# 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_55_19(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['kama'] = ta.KAMA(dataframe, timeperiod=30) dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) stochrsi = ta.STOCHRSI(dataframe, timeperiod=7, fastk_period=3, fastd_period=3) dataframe['fastk'] = stochrsi['fastk'] dataframe['fastd'] = stochrsi['fastd'] dataframe['apo'] = ta.APO(dataframe, fastperiod=12, slowperiod=26) dataframe['ema_fast'] = ta.EMA(dataframe, timeperiod=12) dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=26) 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['close'], dataframe['kama']) ) & ( (dataframe['natr'] > 2.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['fastk'] > 85) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['ema_fast'], dataframe['ema_slow']) ) & ( (dataframe['close'] > dataframe['upperband'] * 0.98) ), 'exit_long'] = 1 return dataframe