Timeframe
N/A
Direction
Long Only
Stoploss
-10.0%
Trailing Stop
No
ROI
0m: 15.0%
Interface Version
N/A
Startup Candles
N/A
Indicators
1
iterativv/NostalgiaForInfinity
davidzr/freqtrade-strategies
BB_RPB_TSL @author jilv220 Simple bollinger brand strategy inspired by this blog ( https://hacks-for-life.blogspot.com/2020/12/freqtrade-notes.html ) RPB, which stands for Real Pull Back, taken from ( https://github.com/GeorgeMurAlkh/freqtrade-stuff/blob/main/user_data/strategies/TheRealPullbackV2.py ) The trailing custom stoploss taken from BigZ04_TSL from Perkmeister ( modded by ilya ) I modified it to better suit my taste and added Hyperopt for this strategy.
davidzr/freqtrade-strategies
BB_RPB_TSL @author jilv220 Simple bollinger brand strategy inspired by this blog ( https://hacks-for-life.blogspot.com/2020/12/freqtrade-notes.html ) RPB, which stands for Real Pull Back, taken from ( https://github.com/GeorgeMurAlkh/freqtrade-stuff/blob/main/user_data/strategies/TheRealPullbackV2.py ) The trailing custom stoploss taken from BigZ04_TSL from Perkmeister ( modded by ilya ) I modified it to better suit my taste and added Hyperopt for this strategy.
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
from technical.indicators import ichimoku
import freqtrade.vendor.qtpylib.indicators as qtpylib
class Stavix2(IStrategy):
minimal_roi = {
"0": 0.15
}
stoploss = -0.10
ticker_interval = '1m'
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
cloud = ichimoku(dataframe, conversion_line_period=200, base_line_periods=350, laggin_span=150, displacement=75)
dataframe['tenkan_sen'] = cloud['tenkan_sen']
dataframe['kijun_sen'] = cloud['kijun_sen']
dataframe['senkou_span_a'] = cloud['senkou_span_a']
dataframe['senkou_span_b'] = cloud['senkou_span_b']
dataframe['chikou_span'] = cloud['chikou_span']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['close'] > dataframe['senkou_span_a']) &
(dataframe['close'] > dataframe['senkou_span_b']) &
(qtpylib.crossed_above(dataframe['kijun_sen'], dataframe['tenkan_sen']))
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['close'] < dataframe['senkou_span_a']) &
(dataframe['close'] < dataframe['senkou_span_b']) &
(qtpylib.crossed_above(dataframe['tenkan_sen'], dataframe['kijun_sen']))
),
'sell'] = 1
return dataframe