From 259dc75a3083b76980bf12d6575764eac96dd202 Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sat, 22 Feb 2020 23:10:46 +0100 Subject: [PATCH 1/7] some order and added weighted BB indicator to list --- .../templates/subtemplates/indicators_full.j2 | 103 +++++++++++------- 1 file changed, 65 insertions(+), 38 deletions(-) diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/subtemplates/indicators_full.j2 index 879a2daa0..87b385dd0 100644 --- a/freqtrade/templates/subtemplates/indicators_full.j2 +++ b/freqtrade/templates/subtemplates/indicators_full.j2 @@ -2,12 +2,17 @@ # Momentum Indicators # ------------------------------------ -# RSI -dataframe['rsi'] = ta.RSI(dataframe) - # ADX dataframe['adx'] = ta.ADX(dataframe) +# # Plus Directional Indicator / Movement +# dataframe['plus_dm'] = ta.PLUS_DM(dataframe) +# dataframe['plus_di'] = ta.PLUS_DI(dataframe) + +# # Minus Directional Indicator / Movement +# dataframe['minus_dm'] = ta.MINUS_DM(dataframe) +# dataframe['minus_di'] = ta.MINUS_DI(dataframe) + # # Aroon, Aroon Oscillator # aroon = ta.AROON(dataframe) # dataframe['aroonup'] = aroon['aroonup'] @@ -20,6 +25,31 @@ dataframe['adx'] = ta.ADX(dataframe) # # Commodity Channel Index: values Oversold:<-100, Overbought:>100 # dataframe['cci'] = ta.CCI(dataframe) +# RSI +dataframe['rsi'] = ta.RSI(dataframe) + +# # Inverse Fisher transform on RSI: values [-1.0, 1.0] (https://goo.gl/2JGGoy) +# rsi = 0.1 * (dataframe['rsi'] - 50) +# dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) + +# # Inverse Fisher transform on RSI normalized: values [0.0, 100.0] (https://goo.gl/2JGGoy) +# dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) + +# # Stochastic Slow +# stoch = ta.STOCH(dataframe) +# dataframe['slowd'] = stoch['slowd'] +# dataframe['slowk'] = stoch['slowk'] + +# Stochastic Fast +stoch_fast = ta.STOCHF(dataframe) +dataframe['fastd'] = stoch_fast['fastd'] +dataframe['fastk'] = stoch_fast['fastk'] + +# # Stochastic RSI +# stoch_rsi = ta.STOCHRSI(dataframe) +# dataframe['fastd_rsi'] = stoch_rsi['fastd'] +# dataframe['fastk_rsi'] = stoch_rsi['fastk'] + # MACD macd = ta.MACD(dataframe) dataframe['macd'] = macd['macd'] @@ -29,60 +59,57 @@ dataframe['macdhist'] = macd['macdhist'] # MFI dataframe['mfi'] = ta.MFI(dataframe) -# # Minus Directional Indicator / Movement -# dataframe['minus_dm'] = ta.MINUS_DM(dataframe) -# dataframe['minus_di'] = ta.MINUS_DI(dataframe) - -# # Plus Directional Indicator / Movement -# dataframe['plus_dm'] = ta.PLUS_DM(dataframe) -# dataframe['plus_di'] = ta.PLUS_DI(dataframe) -# dataframe['minus_di'] = ta.MINUS_DI(dataframe) - # # ROC # dataframe['roc'] = ta.ROC(dataframe) -# # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy) -# rsi = 0.1 * (dataframe['rsi'] - 50) -# dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) - -# # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy) -# dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) - -# # Stoch -# stoch = ta.STOCH(dataframe) -# dataframe['slowd'] = stoch['slowd'] -# dataframe['slowk'] = stoch['slowk'] - -# Stoch fast -stoch_fast = ta.STOCHF(dataframe) -dataframe['fastd'] = stoch_fast['fastd'] -dataframe['fastk'] = stoch_fast['fastk'] - -# # Stoch RSI -# stoch_rsi = ta.STOCHRSI(dataframe) -# dataframe['fastd_rsi'] = stoch_rsi['fastd'] -# dataframe['fastk_rsi'] = stoch_rsi['fastk'] - # Overlap Studies # ------------------------------------ -# Bollinger bands +# 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'] +dataframe["bb_percent"] = ( + (dataframe["close"] - dataframe["bb_lowerband"]) / + (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) +) +dataframe["bb_width"] = ( + (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"] +) + +# Bollinger Bands - Weighted (EMA based instead of SMA) +# weighted_bollinger = qtpylib.weighted_bollinger_bands( +# qtpylib.typical_price(dataframe), window=20, stds=2 +# ) +# dataframe["wbb_upperband"] = weighted_bollinger["upper"] +# dataframe["wbb_lowerband"] = weighted_bollinger["lower"] +# dataframe["wbb_middleband"] = weighted_bollinger["mid"] +# dataframe["wbb_percent"] = ( +# (dataframe["close"] - dataframe["wbb_lowerband"]) / +# (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) +# ) +# dataframe["wbb_width"] = ( +# (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) / dataframe["wbb_middleband"] +# ) # # EMA - Exponential Moving Average # dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3) # dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5) # dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) +# dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21) # dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50) # dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100) # # SMA - Simple Moving Average -# dataframe['sma'] = ta.SMA(dataframe, timeperiod=40) +# dataframe['sma3'] = ta.SMA(dataframe, timeperiod=3) +# dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5) +# dataframe['sma10'] = ta.SMA(dataframe, timeperiod=10) +# dataframe['sma21'] = ta.SMA(dataframe, timeperiod=21) +# dataframe['sma50'] = ta.SMA(dataframe, timeperiod=50) +# dataframe['sma100'] = ta.SMA(dataframe, timeperiod=100) -# SAR Parabol +# Parabolic SAR dataframe['sar'] = ta.SAR(dataframe) # TEMA - Triple Exponential Moving Average @@ -142,7 +169,7 @@ dataframe['htleadsine'] = hilbert['leadsine'] # # Chart type # # ------------------------------------ -# # Heikinashi stategy +# # Heikin Ashi Strategy # heikinashi = qtpylib.heikinashi(dataframe) # dataframe['ha_open'] = heikinashi['open'] # dataframe['ha_close'] = heikinashi['close'] From b49b9b515ed14d1c501e9350fe727f0f16a7722d Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sat, 22 Feb 2020 23:37:15 +0100 Subject: [PATCH 2/7] final touches --- freqtrade/templates/subtemplates/indicators_full.j2 | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/subtemplates/indicators_full.j2 index 87b385dd0..cd106451e 100644 --- a/freqtrade/templates/subtemplates/indicators_full.j2 +++ b/freqtrade/templates/subtemplates/indicators_full.j2 @@ -19,7 +19,7 @@ dataframe['adx'] = ta.ADX(dataframe) # dataframe['aroondown'] = aroon['aroondown'] # dataframe['aroonosc'] = ta.AROONOSC(dataframe) -# # Awesome oscillator +# # Awesome Oscillator # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) # # Commodity Channel Index: values Oversold:<-100, Overbought:>100 From 2957756275367bcd35734989cfe61558356a4a09 Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sat, 22 Feb 2020 23:39:01 +0100 Subject: [PATCH 3/7] final touches plus --- freqtrade/templates/subtemplates/indicators_full.j2 | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/subtemplates/indicators_full.j2 index cd106451e..903aebb73 100644 --- a/freqtrade/templates/subtemplates/indicators_full.j2 +++ b/freqtrade/templates/subtemplates/indicators_full.j2 @@ -22,7 +22,7 @@ dataframe['adx'] = ta.ADX(dataframe) # # Awesome Oscillator # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) -# # Commodity Channel Index: values Oversold:<-100, Overbought:>100 +# # Commodity Channel Index: values Oversold:-100, Overbought:100 # dataframe['cci'] = ta.CCI(dataframe) # RSI From 5ac624446587f95af22b322b53caddd87692f021 Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sat, 22 Feb 2020 23:50:26 +0100 Subject: [PATCH 4/7] added keltner channel and uo --- .../templates/subtemplates/indicators_full.j2 | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/subtemplates/indicators_full.j2 index 903aebb73..af472faef 100644 --- a/freqtrade/templates/subtemplates/indicators_full.j2 +++ b/freqtrade/templates/subtemplates/indicators_full.j2 @@ -22,7 +22,23 @@ dataframe['adx'] = ta.ADX(dataframe) # # Awesome Oscillator # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) -# # Commodity Channel Index: values Oversold:-100, Overbought:100 +# # Keltner Channel +# keltner = qtpylib.keltner_channel(dataframe) +# dataframe["kc_upperband"] = keltner["upper"] +# dataframe["kc_lowerband"] = keltner["lower"] +# dataframe["kc_middleband"] = keltner["mid"] +# dataframe["kc_percent"] = ( +# (dataframe["close"] - dataframe["kc_lowerband"]) / +# (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) +# ) +# dataframe["kc_width"] = ( +# (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) / dataframe["kc_middleband"] +# ) + +# # Ultimate Oscillator +# dataframe['ao'] = ta.ULTOSC(dataframe) + +# # Commodity Channel Index: values [Oversold:-100, Overbought:100] # dataframe['cci'] = ta.CCI(dataframe) # RSI From e04c2dda2cfd3c18690be04dd3b22f98731b0b04 Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sat, 22 Feb 2020 23:58:31 +0100 Subject: [PATCH 5/7] fixed typo --- freqtrade/templates/subtemplates/indicators_full.j2 | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/subtemplates/indicators_full.j2 index af472faef..60a358bec 100644 --- a/freqtrade/templates/subtemplates/indicators_full.j2 +++ b/freqtrade/templates/subtemplates/indicators_full.j2 @@ -36,7 +36,7 @@ dataframe['adx'] = ta.ADX(dataframe) # ) # # Ultimate Oscillator -# dataframe['ao'] = ta.ULTOSC(dataframe) +# dataframe['uo'] = ta.ULTOSC(dataframe) # # Commodity Channel Index: values [Oversold:-100, Overbought:100] # dataframe['cci'] = ta.CCI(dataframe) From f25d6224ddeab8a3889daa69c1fac8eb375d169b Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sun, 23 Feb 2020 16:22:19 +0100 Subject: [PATCH 6/7] modified sample_strategy --- freqtrade/templates/sample_strategy.py | 136 ++++++++++++++++--------- 1 file changed, 90 insertions(+), 46 deletions(-) diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index 92f6aefba..8a4b27c72 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -124,11 +124,16 @@ class SampleStrategy(IStrategy): # Momentum Indicators # ------------------------------------ - # RSI - dataframe['rsi'] = ta.RSI(dataframe) - # ADX - dataframe['adx'] = ta.ADX(dataframe) + # dataframe['adx'] = ta.ADX(dataframe) + + # # Plus Directional Indicator / Movement + # dataframe['plus_dm'] = ta.PLUS_DM(dataframe) + # dataframe['plus_di'] = ta.PLUS_DI(dataframe) + + # # Minus Directional Indicator / Movement + # dataframe['minus_dm'] = ta.MINUS_DM(dataframe) + # dataframe['minus_di'] = ta.MINUS_DI(dataframe) # # Aroon, Aroon Oscillator # aroon = ta.AROON(dataframe) @@ -136,12 +141,53 @@ class SampleStrategy(IStrategy): # dataframe['aroondown'] = aroon['aroondown'] # dataframe['aroonosc'] = ta.AROONOSC(dataframe) - # # Awesome oscillator + # # Awesome Oscillator # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) - # # Commodity Channel Index: values Oversold:<-100, Overbought:>100 + # # Keltner Channel + # keltner = qtpylib.keltner_channel(dataframe) + # dataframe["kc_upperband"] = keltner["upper"] + # dataframe["kc_lowerband"] = keltner["lower"] + # dataframe["kc_middleband"] = keltner["mid"] + # dataframe["kc_percent"] = ( + # (dataframe["close"] - dataframe["kc_lowerband"]) / + # (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) + # ) + # dataframe["kc_width"] = ( + # (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) / dataframe["kc_middleband"] + # ) + + # # Ultimate Oscillator + # dataframe['uo'] = ta.ULTOSC(dataframe) + + # # Commodity Channel Index: values [Oversold:-100, Overbought:100] # dataframe['cci'] = ta.CCI(dataframe) + # RSI + dataframe['rsi'] = ta.RSI(dataframe) + + # # Inverse Fisher transform on RSI: values [-1.0, 1.0] (https://goo.gl/2JGGoy) + # rsi = 0.1 * (dataframe['rsi'] - 50) + # dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) + + # # Inverse Fisher transform on RSI normalized: values [0.0, 100.0] (https://goo.gl/2JGGoy) + # dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) + + # # Stochastic Slow + # stoch = ta.STOCH(dataframe) + # dataframe['slowd'] = stoch['slowd'] + # dataframe['slowk'] = stoch['slowk'] + + # Stochastic Fast + stoch_fast = ta.STOCHF(dataframe) + dataframe['fastd'] = stoch_fast['fastd'] + dataframe['fastk'] = stoch_fast['fastk'] + + # # Stochastic RSI + # stoch_rsi = ta.STOCHRSI(dataframe) + # dataframe['fastd_rsi'] = stoch_rsi['fastd'] + # dataframe['fastk_rsi'] = stoch_rsi['fastk'] + # MACD macd = ta.MACD(dataframe) dataframe['macd'] = macd['macd'] @@ -151,71 +197,69 @@ class SampleStrategy(IStrategy): # MFI dataframe['mfi'] = ta.MFI(dataframe) - # # Minus Directional Indicator / Movement - # dataframe['minus_dm'] = ta.MINUS_DM(dataframe) - # dataframe['minus_di'] = ta.MINUS_DI(dataframe) - - # # Plus Directional Indicator / Movement - # dataframe['plus_dm'] = ta.PLUS_DM(dataframe) - # dataframe['plus_di'] = ta.PLUS_DI(dataframe) - # dataframe['minus_di'] = ta.MINUS_DI(dataframe) - # # ROC # dataframe['roc'] = ta.ROC(dataframe) - # # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy) - # rsi = 0.1 * (dataframe['rsi'] - 50) - # dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) - - # # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy) - # dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) - - # # Stoch - # stoch = ta.STOCH(dataframe) - # dataframe['slowd'] = stoch['slowd'] - # dataframe['slowk'] = stoch['slowk'] - - # Stoch fast - stoch_fast = ta.STOCHF(dataframe) - dataframe['fastd'] = stoch_fast['fastd'] - dataframe['fastk'] = stoch_fast['fastk'] - - # # Stoch RSI - # stoch_rsi = ta.STOCHRSI(dataframe) - # dataframe['fastd_rsi'] = stoch_rsi['fastd'] - # dataframe['fastk_rsi'] = stoch_rsi['fastk'] - # Overlap Studies # ------------------------------------ - # Bollinger bands + # 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'] + dataframe["bb_percent"] = ( + (dataframe["close"] - dataframe["bb_lowerband"]) / + (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) + ) + dataframe["bb_width"] = ( + (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"] + ) + + # Bollinger Bands - Weighted (EMA based instead of SMA) + # weighted_bollinger = qtpylib.weighted_bollinger_bands( + # qtpylib.typical_price(dataframe), window=20, stds=2 + # ) + # dataframe["wbb_upperband"] = weighted_bollinger["upper"] + # dataframe["wbb_lowerband"] = weighted_bollinger["lower"] + # dataframe["wbb_middleband"] = weighted_bollinger["mid"] + # dataframe["wbb_percent"] = ( + # (dataframe["close"] - dataframe["wbb_lowerband"]) / + # (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) + # ) + # dataframe["wbb_width"] = ( + # (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) / + # dataframe["wbb_middleband"] + # ) # # EMA - Exponential Moving Average # dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3) # dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5) # dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) + # dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21) # dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50) # dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100) # # SMA - Simple Moving Average - # dataframe['sma'] = ta.SMA(dataframe, timeperiod=40) + # dataframe['sma3'] = ta.SMA(dataframe, timeperiod=3) + # dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5) + # dataframe['sma10'] = ta.SMA(dataframe, timeperiod=10) + # dataframe['sma21'] = ta.SMA(dataframe, timeperiod=21) + # dataframe['sma50'] = ta.SMA(dataframe, timeperiod=50) + # dataframe['sma100'] = ta.SMA(dataframe, timeperiod=100) - # SAR Parabol - dataframe['sar'] = ta.SAR(dataframe) + # Parabolic SAR + # dataframe['sar'] = ta.SAR(dataframe) # TEMA - Triple Exponential Moving Average - dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) + # dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) # Cycle Indicator # ------------------------------------ # Hilbert Transform Indicator - SineWave - hilbert = ta.HT_SINE(dataframe) - dataframe['htsine'] = hilbert['sine'] - dataframe['htleadsine'] = hilbert['leadsine'] + # hilbert = ta.HT_SINE(dataframe) + # dataframe['htsine'] = hilbert['sine'] + # dataframe['htleadsine'] = hilbert['leadsine'] # Pattern Recognition - Bullish candlestick patterns # ------------------------------------ @@ -264,7 +308,7 @@ class SampleStrategy(IStrategy): # # Chart type # # ------------------------------------ - # # Heikinashi stategy + # # Heikin Ashi Strategy # heikinashi = qtpylib.heikinashi(dataframe) # dataframe['ha_open'] = heikinashi['open'] # dataframe['ha_close'] = heikinashi['close'] From 0eeafcd157c17d6f7de92ab66c6f267c454bcec2 Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Sun, 23 Feb 2020 16:56:55 +0100 Subject: [PATCH 7/7] matched commenting on previous sample_strategy.py --- freqtrade/templates/sample_strategy.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py index 8a4b27c72..17372e1e0 100644 --- a/freqtrade/templates/sample_strategy.py +++ b/freqtrade/templates/sample_strategy.py @@ -125,7 +125,7 @@ class SampleStrategy(IStrategy): # ------------------------------------ # ADX - # dataframe['adx'] = ta.ADX(dataframe) + dataframe['adx'] = ta.ADX(dataframe) # # Plus Directional Indicator / Movement # dataframe['plus_dm'] = ta.PLUS_DM(dataframe) @@ -249,17 +249,17 @@ class SampleStrategy(IStrategy): # dataframe['sma100'] = ta.SMA(dataframe, timeperiod=100) # Parabolic SAR - # dataframe['sar'] = ta.SAR(dataframe) + dataframe['sar'] = ta.SAR(dataframe) # TEMA - Triple Exponential Moving Average - # dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) + dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) # Cycle Indicator # ------------------------------------ # Hilbert Transform Indicator - SineWave - # hilbert = ta.HT_SINE(dataframe) - # dataframe['htsine'] = hilbert['sine'] - # dataframe['htleadsine'] = hilbert['leadsine'] + hilbert = ta.HT_SINE(dataframe) + dataframe['htsine'] = hilbert['sine'] + dataframe['htleadsine'] = hilbert['leadsine'] # Pattern Recognition - Bullish candlestick patterns # ------------------------------------