基本完毕

strategies/daily_breakout.py

@@ -1,18 +1,16 @@
-import MetaTrader5 as mt5
 import pandas as pd
 from datetime import datetime
-from utils import get_rates, has_open_position, close_all, send_order
-from logger import logger
+from .base_strategy import BaseStrategy
+from config import STRATEGY_CONFIG
 
-class Strategy:
-    def __init__(self):
-        self.symbol = "XAUUSD"
-        self.timeframe = mt5.TIMEFRAME_M1
+class DailyBreakoutStrategy(BaseStrategy):
+    def __init__(self, data_provider, symbol, timeframe, bars_count=None):
+        super().__init__(data_provider, symbol, timeframe)
+        # 从配置中获取参数，如果传入参数则使用传入的参数
+        config = STRATEGY_CONFIG.get('daily_breakout', {})
+        self.bars_count = bars_count if bars_count is not None else config.get('bars_count', 1440)
 
     def _calculate_indicators(self, df):
-        """
-        计算日内突破指标
-        """
         df['time'] = pd.to_datetime(df['time'], unit='s')
         today = datetime.now().date()
         day_data = df[df['time'].dt.date == today]
@@ -23,11 +21,7 @@ class Strategy:
         return df, day_high, day_low
 
     def generate_signal(self):
-        """
-        日内突破策略实盘
-        当价格突破当日最高买入，突破当日最低卖出
-        """
-        rates = get_rates(self.symbol, self.timeframe, 1440) # 24 hours * 60 minutes
+        rates = self.data_provider.get_historical_data(self.symbol, self.timeframe, self.bars_count)
         if rates is None or len(rates) < 2:
             return 0
         df = pd.DataFrame(rates)
@@ -36,33 +30,21 @@ class Strategy:
         if day_high is None or day_low is None:
             return 0
 
-        if df['close'].iloc[-2] > day_high:
-            logger.info(f"价格突破当日最高，产生买入信号: {self.symbol}")
+        if df['close'].iloc[-1] > day_high:
             return 1
-        elif df['close'].iloc[-2] < day_low:
-            logger.info(f"价格突破当日最低，产生卖出信号: {self.symbol}")
+        elif df['close'].iloc[-1] < day_low:
             return -1
         return 0
 
     def run_backtest(self, df):
-        """
-        日内突破回测方法
-        计算每个交易日的高低点，突破买卖信号
-        """
         df = df.copy()
         df['time'] = pd.to_datetime(df['time'], unit='s')
+        df['date'] = df['time'].dt.date
+        
+        daily_highs = df.groupby('date')['high'].transform('max')
+        daily_lows = df.groupby('date')['low'].transform('max')
 
         signals = pd.Series(0, index=df.index)
-
-        grouped = df.groupby(df['time'].dt.date)
-
-        for date, group in grouped:
-            day_high = group['high'].max()
-            day_low = group['low'].min()
-            for i, row in group.iterrows():
-                if row['close'] > day_high:
-                    signals.loc[i] = 1
-                elif row['close'] < day_low:
-                    signals.loc[i] = -1
-
-        return signals
+        signals[df['close'] > daily_highs.shift(1)] = 1
+        signals[df['close'] < daily_lows.shift(1)] = -1
+        return signals