# Source: generated via dynamic_strategy_generator from freqtrade.strategy import IStrategy from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib class ACO_5_9(IStrategy): timeframe = '1h' # Standard ROI and Stoploss minimal_roi = {"0": 0.1, "60": 0.05, "120": 0.0} stoploss = -0.05 def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: macd = ta.MACD(dataframe, fastperiod=19, slowperiod=39, signalperiod=9) dataframe['macd'] = macd['macd'] dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdhist'] = macd['macdhist'] dataframe['trix'] = ta.TRIX(dataframe, timeperiod=15) dataframe['adx'] = ta.ADX(dataframe, timeperiod=14) dataframe['ultosc'] = ta.ULTOSC(dataframe, timeperiod1=7, timeperiod2=14, timeperiod3=28) dataframe['trima'] = ta.TRIMA(dataframe, timeperiod=20) dataframe['sar'] = ta.SAR(dataframe, acceleration=0.02, maximum=0.2) bbands = ta.BBANDS(dataframe, timeperiod=14, nbdevup=2.0, nbdevdn=2.0) dataframe['upperband'] = bbands['upperband'] dataframe['middleband'] = bbands['middleband'] dataframe['lowerband'] = bbands['lowerband'] return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal']) ) & ( qtpylib.crossed_above(dataframe['trix'], 0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['adx'] < 20) ) & ( (dataframe['ultosc'] > 65) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['trima']) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['sar']) ) & ( (dataframe['close'] > dataframe['upperband'] * 0.98) ), 'exit_long'] = 1 return dataframe