Timeframe
1h
Direction
Long Only
Stoploss
-5.0%
Trailing Stop
No
ROI
0m: 10.0%, 60m: 5.0%, 120m: 0.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
1
freqtrade/freqtrade-strategies
This strategy uses custom_stoploss() to enforce a fixed risk/reward ratio by first calculating a dynamic initial stoploss via ATR - last negative peak
freqtrade/freqtrade-strategies
this is an example class, implementing a PSAR based trailing stop loss you are supposed to take the `custom_stoploss()` and `populate_indicators()` parts and adapt it to your own strategy
freqtrade/freqtrade-strategies
# Source: generated from predefined_indicators.json
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class SAR_tight(IStrategy):
timeframe = '1h'
# Standard ROI and Stoploss
minimal_roi = {"0": 0.1, "60": 0.05, "120": 0.0}
stoploss = -0.05
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['sar'] = ta.SAR(dataframe, acceleration=0.01, maximum=0.1)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
qtpylib.crossed_above(dataframe['close'], dataframe['sar']),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
qtpylib.crossed_below(dataframe['close'], dataframe['sar']),
'exit_long'] = 1
return dataframe