# 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_16_5(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['ultosc'] = ta.ULTOSC(dataframe, timeperiod1=7, timeperiod2=14, timeperiod3=28) dataframe['aroonosc'] = ta.AROONOSC(dataframe, timeperiod=14) dataframe['ema_fast'] = ta.EMA(dataframe, timeperiod=12) dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=26) dataframe['obv'] = ta.OBV(dataframe) dataframe['obv_sma'] = ta.SMA(dataframe, timeperiod=20, price='obv') dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) dataframe['cci'] = ta.CCI(dataframe, timeperiod=20) dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7) dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14) dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14) dataframe['wma'] = ta.WMA(dataframe, timeperiod=20) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['ultosc'] < 30) ) & ( qtpylib.crossed_above(dataframe['aroonosc'], 0) ) & ( qtpylib.crossed_above(dataframe['ema_fast'], dataframe['ema_slow']) ) & ( qtpylib.crossed_above(dataframe['obv'], dataframe['obv_sma']) ) & ( (dataframe['natr'] > 3.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['cci'] > 150) ) & ( (dataframe['willr'] > -25) ) & ( qtpylib.crossed_below(dataframe['plus_di'], dataframe['minus_di']) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['wma']) ), 'exit_long'] = 1 return dataframe