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Matthias 2019-11-21 06:40:30 +01:00
parent f7322358cf
commit be4a4180ae
2 changed files with 178 additions and 197 deletions
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186
freqtrade/templates/base_strategy.py.j2
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@ -109,58 +109,61 @@ class {{ strategy }}(IStrategy):
# ADX # ADX
dataframe['adx'] = ta.ADX(dataframe) dataframe['adx'] = ta.ADX(dataframe)
"""
# Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# Commodity Channel Index: values Oversold:<-100, Overbought:>100 # # Aroon, Aroon Oscillator
dataframe['cci'] = ta.CCI(dataframe) # aroon = ta.AROON(dataframe)
""" # dataframe['aroonup'] = aroon['aroonup']
# dataframe['aroondown'] = aroon['aroondown']
# dataframe['aroonosc'] = ta.AROONOSC(dataframe)
# # Awesome oscillator
# dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# # Commodity Channel Index: values Oversold:<-100, Overbought:>100
# dataframe['cci'] = ta.CCI(dataframe)
# MACD # MACD
macd = ta.MACD(dataframe) macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd'] dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist'] dataframe['macdhist'] = macd['macdhist']
# MFI # # MFI
dataframe['mfi'] = ta.MFI(dataframe) # dataframe['mfi'] = ta.MFI(dataframe)
""" # # Minus Directional Indicator / Movement
# Minus Directional Indicator / Movement # dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
dataframe['minus_dm'] = ta.MINUS_DM(dataframe) # dataframe['minus_di'] = ta.MINUS_DI(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Plus Directional Indicator / Movement # # Plus Directional Indicator / Movement
dataframe['plus_dm'] = ta.PLUS_DM(dataframe) # dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
dataframe['plus_di'] = ta.PLUS_DI(dataframe) # dataframe['plus_di'] = ta.PLUS_DI(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe) # dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# ROC # # ROC
dataframe['roc'] = ta.ROC(dataframe) # dataframe['roc'] = ta.ROC(dataframe)
# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy) # # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
rsi = 0.1 * (dataframe['rsi'] - 50) # rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) # 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) # # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) # dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# # Stoch
# stoch = ta.STOCH(dataframe)
# dataframe['slowd'] = stoch['slowd']
# dataframe['slowk'] = stoch['slowk']
# Stoch
stoch = ta.STOCH(dataframe)
dataframe['slowd'] = stoch['slowd']
dataframe['slowk'] = stoch['slowk']
"""
# Stoch fast # Stoch fast
stoch_fast = ta.STOCHF(dataframe) stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd'] dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk'] dataframe['fastk'] = stoch_fast['fastk']
""" # # Stoch RSI
# Stoch RSI # stoch_rsi = ta.STOCHRSI(dataframe)
stoch_rsi = ta.STOCHRSI(dataframe) # dataframe['fastd_rsi'] = stoch_rsi['fastd']
dataframe['fastd_rsi'] = stoch_rsi['fastd'] # dataframe['fastk_rsi'] = stoch_rsi['fastk']
dataframe['fastk_rsi'] = stoch_rsi['fastk']
"""
# Overlap Studies # Overlap Studies
# ------------------------------------ # ------------------------------------
@ -171,17 +174,16 @@ class {{ strategy }}(IStrategy):
dataframe['bb_middleband'] = bollinger['mid'] dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper'] dataframe['bb_upperband'] = bollinger['upper']
""" # # EMA - Exponential Moving Average
# EMA - Exponential Moving Average # dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3) # dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5) # dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) # dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50) # dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# # SMA - Simple Moving Average
# dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
# SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
"""
# SAR Parabol # SAR Parabol
dataframe['sar'] = ta.SAR(dataframe) dataframe['sar'] = ta.SAR(dataframe)
@ -197,65 +199,57 @@ class {{ strategy }}(IStrategy):
# Pattern Recognition - Bullish candlestick patterns # Pattern Recognition - Bullish candlestick patterns
# ------------------------------------ # ------------------------------------
""" # # Hammer: values [0, 100]
# Hammer: values [0, 100] # dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe) # # Inverted Hammer: values [0, 100]
# Inverted Hammer: values [0, 100] # dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe) # # Dragonfly Doji: values [0, 100]
# Dragonfly Doji: values [0, 100] # dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe) # # Piercing Line: values [0, 100]
# Piercing Line: values [0, 100] # dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100] # # Morningstar: values [0, 100]
# Morningstar: values [0, 100] # dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100] # # Three White Soldiers: values [0, 100]
# Three White Soldiers: values [0, 100] # dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
"""
# Pattern Recognition - Bearish candlestick patterns # Pattern Recognition - Bearish candlestick patterns
# ------------------------------------ # ------------------------------------
""" # # Hanging Man: values [0, 100]
# Hanging Man: values [0, 100] # dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe) # # Shooting Star: values [0, 100]
# Shooting Star: values [0, 100] # dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe) # # Gravestone Doji: values [0, 100]
# Gravestone Doji: values [0, 100] # dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe) # # Dark Cloud Cover: values [0, 100]
# Dark Cloud Cover: values [0, 100] # dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe) # # Evening Doji Star: values [0, 100]
# Evening Doji Star: values [0, 100] # dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe) # # Evening Star: values [0, 100]
# Evening Star: values [0, 100] # dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
"""
# Pattern Recognition - Bullish/Bearish candlestick patterns # Pattern Recognition - Bullish/Bearish candlestick patterns
# ------------------------------------ # ------------------------------------
""" # # Three Line Strike: values [0, -100, 100]
# Three Line Strike: values [0, -100, 100] # dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe) # # Spinning Top: values [0, -100, 100]
# Spinning Top: values [0, -100, 100] # dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100] # # Engulfing: values [0, -100, 100]
# Engulfing: values [0, -100, 100] # dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100] # # Harami: values [0, -100, 100]
# Harami: values [0, -100, 100] # dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100] # # Three Outside Up/Down: values [0, -100, 100]
# Three Outside Up/Down: values [0, -100, 100] # dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100] # # Three Inside Up/Down: values [0, -100, 100]
# Three Inside Up/Down: values [0, -100, 100] # dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
"""
# Chart type # # Chart type
# ------------------------------------ # # ------------------------------------
""" # # Heikinashi stategy
# Heikinashi stategy # heikinashi = qtpylib.heikinashi(dataframe)
heikinashi = qtpylib.heikinashi(dataframe) # dataframe['ha_open'] = heikinashi['open']
dataframe['ha_open'] = heikinashi['open'] # dataframe['ha_close'] = heikinashi['close']
dataframe['ha_close'] = heikinashi['close'] # dataframe['ha_high'] = heikinashi['high']
dataframe['ha_high'] = heikinashi['high'] # dataframe['ha_low'] = heikinashi['low']
dataframe['ha_low'] = heikinashi['low']
"""
# Retrieve best bid and best ask from the orderbook # Retrieve best bid and best ask from the orderbook
# ------------------------------------ # ------------------------------------

189
freqtrade/templates/sample_strategy.py
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@ -111,64 +111,60 @@ class SampleStrategy(IStrategy):
# ADX # ADX
dataframe['adx'] = ta.ADX(dataframe) dataframe['adx'] = ta.ADX(dataframe)
""" # # Aroon, Aroon Oscillator
# Aroon, Aroon Oscillator # aroon = ta.AROON(dataframe)
aroon = ta.AROON(dataframe) # dataframe['aroonup'] = aroon['aroonup']
dataframe['aroonup'] = aroon['aroonup'] # dataframe['aroondown'] = aroon['aroondown']
dataframe['aroondown'] = aroon['aroondown'] # dataframe['aroonosc'] = ta.AROONOSC(dataframe)
dataframe['aroonosc'] = ta.AROONOSC(dataframe)
# Awesome oscillator # # Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# # Commodity Channel Index: values Oversold:<-100, Overbought:>100
# dataframe['cci'] = ta.CCI(dataframe)
# Commodity Channel Index: values Oversold:<-100, Overbought:>100
dataframe['cci'] = ta.CCI(dataframe)
"""
# MACD # MACD
macd = ta.MACD(dataframe) macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd'] dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist'] dataframe['macdhist'] = macd['macdhist']
# MFI # # MFI
dataframe['mfi'] = ta.MFI(dataframe) # dataframe['mfi'] = ta.MFI(dataframe)
""" # # Minus Directional Indicator / Movement
# Minus Directional Indicator / Movement # dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
dataframe['minus_dm'] = ta.MINUS_DM(dataframe) # dataframe['minus_di'] = ta.MINUS_DI(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Plus Directional Indicator / Movement # # Plus Directional Indicator / Movement
dataframe['plus_dm'] = ta.PLUS_DM(dataframe) # dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
dataframe['plus_di'] = ta.PLUS_DI(dataframe) # dataframe['plus_di'] = ta.PLUS_DI(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe) # dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# ROC # # ROC
dataframe['roc'] = ta.ROC(dataframe) # dataframe['roc'] = ta.ROC(dataframe)
# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy) # # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
rsi = 0.1 * (dataframe['rsi'] - 50) # rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) # 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) # # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) # dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# # Stoch
# stoch = ta.STOCH(dataframe)
# dataframe['slowd'] = stoch['slowd']
# dataframe['slowk'] = stoch['slowk']
# Stoch
stoch = ta.STOCH(dataframe)
dataframe['slowd'] = stoch['slowd']
dataframe['slowk'] = stoch['slowk']
"""
# Stoch fast # Stoch fast
stoch_fast = ta.STOCHF(dataframe) stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd'] dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk'] dataframe['fastk'] = stoch_fast['fastk']
""" # # Stoch RSI
# Stoch RSI # stoch_rsi = ta.STOCHRSI(dataframe)
stoch_rsi = ta.STOCHRSI(dataframe) # dataframe['fastd_rsi'] = stoch_rsi['fastd']
dataframe['fastd_rsi'] = stoch_rsi['fastd'] # dataframe['fastk_rsi'] = stoch_rsi['fastk']
dataframe['fastk_rsi'] = stoch_rsi['fastk']
"""
# Overlap Studies # Overlap Studies
# ------------------------------------ # ------------------------------------
@ -179,17 +175,16 @@ class SampleStrategy(IStrategy):
dataframe['bb_middleband'] = bollinger['mid'] dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper'] dataframe['bb_upperband'] = bollinger['upper']
""" # # EMA - Exponential Moving Average
# EMA - Exponential Moving Average # dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3) # dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5) # dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) # dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50) # dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# # SMA - Simple Moving Average
# dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
# SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
"""
# SAR Parabol # SAR Parabol
dataframe['sar'] = ta.SAR(dataframe) dataframe['sar'] = ta.SAR(dataframe)
@ -205,65 +200,57 @@ class SampleStrategy(IStrategy):
# Pattern Recognition - Bullish candlestick patterns # Pattern Recognition - Bullish candlestick patterns
# ------------------------------------ # ------------------------------------
""" # # Hammer: values [0, 100]
# Hammer: values [0, 100] # dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe) # # Inverted Hammer: values [0, 100]
# Inverted Hammer: values [0, 100] # dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe) # # Dragonfly Doji: values [0, 100]
# Dragonfly Doji: values [0, 100] # dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe) # # Piercing Line: values [0, 100]
# Piercing Line: values [0, 100] # dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100] # # Morningstar: values [0, 100]
# Morningstar: values [0, 100] # dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100] # # Three White Soldiers: values [0, 100]
# Three White Soldiers: values [0, 100] # dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
"""
# Pattern Recognition - Bearish candlestick patterns # Pattern Recognition - Bearish candlestick patterns
# ------------------------------------ # ------------------------------------
""" # # Hanging Man: values [0, 100]
# Hanging Man: values [0, 100] # dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe) # # Shooting Star: values [0, 100]
# Shooting Star: values [0, 100] # dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe) # # Gravestone Doji: values [0, 100]
# Gravestone Doji: values [0, 100] # dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe) # # Dark Cloud Cover: values [0, 100]
# Dark Cloud Cover: values [0, 100] # dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe) # # Evening Doji Star: values [0, 100]
# Evening Doji Star: values [0, 100] # dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe) # # Evening Star: values [0, 100]
# Evening Star: values [0, 100] # dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
"""
# Pattern Recognition - Bullish/Bearish candlestick patterns # Pattern Recognition - Bullish/Bearish candlestick patterns
# ------------------------------------ # ------------------------------------
""" # # Three Line Strike: values [0, -100, 100]
# Three Line Strike: values [0, -100, 100] # dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe) # # Spinning Top: values [0, -100, 100]
# Spinning Top: values [0, -100, 100] # dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100] # # Engulfing: values [0, -100, 100]
# Engulfing: values [0, -100, 100] # dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100] # # Harami: values [0, -100, 100]
# Harami: values [0, -100, 100] # dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100] # # Three Outside Up/Down: values [0, -100, 100]
# Three Outside Up/Down: values [0, -100, 100] # dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100] # # Three Inside Up/Down: values [0, -100, 100]
# Three Inside Up/Down: values [0, -100, 100] # dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
"""
# Chart type # # Chart type
# ------------------------------------ # # ------------------------------------
""" # # Heikinashi stategy
# Heikinashi stategy # heikinashi = qtpylib.heikinashi(dataframe)
heikinashi = qtpylib.heikinashi(dataframe) # dataframe['ha_open'] = heikinashi['open']
dataframe['ha_open'] = heikinashi['open'] # dataframe['ha_close'] = heikinashi['close']
dataframe['ha_close'] = heikinashi['close'] # dataframe['ha_high'] = heikinashi['high']
dataframe['ha_high'] = heikinashi['high'] # dataframe['ha_low'] = heikinashi['low']
dataframe['ha_low'] = heikinashi['low']
"""
# Retrieve best bid and best ask from the orderbook # Retrieve best bid and best ask from the orderbook
# ------------------------------------ # ------------------------------------