Timeframe
5m
Direction
Long Only
Stoploss
-5.0%
Trailing Stop
Yes
ROI
0m: 10.0%, 240m: 5.0%
Interface Version
N/A
Startup Candles
20
Indicators
4
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
"""Strategy 9: Parabolic SAR Trend Follow"""
import talib.abstract as ta
from freqtrade.strategy import IStrategy
from pandas import DataFrame
class ParabolicSarStrategy(IStrategy):
timeframe = "5m"
minimal_roi = {"0": 0.10, "240": 0.05}
stoploss = -0.05
trailing_stop = True
trailing_stop_positive = 0.02
trailing_stop_positive_offset = 0.04
trailing_only_offset_is_reached = True
startup_candle_count = 20
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe["sar"] = ta.SAR(dataframe, acceleration=0.02, maximum=0.2)
dataframe["sar_prev"] = dataframe["sar"].shift(1)
dataframe["close_prev"] = dataframe["close"].shift(1)
dataframe["ema50"] = ta.EMA(dataframe, timeperiod=50)
dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] > dataframe["sar"])
& (dataframe["close_prev"] <= dataframe["sar_prev"])
& (dataframe["adx"] > 20)
& (dataframe["close"] > dataframe["ema50"])
& (dataframe["volume"] > 0),
"enter_long",
] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe["close"] < dataframe["sar"]) | (dataframe["rsi"] > 75),
"exit_long",
] = 1
return dataframe