Timeframe
5m
Direction
Long Only
Stoploss
-4.0%
Trailing Stop
No
ROI
0m: 8.0%, 120m: 4.0%
Interface Version
N/A
Startup Candles
20
Indicators
2
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""Strategy: Bullish Engulfing Pattern Strategy"""
import talib.abstract as ta
from freqtrade.strategy import IStrategy
from pandas import DataFrame
class BullishEngulfingStrategy(IStrategy):
timeframe = "5m"
minimal_roi = {"0": 0.08, "120": 0.04}
stoploss = -0.04
startup_candle_count = 20
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe["engulfing"] = ta.CDLENGULFING(dataframe)
dataframe["hammer"] = ta.CDLHAMMER(dataframe)
dataframe["morning_doji"] = ta.CDLMORNINGDOJISTAR(dataframe)
dataframe["ema50"] = ta.EMA(dataframe, timeperiod=50)
dataframe["ema100"] = ta.EMA(dataframe, timeperiod=100)
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
dataframe["volume_ma"] = dataframe["volume"].rolling(20).mean()
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
((dataframe["engulfing"] > 0) | (dataframe["hammer"] > 0) | (dataframe["morning_doji"] > 0))
& (dataframe["ema50"] > dataframe["ema100"])
& (dataframe["rsi"] < 60)
& (dataframe["volume"] > dataframe["volume_ma"])
& (dataframe["volume"] > 0),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["engulfing"] < 0) | (dataframe["rsi"] > 73),
"exit_long",
] = 1
return dataframe