stable/freqtrade-strategies-master/user_data/strategies/berlinguyinca/CofiBitStrategy.py

81 lines
2.7 KiB
Python

# --- Do not remove these libs ---
import freqtrade.vendor.qtpylib.indicators as qtpylib
import talib.abstract as ta
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
class CofiBitStrategy(IStrategy):
"""
taken from slack by user CofiBit
"""
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
minimal_roi = {
"40": 0.05,
"30": 0.06,
"20": 0.07,
"0": 0.10
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.25
# Optimal timeframe for the strategy
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
stoch_fast = ta.STOCHF(dataframe, 5, 3, 0, 3, 0)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
dataframe['ema_high'] = ta.EMA(dataframe, timeperiod=5, price='high')
dataframe['ema_close'] = ta.EMA(dataframe, timeperiod=5, price='close')
dataframe['ema_low'] = ta.EMA(dataframe, timeperiod=5, price='low')
dataframe['adx'] = ta.ADX(dataframe)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['open'] < dataframe['ema_low']) &
(qtpylib.crossed_above(dataframe['fastk'], dataframe['fastd'])) &
# (dataframe['fastk'] > dataframe['fastd']) &
(dataframe['fastk'] < 30) &
(dataframe['fastd'] < 30) &
(dataframe['adx'] > 30)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(
(dataframe['open'] >= dataframe['ema_high'])
) |
(
# (dataframe['fastk'] > 70) &
# (dataframe['fastd'] > 70)
(qtpylib.crossed_above(dataframe['fastk'], 70)) |
(qtpylib.crossed_above(dataframe['fastd'], 70))
),
'sell'] = 1
return dataframe