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基本完毕
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import MetaTrader5 as mt5
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import pandas as pd
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from utils import get_rates, close_all, send_order
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from logger import logger
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from .base_strategy import BaseStrategy
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from config import STRATEGY_CONFIG
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class Strategy:
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def __init__(self):
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self.symbol = "XAUUSD"
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self.timeframe = mt5.TIMEFRAME_M1
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self.bollinger_period = 20
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self.bollinger_std_dev = 2
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class BollingerStrategy(BaseStrategy):
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def __init__(self, data_provider, symbol, timeframe, period=None, std_dev=None):
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super().__init__(data_provider, symbol, timeframe)
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# 从配置中获取参数,如果传入参数则使用传入的参数
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config = STRATEGY_CONFIG.get('bollinger', {})
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self.period = period if period is not None else config.get('period', 20)
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self.std_dev = std_dev if std_dev is not None else config.get('std_dev', 2.0)
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def _calculate_indicators(self, df):
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"""
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计算布林带指标
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"""
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mean = df['close'].rolling(self.bollinger_period).mean()
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std = df['close'].rolling(self.bollinger_period).std()
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df['upper_band'] = mean + self.bollinger_std_dev * std
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df['lower_band'] = mean - self.bollinger_std_dev * std
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mean = df['close'].rolling(self.period).mean()
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std = df['close'].rolling(self.period).std()
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df['upper_band'] = mean + self.std_dev * std
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df['lower_band'] = mean - self.std_dev * std
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return df
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def generate_signal(self):
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"""
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布林带策略实盘:
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当价格跌破下轨买入,涨破上轨卖出。
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"""
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rates = get_rates(self.symbol, self.timeframe, self.bollinger_period + 30)
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if rates is None or len(rates) < self.bollinger_period:
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rates = self.data_provider.get_historical_data(self.symbol, self.timeframe, self.period + 5)
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if rates is None or len(rates) < self.period:
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return 0
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df = pd.DataFrame(rates)
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df = self._calculate_indicators(df)
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if df['close'].iloc[-2] < df['lower_band'].iloc[-2]:
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logger.info(f"价格跌破下轨,产生买入信号: {self.symbol}")
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if df['close'].iloc[-1] < df['lower_band'].iloc[-1]:
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return 1
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elif df['close'].iloc[-2] > df['upper_band'].iloc[-2]:
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logger.info(f"价格涨破上轨,产生卖出信号: {self.symbol}")
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elif df['close'].iloc[-1] > df['upper_band'].iloc[-1]:
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return -1
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return 0
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def run_backtest(self, df):
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"""
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布林带策略回测:
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价格突破下轨买入,突破上轨卖出
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返回信号序列:1买入,-1卖出,0无操作
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"""
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df = df.copy()
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df = self._calculate_indicators(df)
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signals = pd.Series(0, index=df.index)
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for i in range(self.bollinger_period, len(df)):
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if df['close'].iloc[i-1] < df['lower_band'].iloc[i-1]:
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signals.iat[i] = 1
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elif df['close'].iloc[i-1] > df['upper_band'].iloc[i-1]:
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signals.iat[i] = -1
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return signals
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signals[df['close'] < df['lower_band']] = 1
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signals[df['close'] > df['upper_band']] = -1
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return signals
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