etf/scripts/ab_test_iterations.py

"""
策略迭代 A/B 对比实验脚本
量化三个维度的改进贡献度：
1. 标的池: 原始全市场池 vs. 精选11只核心池
2. 评分公式: 简单斜率(slope_r2) vs. 年化收益率*R2 (weighted_momentum)
3. 观察窗口: 固定25日窗口 vs. 动态ATR窗口 (20-60天)
"""

import sys
import pandas as pd
import numpy as np
from pathlib import Path
from datetime import datetime

# 添加项目根目录
sys.path.insert(0, str(Path(__file__).parent.parent))

from strategies.rotation.engine import RotationStrategy
import matplotlib.pyplot as plt

# ==================== 标的池定义 ====================
ORIGINAL_POOL = {
    "000300.SH": {"name": "沪深300", "market": "A", "etf": "510300.SH"},
    "000905.SH": {"name": "中证500", "market": "A", "etf": "510500.SH"},
    "000852.SH": {"name": "中证1000", "market": "A", "etf": "512100.SH"},
    "399006.SZ": {"name": "创业板指", "market": "A", "etf": "159915.SZ"},
    "000015.SH": {"name": "上证红利", "market": "A", "etf": "510880.SH"},
    "399986.SZ": {"name": "中证银行", "market": "A", "etf": "516310.SH"},
    "399997.SZ": {"name": "中证白酒", "market": "A", "etf": "512690.SH"},
    "399989.SZ": {"name": "中证医疗", "market": "A", "etf": "512170.SH"},
    "399395.SZ": {"name": "国证有色", "market": "COMMODITY", "etf": "159880.SZ"},
    "399998.SZ": {"name": "中证煤炭", "market": "A", "etf": "515220.SH"},
    "399967.SZ": {"name": "中证军工", "market": "A", "etf": "512660.SH"},
    "HSTECH.HK": {"name": "恒生科技", "market": "HK", "etf": "513180.SH"},
    "NDX": {"name": "纳指100", "market": "US", "etf": "513100.SH"},
    "AU.SHF": {"name": "黄金", "market": "COMMODITY", "etf": "518880.SH"}
}

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"}
}

# ==================== 实验配置 ====================
ITERATIONS = [
    {
        "label": "1. 原始基准 (原始池+简单评分+固定窗口)",
        "config": {
            "code_list": ORIGINAL_POOL,
            "factor_type": "slope_r2",
            "auto_day": False,
            "n_days": 25,
            "diversified": False
        }
    },
    {
        "label": "2. 标的池优化 (精选池+简单评分+固定窗口)",
        "config": {
            "code_list": FINAL_POOL,
            "factor_type": "slope_r2",
            "auto_day": False,
            "n_days": 25,
            "diversified": True # 开启跨大类分散
        }
    },
    {
        "label": "3. 评分公式优化 (精选池+加权评分+固定窗口)",
        "config": {
            "code_list": FINAL_POOL,
            "factor_type": "weighted_momentum",
            "auto_day": False,
            "n_days": 25,
            "diversified": True
        }
    },
    {
        "label": "4. 终极版本 (精选池+加权评分+动态窗口)",
        "config": {
            "code_list": FINAL_POOL,
            "factor_type": "weighted_momentum",
            "auto_day": True,
            "n_days": 25, # 提供默认窗口作为 fallback
            "min_days": 20,
            "max_days": 60,
            "diversified": True
        }
    }
]

COMMON_CONFIG = {
    "start_date": "2019-01-01",
    "end_date": datetime.now().strftime('%Y-%m-%d'),
    "select_num": 3,
    "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_experiment():
    results = []
    
    for i, item in enumerate(ITERATIONS):
        print(f"\n{'='*80}")
        print(f"运行实验 {item['label']}")
        print(f"{'='*80}")
        
        cfg = COMMON_CONFIG.copy()
        cfg.update(item['config'])
        
        strategy = RotationStrategy(cfg)
        try:
            res_df = strategy.run()
            
            # 计算指标
            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({
                "label": item['label'],
                "total_ret": total_ret,
                "cagr": cagr,
                "max_dd": max_dd,
                "sharpe": sharpe,
                "nav": nav
            })
            print(f"完成: CAGR={cagr:.2%}, MaxDD={max_dd:.2%}, Sharpe={sharpe:.2f}")
        except Exception as e:
            print(f"实验失败: {e}")
            import traceback
            traceback.print_exc()

    # ==================== 汇总报告 ====================
    print(f"\n\n{'='*100}")
    print(f"{'策略迭代对比报告':^100}")
    print(f"{'='*100}")
    print(f"{'版本':<40} | {'累计收益':>10} | {'年化(CAGR)':>10} | {'最大回撤':>10} | {'夏普比率':>8} | {'贡献增量':>10}")
    print(f"{'-'*100}")
    
    prev_cagr = 0
    for i, r in enumerate(results):
        delta = f"+{(r['cagr'] - prev_cagr)*100:>.2f}%" if i > 0 else "-"
        print(f"{r['label']:<40} | {r['total_ret']:>10.2%} | {r['cagr']:>10.2%} | {r['max_dd']:>10.2%} | {r['sharpe']:>8.2f} | {delta:>10}")
        prev_cagr = r['cagr']
    print(f"{'='*100}")

    # ==================== 绘图 ====================
    plt.figure(figsize=(15, 8))
    for r in results:
        plt.plot(r['nav'].index, r['nav'], label=r['label'], linewidth=1.5)
    
    plt.yscale('log')
    plt.title("策略迭代 A/B 对比 - 净值曲线 (对数坐标)", fontsize=14)
    plt.legend()
    plt.grid(True, alpha=0.3)
    
    output_path = Path(__file__).parent.parent / "results" / "ab_test_iterations.png"
    plt.savefig(output_path)
    print(f"\n对比图表已保存至: {output_path}")

if __name__ == "__main__":
    run_experiment()