181 lines
6.5 KiB
Python
181 lines
6.5 KiB
Python
#!/usr/bin/env python3
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"""
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止损机制回测验证 — 无止损 vs 8%止损 vs 5%止损 vs 10%止损
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======================================================
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在 MA20 策略基础上叠加止损线，对比收益/回撤/胜率。
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用法：python3 stock_stop_loss_validate.py
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"""
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import sys, json, urllib.request
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from datetime import datetime, timedelta
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from pathlib import Path
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import numpy as np
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import pandas as pd
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sys.path.insert(0, str(Path(__file__).parent))
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from stock_ma20_backtest import get_data
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OUTPUT = Path.home() / ".hermes" / "stock_backtest"
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# 测试股票（白酒下跌趋势最能体现止损价值）
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TEST_STOCKS = [
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("000858", "五粮液", "白酒"),
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("600519", "贵州茅台", "白酒"),
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("000568", "泸州老窖", "白酒"),
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("300750", "宁德时代", "新能源"),
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("002415", "海康威视", "科技"),
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]
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def backtest_with_stoploss(df, stop_loss_pct=0.0, initial_cash=100000):
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"""MA20 + 可选止损回测
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stop_loss_pct: 0=无止损，0.08=8%止损
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"""
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if df.empty or len(df) < 30:
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return None
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d = df.copy()
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d["ma20"] = d["close"].rolling(window=20).mean()
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d["prev_close"] = d["close"].shift(1)
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d["prev_ma20"] = d["ma20"].shift(1)
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d["golden_cross"] = (d["prev_close"] < d["prev_ma20"]) & (d["close"] > d["ma20"])
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d["death_cross"] = (d["prev_close"] > d["prev_ma20"]) & (d["close"] < d["ma20"])
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cash = initial_cash
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position = 0
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in_position = False
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buy_price = 0
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buy_date = None
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trades = []
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equity = []
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stop_count = 0
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for i, row in d.iterrows():
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if pd.isna(row["ma20"]):
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continue
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price = row["close"]
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date_str = row["date"].strftime("%Y-%m-%d")
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# 止损检查（持仓时）
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if in_position and stop_loss_pct > 0:
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dd = (price - buy_price) / buy_price * 100
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if dd <= -stop_loss_pct * 100:
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cash += position * price
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trades.append({"type": "STOP_LOSS", "date": date_str, "price": price,
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"shares": position, "profit_pct": dd, "reason": f"止损{dd:.1f}%"})
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position = 0
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in_position = False
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buy_price = 0
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stop_count += 1
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equity.append({"date": date_str, "value": cash})
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continue
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# 金叉买入
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if row["golden_cross"] and not in_position:
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shares = int(cash / price)
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if shares > 0:
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cash -= shares * price
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position = shares
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buy_price = price
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in_position = True
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trades.append({"type": "BUY", "date": date_str, "price": price, "shares": shares})
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# 死叉卖出
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elif row["death_cross"] and in_position:
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cash += position * price
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profit_pct = (price - buy_price) / buy_price * 100
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trades.append({"type": "SELL", "date": date_str, "price": price,
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"shares": position, "profit_pct": profit_pct})
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position = 0
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in_position = False
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buy_price = 0
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equity.append({"date": date_str, "value": cash + position * price})
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final_price = d.iloc[-1]["close"]
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final_value = cash + position * final_price
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# 买入持有
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bph = d.iloc[19]["close"] if len(d) > 19 else d.iloc[0]["close"]
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hold_return = (final_price - bph) / bph * 100 if bph else 0
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strat_return = (final_value - initial_cash) / initial_cash * 100
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alpha = strat_return - hold_return
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# 最大回撤
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eq = [e["value"] for e in equity] or [initial_cash]
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peak = eq[0]
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max_dd = 0
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for v in eq:
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peak = max(peak, v)
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max_dd = max(max_dd, (peak - v) / peak * 100)
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# 胜率（含止损单）
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exits = [t for t in trades if t["type"] in ("SELL", "STOP_LOSS")]
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wins = [t for t in exits if t.get("profit_pct", 0) > 0]
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win_rate = len(wins) / len(exits) * 100 if exits else 0
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return {
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"strat_return": strat_return, "hold_return": hold_return,
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"alpha": alpha, "max_dd": max_dd,
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"n_trades": len(exits), "win_rate": win_rate,
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"stop_count": stop_count, "final_value": final_value,
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}
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def main():
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stop_levels = [0.0, 0.05, 0.08, 0.10]
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print("=" * 76)
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print("止损机制回测验证 — MA20 + 止损线")
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print("=" * 76)
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all_results = []
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for code, name, industry in TEST_STOCKS:
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df = get_data(code, 500)
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if df.empty:
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print(f" ⚠️ {name} 数据获取失败")
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continue
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print(f"\n📊 {name}({code}) [{industry}]")
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print(f" {'止损线':<8} {'策略收益':>10} {'α':>8} {'最大回撤':>10} {'胜率':>7} {'止损次':>6}")
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print(f" {'-'*52}")
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stock_results = {}
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for sl in stop_levels:
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r = backtest_with_stoploss(df, stop_loss_pct=sl)
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if not r:
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continue
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stock_results[f"{sl:.0%}"] = r
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label = f"{sl:.0%}" if sl > 0 else "无止损"
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print(f" {label:<8} {r['strat_return']:>+9.1f}% {r['alpha']:>+7.1f}% "
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f"{r['max_dd']:>9.1f}% {r['win_rate']:>6.1f}% {r['stop_count']:>6}")
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all_results.append({"code": code, "name": name, "industry": industry, "results": stock_results})
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# 汇总：8%止损 vs 无止损
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print("\n" + "=" * 76)
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print("📈 汇总（8%止损 vs 无止损）")
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print("=" * 76)
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alphas_none, alphas_8, dd_none, dd_8 = [], [], [], []
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for r in all_results:
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if "0%" in r["results"] and "8%" in r["results"]:
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alphas_none.append(r["results"]["0%"]["alpha"])
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alphas_8.append(r["results"]["8%"]["alpha"])
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dd_none.append(r["results"]["0%"]["max_dd"])
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dd_8.append(r["results"]["8%"]["max_dd"])
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if alphas_none:
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print(f" 平均 α: 无止损 {np.mean(alphas_none):+.2f}% → 8%止损 {np.mean(alphas_8):+.2f}% "
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f"(差 {np.mean(alphas_8)-np.mean(alphas_none):+.2f}%)")
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print(f" 平均回撤: 无止损 {np.mean(dd_none):.2f}% → 8%止损 {np.mean(dd_8):.2f}% "
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f"(差 {np.mean(dd_8)-np.mean(dd_none):+.2f}%)")
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print(f"\n 结论: {'✅ 8%止损有效（α↑或回撤↓）' if np.mean(dd_8) < np.mean(dd_none) else '⚠️ 止损收益影响需权衡'}")
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out = OUTPUT / "stoploss_validation.json"
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with open(out, "w", encoding="utf-8") as f:
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json.dump({"generated": datetime.now().strftime("%Y-%m-%d %H:%M"),
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"results": all_results}, f, ensure_ascii=False, indent=2, default=str)
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print(f"\n📁 已保存: {out}")
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if __name__ == "__main__":
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main()
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