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BollingerBandsStrategy

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jinzheng8115/freqtrade-crypto-system/user_data/strategies/BollingerBandsStrategy.py · first seen 2026-07-16 · repo updated 2026-02-23 · ⬇ 1 download

Basics mode: spot timeframe: 15m interface version: 3
Settings stoploss: -0.05 has minimal roi trailing startup candle count: 100 hyperopt hyperopt params: 2
Indicators Bollinger_Bands talib
Concepts trailing
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# Bollinger Bands 突破策略
# 原理：价格触及下轨买入，触及上轨卖出
# 适合：波动率变化的市场
from freqtrade.strategy import IStrategy, IntParameter, DecimalParameter
from pandas import DataFrame
import talib.abstract as ta
from functools import reduce

class BollingerBandsStrategy(IStrategy):
    INTERFACE_VERSION = 3
    
    # 可优化参数
    bb_period = IntParameter(15, 25, default=20, space="buy", optimize=True)
    bb_std = DecimalParameter(1.5, 2.5, default=2.0, space="buy", optimize=True)
    
    # 止盈止损
    minimal_roi = {"0": 0.08}
    stoploss = -0.05
    
    timeframe = '15m'
    
    trailing_stop = True
    trailing_stop_positive = 0.03
    trailing_stop_positive_offset = 0.04
    trailing_only_offset_is_reached = True
    
    startup_candle_count = 100
    
    order_types = {
        'entry': 'limit',
        'exit': 'limit',
        'stoploss': 'market',
        'stoploss_on_exchange': False
    }
    
    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        bollinger = ta.BBANDS(dataframe, timeperiod=self.bb_period.value, nbdevup=self.bb_std.value, nbdevdn=self.bb_std.value)
        dataframe['bb_lower'] = bollinger['lowerband']
        dataframe['bb_middle'] = bollinger['middleband']
        dataframe['bb_upper'] = bollinger['upperband']
        dataframe['bb_width'] = (dataframe['bb_upper'] - dataframe['bb_lower']) / dataframe['bb_middle']
        return dataframe
    
    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[:, 'enter_long'] = 0
        
        conditions = [
            # 价格触及下轨
            dataframe['close'] < dataframe['bb_lower'],
            # 带宽足够（非极端收敛）
            dataframe['bb_width'] > 0.02,
        ]
        
        if conditions:
            dataframe.loc[reduce(lambda x, y: x & y, conditions), 'enter_long'] = 1
        
        return dataframe
    
    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[:, 'exit_long'] = 0
        
        conditions = [
            # 价格触及上轨
            dataframe['close'] > dataframe['bb_upper'],
        ]
        
        if conditions:
            dataframe.loc[reduce(lambda x, y: x & y, conditions), 'exit_long'] = 1
        
        return dataframe