcTnwsqwKxmlL51q73BxrZtvbCHpvn9dj\nXW4Wy/eIq48RDT2Fq5wC85IywpZJ3udeBrwAC0p47Vsw/8KYjsePUD/8IeLxF1vbmZ8nu/Wt+N03\nXoFHsnTFznFsPOLQaMSh0ZDRuuP67oC71+Y4Nh7x2Okaz4+EPHaqtiISfW0ZI04TuQDVavKdkstd\n3ndKX97jP72kkz3d5//viJ3jyFjE545V+fuDMyfxNrb57OoKOFmOOTURcaYaL7l5SNcWfXZ0BOzo\nDNie3q4tzG2E8HwZqcV8rb/GwyerPD5QZ6S2/N/j82mu8TGVGU3f3zf0ZPiB7UVu7MngG5QyGrEp\ni9di+R9LZDFTnIhcmuJEZHqKD5kPGokqkqo9/+fEY4dwtfPlXjEPf9VdZDY/hHmLPwRcpX/aBGp2\n9zvxS9OPuPNyq8ju+Enqh/6W6MxXm2678uSv4vfcTrD6Xry2ay5eZrLk7tjBZM5El44EM//cnImW\nJj7wAlxtmPB4iyNJl5EwdozUHUdrJZ6sbWHCFVllAxSswrDrYMh1UHVZamSpuwx1AmpkqLkMExQZ\nch0Mu9IFozh8g2JgZNPSljk/nX/KS0ZT7D07WW649TPqIQF7493sre0+d59HdMF+n65dy+Pe9bwm\n8wU2esfn+tRMayhu4wu1u/lS+FLqZNNjiXkw+Dz3Zb5K3uoNI8UaRo9ZUo4x7188otWKG/F7brli\nxyzzyzLtBH0vu6x1vbZNZPf8Am7iKNHw3mTe3vHD0yycJXftT+O1b7n8g13CqpHja/01Do6ExDh8\nszRxGnJ4NGr5IoyVYHye5/o8XYn5qS8Nsrsr4NZVWfYPhzwzVG9pTtF33VjiDVsLF9xXixynyhH9\n5ZgTExHjoTtXKQCSz8vN7T5riz4fPljm66drnK3EBF5SGjljkEm/UybnxM56sCrvcaYSc3gsGcUJ\nSUJrbSEZvVsOHRNpa3y7dOeSMqSBZ+Q82NYRcGNPhrVFn0JgrMp7tGcW74i7jqzHd27K852b8jjn\nODERs384pBI5wjgZWTw5j/ih0ZAvnawp0TqP8r5x/4Ycb7m2jXVFn9gl77HxumOs7ihHjk3tPp3Z\nxfseEhERERERkeVt8WeQRObA1QapVwY4U4npK3j4ZuBiotNfAReR3fqWhT7ES4pHn296v9d2zYwJ\n1ElmRuaah4hHnr0wmXxuB3WiM18jOvM1rLiJoO9uvM49uNpQcv/gt+ZWOnOB+KvuwoJkvtRo5Blq\n9QnqkcPMCNIknHcZoxi89m0QFDEvh/OyVF2WRweMfx3oYn+0kbOuC+apnF7kYLTuYJ5P6k/VrPze\n3ng3e6u76GCM1d4ZVtsZ1nhnWGOnWe0N0G1DxHg8He3gK+EdHI3X4Zlj3BUIiLjZ38cm7zgZqzPu\niucbye2oa+O068VNmbstxuNT4f18OnwlJRsjS40cNbJWI0ednFVZb/3cGnybPktGOrdnPNYVfYKO\nHWS3/ShmV6ecoCw8M8PaNuG1bYL1D+Lqo0TD+4iH9hKNPAtxFa9tM5lrfgCvuHGhD/eqO1uJ+OD+\nCf71aKWlpJ1cOc8MhTwz1HrJ+B/f03ZRAhWSROjG9oCNLUyl+56bS5deaIrYOZ4bDqmEjm0dAR1T\nklfOOeoxTISOXFqefbkwM9a3+axvm/475KfDmH89WuXJgRrjdcdwLebASNjyHKudWY9N7T6Rg6cH\nr9y86905j83tPpvbAza3++cSkWbQPxFzZDykHpHMK5xL5hVuzxjOJaW7wzi9dclFYvUYarHjwHDI\no6dqLZfTbmZV3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txVPkqZC8+Md99U4l1fGVwUycL+iYj3PnZ1L8zY2Rnw5h1F7lqTpRhc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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x114406050>"
]
},
"metadata": {
"image/png": {
"height": 407,
"width": 936
}
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(14, 7))\n",
"for c in table.columns.values:\n",
" plt.plot(table.index, table[c], lw=3, alpha=0.8,label=c)\n",
"plt.legend(loc='upper left', fontsize=12)\n",
"plt.ylabel('price in $')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It looks like that Amazon and Google's stock price is relatively more expensive than those of Facebook and Apple. But since Facebook and Apple are squashed at the bottom, it is hard to see the movement of these two."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another way to plot this is plotting daily returns (percent change compared to the day before). By plotting daily returns instead of actual prices, we can see the stocks' volatility."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x114ddaf50>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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gitextract_7rt3jnhm/ ├── Efficient _Frontier_implementation.ipynb └── README.md
Condensed preview — 2 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (1,503K chars).
[
{
"path": "Efficient _Frontier_implementation.ipynb",
"chars": 1479528,
"preview": "{\n \"cells\": [\n {\n \"cell_type\": \"markdown\",\n \"metadata\": {},\n \"source\": [\n \"# Efficient Frontiner from Modern P"
},
{
"path": "README.md",
"chars": 662,
"preview": "# The Efficinet Frontier (Markowitz Portfolio Optimisation)\n\nAttached Jupyter Notebook is the efficient frontier modelin"
}
]
About this extraction
This page contains the full source code of the tthustla/efficient_frontier GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 2 files (1.4 MB), approximately 978.7k tokens. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.