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RSIDirectionalWithTrend.py
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RSIDirectionalWithTrend.py
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from freqtrade.strategy import IStrategy, merge_informative_pair
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.exchange import timeframe_to_minutes
import numpy # noqa
class RSIDirectionalWithTrend(IStrategy):
"""
RSIDirectionalWithTrend
author@: Paul Csapak
github@: https://github.com/paulcpk/freqtrade-strategies-that-work
How to use it?
> freqtrade download-data --timeframes 1h --timerange=20180301-20200301
> freqtrade backtesting --export trades -s DoubleEMACrossoverWithTrend --timeframe 1h --timerange=20180301-20200301
> freqtrade plot-dataframe -s DoubleEMACrossoverWithTrend --indicators1 ema100 --timeframe 1h --timerange=20180301-20200301
"""
# Optimal timeframe for the strategy
timeframe = '1h'
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
# timeframe_mins = timeframe_to_minutes(timeframe)
# minimal_roi = {
# "0": 0.08, # 5% for the first 3 candles
# str(timeframe_mins * 12): 0.04, # 2% after 3 candles
# str(timeframe_mins * 24): 0.02, # 1% After 6 candles
# }
# This attribute will be overridden if the config file contains "stoploss"
stoploss = -0.1
# trailing stoploss
trailing_stop = True
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=4)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# RSI crosses above 30
(qtpylib.crossed_above(dataframe['rsi'], 15)) &
(dataframe['low'] > dataframe['ema100']) & # Candle low is above EMA
# Ensure this candle had volume (important for backtesting)
(dataframe['volume'] > 0)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# RSI crosses above 70
(qtpylib.crossed_above(dataframe['rsi'], 85)) |
# OR price is below trend ema
(dataframe['low'] < dataframe['ema100'])
),
'sell'] = 1
return dataframe