Timeframe
5m
Direction
Long Only
Stoploss
-10.0%
Trailing Stop
Yes
ROI
0m: 50.0%
Interface Version
3
Startup Candles
N/A
Indicators
2
freqtrade/freqtrade-strategies
Strategy 003 author@: Gerald Lonlas github@: https://github.com/freqtrade/freqtrade-strategies
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class TrailingStrategy(IStrategy):
INTERFACE_VERSION = 3
# ROI: We set high ROI targets because we want the trailing stop to close the trade
minimal_roi = {
"0": 0.5 # 50% profit target (unlikely to hit, lets trailing stop work)
}
# 1. Stoploss: Initial hard stop
stoploss = -0.10
# 2. Trailing Stop: Logic to lock in gains
trailing_stop = True
trailing_stop_positive = 0.01 # trailing stop jumps to 1% behind price
trailing_stop_positive_offset = 0.02 # ...but only after 2% profit is reached
trailing_only_offset_is_reached = True # Only trail once the offset is reached
timeframe = '5m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# RSIs
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# Bollinger Bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_upperband'] = bollinger['upper']
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# Use same conservative entry as CombinedStrategy
(dataframe['rsi'] < 30) & # Relaxed slightly from 18 to get more trades for testing
(dataframe['close'] < dataframe['bb_lowerband']) &
(dataframe['volume'] > 0)
),
'enter_long'] = 1
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# We primarily rely on Trailing Stop, but keep the "Overbought" safety net
dataframe.loc[
(
(dataframe['rsi'] > 85) &
(dataframe['volume'] > 0)
),
'exit_long'] = 1
return dataframe