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Updated 3/23/18 4:25PMC

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Updated 3/23/18 4:25PMC
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MoonGem 2018-03-23 16:25:56 -05:00 committed by GitHub
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1 changed files with 15 additions and 14 deletions
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29
user_data/strategies/test_strategy.py
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@ -13,7 +13,10 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy # noqa import numpy # noqa
# Update this variable if you change the class name # Make a backup of default_strategy then move this file over your default strategy in freqtrade/strategy and to run run with -s all to find best values when running hyperopt.
#
# Make sure to take note of the if statements at the bottom of the file, and the pattern of > < and >= <= and the triggers configuration.
class_name = 'DefaultStrategy' class_name = 'DefaultStrategy'
@ -64,7 +67,7 @@ class DefaultStrategy(IStrategy):
# ADX # ADX
dataframe['adx'] = ta.ADX(dataframe) dataframe['adx'] = ta.ADX(dataframe)
"""
# Awesome oscillator # Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
@ -116,7 +119,7 @@ class DefaultStrategy(IStrategy):
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
# ------------------------------------ # ------------------------------------
@ -137,7 +140,7 @@ class DefaultStrategy(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)
@ -150,7 +153,6 @@ class DefaultStrategy(IStrategy):
# SMA - Simple Moving Average # SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40) dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
"""
# TEMA - Triple Exponential Moving Average # TEMA - Triple Exponential Moving Average
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
@ -164,7 +166,7 @@ class DefaultStrategy(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]
@ -177,11 +179,11 @@ class DefaultStrategy(IStrategy):
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]
@ -194,11 +196,10 @@ class DefaultStrategy(IStrategy):
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]
@ -211,18 +212,18 @@ class DefaultStrategy(IStrategy):
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']
"""
return dataframe return dataframe