# 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_48_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: dataframe['adx'] = ta.ADX(dataframe, timeperiod=14) dataframe['bop'] = ta.BOP(dataframe) dataframe['kama'] = ta.KAMA(dataframe, timeperiod=30) dataframe['atr'] = ta.ATR(dataframe, timeperiod=14) dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14) dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14) dataframe['apo'] = ta.APO(dataframe, fastperiod=12, slowperiod=26) dataframe['ppo'] = ta.PPO(dataframe, fastperiod=5, slowperiod=20) dataframe['t3'] = ta.T3(dataframe, timeperiod=10, vfactor=0.9) dataframe['sar'] = ta.SAR(dataframe, acceleration=0.03, maximum=0.3) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['adx'] > 30) ) & ( qtpylib.crossed_above(dataframe['bop'], 0) ) & ( qtpylib.crossed_above(dataframe['close'], dataframe['kama']) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( qtpylib.crossed_below(dataframe['plus_di'], dataframe['minus_di']) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['ppo'], 0) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['t3']) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['sar']) ), 'exit_long'] = 1 return dataframe