cfdaily
222 lines
7.0 KiB
Python
222 lines
7.0 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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SingleStockStopLossStrategy 回测执行脚本
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集成关羽风控模块（单票止损），调用远程 API 执行回测
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Author: 关羽 云长
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Date: 2026-03-31
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Description: 对集成了单票止损的进阶多因子策略执行回测
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"""
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import sys
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import os
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import json
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import requests
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from datetime import datetime
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from typing import Dict, List, Optional
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# 配置 API 地址
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API_BASE_URL = "http://192.168.2.154:8088"
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def test_api_connection() -> bool:
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"""测试 API 连接"""
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print("=" * 60)
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print("1. 测试 API 连接")
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print("=" * 60)
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try:
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url = f"{API_BASE_URL}/ping"
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response = requests.get(url, timeout=10)
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print(f"✅ API 连接成功: {response.status_code}")
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print(f" 响应: {response.text[:200]}")
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return True
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except Exception as e:
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print(f"❌ API 连接失败: {e}")
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# 尝试根路径
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try:
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url = f"{API_BASE_URL}/"
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response = requests.get(url, timeout=10)
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print(f"根路径访问成功: {response.status_code}")
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print(f"响应: {response.text[:200]}")
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return True
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except Exception as e2:
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print(f"根路径访问也失败: {e2}")
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return False
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def get_backtest_config() -> Dict:
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"""获取回测配置"""
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config = {
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"strategy_name": "SingleStockStopLossStrategy",
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"description": "进阶多因子动态加权 + 关羽单票止损风控",
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"start_date": "2018-01-01",
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"end_date": "2026-03-31",
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"initial_capital": 1000000,
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"strategy_module": "factors-dynamic-weight-timing-20260327.main_strategy_single_file",
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"strategy_class": "MultiFactorDynamicStrategy",
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"parameters": {
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"rebalance_freq": "M",
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"holding_size": 50,
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"top_select": 0.1,
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"dynamic_weight": True,
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"ic_window": 12,
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"market_timing": True,
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"min_position": 0.3,
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"max_position": 1.0,
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"max_sector_pct": 0.20
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},
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"risk_control": {
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"enabled": True,
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"single_stock_stop_loss": 0.15,
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"portfolio_drawdown_control": True,
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"black_swan_filter": True
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},
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"data_source": "remote_api"
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}
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return config
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def run_backtest(config: Dict) -> Optional[Dict]:
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"""执行回测"""
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print("\n" + "=" * 60)
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print("2. 提交回测任务")
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print("=" * 60)
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try:
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url = f"{API_BASE_URL}/api/backtest/run"
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response = requests.post(url, json=config, timeout=30)
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data = response.json()
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if response.status_code == 200 and data.get("status") == "ok":
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print(f"✅ 回测任务提交成功")
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print(f" 任务ID: {data.get('task_id')}")
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return data
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else:
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print(f"❌ 回测提交失败: {data}")
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return None
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except Exception as e:
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print(f"❌ 回测提交异常: {e}")
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return None
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def poll_backtest_result(task_id: str) -> Optional[Dict]:
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"""轮询回测结果"""
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print("\n" + "=" * 60)
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print("3. 等待回测完成")
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print("=" * 60)
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import time
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max_wait = 3600 # 1小时超时
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wait_step = 10 # 每10秒轮询一次
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for i in range(0, max_wait, wait_step):
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try:
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url = f"{API_BASE_URL}/api/backtest/status/{task_id}"
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response = requests.get(url, timeout=10)
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data = response.json()
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status = data.get("status")
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if status == "completed":
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print(f"✅ 回测完成!")
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return data
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elif status == "running":
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progress = data.get("progress", 0)
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print(f" 回测进行中... 进度: {progress:.1%} ({i}/{max_wait}s)")
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elif status == "error":
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print(f"❌ 回测执行出错: {data.get('error')}")
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return None
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else:
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print(f" 状态: {status} ({i}/{max_wait}s)")
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except Exception as e:
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print(f" 轮询异常: {e} ({i}/{max_wait}s)")
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time.sleep(wait_step)
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print(f"❌ 回测超时")
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return None
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def print_backtest_result(result: Dict):
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"""打印回测结果"""
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print("\n" + "=" * 60)
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print("4. 回测结果")
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print("=" * 60)
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metrics = result.get("metrics", {})
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print(f"\n📊 回测基本信息:")
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print(f" 策略名称: {result.get('strategy_name')}")
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print(f" 回测区间: {result.get('start_date')} ~ {result.get('end_date')}")
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print(f" 初始资金: {result.get('initial_capital'):,.0f}")
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print(f"\n📈 绩效指标:")
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if "total_return" in metrics:
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print(f" 总收益率: {metrics['total_return']:.2%}")
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if "annual_return" in metrics:
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print(f" 年化收益率: {metrics['annual_return']:.2%}")
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if "max_drawdown" in metrics:
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print(f" 最大回撤: {metrics['max_drawdown']:.2%}")
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if "sharpe_ratio" in metrics:
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print(f" 夏普比率: {metrics['sharpe_ratio']:.2f}")
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if "calmar_ratio" in metrics:
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print(f" 卡玛比率: {metrics['calmar_ratio']:.2f}")
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if "win_rate" in metrics:
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print(f" 胜率: {metrics['win_rate']:.2%}")
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if "profit_loss_ratio" in metrics:
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print(f" 盈亏比: {metrics['profit_loss_ratio']:.2f}")
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print(f"\n⚠️ 风控统计:")
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if "stop_loss_count" in metrics:
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print(f" 触发止损次数: {metrics['stop_loss_count']}")
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if "portfolio_rebalance_count" in metrics:
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print(f" 组合降仓次数: {metrics['portfolio_rebalance_count']}")
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if "filtered_stocks_count" in metrics:
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print(f" 黑天鹅过滤数量: {metrics['filtered_stocks_count']}")
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print("\n" + "=" * 60)
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# 保存结果到文件
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result_file = os.path.join(
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os.path.dirname(__file__),
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f"backtest_result_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
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)
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with open(result_file, 'w', encoding='utf-8') as f:
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json.dump(result, f, indent=2, ensure_ascii=False)
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print(f"\n💾 完整结果已保存到: {result_file}")
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def main():
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"""主函数"""
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print("\n")
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print("=" * 60)
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print("SingleStockStopLossStrategy 回测")
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print("进阶多因子动态加权 + 关羽单票止损风控")
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print("=" * 60)
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# 1. 测试 API 连接
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if not test_api_connection():
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print("\n❌ API 连接失败，请检查服务是否正常运行")
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sys.exit(1)
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# 2. 获取回测配置并提交
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config = get_backtest_config()
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submit_result = run_backtest(config)
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if not submit_result:
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sys.exit(1)
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task_id = submit_result.get("task_id")
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if not task_id:
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print("❌ 没有获取到任务ID")
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sys.exit(1)
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# 3. 等待回测完成
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result = poll_backtest_result(task_id)
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if not result:
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sys.exit(1)
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# 4. 打印结果
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print_backtest_result(result)
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print("\n✅ 回测执行完成!")
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if __name__ == "__main__":
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main()
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