mirror of
https://github.com/silencesdg/mt5_python_ea_suite.git
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96 lines
4.0 KiB
Python
96 lines
4.0 KiB
Python
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import pandas as pd
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from tqdm import tqdm
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from core.risk import RiskController
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from config import SIGNAL_THRESHOLDS, BACKTEST_CONFIG, SPREAD
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from logger import logger
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class BacktestEngine:
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def __init__(self, df, trade_direction="both"):
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self.df = df
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self.trade_direction = trade_direction
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self.spread = BACKTEST_CONFIG.get("spread", SPREAD)
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def run_strategy(self, strategy):
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signals = strategy.run_backtest(self.df)
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buy_count = (signals == 1).sum()
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sell_count = (signals == -1).sum()
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logger.info(f"策略 {strategy.__class__.__module__} 信号统计 - 买入: {buy_count}, 卖出: {sell_count}")
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return signals
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def combine_signals(self, signals_list, weights):
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df_signals = pd.concat(signals_list, axis=1).fillna(0)
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weighted_signals = df_signals * weights
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combined = weighted_signals.sum(axis=1)
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def apply_threshold(score):
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if score > SIGNAL_THRESHOLDS["buy_threshold"]:
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return 1
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elif score < SIGNAL_THRESHOLDS["sell_threshold"]:
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return -1
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else:
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return 0
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combined_signal = combined.apply(apply_threshold)
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buy_signals = (combined_signal == 1).sum()
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sell_signals = (combined_signal == -1).sum()
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logger.info(f"组合信号统计 - 买入: {buy_signals}, 卖出: {sell_signals}")
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return combined_signal
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def run_backtest(self, signals, symbol="XAUUSD"):
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df = self.df.copy()
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df['signal'] = signals.shift(1).fillna(0)
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risk_controller = RiskController(self.trade_direction)
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logger.info(f"回测开始: 交易方向={self.trade_direction}")
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# 使用tqdm创建进度条
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for i in tqdm(range(1, len(df)), desc=f"Backtesting ({len(df)} bars)"):
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current_signal = df['signal'].iloc[i]
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# 计算考虑双向点差的买卖价格
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close_price = df['close'].iloc[i]
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spread_points = self.spread
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spread_half = spread_points * 0.01 / 2 # XAUUSD: 1点 = 0.01，双向点差各一半
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current_price = {
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'bid': close_price - spread_half, # 卖出价格（中间价 - 点差/2）
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'ask': close_price + spread_half, # 买入价格（中间价 + 点差/2）
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'last': close_price # 最后成交价（中间价）
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}
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direction = None
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if current_signal == 1:
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direction = "buy"
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elif current_signal == -1:
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direction = "sell"
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if direction:
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risk_controller.process_trading_signal(
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direction, current_price, abs(current_signal), dry_run=True
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)
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risk_controller.monitor_positions(current_price, dry_run=True)
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risk_controller.position_manager.force_close_all_positions(df['close'].iloc[-1], dry_run=True)
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logger.info("回测完成，生成性能报告...")
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summary = risk_controller.position_manager.get_trade_summary()
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logger.info("=" * 80)
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logger.info("回测性能报告")
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logger.info("=" * 80)
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logger.info(f" 总交易次数: {summary['total_trades']}")
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logger.info(f" 盈利次数: {summary['winning_trades']}")
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logger.info(f" 亏损次数: {summary['losing_trades']}")
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logger.info(f" 胜率: {summary['win_rate']:.2f}%")
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logger.info("-" * 40)
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logger.info(f" 总盈亏: ${summary['total_profit_loss']:.2f}")
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logger.info(f" 平均每笔交易盈亏: ${summary['avg_profit_loss']:.2f}")
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logger.info(f" 最大盈利: ${summary['max_profit']:.2f}")
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logger.info(f" 最大亏损: ${summary['max_loss']:.2f}")
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logger.info("=" * 80)
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risk_controller.position_manager.save_to_csv("backtest_trades.csv")
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risk_controller.position_manager.save_to_json("backtest_trades.json")
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return summary
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