feat(strategy): finalize global rotation system with advanced risk controls

Summary of updates: 1. Core Logic (engine.py): Added 'score > 0' filtering to support automatic cash positions during market downturns. 2. Experimental Analysis: Added scripts/analyze_negative_scores.py, scripts/test_select_num.py, and scripts/ab_test_iterations.py. 3. Documentation: Created docs/strategy_evolution_report.md detailing the evolution from benchmark to the final 47% CAGR version. 4. Configuration: Finalized rotation.yaml with 11 core assets and optimal risk parameters.
2026-04-30 00:56:20 +08:00
parent e946dbe804
commit c1fbd2c7db
6 changed files with 504 additions and 14 deletions
--- a/scripts/test_select_num.py
+++ b/scripts/test_select_num.py
@@ -0,0 +1,112 @@
+"""
+持仓数量 (select_num) 敏感度测试
+测试 select_num 分别为 1, 2, 3, 4, 5 时的策略表现
+基于最终精选的 11 只标的池
+"""
+
+import sys
+import pandas as pd
+import numpy as np
+from pathlib import Path
+from datetime import datetime
+import matplotlib.pyplot as plt
+
+# 添加项目根目录
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from strategies.rotation.engine import RotationStrategy
+
+# ==================== 基础配置 ====================
+FINAL_POOL = {
+    "399006.SZ": {"name": "创业板指", "market": "A", "etf": "159915.SZ"},
+    "H30269.CSI": {"name": "中证红利低波", "market": "A", "etf": "512890.SH"},
+    "000015.SH": {"name": "上证红利", "market": "A", "etf": "510880.SH"},
+    "NDX": {"name": "纳指100", "market": "US", "etf": "513100.SH"},
+    "N225": {"name": "日经225", "market": "JP", "etf": "513520.SH"},
+    "GDAXI": {"name": "德国DAX", "market": "EU", "etf": "513030.SH"},
+    "HSI": {"name": "恒生指数", "market": "HK", "etf": "159920.SZ"},
+    "HSTECH.HK": {"name": "恒生科技", "market": "HK", "etf": "513130.SH"},
+    "AU.SHF": {"name": "黄金", "market": "COMMODITY", "etf": "518880.SH"},
+    "CL.NYM": {"name": "原油", "market": "COMMODITY", "etf": "160723.SZ"},
+    "931862.CSI": {"name": "30年国债", "market": "BOND", "etf": "511090.SH"}
+}
+
+BASE_CONFIG = {
+    "start_date": "2019-01-01",
+    "end_date": datetime.now().strftime('%Y-%m-%d'),
+    "code_list": FINAL_POOL,
+    "factor_type": "weighted_momentum",
+    "auto_day": False, # 使用当前设定的固定窗口
+    "n_days": 25,
+    "diversified": True,
+    "rebalance_days": 1,
+    "rebalance_threshold": 0.0,
+    "trade_cost": 0.001,
+    "premium_control": {"enabled": True, "default_threshold": 0.10},
+    "use_cache": True,
+    "ssh_tunnel": {"enabled": True, "host": "8.218.167.69", "port": 22, "username": "root", "key_path": "hk_ecs.pem", "local_port": 1080}
+}
+
+def run_sensitivity_test():
+    test_values = [1, 2, 3, 4, 5]
+    results = []
+    
+    for val in test_values:
+        print(f"\n测试 select_num = {val} ...")
+        cfg = BASE_CONFIG.copy()
+        cfg["select_num"] = val
+        
+        strategy = RotationStrategy(cfg)
+        try:
+            res_df = strategy.run()
+            
+            nav = res_df['轮动策略净值']
+            total_ret = nav.iloc[-1] - 1
+            days = (nav.index[-1] - nav.index[0]).days
+            cagr = (1 + total_ret)**(365.25/days) - 1
+            
+            daily_ret = res_df['轮动策略日收益率']
+            sharpe = daily_ret.mean() / daily_ret.std() * np.sqrt(252) if daily_ret.std() > 0 else 0
+            
+            peak = nav.cummax()
+            dd = (nav - peak) / peak
+            max_dd = dd.min()
+            
+            results.append({
+                "select_num": val,
+                "total_ret": total_ret,
+                "cagr": cagr,
+                "max_dd": max_dd,
+                "sharpe": sharpe,
+                "nav": nav
+            })
+        except Exception as e:
+            print(f"测试失败 (select_num={val}): {e}")
+
+    # ==================== 汇总报告 ====================
+    print(f"\n\n{'='*90}")
+    print(f"{'持仓数量 (select_num) 敏感度测试报告':^90}")
+    print(f"{'='*90}")
+    print(f"{'持仓数':<10} | {'累计收益':>12} | {'年化(CAGR)':>12} | {'最大回撤':>12} | {'夏普比率':>10}")
+    print(f"{'-'*90}")
+    
+    for r in results:
+        print(f"{r['select_num']:<10} | {r['total_ret']:>12.2%} | {r['cagr']:>12.2%} | {r['max_dd']:>12.2%} | {r['sharpe']:>10.2f}")
+    print(f"{'='*90}")
+
+    # ==================== 绘图 ====================
+    plt.figure(figsize=(14, 7))
+    for r in results:
+        plt.plot(r['nav'].index, r['nav'], label=f"select_num = {r['select_num']}")
+    
+    plt.yscale('log')
+    plt.title("持仓数量对净值的影响 (select_num 1-5)", fontsize=14)
+    plt.legend()
+    plt.grid(True, alpha=0.3)
+    
+    output_path = Path(__file__).parent.parent / "results" / "select_num_test.png"
+    plt.savefig(output_path)
+    print(f"\n对比图表已保存至: {output_path}")
+
+if __name__ == "__main__":
+    run_sensitivity_test()