NewQuant/futures_trading_strategies/MA/main2.ipynb

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   "id": "initial_id",
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    "ExecuteTime": {
     "end_time": "2025-07-22T07:44:51.375234Z",
     "start_time": "2025-07-22T07:44:51.352161Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a559dfcf",
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     "start_time": "2025-07-22T07:44:51.391111Z"
    }
   },
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'src'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mModuleNotFoundError\u001b[39m                       Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mturtle\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m down\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01msrc\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01manalysis\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mresult_analyzer\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m ResultAnalyzer\n\u001b[32m      3\u001b[39m \u001b[38;5;66;03m# 导入所有必要的模块\u001b[39;00m\n\u001b[32m      4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01msrc\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mdata_manager\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m DataManager\n",
      "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'src'"
     ]
    }
   ],
   "source": [
    "\n",
    "from turtle import down\n",
    "from src.analysis.result_analyzer import ResultAnalyzer\n",
    "# 导入所有必要的模块\n",
    "from src.data_manager import DataManager\n",
    "from src.backtest_engine import BacktestEngine\n",
    "from src.indicators.indicator_list import INDICATOR_LIST\n",
    "from src.indicators.indicators import RSI, BollingerBandwidth, HistoricalRange, NormalizedATR, RateOfChange, StochasticOscillator\n",
    "from src.strategies.OpenTwoFactorStrategy import SimpleLimitBuyStrategyLong, SimpleLimitBuyStrategyShort, SimpleLimitBuyStrategy\n",
    "\n",
    "\n",
    "# --- 配置参数 ---\n",
    "# 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\n",
    "# data_file_path = '/mnt/d/PyProject/NewQuant/data/data/SHFE_rb2510/SHFE_rb2510_min60.csv'\n",
    "# data_file_path = \"/mnt/d/PyProject/NewQuant/data/data/KQ_m@CZCE_MA/KQ_m@CZCE_MA_min60.csv\"\n",
    "# data_file_path = \"/mnt/d/PyProject/NewQuant/data/data/KQ_m@SHFE_rb/KQ_m@SHFE_rb_min60.csv\"\n",
    "data_file_path = \"/mnt/d/PyProject/NewQuant/data/data/KQ_m@CZCE_MA/KQ_m@CZCE_MA_min60.csv\"\n",
    "\n",
    "initial_capital = 100000.0\n",
    "slippage_rate = 0.000  # 假设每笔交易0.1%的滑点\n",
    "commission_rate = 0.0001  # 假设每笔交易0.02%的佣金\n",
    "\n",
    "global_config = {\n",
    "    'symbol': 'KQ_m@CZCE_MA',\n",
    "}\n",
    "\n",
    "# Short 可用\n",
    "strategy_parameters = {\n",
    "    'main_symbol': \"MA\",  # 根据您的数据文件中的品种名称调整\n",
    "    'trade_volume': 1,\n",
    "    'lag': 7,\n",
    "    # 'range_factor': 1.8,  # 示例值，需要通过网格搜索优化\n",
    "    # 'profit_factor': 2.8,  # 示例值\n",
    "    # 'range_factor': 1.6,  # 示例值，需要通过网格搜索优化\n",
    "    # 'profit_factor': 2.1,  # 示例值\n",
    "    'range_factor_l': 1.8,  # 示例值，需要通过网格搜索优化\n",
    "    'profit_factor_l': 2.8,  # 示例值\n",
    "    'range_factor_s': 1.6,  # 示例值，需要通过网格搜索优化\n",
    "    'profit_factor_s': 2.1,  # 示例值\n",
    "    'max_position': 10,\n",
    "    'enable_log': True,\n",
    "    'stop_loss_points': 20,\n",
    "    'use_indicator': True,\n",
    "    # 'indicator': HistoricalRange(11, 25, 20),\n",
    "    # 'indicator': BollingerBandwidth(window=20, nbdev=2.0, down_bound=1.9, up_bound=3.25),\n",
    "    'indicator_l': HistoricalRange(11, 25, 20),\n",
    "    'indicator_s': BollingerBandwidth(window=20, nbdev=2.0, down_bound=1.9, up_bound=3.25),\n",
    "}\n",
    "start_time = datetime(2021, 1, 1)\n",
    "end_time = datetime(2024, 6, 1)\n",
    "\n",
    "start_time = datetime(2024, 6, 1)\n",
    "end_time = datetime(2025, 8, 1)\n",
    "\n",
    "\n",
    "# --- 1. 初始化数据管理器 ---\n",
    "print(\"初始化数据管理器...\")\n",
    "data_manager = DataManager(file_path=data_file_path, symbol=global_config['symbol'], start_time=start_time, end_time=end_time)\n",
    "# 确保 DataManager 能够重置以进行多次回测\n",
    "# data_manager.reset() # 首次运行不需要重置\n",
    "\n",
    "# --- 2. 初始化回测引擎并运行 ---\n",
    "print(\"\\n初始化回测引擎...\")\n",
    "engine = BacktestEngine(\n",
    "    data_manager=data_manager,\n",
    "    strategy_class=SimpleLimitBuyStrategy,\n",
    "    # current_segment_symbol=strategy_parameters['symbol'],\n",
    "    strategy_params=strategy_parameters,\n",
    "    initial_capital=initial_capital,\n",
    "    slippage_rate=slippage_rate,\n",
    "    commission_rate=commission_rate,\n",
    "    roll_over_mode=True,\n",
    "    start_time=start_time,\n",
    "    end_time=end_time,\n",
    "    indicators=INDICATOR_LIST\n",
    ")\n",
    "\n",
    "print(\"\\n开始运行回测...\")\n",
    "engine.run_backtest()\n",
    "print(\"\\n回测运行完毕。\")\n",
    "\n",
    "# --- 3. 获取回测结果 ---\n",
    "results = engine.get_backtest_results()\n",
    "portfolio_snapshots = results[\"portfolio_snapshots\"]\n",
    "trade_history = results[\"trade_history\"]\n",
    "initial_capital_result = results[\"initial_capital\"]\n",
    "bars = results[\"all_bars\"]\n",
    "\n",
    "# --- 4. 结果分析与可视化 ---\n",
    "if portfolio_snapshots:\n",
    "    analyzer = ResultAnalyzer(portfolio_snapshots, trade_history, bars, initial_capital_result, INDICATOR_LIST)\n",
    "\n",
    "    analyzer.generate_report()\n",
    "    analyzer.plot_performance()\n",
    "    metrics = analyzer.calculate_all_metrics()\n",
    "    print(metrics)\n",
    "\n",
    "    analyzer.analyze_indicators()\n",
    "else:\n",
    "    print(\"\\n没有生成投资组合快照，无法进行结果分析。\")\n",
    "\n",
    "# --- 4. 结果分析与可视化 (待实现) ---\n",
    "# if portfolio_snapshots:\n",
    "#     analyzer = ResultAnalyzer(portfolio_snapshots, trade_history, initial_capital_result)\n",
    "#     metrics = analyzer.calculate_all_metrics()\n",
    "#     print(\"\\n--- 绩效指标 ---\")\n",
    "#     for key, value in metrics.items():\n",
    "#         print(f\"  {key}: {value:.4f}\")\n",
    "#\n",
    "#     print(\"\\n--- 绘制绩效图表 ---\")\n",
    "#     analyzer.plot_performance()\n",
    "# else:\n",
    "#     print(\"\\n没有生成投资组合快照，无法进行结果分析。\")\n",
    "\n"
   ]
  }
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