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BinHV27_5

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remiotore/ccxt-freqtrade/strategies/BinHV27_5_converted.py · ★3 · ⑂2 · first seen 2026-07-28 · repo updated 2026-01-11

Basics mode: spot timeframe: 5m interface version: 3
Settings stoploss: -0.5 has minimal roi
Indicators ADX EMA RSI SMA talib
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from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
from typing import Dict, List
from functools import reduce
from pandas import DataFrame, DatetimeIndex, merge
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy  # noqa

class BinHV27_5(IStrategy):
    INTERFACE_VERSION = 3
    '\n\n        strategy sponsored by user BinH from slack\n\n    '
    minimal_roi = {'0': 1}
    stoploss = -0.5
    timeframe = '5m'

    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
        dataframe['rsi'] = numpy.nan_to_num(ta.RSI(dataframe, timeperiod=5))
        rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'})
        dataframe['emarsi'] = numpy.nan_to_num(ta.EMA(rsiframe, timeperiod=5))
        dataframe['adx'] = numpy.nan_to_num(ta.ADX(dataframe))
        dataframe['minusdi'] = numpy.nan_to_num(ta.MINUS_DI(dataframe))
        minusdiframe = DataFrame(dataframe['minusdi']).rename(columns={'minusdi': 'close'})
        dataframe['minusdiema'] = numpy.nan_to_num(ta.EMA(minusdiframe, timeperiod=25))
        dataframe['plusdi'] = numpy.nan_to_num(ta.PLUS_DI(dataframe))
        plusdiframe = DataFrame(dataframe['plusdi']).rename(columns={'plusdi': 'close'})
        dataframe['plusdiema'] = numpy.nan_to_num(ta.EMA(plusdiframe, timeperiod=5))
        dataframe['lowsma'] = numpy.nan_to_num(ta.EMA(dataframe, timeperiod=60))
        dataframe['highsma'] = numpy.nan_to_num(ta.EMA(dataframe, timeperiod=120))
        dataframe['fastsma'] = numpy.nan_to_num(ta.SMA(dataframe, timeperiod=120))
        dataframe['slowsma'] = numpy.nan_to_num(ta.SMA(dataframe, timeperiod=240))
        dataframe['bigup'] = dataframe['fastsma'].gt(dataframe['slowsma']) & (dataframe['fastsma'] - dataframe['slowsma'] > dataframe['close'] / 300)
        dataframe['bigdown'] = ~dataframe['bigup']
        dataframe['trend'] = dataframe['fastsma'] - dataframe['slowsma']
        dataframe['preparechangetrend'] = dataframe['trend'].gt(dataframe['trend'].shift())
        dataframe['preparechangetrendconfirm'] = dataframe['preparechangetrend'] & dataframe['trend'].shift().gt(dataframe['trend'].shift(2))
        dataframe['continueup'] = dataframe['slowsma'].gt(dataframe['slowsma'].shift()) & dataframe['slowsma'].shift().gt(dataframe['slowsma'].shift(2))
        dataframe['delta'] = dataframe['fastsma'] - dataframe['fastsma'].shift()
        dataframe['slowingdown'] = dataframe['delta'].lt(dataframe['delta'].shift())
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame) -> DataFrame:
        dataframe.loc[dataframe['slowsma'].gt(0) & dataframe['close'].lt(dataframe['highsma']) & dataframe['close'].lt(dataframe['lowsma']) & dataframe['minusdi'].gt(dataframe['minusdiema']) & dataframe['rsi'].ge(dataframe['rsi'].shift()) & (~dataframe['preparechangetrend'] & ~dataframe['continueup'] & dataframe['adx'].gt(25) & dataframe['bigdown'] & dataframe['emarsi'].le(20) | ~dataframe['preparechangetrend'] & dataframe['continueup'] & dataframe['adx'].gt(30) & dataframe['bigdown'] & dataframe['emarsi'].le(20) | ~dataframe['continueup'] & dataframe['adx'].gt(35) & dataframe['bigup'] & dataframe['emarsi'].le(20) | dataframe['continueup'] & dataframe['adx'].gt(30) & dataframe['bigup'] & dataframe['emarsi'].le(25)), 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame) -> DataFrame:
        buyframe = dataframe[dataframe['buy'] == 1].tail(1)
        if len(buyframe) == 0:
            dataframe.loc[[False], 'exit_long'] = 0
            return dataframe
        trend = buyframe.iloc[0]['trend']
        bigup = buyframe.iloc[0]['bigup']
        bigdown = buyframe.iloc[0]['bigdown']
        price = buyframe.iloc[0]['close']
        dataframe.loc[bigup & ~dataframe['preparechangetrendconfirm'] & ~dataframe['continueup'] & (dataframe['close'].gt(dataframe['lowsma']) | dataframe['close'].gt(dataframe['highsma'])) & dataframe['highsma'].gt(0) & (dataframe['bigdown'] | dataframe['trend'].lt(trend)) | bigdown & ~dataframe['preparechangetrendconfirm'] & ~dataframe['continueup'] & dataframe['close'].gt(dataframe['highsma']) & dataframe['highsma'].gt(0) & (dataframe['emarsi'].ge(75) | dataframe['close'].gt(dataframe['slowsma'])) & (dataframe['bigdown'] | dataframe['trend'].lt(trend)) | ~dataframe['preparechangetrendconfirm'] & dataframe['close'].gt(dataframe['highsma']) & dataframe['highsma'].gt(0) & dataframe['adx'].gt(30) & dataframe['emarsi'].ge(80) & dataframe['bigup'] | dataframe['preparechangetrendconfirm'] & ~dataframe['continueup'] & dataframe['slowingdown'] & dataframe['emarsi'].ge(75) & dataframe['slowsma'].gt(0) | dataframe['preparechangetrendconfirm'] & dataframe['minusdi'].lt(dataframe['plusdi']) & dataframe['close'].gt(dataframe['lowsma']) & dataframe['slowsma'].gt(0), 'exit_long'] = 1
        return dataframe