实现简单单品种回测

main.py

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+# main.py
+
+from src.analysis.result_analyzer import ResultAnalyzer
+# 导入所有必要的模块
+from src.data_manager import DataManager
+from src.backtest_engine import BacktestEngine
+from src.strategies.simple_limit_buy_strategy import SimpleLimitBuyStrategy
+
+
+def main():
+    # --- 配置参数 ---
+    # 获取当前脚本所在目录，假设数据文件在项目根目录下的 data 文件夹内
+    data_file_path = '/mnt/d/PyProject/NewQuant/data/data/SHFE_rb2501/SHFE_rb2501_m60_20240901_20241201_min60.csv'
+
+    initial_capital = 100000.0
+    slippage_rate = 0.001  # 假设每笔交易0.1%的滑点
+    commission_rate = 0.0002  # 假设每笔交易0.02%的佣金
+
+    strategy_parameters = {
+        'symbol': "SHFE_rb2501",  # 根据您的数据文件中的品种名称调整
+        'trade_volume': 1,  # 每次交易1手/股
+        'limit_price_factor': 0.995,  # 限价单价格为开盘价的99.5%
+        'max_position': 10  # 最大持仓10手/股
+    }
+
+    # --- 1. 初始化数据管理器 ---
+    print("初始化数据管理器...")
+    data_manager = DataManager(file_path=data_file_path)
+    # 确保 DataManager 能够重置以进行多次回测
+    # data_manager.reset() # 首次运行不需要重置
+
+    # --- 2. 初始化回测引擎并运行 ---
+    print("\n初始化回测引擎...")
+    engine = BacktestEngine(
+        data_manager=data_manager,
+        strategy_class=SimpleLimitBuyStrategy,
+        strategy_params=strategy_parameters,
+        initial_capital=initial_capital,
+        slippage_rate=slippage_rate,
+        commission_rate=commission_rate
+    )
+
+    print("\n开始运行回测...")
+    engine.run_backtest()
+    print("\n回测运行完毕。")
+
+    # --- 3. 获取回测结果 ---
+    results = engine.get_backtest_results()
+    portfolio_snapshots = results["portfolio_snapshots"]
+    trade_history = results["trade_history"]
+    initial_capital_result = results["initial_capital"]
+
+    # --- 4. 结果分析与可视化 ---
+    if portfolio_snapshots:
+        analyzer = ResultAnalyzer(portfolio_snapshots, trade_history, initial_capital_result)
+
+        analyzer.generate_report()
+        analyzer.plot_performance()
+    else:
+        print("\n没有生成投资组合快照，无法进行结果分析。")
+
+    # --- 4. 结果分析与可视化 (待实现) ---
+    # if portfolio_snapshots:
+    #     analyzer = ResultAnalyzer(portfolio_snapshots, trade_history, initial_capital_result)
+    #     metrics = analyzer.calculate_all_metrics()
+    #     print("\n--- 绩效指标 ---")
+    #     for key, value in metrics.items():
+    #         print(f"  {key}: {value:.4f}")
+    #
+    #     print("\n--- 绘制绩效图表 ---")
+    #     analyzer.plot_performance()
+    # else:
+    #     print("\n没有生成投资组合快照，无法进行结果分析。")
+
+
+if __name__ == '__main__':
+    main()