Timeframe
5m
Direction
Long Only
Stoploss
-6.0%
Trailing Stop
No
ROI
0m: 1.2%, 30m: 0.6%, 90m: 0.0%
Interface Version
N/A
Startup Candles
100
Indicators
2
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
# Klineo Backtesting Strategy: Bollinger Bands Mean Reversion
# Timeframe: 5m | Entry: close < bb_lower AND rsi < 30 | Exit: close > bb_mid OR rsi > 55
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
class KlineoBollingerRevert(IStrategy):
timeframe = "5m"
startup_candle_count = 100
minimal_roi = {"0": 0.012, "30": 0.006, "90": 0.0}
stoploss = -0.06
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
bbands = ta.BBANDS(dataframe, timeperiod=20, nbdevup=2, nbdevdn=2)
dataframe["bb_upper"] = bbands["upperband"]
dataframe["bb_middle"] = bbands["middleband"]
dataframe["bb_lower"] = bbands["lowerband"]
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] < dataframe["bb_lower"]) & (dataframe["rsi"] < 30),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] > dataframe["bb_middle"]) | (dataframe["rsi"] > 55),
"exit_long",
] = 1
return dataframe