Timeframe
N/A
Direction
Long Only
Stoploss
-12.6%
Trailing Stop
No
ROI
0m: 26.6%, 30m: 10.3%, 210m: 3.5%, 540m: 0.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
2
freqtrade/freqtrade-strategies
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
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
__author__ = "Robert Roman"
__copyright__ = "Free For Use"
__license__ = "MIT"
__version__ = "1.0"
__maintainer__ = "Robert Roman"
__email__ = "robertroman7@gmail.com"
__BTC_donation__ = "3FgFaG15yntZYSUzfEpxr5mDt1RArvcQrK"
# Optimized With Sortino Ratio and 2 years data
class adx_strategy(IStrategy):
ticker_interval = '15m'
# ROI table:
minimal_roi = {
"0": 0.26552,
"30": 0.10255,
"210": 0.03545,
"540": 0
}
# Stoploss:
stoploss = -0.1255
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# ADX
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
dataframe['sar'] = ta.SAR(dataframe)
dataframe['mom'] = ta.MOM(dataframe, timeperiod=14)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 16) &
(dataframe['minus_di'] > 4) &
# (dataframe['plus_di'] > 33) &
(qtpylib.crossed_above(dataframe['minus_di'], dataframe['plus_di']))
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 43) &
# (dataframe['minus_di'] > 22) &
(dataframe['plus_di'] > 24) &
(qtpylib.crossed_above(dataframe['plus_di'], dataframe['minus_di']))
),
'sell'] = 1
return dataframe