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Repository: davidzr/freqtrade-strategies
Branch: main
Commit: 9623c1f3d8c7
Files: 467
Total size: 16.5 MB
Directory structure:
gitextract_m9eikmuu/
├── LICENSE
├── README.md
└── strategies/
├── ADXMomentum/
│ └── ADXMomentum.py
├── ADX_15M_USDT/
│ └── ADX_15M_USDT.py
├── ADX_15M_USDT2/
│ └── ADX_15M_USDT2.py
├── ASDTSRockwellTrading/
│ └── ASDTSRockwellTrading.py
├── ActionZone/
│ └── ActionZone.py
├── AdxSmas/
│ └── AdxSmas.py
├── AlligatorStrat/
│ └── AlligatorStrat.py
├── AlligatorStrategy/
│ └── AlligatorStrategy.py
├── AlwaysBuy/
│ └── AlwaysBuy.py
├── Apollo11/
│ └── Apollo11.py
├── AverageStrategy/
│ └── AverageStrategy.py
├── AwesomeMacd/
│ └── AwesomeMacd.py
├── BBMod1/
│ └── BBMod1.py
├── BBRSI/
│ └── BBRSI.py
├── BBRSI2/
│ └── BBRSI2.py
├── BBRSI21/
│ └── BBRSI21.py
├── BBRSI3366/
│ └── BBRSI3366.py
├── BBRSI4cust/
│ └── BBRSI4cust.py
├── BBRSINaiveStrategy/
│ └── BBRSINaiveStrategy.py
├── BBRSIOptim2020Strategy/
│ └── BBRSIOptim2020Strategy.py
├── BBRSIOptimStrategy/
│ └── BBRSIOptimStrategy.py
├── BBRSIOptimizedStrategy/
│ └── BBRSIOptimizedStrategy.py
├── BBRSIS/
│ └── BBRSIS.py
├── BBRSIStrategy/
│ └── BBRSIStrategy.py
├── BBRSITV/
│ └── BBRSITV.py
├── BBRSIoriginal/
│ └── BBRSIoriginal.py
├── BBRSIv2/
│ └── BBRSIv2.py
├── BB_RPB_TSL/
│ └── BB_RPB_TSL.py
├── BB_RPB_TSL_2/
│ └── BB_RPB_TSL_2.py
├── BB_RPB_TSL_BI/
│ └── BB_RPB_TSL_BI.py
├── BB_RPB_TSL_BIV1/
│ └── BB_RPB_TSL_BIV1.py
├── BB_RPB_TSL_RNG/
│ └── BB_RPB_TSL_RNG.py
├── BB_RPB_TSL_RNG_2/
│ └── BB_RPB_TSL_RNG_2.py
├── BB_RPB_TSL_RNG_TBS/
│ └── BB_RPB_TSL_RNG_TBS.py
├── BB_RPB_TSL_RNG_TBS_GOLD/
│ └── BB_RPB_TSL_RNG_TBS_GOLD.py
├── BB_RPB_TSL_RNG_VWAP/
│ └── BB_RPB_TSL_RNG_VWAP.py
├── BB_RPB_TSL_SMA_Tranz/
│ └── BB_RPB_TSL_SMA_Tranz.py
├── BB_RPB_TSL_SMA_Tranz_TB_1_1_1/
│ └── BB_RPB_TSL_SMA_Tranz_TB_1_1_1.py
├── BB_RPB_TSL_SMA_Tranz_TB_MOD/
│ └── BB_RPB_TSL_SMA_Tranz_TB_MOD.py
├── BB_RPB_TSL_Tranz/
│ └── BB_RPB_TSL_Tranz.py
├── BB_RPB_TSL_c7c477d_20211030/
│ └── BB_RPB_TSL_c7c477d_20211030.py
├── BB_RPB_TSLmeneguzzo/
│ └── BB_RPB_TSLmeneguzzo.py
├── BB_RSI/
│ └── BB_RSI.py
├── BB_Strategy04/
│ └── BB_Strategy04.py
├── BBands/
│ └── BBands.py
├── BBandsRSI/
│ └── BBandsRSI.py
├── BBlower/
│ └── BBlower.py
├── Babico_SMA5xBBmid/
│ └── Babico_SMA5xBBmid.py
├── Bandtastic/
│ └── Bandtastic.py
├── BbRoi/
│ └── BbRoi.py
├── BbandRsi/
│ └── BbandRsi.py
├── BbandRsiRolling/
│ └── BbandRsiRolling.py
├── BcmbigzDevelop/
│ └── BcmbigzDevelop.py
├── BcmbigzV1/
│ └── BcmbigzV1.py
├── BigPete/
│ └── BigPete.py
├── BigZ03/
│ └── BigZ03.py
├── BigZ0307HO/
│ └── BigZ0307HO.py
├── BigZ03HO/
│ └── BigZ03HO.py
├── BigZ04/
│ └── BigZ04.py
├── BigZ0407/
│ └── BigZ0407.py
├── BigZ0407HO/
│ └── BigZ0407HO.py
├── BigZ04HO/
│ └── BigZ04HO.py
├── BigZ04HO2/
│ └── BigZ04HO2.py
├── BigZ04_TSL3/
│ └── BigZ04_TSL3.py
├── BigZ04_TSL4/
│ └── BigZ04_TSL4.py
├── BigZ06/
│ └── BigZ06.py
├── BigZ07/
│ └── BigZ07.py
├── BigZ07Next/
│ └── BigZ07Next.py
├── BigZ07Next2/
│ └── BigZ07Next2.py
├── BinClucMad/
│ └── BinClucMad.py
├── BinClucMadDevelop/
│ └── BinClucMadDevelop.py
├── BinClucMadSMADevelop/
│ └── BinClucMadSMADevelop.py
├── BinClucMadV1/
│ └── BinClucMadV1.py
├── BinHV27/
│ └── BinHV27.py
├── BinHV45/
│ └── BinHV45.py
├── BinHV45HO/
│ └── BinHV45HO.py
├── BreakEven/
│ └── BreakEven.py
├── BuyAllSellAllStrategy/
│ └── BuyAllSellAllStrategy.py
├── BuyOnly/
│ └── BuyOnly.py
├── CBPete9/
│ └── CBPete9.py
├── CCIStrategy/
│ └── CCIStrategy.py
├── CMCWinner/
│ └── CMCWinner.py
├── Cci/
│ └── Cci.py
├── Chandem/
│ └── Chandem.py
├── Chandemtwo/
│ └── Chandemtwo.py
├── Chispei/
│ └── Chispei.py
├── Cluc4/
│ └── Cluc4.py
├── Cluc4werk/
│ └── Cluc4werk.py
├── Cluc5werk/
│ └── Cluc5werk.py
├── Cluc7werk/
│ └── Cluc7werk.py
├── ClucFiatROI/
│ └── ClucFiatROI.py
├── ClucFiatSlow/
│ └── ClucFiatSlow.py
├── ClucHAnix/
│ └── ClucHAnix.py
├── ClucHAnix5m/
│ └── ClucHAnix5m.py
├── ClucHAnix_5m/
│ └── ClucHAnix_5m.py
├── ClucHAnix_5m1/
│ └── ClucHAnix_5m1.py
├── ClucHAnix_BB_RPB_MOD/
│ └── ClucHAnix_BB_RPB_MOD.py
├── ClucHAnix_BB_RPB_MOD2_ROI/
│ └── ClucHAnix_BB_RPB_MOD2_ROI.py
├── ClucHAnix_BB_RPB_MOD_CTT/
│ └── ClucHAnix_BB_RPB_MOD_CTT.py
├── ClucHAnix_BB_RPB_MOD_E0V1E_ROI/
│ └── ClucHAnix_BB_RPB_MOD_E0V1E_ROI.py
├── ClucHAnix_hhll/
│ └── ClucHAnix_hhll.py
├── ClucHAwerk/
│ └── ClucHAwerk.py
├── ClucMay72018/
│ └── ClucMay72018.py
├── CofiBitStrategy/
│ └── CofiBitStrategy.py
├── CombinedBinHAndCluc/
│ └── CombinedBinHAndCluc.py
├── CombinedBinHAndCluc2021/
│ └── CombinedBinHAndCluc2021.py
├── CombinedBinHAndCluc2021Bull/
│ └── CombinedBinHAndCluc2021Bull.py
├── CombinedBinHAndClucHyperV0/
│ └── CombinedBinHAndClucHyperV0.py
├── CombinedBinHAndClucHyperV3/
│ └── CombinedBinHAndClucHyperV3.py
├── CombinedBinHAndClucV2/
│ └── CombinedBinHAndClucV2.py
├── CombinedBinHAndClucV3/
│ └── CombinedBinHAndClucV3.py
├── CombinedBinHAndClucV4/
│ └── CombinedBinHAndClucV4.py
├── CombinedBinHAndClucV5/
│ └── CombinedBinHAndClucV5.py
├── CombinedBinHAndClucV5Hyperoptable/
│ └── CombinedBinHAndClucV5Hyperoptable.py
├── CombinedBinHAndClucV6/
│ └── CombinedBinHAndClucV6.py
├── CombinedBinHAndClucV6H/
│ └── CombinedBinHAndClucV6H.py
├── CombinedBinHAndClucV7/
│ └── CombinedBinHAndClucV7.py
├── CombinedBinHAndClucV8/
│ └── CombinedBinHAndClucV8.py
├── CombinedBinHAndClucV8Hyper/
│ └── CombinedBinHAndClucV8Hyper.py
├── CombinedBinHAndClucV8XH/
│ └── CombinedBinHAndClucV8XH.py
├── CombinedBinHAndClucV8XHO/
│ └── CombinedBinHAndClucV8XHO.py
├── CombinedBinHClucAndMADV3/
│ └── CombinedBinHClucAndMADV3.py
├── CombinedBinHClucAndMADV5/
│ └── CombinedBinHClucAndMADV5.py
├── CombinedBinHClucAndMADV6/
│ └── CombinedBinHClucAndMADV6.py
├── CombinedBinHClucAndMADV9/
│ └── CombinedBinHClucAndMADV9.py
├── Combined_Indicators/
│ └── Combined_Indicators.py
├── Combined_NFIv6_SMA/
│ └── Combined_NFIv6_SMA.py
├── Combined_NFIv7_SMA/
│ └── Combined_NFIv7_SMA.py
├── Combined_NFIv7_SMA_Rallipanos_20210707/
│ └── Combined_NFIv7_SMA_Rallipanos_20210707.py
├── Combined_NFIv7_SMA_bAdBoY_20211204/
│ └── Combined_NFIv7_SMA_bAdBoY_20211204.py
├── CoreStrategy/
│ └── CoreStrategy.py
├── CrossEMAStrategy/
│ └── CrossEMAStrategy.py
├── CryptoFrog/
│ └── CryptoFrog.py
├── CryptoFrogHO/
│ └── CryptoFrogHO.py
├── CryptoFrogHO2/
│ └── CryptoFrogHO2.py
├── CryptoFrogHO2A/
│ └── CryptoFrogHO2A.py
├── CryptoFrogHO3A1/
│ └── CryptoFrogHO3A1.py
├── CryptoFrogHO3A2/
│ └── CryptoFrogHO3A2.py
├── CryptoFrogHO3A3/
│ └── CryptoFrogHO3A3.py
├── CryptoFrogHO3A4/
│ └── CryptoFrogHO3A4.py
├── CryptoFrogNFI/
│ └── CryptoFrogNFI.py
├── CryptoFrogNFIHO1A/
│ └── CryptoFrogNFIHO1A.py
├── CryptoFrogOffset/
│ └── CryptoFrogOffset.py
├── CustomStoplossWithPSAR/
│ └── CustomStoplossWithPSAR.py
├── DCBBBounce/
│ └── DCBBBounce.py
├── DD/
│ └── DD.py
├── DIV_v1/
│ └── DIV_v1.py
├── DevilStra/
│ └── DevilStra.py
├── Diamond/
│ └── Diamond.py
├── Divergences/
│ └── Divergences.py
├── Dracula/
│ └── Dracula.py
├── Dyna_opti/
│ └── Dyna_opti.py
├── EI3v2_tag_cofi_green/
│ └── EI3v2_tag_cofi_green.py
├── EMA50/
│ └── EMA50.py
├── EMA520015_V17/
│ └── EMA520015_V17.py
├── EMABBRSI/
│ └── EMABBRSI.py
├── EMABreakout/
│ └── EMABreakout.py
├── EMASkipPump/
│ └── EMASkipPump.py
├── EMAVolume/
│ └── EMAVolume.py
├── EMA_CROSSOVER_STRATEGY/
│ └── EMA_CROSSOVER_STRATEGY.py
├── EXPERIMENTAL_STRATEGY/
│ └── EXPERIMENTAL_STRATEGY.py
├── ElliotV2/
│ └── ElliotV2.py
├── ElliotV4/
│ └── ElliotV4.py
├── ElliotV531/
│ └── ElliotV531.py
├── ElliotV5HO/
│ └── ElliotV5HO.py
├── ElliotV5HOMod2/
│ └── ElliotV5HOMod2.py
├── ElliotV5HOMod3/
│ └── ElliotV5HOMod3.py
├── ElliotV7/
│ └── ElliotV7.py
├── ElliotV8HO/
│ └── ElliotV8HO.py
├── ElliotV8_original/
│ └── ElliotV8_original.py
├── ElliotV8_original_ichiv2/
│ └── ElliotV8_original_ichiv2.py
├── ElliotV8_original_ichiv3/
│ └── ElliotV8_original_ichiv3.py
├── Elliotv8/
│ └── Elliotv8.py
├── FRAYSTRAT/
│ └── FRAYSTRAT.py
├── Fakebuy/
│ └── Fakebuy.py
├── FastSupertrend/
│ └── FastSupertrend.py
├── FastSupertrendOpt/
│ └── FastSupertrendOpt.py
├── FiveMinCrossAbove/
│ └── FiveMinCrossAbove.py
├── FixedRiskRewardLoss/
│ └── FixedRiskRewardLoss.py
├── ForexSignal/
│ └── ForexSignal.py
├── FrostAuraM115mStrategy/
│ └── FrostAuraM115mStrategy.py
├── FrostAuraM11hStrategy/
│ └── FrostAuraM11hStrategy.py
├── FrostAuraM21hStrategy/
│ └── FrostAuraM21hStrategy.py
├── FrostAuraM315mStrategy/
│ └── FrostAuraM315mStrategy.py
├── FrostAuraM31hStrategy/
│ └── FrostAuraM31hStrategy.py
├── FrostAuraRandomStrategy/
│ └── FrostAuraRandomStrategy.py
├── GodCard/
│ └── GodCard.py
├── GodStraNew/
│ └── GodStraNew.py
├── GodStraNew40/
│ └── GodStraNew40.py
├── GodStraNew_SMAonly/
│ └── GodStraNew_SMAonly.py
├── Guacamole/
│ └── Guacamole.py
├── Gumbo1/
│ └── Gumbo1.py
├── Hacklemore2/
│ └── Hacklemore2.py
├── Hacklemore3/
│ └── Hacklemore3.py
├── HansenSmaOffsetV1/
│ └── HansenSmaOffsetV1.py
├── HarmonicDivergence/
│ └── HarmonicDivergence.py
├── Heracles/
│ └── Heracles.py
├── HourBasedStrategy/
│ └── HourBasedStrategy.py
├── HyperStra_GSN_SMAOnly/
│ └── HyperStra_GSN_SMAOnly.py
├── HyperStra_SMAOnly/
│ └── HyperStra_SMAOnly.py
├── INSIDEUP/
│ └── INSIDEUP.py
├── Ichess/
│ └── Ichess.py
├── Ichi/
│ └── Ichi.py
├── Ichimoku/
│ └── Ichimoku.py
├── Ichimoku_SenkouSpanCross/
│ └── Ichimoku_SenkouSpanCross.py
├── Ichimoku_v12/
│ └── Ichimoku_v12.py
├── Ichimoku_v30/
│ └── Ichimoku_v30.py
├── Ichimoku_v31/
│ └── Ichimoku_v31.py
├── Ichimoku_v32/
│ └── Ichimoku_v32.py
├── Ichimoku_v33/
│ └── Ichimoku_v33.py
├── Ichimoku_v37/
│ └── Ichimoku_v37.py
├── InformativeSample/
│ └── InformativeSample.py
├── Inverse/
│ └── Inverse.py
├── InverseV2/
│ └── InverseV2.py
├── JustROCR/
│ └── JustROCR.py
├── JustROCR3/
│ └── JustROCR3.py
├── JustROCR5/
│ └── JustROCR5.py
├── JustROCR6/
│ └── JustROCR6.py
├── KAMACCIRSI/
│ └── KAMACCIRSI.py
├── KC_BB/
│ └── KC_BB.py
├── Kamaflage/
│ └── Kamaflage.py
├── Leveraged/
│ └── Leveraged.py
├── LookaheadStrategy/
│ └── LookaheadStrategy.py
├── Low_BB/
│ └── Low_BB.py
├── LuxOSC/
│ └── LuxOSC.py
├── MAC/
│ └── MAC.py
├── MACDCCI/
│ └── MACDCCI.py
├── MACDRSI200/
│ └── MACDRSI200.py
├── MACDStrategy/
│ └── MACDStrategy.py
├── MACDStrategy_crossed/
│ └── MACDStrategy_crossed.py
├── MACD_EMA/
│ └── MACD_EMA.py
├── MACD_TRIPLE_MA/
│ └── MACD_TRIPLE_MA.py
├── MACD_TRI_EMA/
│ └── MACD_TRI_EMA.py
├── MADisplaceV3/
│ └── MADisplaceV3.py
├── MFI/
│ └── MFI.py
├── Macd/
│ └── Macd.py
├── MacheteV8b/
│ └── MacheteV8b.py
├── MacheteV8bRallimod2/
│ └── MacheteV8bRallimod2.py
├── MarketChyperHyperStrategy/
│ └── MarketChyperHyperStrategy.py
├── Maro4hMacdSd/
│ └── Maro4hMacdSd.py
├── Martin/
│ └── Martin.py
├── MiniLambo/
│ └── MiniLambo.py
├── Minmax/
│ └── Minmax.py
├── MomStrategy/
│ └── MomStrategy.py
├── Momentumv2/
│ └── Momentumv2.py
├── MontrealStrategy/
│ └── MontrealStrategy.py
├── MostOfAll/
│ └── MostOfAll.py
├── MultiMA_TSL/
│ └── MultiMA_TSL.py
├── MultiMA_TSL3/
│ └── MultiMA_TSL3.py
├── MultiMA_TSL3_Mod/
│ └── MultiMA_TSL3_Mod.py
├── MultiMa/
│ └── MultiMa.py
├── MultiOffsetLamboV0/
│ └── MultiOffsetLamboV0.py
├── MultiRSI/
│ └── MultiRSI.py
├── NASOSRv6_private_Reinuvader_20211121/
│ └── NASOSRv6_private_Reinuvader_20211121.py
├── NASOSv4/
│ └── NASOSv4.py
├── NASOSv5/
│ └── NASOSv5.py
├── NASOSv5_mod1/
│ └── NASOSv5_mod1.py
├── NASOSv5_mod1_DanMod/
│ └── NASOSv5_mod1_DanMod.py
├── NASOSv5_mod2/
│ └── NASOSv5_mod2.py
├── NASOSv5_mod3/
│ └── NASOSv5_mod3.py
├── NFI46/
│ └── NFI46.py
├── NFI46Frog/
│ └── NFI46Frog.py
├── NFI46FrogZ/
│ └── NFI46FrogZ.py
├── NFI46Offset/
│ └── NFI46Offset.py
├── NFI46OffsetHOA1/
│ └── NFI46OffsetHOA1.py
├── NFI46Z/
│ └── NFI46Z.py
├── NFI47V2/
│ └── NFI47V2.py
├── NFI4Frog/
│ └── NFI4Frog.py
├── NFI5MOHO/
│ └── NFI5MOHO.py
├── NFI5MOHO2/
│ └── NFI5MOHO2.py
├── NFI5MOHO_WIP/
│ └── NFI5MOHO_WIP.py
├── NFI5MOHO_WIP_1/
│ └── NFI5MOHO_WIP_1.py
├── NFI5MOHO_WIP_2/
│ └── NFI5MOHO_WIP_2.py
├── NFI731_BUSD/
│ └── NFI731_BUSD.py
├── NFI7MOHO/
│ └── NFI7MOHO.py
├── NFINextMOHO/
│ └── NFINextMOHO.py
├── NFINextMOHO2/
│ └── NFINextMOHO2.py
├── NFINextMultiOffsetAndHO/
│ └── NFINextMultiOffsetAndHO.py
├── NFINextMultiOffsetAndHO2/
│ └── NFINextMultiOffsetAndHO2.py
├── NFIX_BB_RPB/
│ └── NFIX_BB_RPB.py
├── NFIX_BB_RPB_c7c477d_20211030/
│ └── NFIX_BB_RPB_c7c477d_20211030.py
├── NfiNextModded/
│ └── NfiNextModded.py
├── NormalizerStrategy/
│ └── NormalizerStrategy.py
├── NormalizerStrategyHO2/
│ └── NormalizerStrategyHO2.py
├── Nostalgia/
│ └── Nostalgia.py
├── NostalgiaForInfinityNext/
│ └── NostalgiaForInfinityNext.py
├── NostalgiaForInfinityNextGen/
│ └── NostalgiaForInfinityNextGen.py
├── NostalgiaForInfinityNextGen_TSL/
│ └── NostalgiaForInfinityNextGen_TSL.py
├── NostalgiaForInfinityNextV7155/
│ └── NostalgiaForInfinityNextV7155.py
├── NostalgiaForInfinityNext_ChangeToTower_V5_2/
│ └── NostalgiaForInfinityNext_ChangeToTower_V5_2.py
├── NostalgiaForInfinityNext_ChangeToTower_V5_3/
│ └── NostalgiaForInfinityNext_ChangeToTower_V5_3.py
├── NostalgiaForInfinityNext_ChangeToTower_V6/
│ └── NostalgiaForInfinityNext_ChangeToTower_V6.py
├── NostalgiaForInfinityNext_maximizer/
│ └── NostalgiaForInfinityNext_maximizer.py
├── NostalgiaForInfinityV1/
│ └── NostalgiaForInfinityV1.py
├── NostalgiaForInfinityV2/
│ └── NostalgiaForInfinityV2.py
├── NostalgiaForInfinityV3/
│ └── NostalgiaForInfinityV3.py
├── NostalgiaForInfinityV4/
│ └── NostalgiaForInfinityV4.py
├── NostalgiaForInfinityV4HO/
│ └── NostalgiaForInfinityV4HO.py
├── NostalgiaForInfinityV5/
│ └── NostalgiaForInfinityV5.py
├── NostalgiaForInfinityV5MultiOffsetAndHO/
│ └── NostalgiaForInfinityV5MultiOffsetAndHO.py
├── NostalgiaForInfinityV5MultiOffsetAndHO2/
│ └── NostalgiaForInfinityV5MultiOffsetAndHO2.py
├── NostalgiaForInfinityV6/
│ └── NostalgiaForInfinityV6.py
├── NostalgiaForInfinityV6HO/
│ └── NostalgiaForInfinityV6HO.py
├── NostalgiaForInfinityV7/
│ └── NostalgiaForInfinityV7.py
├── NostalgiaForInfinityV7_7_2/
│ └── NostalgiaForInfinityV7_7_2.py
├── NostalgiaForInfinityV7_SMA/
│ └── NostalgiaForInfinityV7_SMA.py
├── NostalgiaForInfinityV7_SMAv2/
│ └── NostalgiaForInfinityV7_SMAv2.py
├── NostalgiaForInfinityV7_SMAv2_1/
│ └── NostalgiaForInfinityV7_SMAv2_1.py
├── NostalgiaForInfinityX/
│ └── NostalgiaForInfinityX.py
├── NostalgiaForInfinityX2/
│ └── NostalgiaForInfinityX2.py
├── NostalgiaForInfinityXw/
│ └── NostalgiaForInfinityXw.py
├── NotAnotherSMAOffSetStrategy_V2/
│ └── NotAnotherSMAOffSetStrategy_V2.py
├── NotAnotherSMAOffsetStrategy/
│ └── NotAnotherSMAOffsetStrategy.py
├── NotAnotherSMAOffsetStrategyHO/
│ └── NotAnotherSMAOffsetStrategyHO.py
├── NotAnotherSMAOffsetStrategyHOv3/
│ └── NotAnotherSMAOffsetStrategyHOv3.py
├── NotAnotherSMAOffsetStrategyLite/
│ └── NotAnotherSMAOffsetStrategyLite.py
├── NotAnotherSMAOffsetStrategyModHO/
│ └── NotAnotherSMAOffsetStrategyModHO.py
├── NotAnotherSMAOffsetStrategyModHO_LamineDz_20210901/
│ └── NotAnotherSMAOffsetStrategyModHO_LamineDz_20210901.py
├── NotAnotherSMAOffsetStrategyX1/
│ └── NotAnotherSMAOffsetStrategyX1.py
├── NotAnotherSMAOffsetStrategy_uzi/
│ └── NotAnotherSMAOffsetStrategy_uzi.py
├── NotAnotherSMAOffsetStrategy_uzi3/
│ └── NotAnotherSMAOffsetStrategy_uzi3.py
├── NowoIchimoku1hV1/
│ └── NowoIchimoku1hV1.py
├── NowoIchimoku1hV2/
│ └── NowoIchimoku1hV2.py
├── NowoIchimoku5mV2/
│ └── NowoIchimoku5mV2.py
├── ONUR/
│ └── ONUR.py
├── ObeliskIM_v1_1/
│ └── ObeliskIM_v1_1.py
├── ObeliskRSI_v6_1/
│ └── ObeliskRSI_v6_1.py
├── Obelisk_3EMA_StochRSI_ATR/
│ └── Obelisk_3EMA_StochRSI_ATR.py
├── Obelisk_Ichimoku_Slow_v1_3/
│ └── Obelisk_Ichimoku_Slow_v1_3.py
├── Obelisk_Ichimoku_ZEMA_v1/
│ └── Obelisk_Ichimoku_ZEMA_v1.py
├── Obelisk_TradePro_Ichi_v1_1/
│ └── Obelisk_TradePro_Ichi_v1_1.py
├── Obelisk_TradePro_Ichi_v2_1/
│ └── Obelisk_TradePro_Ichi_v2_1.py
├── PRICEFOLLOWING/
│ └── PRICEFOLLOWING.py
├── PRICEFOLLOWING2/
│ └── PRICEFOLLOWING2.py
├── PRICEFOLLOWINGX/
│ └── PRICEFOLLOWINGX.py
├── Persia/
│ └── Persia.py
├── PrawnstarOBV/
│ └── PrawnstarOBV.py
├── PumpDetector/
│ └── PumpDetector.py
├── Quickie/
│ └── Quickie.py
├── RSI/
│ └── RSI.py
├── RSIBB02/
│ └── RSIBB02.py
├── RSIv2/
│ └── RSIv2.py
├── RalliV1/
│ └── RalliV1.py
├── RalliV1_disable56/
│ └── RalliV1_disable56.py
├── RaposaDivergenceV1/
│ └── RaposaDivergenceV1.py
├── ReinforcedAverageStrategy/
│ └── ReinforcedAverageStrategy.py
├── ReinforcedQuickie/
│ └── ReinforcedQuickie.py
├── ReinforcedSmoothScalp/
│ └── ReinforcedSmoothScalp.py
├── Renko/
│ └── Renko.py
├── RobotradingBody/
│ └── RobotradingBody.py
├── Roth01/
│ └── Roth01.py
├── Roth03/
│ └── Roth03.py
├── SAR/
│ └── SAR.py
├── SMAIP3/
│ └── SMAIP3.py
├── SMAIP3v2/
│ └── SMAIP3v2.py
├── SMAOG/
│ └── SMAOG.py
├── SMAOPv1_TTF/
│ └── SMAOPv1_TTF.py
├── SMAOffset/
│ └── SMAOffset.py
├── SMAOffsetProtectOpt/
│ └── SMAOffsetProtectOpt.py
├── SMAOffsetProtectOptV0/
│ └── SMAOffsetProtectOptV0.py
├── SMAOffsetProtectOptV1/
│ └── SMAOffsetProtectOptV1.py
├── SMAOffsetProtectOptV1HO1/
│ └── SMAOffsetProtectOptV1HO1.py
├── SMAOffsetProtectOptV1Mod/
│ └── SMAOffsetProtectOptV1Mod.py
├── SMAOffsetProtectOptV1Mod2/
│ └── SMAOffsetProtectOptV1Mod2.py
├── SMAOffsetProtectOptV1_kkeue_20210619/
│ └── SMAOffsetProtectOptV1_kkeue_20210619.py
├── SMAOffsetV2/
│ └── SMAOffsetV2.py
├── SMA_BBRSI/
│ └── SMA_BBRSI.py
├── SRsi/
│ └── SRsi.py
├── STRATEGY_RSI_BB_BOUNDS_CROSS/
│ └── STRATEGY_RSI_BB_BOUNDS_CROSS.py
├── STRATEGY_RSI_BB_CROSS/
│ └── STRATEGY_RSI_BB_CROSS.py
├── SampleStrategy/
│ └── SampleStrategy.py
├── SampleStrategyV2/
│ └── SampleStrategyV2.py
├── Saturn5/
│ └── Saturn5.py
├── Scalp/
│ └── Scalp.py
├── Schism/
│ └── Schism.py
├── Schism2/
│ └── Schism2.py
├── Schism2MM/
│ └── Schism2MM.py
├── Schism3/
│ └── Schism3.py
├── Schism4/
│ └── Schism4.py
├── Schism5/
│ └── Schism5.py
├── Schism6/
│ └── Schism6.py
├── Seb/
│ └── Seb.py
├── Simple/
│ └── Simple.py
├── SlowPotato/
│ └── SlowPotato.py
├── Slowbro/
│ └── Slowbro.py
├── SmoothOperator/
│ └── SmoothOperator.py
├── SmoothScalp/
│ └── SmoothScalp.py
├── Stavix2/
│ └── Stavix2.py
├── Stinkfist/
│ └── Stinkfist.py
├── StochRSITEMA/
│ └── StochRSITEMA.py
├── Strategy001/
│ └── Strategy001.py
├── Strategy001_custom_sell/
│ └── Strategy001_custom_sell.py
├── Strategy002/
│ └── Strategy002.py
├── Strategy003/
│ └── Strategy003.py
├── Strategy004/
│ └── Strategy004.py
├── Strategy005/
│ └── Strategy005.py
├── StrategyScalpingFast/
│ └── StrategyScalpingFast.py
├── StrategyScalpingFast2/
│ └── StrategyScalpingFast2.py
├── SuperHV27/
│ └── SuperHV27.py
├── SuperTrend/
│ └── SuperTrend.py
├── SuperTrendPure/
│ └── SuperTrendPure.py
├── SupertrendStrategy/
│ └── SupertrendStrategy.py
├── SwingHigh/
│ └── SwingHigh.py
├── SwingHighToSky/
│ └── SwingHighToSky.py
├── TDSequentialStrategy/
│ └── TDSequentialStrategy.py
├── TEMA/
│ └── TEMA.py
├── TechnicalExampleStrategy/
│ └── TechnicalExampleStrategy.py
├── TemaMaster/
│ └── TemaMaster.py
├── TemaMaster3/
│ └── TemaMaster3.py
├── TemaPure/
│ └── TemaPure.py
├── TemaPureNeat/
│ └── TemaPureNeat.py
├── TemaPureTwo/
│ └── TemaPureTwo.py
├── TenderEnter/
│ └── TenderEnter.py
├── TheForce/
│ └── TheForce.py
├── TheRealPullbackV2/
│ └── TheRealPullbackV2.py
├── TrailingBuyStrat2/
│ └── TrailingBuyStrat2.py
├── Trend_Strength_Directional/
│ └── Trend_Strength_Directional.py
├── TrixStrategy/
│ └── TrixStrategy.py
├── TrixV15Strategy/
│ └── TrixV15Strategy.py
├── TrixV21Strategy/
│ └── TrixV21Strategy.py
├── TrixV23Strategy/
│ └── TrixV23Strategy.py
├── UltimateMomentumIndicator/
│ └── UltimateMomentumIndicator.py
├── Uptrend/
│ └── Uptrend.py
├── UziChan/
│ └── UziChan.py
├── UziChan2/
│ └── UziChan2.py
├── VWAP/
│ └── VWAP.py
├── WaveTrendStra/
│ └── WaveTrendStra.py
├── XebTradeStrat/
│ └── XebTradeStrat.py
├── XtraThicc/
│ └── XtraThicc.py
├── YOLO/
│ └── YOLO.py
├── adaptive/
│ └── adaptive.py
├── adx_opt_strat/
│ └── adx_opt_strat.py
├── adxbbrsi2/
│ └── adxbbrsi2.py
├── bb_rsi_opt_new/
│ └── bb_rsi_opt_new.py
├── bbema/
│ └── bbema.py
├── bbrsi1_strategy/
│ └── bbrsi1_strategy.py
├── bbrsi4Freq/
│ └── bbrsi4Freq.py
├── bestV2/
│ └── bestV2.py
├── botbaby/
│ └── botbaby.py
├── conny/
│ └── conny.py
├── cryptohassle/
│ └── cryptohassle.py
├── custom/
│ └── custom.py
├── custom_sell/
│ └── custom_sell.py
├── e6v34/
│ └── e6v34.py
├── ema/
│ └── ema.py
├── epretrace/
│ └── epretrace.py
├── fahmibah/
│ └── fahmibah.py
├── flawless_lambo/
│ └── flawless_lambo.py
├── hansencandlepatternV1/
│ └── hansencandlepatternV1.py
├── heikin/
│ └── heikin.py
├── hlhb/
│ └── hlhb.py
├── ichiV1/
│ └── ichiV1.py
├── ichiV1_Marius/
│ └── ichiV1_Marius.py
├── keltnerchannel/
│ └── keltnerchannel.py
├── mabStra/
│ └── mabStra.py
├── macd_recovery/
│ └── macd_recovery.py
├── mark_strat/
│ └── mark_strat.py
├── mark_strat_opt/
│ └── mark_strat_opt.py
├── quantumfirst/
│ └── quantumfirst.py
├── redditMA/
│ └── redditMA.py
├── stoploss/
│ └── stoploss.py
├── stratfib/
│ └── stratfib.py
├── strato/
│ └── strato.py
├── true_lambo/
│ └── true_lambo.py
└── wtc/
└── wtc.py
================================================
FILE CONTENTS
================================================
================================================
FILE: LICENSE
================================================
GNU GENERAL PUBLIC LICENSE
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================================================
FILE: README.md
================================================
# Freqtrade Strategies Repository
This repository is dedicated to sharing open-source trading strategies for the Freqtrade cryptocurrency trading bot. We encourage contributors to help keep these strategies up to date with the latest Freqtrade versions and to add new strategies to benefit the community.
## About Freqtrade
[Freqtrade](https://www.freqtrade.io/) is an open-source cryptocurrency trading bot that allows users to create, backtest, and execute trading strategies on various cryptocurrency exchanges.
## Getting Started
### Prerequisites
Before you start contributing to this project, ensure you have the following:
- [Freqtrade](https://www.freqtrade.io/) installed on your machine.
- Basic knowledge of Python and Freqtrade.
- Familiarity with version control using Git.
================================================
FILE: strategies/ADXMomentum/ADXMomentum.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
# --------------------------------
class ADXMomentum(IStrategy):
"""
author@: Gert Wohlgemuth
converted from:
https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/AdxMomentum.cs
"""
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.01
}
# Optimal stoploss designed for the strategy
stoploss = -0.25
# Optimal timeframe for the strategy
timeframe = '1h'
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 20
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
dataframe['sar'] = ta.SAR(dataframe)
dataframe['mom'] = ta.MOM(dataframe, timeperiod=14)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 25) &
(dataframe['mom'] > 0) &
(dataframe['plus_di'] > 25) &
(dataframe['plus_di'] > dataframe['minus_di'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 25) &
(dataframe['mom'] < 0) &
(dataframe['minus_di'] > 25) &
(dataframe['plus_di'] < dataframe['minus_di'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/ADX_15M_USDT/ADX_15M_USDT.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class ADX_15M_USDT(IStrategy):
ticker_interval = '15m'
# ROI table:
minimal_roi = {
"0": 0.26552,
"30": 0.10255,
"210": 0.03545,
"540": 0
}
# Stoploss:
stoploss = -0.1255
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
dataframe['sar'] = ta.SAR(dataframe)
dataframe['mom'] = ta.MOM(dataframe, timeperiod=14)
dataframe['sell-adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['sell-plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['sell-minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
dataframe['sell-sar'] = ta.SAR(dataframe)
dataframe['sell-mom'] = ta.MOM(dataframe, timeperiod=14)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 16) &
(dataframe['minus_di'] > 4) &
(dataframe['plus_di'] > 20) &
(qtpylib.crossed_above( dataframe['plus_di'],dataframe['minus_di']))
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 43) &
(dataframe['minus_di'] > 22) &
(dataframe['plus_di'] > 20) &
(qtpylib.crossed_above(dataframe['sell-minus_di'], dataframe['sell-plus_di']))
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/ADX_15M_USDT2/ADX_15M_USDT2.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class ADX_15M_USDT2(IStrategy):
ticker_interval = '15m'
# ROI table:
minimal_roi = {
"0": 0.10313,
"102": 0.07627,
"275": 0.04228,
"588": 0
}
# Stoploss:
stoploss = -0.31941
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
dataframe['sar'] = ta.SAR(dataframe)
dataframe['mom'] = ta.MOM(dataframe, timeperiod=14)
dataframe['sell-adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['sell-plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['sell-minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
dataframe['sell-sar'] = ta.SAR(dataframe)
dataframe['sell-mom'] = ta.MOM(dataframe, timeperiod=14)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
#(dataframe['adx'] > 45) &
#(dataframe['minus_di'] > 26) &
# (dataframe['plus_di'] > 33) &
(qtpylib.crossed_above(dataframe['minus_di'], dataframe['plus_di']))
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 91) &
# (dataframe['minus_di'] > 22) &
(dataframe['sell-minus_di'] > 91) &
#(dataframe['plus_di'] > 24) &
(qtpylib.crossed_above(dataframe['sell-plus_di'], dataframe['sell-minus_di']))
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/ASDTSRockwellTrading/ASDTSRockwellTrading.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class ASDTSRockwellTrading(IStrategy):
"""
trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0
author@: Gert Wohlgemuth
idea:
uptrend definition:
MACD above 0 line AND above MACD signal
downtrend definition:
MACD below 0 line and below MACD signal
sell definition:
MACD below MACD signal
it's basically a very simple MACD based strategy and we ignore the definition of the entry and exit points in this case, since the trading bot, will take of this already
"""
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"60": 0.01,
"30": 0.03,
"20": 0.04,
"0": 0.05
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.3
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['macd'] > 0) &
(dataframe['macd'] > dataframe['macdsignal'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['macd'] < dataframe['macdsignal'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/ActionZone/ActionZone.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy import IStrategy
from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParameter
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import datetime
class ActionZone(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 100000
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -1.00
use_custom_stoploss = True
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal timeframe for the strategy.
timeframe = '1d'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Number of candles used for calculations in lowest price of period
min_price_period: int = 14
# max loss able for calculation position size
max_loss_per_trade = 10 # USD
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'fastMA': {
'color': 'red',
'fill_to': 'slowMA',
'fill_color': 'rgba(232, 232, 232,0.2)'
},
'slowMA': {
'color': 'blue',
},
},
}
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, current_rate: float, current_profit: float, **kwargs) -> float:
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
last_candle = dataframe.iloc[-1].squeeze()
stoploss_price = last_candle['lowest']
# Convert absolute price to percentage relative to current_rate
if stoploss_price < current_rate:
return (stoploss_price / current_rate) - 1
# return maximum stoploss value, keeping current stoploss price unchanged
return 1
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float, proposed_stake: float, min_stake: float, max_stake: float, **kwargs) -> float:
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
last_candle = dataframe.iloc[-1].squeeze()
stop_price = last_candle['lowest']
volume_for_buy = self.max_loss_per_trade / (current_rate - stop_price)
use_money = volume_for_buy * current_rate
return use_money
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Dataframe with data from the exchange
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
# MIN - Lowest value over a specified period
lowest = ta.MIN(dataframe, timeperiod=self.min_price_period)
dataframe['lowest'] = lowest
# EMA - Exponential Moving Average
fastEMA = ta.EMA(dataframe, timeperiod=12)
slowEMA = ta.EMA(dataframe, timeperiod=26)
dataframe['fastMA'] = fastEMA
dataframe['slowMA'] = slowEMA
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['fastMA'] > dataframe['slowMA']) & # Bull
(dataframe['close'] > dataframe['fastMA'] ) & # Price Cross Up
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with sell column
"""
dataframe.loc[
(
(dataframe['fastMA'] < dataframe['slowMA']) & # Bear
(dataframe['close'] < dataframe['fastMA'] ) & # Price Cross Down
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/AdxSmas/AdxSmas.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class AdxSmas(IStrategy):
"""
author@: Gert Wohlgemuth
converted from:
https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/AdxSmas.cs
"""
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.1
}
# Optimal stoploss designed for the strategy
stoploss = -0.25
# Optimal timeframe for the strategy
timeframe = '1h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['short'] = ta.SMA(dataframe, timeperiod=3)
dataframe['long'] = ta.SMA(dataframe, timeperiod=6)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 25) &
(qtpylib.crossed_above(dataframe['short'], dataframe['long']))
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] < 25) &
(qtpylib.crossed_above(dataframe['long'], dataframe['short']))
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/AlligatorStrat/AlligatorStrat.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class AlligatorStrat(IStrategy):
"""
author@: Gert Wohlgemuth
idea:
buys and sells on crossovers - doesn't really perfom that well and its just a proof of concept
"""
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.1
# "53": 0.06157,
# "93": 0.0518,
# "187": 0.03,
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.2
# Optimal ticker interval for the strategy
ticker_interval = '4h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# CCIPeriod = 14
# T3Period = 5
# b = 0.618
dataframe['SMAShort'] = ta.SMA(dataframe, timeperiod=5)
dataframe['SMAMedium'] = ta.SMA(dataframe, timeperiod=8)
dataframe['SMALong'] = ta.SMA(dataframe, timeperiod=13)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
# b2 = b*b2b3 = b2 * b2c1 = -b3
# c2 = (3 * (b2+b3))
# c3 = -3 * (2*b2+b+b3)
# c4 = (1+3*b+b3+3*b2)
# nr = 1 + 0.5 * (T3period - 1)
# w1 = 2 / (nr + 1)
# w2 = 1 - w1
# xcci = ta.CCI(CCIPeriod)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
#or cross above SMALong to be more conservative
(
qtpylib.crossed_above(dataframe['SMAShort'], dataframe['SMAMedium']) &
((dataframe['macd'] > -0.00001)) &
(dataframe['macd'] > dataframe['macdsignal'])
)
|
qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal'])
# |
# (
# (dataframe['SMAShort'] > dataframe['SMAMedium']) &
# ((dataframe['macd'] > -0.00006)) &
# qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal'])
# )
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
# qtpylib.crossed_below(dataframe['SMAShort'], dataframe['SMALong']) &
((dataframe['close'] < dataframe['SMAMedium']) &
(dataframe['macd'] < dataframe['macdsignal'])
)
|
qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal'])
# (dataframe['cci'] >= 100.0)
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/AlligatorStrategy/AlligatorStrategy.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IStrategy, IntParameter)
# --------------------------------
# Add your lib to import here
import ta
# This class is a sample. Feel free to customize it.
class AlligatorStrategy(IStrategy):
"""
Sources
Crypto Robot : https://www.youtube.com/watch?v=tHYs5135jUA
Github : https://github.com/CryptoRobotFr/TrueStrategy/blob/main/AligatorStrategy/Aligator_Strategy_backtest.ipynb
freqtrade backtesting -s AlligatorStrategy --timerange=20200903-20210826 --stake-amount unlimited -p EGLD/USDT --config user_data/config_binance.json --enable-position-stacking
=============== SUMMARY METRICS ================
| Metric | Value |
|------------------------+---------------------|
| Backtesting from | 2020-09-11 11:00:00 |
| Backtesting to | 2021-08-26 00:00:00 |
| Max open trades | 1 |
| | |
| Total/Daily Avg Trades | 258 / 0.74 |
| Starting balance | 1000.000 USDT |
| Final balance | 14245.054 USDT |
| Absolute profit | 13245.054 USDT |
| Total profit % | 1324.51% |
| Trades per day | 0.74 |
| Avg. daily profit % | 3.81% |
| Avg. stake amount | 829.268 USDT |
| Total trade volume | 213951.164 USDT |
| | |
| Best Pair | EGLD/USDT 4287.66% |
| Worst Pair | EGLD/USDT 4287.66% |
| Best trade | EGLD/USDT 305.28% |
| Worst trade | EGLD/USDT -10.69% |
| Best day | 7078.313 USDT |
| Worst day | -1052.860 USDT |
| Days win/draw/lose | 8 / 275 / 19 |
| Avg. Duration Winners | 9 days, 18:58:00 |
| Avg. Duration Loser | 2 days, 9:00:00 |
| Rejected Buy signals | 3045 |
| | |
| Min balance | 905.332 USDT |
| Max balance | 16789.797 USDT |
| Drawdown | 169.59% |
| Drawdown | 2544.743 USDT |
| Drawdown high | 15789.797 USDT |
| Drawdown low | 13245.054 USDT |
| Drawdown Start | 2021-08-12 18:00:00 |
| Drawdown End | 2021-08-24 18:00:00 |
| Market change | 497.97% |
================================================
You must keep:
- the lib in the section "Do not remove these libs"
- the methods: populate_indicators, populate_buy_trend, populate_sell_trend
You should keep:
- timeframe, minimal_roi, stoploss, trailing_*
"""
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 100 # inactive
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.99 # inactive
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Hyperoptable parameters
buy_stoch_rsi = DecimalParameter(0.5, 1, decimals=3, default=0.82, space="buy")
sell_stoch_rsi = DecimalParameter(0, 0.5, decimals=3, default=0.2, space="sell")
# Optimal timeframe for the strategy.
timeframe = '1h'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count = 200 # EMA200
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'ema7':{},
'ema30':{},
'ema50':{},
'ema100':{},
'ema121':{},
'ema200':{}
},
'subplots': {
"STOCH RSI": {
'stoch_rsi': {}
}
}
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Dataframe with data from the exchange
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
# Momentum Indicators
# ------------------------------------
# # Stochastic RSI
dataframe['stoch_rsi'] = ta.momentum.stochrsi(close=dataframe['close'], window=14, smooth1=3, smooth2=3) #Non moyenné
# Overlap Studies
# ------------------------------------
# # EMA - Exponential Moving Average
dataframe['ema7']=ta.trend.ema_indicator(close=dataframe['close'], window=7)
dataframe['ema30']=ta.trend.ema_indicator(close=dataframe['close'], window=30)
dataframe['ema50']=ta.trend.ema_indicator(close=dataframe['close'], window=50)
dataframe['ema100']=ta.trend.ema_indicator(close=dataframe['close'], window=100)
dataframe['ema121']=ta.trend.ema_indicator(close=dataframe['close'], window=121)
dataframe['ema200']=ta.trend.ema_indicator(close=dataframe['close'], window=200)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['ema7'] > dataframe['ema30']) &
(dataframe['ema30'] > dataframe['ema50']) &
(dataframe['ema50'] > dataframe['ema100']) &
(dataframe['ema100'] > dataframe['ema121']) &
(dataframe['ema121'] > dataframe['ema200']) &
(dataframe['stoch_rsi'] < self.buy_stoch_rsi.value) &
(dataframe['volume'] > 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with sell column
"""
dataframe.loc[
(
(dataframe['ema121'] > dataframe['ema7']) &
(dataframe['stoch_rsi'] > self.sell_stoch_rsi.value) &
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/AlwaysBuy/AlwaysBuy.py
================================================
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
class AlwaysBuy(IStrategy):
INTERFACE_VERSION = 3
# ROI table:
# fmt: off
minimal_roi = {
"0": 1,
"100": 2,
"200": 3,
"300": -1
}
# fmt: on
# Stoploss:
stoploss = -0.2
# Trailing stop:
trailing_stop = False
trailing_stop_positive = 0.005
trailing_stop_positive_offset = 0.03
trailing_only_offset_is_reached = True
# Buy hypers
timeframe = "5m"
use_exit_signal = False
# #################### END OF RESULT PLACE ####################
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[:, ["enter_long", "enter_tag"]] = (1, "entry_reason")
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
return dataframe
================================================
FILE: strategies/Apollo11/Apollo11.py
================================================
from datetime import datetime
from datetime import timedelta
from functools import reduce
import freqtrade.vendor.qtpylib.indicators as qtpylib
import talib.abstract as ta
from freqtrade.persistence import Trade
from freqtrade.strategy import IStrategy
from pandas import DataFrame
def to_minutes(**timdelta_kwargs):
return int(timedelta(**timdelta_kwargs).total_seconds() / 60)
class Apollo11(IStrategy):
# Strategy created by Shane Jones https://twitter.com/shanejones
#
# Assited by a number of contributors https://github.com/shanejones/goddard/graphs/contributors
#
# Original repo hosted at https://github.com/shanejones/goddard
timeframe = "15m"
# Stoploss
stoploss = -0.16
startup_candle_count: int = 480
trailing_stop = False
use_custom_stoploss = True
use_sell_signal = False
# signal controls
buy_signal_1 = True
buy_signal_2 = True
buy_signal_3 = True
# ROI table:
minimal_roi = {
"0": 10, # This is 10000%, which basically disables ROI
}
# Indicator values:
# Signal 1
s1_ema_xs = 3
s1_ema_sm = 5
s1_ema_md = 10
s1_ema_xl = 50
s1_ema_xxl = 240
# Signal 2
s2_ema_input = 50
s2_ema_offset_input = -1
s2_bb_sma_length = 49
s2_bb_std_dev_length = 64
s2_bb_lower_offset = 3
s2_fib_sma_len = 50
s2_fib_atr_len = 14
s2_fib_lower_value = 4.236
s3_ema_long = 50
s3_ema_short = 20
s3_ma_fast = 10
s3_ma_slow = 20
@property
def protections(self):
return [
{
# Don't enter a trade right after selling a trade.
"method": "CooldownPeriod",
"stop_duration": to_minutes(minutes=0),
},
{
# Stop trading if max-drawdown is reached.
"method": "MaxDrawdown",
"lookback_period": to_minutes(hours=12),
"trade_limit": 20, # Considering all pairs that have a minimum of 20 trades
"stop_duration": to_minutes(hours=1),
"max_allowed_drawdown": 0.2, # If max-drawdown is > 20% this will activate
},
{
# Stop trading if a certain amount of stoploss occurred within a certain time window.
"method": "StoplossGuard",
"lookback_period": to_minutes(hours=6),
"trade_limit": 4, # Considering all pairs that have a minimum of 4 trades
"stop_duration": to_minutes(minutes=30),
"only_per_pair": False, # Looks at all pairs
},
{
# Lock pairs with low profits
"method": "LowProfitPairs",
"lookback_period": to_minutes(hours=1, minutes=30),
"trade_limit": 2, # Considering all pairs that have a minimum of 2 trades
"stop_duration": to_minutes(hours=15),
"required_profit": 0.02, # If profit < 2% this will activate for a pair
},
{
# Lock pairs with low profits
"method": "LowProfitPairs",
"lookback_period": to_minutes(hours=6),
"trade_limit": 4, # Considering all pairs that have a minimum of 4 trades
"stop_duration": to_minutes(minutes=30),
"required_profit": 0.01, # If profit < 1% this will activate for a pair
},
]
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Adding EMA's into the dataframe
dataframe["s1_ema_xs"] = ta.EMA(dataframe, timeperiod=self.s1_ema_xs)
dataframe["s1_ema_sm"] = ta.EMA(dataframe, timeperiod=self.s1_ema_sm)
dataframe["s1_ema_md"] = ta.EMA(dataframe, timeperiod=self.s1_ema_md)
dataframe["s1_ema_xl"] = ta.EMA(dataframe, timeperiod=self.s1_ema_xl)
dataframe["s1_ema_xxl"] = ta.EMA(dataframe, timeperiod=self.s1_ema_xxl)
s2_ema_value = ta.EMA(dataframe, timeperiod=self.s2_ema_input)
s2_ema_xxl_value = ta.EMA(dataframe, timeperiod=200)
dataframe["s2_ema"] = s2_ema_value - s2_ema_value * self.s2_ema_offset_input
dataframe["s2_ema_xxl_off"] = s2_ema_xxl_value - s2_ema_xxl_value * self.s2_fib_lower_value
dataframe["s2_ema_xxl"] = ta.EMA(dataframe, timeperiod=200)
s2_bb_sma_value = ta.SMA(dataframe, timeperiod=self.s2_bb_sma_length)
s2_bb_std_dev_value = ta.STDDEV(dataframe, self.s2_bb_std_dev_length)
dataframe["s2_bb_std_dev_value"] = s2_bb_std_dev_value
dataframe["s2_bb_lower_band"] = s2_bb_sma_value - (s2_bb_std_dev_value * self.s2_bb_lower_offset)
s2_fib_atr_value = ta.ATR(dataframe, timeframe=self.s2_fib_atr_len)
s2_fib_sma_value = ta.SMA(dataframe, timeperiod=self.s2_fib_sma_len)
dataframe["s2_fib_lower_band"] = s2_fib_sma_value - s2_fib_atr_value * self.s2_fib_lower_value
s3_bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=3)
dataframe["s3_bb_lowerband"] = s3_bollinger["lower"]
dataframe["s3_ema_long"] = ta.EMA(dataframe, timeperiod=self.s3_ema_long)
dataframe["s3_ema_short"] = ta.EMA(dataframe, timeperiod=self.s3_ema_short)
dataframe["s3_fast_ma"] = ta.EMA(dataframe["volume"] * dataframe["close"], self.s3_ma_fast) / ta.EMA(
dataframe["volume"], self.s3_ma_fast
)
dataframe["s3_slow_ma"] = ta.EMA(dataframe["volume"] * dataframe["close"], self.s3_ma_slow) / ta.EMA(
dataframe["volume"], self.s3_ma_slow
)
# Volume weighted MACD
dataframe["fastMA"] = ta.EMA(dataframe["volume"] * dataframe["close"], 12) / ta.EMA(dataframe["volume"], 12)
dataframe["slowMA"] = ta.EMA(dataframe["volume"] * dataframe["close"], 26) / ta.EMA(dataframe["volume"], 26)
dataframe["vwmacd"] = dataframe["fastMA"] - dataframe["slowMA"]
dataframe["signal"] = ta.EMA(dataframe["vwmacd"], 9)
dataframe["hist"] = dataframe["vwmacd"] - dataframe["signal"]
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# basic buy methods to keep the strategy simple
if self.buy_signal_1:
conditions = [
dataframe["vwmacd"] < dataframe["signal"],
dataframe["low"] < dataframe["s1_ema_xxl"],
dataframe["close"] > dataframe["s1_ema_xxl"],
qtpylib.crossed_above(dataframe["s1_ema_sm"], dataframe["s1_ema_md"]),
dataframe["s1_ema_xs"] < dataframe["s1_ema_xl"],
dataframe["volume"] > 0,
]
dataframe.loc[reduce(lambda x, y: x & y, conditions), ["buy", "buy_tag"]] = (1, "buy_signal_1")
if self.buy_signal_2:
conditions = [
qtpylib.crossed_above(dataframe["s2_fib_lower_band"], dataframe["s2_bb_lower_band"]),
dataframe["close"] < dataframe["s2_ema"],
dataframe["volume"] > 0,
]
dataframe.loc[reduce(lambda x, y: x & y, conditions), ["buy", "buy_tag"]] = (1, "buy_signal_2")
if self.buy_signal_3:
conditions = [
dataframe["low"] < dataframe["s3_bb_lowerband"],
dataframe["high"] > dataframe["s3_slow_ma"],
dataframe["high"] < dataframe["s3_ema_long"],
dataframe["volume"] > 0,
]
dataframe.loc[reduce(lambda x, y: x & y, conditions), ["buy", "buy_tag"]] = (1, "buy_signal_3")
if not all([self.buy_signal_1, self.buy_signal_2, self.buy_signal_3]):
dataframe.loc[(), "buy"] = 0
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# This is essentailly ignored as we're using strict ROI / Stoploss / TTP sale scenarios
dataframe.loc[(), "sell"] = 0
return dataframe
def custom_stoploss(
self, pair: str, trade: Trade, current_time: datetime, current_rate: float, current_profit: float, **kwargs
) -> float:
if current_profit > 0.2:
return 0.04
if current_profit > 0.1:
return 0.03
if current_profit > 0.06:
return 0.02
if current_profit > 0.03:
return 0.01
# Let's try to minimize the loss
if current_profit <= -0.10:
if trade.open_date_utc + timedelta(hours=60) < current_time:
# After 60H since buy
return current_profit / 1.75
if current_profit <= -0.08:
if trade.open_date_utc + timedelta(hours=120) < current_time:
# After 120H since buy
return current_profit / 1.70
return -1
================================================
FILE: strategies/AverageStrategy/AverageStrategy.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class AverageStrategy(IStrategy):
"""
author@: Gert Wohlgemuth
idea:
buys and sells on crossovers - doesn't really perfom that well and its just a proof of concept
"""
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.5
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.2
# Optimal timeframe for the strategy
timeframe = '4h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['maShort'] = ta.EMA(dataframe, timeperiod=8)
dataframe['maMedium'] = ta.EMA(dataframe, timeperiod=21)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
qtpylib.crossed_above(dataframe['maShort'], dataframe['maMedium'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
qtpylib.crossed_above(dataframe['maMedium'], dataframe['maShort'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/AwesomeMacd/AwesomeMacd.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class AwesomeMacd(IStrategy):
"""
author@: Gert Wohlgemuth
converted from:
https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/AwesomeMacd.cs
"""
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.1
}
# Optimal stoploss designed for the strategy
stoploss = -0.25
# Optimal timeframe for the strategy
timeframe = '1h'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['macd'] > 0) &
(dataframe['ao'] > 0) &
(dataframe['ao'].shift() < 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['macd'] < 0) &
(dataframe['ao'] < 0) &
(dataframe['ao'].shift() > 0)
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBMod1/BBMod1.py
================================================
# --- Do not remove these libs ---
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
import talib.abstract as ta
import pandas_ta as pta
from freqtrade.persistence import Trade
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame, Series
from datetime import datetime
from freqtrade.strategy import merge_informative_pair, DecimalParameter, IntParameter, stoploss_from_open
from functools import reduce
from technical.indicators import RMI, zema, VIDYA
# --------------------------------
def ha_typical_price(bars):
res = (bars['ha_high'] + bars['ha_low'] + bars['ha_close']) / 3.
return Series(index=bars.index, data=res)
# Volume Weighted Moving Average
def vwma(dataframe: DataFrame, length: int = 10):
"""Indicator: Volume Weighted Moving Average (VWMA)"""
# Calculate Result
pv = dataframe['close'] * dataframe['volume']
vwma = Series(ta.SMA(pv, timeperiod=length) / ta.SMA(dataframe['volume'], timeperiod=length))
return vwma
# Modified Elder Ray Index
def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
slow_ma = Series(ta.EMA(vwma(dataframe, length=len_slow_ma), timeperiod=len_slow_ma))
return slow_ma >= slow_ma.shift(1) # we just need true & false for ERI trend
def EWO(dataframe, ema_length=5, ema2_length=35):
df = dataframe.copy()
ema1 = ta.EMA(df, timeperiod=ema_length)
ema2 = ta.EMA(df, timeperiod=ema2_length)
emadif = (ema1 - ema2) / df['low'] * 100
return emadif
def range_percent_change(dataframe: DataFrame, method, length: int) -> float:
"""
Rolling Percentage Change Maximum across interval.
:param dataframe: DataFrame The original OHLC dataframe
:param method: High to Low / Open to Close
:param length: int The length to look back
"""
if method == 'HL':
return (dataframe['high'].rolling(length).max() - dataframe['low'].rolling(length).min()) / dataframe[
'low'].rolling(length).min()
elif method == 'OC':
return (dataframe['open'].rolling(length).max() - dataframe['close'].rolling(length).min()) / dataframe[
'close'].rolling(length).min()
else:
raise ValueError(f"Method {method} not defined!")
# Williams %R
def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
"""Williams %R, or just %R, is a technical analysis oscillator showing the current closing price in relation to the
high and low of the past N days (for a given N). It was developed by a publisher and promoter of trading
materials, Larry Williams.Its purpose is to tell whether a stock or commodity market is trading near the high or
the low, or somewhere in between,of its recent trading range.The oscillator is on a negative scale, from
−100 (lowest) up to 0 (highest).
"""
highest_high = dataframe["high"].rolling(center=False, window=period).max()
lowest_low = dataframe["low"].rolling(center=False, window=period).min()
wr = Series(
(highest_high - dataframe["close"]) / (highest_high - lowest_low),
name=f"{period} Williams %R",
)
return wr * -100
# Chaikin Money Flow
def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
"""Chaikin Money Flow (CMF)
It measures the amount of Money Flow Volume over a specific period.
http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:chaikin_money_flow_cmf
Args:
dataframe(pandas.Dataframe): dataframe containing ohlcv
n(int): n period.
fillna(bool): if fill nan values.
Returns:
pandas.Series: New feature generated.
"""
mfv = ((dataframe['close'] - dataframe['low']) - (dataframe['high'] - dataframe['close'])) / (
dataframe['high'] - dataframe['low'])
mfv = mfv.fillna(0.0) # float division by zero
mfv *= dataframe['volume']
cmf = (mfv.rolling(n, min_periods=0).sum()
/ dataframe['volume'].rolling(n, min_periods=0).sum())
if fillna:
cmf = cmf.replace([np.inf, -np.inf], np.nan).fillna(0)
return Series(cmf, name='cmf')
def vmap_b(dataframe, window_size=20, num_of_std=1):
df = dataframe.copy()
df['vwap'] = qtpylib.rolling_vwap(df, window=window_size)
rolling_std = df['vwap'].rolling(window=window_size).std()
df['vwap_low'] = df['vwap'] - (rolling_std * num_of_std)
df['vwap_high'] = df['vwap'] + (rolling_std * num_of_std)
return df['vwap_low'], df['vwap'], df['vwap_high']
def top_percent_change(dataframe: DataFrame, length: int) -> float:
"""
Percentage change of the current close from the range maximum Open price
:param dataframe: DataFrame The original OHLC dataframe
:param length: int The length to look back
"""
if length == 0:
return (dataframe['open'] - dataframe['close']) / dataframe['close']
else:
return (dataframe['open'].rolling(length).max() - dataframe['close']) / dataframe['close']
class BBMod1(IStrategy):
"""
BBMod1 modified from BB_RPB_TSL ( https://github.com/jilv220/BB_RPB_TSL )
@author jilv220
Simple bollinger brand strategy inspired by this blog ( https://hacks-for-life.blogspot.com/2020/12/freqtrade
-notes.html )RPB, which stands for Real Pull Back, taken from ( https://github.com/GeorgeMurAlkh/freqtrade-stuff
/blob/main/user_data/strategies/TheRealPullbackV2.py )The trailing custom stoploss taken from BigZ04_TSL from
Perkmeister ( modded by ilya )I modified it to better suit my taste and added Hyperopt for this strategy.
"""
# buy space
buy_params = {
##
"buy_bb_width_1h": 0.954,
"buy_roc_1h": 86,
##
"buy_threshold": 0.003,
"buy_bb_factor": 0.999,
#
"buy_bb_delta": 0.025,
"buy_bb_width": 0.095,
##
"buy_cci": -116,
"buy_cci_length": 25,
"buy_rmi": 49,
"buy_rmi_length": 17,
"buy_srsi_fk": 32,
##
# rng
"buy_closedelta": 12.148,
# rng
"buy_ema_diff": 0.022,
##
"buy_ema_high": 0.968,
"buy_ema_low": 0.935,
"buy_ewo": -5.001,
"buy_rsi": 23,
"buy_rsi_fast": 44,
##
"buy_ema_high_2": 1.087,
"buy_ema_low_2": 0.970,
"buy_ewo_high_2": 4.179,
"buy_rsi_ewo_2": 35,
"buy_rsi_fast_ewo_2": 45,
##
"buy_closedelta_local_dip": 12.044,
"buy_ema_diff_local_dip": 0.024,
"buy_ema_high_local_dip": 1.014,
"buy_rsi_local_dip": 21,
##
"buy_r_deadfish_bb_factor": 1.014,
"buy_r_deadfish_bb_width": 0.299,
"buy_r_deadfish_ema": 1.054,
"buy_r_deadfish_volume_factor": 1.59,
"buy_r_deadfish_cti": -0.115,
"buy_r_deadfish_r14": -44.34,
##
"buy_clucha_bbdelta_close": 0.01889,
"buy_clucha_bbdelta_tail": 0.72235,
"buy_clucha_close_bblower": 0.0127,
"buy_clucha_closedelta_close": 0.00916,
"buy_clucha_rocr_1h": 0.79492,
##
"buy_adx": 13,
"buy_cofi_r14": -85.016,
"buy_cofi_cti": -0.892,
"buy_ema_cofi": 1.147,
"buy_ewo_high": 8.594,
"buy_fastd": 28,
"buy_fastk": 39,
##
"buy_gumbo_ema": 1.121,
"buy_gumbo_ewo_low": -9.442,
"buy_gumbo_cti": -0.374,
"buy_gumbo_r14": -51.971,
##
"buy_sqzmom_ema": 0.981,
"buy_sqzmom_ewo": -3.966,
"buy_sqzmom_r14": -45.068,
##
"buy_nfix_39_ema": 0.912,
##
"buy_nfix_49_cti": -0.105,
"buy_nfix_49_r14": -81.827,
}
# sell space
sell_params = {
##
"sell_cmf": -0.046,
"sell_ema": 0.988,
"sell_ema_close_delta": 0.022,
##
"sell_deadfish_profit": -0.063,
"sell_deadfish_bb_factor": 0.954,
"sell_deadfish_bb_width": 0.043,
"sell_deadfish_volume_factor": 2.37,
##
"sell_cti_r_cti": 0.844,
"sell_cti_r_r": -19.99,
"high_offset_2": 0.997,
"pHSL": -0.99,
"pPF_1": 0.019,
"pPF_2": 0.05,
"pSL_1": 0.017,
"pSL_2": 0.045,
}
minimal_roi = {
"0": 100
}
# Optimal timeframe for the strategy
timeframe = '5m'
inf_1h = '1h'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = True
startup_candle_count = 120
order_types = {
'buy': 'limit',
'sell': 'limit',
'emergencysell': 'limit',
'forcebuy': "limit",
'forcesell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False,
'stoploss_on_exchange_interval': 60,
'stoploss_on_exchange_limit_ratio': 0.99
}
# Disabled
stoploss = -0.99
# Custom stoploss
use_custom_stoploss = True
use_sell_signal = True
lower_trailing_list = ["vwap", "clucHA", "clucHA2", "nfi_38", "nfi7_33", "nfi7_37", "cofi"]
############################################################################
# Buy params
is_optimize_dip = False
buy_rmi = IntParameter(30, 50, default=35, optimize=is_optimize_dip)
buy_cci = IntParameter(-135, -90, default=-133, optimize=is_optimize_dip)
buy_srsi_fk = IntParameter(30, 50, default=25, optimize=is_optimize_dip)
buy_cci_length = IntParameter(25, 45, default=25, optimize=is_optimize_dip)
buy_rmi_length = IntParameter(8, 20, default=8, optimize=is_optimize_dip)
is_optimize_break = False
buy_bb_width = DecimalParameter(0.065, 0.135, default=0.095, optimize=is_optimize_break)
buy_bb_delta = DecimalParameter(0.018, 0.035, default=0.025, optimize=is_optimize_break)
is_optimize_local_uptrend = False
buy_ema_diff = DecimalParameter(0.022, 0.027, default=0.025, optimize=is_optimize_local_uptrend)
buy_bb_factor = DecimalParameter(0.990, 0.999, default=0.995, optimize=False)
buy_closedelta = DecimalParameter(12.0, 18.0, default=15.0, optimize=is_optimize_local_uptrend)
is_optimize_local_dip = False
buy_ema_diff_local_dip = DecimalParameter(0.022, 0.027, default=0.025, optimize=is_optimize_local_dip)
buy_ema_high_local_dip = DecimalParameter(0.90, 1.2, default=0.942, optimize=is_optimize_local_dip)
buy_closedelta_local_dip = DecimalParameter(12.0, 18.0, default=15.0, optimize=is_optimize_local_dip)
buy_rsi_local_dip = IntParameter(15, 45, default=28, optimize=is_optimize_local_dip)
buy_crsi_local_dip = IntParameter(10, 18, default=10, optimize=False)
is_optimize_ewo = False
buy_rsi_fast = IntParameter(35, 50, default=45, optimize=is_optimize_ewo)
buy_rsi = IntParameter(15, 35, default=35, optimize=is_optimize_ewo)
buy_ewo = DecimalParameter(-6.0, 5, default=-5.585, optimize=is_optimize_ewo)
buy_ema_low = DecimalParameter(0.9, 0.99, default=0.942, optimize=is_optimize_ewo)
buy_ema_high = DecimalParameter(0.95, 1.2, default=1.084, optimize=is_optimize_ewo)
is_optimize_ewo_2 = False
buy_rsi_fast_ewo_2 = IntParameter(15, 50, default=45, optimize=is_optimize_ewo_2)
buy_rsi_ewo_2 = IntParameter(15, 50, default=35, optimize=is_optimize_ewo_2)
buy_ema_low_2 = DecimalParameter(0.90, 1.2, default=0.970, optimize=is_optimize_ewo_2)
buy_ema_high_2 = DecimalParameter(0.90, 1.2, default=1.087, optimize=is_optimize_ewo_2)
buy_ewo_high_2 = DecimalParameter(2, 12, default=4.179, optimize=is_optimize_ewo_2)
is_optimize_r_deadfish = False
buy_r_deadfish_ema = DecimalParameter(0.90, 1.2, default=1.087, optimize=is_optimize_r_deadfish)
buy_r_deadfish_bb_width = DecimalParameter(0.03, 0.75, default=0.05, optimize=is_optimize_r_deadfish)
buy_r_deadfish_bb_factor = DecimalParameter(0.90, 1.2, default=1.0, optimize=is_optimize_r_deadfish)
buy_r_deadfish_volume_factor = DecimalParameter(1, 2.5, default=1.0, optimize=is_optimize_r_deadfish)
is_optimize_r_deadfish_protection = False
buy_r_deadfish_cti = DecimalParameter(-0.6, -0.0, default=-0.5, optimize=is_optimize_r_deadfish_protection)
buy_r_deadfish_r14 = DecimalParameter(-60, -44, default=-60, optimize=is_optimize_r_deadfish_protection)
is_optimize_clucha = False
buy_clucha_bbdelta_close = DecimalParameter(0.01, 0.05, default=0.02206, optimize=is_optimize_clucha)
buy_clucha_bbdelta_tail = DecimalParameter(0.7, 1.2, default=1.02515, optimize=is_optimize_clucha)
buy_clucha_closedelta_close = DecimalParameter(0.001, 0.05, default=0.04401, optimize=is_optimize_clucha)
buy_clucha_rocr_1h = DecimalParameter(0.1, 1.0, default=0.47782, optimize=is_optimize_clucha)
buy_clucha_close_bblower = DecimalParameter(0.0005, 0.02, default=0.00799, optimize=is_optimize_clucha)
is_optimize_cofi = False
buy_ema_cofi = DecimalParameter(0.94, 1.2, default=0.97, optimize=is_optimize_cofi)
buy_fastk = IntParameter(0, 40, default=20, optimize=is_optimize_cofi)
buy_fastd = IntParameter(0, 40, default=20, optimize=is_optimize_cofi)
buy_adx = IntParameter(0, 30, default=30, optimize=is_optimize_cofi)
buy_ewo_high = DecimalParameter(2, 12, default=3.553, optimize=is_optimize_cofi)
is_optimize_cofi_protection = False
buy_cofi_cti = DecimalParameter(-0.9, -0.0, default=-0.5, optimize=is_optimize_cofi_protection)
buy_cofi_r14 = DecimalParameter(-100, -44, default=-60, optimize=is_optimize_cofi_protection)
is_optimize_gumbo = False
buy_gumbo_ema = DecimalParameter(0.9, 1.2, default=0.97, optimize=is_optimize_gumbo)
buy_gumbo_ewo_low = DecimalParameter(-12.0, 5, default=-5.585, optimize=is_optimize_gumbo)
is_optimize_gumbo_protection = False
buy_gumbo_cti = DecimalParameter(-0.9, -0.0, default=-0.5, optimize=is_optimize_gumbo_protection)
buy_gumbo_r14 = DecimalParameter(-100, -44, default=-60, optimize=is_optimize_gumbo_protection)
is_optimize_sqzmom_protection = False
buy_sqzmom_ema = DecimalParameter(0.9, 1.2, default=0.97, optimize=is_optimize_sqzmom_protection)
buy_sqzmom_ewo = DecimalParameter(-12, 12, default=0, optimize=is_optimize_sqzmom_protection)
buy_sqzmom_r14 = DecimalParameter(-100, -22, default=-50, optimize=is_optimize_sqzmom_protection)
is_optimize_nfix_39 = True
buy_nfix_39_ema = DecimalParameter(0.9, 1.2, default=0.97, optimize=is_optimize_nfix_39)
is_optimize_nfix_49_protection = False
buy_nfix_49_cti = DecimalParameter(-0.9, -0.0, default=-0.5, optimize=is_optimize_nfix_49_protection)
buy_nfix_49_r14 = DecimalParameter(-100, -44, default=-60, optimize=is_optimize_nfix_49_protection)
is_optimize_btc_safe = False
buy_btc_safe = IntParameter(-300, 50, default=-200, optimize=is_optimize_btc_safe)
buy_btc_safe_1d = DecimalParameter(-0.075, -0.025, default=-0.05, optimize=is_optimize_btc_safe)
buy_threshold = DecimalParameter(0.003, 0.012, default=0.008, optimize=is_optimize_btc_safe)
is_optimize_check = False
buy_roc_1h = IntParameter(-25, 200, default=10, optimize=is_optimize_check)
buy_bb_width_1h = DecimalParameter(0.3, 2.0, default=0.3, optimize=is_optimize_check)
# Sell params
sell_btc_safe = IntParameter(-400, -300, default=-365, optimize=False)
is_optimize_sell_stoploss = False
sell_cmf = DecimalParameter(-0.4, 0.0, default=0.0, optimize=is_optimize_sell_stoploss)
sell_ema_close_delta = DecimalParameter(0.022, 0.027, default=0.024, optimize=is_optimize_sell_stoploss)
sell_ema = DecimalParameter(0.97, 0.99, default=0.987, optimize=is_optimize_sell_stoploss)
is_optimize_deadfish = False
sell_deadfish_bb_width = DecimalParameter(0.03, 0.75, default=0.05, optimize=is_optimize_deadfish)
sell_deadfish_profit = DecimalParameter(-0.15, -0.05, default=-0.05, optimize=is_optimize_deadfish)
sell_deadfish_bb_factor = DecimalParameter(0.90, 1.20, default=1.0, optimize=is_optimize_deadfish)
sell_deadfish_volume_factor = DecimalParameter(1, 2.5, default=1.0, optimize=is_optimize_deadfish)
is_optimize_bleeding = False
sell_bleeding_cti = DecimalParameter(-0.9, -0.0, default=-0.5, optimize=is_optimize_bleeding)
sell_bleeding_r14 = DecimalParameter(-100, -44, default=-60, optimize=is_optimize_bleeding)
sell_bleeding_volume_factor = DecimalParameter(1, 2.5, default=1.0, optimize=is_optimize_bleeding)
is_optimize_cti_r = False
sell_cti_r_cti = DecimalParameter(0.55, 1, default=0.5, optimize=is_optimize_cti_r)
sell_cti_r_r = DecimalParameter(-15, 0, default=-20, optimize=is_optimize_cti_r)
# rng sell
high_offset_2 = DecimalParameter(0.99, 1.5, default=sell_params['high_offset_2'], space='sell', optimize=True)
# hard stoploss profit
pHSL = DecimalParameter(-0.200, -0.040, default=-0.08, decimals=3, space='sell', load=True)
# profit threshold 1, trigger point, SL_1 is used
pPF_1 = DecimalParameter(0.008, 0.020, default=0.016, decimals=3, space='sell', load=True)
pSL_1 = DecimalParameter(0.008, 0.020, default=0.011, decimals=3, space='sell', load=True)
# profit threshold 2, SL_2 is used
pPF_2 = DecimalParameter(0.040, 0.100, default=0.080, decimals=3, space='sell', load=True)
pSL_2 = DecimalParameter(0.020, 0.070, default=0.040, decimals=3, space='sell', load=True)
############################################################################
def informative_pairs(self):
pairs = self.dp.current_whitelist()
informative_pairs = [(pair, '1h') for pair in pairs]
return informative_pairs
def informative_1h_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
assert self.dp, "DataProvider is required for multiple timeframes."
# Get the informative pair
informative_1h = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=self.inf_1h)
# EMA
informative_1h['ema_8'] = ta.EMA(informative_1h, timeperiod=8)
informative_1h['ema_50'] = ta.EMA(informative_1h, timeperiod=50)
informative_1h['ema_100'] = ta.EMA(informative_1h, timeperiod=100)
informative_1h['ema_200'] = ta.EMA(informative_1h, timeperiod=200)
# CTI
informative_1h['cti'] = pta.cti(informative_1h["close"], length=20)
informative_1h['cti_40'] = pta.cti(informative_1h["close"], length=40)
# CRSI (3, 2, 100)
crsi_closechange = informative_1h['close'] / informative_1h['close'].shift(1)
crsi_updown = np.where(crsi_closechange.gt(1), 1.0, np.where(crsi_closechange.lt(1), -1.0, 0.0))
informative_1h['crsi'] = (ta.RSI(informative_1h['close'], timeperiod=3) + ta.RSI(crsi_updown, timeperiod=2) +
ta.ROC(informative_1h['close'], 100)) / 3
# Williams %R
informative_1h['r_96'] = williams_r(informative_1h, period=96)
informative_1h['r_480'] = williams_r(informative_1h, period=480)
# Bollinger bands
bollinger2 = qtpylib.bollinger_bands(qtpylib.typical_price(informative_1h), window=20, stds=2)
informative_1h['bb_lowerband2'] = bollinger2['lower']
informative_1h['bb_middleband2'] = bollinger2['mid']
informative_1h['bb_upperband2'] = bollinger2['upper']
informative_1h['bb_width'] = ((informative_1h['bb_upperband2'] - informative_1h['bb_lowerband2']) /
informative_1h['bb_middleband2'])
# ROC
informative_1h['roc'] = ta.ROC(dataframe, timeperiod=9)
# MOMDIV
mom = momdiv(informative_1h)
informative_1h['momdiv_buy'] = mom['momdiv_buy']
informative_1h['momdiv_sell'] = mom['momdiv_sell']
informative_1h['momdiv_coh'] = mom['momdiv_coh']
informative_1h['momdiv_col'] = mom['momdiv_col']
# RSI
informative_1h['rsi'] = ta.RSI(informative_1h, timeperiod=14)
# CMF
informative_1h['cmf'] = chaikin_money_flow(informative_1h, 20)
# Heikin Ashi
inf_heikinashi = qtpylib.heikinashi(informative_1h)
informative_1h['ha_close'] = inf_heikinashi['close']
informative_1h['rocr'] = ta.ROCR(informative_1h['ha_close'], timeperiod=168)
# T3 Average
informative_1h['T3'] = t3(informative_1h)
# Elliot
informative_1h['EWO'] = EWO(informative_1h, 50, 200)
# nfi 37
informative_1h['hl_pct_change_5'] = range_percent_change(informative_1h, 'HL', 5)
informative_1h['low_5'] = informative_1h['low'].shift().rolling(5).min()
informative_1h['safe_dump_50'] = (
(informative_1h['hl_pct_change_5'] < 0.66) | (informative_1h['close'] < informative_1h['low_5']) | (
informative_1h['close'] > informative_1h['open']))
return informative_1h
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
current_rate: float, current_profit: float, **kwargs) -> float:
# hard stoploss profit
stoploss = self.pHSL.value
pf_1 = self.pPF_1.value
sl_1 = self.pSL_1.value
pf_2 = self.pPF_2.value
sl_2 = self.pSL_2.value
buy_tag = ''
if hasattr(trade, 'buy_tag') and trade.buy_tag is not None:
buy_tag = trade.buy_tag
buy_tags = buy_tag.split()
if len(buy_tags) == 1:
for i in self.lower_trailing_list:
if i in buy_tags:
if current_profit >= 0.019:
break
elif current_profit >= 0.01:
return 0.009
# For profits between PF_1 and PF_2 the stoploss (sl_profit) used is linearly interpolated
# between the values of SL_1 and SL_2. For all profits above PL_2 the sl_profit value
# rises linearly with current profit, for profits below PF_1 the hard stoploss profit is used.
if current_profit > pf_2:
sl_profit = sl_2 + (current_profit - pf_2)
elif current_profit > pf_1:
sl_profit = sl_1 + ((current_profit - pf_1) * (sl_2 - sl_1) / (pf_2 - pf_1))
else:
sl_profit = stoploss
# Only for hyperopt invalid return
if sl_profit >= current_profit:
return -0.99
return stoploss_from_open(sl_profit, current_profit)
def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
current_profit: float, **kwargs):
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
last_candle = dataframe.iloc[-1]
previous_candle_1 = dataframe.iloc[-2]
previous_candle_2 = dataframe.iloc[-3]
buy_tag = ''
if hasattr(trade, 'buy_tag') and trade.buy_tag is not None:
buy_tag = trade.buy_tag
buy_tags = buy_tag.split()
if current_profit >= 0.01 and len(buy_tags) == 1:
for i in self.lower_trailing_list:
if i in buy_tags:
return None
if current_profit >= 0.019:
return None
if 0.019 > current_profit >= 0.0:
if (last_candle['cti'] > self.sell_cti_r_cti.value) and (last_candle['r_14'] > self.sell_cti_r_r.value):
return f"sell_profit_cti_r_0_1( {buy_tag})"
elif buy_tag in ['nfix_39 ']: # handle nfix_39 buy condition
if (
(last_candle['fisher'] > 0.39075)
and (last_candle['ha_high'] <= previous_candle_1['ha_high'])
and (previous_candle_1['ha_high'] <= previous_candle_2['ha_high'])
and (last_candle['ha_close'] <= previous_candle_1['ha_close'])
and (last_candle['ema_4'] > last_candle['ha_close'])
and (last_candle['ha_close'] * 0.99754 > last_candle['bb_middleband2'])
):
return f"sell_scalp( {buy_tag})"
# when loss is -,use sell signal.
if (
(current_profit < 0.0)
and (last_candle['close'] > last_candle['sma_9'])
and (last_candle['close'] > last_candle['ema_24'] * self.high_offset_2.value)
and (last_candle['rsi'] > 50)
and (last_candle['rsi_fast'] > last_candle['rsi_slow'])
):
return f"sell_offset( {buy_tag})"
if (
(current_profit < 0.0)
and (last_candle['close'] > last_candle['ema_49'] * 1.006)
):
return f"sell_offset2( {buy_tag})"
############################################################################
def normal_tf_indicators(self, dataframe: DataFrame) -> DataFrame:
# Bollinger bands
bollinger2 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband2'] = bollinger2['lower']
dataframe['bb_middleband2'] = bollinger2['mid']
dataframe['bb_upperband2'] = bollinger2['upper']
bollinger3 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=3)
dataframe['bb_lowerband3'] = bollinger3['lower']
dataframe['bb_middleband3'] = bollinger3['mid']
dataframe['bb_upperband3'] = bollinger3['upper']
# Other BB checks
dataframe['bb_width'] = (
(dataframe['bb_upperband2'] - dataframe['bb_lowerband2']) / dataframe['bb_middleband2'])
dataframe['bb_delta'] = ((dataframe['bb_lowerband2'] - dataframe['bb_lowerband3']) / dataframe['bb_lowerband2'])
# CCI hyperopt
for val in self.buy_cci_length.range:
dataframe[f'cci_length_{val}'] = ta.CCI(dataframe, val)
dataframe['cci'] = ta.CCI(dataframe, 26)
dataframe['cci_long'] = ta.CCI(dataframe, 170)
# RMI hyperopt
for val in self.buy_rmi_length.range:
dataframe[f'rmi_length_{val}'] = RMI(dataframe, length=val, mom=4)
# SRSI hyperopt
stoch = ta.STOCHRSI(dataframe, 15, 20, 2, 2)
dataframe['srsi_fk'] = stoch['fastk']
dataframe['srsi_fd'] = stoch['fastd']
# BinH
dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs()
dataframe['hma_50'] = qtpylib.hull_moving_average(dataframe['close'], window=50)
# SMA
dataframe['sma_9'] = ta.SMA(dataframe, timeperiod=9)
dataframe['sma_15'] = ta.SMA(dataframe, timeperiod=15)
dataframe['sma_20'] = ta.SMA(dataframe, timeperiod=20)
dataframe['sma_21'] = ta.SMA(dataframe, timeperiod=21)
dataframe['sma_28'] = ta.SMA(dataframe, timeperiod=28)
dataframe['sma_30'] = ta.SMA(dataframe, timeperiod=30)
dataframe['sma_75'] = ta.SMA(dataframe, timeperiod=75)
# CTI
dataframe['cti'] = pta.cti(dataframe["close"], length=20)
# CMF
dataframe['cmf'] = chaikin_money_flow(dataframe, 20)
# CRSI (3, 2, 100)
crsi_closechange = dataframe['close'] / dataframe['close'].shift(1)
crsi_updown = np.where(crsi_closechange.gt(1), 1.0, np.where(crsi_closechange.lt(1), -1.0, 0.0))
dataframe['crsi'] = (ta.RSI(dataframe['close'], timeperiod=3) + ta.RSI(crsi_updown, timeperiod=2) + ta.ROC(
dataframe['close'], 100)) / 3
# EMA
dataframe['ema_4'] = ta.EMA(dataframe, timeperiod=4)
dataframe['ema_8'] = ta.EMA(dataframe, timeperiod=8)
dataframe['ema_12'] = ta.EMA(dataframe, timeperiod=12)
dataframe['ema_13'] = ta.EMA(dataframe, timeperiod=13)
dataframe['ema_16'] = ta.EMA(dataframe, timeperiod=16)
dataframe['ema_20'] = ta.EMA(dataframe, timeperiod=20)
dataframe['ema_24'] = ta.EMA(dataframe, timeperiod=24)
dataframe['ema_26'] = ta.EMA(dataframe, timeperiod=26)
dataframe['ema_49'] = ta.EMA(dataframe, timeperiod=49)
dataframe['ema_50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema_100'] = ta.EMA(dataframe, timeperiod=100)
dataframe['ema_200'] = ta.EMA(dataframe, timeperiod=200)
# RSI
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
dataframe['rsi_fast'] = ta.RSI(dataframe, timeperiod=4)
dataframe['rsi_slow'] = ta.RSI(dataframe, timeperiod=20)
dataframe['rsi_84'] = ta.RSI(dataframe, timeperiod=84)
dataframe['rsi_112'] = ta.RSI(dataframe, timeperiod=112)
# Elliot
dataframe['EWO'] = EWO(dataframe, 50, 200)
# Williams %R
dataframe['r_14'] = williams_r(dataframe, period=14)
dataframe['r_32'] = williams_r(dataframe, period=32)
dataframe['r_64'] = williams_r(dataframe, period=64)
dataframe['r_96'] = williams_r(dataframe, period=96)
dataframe['r_480'] = williams_r(dataframe, period=480)
# Volume
dataframe['volume_mean_4'] = dataframe['volume'].rolling(4).mean().shift(1)
dataframe['volume_mean_12'] = dataframe['volume'].rolling(12).mean().shift(1)
dataframe['volume_mean_24'] = dataframe['volume'].rolling(24).mean().shift(1)
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
# Heiken Ashi
heikinashi = qtpylib.heikinashi(dataframe)
dataframe['ha_open'] = heikinashi['open']
dataframe['ha_close'] = heikinashi['close']
dataframe['ha_high'] = heikinashi['high']
dataframe['ha_low'] = heikinashi['low']
# BB 40
bollinger2_40 = qtpylib.bollinger_bands(ha_typical_price(dataframe), window=40, stds=2)
dataframe['bb_lowerband2_40'] = bollinger2_40['lower']
dataframe['bb_middleband2_40'] = bollinger2_40['mid']
dataframe['bb_upperband2_40'] = bollinger2_40['upper']
# ClucHA
dataframe['bb_delta_cluc'] = (dataframe['bb_middleband2_40'] - dataframe['bb_lowerband2_40']).abs()
dataframe['ha_closedelta'] = (dataframe['ha_close'] - dataframe['ha_close'].shift()).abs()
dataframe['tail'] = (dataframe['ha_close'] - dataframe['ha_low']).abs()
dataframe['ema_slow'] = ta.EMA(dataframe['ha_close'], timeperiod=50)
dataframe['rocr'] = ta.ROCR(dataframe['ha_close'], timeperiod=28)
# Cofi
stoch_fast = ta.STOCHF(dataframe, 5, 3, 0, 3, 0)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
dataframe['adx'] = ta.ADX(dataframe)
# Profit Maximizer - PMAX
dataframe['pm'], dataframe['pmx'] = pmax(heikinashi, ma_type=1, length=9, multiplier=27, period=10, src=3)
dataframe['source'] = (dataframe['high'] + dataframe['low'] + dataframe['open'] + dataframe['close'])/4
dataframe['pmax_thresh'] = ta.EMA(dataframe['source'], timeperiod=9)
# MOMDIV
mom = momdiv(dataframe)
dataframe['momdiv_buy'] = mom['momdiv_buy']
dataframe['momdiv_sell'] = mom['momdiv_sell']
dataframe['momdiv_coh'] = mom['momdiv_coh']
dataframe['momdiv_col'] = mom['momdiv_col']
# T3 Average
dataframe['T3'] = t3(dataframe)
# True range
dataframe['trange'] = ta.TRANGE(dataframe)
# KC
dataframe['range_ma_28'] = ta.SMA(dataframe['trange'], 28)
dataframe['kc_upperband_28_1'] = dataframe['sma_28'] + dataframe['range_ma_28']
dataframe['kc_lowerband_28_1'] = dataframe['sma_28'] - dataframe['range_ma_28']
# KC 20
dataframe['range_ma_20'] = ta.SMA(dataframe['trange'], 20)
dataframe['kc_upperband_20_2'] = dataframe['sma_20'] + dataframe['range_ma_20'] * 2
dataframe['kc_lowerband_20_2'] = dataframe['sma_20'] - dataframe['range_ma_20'] * 2
dataframe['kc_bb_delta'] = (dataframe['kc_lowerband_20_2'] - dataframe['bb_lowerband2']) / dataframe[
'bb_lowerband2'] * 100
# Linreg
dataframe['hh_20'] = ta.MAX(dataframe['high'], 20)
dataframe['ll_20'] = ta.MIN(dataframe['low'], 20)
dataframe['avg_hh_ll_20'] = (dataframe['hh_20'] + dataframe['ll_20']) / 2
dataframe['avg_close_20'] = ta.SMA(dataframe['close'], 20)
dataframe['avg_val_20'] = (dataframe['avg_hh_ll_20'] + dataframe['avg_close_20']) / 2
dataframe['linreg_val_20'] = ta.LINEARREG(dataframe['close'] - dataframe['avg_val_20'], 20, 0)
# fisher
rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe["fisher"] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
# Modified Elder Ray Index
dataframe['moderi_96'] = moderi(dataframe, 96)
# vmap indicators
vwap_low, vwap, vwap_high = vmap_b(dataframe, 20, 1)
dataframe['vwap_low'] = vwap_low
dataframe['tcp_percent_4'] = top_percent_change(dataframe, 4)
return dataframe
############################################################################
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# The indicators for the 1h informative timeframe
informative_1h = self.informative_1h_indicators(dataframe, metadata)
dataframe = merge_informative_pair(dataframe, informative_1h, self.timeframe, self.inf_1h, ffill=True)
# The indicators for the normal (5m) timeframe
dataframe = self.normal_tf_indicators(dataframe)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
conditions = []
dataframe.loc[:, 'buy_tag'] = ''
is_dip = (
(dataframe[f'rmi_length_{self.buy_rmi_length.value}'] < self.buy_rmi.value) &
(dataframe[f'cci_length_{self.buy_cci_length.value}'] <= self.buy_cci.value) &
(dataframe['srsi_fk'] < self.buy_srsi_fk.value)
)
# is_sqz_off = (
# (dataframe['bb_lowerband2'] < dataframe['kc_lowerband_28_1']) &
# (dataframe['bb_upperband2'] > dataframe['kc_upperband_28_1'])
# )
is_break = (
(dataframe['bb_delta'] > self.buy_bb_delta.value) &
(dataframe['bb_width'] > self.buy_bb_width.value) &
(dataframe['closedelta'] > dataframe['close'] * 17.922 / 1000) & # use origin bb_rpb_tsl value
(dataframe['close'] < dataframe['bb_lowerband3'] * self.buy_bb_factor.value)
)
is_local_uptrend = ( # from NFI next gen, credit goes to @iterativ
(dataframe['ema_26'] > dataframe['ema_12']) &
(dataframe['ema_26'] - dataframe['ema_12'] > dataframe['open'] * self.buy_ema_diff.value) &
(dataframe['ema_26'].shift() - dataframe['ema_12'].shift() > dataframe['open'] / 100) &
(dataframe['close'] < dataframe['bb_lowerband2'] * self.buy_bb_factor.value) &
(dataframe['closedelta'] > dataframe['close'] * self.buy_closedelta.value / 1000)
)
is_local_uptrend2 = ( # use origin bb_rpb_tsl value
(dataframe['ema_26'] > dataframe['ema_12']) &
(dataframe['ema_26'] - dataframe['ema_12'] > dataframe['open'] * 0.026) &
(dataframe['ema_26'].shift() - dataframe['ema_12'].shift() > dataframe['open'] / 100) &
(dataframe['close'] < dataframe['bb_lowerband2'] * self.buy_bb_factor.value) &
(dataframe['closedelta'] > dataframe['close'] * 17.922 / 1000)
)
is_local_dip = (
(dataframe['ema_26'] > dataframe['ema_12']) &
(dataframe['ema_26'] - dataframe['ema_12'] > dataframe['open'] * self.buy_ema_diff_local_dip.value) &
(dataframe['ema_26'].shift() - dataframe['ema_12'].shift() > dataframe['open'] / 100) &
(dataframe['close'] < dataframe['ema_20'] * self.buy_ema_high_local_dip.value) &
(dataframe['rsi'] < self.buy_rsi_local_dip.value) &
(dataframe['crsi'] > self.buy_crsi_local_dip.value) &
(dataframe['closedelta'] > dataframe['close'] * self.buy_closedelta_local_dip.value / 1000)
)
is_ewo = ( # from SMA offset
(dataframe['rsi_fast'] < self.buy_rsi_fast.value) &
(dataframe['close'] < dataframe['ema_8'] * self.buy_ema_low.value) &
(dataframe['EWO'] > self.buy_ewo.value) &
(dataframe['close'] < dataframe['ema_16'] * self.buy_ema_high.value) &
(dataframe['rsi'] < self.buy_rsi.value)
)
# is_ewo_2 = (
# (dataframe['rsi_fast'] < self.buy_rsi_fast_ewo_2.value) &
# (dataframe['close'] < dataframe['ema_8'] * self.buy_ema_low_2.value) &
# (dataframe['EWO'] > self.buy_ewo_high_2.value) &
# (dataframe['close'] < dataframe['ema_16'] * self.buy_ema_high_2.value) &
# (dataframe['rsi'] < self.buy_rsi_ewo_2.value)
# )
# is_r_deadfish = ( # reverse deadfish
# (dataframe['ema_100'] < dataframe['ema_200'] * self.buy_r_deadfish_ema.value) &
# (dataframe['bb_width'] > self.buy_r_deadfish_bb_width.value) &
# (dataframe['close'] < dataframe['bb_middleband2'] * self.buy_r_deadfish_bb_factor.value) &
# (dataframe['volume_mean_12'] > dataframe['volume_mean_24'] * self.buy_r_deadfish_volume_factor.value) &
# (dataframe['cti'] < self.buy_r_deadfish_cti.value) &
# (dataframe['r_14'] < self.buy_r_deadfish_r14.value)
# )
is_clucha = (
(dataframe['rocr_1h'].gt(self.buy_clucha_rocr_1h.value)) &
(dataframe['bb_lowerband2_40'].shift().gt(0)) &
(dataframe['bb_delta_cluc'].gt(dataframe['ha_close'] * self.buy_clucha_bbdelta_close.value)) &
(dataframe['ha_closedelta'].gt(dataframe['ha_close'] * self.buy_clucha_closedelta_close.value)) &
(dataframe['tail'].lt(dataframe['bb_delta_cluc'] * self.buy_clucha_bbdelta_tail.value)) &
(dataframe['ha_close'].lt(dataframe['bb_lowerband2_40'].shift())) &
(dataframe['ha_close'].le(dataframe['ha_close'].shift()))
)
is_clucha2 = (
(dataframe['rocr_1h'].gt(self.buy_clucha_rocr_1h.value)) &
(dataframe['ha_close'] < dataframe['ema_slow']) &
(dataframe['ha_close'] < self.buy_clucha_close_bblower.value * dataframe['bb_lowerband2_40'])
)
is_cofi = ( # Modified from cofi, credit goes to original author "slack user CofiBit"
(dataframe['open'] < dataframe['ema_8'] * self.buy_ema_cofi.value) &
(qtpylib.crossed_above(dataframe['fastk'], dataframe['fastd'])) &
(dataframe['fastk'] < self.buy_fastk.value) &
(dataframe['fastd'] < self.buy_fastd.value) &
(dataframe['adx'] > self.buy_adx.value) &
(dataframe['EWO'] > self.buy_ewo_high.value) &
(dataframe['cti'] < self.buy_cofi_cti.value) &
(dataframe['r_14'] < self.buy_cofi_r14.value)
)
# is_gumbo = ( # Modified from gumbo1, creadit goes to original author @raph92
# (dataframe['EWO'] < self.buy_gumbo_ewo_low.value) &
# (dataframe['bb_middleband2_1h'] >= dataframe['T3_1h']) &
# (dataframe['T3'] <= dataframe['ema_8'] * self.buy_gumbo_ema.value) &
# (dataframe['cti'] < self.buy_gumbo_cti.value) &
# (dataframe['r_14'] < self.buy_gumbo_r14.value)
# )
# is_sqzmom = ( # Modified from squeezeMomentum, credit goes to original author @LazyBear of TradingView
# is_sqz_off &
# (dataframe['linreg_val_20'].shift(2) > dataframe['linreg_val_20'].shift(1)) &
# (dataframe['linreg_val_20'].shift(1) < dataframe['linreg_val_20']) &
# (dataframe['linreg_val_20'] < 0) &
# (dataframe['close'] < dataframe['ema_13'] * self.buy_sqzmom_ema.value) &
# (dataframe['EWO'] < self.buy_sqzmom_ewo.value) &
# (dataframe['r_14'] < self.buy_sqzmom_r14.value)
# )
# NFI quick mode, credit goes to @iterativ
is_nfi_32 = ( # NFIX 26
(dataframe['rsi_slow'] < dataframe['rsi_slow'].shift(1)) &
(dataframe['rsi_fast'] < 46) &
(dataframe['rsi'] > 19) &
(dataframe['close'] < dataframe['sma_15'] * 0.942) &
(dataframe['cti'] < -0.86)
)
is_nfi_33 = (
(dataframe['close'] < (dataframe['ema_13'] * 0.978)) &
(dataframe['EWO'] > 8) &
(dataframe['cti'] < -0.88) &
(dataframe['rsi'] < 32) &
(dataframe['r_14'] < -98.0) &
(dataframe['volume'] < (dataframe['volume_mean_4'] * 2.5))
)
is_nfi_38 = (
(dataframe['pm'] > dataframe['pmax_thresh']) &
(dataframe['close'] < dataframe['sma_75'] * 0.98) &
(dataframe['EWO'] < -4.4) &
(dataframe['cti'] < -0.95) &
(dataframe['r_14'] < -97) &
(dataframe['crsi_1h'] > 0.5)
)
is_nfix_5 = (
(dataframe['ema_200_1h'] > dataframe['ema_200_1h'].shift(12)) &
(dataframe['ema_200_1h'].shift(12) > dataframe['ema_200_1h'].shift(24)) &
(dataframe['close'] < dataframe['sma_75'] * 0.932) &
(dataframe['EWO'] > 3.6) &
(dataframe['cti'] < -0.9) &
(dataframe['r_14'] < -97.0)
)
is_nfix_39 = (
(dataframe['ema_200_1h'] > dataframe['ema_200_1h'].shift(12)) &
(dataframe['ema_200_1h'].shift(12) > dataframe['ema_200_1h'].shift(24)) &
(dataframe['bb_lowerband2_40'].shift().gt(0)) &
(dataframe['bb_delta_cluc'].gt(dataframe['close'] * 0.056)) &
(dataframe['closedelta'].gt(dataframe['close'] * 0.01)) &
(dataframe['tail'].lt(dataframe['bb_delta_cluc'] * 0.5)) &
(dataframe['close'].lt(dataframe['bb_lowerband2_40'].shift())) &
(dataframe['close'].le(dataframe['close'].shift())) &
(dataframe['close'] > dataframe['ema_13'] * self.buy_nfix_39_ema.value)
)
is_nfix_49 = (
(dataframe['ema_26'].shift(3) > dataframe['ema_12'].shift(3)) &
(dataframe['ema_26'].shift(3) - dataframe['ema_12'].shift(3) > dataframe['open'].shift(3) * 0.032) &
(dataframe['ema_26'].shift(9) - dataframe['ema_12'].shift(9) > dataframe['open'].shift(3) / 100) &
(dataframe['close'].shift(3) < dataframe['ema_20'].shift(3) * 0.916) &
(dataframe['rsi'].shift(3) < 32.5) &
(dataframe['crsi'].shift(3) > 18.0) &
(dataframe['cti'] < self.buy_nfix_49_cti.value) &
(dataframe['r_14'] < self.buy_nfix_49_r14.value)
)
is_nfi7_33 = (
(dataframe['moderi_96']) &
(dataframe['cti'] < -0.88) &
(dataframe['close'] < (dataframe['ema_13'] * 0.988)) &
(dataframe['EWO'] > 6.4) &
(dataframe['rsi'] < 32.0) &
(dataframe['volume'] < (dataframe['volume_mean_4'] * 2.0))
)
is_nfi7_37 = (
(dataframe['pm'] > dataframe['pmax_thresh']) &
(dataframe['close'] < dataframe['sma_75'] * 0.98) &
(dataframe['EWO'] > 9.8) &
(dataframe['rsi'] < 56.0) &
(dataframe['cti'] < -0.7) &
(dataframe['safe_dump_50_1h'])
)
is_vwap = (
(dataframe['close'] < dataframe['vwap_low']) &
(dataframe['tcp_percent_4'] > 0.04) &
(dataframe['cti'] < -0.8) &
(dataframe['rsi'] < 35) &
(dataframe['rsi_84'] < 60) &
(dataframe['rsi_112'] < 60) &
(dataframe['volume'] > 0)
)
# Additional Check
is_bb_checked = is_dip & is_break
# Condition Append
conditions.append(is_bb_checked) # ~2.32 / 91.1% / 46.27% D
dataframe.loc[is_bb_checked, 'buy_tag'] += 'bb '
conditions.append(is_local_uptrend) # ~3.28 / 92.4% / 69.72%
dataframe.loc[is_local_uptrend, 'buy_tag'] += 'local_uptrend '
conditions.append(is_local_dip) # ~0.76 / 91.1% / 15.54%
dataframe.loc[is_local_dip, 'buy_tag'] += 'local_dip '
conditions.append(is_ewo) # ~0.92 / 92.0% / 43.74% D
dataframe.loc[is_ewo, 'buy_tag'] += 'ewo '
# conditions.append(is_ewo_2) # ~2.86 / 91.5% / 33.31% D
# dataframe.loc[is_ewo_2, 'buy_tag'] += 'ewo2 '
# conditions.append(is_r_deadfish) # ~0.99 / 86.9% / 21.93% D
# dataframe.loc[is_r_deadfish, 'buy_tag'] += 'r_deadfish '
conditions.append(is_clucha) # ~7.2 / 92.5% / 97.98% D
dataframe.loc[is_clucha, 'buy_tag'] += 'clucHA '
conditions.append(is_clucha2)
dataframe.loc[is_clucha2, 'buy_tag'] += 'clucHA2 '
conditions.append(is_cofi) # ~0.4 / 94.4% / 9.59% D
dataframe.loc[is_cofi, 'buy_tag'] += 'cofi '
# conditions.append(is_gumbo) # ~2.63 / 90.6% / 41.49% D
# dataframe.loc[is_gumbo, 'buy_tag'] += 'gumbo '
# conditions.append(is_sqzmom) # ~3.14 / 92.4% / 64.14% D
# dataframe.loc[is_sqzmom, 'buy_tag'] += 'sqzmom '
conditions.append(is_nfi_32) # ~0.78 / 92.0 % / 37.41% D
dataframe.loc[is_nfi_32, 'buy_tag'] += 'nfi_32 '
conditions.append(is_nfi_33) # ~0.11 / 100% D
dataframe.loc[is_nfi_33, 'buy_tag'] += 'nfi_33 '
conditions.append(is_nfi_38) # ~1.13 / 88.5% / 31.34% D
dataframe.loc[is_nfi_38, 'buy_tag'] += 'nfi_38 '
conditions.append(is_nfix_5) # ~0.25 / 97.7% / 6.53% D
dataframe.loc[is_nfix_5, 'buy_tag'] += 'nfix_5 '
conditions.append(is_nfix_39) # ~5.33 / 91.8% / 58.57% D
dataframe.loc[is_nfix_39, 'buy_tag'] += 'nfix_39 '
conditions.append(is_nfix_49) # ~0.33 / 100% / 0% D
dataframe.loc[is_nfix_49, 'buy_tag'] += 'nfix_49 '
conditions.append(is_nfi7_33) # ~0.71 / 91.3% / 28.94% D
dataframe.loc[is_nfi7_33, 'buy_tag'] += 'nfi7_33 '
conditions.append(is_nfi7_37) # ~0.46 / 92.6% / 17.05% D
dataframe.loc[is_nfi7_37, 'buy_tag'] += 'nfi7_37 '
conditions.append(is_vwap)
dataframe.loc[is_vwap, 'buy_tag'] += 'vwap '
conditions.append(is_local_uptrend2)
dataframe.loc[is_local_uptrend2, 'buy_tag'] += 'local_uptrend2 '
if conditions:
dataframe.loc[
reduce(lambda x, y: x | y, conditions),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[(dataframe['volume'] > 0), 'sell'] = 0
return dataframe
# PMAX
def pmax(df, period, multiplier, length, ma_type, src):
period = int(period)
multiplier = int(multiplier)
length = int(length)
ma_type = int(ma_type)
src = int(src)
mavalue = f'MA_{ma_type}_{length}'
atr = f'ATR_{period}'
if src == 1:
masrc = df["close"]
elif src == 2:
masrc = (df["high"] + df["low"]) / 2
elif src == 3:
masrc = (df["high"] + df["low"] + df["close"] + df["open"]) / 4
if ma_type == 1:
mavalue = ta.EMA(masrc, timeperiod=length)
elif ma_type == 2:
mavalue = ta.DEMA(masrc, timeperiod=length)
elif ma_type == 3:
mavalue = ta.T3(masrc, timeperiod=length)
elif ma_type == 4:
mavalue = ta.SMA(masrc, timeperiod=length)
elif ma_type == 5:
mavalue = VIDYA(df, length=length)
elif ma_type == 6:
mavalue = ta.TEMA(masrc, timeperiod=length)
elif ma_type == 7:
mavalue = ta.WMA(df, timeperiod=length)
elif ma_type == 8:
mavalue = vwma(df, length)
elif ma_type == 9:
mavalue = zema(df, period=length)
df[atr] = ta.ATR(df, timeperiod=period)
df['basic_ub'] = mavalue + ((multiplier/10) * df[atr])
df['basic_lb'] = mavalue - ((multiplier/10) * df[atr])
basic_ub = df['basic_ub'].values
final_ub = np.full(len(df), 0.00)
basic_lb = df['basic_lb'].values
final_lb = np.full(len(df), 0.00)
for i in range(period, len(df)):
final_ub[i] = basic_ub[i] if (
basic_ub[i] < final_ub[i - 1]
or mavalue[i - 1] > final_ub[i - 1]) else final_ub[i - 1]
final_lb[i] = basic_lb[i] if (
basic_lb[i] > final_lb[i - 1]
or mavalue[i - 1] < final_lb[i - 1]) else final_lb[i - 1]
df['final_ub'] = final_ub
df['final_lb'] = final_lb
pm_arr = np.full(len(df), 0.00)
for i in range(period, len(df)):
pm_arr[i] = (
final_ub[i] if (pm_arr[i - 1] == final_ub[i - 1]
and mavalue[i] <= final_ub[i])
else final_lb[i] if (
pm_arr[i - 1] == final_ub[i - 1]
and mavalue[i] > final_ub[i]) else final_lb[i]
if (pm_arr[i - 1] == final_lb[i - 1]
and mavalue[i] >= final_lb[i]) else final_ub[i]
if (pm_arr[i - 1] == final_lb[i - 1]
and mavalue[i] < final_lb[i]) else 0.00)
pm = Series(pm_arr)
# Mark the trend direction up/down
pmx = np.where((pm_arr > 0.00), np.where((mavalue < pm_arr), 'down', 'up'), np.NaN)
return pm, pmx
# Mom DIV
def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = 20, bb_dev: float = 2.0,
lookback: int = 30) -> DataFrame:
mom: Series = ta.MOM(dataframe, timeperiod=mom_length)
upperband, middleband, lowerband = ta.BBANDS(mom, timeperiod=bb_length, nbdevup=bb_dev, nbdevdn=bb_dev, ma_type=0)
buy = qtpylib.crossed_below(mom, lowerband)
sell = qtpylib.crossed_above(mom, upperband)
hh = dataframe['high'].rolling(lookback).max()
ll = dataframe['low'].rolling(lookback).min()
coh = dataframe['high'] >= hh
col = dataframe['low'] <= ll
df = DataFrame({
"momdiv_mom": mom,
"momdiv_upperb": upperband,
"momdiv_lowerb": lowerband,
"momdiv_buy": buy,
"momdiv_sell": sell,
"momdiv_coh": coh,
"momdiv_col": col,
}, index=dataframe['close'].index)
return df
def t3(dataframe, length=5):
"""
T3 Average by HPotter on Tradingview
https://www.tradingview.com/script/qzoC9H1I-T3-Average/
"""
df = dataframe.copy()
df['xe1'] = ta.EMA(df['close'], timeperiod=length)
df['xe2'] = ta.EMA(df['xe1'], timeperiod=length)
df['xe3'] = ta.EMA(df['xe2'], timeperiod=length)
df['xe4'] = ta.EMA(df['xe3'], timeperiod=length)
df['xe5'] = ta.EMA(df['xe4'], timeperiod=length)
df['xe6'] = ta.EMA(df['xe5'], timeperiod=length)
b = 0.7
c1 = -b * b * b
c2 = 3 * b * b + 3 * b * b * b
c3 = -6 * b * b - 3 * b - 3 * b * b * b
c4 = 1 + 3 * b + b * b * b + 3 * b * b
df['T3Average'] = c1 * df['xe6'] + c2 * df['xe5'] + c3 * df['xe4'] + c4 * df['xe3']
return df['T3Average']
================================================
FILE: strategies/BBRSI/BBRSI.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class bbrsi(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 0.21547444718127343,
"21": 0.054918778723794665,
"48": 0.013037720775643222,
"125": 0
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.3603667187598833
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
timeframe = '4h'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
# plot_config = {
# 'main_plot': {
# 'tema': {},
# 'sar': {'color': 'white'},
# },
# 'subplots': {
# "MACD": {
# 'macd': {'color': 'blue'},
# 'macdsignal': {'color': 'orange'},
# },
# "RSI": {
# 'rsi': {'color': 'red'},
# }
# }
# }
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger bands
bollinger_1sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['bb_upperband_1sd'] = bollinger_1sd['upper']
dataframe['bb_lowerband_1sd'] = bollinger_1sd['lower']
bollinger_4sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=4)
dataframe['bb_lowerband_4sd'] = bollinger_4sd['lower']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 25) &
(dataframe['close'] < dataframe['bb_lowerband_1sd'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 95) &
(dataframe['close'] > dataframe['bb_upperband_1sd'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSI2/BBRSI2.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class BBRSI2(IStrategy):
minimal_roi = {
"0": 0.30,
"120": 0.20,
"360": 0.15,
"720": 0
}
stoploss = -0.20
timeframe = '1m'
trailing_stop = True
order_types = {
"buy": "limit",
"sell": "limit",
"emergencysell": "market",
"forcebuy": "market",
"forcesell": "market",
"stoploss": "market",
"stoploss_on_exchange": True,
"stoploss_on_exchange_interval": 60,
"stoploss_on_exchange_limit_ratio": 0.99,
}
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# Bollinger Bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
# dataframe['bb_upperband'] = bollinger['upper']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 35)
& (dataframe['close'] < dataframe['bb_lowerband'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 75)
& (dataframe['close'] > dataframe['bb_middleband'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSI21/BBRSI21.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class BBRSI21(IStrategy):
"""
author@: Gert Wohlgemuth
converted from:
https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/BbandRsi.cs
"""
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.22766,
"31": 0.06155,
"78": 0.03227,
"105": 0
}
# Trailing stop:
trailing_stop = True
trailing_stop_positive = 0.17832
trailing_stop_positive_offset = 0.24807
trailing_only_offset_is_reached = True
# Optimal stoploss designed for the strategy
stoploss = -0.30054
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators.
Can be a copy of the corresponding method from the strategy,
or will be loaded from the strategy.
Must align to populate_indicators used (either from this File, or from the strategy)
Only used when --spaces does not include buy
"""
dataframe.loc[
(
(dataframe['close'] < dataframe['bb_lowerband']) &
# (dataframe['mfi'] > 16) &
# (dataframe['adx'] > 25) &
(dataframe['rsi'] < 21)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators.
Can be a copy of the corresponding method from the strategy,
or will be loaded from the strategy.
Must align to populate_indicators used (either from this File, or from the strategy)
Only used when --spaces does not include sell
"""
dataframe.loc[
(
(dataframe['close'] > dataframe['bb_upperband']) &
(dataframe['rsi'] > 99)
# (qtpylib.crossed_above(
# dataframe['macdsignal'], dataframe['macd']
# )) &
# (dataframe['fastd'] > 54)
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSI3366/BBRSI3366.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# --------------------------------
class BBRSI3366(IStrategy):
"""
author@: Gert Wohlgemuth
converted from:
https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/BbandRsi.cs
"""
# Minimal ROI designed for the strategy.
# adjust based on market conditions. We would recommend to keep it low for quick turn arounds
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"0": 0.09521,
"13": 0.07341,
"30": 0.01468,
"85": 0
}
# Trailing stop:
trailing_stop = True
trailing_stop_positive = 0.05069
trailing_stop_positive_offset = 0.06189
trailing_only_offset_is_reached = False
# Optimal stoploss designed for the strategy
stoploss = -0.33233
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
# SAR
dataframe['sar'] = ta.SAR(dataframe)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators.
Can be a copy of the corresponding method from the strategy,
or will be loaded from the strategy.
Must align to populate_indicators used (either from this File, or from the strategy)
Only used when --spaces does not include buy
"""
dataframe.loc[
(
# (qtpylib.crossed_above(
# dataframe['close'], dataframe['bb_lowerband']
# )) &
# (dataframe['close'] < dataframe['bb_lowerband']) &
# (dataframe['mfi'] < 16) &
# (dataframe['adx'] > 25) &
(dataframe['rsi'] < 33)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators.
Can be a copy of the corresponding method from the strategy,
or will be loaded from the strategy.
Must align to populate_indicators used (either from this File, or from the strategy)
Only used when --spaces does not include sell
"""
dataframe.loc[
(
# (qtpylib.crossed_above(
# dataframe['close'], dataframe['bb_upperband']
# )) &
(dataframe['close'] > dataframe['bb_upperband']) &
(dataframe['rsi'] > 66) #&
# (qtpylib.crossed_above(
# dataframe['sar'], dataframe['close']
# ))
# (qtpylib.crossed_above(
# dataframe['macdsignal'], dataframe['macd']
# )) &
# (dataframe['fastd'] > 54)
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSI4cust/BBRSI4cust.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IStrategy, IntParameter)
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# This class is a sample. Feel free to customize it.
class BBRSI4cust(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 3
# Can this strategy go short?
can_short: bool = False
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
# "60": 0.01,
# "30": 0.02,
"0": 0.003
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.1
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal timeframe for the strategy.
timeframe = '15m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the config.
use_exit_signal = True
exit_profit_only = False
ignore_roi_if_entry_signal = False
# Hyperoptable parameters
# buy_rsi = IntParameter(low=25, high=35, default=35, space='buy', optimize=True, load=True)
buy_bb = IntParameter(low=1, high=4, default=1, space='buy', optimize=True, load=True)
buy_di = IntParameter(low=10, high=20, default=20, space='buy', optimize=True, load=True)
sell_bb = IntParameter(low=1, high=4, default=1, space='sell', optimize=True, load=True)
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'entry': 'limit',
'exit': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'entry': 'gtc',
'exit': 'gtc'
}
plot_config = {
'main_plot': {
'bb_lowerband': {'color': 'blue'},
'bb_middleband': {'color': 'orange'},
'bb_upperband': {'color': 'blue'},
},
'subplots': {
"DI": {
'plus_di': {'color': 'green'},
'di_overbought': {'color': 'black'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Momentum Indicators
# ------------------------------------
# Plus Directional Indicator / Movement
dataframe['plus_di'] = ta.PLUS_DI(dataframe)
dataframe['di_overbought'] = 20
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger Bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=self.buy_bb.value)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
bollinger1 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=self.sell_bb.value)
dataframe['bb_lowerband1'] = bollinger1['lower']
dataframe['bb_middleband1'] = bollinger1['mid']
dataframe['bb_upperband1'] = bollinger1['upper']
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# Signal: RSI crosses above 30
(dataframe['plus_di'] > self.buy_di.value) &
(qtpylib.crossed_below(dataframe['low'], dataframe['bb_lowerband'])) &
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# Signal: RSI crosses above 70
(qtpylib.crossed_above(dataframe['high'], dataframe['bb_middleband1'])) &
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'exit_long'] = 1
return dataframe
def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, current_profit: float, **kwargs):
"""
Sell only when matching some criteria other than those used to generate the sell signal
:return: str sell_reason, if any, otherwise None
"""
# get dataframe
dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
# get the current candle
current_candle = dataframe.iloc[-1].squeeze()
# if (qtpylib.crossed_above(current_candle['high'], dataframe['bb_middleband1'])) == True:
if (qtpylib.crossed_above(current_rate, current_candle['bb_middleband1'])):
return "bb_profit_sell"
# else, hold
return None
================================================
FILE: strategies/BBRSINaiveStrategy/BBRSINaiveStrategy.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class BBRSINaiveStrategy(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"60": 0.01,
"30": 0.02,
"0": 0.04
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.1
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
timeframe = '15m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'bb_upperband': {'color': 'green'},
'bb_midband': {'color': 'orange'},
'bb_lowerband': {'color': 'red'},
},
'subplots': {
"RSI": {
'rsi': {'color': 'yellow'},
}
}
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger bands
bollinger = qtpylib.bollinger_bands(
qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_upperband'] = bollinger['upper']
dataframe['bb_midband'] = bollinger['mid']
dataframe['bb_lowerband'] = bollinger['lower']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 25) & # Signal: RSI is greater 25
# Signal: price is less than lower bb
(dataframe['close'] < dataframe['bb_lowerband'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 70) & # Signal: RSI is greater 70
# Signal: price is greater than mid bb
(dataframe['close'] > dataframe['bb_midband'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSIOptim2020Strategy/BBRSIOptim2020Strategy.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# This class is a sample. Feel free to customize it.
class BBRSIOptim2020Strategy(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 0.336,
"40": 0.072,
"218": 0.021,
"459": 0
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.331
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
'subplots': {
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger Bands
bollinger_1sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['bb_middleband_1sd'] = bollinger_1sd['mid']
bollinger_3sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=3)
dataframe['bb_lowerband_3sd'] = bollinger_3sd['lower']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# (dataframe['rsi'] > 12) &
(dataframe['close'] < dataframe['bb_lowerband_3sd'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# (dataframe['rsi'] > 96) &
(dataframe['close'] > dataframe['bb_middleband_1sd'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSIOptimStrategy/BBRSIOptimStrategy.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# This class is a sample. Feel free to customize it.
class BBRSIOptimStrategy(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 0.323,
"107": 0.097,
"150": 0.019,
"238": 0
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.344
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
'subplots': {
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger Bands
bollinger_1sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['bb_lowerband_1sd'] = bollinger_1sd['lower']
bollinger_2sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband_2sd'] = bollinger_2sd['lower']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 12) &
(dataframe['close'] < dataframe['bb_lowerband_2sd'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 96) &
(dataframe['close'] > dataframe['bb_lowerband_1sd'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSIOptimizedStrategy/BBRSIOptimizedStrategy.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
# Based on the Hyperopt results when running against BBRISHyperopt
class BBRSIOptimizedStrategy(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 0.186,
"37": 0.074,
"89": 0.033,
"195": 0
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.295
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
'main_plot': {
'bb_upperband': {'color': 'green'},
'bb_midband': {'color': 'orange'},
'bb_lowerband': {'color': 'red'},
},
'subplots': {
"RSI": {
'rsi': {'color': 'yellow'},
}
}
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger bands
bollinger_1sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['bb_midband_1sd'] = bollinger_1sd['mid']
bollinger_3sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=3)
dataframe['bb_lowerband_3sd'] = bollinger_3sd['lower']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# (dataframe['rsi'] > 38) & # Signal: RSI is greater 38
(dataframe['close'] < dataframe['bb_lowerband_3sd']) # Signal: price is less than lower bb 2sd
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 64) & # Signal: RSI is greater 88
(dataframe['close'] > dataframe['bb_midband_1sd']) # Signal: price is greater than mid bb
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSIS/BBRSIS.py
================================================
import talib.abstract as ta
from pandas import DataFrame
from technical.util import resample_to_interval, resampled_merge
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.strategy import IStrategy, merge_informative_pair
class BBRSIS(IStrategy):
"""
Default Strategy provided by freqtrade bot.
You can override it with your own strategy
"""
# Minimal ROI designed for the strategy
minimal_roi = {
"0": 0.30,
}
# Optimal stoploss designed for the strategy
stoploss = -0.99
# Optimal ticker interval for the strategy
ticker_interval = '5m'
# Optional order type mapping
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
}
# Optional time in force for orders
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc',
}
def get_ticker_indicator(self):
return int(self.timeframe[:-1])
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
# Momentum Indicator
# ------------------------------------
# RSIs
dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5)
dataframe['sma75'] = ta.SMA(dataframe, timeperiod=75)
dataframe['sma200'] = ta.SMA(dataframe, timeperiod=200)
dataframe_short = resample_to_interval(dataframe, self.get_ticker_indicator() * 3)
dataframe_medium = resample_to_interval(dataframe, self.get_ticker_indicator() * 6)
dataframe_long = resample_to_interval(dataframe, self.get_ticker_indicator() * 10)
dataframe_short['rsi'] = ta.RSI(dataframe_short, timeperiod=20)
dataframe_medium['rsi'] = ta.RSI(dataframe_medium, timeperiod=20)
dataframe_long['rsi'] = ta.RSI(dataframe_long, timeperiod=20)
dataframe = resampled_merge(dataframe, dataframe_short)
dataframe = resampled_merge(dataframe, dataframe_medium)
dataframe = resampled_merge(dataframe, dataframe_long)
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=20)
dataframe.fillna(method='ffill', inplace = True)
# Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=3)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['close'] < dataframe['bb_lowerband']) &
(dataframe['sma5'] >= dataframe['sma75']) &
(dataframe['sma75'] >= dataframe['sma200']) &
(dataframe['rsi'] < (dataframe['resample_{}_rsi'.format(self.get_ticker_indicator() * 3)] - 5)) &
(dataframe['volume'] > 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['close'] > dataframe['bb_middleband']) &
(dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*3)] + 5) &
(dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*6)]) &
(dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*10)]) &
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSIStrategy/BBRSIStrategy.py
================================================
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# isort: skip_file
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class BBRSIStrategy(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 0.21547444718127343,
"21": 0.054918778723794665,
"48": 0.013037720775643222,
"125": 0
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.3603667187598833
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
timeframe = '15m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
# plot_config = {
# 'main_plot': {
# 'tema': {},
# 'sar': {'color': 'white'},
# },
# 'subplots': {
# "MACD": {
# 'macd': {'color': 'blue'},
# 'macdsignal': {'color': 'orange'},
# },
# "RSI": {
# 'rsi': {'color': 'red'},
# }
# }
# }
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Bollinger bands
bollinger_1sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['bb_upperband_1sd'] = bollinger_1sd['upper']
dataframe['bb_lowerband_1sd'] = bollinger_1sd['lower']
bollinger_4sd = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=4)
dataframe['bb_lowerband_4sd'] = bollinger_4sd['lower']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 25) &
(dataframe['close'] < dataframe['bb_lowerband_1sd'])
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 95) &
(dataframe['close'] > dataframe['bb_upperband_1sd'])
),
'sell'] = 1
return dataframe
================================================
FILE: strategies/BBRSITV/BBRSITV.py
================================================
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame, Series
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
from freqtrade.strategy import DecimalParameter, IntParameter, stoploss_from_open
from datetime import datetime, timedelta
from functools import reduce
# --------------------------------
def EWO(dataframe, ema_length=5, ema2_length=35):
df = dataframe.copy()
ema1 = ta.EMA(df, timeperiod=ema_length)
ema2 = ta.EMA(df, timeperiod=ema2_length)
emadif = (ema1 - ema2) / df['close'] * 100
return emadif
# Volume Weighted Moving Average
def vwma(dataframe: DataFrame, length: int = 10):
"""Indicator: Volume Weighted Moving Average (VWMA)"""
# Calculate Result
pv = dataframe['close'] * dataframe['volume']
vwma = Series(ta.SMA(pv, timeperiod=length) / ta.SMA(dataframe['volume'], timeperiod=length))
return vwma
# Modified Elder Ray Index
def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
slow_ma = Series(ta.EMA(vwma(dataframe, length=len_slow_ma), timeperiod=len_slow_ma))
return slow_ma >= slow_ma.shift(1) # we just need true & false for ERI trend
class BBRSITV(IStrategy):
INTERFACE_VERSION = 2
# Buy hyperspace params:
buy_params = {
"ewo_high": 4.86,
"for_ma_length": 22,
"for_sigma": 1.74,
}
# Sell hyperspace params:
sell_params = {
"for_ma_length_sell": 65,
"for_sigma_sell": 1.895,
"rsi_high": 72,
}
# ROI table: # value loaded from strategy
minimal_roi = {
"0": 0.1
}
# Stoploss:
stoploss = -0.25 # value loaded from strategy
# Trailing stop:
trailing_stop = False # value loaded from strategy
trailing_stop_positive = 0.005 # value loaded from strategy
trailing_stop_positive_offset = 0.025 # value loaded from strategy
trailing_only_offset_is_reached = True # value loaded from strategy
# Sell signal
use_sell_signal = True
sell_profit_only = False
sell_profit_offset = 0.01
ignore_roi_if_buy_signal = False
process_only_new_candles = True
startup_candle_count = 30
protections = [
# {
# "method": "StoplossGuard",
# "lookback_period_candles": 12,
# "trade_limit": 1,
# "stop_duration_candles": 6,
# "only_per_pair": True
# },
# {
# "method": "StoplossGuard",
# "lookback_period_candles": 12,
# "trade_limit": 2,
# "stop_duration_candles": 6,
# "only_per_pair": False
# },
{
"method": "LowProfitPairs",
"lookback_period_candles": 60,
"trade_limit": 1,
"stop_duration": 60,
"required_profit": -0.05
},
{
"method": "MaxDrawdown",
"lookback_period_candles": 24,
"trade_limit": 1,
"stop_duration_candles": 12,
"max_allowed_drawdown": 0.2
},
]
ewo_high = DecimalParameter(0, 7.0, default=buy_params['ewo_high'], space='buy', optimize=True)
for_sigma = DecimalParameter(0, 10.0, default=buy_params['for_sigma'], space='buy', optimize=True)
for_sigma_sell = DecimalParameter(0, 10.0, default=sell_params['for_sigma_sell'], space='sell', optimize=True)
rsi_high = IntParameter(60, 100, default=sell_params['rsi_high'], space='sell', optimize=True)
for_ma_length = IntParameter(5, 80, default=buy_params['for_ma_length'], space='buy', optimize=True)
for_ma_length_sell = IntParameter(5, 80, default=sell_params['for_ma_length_sell'], space='sell', optimize=True)
# Optimal timeframe for the strategy
timeframe = '5m'
# Protection
fast_ewo = 50
slow_ewo = 200
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# //@version=3
# study(" RSI + BB (EMA) + Dispersion (2.0)", overlay=false)
#
# // Инициализация параметров
# src = input(title="Source", type=source, defval=close) // Устанавливаем тип цены для расчетов
src = 'close'
# for_rsi = input(title="RSI_period", type=integer, defval=14) // Период для RSI
for_rsi = 14
# for_ma = input(title="Basis_BB", type=integer, defval=20) // Период для MA внутри BB
# for_ma = 20
# for_mult = input(title="Stdev", type=integer, defval=2, minval=1, maxval=5) // Число стандартных отклонений для BB
for_mult = 2
# for_sigma = input(title="Dispersion", type=float, defval=0.1, minval=0.01, maxval=1) // Дисперсия вокруг MA
for_sigma = 0.1
#
# // Условия работы скрипта
# current_rsi = rsi(src, for_rsi) // Текущее положение индикатора RSI
dataframe['rsi'] = ta.RSI(dataframe[src], for_rsi)
dataframe['rsi_4'] = ta.RSI(dataframe[src], 4)
if self.config['runmode'].value == 'hyperopt':
for for_ma in range(5, 81):
# basis = ema(current_rsi, for_ma)
dataframe[f'basis_{for_ma}'] = ta.EMA(dataframe['rsi'], for_ma)
# dev = for_mult * stdev(current_rsi, for_ma)
dataframe[f'dev_{for_ma}'] = ta.STDDEV(dataframe['rsi'], for_ma)
# upper = basis + dev
#dataframe[f'upper_{for_ma}'] = (dataframe[f'basis_{for_ma}'] + (dataframe[f'dev_{for_ma}'] * for_mult))
# lower = basis - dev
#dataframe[f'lower_{for_ma}'] = dataframe[f'basis_{for_ma}'] - (dataframe[f'dev_{for_ma}'] * for_mult)
# disp_up = basis + ((upper - lower) * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (сверху)
# dataframe[f'disp_up_{for_ma}'] = dataframe[f'basis_{for_ma}'] + ((dataframe[f'upper_{for_ma}'] - dataframe[f'lower_{for_ma}']) * for_sigma)
# disp_down = basis - ((upper - lower) * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (снизу)
# dataframe[f'disp_down_{for_ma}'] = dataframe[f'basis_{for_ma}'] - ((dataframe[f'upper_{for_ma}'] - dataframe[f'lower_{for_ma}']) * for_sigma)
# color_rsi = current_rsi >= disp_up ? lime : current_rsi <= disp_down ? red : #ffea00 // Текущий цвет RSI, в зависимости от его местоположения внутри BB
else:
dataframe[f'basis_{self.for_ma_length.value}'] = ta.EMA(dataframe['rsi'], self.for_ma_length.value)
dataframe[f'basis_{self.for_ma_length_sell.value}'] = ta.EMA(dataframe['rsi'], self.for_ma_length_sell.value)
# dev = for_mult * stdev(current_rsi, for_ma)
dataframe[f'dev_{self.for_ma_length.value}'] = ta.STDDEV(dataframe['rsi'], self.for_ma_length.value)
dataframe[f'dev_{self.for_ma_length_sell.value}'] = ta.STDDEV(dataframe['rsi'], self.for_ma_length_sell.value)
#
# // Дополнительные линии и заливка для областей для RSI
# h1 = hline(70, color=#d4d4d4, linestyle=dotted, linewidth=1)
h1 = 70
# h2 = hline(30, color=#d4d4d4, linestyle=dotted, linewidth=1)
h2 = 30
# fill (h1, h2, transp=95)
#
# // Алерты и условия срабатывания
# rsi_Green = crossover(current_rsi, disp_up)
# rsi_Red = crossunder(current_rsi, disp_down)
# alertcondition(condition=rsi_Green,
# title="RSI cross Above Dispersion Area",
# message="The RSI line closing crossed above the Dispersion area.")
#
# alertcondition(condition=rsi_Red,
# title="RSI cross Under Dispersion Area",
# message="The RSI line closing crossed below the Dispersion area")
#
# // Результаты и покраска
# plot(basis, color=black)
# plot(upper, color=#00fff0, linewidth=2)
# plot(lower, color=#00fff0, linewidth=2)
# s1 = plot(disp_up, color=white)
# s2 = plot(disp_down, color=white)
# fill(s1, s2, color=white, transp=80)
# plot(current_rsi, color=color_rsi, linewidth=2)
dataframe['EWO'] = EWO(dataframe, self.fast_ewo, self.slow_ewo)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# upper = basis + dev
# lower = basis - dev
# disp_up = basis + ((upper - lower) * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (сверху)
# disp_up = basis + ((basis + dev * for_mult) - (basis - dev * for_mult)) * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (сверху)
# disp_up = basis + (basis + dev * for_mult - basis + dev * for_mult)) * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (сверху)
# disp_up = basis + (2 * dev * for_sigma * for_mult) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (сверху)
(dataframe['rsi'] < (dataframe[f'basis_{self.for_ma_length.value}'] - (dataframe[f'dev_{self.for_ma_length.value}'] * self.for_sigma.value))) &
(dataframe['EWO'] > self.ewo_high.value) &
(dataframe['volume'] > 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
(dataframe['rsi'] > self.rsi_high.value) |
# upper = basis + dev
# lower = basis - dev
# disp_down = basis - ((upper - lower) * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (снизу)
# disp_down = basis - ((2* dev * for_sigma) // Минимально-допустимый порог в области мувинга, который должен преодолеть RSI (снизу)
(dataframe['rsi'] > dataframe[f'basis_{self.for_ma_length_sell.value}'] + ((dataframe[f'dev_{self.for_ma_length_sell.value}'] * self.for_sigma_sell.value)))
) &
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe
class BBRSITV4(BBRSITV):
minimal_roi = {
"0": 0.07
}
ignore_roi_if_buy_signal = True
startup_candle_count = 400
stoploss = -0.3 # value loaded from strategy
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] < (dataframe[f'basis_{self.for_ma_length.value}'] - (dataframe[f'dev_{self.for_ma_length.value}'] * self.for_sigma.value)))
&
(
(
(dataframe['EWO'] > self.ewo_high.value)
&
(dataframe['EWO'] < 10)
)
|
(
(dataframe['EWO'] >= 10)
&
(dataframe['rsi'] < 40)
)
)
&
(dataframe['rsi_4'] < 25)
&
(dataframe['volume'] > 0)
# &
# (dataframe["roc_bbwidth_max"] < 70)
),
'buy'] = 1
return dataframe
class BBRSITV1(BBRSITV):
"""
2021-07-01 00:00:00 -> 2021-09-28 00:00:00 | Max open trades : 4
============================================================================= STRATEGY SUMMARY =============================================================================
| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |
|-----------------------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------+-----------------------|
| Elliotv8_08SL | 906 | 0.92 | 832.19 | 19770.304 | 659.01 | 0:38:00 | 717 0 189 79.1 | 2020.917 USDT 79.84% |
| SMAOffsetProtectOptV1 | 417 | 1.33 | 555.91 | 8423.809 | 280.79 | 1:44:00 | 300 0 117 71.9 | 1056.072 USDT 61.08% |
| BBRSITV | 309 | 1.10 | 340.17 | 3869.800 | 128.99 | 2:53:00 | 223 0 86 72.2 | 261.984 USDT 25.84% |
============================================================================================================================================================================
"""
INTERFACE_VERSION = 2
# Buy hyperspace params:
buy_params = {
"ewo_high": 4.964,
"for_ma_length": 12,
"for_sigma": 2.313,
}
# Sell hyperspace params:
sell_params = {
"for_ma_length_sell": 78,
"for_sigma_sell": 1.67,
"rsi_high": 60,
}
# ROI table: # value loaded from strategy
minimal_roi = {
"0": 0.1
}
# Stoploss:
stoploss = -0.25 # value loaded from strategy
# Trailing stop:
trailing_stop = False # value loaded from strategy
trailing_stop_positive = 0.005 # value loaded from strategy
trailing_stop_positive_offset = 0.025 # value loaded from strategy
trailing_only_offset_is_reached = True # value loaded from strategy
class BBRSITV2(BBRSITV):
"""
2021-07-01 00:00:00 -> 2021-09-28 00:00:00 | Max open trades : 4
============================================================================= STRATEGY SUMMARY =============================================================================
| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |
|-----------------------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------+-----------------------|
| Elliotv8_08SL | 906 | 0.92 | 832.19 | 19770.304 | 659.01 | 0:38:00 | 717 0 189 79.1 | 2020.917 USDT 79.84% |
| SMAOffsetProtectOptV1 | 417 | 1.33 | 555.91 | 8423.809 | 280.79 | 1:44:00 | 300 0 117 71.9 | 1056.072 USDT 61.08% |
| BBRSITV | 486 | 1.11 | 537.58 | 7689.862 | 256.33 | 5:01:00 | 287 0 199 59.1 | 1279.461 USDT 75.45% |
============================================================================================================================================================================
"""
# Buy hyperspace params:
buy_params = {
"ewo_high": 4.85,
"for_ma_length": 11,
"for_sigma": 2.066,
}
# Sell hyperspace params:
sell_params = {
"for_ma_length_sell": 61,
"for_sigma_sell": 1.612,
"rsi_high": 87,
}
# ROI table: # value loaded from strategy
minimal_roi = {
"0": 0.1
}
# Stoploss:
stoploss = -0.25 # value loaded from strategy
# Trailing stop:
trailing_stop = False # value loaded from strategy
trailing_stop_positive = 0.005 # value loaded from strategy
trailing_stop_positive_offset = 0.025 # value loaded from strategy
trailing_only_offset_is_reached = True # value loaded from strategy
class BBRSITV3(BBRSITV):
"""
2021-07-01 00:00:00 -> 2021-09-28 00:00:00 | Max open trades : 4
============================================================================== STRATEGY SUMMARY =============================================================================
| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit USDT | Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |
|-----------------------+--------+----------------+----------------+-------------------+----------------+----------------+-------------------------+------------------------|
| Elliotv8_08SL | 906 | 0.92 | 832.19 | 19770.304 | 659.01 | 0:38:00 | 717 0 189 79.1 | 2020.917 USDT 79.84% |
| SMAOffsetProtectOptV1 | 417 | 1.33 | 555.91 | 8423.809 | 280.79 | 1:44:00 | 300 0 117 71.9 | 1056.072 USDT 61.08% |
| BBRSITV | 627 | 1.14 | 715.85 | 12998.605 | 433.29 | 5:35:00 | 374 0 253 59.6 | 2294.408 USDT 100.60% |
============================================================================================================================================================================="""
INTERFACE_VERSION = 2
# Buy hyperspace params:
buy_params = {
"ewo_high": 4.86,
"for_ma_length": 22,
"for_sigma": 1.74,
}
# Sell hyperspace params:
sell_params = {
"for_ma_length_sell": 65,
"for_sigma_sell": 1.895,
"rsi_high": 72,
}
# ROI table: # value loaded from strategy
minimal_roi = {
"0": 0.1
}
# Stoploss:
stoploss = -0.25 # value loaded from strategy
# Trailing stop:
trailing_stop = True
trailing_stop_positive = 0.078
trailing_stop_positive_offset = 0.095
trailing_only_offset_is_reached = False
class BBRSITV5(BBRSITV):
minimal_roi = {
"0": 0.04
}
ignore_roi_if_buy_signal = True
startup_candle_count = 400
use_custom_stoploss = True
stoploss = -0.3 # value loaded from strategy
sell_params = {
##
"pHSL": -0.178,
"pPF_1": 0.01,
"pPF_2": 0.048,
"pSL_1": 0.009,
"pSL_2": 0.043,
}
is_optimize_trailing = True
pHSL = DecimalParameter(-0.200, -0.040, default=-0.08, decimals=3, space='sell', optimize=is_optimize_trailing , load=True)
# profit threshold 1, trigger point, SL_1 is used
pPF_1 = DecimalParameter(0.008, 0.020, default=0.016, decimals=3, space='sell', optimize=is_optimize_trailing , load=True)
pSL_1 = DecimalParameter(0.008, 0.020, default=0.011, decimals=3, space='sell', optimize=is_optimize_trailing , load=True)
# profit threshold 2, SL_2 is used
pPF_2 = DecimalParameter(0.040, 0.100, default=0.080, decimals=3, space='sell', optimize=is_optimize_trailing , load=True)
pSL_2 = DecimalParameter(0.020, 0.070, default=0.040, decimals=3, space='sell', optimize=is_optimize_trailing , load=True)
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
current_rate: float, current_profit: float, **kwargs) -> float:
# hard stoploss profit
HSL = self.pHSL.value
PF_1 = self.pPF_1.value
SL_1 = self.pSL_1.value
PF_2 = self.pPF_2.value
SL_2 = self.pSL_2.value
# For profits between PF_1 and PF_2 the stoploss (sl_profit) used is linearly interpolated
# between the values of SL_1 and SL_2. For all profits above PL_2 the sl_profit value
# rises linearly with current profit, for profits below PF_1 the hard stoploss profit is used.
if (current_profit > PF_2):
sl_profit = SL_2 + (current_profit - PF_2)
elif (current_profit > PF_1):
sl_profit = SL_1 + ((current_profit - PF_1) * (SL_2 - SL_1) / (PF_2 - PF_1))
else:
sl_profit = HSL
# Only for hyperopt invalid return
if (sl_profit >= current_profit):
return -0.99
return stoploss_from_open(sl_profit, current_profit)
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] < (dataframe[f'basis_{self.for_ma_length.value}'] - (dataframe[f'dev_{self.for_ma_length.value}'] * self.for_sigma.value)))
&
(
(
(dataframe['EWO'] > self.ewo_high.value)
&
(dataframe['EWO'] < 10)
)
|
(
(dataframe['EWO'] >= 10)
gitextract_m9eikmuu/
├── LICENSE
├── README.md
└── strategies/
├── ADXMomentum/
│ └── ADXMomentum.py
├── ADX_15M_USDT/
│ └── ADX_15M_USDT.py
├── ADX_15M_USDT2/
│ └── ADX_15M_USDT2.py
├── ASDTSRockwellTrading/
│ └── ASDTSRockwellTrading.py
├── ActionZone/
│ └── ActionZone.py
├── AdxSmas/
│ └── AdxSmas.py
├── AlligatorStrat/
│ └── AlligatorStrat.py
├── AlligatorStrategy/
│ └── AlligatorStrategy.py
├── AlwaysBuy/
│ └── AlwaysBuy.py
├── Apollo11/
│ └── Apollo11.py
├── AverageStrategy/
│ └── AverageStrategy.py
├── AwesomeMacd/
│ └── AwesomeMacd.py
├── BBMod1/
│ └── BBMod1.py
├── BBRSI/
│ └── BBRSI.py
├── BBRSI2/
│ └── BBRSI2.py
├── BBRSI21/
│ └── BBRSI21.py
├── BBRSI3366/
│ └── BBRSI3366.py
├── BBRSI4cust/
│ └── BBRSI4cust.py
├── BBRSINaiveStrategy/
│ └── BBRSINaiveStrategy.py
├── BBRSIOptim2020Strategy/
│ └── BBRSIOptim2020Strategy.py
├── BBRSIOptimStrategy/
│ └── BBRSIOptimStrategy.py
├── BBRSIOptimizedStrategy/
│ └── BBRSIOptimizedStrategy.py
├── BBRSIS/
│ └── BBRSIS.py
├── BBRSIStrategy/
│ └── BBRSIStrategy.py
├── BBRSITV/
│ └── BBRSITV.py
├── BBRSIoriginal/
│ └── BBRSIoriginal.py
├── BBRSIv2/
│ └── BBRSIv2.py
├── BB_RPB_TSL/
│ └── BB_RPB_TSL.py
├── BB_RPB_TSL_2/
│ └── BB_RPB_TSL_2.py
├── BB_RPB_TSL_BI/
│ └── BB_RPB_TSL_BI.py
├── BB_RPB_TSL_BIV1/
│ └── BB_RPB_TSL_BIV1.py
├── BB_RPB_TSL_RNG/
│ └── BB_RPB_TSL_RNG.py
├── BB_RPB_TSL_RNG_2/
│ └── BB_RPB_TSL_RNG_2.py
├── BB_RPB_TSL_RNG_TBS/
│ └── BB_RPB_TSL_RNG_TBS.py
├── BB_RPB_TSL_RNG_TBS_GOLD/
│ └── BB_RPB_TSL_RNG_TBS_GOLD.py
├── BB_RPB_TSL_RNG_VWAP/
│ └── BB_RPB_TSL_RNG_VWAP.py
├── BB_RPB_TSL_SMA_Tranz/
│ └── BB_RPB_TSL_SMA_Tranz.py
├── BB_RPB_TSL_SMA_Tranz_TB_1_1_1/
│ └── BB_RPB_TSL_SMA_Tranz_TB_1_1_1.py
├── BB_RPB_TSL_SMA_Tranz_TB_MOD/
│ └── BB_RPB_TSL_SMA_Tranz_TB_MOD.py
├── BB_RPB_TSL_Tranz/
│ └── BB_RPB_TSL_Tranz.py
├── BB_RPB_TSL_c7c477d_20211030/
│ └── BB_RPB_TSL_c7c477d_20211030.py
├── BB_RPB_TSLmeneguzzo/
│ └── BB_RPB_TSLmeneguzzo.py
├── BB_RSI/
│ └── BB_RSI.py
├── BB_Strategy04/
│ └── BB_Strategy04.py
├── BBands/
│ └── BBands.py
├── BBandsRSI/
│ └── BBandsRSI.py
├── BBlower/
│ └── BBlower.py
├── Babico_SMA5xBBmid/
│ └── Babico_SMA5xBBmid.py
├── Bandtastic/
│ └── Bandtastic.py
├── BbRoi/
│ └── BbRoi.py
├── BbandRsi/
│ └── BbandRsi.py
├── BbandRsiRolling/
│ └── BbandRsiRolling.py
├── BcmbigzDevelop/
│ └── BcmbigzDevelop.py
├── BcmbigzV1/
│ └── BcmbigzV1.py
├── BigPete/
│ └── BigPete.py
├── BigZ03/
│ └── BigZ03.py
├── BigZ0307HO/
│ └── BigZ0307HO.py
├── BigZ03HO/
│ └── BigZ03HO.py
├── BigZ04/
│ └── BigZ04.py
├── BigZ0407/
│ └── BigZ0407.py
├── BigZ0407HO/
│ └── BigZ0407HO.py
├── BigZ04HO/
│ └── BigZ04HO.py
├── BigZ04HO2/
│ └── BigZ04HO2.py
├── BigZ04_TSL3/
│ └── BigZ04_TSL3.py
├── BigZ04_TSL4/
│ └── BigZ04_TSL4.py
├── BigZ06/
│ └── BigZ06.py
├── BigZ07/
│ └── BigZ07.py
├── BigZ07Next/
│ └── BigZ07Next.py
├── BigZ07Next2/
│ └── BigZ07Next2.py
├── BinClucMad/
│ └── BinClucMad.py
├── BinClucMadDevelop/
│ └── BinClucMadDevelop.py
├── BinClucMadSMADevelop/
│ └── BinClucMadSMADevelop.py
├── BinClucMadV1/
│ └── BinClucMadV1.py
├── BinHV27/
│ └── BinHV27.py
├── BinHV45/
│ └── BinHV45.py
├── BinHV45HO/
│ └── BinHV45HO.py
├── BreakEven/
│ └── BreakEven.py
├── BuyAllSellAllStrategy/
│ └── BuyAllSellAllStrategy.py
├── BuyOnly/
│ └── BuyOnly.py
├── CBPete9/
│ └── CBPete9.py
├── CCIStrategy/
│ └── CCIStrategy.py
├── CMCWinner/
│ └── CMCWinner.py
├── Cci/
│ └── Cci.py
├── Chandem/
│ └── Chandem.py
├── Chandemtwo/
│ └── Chandemtwo.py
├── Chispei/
│ └── Chispei.py
├── Cluc4/
│ └── Cluc4.py
├── Cluc4werk/
│ └── Cluc4werk.py
├── Cluc5werk/
│ └── Cluc5werk.py
├── Cluc7werk/
│ └── Cluc7werk.py
├── ClucFiatROI/
│ └── ClucFiatROI.py
├── ClucFiatSlow/
│ └── ClucFiatSlow.py
├── ClucHAnix/
│ └── ClucHAnix.py
├── ClucHAnix5m/
│ └── ClucHAnix5m.py
├── ClucHAnix_5m/
│ └── ClucHAnix_5m.py
├── ClucHAnix_5m1/
│ └── ClucHAnix_5m1.py
├── ClucHAnix_BB_RPB_MOD/
│ └── ClucHAnix_BB_RPB_MOD.py
├── ClucHAnix_BB_RPB_MOD2_ROI/
│ └── ClucHAnix_BB_RPB_MOD2_ROI.py
├── ClucHAnix_BB_RPB_MOD_CTT/
│ └── ClucHAnix_BB_RPB_MOD_CTT.py
├── ClucHAnix_BB_RPB_MOD_E0V1E_ROI/
│ └── ClucHAnix_BB_RPB_MOD_E0V1E_ROI.py
├── ClucHAnix_hhll/
│ └── ClucHAnix_hhll.py
├── ClucHAwerk/
│ └── ClucHAwerk.py
├── ClucMay72018/
│ └── ClucMay72018.py
├── CofiBitStrategy/
│ └── CofiBitStrategy.py
├── CombinedBinHAndCluc/
│ └── CombinedBinHAndCluc.py
├── CombinedBinHAndCluc2021/
│ └── CombinedBinHAndCluc2021.py
├── CombinedBinHAndCluc2021Bull/
│ └── CombinedBinHAndCluc2021Bull.py
├── CombinedBinHAndClucHyperV0/
│ └── CombinedBinHAndClucHyperV0.py
├── CombinedBinHAndClucHyperV3/
│ └── CombinedBinHAndClucHyperV3.py
├── CombinedBinHAndClucV2/
│ └── CombinedBinHAndClucV2.py
├── CombinedBinHAndClucV3/
│ └── CombinedBinHAndClucV3.py
├── CombinedBinHAndClucV4/
│ └── CombinedBinHAndClucV4.py
├── CombinedBinHAndClucV5/
│ └── CombinedBinHAndClucV5.py
├── CombinedBinHAndClucV5Hyperoptable/
│ └── CombinedBinHAndClucV5Hyperoptable.py
├── CombinedBinHAndClucV6/
│ └── CombinedBinHAndClucV6.py
├── CombinedBinHAndClucV6H/
│ └── CombinedBinHAndClucV6H.py
├── CombinedBinHAndClucV7/
│ └── CombinedBinHAndClucV7.py
├── CombinedBinHAndClucV8/
│ └── CombinedBinHAndClucV8.py
├── CombinedBinHAndClucV8Hyper/
│ └── CombinedBinHAndClucV8Hyper.py
├── CombinedBinHAndClucV8XH/
│ └── CombinedBinHAndClucV8XH.py
├── CombinedBinHAndClucV8XHO/
│ └── CombinedBinHAndClucV8XHO.py
├── CombinedBinHClucAndMADV3/
│ └── CombinedBinHClucAndMADV3.py
├── CombinedBinHClucAndMADV5/
│ └── CombinedBinHClucAndMADV5.py
├── CombinedBinHClucAndMADV6/
│ └── CombinedBinHClucAndMADV6.py
├── CombinedBinHClucAndMADV9/
│ └── CombinedBinHClucAndMADV9.py
├── Combined_Indicators/
│ └── Combined_Indicators.py
├── Combined_NFIv6_SMA/
│ └── Combined_NFIv6_SMA.py
├── Combined_NFIv7_SMA/
│ └── Combined_NFIv7_SMA.py
├── Combined_NFIv7_SMA_Rallipanos_20210707/
│ └── Combined_NFIv7_SMA_Rallipanos_20210707.py
├── Combined_NFIv7_SMA_bAdBoY_20211204/
│ └── Combined_NFIv7_SMA_bAdBoY_20211204.py
├── CoreStrategy/
│ └── CoreStrategy.py
├── CrossEMAStrategy/
│ └── CrossEMAStrategy.py
├── CryptoFrog/
│ └── CryptoFrog.py
├── CryptoFrogHO/
│ └── CryptoFrogHO.py
├── CryptoFrogHO2/
│ └── CryptoFrogHO2.py
├── CryptoFrogHO2A/
│ └── CryptoFrogHO2A.py
├── CryptoFrogHO3A1/
│ └── CryptoFrogHO3A1.py
├── CryptoFrogHO3A2/
│ └── CryptoFrogHO3A2.py
├── CryptoFrogHO3A3/
│ └── CryptoFrogHO3A3.py
├── CryptoFrogHO3A4/
│ └── CryptoFrogHO3A4.py
├── CryptoFrogNFI/
│ └── CryptoFrogNFI.py
├── CryptoFrogNFIHO1A/
│ └── CryptoFrogNFIHO1A.py
├── CryptoFrogOffset/
│ └── CryptoFrogOffset.py
├── CustomStoplossWithPSAR/
│ └── CustomStoplossWithPSAR.py
├── DCBBBounce/
│ └── DCBBBounce.py
├── DD/
│ └── DD.py
├── DIV_v1/
│ └── DIV_v1.py
├── DevilStra/
│ └── DevilStra.py
├── Diamond/
│ └── Diamond.py
├── Divergences/
│ └── Divergences.py
├── Dracula/
│ └── Dracula.py
├── Dyna_opti/
│ └── Dyna_opti.py
├── EI3v2_tag_cofi_green/
│ └── EI3v2_tag_cofi_green.py
├── EMA50/
│ └── EMA50.py
├── EMA520015_V17/
│ └── EMA520015_V17.py
├── EMABBRSI/
│ └── EMABBRSI.py
├── EMABreakout/
│ └── EMABreakout.py
├── EMASkipPump/
│ └── EMASkipPump.py
├── EMAVolume/
│ └── EMAVolume.py
├── EMA_CROSSOVER_STRATEGY/
│ └── EMA_CROSSOVER_STRATEGY.py
├── EXPERIMENTAL_STRATEGY/
│ └── EXPERIMENTAL_STRATEGY.py
├── ElliotV2/
│ └── ElliotV2.py
├── ElliotV4/
│ └── ElliotV4.py
├── ElliotV531/
│ └── ElliotV531.py
├── ElliotV5HO/
│ └── ElliotV5HO.py
├── ElliotV5HOMod2/
│ └── ElliotV5HOMod2.py
├── ElliotV5HOMod3/
│ └── ElliotV5HOMod3.py
├── ElliotV7/
│ └── ElliotV7.py
├── ElliotV8HO/
│ └── ElliotV8HO.py
├── ElliotV8_original/
│ └── ElliotV8_original.py
├── ElliotV8_original_ichiv2/
│ └── ElliotV8_original_ichiv2.py
├── ElliotV8_original_ichiv3/
│ └── ElliotV8_original_ichiv3.py
├── Elliotv8/
│ └── Elliotv8.py
├── FRAYSTRAT/
│ └── FRAYSTRAT.py
├── Fakebuy/
│ └── Fakebuy.py
├── FastSupertrend/
│ └── FastSupertrend.py
├── FastSupertrendOpt/
│ └── FastSupertrendOpt.py
├── FiveMinCrossAbove/
│ └── FiveMinCrossAbove.py
├── FixedRiskRewardLoss/
│ └── FixedRiskRewardLoss.py
├── ForexSignal/
│ └── ForexSignal.py
├── FrostAuraM115mStrategy/
│ └── FrostAuraM115mStrategy.py
├── FrostAuraM11hStrategy/
│ └── FrostAuraM11hStrategy.py
├── FrostAuraM21hStrategy/
│ └── FrostAuraM21hStrategy.py
├── FrostAuraM315mStrategy/
│ └── FrostAuraM315mStrategy.py
├── FrostAuraM31hStrategy/
│ └── FrostAuraM31hStrategy.py
├── FrostAuraRandomStrategy/
│ └── FrostAuraRandomStrategy.py
├── GodCard/
│ └── GodCard.py
├── GodStraNew/
│ └── GodStraNew.py
├── GodStraNew40/
│ └── GodStraNew40.py
├── GodStraNew_SMAonly/
│ └── GodStraNew_SMAonly.py
├── Guacamole/
│ └── Guacamole.py
├── Gumbo1/
│ └── Gumbo1.py
├── Hacklemore2/
│ └── Hacklemore2.py
├── Hacklemore3/
│ └── Hacklemore3.py
├── HansenSmaOffsetV1/
│ └── HansenSmaOffsetV1.py
├── HarmonicDivergence/
│ └── HarmonicDivergence.py
├── Heracles/
│ └── Heracles.py
├── HourBasedStrategy/
│ └── HourBasedStrategy.py
├── HyperStra_GSN_SMAOnly/
│ └── HyperStra_GSN_SMAOnly.py
├── HyperStra_SMAOnly/
│ └── HyperStra_SMAOnly.py
├── INSIDEUP/
│ └── INSIDEUP.py
├── Ichess/
│ └── Ichess.py
├── Ichi/
│ └── Ichi.py
├── Ichimoku/
│ └── Ichimoku.py
├── Ichimoku_SenkouSpanCross/
│ └── Ichimoku_SenkouSpanCross.py
├── Ichimoku_v12/
│ └── Ichimoku_v12.py
├── Ichimoku_v30/
│ └── Ichimoku_v30.py
├── Ichimoku_v31/
│ └── Ichimoku_v31.py
├── Ichimoku_v32/
│ └── Ichimoku_v32.py
├── Ichimoku_v33/
│ └── Ichimoku_v33.py
├── Ichimoku_v37/
│ └── Ichimoku_v37.py
├── InformativeSample/
│ └── InformativeSample.py
├── Inverse/
│ └── Inverse.py
├── InverseV2/
│ └── InverseV2.py
├── JustROCR/
│ └── JustROCR.py
├── JustROCR3/
│ └── JustROCR3.py
├── JustROCR5/
│ └── JustROCR5.py
├── JustROCR6/
│ └── JustROCR6.py
├── KAMACCIRSI/
│ └── KAMACCIRSI.py
├── KC_BB/
│ └── KC_BB.py
├── Kamaflage/
│ └── Kamaflage.py
├── Leveraged/
│ └── Leveraged.py
├── LookaheadStrategy/
│ └── LookaheadStrategy.py
├── Low_BB/
│ └── Low_BB.py
├── LuxOSC/
│ └── LuxOSC.py
├── MAC/
│ └── MAC.py
├── MACDCCI/
│ └── MACDCCI.py
├── MACDRSI200/
│ └── MACDRSI200.py
├── MACDStrategy/
│ └── MACDStrategy.py
├── MACDStrategy_crossed/
│ └── MACDStrategy_crossed.py
├── MACD_EMA/
│ └── MACD_EMA.py
├── MACD_TRIPLE_MA/
│ └── MACD_TRIPLE_MA.py
├── MACD_TRI_EMA/
│ └── MACD_TRI_EMA.py
├── MADisplaceV3/
│ └── MADisplaceV3.py
├── MFI/
│ └── MFI.py
├── Macd/
│ └── Macd.py
├── MacheteV8b/
│ └── MacheteV8b.py
├── MacheteV8bRallimod2/
│ └── MacheteV8bRallimod2.py
├── MarketChyperHyperStrategy/
│ └── MarketChyperHyperStrategy.py
├── Maro4hMacdSd/
│ └── Maro4hMacdSd.py
├── Martin/
│ └── Martin.py
├── MiniLambo/
│ └── MiniLambo.py
├── Minmax/
│ └── Minmax.py
├── MomStrategy/
│ └── MomStrategy.py
├── Momentumv2/
│ └── Momentumv2.py
├── MontrealStrategy/
│ └── MontrealStrategy.py
├── MostOfAll/
│ └── MostOfAll.py
├── MultiMA_TSL/
│ └── MultiMA_TSL.py
├── MultiMA_TSL3/
│ └── MultiMA_TSL3.py
├── MultiMA_TSL3_Mod/
│ └── MultiMA_TSL3_Mod.py
├── MultiMa/
│ └── MultiMa.py
├── MultiOffsetLamboV0/
│ └── MultiOffsetLamboV0.py
├── MultiRSI/
│ └── MultiRSI.py
├── NASOSRv6_private_Reinuvader_20211121/
│ └── NASOSRv6_private_Reinuvader_20211121.py
├── NASOSv4/
│ └── NASOSv4.py
├── NASOSv5/
│ └── NASOSv5.py
├── NASOSv5_mod1/
│ └── NASOSv5_mod1.py
├── NASOSv5_mod1_DanMod/
│ └── NASOSv5_mod1_DanMod.py
├── NASOSv5_mod2/
│ └── NASOSv5_mod2.py
├── NASOSv5_mod3/
│ └── NASOSv5_mod3.py
├── NFI46/
│ └── NFI46.py
├── NFI46Frog/
│ └── NFI46Frog.py
├── NFI46FrogZ/
│ └── NFI46FrogZ.py
├── NFI46Offset/
│ └── NFI46Offset.py
├── NFI46OffsetHOA1/
│ └── NFI46OffsetHOA1.py
├── NFI46Z/
│ └── NFI46Z.py
├── NFI47V2/
│ └── NFI47V2.py
├── NFI4Frog/
│ └── NFI4Frog.py
├── NFI5MOHO/
│ └── NFI5MOHO.py
├── NFI5MOHO2/
│ └── NFI5MOHO2.py
├── NFI5MOHO_WIP/
│ └── NFI5MOHO_WIP.py
├── NFI5MOHO_WIP_1/
│ └── NFI5MOHO_WIP_1.py
├── NFI5MOHO_WIP_2/
│ └── NFI5MOHO_WIP_2.py
├── NFI731_BUSD/
│ └── NFI731_BUSD.py
├── NFI7MOHO/
│ └── NFI7MOHO.py
├── NFINextMOHO/
│ └── NFINextMOHO.py
├── NFINextMOHO2/
│ └── NFINextMOHO2.py
├── NFINextMultiOffsetAndHO/
│ └── NFINextMultiOffsetAndHO.py
├── NFINextMultiOffsetAndHO2/
│ └── NFINextMultiOffsetAndHO2.py
├── NFIX_BB_RPB/
│ └── NFIX_BB_RPB.py
├── NFIX_BB_RPB_c7c477d_20211030/
│ └── NFIX_BB_RPB_c7c477d_20211030.py
├── NfiNextModded/
│ └── NfiNextModded.py
├── NormalizerStrategy/
│ └── NormalizerStrategy.py
├── NormalizerStrategyHO2/
│ └── NormalizerStrategyHO2.py
├── Nostalgia/
│ └── Nostalgia.py
├── NostalgiaForInfinityNext/
│ └── NostalgiaForInfinityNext.py
├── NostalgiaForInfinityNextGen/
│ └── NostalgiaForInfinityNextGen.py
├── NostalgiaForInfinityNextGen_TSL/
│ └── NostalgiaForInfinityNextGen_TSL.py
├── NostalgiaForInfinityNextV7155/
│ └── NostalgiaForInfinityNextV7155.py
├── NostalgiaForInfinityNext_ChangeToTower_V5_2/
│ └── NostalgiaForInfinityNext_ChangeToTower_V5_2.py
├── NostalgiaForInfinityNext_ChangeToTower_V5_3/
│ └── NostalgiaForInfinityNext_ChangeToTower_V5_3.py
├── NostalgiaForInfinityNext_ChangeToTower_V6/
│ └── NostalgiaForInfinityNext_ChangeToTower_V6.py
├── NostalgiaForInfinityNext_maximizer/
│ └── NostalgiaForInfinityNext_maximizer.py
├── NostalgiaForInfinityV1/
│ └── NostalgiaForInfinityV1.py
├── NostalgiaForInfinityV2/
│ └── NostalgiaForInfinityV2.py
├── NostalgiaForInfinityV3/
│ └── NostalgiaForInfinityV3.py
├── NostalgiaForInfinityV4/
│ └── NostalgiaForInfinityV4.py
├── NostalgiaForInfinityV4HO/
│ └── NostalgiaForInfinityV4HO.py
├── NostalgiaForInfinityV5/
│ └── NostalgiaForInfinityV5.py
├── NostalgiaForInfinityV5MultiOffsetAndHO/
│ └── NostalgiaForInfinityV5MultiOffsetAndHO.py
├── NostalgiaForInfinityV5MultiOffsetAndHO2/
│ └── NostalgiaForInfinityV5MultiOffsetAndHO2.py
├── NostalgiaForInfinityV6/
│ └── NostalgiaForInfinityV6.py
├── NostalgiaForInfinityV6HO/
│ └── NostalgiaForInfinityV6HO.py
├── NostalgiaForInfinityV7/
│ └── NostalgiaForInfinityV7.py
├── NostalgiaForInfinityV7_7_2/
│ └── NostalgiaForInfinityV7_7_2.py
├── NostalgiaForInfinityV7_SMA/
│ └── NostalgiaForInfinityV7_SMA.py
├── NostalgiaForInfinityV7_SMAv2/
│ └── NostalgiaForInfinityV7_SMAv2.py
├── NostalgiaForInfinityV7_SMAv2_1/
│ └── NostalgiaForInfinityV7_SMAv2_1.py
├── NostalgiaForInfinityX/
│ └── NostalgiaForInfinityX.py
├── NostalgiaForInfinityX2/
│ └── NostalgiaForInfinityX2.py
├── NostalgiaForInfinityXw/
│ └── NostalgiaForInfinityXw.py
├── NotAnotherSMAOffSetStrategy_V2/
│ └── NotAnotherSMAOffSetStrategy_V2.py
├── NotAnotherSMAOffsetStrategy/
│ └── NotAnotherSMAOffsetStrategy.py
├── NotAnotherSMAOffsetStrategyHO/
│ └── NotAnotherSMAOffsetStrategyHO.py
├── NotAnotherSMAOffsetStrategyHOv3/
│ └── NotAnotherSMAOffsetStrategyHOv3.py
├── NotAnotherSMAOffsetStrategyLite/
│ └── NotAnotherSMAOffsetStrategyLite.py
├── NotAnotherSMAOffsetStrategyModHO/
│ └── NotAnotherSMAOffsetStrategyModHO.py
├── NotAnotherSMAOffsetStrategyModHO_LamineDz_20210901/
│ └── NotAnotherSMAOffsetStrategyModHO_LamineDz_20210901.py
├── NotAnotherSMAOffsetStrategyX1/
│ └── NotAnotherSMAOffsetStrategyX1.py
├── NotAnotherSMAOffsetStrategy_uzi/
│ └── NotAnotherSMAOffsetStrategy_uzi.py
├── NotAnotherSMAOffsetStrategy_uzi3/
│ └── NotAnotherSMAOffsetStrategy_uzi3.py
├── NowoIchimoku1hV1/
│ └── NowoIchimoku1hV1.py
├── NowoIchimoku1hV2/
│ └── NowoIchimoku1hV2.py
├── NowoIchimoku5mV2/
│ └── NowoIchimoku5mV2.py
├── ONUR/
│ └── ONUR.py
├── ObeliskIM_v1_1/
│ └── ObeliskIM_v1_1.py
├── ObeliskRSI_v6_1/
│ └── ObeliskRSI_v6_1.py
├── Obelisk_3EMA_StochRSI_ATR/
│ └── Obelisk_3EMA_StochRSI_ATR.py
├── Obelisk_Ichimoku_Slow_v1_3/
│ └── Obelisk_Ichimoku_Slow_v1_3.py
├── Obelisk_Ichimoku_ZEMA_v1/
│ └── Obelisk_Ichimoku_ZEMA_v1.py
├── Obelisk_TradePro_Ichi_v1_1/
│ └── Obelisk_TradePro_Ichi_v1_1.py
├── Obelisk_TradePro_Ichi_v2_1/
│ └── Obelisk_TradePro_Ichi_v2_1.py
├── PRICEFOLLOWING/
│ └── PRICEFOLLOWING.py
├── PRICEFOLLOWING2/
│ └── PRICEFOLLOWING2.py
├── PRICEFOLLOWINGX/
│ └── PRICEFOLLOWINGX.py
├── Persia/
│ └── Persia.py
├── PrawnstarOBV/
│ └── PrawnstarOBV.py
├── PumpDetector/
│ └── PumpDetector.py
├── Quickie/
│ └── Quickie.py
├── RSI/
│ └── RSI.py
├── RSIBB02/
│ └── RSIBB02.py
├── RSIv2/
│ └── RSIv2.py
├── RalliV1/
│ └── RalliV1.py
├── RalliV1_disable56/
│ └── RalliV1_disable56.py
├── RaposaDivergenceV1/
│ └── RaposaDivergenceV1.py
├── ReinforcedAverageStrategy/
│ └── ReinforcedAverageStrategy.py
├── ReinforcedQuickie/
│ └── ReinforcedQuickie.py
├── ReinforcedSmoothScalp/
│ └── ReinforcedSmoothScalp.py
├── Renko/
│ └── Renko.py
├── RobotradingBody/
│ └── RobotradingBody.py
├── Roth01/
│ └── Roth01.py
├── Roth03/
│ └── Roth03.py
├── SAR/
│ └── SAR.py
├── SMAIP3/
│ └── SMAIP3.py
├── SMAIP3v2/
│ └── SMAIP3v2.py
├── SMAOG/
│ └── SMAOG.py
├── SMAOPv1_TTF/
│ └── SMAOPv1_TTF.py
├── SMAOffset/
│ └── SMAOffset.py
├── SMAOffsetProtectOpt/
│ └── SMAOffsetProtectOpt.py
├── SMAOffsetProtectOptV0/
│ └── SMAOffsetProtectOptV0.py
├── SMAOffsetProtectOptV1/
│ └── SMAOffsetProtectOptV1.py
├── SMAOffsetProtectOptV1HO1/
│ └── SMAOffsetProtectOptV1HO1.py
├── SMAOffsetProtectOptV1Mod/
│ └── SMAOffsetProtectOptV1Mod.py
├── SMAOffsetProtectOptV1Mod2/
│ └── SMAOffsetProtectOptV1Mod2.py
├── SMAOffsetProtectOptV1_kkeue_20210619/
│ └── SMAOffsetProtectOptV1_kkeue_20210619.py
├── SMAOffsetV2/
│ └── SMAOffsetV2.py
├── SMA_BBRSI/
│ └── SMA_BBRSI.py
├── SRsi/
│ └── SRsi.py
├── STRATEGY_RSI_BB_BOUNDS_CROSS/
│ └── STRATEGY_RSI_BB_BOUNDS_CROSS.py
├── STRATEGY_RSI_BB_CROSS/
│ └── STRATEGY_RSI_BB_CROSS.py
├── SampleStrategy/
│ └── SampleStrategy.py
├── SampleStrategyV2/
│ └── SampleStrategyV2.py
├── Saturn5/
│ └── Saturn5.py
├── Scalp/
│ └── Scalp.py
├── Schism/
│ └── Schism.py
├── Schism2/
│ └── Schism2.py
├── Schism2MM/
│ └── Schism2MM.py
├── Schism3/
│ └── Schism3.py
├── Schism4/
│ └── Schism4.py
├── Schism5/
│ └── Schism5.py
├── Schism6/
│ └── Schism6.py
├── Seb/
│ └── Seb.py
├── Simple/
│ └── Simple.py
├── SlowPotato/
│ └── SlowPotato.py
├── Slowbro/
│ └── Slowbro.py
├── SmoothOperator/
│ └── SmoothOperator.py
├── SmoothScalp/
│ └── SmoothScalp.py
├── Stavix2/
│ └── Stavix2.py
├── Stinkfist/
│ └── Stinkfist.py
├── StochRSITEMA/
│ └── StochRSITEMA.py
├── Strategy001/
│ └── Strategy001.py
├── Strategy001_custom_sell/
│ └── Strategy001_custom_sell.py
├── Strategy002/
│ └── Strategy002.py
├── Strategy003/
│ └── Strategy003.py
├── Strategy004/
│ └── Strategy004.py
├── Strategy005/
│ └── Strategy005.py
├── StrategyScalpingFast/
│ └── StrategyScalpingFast.py
├── StrategyScalpingFast2/
│ └── StrategyScalpingFast2.py
├── SuperHV27/
│ └── SuperHV27.py
├── SuperTrend/
│ └── SuperTrend.py
├── SuperTrendPure/
│ └── SuperTrendPure.py
├── SupertrendStrategy/
│ └── SupertrendStrategy.py
├── SwingHigh/
│ └── SwingHigh.py
├── SwingHighToSky/
│ └── SwingHighToSky.py
├── TDSequentialStrategy/
│ └── TDSequentialStrategy.py
├── TEMA/
│ └── TEMA.py
├── TechnicalExampleStrategy/
│ └── TechnicalExampleStrategy.py
├── TemaMaster/
│ └── TemaMaster.py
├── TemaMaster3/
│ └── TemaMaster3.py
├── TemaPure/
│ └── TemaPure.py
├── TemaPureNeat/
│ └── TemaPureNeat.py
├── TemaPureTwo/
│ └── TemaPureTwo.py
├── TenderEnter/
│ └── TenderEnter.py
├── TheForce/
│ └── TheForce.py
├── TheRealPullbackV2/
│ └── TheRealPullbackV2.py
├── TrailingBuyStrat2/
│ └── TrailingBuyStrat2.py
├── Trend_Strength_Directional/
│ └── Trend_Strength_Directional.py
├── TrixStrategy/
│ └── TrixStrategy.py
├── TrixV15Strategy/
│ └── TrixV15Strategy.py
├── TrixV21Strategy/
│ └── TrixV21Strategy.py
├── TrixV23Strategy/
│ └── TrixV23Strategy.py
├── UltimateMomentumIndicator/
│ └── UltimateMomentumIndicator.py
├── Uptrend/
│ └── Uptrend.py
├── UziChan/
│ └── UziChan.py
├── UziChan2/
│ └── UziChan2.py
├── VWAP/
│ └── VWAP.py
├── WaveTrendStra/
│ └── WaveTrendStra.py
├── XebTradeStrat/
│ └── XebTradeStrat.py
├── XtraThicc/
│ └── XtraThicc.py
├── YOLO/
│ └── YOLO.py
├── adaptive/
│ └── adaptive.py
├── adx_opt_strat/
│ └── adx_opt_strat.py
├── adxbbrsi2/
│ └── adxbbrsi2.py
├── bb_rsi_opt_new/
│ └── bb_rsi_opt_new.py
├── bbema/
│ └── bbema.py
├── bbrsi1_strategy/
│ └── bbrsi1_strategy.py
├── bbrsi4Freq/
│ └── bbrsi4Freq.py
├── bestV2/
│ └── bestV2.py
├── botbaby/
│ └── botbaby.py
├── conny/
│ └── conny.py
├── cryptohassle/
│ └── cryptohassle.py
├── custom/
│ └── custom.py
├── custom_sell/
│ └── custom_sell.py
├── e6v34/
│ └── e6v34.py
├── ema/
│ └── ema.py
├── epretrace/
│ └── epretrace.py
├── fahmibah/
│ └── fahmibah.py
├── flawless_lambo/
│ └── flawless_lambo.py
├── hansencandlepatternV1/
│ └── hansencandlepatternV1.py
├── heikin/
│ └── heikin.py
├── hlhb/
│ └── hlhb.py
├── ichiV1/
│ └── ichiV1.py
├── ichiV1_Marius/
│ └── ichiV1_Marius.py
├── keltnerchannel/
│ └── keltnerchannel.py
├── mabStra/
│ └── mabStra.py
├── macd_recovery/
│ └── macd_recovery.py
├── mark_strat/
│ └── mark_strat.py
├── mark_strat_opt/
│ └── mark_strat_opt.py
├── quantumfirst/
│ └── quantumfirst.py
├── redditMA/
│ └── redditMA.py
├── stoploss/
│ └── stoploss.py
├── stratfib/
│ └── stratfib.py
├── strato/
│ └── strato.py
├── true_lambo/
│ └── true_lambo.py
└── wtc/
└── wtc.py
Showing preview only (531K chars total). Download the full file or copy to clipboard to get everything.
SYMBOL INDEX (5082 symbols across 465 files)
FILE: strategies/ADXMomentum/ADXMomentum.py
class ADXMomentum (line 10) | class ADXMomentum(IStrategy):
method populate_indicators (line 37) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 46) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 58) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ADX_15M_USDT/ADX_15M_USDT.py
class ADX_15M_USDT (line 11) | class ADX_15M_USDT(IStrategy):
method populate_indicators (line 25) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 40) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 52) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ADX_15M_USDT2/ADX_15M_USDT2.py
class ADX_15M_USDT2 (line 11) | class ADX_15M_USDT2(IStrategy):
method populate_indicators (line 25) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 40) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 52) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ASDTSRockwellTrading/ASDTSRockwellTrading.py
class ASDTSRockwellTrading (line 13) | class ASDTSRockwellTrading(IStrategy):
method populate_indicators (line 50) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 59) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 74) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ActionZone/ActionZone.py
class ActionZone (line 18) | class ActionZone(IStrategy):
method custom_stoploss (line 88) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_stake_amount (line 101) | def custom_stake_amount(self, pair: str, current_time: datetime, curre...
method informative_pairs (line 111) | def informative_pairs(self):
method populate_indicators (line 124) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 149) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 166) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/AdxSmas/AdxSmas.py
class AdxSmas (line 11) | class AdxSmas(IStrategy):
method populate_indicators (line 35) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 42) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 52) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/AlligatorStrat/AlligatorStrat.py
class AlligatorStrat (line 10) | class AlligatorStrat(IStrategy):
method populate_indicators (line 36) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 68) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 95) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/AlligatorStrategy/AlligatorStrategy.py
class AlligatorStrategy (line 18) | class AlligatorStrategy(IStrategy):
method informative_pairs (line 138) | def informative_pairs(self):
method populate_indicators (line 151) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 182) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 203) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/AlwaysBuy/AlwaysBuy.py
class AlwaysBuy (line 5) | class AlwaysBuy(IStrategy):
method populate_indicators (line 32) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_entry_trend (line 36) | def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -...
method populate_exit_trend (line 42) | def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Apollo11/Apollo11.py
function to_minutes (line 12) | def to_minutes(**timdelta_kwargs):
class Apollo11 (line 16) | class Apollo11(IStrategy):
method protections (line 69) | def protections(self):
method populate_indicators (line 110) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 156) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 192) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 197) | def custom_stoploss(
FILE: strategies/AverageStrategy/AverageStrategy.py
class AverageStrategy (line 10) | class AverageStrategy(IStrategy):
method populate_indicators (line 32) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 39) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 53) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/AwesomeMacd/AwesomeMacd.py
class AwesomeMacd (line 11) | class AwesomeMacd(IStrategy):
method populate_indicators (line 35) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 46) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 57) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBMod1/BBMod1.py
function ha_typical_price (line 17) | def ha_typical_price(bars):
function vwma (line 23) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 32) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 37) | def EWO(dataframe, ema_length=5, ema2_length=35):
function range_percent_change (line 45) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 64) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 84) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
function vmap_b (line 106) | def vmap_b(dataframe, window_size=20, num_of_std=1):
function top_percent_change (line 115) | def top_percent_change(dataframe: DataFrame, length: int) -> float:
class BBMod1 (line 128) | class BBMod1(IStrategy):
method informative_pairs (line 407) | def informative_pairs(self):
method informative_1h_indicators (line 414) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 484) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 524) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method normal_tf_indicators (line 579) | def normal_tf_indicators(self, dataframe: DataFrame) -> DataFrame:
method populate_indicators (line 757) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 768) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1050) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function pmax (line 1056) | def pmax(df, period, multiplier, length, ma_type, src):
function momdiv (line 1135) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function t3 (line 1157) | def t3(dataframe, length=5):
FILE: strategies/BBRSI/BBRSI.py
class bbrsi (line 15) | class bbrsi(IStrategy):
method informative_pairs (line 83) | def informative_pairs(self):
method populate_indicators (line 96) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 110) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 120) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSI2/BBRSI2.py
class BBRSI2 (line 12) | class BBRSI2(IStrategy):
method populate_indicators (line 38) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 51) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 61) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSI21/BBRSI21.py
class BBRSI21 (line 11) | class BBRSI21(IStrategy):
method populate_indicators (line 43) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 54) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 73) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSI3366/BBRSI3366.py
class BBRSI3366 (line 11) | class BBRSI3366(IStrategy):
method populate_indicators (line 43) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 59) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 81) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSI4cust/BBRSI4cust.py
class BBRSI4cust (line 19) | class BBRSI4cust(IStrategy):
method populate_indicators (line 100) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_entry_trend (line 127) | def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -...
method populate_exit_trend (line 140) | def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_exit (line 154) | def custom_exit(self, pair: str, trade: 'Trade', current_time: 'dateti...
FILE: strategies/BBRSINaiveStrategy/BBRSINaiveStrategy.py
class BBRSINaiveStrategy (line 16) | class BBRSINaiveStrategy(IStrategy):
method informative_pairs (line 80) | def informative_pairs(self):
method populate_indicators (line 93) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 106) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 117) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSIOptim2020Strategy/BBRSIOptim2020Strategy.py
class BBRSIOptim2020Strategy (line 17) | class BBRSIOptim2020Strategy(IStrategy):
method informative_pairs (line 84) | def informative_pairs(self):
method populate_indicators (line 97) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 111) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 121) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSIOptimStrategy/BBRSIOptimStrategy.py
class BBRSIOptimStrategy (line 17) | class BBRSIOptimStrategy(IStrategy):
method informative_pairs (line 84) | def informative_pairs(self):
method populate_indicators (line 97) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 111) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 121) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSIOptimizedStrategy/BBRSIOptimizedStrategy.py
class BBRSIOptimizedStrategy (line 16) | class BBRSIOptimizedStrategy(IStrategy):
method informative_pairs (line 81) | def informative_pairs(self):
method populate_indicators (line 94) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 107) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 117) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSIS/BBRSIS.py
class BBRSIS (line 9) | class BBRSIS(IStrategy):
method get_ticker_indicator (line 40) | def get_ticker_indicator(self):
method populate_indicators (line 43) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 85) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 104) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSIStrategy/BBRSIStrategy.py
class BBRSIStrategy (line 15) | class BBRSIStrategy(IStrategy):
method informative_pairs (line 83) | def informative_pairs(self):
method populate_indicators (line 96) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 110) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 120) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSITV/BBRSITV.py
function EWO (line 12) | def EWO(dataframe, ema_length=5, ema2_length=35):
function vwma (line 20) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 28) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
class BBRSITV (line 32) | class BBRSITV(IStrategy):
method populate_indicators (line 116) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 190) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 207) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class BBRSITV4 (line 224) | class BBRSITV4(BBRSITV):
method populate_buy_trend (line 233) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
class BBRSITV1 (line 262) | class BBRSITV1(BBRSITV):
class BBRSITV2 (line 303) | class BBRSITV2(BBRSITV):
class BBRSITV3 (line 343) | class BBRSITV3(BBRSITV):
class BBRSITV5 (line 384) | class BBRSITV5(BBRSITV):
method custom_stoploss (line 412) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_buy_trend (line 439) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/BBRSIoriginal/BBRSIoriginal.py
class BBRSIoriginal (line 11) | class BBRSIoriginal(IStrategy):
method populate_indicators (line 45) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 79) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 95) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBRSIv2/BBRSIv2.py
class BBRSIv2 (line 15) | class BBRSIv2(IStrategy):
method custom_stoploss (line 68) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 86) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 107) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 142) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_RPB_TSL/BB_RPB_TSL.py
function ha_typical_price (line 17) | def ha_typical_price(bars):
function vwma (line 22) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 30) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 34) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 41) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 50) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 66) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 85) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL (line 105) | class BB_RPB_TSL(IStrategy):
method informative_pairs (line 360) | def informative_pairs(self):
method informative_1h_indicators (line 367) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 444) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 460) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 583) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 606) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 771) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 782) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1054) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function pmax (line 1062) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 1152) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function T3 (line 1172) | def T3(dataframe, length=5):
FILE: strategies/BB_RPB_TSL_2/BB_RPB_TSL_2.py
function ha_typical_price (line 17) | def ha_typical_price(bars):
function EWO (line 21) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 28) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 37) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 53) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 72) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL_2 (line 92) | class BB_RPB_TSL_2(IStrategy):
method informative_pairs (line 312) | def informative_pairs(self):
method custom_stoploss (line 328) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 344) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 432) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method informative_1h_indicators (line 460) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method informative_5m_indicators (line 520) | def informative_5m_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 652) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 782) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 796) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1204) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function pmax (line 1212) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 1302) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
FILE: strategies/BB_RPB_TSL_BI/BB_RPB_TSL_BI.py
function ha_typical_price (line 17) | def ha_typical_price(bars):
function EWO (line 21) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 28) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 37) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 53) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 72) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL_BI (line 92) | class BB_RPB_TSL_BI(IStrategy):
method informative_pairs (line 313) | def informative_pairs(self):
method informative_1h_indicators (line 320) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 384) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 400) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 488) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 516) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 646) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 657) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 878) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function pmax (line 886) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 976) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
FILE: strategies/BB_RPB_TSL_BIV1/BB_RPB_TSL_BIV1.py
function ha_typical_price (line 17) | def ha_typical_price(bars):
function EWO (line 21) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 28) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 37) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 53) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 72) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL_BIV1 (line 92) | class BB_RPB_TSL_BIV1(IStrategy):
method informative_pairs (line 313) | def informative_pairs(self):
method informative_1h_indicators (line 320) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 384) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 400) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 488) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 516) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 646) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 657) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 878) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function pmax (line 886) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 976) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
FILE: strategies/BB_RPB_TSL_RNG/BB_RPB_TSL_RNG.py
function EWO (line 16) | def EWO(dataframe, ema_length=5, ema2_length=35):
function williams_r (line 24) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
class BB_RPB_TSL_RNG (line 42) | class BB_RPB_TSL_RNG(IStrategy):
method informative_pairs (line 183) | def informative_pairs(self):
method custom_stoploss (line 192) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 221) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 327) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 452) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_RPB_TSL_RNG_2/BB_RPB_TSL_RNG_2.py
function EWO (line 16) | def EWO(dataframe, ema_length=5, ema2_length=35):
function williams_r (line 24) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
class BB_RPB_TSL_RNG_2 (line 42) | class BB_RPB_TSL_RNG_2(IStrategy):
method informative_pairs (line 183) | def informative_pairs(self):
method custom_stoploss (line 192) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 221) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 327) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 452) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_RPB_TSL_RNG_TBS/BB_RPB_TSL_RNG_TBS.py
function EWO (line 17) | def EWO(dataframe, ema_length=5, ema2_length=35):
function williams_r (line 25) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
class BB_RPB_TSL_RNG_TBS (line 43) | class BB_RPB_TSL_RNG_TBS(IStrategy):
method informative_pairs (line 184) | def informative_pairs(self):
method custom_stoploss (line 201) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 230) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 340) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 465) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class TrailingBuyStrat2 (line 497) | class TrailingBuyStrat2(BB_RPB_TSL_RNG_TBS):
method trailing_buy (line 534) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 542) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 564) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 571) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 618) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 623) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 704) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/BB_RPB_TSL_RNG_TBS_GOLD/BB_RPB_TSL_RNG_TBS_GOLD.py
function EWO (line 17) | def EWO(dataframe, ema_length=5, ema2_length=35):
function williams_r (line 25) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
class BB_RPB_TSL_RNG_TBS_GOLD (line 43) | class BB_RPB_TSL_RNG_TBS_GOLD(IStrategy):
method informative_pairs (line 184) | def informative_pairs(self):
method custom_stoploss (line 201) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 230) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 340) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 465) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class TrailingBuyStrat2 (line 497) | class TrailingBuyStrat2(BB_RPB_TSL_RNG_TBS_GOLD):
method trailing_buy (line 534) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 542) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 564) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 571) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 618) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 623) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 704) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/BB_RPB_TSL_RNG_VWAP/BB_RPB_TSL_RNG_VWAP.py
function EWO (line 16) | def EWO(dataframe, ema_length=5, ema2_length=35):
function williams_r (line 24) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function vmap_b (line 46) | def vmap_b(dataframe, window_size=20, num_of_std=1):
function top_percent_change (line 55) | def top_percent_change(dataframe: DataFrame, length: int) -> float:
class BB_RPB_TSL_RNG_VWAP (line 69) | class BB_RPB_TSL_RNG_VWAP(IStrategy):
method informative_pairs (line 226) | def informative_pairs(self):
method custom_stoploss (line 235) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 275) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 389) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 527) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_RPB_TSL_SMA_Tranz/BB_RPB_TSL_SMA_Tranz.py
function ha_typical_price (line 32) | def ha_typical_price(bars):
function VWAPB (line 36) | def VWAPB(dataframe, window_size=20, num_of_std=1):
function vwma (line 45) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 53) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 57) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 64) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 73) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 89) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 108) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
function HA (line 128) | def HA(dataframe, smoothing=None):
function pump_warning (line 154) | def pump_warning(dataframe, perc=15):
function pump_warning2 (line 162) | def pump_warning2(dataframe, params):
function dump_warning (line 212) | def dump_warning(dataframe, buy_threshold):
function ewo (line 233) | def ewo(dataframe, sma1_length=5, sma2_length=35):
function ema_vwma_osc (line 240) | def ema_vwma_osc(dataframe, len_slow_ma):
function pivot_points (line 244) | def pivot_points(dataframe: DataFrame, mode = 'fibonacci') -> Series:
function heikin_ashi (line 264) | def heikin_ashi(dataframe, smooth_inputs = False, smooth_outputs = False...
function pmax (line 298) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 388) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function pct_change (line 408) | def pct_change(a, b):
function T3 (line 411) | def T3(dataframe, length=5):
class BB_RPB_TSL_SMA_Tranz (line 433) | class BB_RPB_TSL_SMA_Tranz(IStrategy):
class HyperOpt (line 631) | class HyperOpt:
method generate_roi_table (line 633) | def generate_roi_table(params: dict):
method roi_space (line 654) | def roi_space() -> List[Dimension]:
method get_ticker_indicator (line 1439) | def get_ticker_indicator(self):
method range_percent_change (line 1444) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 1460) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 1473) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1483) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1493) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1503) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 1515) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 1532) | def informative_pairs(self):
method informative_1h_indicators (line 1540) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method informative_15m_indicators (line 1702) | def informative_15m_indicators(self, dataframe: DataFrame, metadata: d...
method custom_sell (line 1770) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 1936) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method confirm_trade_entry (line 1958) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method confirm_trade_exit (line 1981) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method normal_tf_indicators (line 1987) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_btc_indicators (line 2287) | def populate_btc_indicators(self, dataframe: DataFrame, metadata: dict...
method populate_indicators (line 2302) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 2333) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 3371) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class UziChanTB2 (line 3460) | class UziChanTB2(BB_RPB_TSL_SMA_Tranz):
method trailing_buy (line 3510) | def trailing_buy(self, pair, reinit=False):
method trailing_sell (line 3518) | def trailing_sell(self, pair, reinit=False):
method trailing_buy_info (line 3527) | def trailing_buy_info(self, pair: str, current_price: float):
method trailing_sell_info (line 3551) | def trailing_sell_info(self, pair: str, current_price: float):
method current_trailing_buy_profit_ratio (line 3573) | def current_trailing_buy_profit_ratio(self, pair: str, current_price: ...
method current_trailing_sell_profit_ratio (line 3580) | def current_trailing_sell_profit_ratio(self, pair: str, current_price:...
method trailing_buy_offset (line 3589) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method trailing_sell_offset (line 3636) | def trailing_sell_offset(self, dataframe, pair: str, current_price: fl...
method populate_indicators (line 3685) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 3691) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method confirm_trade_exit (line 3766) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method populate_buy_trend (line 3845) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 3869) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_RPB_TSL_SMA_Tranz_TB_1_1_1/BB_RPB_TSL_SMA_Tranz_TB_1_1_1.py
function ha_typical_price (line 29) | def ha_typical_price(bars):
function vwma (line 34) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 42) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 46) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 53) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 62) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 78) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 97) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL_SMA_Tranz_TB_1_1_1 (line 117) | class BB_RPB_TSL_SMA_Tranz_TB_1_1_1(IStrategy):
method get_ticker_indicator (line 952) | def get_ticker_indicator(self):
method range_percent_change (line 957) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 973) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 986) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 996) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1006) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1016) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 1028) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 1045) | def informative_pairs(self):
method informative_1h_indicators (line 1053) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method informative_15m_indicators (line 1216) | def informative_15m_indicators(self, dataframe: DataFrame, metadata: d...
method custom_sell (line 1283) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 1449) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 1472) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1700) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1714) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2641) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class BB_RPB_TSL_Tranz_TrailingBuy (line 2729) | class BB_RPB_TSL_Tranz_TrailingBuy(BB_RPB_TSL_SMA_Tranz_TB_1_1_1):
method trailing_buy (line 2766) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 2774) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 2796) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 2803) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 2850) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 2855) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 2936) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
function ewo (line 2962) | def ewo(dataframe, sma1_length=5, sma2_length=35):
function ema_vwma_osc (line 2969) | def ema_vwma_osc(dataframe, len_slow_ma):
function pivot_points (line 2973) | def pivot_points(dataframe: DataFrame, mode = 'fibonacci') -> Series:
function heikin_ashi (line 2993) | def heikin_ashi(dataframe, smooth_inputs = False, smooth_outputs = False...
function pmax (line 3027) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 3117) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function T3 (line 3137) | def T3(dataframe, length=5):
FILE: strategies/BB_RPB_TSL_SMA_Tranz_TB_MOD/BB_RPB_TSL_SMA_Tranz_TB_MOD.py
function ha_typical_price (line 30) | def ha_typical_price(bars):
function vwma (line 35) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 43) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 47) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 54) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 63) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 79) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 98) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
function HA (line 118) | def HA(dataframe, smoothing=None):
function pump_warning (line 144) | def pump_warning(dataframe, perc=15):
function ewo (line 154) | def ewo(dataframe, sma1_length=5, sma2_length=35):
function ema_vwma_osc (line 161) | def ema_vwma_osc(dataframe, len_slow_ma):
function pivot_points (line 165) | def pivot_points(dataframe: DataFrame, mode = 'fibonacci') -> Series:
function heikin_ashi (line 185) | def heikin_ashi(dataframe, smooth_inputs = False, smooth_outputs = False...
function pmax (line 219) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 309) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function pct_change (line 329) | def pct_change(a, b):
function T3 (line 332) | def T3(dataframe, length=5):
class BB_RPB_TSL_SMA_Tranz_TB_MOD (line 354) | class BB_RPB_TSL_SMA_Tranz_TB_MOD(IStrategy):
method protections (line 1284) | def protections(self):
method pump_warning2 (line 1301) | def pump_warning2(self, dataframe):
method get_ticker_indicator (line 1314) | def get_ticker_indicator(self):
method range_percent_change (line 1319) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 1335) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 1348) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1358) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1368) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1378) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 1390) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 1407) | def informative_pairs(self):
method informative_1h_indicators (line 1416) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 1579) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_15m_indicators (line 1593) | def informative_15m_indicators(self, dataframe: DataFrame, metadata: d...
method custom_sell (line 1660) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 1826) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 1849) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 2113) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 2132) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2964) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class BB_RPB_TSL_Tranz_TrailingBuy (line 3052) | class BB_RPB_TSL_Tranz_TrailingBuy(BB_RPB_TSL_SMA_Tranz_TB):
method trailing_buy (line 3089) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 3097) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 3119) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 3126) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 3173) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 3178) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 3259) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/BB_RPB_TSL_Tranz/BB_RPB_TSL_Tranz.py
function ha_typical_price (line 28) | def ha_typical_price(bars):
function vwma (line 33) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 41) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 45) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 52) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 61) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 77) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 96) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL_Tranz (line 116) | class BB_RPB_TSL_Tranz(IStrategy):
method informative_pairs (line 389) | def informative_pairs(self):
method informative_1h_indicators (line 397) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method informative_15m_indicators (line 491) | def informative_15m_indicators(self, dataframe: DataFrame, metadata: d...
method custom_stoploss (line 558) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 574) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 697) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 720) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 911) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 925) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1544) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class BB_RPB_TSL_Tranz_TrailingBuy (line 1550) | class BB_RPB_TSL_Tranz_TrailingBuy(BB_RPB_TSL_Tranz):
method trailing_buy (line 1587) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 1595) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 1617) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 1624) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 1671) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 1676) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 1757) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
function ewo (line 1782) | def ewo(dataframe, sma1_length=5, sma2_length=35):
function ema_vwma_osc (line 1789) | def ema_vwma_osc(dataframe, len_slow_ma):
function pivot_points (line 1793) | def pivot_points(dataframe: DataFrame, mode = 'fibonacci') -> Series:
function heikin_ashi (line 1813) | def heikin_ashi(dataframe, smooth_inputs = False, smooth_outputs = False...
function pmax (line 1847) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 1937) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function T3 (line 1957) | def T3(dataframe, length=5):
FILE: strategies/BB_RPB_TSL_c7c477d_20211030/BB_RPB_TSL_c7c477d_20211030.py
function EWO (line 16) | def EWO(dataframe, ema_length=5, ema2_length=35):
function williams_r (line 24) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 43) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSL_c7c477d_20211030 (line 63) | class BB_RPB_TSL_c7c477d_20211030(IStrategy):
method informative_pairs (line 206) | def informative_pairs(self):
method informative_1h_indicators (line 214) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 237) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method normal_tf_indicators (line 266) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 367) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 377) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 503) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_RPB_TSLmeneguzzo/BB_RPB_TSLmeneguzzo.py
function ha_typical_price (line 17) | def ha_typical_price(bars):
function vwma (line 22) | def vwma(dataframe: DataFrame, length: int = 10):
function moderi (line 30) | def moderi(dataframe: DataFrame, len_slow_ma: int = 32) -> Series:
function EWO (line 34) | def EWO(dataframe, ema_length=5, ema2_length=35):
function SROC (line 41) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function range_percent_change (line 50) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function williams_r (line 65) | def williams_r(dataframe: DataFrame, period: int = 14) -> Series:
function chaikin_money_flow (line 84) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class BB_RPB_TSLmeneguzzo (line 104) | class BB_RPB_TSLmeneguzzo(IStrategy):
method informative_pairs (line 330) | def informative_pairs(self):
method informative_1h_indicators (line 337) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method custom_stoploss (line 414) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 430) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method confirm_trade_entry (line 542) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method normal_tf_indicators (line 565) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 730) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 741) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 954) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function pmax (line 962) | def pmax(df, period, multiplier, length, MAtype, src):
function momdiv (line 1052) | def momdiv(dataframe: DataFrame, mom_length: int = 10, bb_length: int = ...
function T3 (line 1072) | def T3(dataframe, length=5):
FILE: strategies/BB_RSI/BB_RSI.py
class BB_RSI (line 12) | class BB_RSI(IStrategy):
method informative_pairs (line 60) | def informative_pairs(self):
method populate_indicators (line 73) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 94) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 111) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BB_Strategy04/BB_Strategy04.py
class BB_Strategy04 (line 16) | class BB_Strategy04(IStrategy):
method informative_pairs (line 94) | def informative_pairs(self):
method populate_indicators (line 107) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 130) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 149) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBands/BBands.py
class BBands (line 19) | class BBands(IStrategy):
method plot_config (line 91) | def plot_config(self):
method informative_pairs (line 110) | def informative_pairs(self):
method populate_indicators (line 123) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 343) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 360) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBandsRSI/BBandsRSI.py
class BBandsRSI (line 19) | class BBandsRSI(IStrategy):
method plot_config (line 89) | def plot_config(self):
method populate_indicators (line 107) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 145) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 162) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BBlower/BBlower.py
class BBlower (line 20) | class BBlower(IStrategy):
method informative_pairs (line 63) | def informative_pairs(self):
method populate_indicators (line 76) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 115) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 146) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Babico_SMA5xBBmid/Babico_SMA5xBBmid.py
class Babico_SMA5xBBmid (line 8) | class Babico_SMA5xBBmid(IStrategy):
method populate_indicators (line 38) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 49) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 57) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Bandtastic/Bandtastic.py
class Bandtastic (line 22) | class Bandtastic(IStrategy):
method populate_indicators (line 66) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 93) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 127) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BbRoi/BbRoi.py
class BbRoi (line 11) | class BbRoi(IStrategy):
method populate_indicators (line 41) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 57) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 70) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BbandRsi/BbandRsi.py
class BbandRsi (line 11) | class BbandRsi(IStrategy):
method populate_indicators (line 35) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 46) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 56) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BbandRsiRolling/BbandRsiRolling.py
class BbandRsiRolling (line 12) | class BbandRsiRolling(IStrategy):
method populate_indicators (line 45) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 59) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 69) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BcmbigzDevelop/BcmbigzDevelop.py
class BcmbigzDevelop (line 23) | class BcmbigzDevelop(IStrategy):
method confirm_trade_exit (line 348) | def confirm_trade_exit(
method custom_sell (line 375) | def custom_sell(
method custom_stoploss (line 439) | def custom_stoploss(
method informative_pairs (line 485) | def informative_pairs(self):
method informative_1h_indicators (line 490) | def informative_1h_indicators(
method normal_tf_indicators (line 528) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 576) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 588) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1194) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function SSLChannels (line 1234) | def SSLChannels(dataframe, length=7):
function MFV (line 1249) | def MFV(dataframe):
FILE: strategies/BcmbigzV1/BcmbigzV1.py
class BcmbigzV1 (line 13) | class BcmbigzV1(IStrategy):
method confirm_trade_exit (line 117) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 135) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 151) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 188) | def informative_pairs(self):
method informative_1h_indicators (line 193) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 210) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 238) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 248) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 513) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function MFV (line 525) | def MFV(dataframe):
FILE: strategies/BigPete/BigPete.py
function EWO (line 58) | def EWO(dataframe, ema_length=5, ema2_length=35):
class BigPete (line 66) | class BigPete(IStrategy):
method confirm_trade_exit (line 235) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 240) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 248) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 272) | def informative_pairs(self):
method informative_1h_indicators (line 277) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 294) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 328) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 338) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 506) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ03/BigZ03.py
class BigZ03 (line 54) | class BigZ03(IStrategy):
method custom_stoploss (line 158) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 196) | def informative_pairs(self):
method informative_1h_indicators (line 201) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 213) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 240) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 250) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 443) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ0307HO/BigZ0307HO.py
class BigZ0307HO (line 55) | class BigZ0307HO(IStrategy):
method custom_sell (line 447) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 612) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method range_percent_change (line 650) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 666) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 679) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 689) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 699) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 709) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 721) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 736) | def informative_pairs(self):
method informative_1h_indicators (line 741) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 800) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 871) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 881) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1074) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 1163) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 1171) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/BigZ03HO/BigZ03HO.py
class BigZ03HO (line 54) | class BigZ03HO(IStrategy):
method custom_stoploss (line 181) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 219) | def informative_pairs(self):
method informative_1h_indicators (line 224) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 236) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 263) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 273) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 466) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ04/BigZ04.py
class BigZ04 (line 54) | class BigZ04(IStrategy):
method confirm_trade_exit (line 158) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 164) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 170) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 208) | def informative_pairs(self):
method informative_1h_indicators (line 213) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 230) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 257) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 267) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 516) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ0407/BigZ0407.py
class BigZ0407 (line 55) | class BigZ0407(IStrategy):
method confirm_trade_exit (line 422) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 427) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 592) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method range_percent_change (line 630) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 646) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 659) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 669) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 679) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 689) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 701) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 716) | def informative_pairs(self):
method informative_1h_indicators (line 721) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 780) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 851) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 861) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1109) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 1198) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 1206) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/BigZ0407HO/BigZ0407HO.py
class BigZ0407HO (line 55) | class BigZ0407HO(IStrategy):
method confirm_trade_exit (line 460) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 465) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 630) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method range_percent_change (line 668) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 684) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 697) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 707) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 717) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 727) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 739) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 754) | def informative_pairs(self):
method informative_1h_indicators (line 759) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 818) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 889) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 899) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1147) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 1236) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 1244) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/BigZ04HO/BigZ04HO.py
class BigZ04HO (line 54) | class BigZ04HO(IStrategy):
method confirm_trade_exit (line 175) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 181) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 187) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 225) | def informative_pairs(self):
method informative_1h_indicators (line 230) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 247) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 274) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 284) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 533) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ04HO2/BigZ04HO2.py
class BigZ04HO2 (line 54) | class BigZ04HO2(IStrategy):
method confirm_trade_exit (line 221) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 226) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 231) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 269) | def informative_pairs(self):
method informative_1h_indicators (line 274) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 291) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 317) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 327) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 575) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ04_TSL3/BigZ04_TSL3.py
class BigZ04_TSL3 (line 58) | class BigZ04_TSL3(IStrategy):
method confirm_trade_exit (line 194) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 199) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 207) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 235) | def informative_pairs(self):
method informative_1h_indicators (line 240) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 257) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 291) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 301) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 550) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ04_TSL4/BigZ04_TSL4.py
function EWO (line 57) | def EWO(dataframe, ema_length=5, ema2_length=35):
class BigZ04_TSL4 (line 65) | class BigZ04_TSL4(IStrategy):
method confirm_trade_exit (line 207) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 212) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 220) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 244) | def informative_pairs(self):
method informative_1h_indicators (line 249) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 266) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 300) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 310) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 562) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BigZ06/BigZ06.py
class BigZ06 (line 57) | class BigZ06(IStrategy):
method confirm_trade_exit (line 161) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 167) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 183) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 221) | def informative_pairs(self):
method informative_1h_indicators (line 226) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 243) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 274) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 284) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 549) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function MFV (line 561) | def MFV(dataframe):
FILE: strategies/BigZ07/BigZ07.py
class BigZ07 (line 57) | class BigZ07(IStrategy):
method confirm_trade_exit (line 161) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_sell (line 179) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method custom_stoploss (line 195) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 232) | def informative_pairs(self):
method informative_1h_indicators (line 237) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 254) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 282) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 292) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 557) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function MFV (line 569) | def MFV(dataframe):
FILE: strategies/BigZ07Next/BigZ07Next.py
class BigZ07Next (line 45) | class BigZ07Next(IStrategy):
method confirm_trade_exit (line 400) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method get_ticker_indicator (line 417) | def get_ticker_indicator(self):
method custom_sell (line 420) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method range_percent_change (line 587) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 603) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 616) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 626) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 636) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 646) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 658) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 673) | def informative_pairs(self):
method informative_1h_indicators (line 682) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 739) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method resampled_tf_indicators (line 809) | def resampled_tf_indicators(self, dataframe: DataFrame, metadata: dict...
method base_tf_btc_indicators (line 816) | def base_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict)...
method info_tf_btc_indicators (line 828) | def info_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict)...
method populate_indicators (line 840) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 889) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1154) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 1244) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 1252) | def chaikin_money_flow(dataframe, n=20, fillna=False):
function MFV (line 1274) | def MFV(dataframe):
FILE: strategies/BigZ07Next2/BigZ07Next2.py
class BigZ07Next2 (line 45) | class BigZ07Next2(IStrategy):
method confirm_trade_exit (line 400) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method get_ticker_indicator (line 417) | def get_ticker_indicator(self):
method custom_sell (line 420) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method range_percent_change (line 587) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 603) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 616) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 626) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 636) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 646) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 658) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 673) | def informative_pairs(self):
method informative_1h_indicators (line 682) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 739) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method resampled_tf_indicators (line 809) | def resampled_tf_indicators(self, dataframe: DataFrame, metadata: dict...
method base_tf_btc_indicators (line 816) | def base_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict)...
method info_tf_btc_indicators (line 828) | def info_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict)...
method populate_indicators (line 840) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 889) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1154) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 1244) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 1252) | def chaikin_money_flow(dataframe, n=20, fillna=False):
function MFV (line 1274) | def MFV(dataframe):
FILE: strategies/BinClucMad/BinClucMad.py
function SSLChannels (line 12) | def SSLChannels(dataframe, length=7):
class BinClucMad (line 24) | class BinClucMad(IStrategy):
method custom_stoploss (line 139) | def custom_stoploss(
method informative_pairs (line 178) | def informative_pairs(self):
method informative_1h_indicators (line 183) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 200) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 223) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 233) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 439) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BinClucMadDevelop/BinClucMadDevelop.py
function SSLChannels (line 17) | def SSLChannels(dataframe, length=7):
class BinClucMadDevelop (line 29) | class BinClucMadDevelop(IStrategy):
method confirm_trade_exit (line 199) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_stoploss (line 222) | def custom_stoploss(
method custom_sell (line 264) | def custom_sell(
method informative_pairs (line 309) | def informative_pairs(self):
method informative_1h_indicators (line 314) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 336) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 369) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 379) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 736) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function SSLChannels_ATR (line 768) | def SSLChannels_ATR(dataframe, length=7):
FILE: strategies/BinClucMadSMADevelop/BinClucMadSMADevelop.py
class BinClucMadSMADevelop (line 23) | class BinClucMadSMADevelop(IStrategy):
method custom_stoploss (line 362) | def custom_stoploss(
method custom_sell (line 404) | def custom_sell(
method informative_pairs (line 464) | def informative_pairs(self):
method informative_1h_indicators (line 469) | def informative_1h_indicators(
method normal_tf_indicators (line 497) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 548) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 564) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1122) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function SSLChannels_ATR (line 1171) | def SSLChannels_ATR(dataframe, length=7):
function SSLChannels (line 1192) | def SSLChannels(dataframe, length=7):
function EWO (line 1206) | def EWO(dataframe, ema_length=5, ema2_length=35):
FILE: strategies/BinClucMadV1/BinClucMadV1.py
function SSLChannels (line 20) | def SSLChannels(dataframe, length=7):
class BinClucMadV1 (line 32) | class BinClucMadV1(IStrategy):
method custom_stoplossv8 (line 192) | def custom_stoplossv8(
method custom_stoploss (line 232) | def custom_stoploss(
method custom_sell (line 256) | def custom_sell(
method informative_pairs (line 299) | def informative_pairs(self):
method informative_1h_indicators (line 304) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 326) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 359) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 369) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 688) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BinHV27/BinHV27.py
class BinHV27 (line 19) | class BinHV27(IStrategy):
method populate_indicators (line 33) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 57) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 94) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BinHV45/BinHV45.py
function bollinger_bands (line 12) | def bollinger_bands(stock_price, window_size, num_of_std):
class BinHV45 (line 20) | class BinHV45(IStrategy):
method populate_indicators (line 41) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 53) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 66) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BinHV45HO/BinHV45HO.py
function bollinger_bands (line 14) | def bollinger_bands(stock_price, window_size, num_of_std):
class BinHV45HO (line 22) | class BinHV45HO(IStrategy):
method populate_indicators (line 40) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 50) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 63) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BreakEven/BreakEven.py
class BreakEven (line 7) | class BreakEven(IStrategy):
method populate_indicators (line 52) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 55) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 62) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/BuyAllSellAllStrategy/BuyAllSellAllStrategy.py
class BuyAllSellAllStrategy (line 8) | class BuyAllSellAllStrategy(IStrategy):
method populate_indicators (line 16) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 19) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 23) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_sell (line 27) | def custom_sell(
FILE: strategies/BuyOnly/BuyOnly.py
class BuyOnly (line 16) | class BuyOnly(IStrategy):
method informative_pairs (line 85) | def informative_pairs(self):
method populate_indicators (line 98) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 319) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 340) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CBPete9/CBPete9.py
function SSLChannels (line 57) | def SSLChannels(dataframe, length = 7):
class CBPete9 (line 68) | class CBPete9(IStrategy):
method custom_stoploss (line 162) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 192) | def informative_pairs(self):
method informative_1h_indicators (line 197) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 214) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 237) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 248) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 379) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CCIStrategy/CCIStrategy.py
class CCIStrategy (line 12) | class CCIStrategy(IStrategy):
method populate_indicators (line 26) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 44) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 66) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method chaikin_mf (line 84) | def chaikin_mf(self, df, periods=20):
method resample (line 97) | def resample(self, dataframe, interval, factor):
FILE: strategies/CMCWinner/CMCWinner.py
class CMCWinner (line 14) | class CMCWinner(IStrategy):
method populate_indicators (line 46) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 66) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 82) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Cci/Cci.py
class Cci (line 12) | class Cci(IStrategy):
method populate_indicators (line 29) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 36) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 50) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method resample (line 64) | def resample(self, dataframe, interval, factor):
FILE: strategies/Chandem/Chandem.py
class Chandem (line 20) | class Chandem(IStrategy):
method informative_pairs (line 61) | def informative_pairs(self):
method populate_indicators (line 74) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 98) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 115) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Chandemtwo/Chandemtwo.py
class Chandemtwo (line 20) | class Chandemtwo(IStrategy):
method informative_pairs (line 62) | def informative_pairs(self):
method populate_indicators (line 75) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 99) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 117) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Chispei/Chispei.py
class Chispei (line 23) | class Chispei(IStrategy):
method populate_indicators (line 39) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 46) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 56) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Cluc4/Cluc4.py
function bollinger_bands (line 8) | def bollinger_bands(stock_price, window_size, num_of_std):
class Cluc4 (line 14) | class Cluc4(IStrategy):
method informative_pairs (line 29) | def informative_pairs(self):
method populate_indicators (line 34) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 53) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 73) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Cluc4werk/Cluc4werk.py
function bollinger_bands (line 8) | def bollinger_bands(stock_price, window_size, num_of_std):
class Cluc4werk (line 14) | class Cluc4werk(IStrategy):
method informative_pairs (line 71) | def informative_pairs(self):
method populate_indicators (line 94) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 124) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 148) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Cluc5werk/Cluc5werk.py
function bollinger_bands (line 8) | def bollinger_bands(stock_price, window_size, num_of_std):
class Cluc5werk (line 14) | class Cluc5werk(IStrategy):
method informative_pairs (line 68) | def informative_pairs(self):
method populate_indicators (line 73) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 96) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 129) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class Cluc5werk_ETH (line 144) | class Cluc5werk_ETH(Cluc5werk):
class Cluc5werk_BTC (line 183) | class Cluc5werk_BTC(Cluc5werk):
class Cluc5werk_USD (line 227) | class Cluc5werk_USD(Cluc5werk):
FILE: strategies/Cluc7werk/Cluc7werk.py
class Cluc7werk (line 8) | class Cluc7werk(IStrategy):
method populate_indicators (line 63) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 90) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 114) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ClucFiatROI/ClucFiatROI.py
class ClucFiatROI (line 11) | class ClucFiatROI(IStrategy):
method populate_indicators (line 62) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 94) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 140) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method check_buy_timeout (line 159) | def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kw...
method check_sell_timeout (line 168) | def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **k...
FILE: strategies/ClucFiatSlow/ClucFiatSlow.py
class ClucFiatSlow (line 10) | class ClucFiatSlow(IStrategy):
method populate_indicators (line 61) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 88) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 112) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method check_buy_timeout (line 131) | def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kw...
method check_sell_timeout (line 140) | def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **k...
FILE: strategies/ClucHAnix/ClucHAnix.py
function bollinger_bands (line 10) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 17) | def ha_typical_price(bars):
class ClucHAnix (line 22) | class ClucHAnix(IStrategy):
method informative_pairs (line 104) | def informative_pairs(self):
method custom_stoploss (line 109) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 136) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 179) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 203) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ClucHAnix5m/ClucHAnix5m.py
function bollinger_bands (line 24) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 30) | def ha_typical_price(bars):
class ClucHAnix5m (line 34) | class ClucHAnix5m(IStrategy):
method informative_pairs (line 215) | def informative_pairs(self):
method custom_stoploss (line 226) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 255) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 341) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 458) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_exit (line 475) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function pct_change (line 483) | def pct_change(a, b):
function EWO (line 486) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ClucHAnix_BB_RPB_MOD2_ROI_DYNAMIC_TB (line 493) | class ClucHAnix_BB_RPB_MOD2_ROI_DYNAMIC_TB(ClucHAnix5m):
method trailing_buy (line 522) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 530) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 552) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 559) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 609) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 614) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 688) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/ClucHAnix_5m/ClucHAnix_5m.py
function bollinger_bands (line 9) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 15) | def ha_typical_price(bars):
class ClucHAnix_5m (line 19) | class ClucHAnix_5m(IStrategy):
method informative_pairs (line 113) | def informative_pairs(self):
method custom_stoploss (line 119) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 146) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 189) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 212) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ClucHAnix_5m1/ClucHAnix_5m1.py
function bollinger_bands (line 17) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 24) | def ha_typical_price(bars):
class ClucHAnix_5m1 (line 29) | class ClucHAnix_5m1(IStrategy):
method informative_pairs (line 123) | def informative_pairs(self):
method custom_stoploss (line 129) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 156) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 205) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 228) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class ClucHAnix_5mTB1 (line 245) | class ClucHAnix_5mTB1(ClucHAnix_5m1):
method trailing_buy (line 274) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 282) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 304) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 311) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 361) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 366) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 440) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/ClucHAnix_BB_RPB_MOD/ClucHAnix_BB_RPB_MOD.py
function bollinger_bands (line 18) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 24) | def ha_typical_price(bars):
class ClucHAnix_BB_RPB_MOD (line 28) | class ClucHAnix_BB_RPB_MOD(IStrategy):
method informative_pairs (line 203) | def informative_pairs(self):
method custom_stoploss (line 214) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 243) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 324) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 441) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_exit (line 458) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function pct_change (line 466) | def pct_change(a, b):
function EWO (line 469) | def EWO(dataframe, ema_length=5, ema2_length=35):
FILE: strategies/ClucHAnix_BB_RPB_MOD2_ROI/ClucHAnix_BB_RPB_MOD2_ROI.py
function bollinger_bands (line 25) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 31) | def ha_typical_price(bars):
class ClucHAnix_BB_RPB_MOD2_ROI (line 35) | class ClucHAnix_BB_RPB_MOD2_ROI(IStrategy):
method informative_pairs (line 216) | def informative_pairs(self):
method custom_stoploss (line 227) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 256) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 342) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 459) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_exit (line 476) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function pct_change (line 484) | def pct_change(a, b):
function EWO (line 487) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ClucHAnix_BB_RPB_MOD2_ROI_DYNAMIC_TB (line 494) | class ClucHAnix_BB_RPB_MOD2_ROI_DYNAMIC_TB(ClucHAnix_BB_RPB_MOD2_ROI):
method trailing_buy (line 523) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 531) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 553) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 560) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 610) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 615) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 689) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/ClucHAnix_BB_RPB_MOD_CTT/ClucHAnix_BB_RPB_MOD_CTT.py
function bollinger_bands (line 22) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 28) | def ha_typical_price(bars):
class ClucHAnix_BB_RPB_MOD_CTT (line 32) | class ClucHAnix_BB_RPB_MOD_CTT(IStrategy):
method informative_pairs (line 213) | def informative_pairs(self):
method custom_stoploss (line 224) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 253) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 355) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 484) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_exit (line 501) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function pct_change (line 509) | def pct_change(a, b):
function EWO (line 512) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ClucHAnix_BB_RPB_MOD_CTT_STB (line 519) | class ClucHAnix_BB_RPB_MOD_CTT_STB(ClucHAnix_BB_RPB_MOD_CTT):
method trailing_buy (line 556) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 564) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 586) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 593) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 640) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 645) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 726) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
class ClucHAnix_BB_RPB_MOD_CTT_DTB (line 750) | class ClucHAnix_BB_RPB_MOD_CTT_DTB(ClucHAnix_BB_RPB_MOD_CTT):
method trailing_buy (line 779) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 787) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 809) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 816) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 866) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 871) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 945) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/ClucHAnix_BB_RPB_MOD_E0V1E_ROI/ClucHAnix_BB_RPB_MOD_E0V1E_ROI.py
function bollinger_bands (line 25) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 31) | def ha_typical_price(bars):
class ClucHAnix_BB_RPB_MOD_E0V1E_ROI (line 35) | class ClucHAnix_BB_RPB_MOD_E0V1E_ROI(IStrategy):
class HyperOpt (line 41) | class HyperOpt:
method generate_roi_table (line 43) | def generate_roi_table(params: Dict) -> Dict[int, float]:
method roi_space (line 64) | def roi_space() -> List[Dimension]:
method informative_pairs (line 259) | def informative_pairs(self):
method custom_stoploss (line 270) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 299) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 385) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 502) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_exit (line 519) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function pct_change (line 527) | def pct_change(a, b):
function EWO (line 530) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ClucHAnix_BB_RPB_MOD_E0V1E_ROI_DYNAMIC_TB (line 537) | class ClucHAnix_BB_RPB_MOD_E0V1E_ROI_DYNAMIC_TB(ClucHAnix_BB_RPB_MOD_E0V...
method trailing_buy (line 566) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 574) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 596) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 603) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 653) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 658) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 732) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/ClucHAnix_hhll/ClucHAnix_hhll.py
function bollinger_bands (line 15) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 22) | def ha_typical_price(bars):
class ClucHAnix_hhll (line 27) | class ClucHAnix_hhll(IStrategy):
method informative_pairs (line 139) | def informative_pairs(self):
method custom_stoploss (line 145) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method confirm_trade_entry (line 174) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method custom_sell (line 195) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method populate_indicators (line 295) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 393) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 420) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function vwma (line 454) | def vwma(dataframe: DataFrame, length: int = 10):
function ema_vwma_osc (line 463) | def ema_vwma_osc(dataframe, len_slow_ma):
function range_percent_change (line 467) | def range_percent_change(dataframe: DataFrame, method, length: int) -> f...
function chaikin_money_flow (line 483) | def chaikin_money_flow(dataframe, n=20, fillna=False) -> Series:
class ClucHAnix_hhll_TB (line 503) | class ClucHAnix_hhll_TB(ClucHAnix_hhll):
method trailing_buy (line 540) | def trailing_buy(self, pair, reinit=False):
method trailing_buy_info (line 548) | def trailing_buy_info(self, pair: str, current_price: float):
method current_trailing_profit_ratio (line 570) | def current_trailing_profit_ratio(self, pair: str, current_price: floa...
method trailing_buy_offset (line 577) | def trailing_buy_offset(self, dataframe, pair: str, current_price: flo...
method populate_indicators (line 624) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_entry (line 629) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
method populate_buy_trend (line 710) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
FILE: strategies/ClucHAwerk/ClucHAwerk.py
function bollinger_bands (line 8) | def bollinger_bands(stock_price, window_size, num_of_std):
function ha_typical_price (line 14) | def ha_typical_price(bars):
class ClucHAwerk (line 18) | class ClucHAwerk(IStrategy):
method informative_pairs (line 74) | def informative_pairs(self):
method populate_indicators (line 79) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 115) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 140) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class ClucHAwerk_ETH (line 153) | class ClucHAwerk_ETH(ClucHAwerk):
class ClucHAwerk_BTC (line 206) | class ClucHAwerk_BTC(ClucHAwerk):
class ClucHAwerk_USD (line 254) | class ClucHAwerk_USD(ClucHAwerk):
FILE: strategies/ClucMay72018/ClucMay72018.py
class ClucMay72018 (line 20) | class ClucMay72018(IStrategy):
method populate_indicators (line 42) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 56) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 72) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CofiBitStrategy/CofiBitStrategy.py
class CofiBitStrategy (line 12) | class CofiBitStrategy(IStrategy):
method populate_indicators (line 48) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 59) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 77) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndCluc/CombinedBinHAndCluc.py
function bollinger_bands (line 10) | def bollinger_bands(stock_price, window_size, num_of_std):
class CombinedBinHAndCluc (line 17) | class CombinedBinHAndCluc(IStrategy):
method populate_indicators (line 33) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 49) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 68) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndCluc2021/CombinedBinHAndCluc2021.py
function bollinger_bands (line 10) | def bollinger_bands(stock_price, window_size, num_of_std):
class CombinedBinHAndCluc2021 (line 17) | class CombinedBinHAndCluc2021(IStrategy):
method populate_indicators (line 40) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 59) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 84) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndCluc2021Bull/CombinedBinHAndCluc2021Bull.py
function bollinger_bands (line 10) | def bollinger_bands(stock_price, window_size, num_of_std):
class CombinedBinHAndCluc2021Bull (line 17) | class CombinedBinHAndCluc2021Bull(IStrategy):
method populate_indicators (line 40) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 59) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 84) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucHyperV0/CombinedBinHAndClucHyperV0.py
class CombinedBinHAndClucHyperV0 (line 15) | class CombinedBinHAndClucHyperV0(IStrategy):
method custom_stoploss (line 75) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 101) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 127) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 162) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucHyperV3/CombinedBinHAndClucHyperV3.py
class CombinedBinHAndClucHyperV3 (line 15) | class CombinedBinHAndClucHyperV3(IStrategy):
method custom_stoploss (line 86) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 112) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 141) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 180) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV2/CombinedBinHAndClucV2.py
function bollinger_bands (line 14) | def bollinger_bands(stock_price, window_size, num_of_std):
function SSLChannels (line 21) | def SSLChannels(dataframe, length = 7):
class CombinedBinHAndClucV2 (line 33) | class CombinedBinHAndClucV2(IStrategy):
method informative_pairs (line 62) | def informative_pairs(self):
method get_informative_indicators (line 68) | def get_informative_indicators(dataframe: DataFrame, metadata: dict):
method populate_indicators (line 91) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 129) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 152) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV3/CombinedBinHAndClucV3.py
function bollinger_bands (line 9) | def bollinger_bands(stock_price, window_size, num_of_std):
class CombinedBinHAndClucV3 (line 16) | class CombinedBinHAndClucV3(IStrategy):
method custom_stoploss (line 52) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 58) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 78) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 98) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV4/CombinedBinHAndClucV4.py
function bollinger_bands (line 9) | def bollinger_bands(stock_price, window_size, num_of_std):
class CombinedBinHAndClucV4 (line 16) | class CombinedBinHAndClucV4(IStrategy):
method custom_stoploss (line 56) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 63) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 81) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 103) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV5/CombinedBinHAndClucV5.py
class CombinedBinHAndClucV5 (line 36) | class CombinedBinHAndClucV5(IStrategy):
method custom_stoploss (line 76) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 83) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 102) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 124) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV5Hyperoptable/CombinedBinHAndClucV5Hyperoptable.py
class CombinedBinHAndClucV5Hyperoptable (line 39) | class CombinedBinHAndClucV5Hyperoptable(IStrategy):
method custom_stoploss (line 83) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 93) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 112) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 134) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
class HyperOpt (line 147) | class HyperOpt:
method sell_indicator_space (line 152) | def sell_indicator_space() -> List[Dimension]:
FILE: strategies/CombinedBinHAndClucV6/CombinedBinHAndClucV6.py
function SSLChannels (line 39) | def SSLChannels(dataframe, length = 7):
class CombinedBinHAndClucV6 (line 51) | class CombinedBinHAndClucV6(IStrategy):
method custom_stoploss (line 92) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method confirm_trade_exit (line 99) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method informative_pairs (line 109) | def informative_pairs(self):
method informative_1h_indicators (line 114) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 130) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 159) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 169) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 208) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV6H/CombinedBinHAndClucV6H.py
class CombinedBinHAndClucV6H (line 52) | class CombinedBinHAndClucV6H(IStrategy):
method informative_pairs (line 181) | def informative_pairs(self):
method get_informative_indicators (line 192) | def get_informative_indicators(self, dataframe: DataFrame, metadata: d...
method get_main_indicators (line 215) | def get_main_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_indicators (line 253) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 270) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 370) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 392) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method confirm_trade_exit (line 403) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function SSLChannels_ATR (line 432) | def SSLChannels_ATR(dataframe, length=7):
FILE: strategies/CombinedBinHAndClucV7/CombinedBinHAndClucV7.py
function SSLChannels (line 41) | def SSLChannels(dataframe, length = 7):
class CombinedBinHAndClucV7 (line 53) | class CombinedBinHAndClucV7(IStrategy):
method custom_stoploss (line 125) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method confirm_trade_exit (line 132) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method informative_pairs (line 151) | def informative_pairs(self):
method informative_1h_indicators (line 156) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 174) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 207) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 217) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 293) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV8/CombinedBinHAndClucV8.py
function SSLChannels (line 41) | def SSLChannels(dataframe, length = 7):
class CombinedBinHAndClucV8 (line 53) | class CombinedBinHAndClucV8(IStrategy):
method custom_stoploss (line 143) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 156) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 180) | def informative_pairs(self):
method informative_1h_indicators (line 185) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 205) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 240) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 250) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 349) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV8Hyper/CombinedBinHAndClucV8Hyper.py
function SSLChannels (line 41) | def SSLChannels(dataframe, length = 7):
class CombinedBinHAndClucV8Hyper (line 53) | class CombinedBinHAndClucV8Hyper(IStrategy):
method custom_stoploss (line 180) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 193) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 217) | def informative_pairs(self):
method informative_1h_indicators (line 222) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 242) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 277) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 287) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 386) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV8XH/CombinedBinHAndClucV8XH.py
function SSLChannels (line 42) | def SSLChannels(dataframe, length=7):
class CombinedBinHAndClucV8XH (line 55) | class CombinedBinHAndClucV8XH(IStrategy):
method custom_stoploss (line 227) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 250) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 274) | def informative_pairs(self):
method informative_1h_indicators (line 279) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 301) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 340) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 351) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 451) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHAndClucV8XHO/CombinedBinHAndClucV8XHO.py
function SSLChannels (line 42) | def SSLChannels(dataframe, length=7):
class CombinedBinHAndClucV8XHO (line 55) | class CombinedBinHAndClucV8XHO(IStrategy):
method custom_stoploss (line 206) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method custom_sell (line 229) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 253) | def informative_pairs(self):
method informative_1h_indicators (line 258) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 280) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 319) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 330) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 430) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHClucAndMADV3/CombinedBinHClucAndMADV3.py
class CombinedBinHClucAndMADV3 (line 32) | class CombinedBinHClucAndMADV3(IStrategy):
method custom_stoploss (line 73) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 81) | def informative_pairs(self):
method informative_1h_indicators (line 86) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 98) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 129) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 140) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 177) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHClucAndMADV5/CombinedBinHClucAndMADV5.py
function SSLChannels (line 48) | def SSLChannels(dataframe, length = 7):
class CombinedBinHClucAndMADV5 (line 59) | class CombinedBinHClucAndMADV5(IStrategy):
method custom_stoploss (line 101) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 109) | def informative_pairs(self):
method informative_1h_indicators (line 114) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 131) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 165) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 176) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 236) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHClucAndMADV6/CombinedBinHClucAndMADV6.py
function SSLChannels (line 56) | def SSLChannels(dataframe, length = 7):
class CombinedBinHClucAndMADV6 (line 67) | class CombinedBinHClucAndMADV6(IStrategy):
method custom_stoploss (line 110) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 118) | def informative_pairs(self):
method informative_1h_indicators (line 123) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 140) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 165) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 176) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 239) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CombinedBinHClucAndMADV9/CombinedBinHClucAndMADV9.py
function SSLChannels (line 57) | def SSLChannels(dataframe, length=7):
class CombinedBinHClucAndMADV9 (line 69) | class CombinedBinHClucAndMADV9(IStrategy):
method custom_stoploss (line 163) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 193) | def informative_pairs(self):
method informative_1h_indicators (line 198) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 215) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 237) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 247) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 386) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Combined_Indicators/Combined_Indicators.py
function bollinger_bands (line 10) | def bollinger_bands(stock_price, window_size, num_of_std):
class Combined_Indicators (line 17) | class Combined_Indicators(IStrategy):
method populate_indicators (line 41) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 57) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 76) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Combined_NFIv6_SMA/Combined_NFIv6_SMA.py
class Combined_NFIv6_SMA (line 43) | class Combined_NFIv6_SMA(IStrategy):
method get_ticker_indicator (line 940) | def get_ticker_indicator(self):
method custom_sell (line 943) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method range_percent_change (line 1087) | def range_percent_change(self, dataframe: DataFrame, length: int) -> f...
method range_maxgap (line 1097) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1107) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1117) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1127) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method informative_pairs (line 1139) | def informative_pairs(self):
method informative_1h_indicators (line 1146) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 1216) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1293) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1304) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2170) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 2262) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 2270) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/Combined_NFIv7_SMA/Combined_NFIv7_SMA.py
class Combined_NFIv7_SMA (line 44) | class Combined_NFIv7_SMA(IStrategy):
method get_ticker_indicator (line 1121) | def get_ticker_indicator(self):
method custom_sell (line 1124) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method range_percent_change (line 1289) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 1305) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 1318) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1328) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1338) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1348) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 1360) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 1375) | def informative_pairs(self):
method informative_1h_indicators (line 1382) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 1491) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1571) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1582) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2487) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 2577) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 2585) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/Combined_NFIv7_SMA_Rallipanos_20210707/Combined_NFIv7_SMA_Rallipanos_20210707.py
class Combined_NFIv7_SMA_Rallipanos_20210707 (line 44) | class Combined_NFIv7_SMA_Rallipanos_20210707(IStrategy):
method get_ticker_indicator (line 1121) | def get_ticker_indicator(self):
method custom_sell (line 1124) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method range_percent_change (line 1289) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 1305) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 1318) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1328) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1338) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1348) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 1360) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 1375) | def informative_pairs(self):
method informative_1h_indicators (line 1382) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 1491) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1571) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1582) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2487) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 2577) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 2585) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/Combined_NFIv7_SMA_bAdBoY_20211204/Combined_NFIv7_SMA_bAdBoY_20211204.py
class Combined_NFIv7_SMA_bAdBoY_20211204 (line 44) | class Combined_NFIv7_SMA_bAdBoY_20211204(IStrategy):
method get_ticker_indicator (line 1121) | def get_ticker_indicator(self):
method custom_sell (line 1124) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method range_percent_change (line 1289) | def range_percent_change(self, dataframe: DataFrame, method, length: i...
method top_percent_change (line 1305) | def top_percent_change(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap (line 1318) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1328) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1338) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1348) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method safe_dips (line 1360) | def safe_dips(self, dataframe: DataFrame, thresh_0, thresh_2, thresh_1...
method informative_pairs (line 1375) | def informative_pairs(self):
method informative_1h_indicators (line 1382) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method normal_tf_indicators (line 1491) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1571) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1582) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2487) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function EWO (line 2577) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 2585) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/CoreStrategy/CoreStrategy.py
class CoreStrategy (line 23) | class CoreStrategy(IStrategy):
method custom_stoploss (line 362) | def custom_stoploss(
method custom_sell (line 404) | def custom_sell(
method informative_pairs (line 464) | def informative_pairs(self):
method informative_1h_indicators (line 469) | def informative_1h_indicators(
method normal_tf_indicators (line 497) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 548) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 564) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 1122) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function SSLChannels_ATR (line 1171) | def SSLChannels_ATR(dataframe, length=7):
function SSLChannels (line 1192) | def SSLChannels(dataframe, length=7):
function EWO (line 1206) | def EWO(dataframe, ema_length=5, ema2_length=35):
class BinClucMadv1 (line 1214) | class BinClucMadv1(CoreStrategy):
class BinClucMadv2 (line 1254) | class BinClucMadv2(CoreStrategy):
class BinClucMadSMAv1 (line 1295) | class BinClucMadSMAv1(CoreStrategy):
class BinClucMadSMAv2 (line 1339) | class BinClucMadSMAv2(CoreStrategy):
FILE: strategies/CrossEMAStrategy/CrossEMAStrategy.py
class CrossEMAStrategy (line 19) | class CrossEMAStrategy(IStrategy):
method informative_pairs (line 136) | def informative_pairs(self):
method populate_indicators (line 149) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 172) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 189) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/CryptoFrog/CryptoFrog.py
class CryptoFrog (line 20) | class CryptoFrog(IStrategy):
method informative_pairs (line 133) | def informative_pairs(self):
method HA (line 141) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 167) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 181) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 194) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 261) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 295) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 358) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 395) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 420) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 469) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 482) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 504) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 528) | class HyperOpt:
method indicator_space (line 533) | def indicator_space() -> List[Dimension]:
function RMI (line 538) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 556) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 573) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO/CryptoFrogHO.py
class CryptoFrogHO (line 20) | class CryptoFrogHO(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO2/CryptoFrogHO2.py
class CryptoFrogHO2 (line 20) | class CryptoFrogHO2(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO2A/CryptoFrogHO2A.py
class CryptoFrogHO2A (line 20) | class CryptoFrogHO2A(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO3A1/CryptoFrogHO3A1.py
class CryptoFrogHO3A1 (line 20) | class CryptoFrogHO3A1(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO3A2/CryptoFrogHO3A2.py
class CryptoFrogHO3A2 (line 20) | class CryptoFrogHO3A2(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO3A3/CryptoFrogHO3A3.py
class CryptoFrogHO3A3 (line 20) | class CryptoFrogHO3A3(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogHO3A4/CryptoFrogHO3A4.py
class CryptoFrogHO3A4 (line 20) | class CryptoFrogHO3A4(IStrategy):
method informative_pairs (line 144) | def informative_pairs(self):
method HA (line 152) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 178) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 192) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 205) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method populate_indicators (line 272) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 406) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 431) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 480) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 493) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 515) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 539) | class HyperOpt:
method indicator_space (line 544) | def indicator_space() -> List[Dimension]:
function RMI (line 549) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 567) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 584) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
FILE: strategies/CryptoFrogNFI/CryptoFrogNFI.py
class CryptoFrogNFI (line 21) | class CryptoFrogNFI(IStrategy):
method custom_sell (line 1004) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 1148) | def informative_pairs(self):
method HA (line 1154) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 1180) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 1194) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 1207) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method informative_1h_indicators (line 1273) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method range_percent_change (line 1331) | def range_percent_change(self, dataframe: DataFrame, length: int) -> f...
method range_maxgap (line 1341) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1351) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1361) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1371) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method normal_tf_indicators (line 1383) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1448) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1490) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2369) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 2493) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 2518) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 2567) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 2580) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 2602) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 2626) | class HyperOpt:
method indicator_space (line 2631) | def indicator_space() -> List[Dimension]:
function RMI (line 2636) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 2654) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 2671) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function EWO (line 2681) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 2689) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/CryptoFrogNFIHO1A/CryptoFrogNFIHO1A.py
class CryptoFrogNFIHO1A (line 21) | class CryptoFrogNFIHO1A(IStrategy):
method custom_sell (line 1546) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 1690) | def informative_pairs(self):
method HA (line 1696) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 1722) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 1736) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 1749) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method informative_1h_indicators (line 1815) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method range_percent_change (line 1873) | def range_percent_change(self, dataframe: DataFrame, length: int) -> f...
method range_maxgap (line 1883) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1893) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1903) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1913) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method normal_tf_indicators (line 1925) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1990) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 2032) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2911) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 3035) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 3060) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 3109) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 3122) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 3144) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 3168) | class HyperOpt:
method indicator_space (line 3173) | def indicator_space() -> List[Dimension]:
function RMI (line 3178) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 3196) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 3213) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function EWO (line 3223) | def EWO(dataframe, sma1_length=5, sma2_length=35):
function chaikin_money_flow (line 3231) | def chaikin_money_flow(dataframe, n=20, fillna=False):
FILE: strategies/CryptoFrogOffset/CryptoFrogOffset.py
class CryptoFrogOffset (line 21) | class CryptoFrogOffset(IStrategy):
method custom_sell (line 1528) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 1650) | def informative_pairs(self):
method HA (line 1658) | def HA(self, dataframe, smoothing=None):
method hansen_HA (line 1684) | def hansen_HA(self, informative_df, period=6):
method bbw_expansion (line 1698) | def bbw_expansion(self, bbw_rolling, mult=1.1):
method do_indicators (line 1711) | def do_indicators(self, dataframe: DataFrame, metadata: dict) -> DataF...
method informative_1h_indicators (line 1777) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method range_percent_change (line 1830) | def range_percent_change(self, dataframe: DataFrame, length: int) -> f...
method range_maxgap (line 1840) | def range_maxgap(self, dataframe: DataFrame, length: int) -> float:
method range_maxgap_adjusted (line 1850) | def range_maxgap_adjusted(self, dataframe: DataFrame, length: int, adj...
method range_height (line 1860) | def range_height(self, dataframe: DataFrame, length: int) -> float:
method safe_pump (line 1870) | def safe_pump(self, dataframe: DataFrame, length: int, thresh: float, ...
method normal_tf_indicators (line 1882) | def normal_tf_indicators(self, dataframe: DataFrame, metadata: dict) -...
method populate_indicators (line 1947) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 1989) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 2052) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 2146) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 2171) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 2220) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method get_current_price (line 2233) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 2255) | def populate_trades(self, pair: str) -> dict:
class HyperOpt (line 2279) | class HyperOpt:
method indicator_space (line 2284) | def indicator_space() -> List[Dimension]:
function RMI (line 2289) | def RMI(dataframe, *, length=20, mom=5):
function SSLChannels_ATR (line 2307) | def SSLChannels_ATR(dataframe, length=7):
function SROC (line 2324) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
function EWO (line 2334) | def EWO(dataframe, sma1_length=5, sma2_length=35):
FILE: strategies/CustomStoplossWithPSAR/CustomStoplossWithPSAR.py
class CustomStoplossWithPSAR (line 18) | class CustomStoplossWithPSAR(IStrategy):
method custom_stoploss (line 31) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 57) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 67) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 82) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/DCBBBounce/DCBBBounce.py
class DCBBBounce (line 16) | class DCBBBounce(IStrategy):
method informative_pairs (line 106) | def informative_pairs(self):
method populate_indicators (line 119) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 179) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 227) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/DD/DD.py
class DD (line 11) | class DD(IStrategy):
method populate_indicators (line 43) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 54) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 73) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/DIV_v1/DIV_v1.py
class DIV_v1 (line 10) | class DIV_v1(IStrategy):
method get_ticker_indicator (line 70) | def get_ticker_indicator(self):
method populate_indicators (line 73) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 82) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 93) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
function divergence (line 97) | def divergence(dataframe: DataFrame, source='rsi'):
FILE: strategies/DevilStra/DevilStra.py
function spell_finder (line 327) | def spell_finder(index, space):
function normalize (line 331) | def normalize(df):
function gene_calculator (line 336) | def gene_calculator(dataframe, indicator):
function condition_generator (line 404) | def condition_generator(dataframe, operator, indicator, crossed_indicato...
class DevilStra (line 536) | class DevilStra(IStrategy):
method populate_indicators (line 582) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 586) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 656) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Diamond/Diamond.py
class Diamond (line 54) | class Diamond(IStrategy):
method populate_indicators (line 117) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 125) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 142) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Divergences/Divergences.py
class Divergences (line 16) | class Divergences(IStrategy):
method informative_pairs (line 100) | def informative_pairs(self):
method populate_indicators (line 113) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 367) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 385) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Dracula/Dracula.py
function EWO (line 40) | def EWO(dataframe, ema_length=5, ema2_length=35):
function chaikin_money_flow (line 47) | def chaikin_money_flow(dataframe, n=20, fillna=False):
class SupResFinder (line 68) | class SupResFinder():
method isSupport (line 69) | def isSupport(self, df, i):
method isResistance (line 75) | def isResistance(self, df, i):
method getSupport (line 81) | def getSupport(self, df):
method getResistance (line 96) | def getResistance(self, df):
class Dracula (line 112) | class Dracula(IStrategy):
method populate_indicators (line 152) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 172) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method custom_sell (line 206) | def custom_sell(self, pair: str, trade: Trade, current_time: datetime,...
method populate_sell_trend (line 235) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Dyna_opti/Dyna_opti.py
function same_length (line 33) | def same_length(bigger, shorter):
function linear_growth (line 39) | def linear_growth(start: float, end: float, start_time: int, end_time: i...
function linear_decay (line 48) | def linear_decay(start: float, end: float, start_time: int, end_time: in...
function zema (line 61) | def zema(dataframe, period, field='close'):
function RMI (line 75) | def RMI(dataframe, *, length=20, mom=5):
function mastreak (line 93) | def mastreak(dataframe: DataFrame, period: int = 4, field='close') -> Se...
function pcc (line 112) | def pcc(dataframe: DataFrame, period: int = 20, mult: int = 2):
function SSLChannels (line 136) | def SSLChannels(dataframe, length=10, mode='sma'):
function SSLChannels_ATR (line 161) | def SSLChannels_ATR(dataframe, length=7):
function WaveTrend (line 178) | def WaveTrend(dataframe, chlen=10, avg=21, smalen=4):
function T3 (line 197) | def T3(dataframe, length=5):
function SROC (line 220) | def SROC(dataframe, roclen=21, emalen=13, smooth=21):
class Dyna_opti (line 241) | class Dyna_opti(IStrategy):
method informative_pairs (line 332) | def informative_pairs(self):
method populate_indicators (line 342) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 429) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 465) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 474) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method min_roi_reached_dynamic (line 500) | def min_roi_reached_dynamic(self, trade: Trade, current_profit: float,...
method min_roi_reached (line 550) | def min_roi_reached(self, trade: Trade, current_profit: float, current...
method check_buy_timeout (line 566) | def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kw...
method check_sell_timeout (line 574) | def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **k...
method get_pair_params (line 587) | def get_pair_params(self, pair: str, params: str) -> Dict:
method get_current_price (line 623) | def get_current_price(self, pair: str, refresh: bool) -> float:
method populate_trades (line 645) | def populate_trades(self, pair: str) -> dict:
FILE: strategies/EI3v2_tag_cofi_green/EI3v2_tag_cofi_green.py
function EWO (line 24) | def EWO(dataframe, ema_length=5, ema2_length=3):
class EI3v2_tag_cofi_green (line 33) | class EI3v2_tag_cofi_green(IStrategy):
method protections (line 72) | def protections(self):
method custom_sell (line 179) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
method informative_pairs (line 185) | def informative_pairs(self):
method pump_dump_protection (line 199) | def pump_dump_protection(self, dataframe: DataFrame, metadata: dict) -...
method base_tf_btc_indicators (line 217) | def base_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict)...
method info_tf_btc_indicators (line 229) | def info_tf_btc_indicators(self, dataframe: DataFrame, metadata: dict)...
method populate_indicators (line 242) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 306) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 375) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method confirm_trade_exit (line 404) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
function pct_change (line 412) | def pct_change(a, b):
class EI3v2_tag_cofi_dca_green (line 415) | class EI3v2_tag_cofi_dca_green(EI3v2_tag_cofi_green):
method populate_indicators (line 432) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method adjust_trade_position (line 437) | def adjust_trade_position(self, trade: Trade, current_time: datetime,
FILE: strategies/EMA50/EMA50.py
class EMA50 (line 20) | class EMA50(IStrategy):
method informative_pairs (line 119) | def informative_pairs(self):
method populate_indicators (line 132) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 352) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 379) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/EMA520015_V17/EMA520015_V17.py
class EMA520015_V17 (line 11) | class EMA520015_V17(IStrategy):
method populate_indicators (line 36) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 58) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 70) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_sell (line 81) | def custom_sell(self, pair: str, trade: 'Trade', current_time: 'dateti...
FILE: strategies/EMABBRSI/EMABBRSI.py
class EMABBRSI (line 10) | class EMABBRSI(IStrategy):
method populate_indicators (line 43) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 81) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 112) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/EMABreakout/EMABreakout.py
class EMABreakout (line 20) | class EMABreakout(IStrategy):
method informative_pairs (line 105) | def informative_pairs(self):
method populate_indicators (line 118) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 340) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 371) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/EMASkipPump/EMASkipPump.py
class EMASkipPump (line 12) | class EMASkipPump(IStrategy):
method populate_indicators (line 36) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 62) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 75) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/EMAVolume/EMAVolume.py
class EMAVolume (line 10) | class EMAVolume(IStrategy):
method populate_indicators (line 32) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 42) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 57) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/EMA_CROSSOVER_STRATEGY/EMA_CROSSOVER_STRATEGY.py
class EMA_CROSSOVER_STRATEGY (line 16) | class EMA_CROSSOVER_STRATEGY(IStrategy):
method informative_pairs (line 97) | def informative_pairs(self):
method populate_indicators (line 110) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 129) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 148) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/EXPERIMENTAL_STRATEGY/EXPERIMENTAL_STRATEGY.py
class EXPERIMENTAL_STRATEGY (line 16) | class EXPERIMENTAL_STRATEGY(IStrategy):
method informative_pairs (line 54) | def informative_pairs(self):
method populate_indicators (line 67) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 119) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 141) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV2/ElliotV2.py
function EWO (line 32) | def EWO(dataframe, ema_length=5, ema2_length=35):
function populate_indicators (line 39) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> D...
class ElliotV2 (line 260) | class ElliotV2(IStrategy):
method informative_pairs (line 327) | def informative_pairs(self):
method get_informative_indicators (line 334) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 341) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 359) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 387) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV4/ElliotV4.py
function EWO (line 18) | def EWO(dataframe, ema_length=5, ema2_length=35):
function populate_indicators (line 26) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> D...
class ElliotV4 (line 219) | class ElliotV4(IStrategy):
method informative_pairs (line 287) | def informative_pairs(self):
method get_informative_indicators (line 295) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 302) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 320) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 348) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV531/ElliotV531.py
function EWO (line 50) | def EWO(dataframe, ema_length=5, ema2_length=35):
function populate_indicators (line 58) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> D...
class ElliotV531 (line 227) | class ElliotV531(IStrategy):
method confirm_trade_exit (line 339) | def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str,...
method custom_stoploss (line 370) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 430) | def informative_pairs(self):
method get_informative_indicators (line 437) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 444) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 465) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 493) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV5HO/ElliotV5HO.py
function EWO (line 48) | def EWO(dataframe, ema_length=5, ema2_length=35):
function populate_indicators (line 56) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> D...
class ElliotV5HO (line 225) | class ElliotV5HO(IStrategy):
method custom_stoploss (line 331) | def custom_stoploss(self, pair: str, trade: Trade, current_time: datet...
method informative_pairs (line 349) | def informative_pairs(self):
method get_informative_indicators (line 356) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 363) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 381) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 409) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV5HOMod2/ElliotV5HOMod2.py
function EWO (line 18) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ElliotV5HOMod2 (line 26) | class ElliotV5HOMod2(IStrategy):
method informative_pairs (line 119) | def informative_pairs(self):
method get_informative_indicators (line 127) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 134) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 171) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 200) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 218) | def custom_stoploss(self, pair: str, trade: Trade, current_time: datet...
FILE: strategies/ElliotV5HOMod3/ElliotV5HOMod3.py
function EWO (line 18) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ElliotV5HOMod3 (line 26) | class ElliotV5HOMod3(IStrategy):
method informative_pairs (line 113) | def informative_pairs(self):
method get_informative_indicators (line 121) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 128) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 154) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 182) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method custom_stoploss (line 200) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
FILE: strategies/ElliotV7/ElliotV7.py
function EWO (line 35) | def EWO(dataframe, ema_length=5, ema2_length=35):
function populate_indicators (line 42) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> D...
class ElliotV7 (line 47) | class ElliotV7(IStrategy):
method custom_stoploss (line 116) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method informative_pairs (line 125) | def informative_pairs(self):
method informative_1h_indicators (line 132) | def informative_1h_indicators(self, dataframe: DataFrame, metadata: di...
method populate_indicators (line 148) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 179) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 217) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV8HO/ElliotV8HO.py
function EWO (line 12) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ElliotV8HO (line 20) | class ElliotV8HO(IStrategy):
method informative_pairs (line 120) | def informative_pairs(self):
method get_informative_indicators (line 128) | def get_informative_indicators(self, metadata: dict):
method populate_indicators (line 135) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 167) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 207) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV8_original/ElliotV8_original.py
function EWO (line 35) | def EWO(dataframe, ema_length=5, ema2_length=35):
class ElliotV8_original (line 44) | class ElliotV8_original(IStrategy):
method populate_indicators (line 113) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 138) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 176) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV8_original_ichiv2/ElliotV8_original_ichiv2.py
function EWO (line 35) | def EWO(dataframe, ema_length=5, ema2_length=3):
class ElliotV8_original_ichiv2 (line 44) | class ElliotV8_original_ichiv2(IStrategy):
method protections (line 57) | def protections(self):
method populate_indicators (line 149) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 174) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 212) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ElliotV8_original_ichiv3/ElliotV8_original_ichiv3.py
function EWO (line 35) | def EWO(dataframe, ema_length=5, ema2_length=3):
class ElliotV8_original_ichiv3 (line 44) | class ElliotV8_original_ichiv3(IStrategy):
method protections (line 58) | def protections(self):
method populate_indicators (line 151) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 176) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 214) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Elliotv8/Elliotv8.py
function EWO (line 38) | def EWO(dataframe, ema_length=5, ema2_length=35):
class Elliotv8 (line 47) | class Elliotv8(IStrategy):
method populate_indicators (line 116) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 141) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 179) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FRAYSTRAT/FRAYSTRAT.py
class FRAYSTRAT (line 19) | class FRAYSTRAT(IStrategy):
method protections (line 37) | def protections(self):
method informative_pairs (line 145) | def informative_pairs(self):
method populate_indicators (line 158) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 377) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 412) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Fakebuy/Fakebuy.py
function bollinger_bands (line 19) | def bollinger_bands(stock_price, window_size, num_of_std):
class Fakebuy (line 25) | class Fakebuy(IStrategy):
method informative_pairs (line 58) | def informative_pairs(self):
method populate_indicators (line 63) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 122) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 169) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method get_current_price (line 205) | def get_current_price(self, pair: str) -> float:
method check_buy_timeout (line 225) | def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kw...
method check_sell_timeout (line 233) | def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **k...
method confirm_trade_entry (line 241) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
FILE: strategies/FastSupertrend/FastSupertrend.py
class FastSupertrend (line 25) | class FastSupertrend(IStrategy):
method populate_indicators (line 84) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 111) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 123) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method supertrend (line 139) | def supertrend(self, dataframe: DataFrame, multiplier, period):
FILE: strategies/FastSupertrendOpt/FastSupertrendOpt.py
class FastSupertrendOpt (line 25) | class FastSupertrendOpt(IStrategy):
method populate_indicators (line 85) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 88) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 107) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method supertrend (line 123) | def supertrend(self, dataframe: DataFrame, multiplier, period):
FILE: strategies/FiveMinCrossAbove/FiveMinCrossAbove.py
class FiveMinCrossAbove (line 13) | class FiveMinCrossAbove(IStrategy):
method informative_pairs (line 60) | def informative_pairs(self):
method populate_indicators (line 73) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 90) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 107) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FixedRiskRewardLoss/FixedRiskRewardLoss.py
class FixedRiskRewardLoss (line 20) | class FixedRiskRewardLoss(IStrategy):
method custom_stoploss (line 40) | def custom_stoploss(self, pair: str, trade: 'Trade', current_time: dat...
method populate_indicators (line 90) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 100) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 111) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/ForexSignal/ForexSignal.py
class ForexSignal (line 18) | class ForexSignal(IStrategy):
method informative_pairs (line 100) | def informative_pairs(self):
method populate_indicators (line 110) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 139) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 157) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FrostAuraM115mStrategy/FrostAuraM115mStrategy.py
class FrostAuraM115mStrategy (line 8) | class FrostAuraM115mStrategy(IStrategy):
method informative_pairs (line 81) | def informative_pairs(self):
method populate_indicators (line 84) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 106) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 119) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FrostAuraM11hStrategy/FrostAuraM11hStrategy.py
class FrostAuraM11hStrategy (line 8) | class FrostAuraM11hStrategy(IStrategy):
method informative_pairs (line 81) | def informative_pairs(self):
method populate_indicators (line 84) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 106) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 119) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FrostAuraM21hStrategy/FrostAuraM21hStrategy.py
class FrostAuraM21hStrategy (line 8) | class FrostAuraM21hStrategy(IStrategy):
method informative_pairs (line 81) | def informative_pairs(self):
method populate_indicators (line 84) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 95) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 109) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FrostAuraM315mStrategy/FrostAuraM315mStrategy.py
class FrostAuraM315mStrategy (line 8) | class FrostAuraM315mStrategy(IStrategy):
method informative_pairs (line 81) | def informative_pairs(self):
method populate_indicators (line 84) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 116) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 132) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FrostAuraM31hStrategy/FrostAuraM31hStrategy.py
class FrostAuraM31hStrategy (line 8) | class FrostAuraM31hStrategy(IStrategy):
method informative_pairs (line 81) | def informative_pairs(self):
method populate_indicators (line 84) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 116) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 132) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/FrostAuraRandomStrategy/FrostAuraRandomStrategy.py
class FrostAuraRandomStrategy (line 7) | class FrostAuraRandomStrategy(IStrategy):
method populate_indicators (line 78) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 86) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 100) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/GodCard/GodCard.py
class GodCard (line 13) | class GodCard(IStrategy):
method protections (line 24) | def protections(self):
method informative_pairs (line 105) | def informative_pairs(self):
method populate_indicators (line 109) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 135) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 161) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/GodStraNew/GodStraNew.py
function normalize (line 251) | def normalize(df):
function gene_calculator (line 256) | def gene_calculator(dataframe, indicator):
function condition_generator (line 324) | def condition_generator(dataframe, operator, indicator, crossed_indicato...
class GodStraNew (line 451) | class GodStraNew(IStrategy):
method populate_indicators (line 508) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 518) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 572) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/GodStraNew40/GodStraNew40.py
function normalize (line 251) | def normalize(df):
function gene_calculator (line 256) | def gene_calculator(dataframe, indicator):
function condition_generator (line 324) | def condition_generator(dataframe, operator, indicator, crossed_indicato...
class GodStraNew40 (line 483) | class GodStraNew40(IStrategy):
method populate_indicators (line 540) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 550) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 604) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/GodStraNew_SMAonly/GodStraNew_SMAonly.py
function normalize (line 251) | def normalize(df):
function gene_calculator (line 256) | def gene_calculator(dataframe, indicator):
function condition_generator (line 324) | def condition_generator(dataframe, operator, indicator, crossed_indicato...
class GodStraNew_SMAonly (line 451) | class GodStraNew_SMAonly(IStrategy):
method populate_indicators (line 554) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 564) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 618) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
FILE: strategies/Guacamole/Guacamole.py
class Guacamole (line 14) | class Guacamole(IStrategy):
method populate_indicators (line 68) | def populate_indicators(self, dataframe: DataFrame, metadata: dict) ->...
method populate_buy_trend (line 85) | def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> ...
method populate_sell_trend (line 114) | def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) ->...
method check_buy_timeout (line 142) | def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kw...
method check_sell_timeout (line 150) | def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **k...
method confirm_trade_entry (line 158) | def confirm_trade_entry(self, pair: str, order_type: str, amount: floa...
FILE: strategies/Gumbo1/Gumbo1.py
class Gumbo1 (line 27) | class Gumbo1(IStrategy):
method informative_pairs (line 49) | def informative_pairs(self) -> ListPairs
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Download .json
Condensed preview — 467 files, each showing path, character count, and a content snippet. Download the .json file for the full structured content (17,803K chars).
[
{
"path": "LICENSE",
"chars": 35141,
"preview": " GNU GENERAL PUBLIC LICENSE\n Version 3, 29 June 2007\n\n Copyright (C) 2007 Free "
},
{
"path": "README.md",
"chars": 794,
"preview": "# Freqtrade Strategies Repository\n\nThis repository is dedicated to sharing open-source trading strategies for the Freqtr"
},
{
"path": "strategies/ADXMomentum/ADXMomentum.py",
"chars": 2102,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/ADX_15M_USDT/ADX_15M_USDT.py",
"chars": 2067,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/ADX_15M_USDT2/ADX_15M_USDT2.py",
"chars": 2135,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/ASDTSRockwellTrading/ASDTSRockwellTrading.py",
"chars": 2540,
"preview": "\n# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfro"
},
{
"path": "strategies/ActionZone/ActionZone.py",
"chars": 6666,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n# isort: skip_"
},
{
"path": "strategies/AdxSmas/AdxSmas.py",
"chars": 1749,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/AlligatorStrat/AlligatorStrat.py",
"chars": 3502,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\n# ---"
},
{
"path": "strategies/AlligatorStrategy/AlligatorStrategy.py",
"chars": 8852,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n# isort: skip_"
},
{
"path": "strategies/AlwaysBuy/AlwaysBuy.py",
"chars": 1039,
"preview": "from freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\n\n\nclass AlwaysBuy(IStrategy):\n\n INTER"
},
{
"path": "strategies/Apollo11/Apollo11.py",
"chars": 8834,
"preview": "from datetime import datetime\nfrom datetime import timedelta\nfrom functools import reduce\n\nimport freqtrade.vendor.qtpyl"
},
{
"path": "strategies/AverageStrategy/AverageStrategy.py",
"chars": 1964,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\n# ---"
},
{
"path": "strategies/AwesomeMacd/AwesomeMacd.py",
"chars": 1900,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BBMod1/BBMod1.py",
"chars": 52576,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BBRSI/BBRSI.py",
"chars": 4154,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/BBRSI2/BBRSI2.py",
"chars": 1897,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/BBRSI21/BBRSI21.py",
"chars": 3052,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BBRSI3366/BBRSI3366.py",
"chars": 3526,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BBRSI4cust/BBRSI4cust.py",
"chars": 5709,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n# isort: skip_"
},
{
"path": "strategies/BBRSINaiveStrategy/BBRSINaiveStrategy.py",
"chars": 4046,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/BBRSIOptim2020Strategy/BBRSIOptim2020Strategy.py",
"chars": 4082,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/BBRSIOptimStrategy/BBRSIOptimStrategy.py",
"chars": 4075,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/BBRSIOptimizedStrategy/BBRSIOptimizedStrategy.py",
"chars": 4182,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/BBRSIS/BBRSIS.py",
"chars": 4812,
"preview": "import talib.abstract as ta\nfrom pandas import DataFrame\nfrom technical.util import resample_to_interval, resampled_merg"
},
{
"path": "strategies/BBRSIStrategy/BBRSIStrategy.py",
"chars": 4164,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/BBRSITV/BBRSITV.py",
"chars": 20936,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame, Seri"
},
{
"path": "strategies/BBRSIoriginal/BBRSIoriginal.py",
"chars": 3653,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n\nimport talib.abstract as ta\nimport"
},
{
"path": "strategies/BBRSIv2/BBRSIv2.py",
"chars": 5532,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BB_RPB_TSL/BB_RPB_TSL.py",
"chars": 55228,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_2/BB_RPB_TSL_2.py",
"chars": 62546,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_BI/BB_RPB_TSL_BI.py",
"chars": 45255,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_BIV1/BB_RPB_TSL_BIV1.py",
"chars": 45257,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_RNG/BB_RPB_TSL_RNG.py",
"chars": 20828,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_RNG_2/BB_RPB_TSL_RNG_2.py",
"chars": 20818,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_RNG_TBS/BB_RPB_TSL_RNG_TBS.py",
"chars": 35038,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_RNG_TBS_GOLD/BB_RPB_TSL_RNG_TBS_GOLD.py",
"chars": 35050,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_RNG_VWAP/BB_RPB_TSL_RNG_VWAP.py",
"chars": 23333,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSL_SMA_Tranz/BB_RPB_TSL_SMA_Tranz.py",
"chars": 225254,
"preview": "# --- Do not remove these libs ---\nimport pandas_ta as pta\nimport copy\nimport logging\nimport pathlib\nimport rapidjson\nim"
},
{
"path": "strategies/BB_RPB_TSL_SMA_Tranz_TB_1_1_1/BB_RPB_TSL_SMA_Tranz_TB_1_1_1.py",
"chars": 189397,
"preview": "# --- Do not remove these libs ---\nimport pandas_ta as pta\nimport copy\nimport logging\nimport pathlib\nimport rapidjson\nim"
},
{
"path": "strategies/BB_RPB_TSL_SMA_Tranz_TB_MOD/BB_RPB_TSL_SMA_Tranz_TB_MOD.py",
"chars": 193528,
"preview": "# --- Do not remove these libs ---\nimport pandas_ta as pta\nimport copy\nimport logging\nimport pathlib\nimport rapidjson\nim"
},
{
"path": "strategies/BB_RPB_TSL_Tranz/BB_RPB_TSL_Tranz.py",
"chars": 96261,
"preview": "# --- Do not remove these libs ---\nimport pandas_ta as pta\nimport copy\nimport logging\nimport pathlib\nimport rapidjson\nim"
},
{
"path": "strategies/BB_RPB_TSL_c7c477d_20211030/BB_RPB_TSL_c7c477d_20211030.py",
"chars": 23343,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RPB_TSLmeneguzzo/BB_RPB_TSLmeneguzzo.py",
"chars": 49391,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib"
},
{
"path": "strategies/BB_RSI/BB_RSI.py",
"chars": 3929,
"preview": "\n# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfro"
},
{
"path": "strategies/BB_Strategy04/BB_Strategy04.py",
"chars": 6262,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n\n# --- Do not remove these libs ---"
},
{
"path": "strategies/BBands/BBands.py",
"chars": 15379,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n\n# --- Do not "
},
{
"path": "strategies/BBandsRSI/BBandsRSI.py",
"chars": 6295,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n\n# --- Do not "
},
{
"path": "strategies/BBlower/BBlower.py",
"chars": 5941,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Dec 2 13:50:49 2020\n\n@author: alex\n\"\"\"\n\n# --- Do not "
},
{
"path": "strategies/Babico_SMA5xBBmid/Babico_SMA5xBBmid.py",
"chars": 1813,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/Bandtastic/Bandtastic.py",
"chars": 7104,
"preview": "import talib.abstract as ta\nimport numpy as np # noqa\nimport pandas as pd\nfrom functools import reduce\nfrom pandas impo"
},
{
"path": "strategies/BbRoi/BbRoi.py",
"chars": 2466,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BbandRsi/BbandRsi.py",
"chars": 1819,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BbandRsiRolling/BbandRsiRolling.py",
"chars": 2051,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/BcmbigzDevelop/BcmbigzDevelop.py",
"chars": 53815,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BcmbigzV1/BcmbigzV1.py",
"chars": 23739,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigPete/BigPete.py",
"chars": 32080,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom typing import "
},
{
"path": "strategies/BigZ03/BigZ03.py",
"chars": 24775,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ0307HO/BigZ0307HO.py",
"chars": 80815,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ03HO/BigZ03HO.py",
"chars": 25507,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ04/BigZ04.py",
"chars": 25981,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ0407/BigZ0407.py",
"chars": 80705,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ0407HO/BigZ0407HO.py",
"chars": 82269,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ04HO/BigZ04HO.py",
"chars": 26742,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ04HO2/BigZ04HO2.py",
"chars": 30377,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ04_TSL3/BigZ04_TSL3.py",
"chars": 28684,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ04_TSL4/BigZ04_TSL4.py",
"chars": 29070,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ06/BigZ06.py",
"chars": 27659,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ07/BigZ07.py",
"chars": 27940,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BigZ07Next/BigZ07Next.py",
"chars": 81775,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/BigZ07Next2/BigZ07Next2.py",
"chars": 81775,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/BinClucMad/BinClucMad.py",
"chars": 22666,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BinClucMadDevelop/BinClucMadDevelop.py",
"chars": 42857,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BinClucMadSMADevelop/BinClucMadSMADevelop.py",
"chars": 50925,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BinClucMadV1/BinClucMadV1.py",
"chars": 38236,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/BinHV27/BinHV27.py",
"chars": 5843,
"preview": "from freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom functools import reduce\nfrom panda"
},
{
"path": "strategies/BinHV45/BinHV45.py",
"chars": 2622,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy import IStrategy\nfrom freqtrade.strategy import IntParameter\n"
},
{
"path": "strategies/BinHV45HO/BinHV45HO.py",
"chars": 2687,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/BreakEven/BreakEven.py",
"chars": 2222,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\n# ---"
},
{
"path": "strategies/BuyAllSellAllStrategy/BuyAllSellAllStrategy.py",
"chars": 1151,
"preview": "from freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nfrom freqtrade.persistence import Trade\n"
},
{
"path": "strategies/BuyOnly/BuyOnly.py",
"chars": 13949,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n\n# --- Do not remove these libs ---"
},
{
"path": "strategies/CBPete9/CBPete9.py",
"chars": 20118,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/CCIStrategy/CCIStrategy.py",
"chars": 4424,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/CMCWinner/CMCWinner.py",
"chars": 3157,
"preview": "\n# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\n# --"
},
{
"path": "strategies/Cci/Cci.py",
"chars": 2979,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/Chandem/Chandem.py",
"chars": 4416,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Dec 2 13:50:49 2020\n\n@author: alex\n\"\"\"\n\n# --- Do not "
},
{
"path": "strategies/Chandemtwo/Chandemtwo.py",
"chars": 4552,
"preview": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Dec 2 13:50:49 2020\n\n@author: alex\n\"\"\"\n\n# --- Do not "
},
{
"path": "strategies/Chispei/Chispei.py",
"chars": 1930,
"preview": "# Freqtrade_backtest_validation_freqtrade1.py\n# This script is 1 of a pair the other being freqtrade_backtest_validation"
},
{
"path": "strategies/Cluc4/Cluc4.py",
"chars": 3494,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Cluc4werk/Cluc4werk.py",
"chars": 5966,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Cluc5werk/Cluc5werk.py",
"chars": 9793,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Cluc7werk/Cluc7werk.py",
"chars": 4224,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/ClucFiatROI/ClucFiatROI.py",
"chars": 6157,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nfrom functools import reduce\nimport talib.abstr"
},
{
"path": "strategies/ClucFiatSlow/ClucFiatSlow.py",
"chars": 4958,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/ClucHAnix/ClucHAnix.py",
"chars": 7878,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/ClucHAnix5m/ClucHAnix5m.py",
"chars": 34272,
"preview": "from datetime import datetime, timedelta, timezone\nfrom functools import reduce\nfrom typing import List\n# --- Do not rem"
},
{
"path": "strategies/ClucHAnix_5m/ClucHAnix_5m.py",
"chars": 8517,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/ClucHAnix_5m1/ClucHAnix_5m1.py",
"chars": 21764,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\r\nimport numpy as np\r\nimport talib.abstract as ta\r\nfrom freqtrade.s"
},
{
"path": "strategies/ClucHAnix_BB_RPB_MOD/ClucHAnix_BB_RPB_MOD.py",
"chars": 21311,
"preview": "from datetime import datetime, timedelta, timezone\nfrom functools import reduce\nfrom typing import List\n\nimport freqtrad"
},
{
"path": "strategies/ClucHAnix_BB_RPB_MOD2_ROI/ClucHAnix_BB_RPB_MOD2_ROI.py",
"chars": 34277,
"preview": "from datetime import datetime, timedelta, timezone\nfrom functools import reduce\nfrom typing import List\n# --- Do not rem"
},
{
"path": "strategies/ClucHAnix_BB_RPB_MOD_CTT/ClucHAnix_BB_RPB_MOD_CTT.py",
"chars": 50611,
"preview": "from datetime import datetime, timedelta, timezone\r\nfrom functools import reduce\r\nfrom freqtrade.strategy.interface impo"
},
{
"path": "strategies/ClucHAnix_BB_RPB_MOD_E0V1E_ROI/ClucHAnix_BB_RPB_MOD_E0V1E_ROI.py",
"chars": 37392,
"preview": "from datetime import datetime, timedelta, timezone\r\nfrom functools import reduce\r\nfrom typing import List\r\n# --- Do not "
},
{
"path": "strategies/ClucHAnix_hhll/ClucHAnix_hhll.py",
"chars": 34704,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\r\nimport numpy as np\r\nimport talib.abstract as ta\r\nimport time\r\nimp"
},
{
"path": "strategies/ClucHAwerk/ClucHAwerk.py",
"chars": 13933,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/ClucMay72018/ClucMay72018.py",
"chars": 2858,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/CofiBitStrategy/CofiBitStrategy.py",
"chars": 3027,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport talib.abstract as ta\nfro"
},
{
"path": "strategies/CombinedBinHAndCluc/CombinedBinHAndCluc.py",
"chars": 3228,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/CombinedBinHAndCluc2021/CombinedBinHAndCluc2021.py",
"chars": 3790,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/CombinedBinHAndCluc2021Bull/CombinedBinHAndCluc2021Bull.py",
"chars": 3804,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/CombinedBinHAndClucHyperV0/CombinedBinHAndClucHyperV0.py",
"chars": 8965,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/CombinedBinHAndClucHyperV3/CombinedBinHAndClucHyperV3.py",
"chars": 10056,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/CombinedBinHAndClucV2/CombinedBinHAndClucV2.py",
"chars": 6119,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/CombinedBinHAndClucV3/CombinedBinHAndClucV3.py",
"chars": 4402,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV4/CombinedBinHAndClucV4.py",
"chars": 4729,
"preview": "# Definition of Bollinger Bands\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.ab"
},
{
"path": "strategies/CombinedBinHAndClucV5/CombinedBinHAndClucV5.py",
"chars": 6798,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV5Hyperoptable/CombinedBinHAndClucV5Hyperoptable.py",
"chars": 8137,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV6/CombinedBinHAndClucV6.py",
"chars": 10525,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV6H/CombinedBinHAndClucV6H.py",
"chars": 20405,
"preview": "# --- Do not remove these libs --------------------------------------------------------------------\nimport freqtrade.ven"
},
{
"path": "strategies/CombinedBinHAndClucV7/CombinedBinHAndClucV7.py",
"chars": 16156,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV8/CombinedBinHAndClucV8.py",
"chars": 20587,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV8Hyper/CombinedBinHAndClucV8Hyper.py",
"chars": 21408,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV8XH/CombinedBinHAndClucV8XH.py",
"chars": 23737,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHAndClucV8XHO/CombinedBinHAndClucV8XHO.py",
"chars": 24318,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CombinedBinHClucAndMADV3/CombinedBinHClucAndMADV3.py",
"chars": 8682,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/CombinedBinHClucAndMADV5/CombinedBinHClucAndMADV5.py",
"chars": 12759,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/CombinedBinHClucAndMADV6/CombinedBinHClucAndMADV6.py",
"chars": 13559,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/CombinedBinHClucAndMADV9/CombinedBinHClucAndMADV9.py",
"chars": 20540,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/Combined_Indicators/Combined_Indicators.py",
"chars": 3387,
"preview": "# --- Do not remove these libs ---\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\n# ----------"
},
{
"path": "strategies/Combined_NFIv6_SMA/Combined_NFIv6_SMA.py",
"chars": 193637,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Combined_NFIv7_SMA/Combined_NFIv7_SMA.py",
"chars": 221631,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Combined_NFIv7_SMA_Rallipanos_20210707/Combined_NFIv7_SMA_Rallipanos_20210707.py",
"chars": 221651,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Combined_NFIv7_SMA_bAdBoY_20211204/Combined_NFIv7_SMA_bAdBoY_20211204.py",
"chars": 221647,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/CoreStrategy/CoreStrategy.py",
"chars": 57008,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.pers"
},
{
"path": "strategies/CrossEMAStrategy/CrossEMAStrategy.py",
"chars": 7825,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n# isort: skip_"
},
{
"path": "strategies/CryptoFrog/CryptoFrog.py",
"chars": 25118,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO/CryptoFrogHO.py",
"chars": 25401,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO2/CryptoFrogHO2.py",
"chars": 25376,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO2A/CryptoFrogHO2A.py",
"chars": 25377,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO3A1/CryptoFrogHO3A1.py",
"chars": 25453,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO3A2/CryptoFrogHO3A2.py",
"chars": 25451,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO3A3/CryptoFrogHO3A3.py",
"chars": 25450,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogHO3A4/CryptoFrogHO3A4.py",
"chars": 25449,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogNFI/CryptoFrogNFI.py",
"chars": 210328,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogNFIHO1A/CryptoFrogNFIHO1A.py",
"chars": 236623,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CryptoFrogOffset/CryptoFrogOffset.py",
"chars": 168296,
"preview": "from typing import Dict, List, Optional, Tuple\nfrom datetime import datetime, timedelta\nfrom cachetools import TTLCache\n"
},
{
"path": "strategies/CustomStoplossWithPSAR/CustomStoplossWithPSAR.py",
"chars": 3731,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/DCBBBounce/DCBBBounce.py",
"chars": 8676,
"preview": "\n# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfro"
},
{
"path": "strategies/DD/DD.py",
"chars": 3048,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/DIV_v1/DIV_v1.py",
"chars": 4047,
"preview": "from pandas import DataFrame\nimport talib.abstract as ta\nfrom functools import reduce\nimport numpy as np\nfrom freqtrade."
},
{
"path": "strategies/DevilStra/DevilStra.py",
"chars": 26616,
"preview": "# DevilStra Strategy\n# 𝔇𝔢𝔳𝔦𝔩 𝔦𝔰 𝔞𝔩𝔴𝔞𝔶𝔰 𝔰𝔱𝔯𝔬𝔫𝔤𝔢𝔯 𝔱𝔥𝔞𝔫 𝔊𝔬𝔡.\n# 𝔅𝔲𝔱 𝔱𝔥𝔢 𝔬𝔫𝔩𝔶 𝔬𝔫𝔢 𝔴𝔥𝔬 𝔥𝔞𝔰 𝔱𝔥𝔢 𝔞𝔟𝔦𝔩𝔦𝔱𝔶\n# 𝔗𝔬 𝔠𝔯𝔢𝔞𝔱𝔢 𝔫𝔢𝔴 𝔠𝔯𝔢𝔞𝔱𝔲𝔯"
},
{
"path": "strategies/Diamond/Diamond.py",
"chars": 8211,
"preview": "# 𝐼𝓉 𝒾𝓈 𝒟𝒾𝒶𝓂𝑜𝓃𝒹 𝒮𝓉𝓇𝒶𝓉𝑒𝑔𝓎.\n# 𝒯𝒽𝒶𝓉 𝓉𝒶𝓀𝑒𝓈 𝒽𝑒𝓇 𝑜𝓌𝓃 𝓇𝒾𝑔𝒽𝓉𝓈 𝓁𝒾𝓀𝑒 𝒜𝒻𝑔𝒽𝒶𝓃𝒾𝓈𝓉𝒶𝓃 𝓌𝑜𝓂𝑒𝓃\n# 𝒯𝒽𝑜𝓈𝑒 𝓌𝒽𝑜 𝓈𝓉𝒾𝓁𝓁 𝓅𝓇𝑜𝓊𝒹 𝒶𝓃𝒹 𝒽𝑜𝓅𝑒𝒻𝓊𝓁.\n# 𝒯𝒽𝑜𝓈"
},
{
"path": "strategies/Divergences/Divergences.py",
"chars": 15834,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/Dracula/Dracula.py",
"chars": 10345,
"preview": "\nfrom freqtrade.strategy import DecimalParameter, IntParameter\n\nfrom freqtrade.strategy.interface import IStrategy\nfrom "
},
{
"path": "strategies/Dyna_opti/Dyna_opti.py",
"chars": 27805,
"preview": "import numpy as np\r\nimport talib.abstract as ta\r\nimport freqtrade.vendor.qtpylib.indicators as qtpylib\r\nimport arrow\r\n\r\n"
},
{
"path": "strategies/EI3v2_tag_cofi_green/EI3v2_tag_cofi_green.py",
"chars": 18747,
"preview": "# --- Do not remove these libs ---\r\nfrom freqtrade.strategy.interface import IStrategy\r\nfrom typing import Dict, List\r\nf"
},
{
"path": "strategies/EMA50/EMA50.py",
"chars": 16301,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n\n# --- Do not "
},
{
"path": "strategies/EMA520015_V17/EMA520015_V17.py",
"chars": 2593,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\nimpor"
},
{
"path": "strategies/EMABBRSI/EMABBRSI.py",
"chars": 4664,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n\nimport talib.abstract as ta\nfrom p"
},
{
"path": "strategies/EMABreakout/EMABreakout.py",
"chars": 15492,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n\n# --- Do not "
},
{
"path": "strategies/EMASkipPump/EMASkipPump.py",
"chars": 2985,
"preview": "from freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom functools import reduce\nfrom panda"
},
{
"path": "strategies/EMAVolume/EMAVolume.py",
"chars": 2364,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom pandas import DataFrame\n# ---"
},
{
"path": "strategies/EMA_CROSSOVER_STRATEGY/EMA_CROSSOVER_STRATEGY.py",
"chars": 6308,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n\n# --- Do not remove these libs ---"
},
{
"path": "strategies/EXPERIMENTAL_STRATEGY/EXPERIMENTAL_STRATEGY.py",
"chars": 5482,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n\n# --- Do not remove these libs ---"
},
{
"path": "strategies/ElliotV2/ElliotV2.py",
"chars": 15193,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV4/ElliotV4.py",
"chars": 12088,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV531/ElliotV531.py",
"chars": 16942,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV5HO/ElliotV5HO.py",
"chars": 13768,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV5HOMod2/ElliotV5HOMod2.py",
"chars": 7234,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV5HOMod3/ElliotV5HOMod3.py",
"chars": 6409,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV7/ElliotV7.py",
"chars": 8611,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV8HO/ElliotV8HO.py",
"chars": 7317,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom functools import reduce\nfrom "
},
{
"path": "strategies/ElliotV8_original/ElliotV8_original.py",
"chars": 6421,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV8_original_ichiv2/ElliotV8_original_ichiv2.py",
"chars": 7613,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/ElliotV8_original_ichiv3/ElliotV8_original_ichiv3.py",
"chars": 7650,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/Elliotv8/Elliotv8.py",
"chars": 6548,
"preview": "# for live trailing_stop = False and use_custom_stoploss = True\n# for backtest trailing_stop = True and use_custom_stopl"
},
{
"path": "strategies/FRAYSTRAT/FRAYSTRAT.py",
"chars": 18086,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# flake8: noqa: F401\n# isort: skip_"
},
{
"path": "strategies/Fakebuy/Fakebuy.py",
"chars": 10281,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/FastSupertrend/FastSupertrend.py",
"chars": 7817,
"preview": "\"\"\"\nSupertrend strategy:\n* Description: Generate a 3 supertrend indicators for 'buy' strategies & 3 supertrend indicator"
},
{
"path": "strategies/FastSupertrendOpt/FastSupertrendOpt.py",
"chars": 7475,
"preview": "\"\"\"\nSupertrend strategy:\n* Description: Generate a 3 supertrend indicators for 'buy' strategies & 3 supertrend indicator"
},
{
"path": "strategies/FiveMinCrossAbove/FiveMinCrossAbove.py",
"chars": 3851,
"preview": "# --- Do not remove these libs ---\nfrom freqtrade.strategy.interface import IStrategy\nfrom typing import Dict, List\nfrom"
},
{
"path": "strategies/FixedRiskRewardLoss/FixedRiskRewardLoss.py",
"chars": 4912,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/ForexSignal/ForexSignal.py",
"chars": 5862,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\n# isort: skip_file\n# --- Do not rem"
},
{
"path": "strategies/FrostAuraM115mStrategy/FrostAuraM115mStrategy.py",
"chars": 3918,
"preview": "import numpy as np\nimport pandas as pd\nfrom pandas import DataFrame\nfrom freqtrade.strategy.interface import IStrategy\ni"
},
{
"path": "strategies/FrostAuraM11hStrategy/FrostAuraM11hStrategy.py",
"chars": 3952,
"preview": "import numpy as np\nimport pandas as pd\nfrom pandas import DataFrame\nfrom freqtrade.strategy.interface import IStrategy\ni"
},
{
"path": "strategies/FrostAuraM21hStrategy/FrostAuraM21hStrategy.py",
"chars": 3296,
"preview": "import numpy as np\nimport pandas as pd\nfrom pandas import DataFrame\nfrom freqtrade.strategy.interface import IStrategy\ni"
},
{
"path": "strategies/FrostAuraM315mStrategy/FrostAuraM315mStrategy.py",
"chars": 4564,
"preview": "import numpy as np\nimport pandas as pd\nfrom pandas import DataFrame\nfrom freqtrade.strategy.interface import IStrategy\ni"
},
{
"path": "strategies/FrostAuraM31hStrategy/FrostAuraM31hStrategy.py",
"chars": 4610,
"preview": "import numpy as np\nimport pandas as pd\nfrom pandas import DataFrame\nfrom freqtrade.strategy.interface import IStrategy\ni"
},
{
"path": "strategies/FrostAuraRandomStrategy/FrostAuraRandomStrategy.py",
"chars": 3374,
"preview": "from pandas import DataFrame\nfrom freqtrade.strategy.interface import IStrategy\nfrom freqtrade.strategy import (IntParam"
},
{
"path": "strategies/GodCard/GodCard.py",
"chars": 6241,
"preview": "from freqtrade.strategy import IStrategy\nfrom freqtrade.strategy import (BooleanParameter, CategoricalParameter, Decimal"
},
{
"path": "strategies/GodStraNew/GodStraNew.py",
"chars": 25442,
"preview": "# GodStraNew Strategy\n# Author: @Mablue (Masoud Azizi)\n# github: https://github.com/mablue/\n# freqtrade hyperopt --hyper"
},
{
"path": "strategies/GodStraNew40/GodStraNew40.py",
"chars": 26784,
"preview": "# GodStraNew Strategy\n# Author: @Mablue (Masoud Azizi)\n# github: https://github.com/mablue/\n# freqtrade hyperopt --hyper"
},
{
"path": "strategies/GodStraNew_SMAonly/GodStraNew_SMAonly.py",
"chars": 26714,
"preview": "# GodStraNew Strategy\n# Author: @Mablue (Masoud Azizi)\n# github: https://github.com/mablue/\n# freqtrade hyperopt --hyper"
},
{
"path": "strategies/Guacamole/Guacamole.py",
"chars": 5806,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\nimport freqtrade.vendor.qtpylib.ind"
},
{
"path": "strategies/Gumbo1/Gumbo1.py",
"chars": 5264,
"preview": "\"\"\"\nhttps://github.com/raph92?tab=repositories\n\"\"\"\nimport logging\n\n# --- Do not remove these libs ---\nimport sys\nfrom fu"
},
{
"path": "strategies/Hacklemore2/Hacklemore2.py",
"chars": 5856,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/Hacklemore3/Hacklemore3.py",
"chars": 6600,
"preview": "import freqtrade.vendor.qtpylib.indicators as qtpylib\nimport numpy as np\nimport talib.abstract as ta\nfrom freqtrade.stra"
},
{
"path": "strategies/HansenSmaOffsetV1/HansenSmaOffsetV1.py",
"chars": 2482,
"preview": "# --- Do not remove these libs --- freqtrade backtesting --strategy SmoothScalp --timerange 20210110-20210410\nfrom freqt"
},
{
"path": "strategies/HarmonicDivergence/HarmonicDivergence.py",
"chars": 34770,
"preview": "# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement\r\n# flake8: noqa: F401\r\n\r\n# --- Do n"
},
{
"path": "strategies/Heracles/Heracles.py",
"chars": 3680,
"preview": "# Heracles Strategy: Strongest Son of GodStra\n# ( With just 1 Genome! its a bacteria :D )\n# Author: @Mablue (Masoud Aziz"
},
{
"path": "strategies/HourBasedStrategy/HourBasedStrategy.py",
"chars": 4280,
"preview": "# Hour Strategy\n# In this strategy we try to find the best hours to buy and sell in a day.(in hourly timeframe)\n# Becaus"
}
]
// ... and 267 more files (download for full content)
About this extraction
This page contains the full source code of the davidzr/freqtrade-strategies GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 467 files (16.5 MB), approximately 4.4M tokens, and a symbol index with 5082 extracted functions, classes, methods, constants, and types. 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.