feat: 普适指标重构——跨独立年份有效性(有效年占比×覆盖因子)+特例剔除检验(leave1),体现非特例宗旨

deploy/profile-scripts/regime_perf_by_period.py

@@ -57,7 +57,10 @@ def create_table(conn):
             sharpe_ratio REAL,
             profit_factor REAL,
             universality_months INTEGER,
+            universality_years INTEGER,
+            universality_valid_years INTEGER,
             universality_score REAL,
+            universality_leave1 REAL,
             updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
             PRIMARY KEY (strategy, market, regime, period_tag)
         )
@@ -160,24 +163,45 @@ def process_period(conn, market, period_tag):
                 cagr = round(((1 + ret / 100) ** (365 / span_days) - 1) * 100, 1)
             else:
                 cagr = None
-            # 普适：该温区 trades 的 entry_date 去重月份数 / 该温区总月份数（2026-08-16 修复：
-            #   原 server 端信号数÷3估算 → s2_panic 2255信号估算751月=100分,实际只2个月）
+            # 普适（2026-08-17 重构，老莫）：跨独立年份的有效性，而非覆盖广度
+            # 核心：策略不是靠某次历史特例（如某次大反弹）才成立，而是多个独立时段都有效
             _uniq_months = len({t.get("entry_date", "")[:7] for t in reg_trades if t.get("entry_date")})
-            _regime_months_all = {d[:7] for d, r in rmap.items() if r == reg}
-            _regime_total_months = len(_regime_months_all)
-            _univ_score = round(min(_uniq_months / max(_regime_total_months, 1) * 100, 100)) if _uniq_months else 0
+            _univ_score = _univ_years = _univ_valid = _univ_leave1 = 0
+            _ed_list = [t.get("entry_date", "")[:4] for t in reg_trades if t.get("entry_date")]
+            if len(_ed_list) >= 5:
+                from collections import defaultdict
+                _yr = defaultdict(list)
+                for _y, _t in zip(_ed_list, reg_trades):
+                    _yr[_y].append(_t.get("profit_pct", 0))
+                _yearly = {_y: {"n": len(_v), "wr": sum(1 for p in _v if p > 0) / len(_v) * 100,
+                                "avg": sum(_v) / len(_v)} for _y, _v in _yr.items()}
+                # 只统计有足够样本的年（>=5笔）
+                _stat_years = {_y: _d for _y, _d in _yearly.items() if _d["n"] >= 5}
+                if _stat_years:
+                    _univ_years = len(_stat_years)
+                    _univ_valid = sum(1 for _d in _stat_years.values() if _d["wr"] > 50)
+                    # 覆盖因子：>=3年给满覆盖分，<3年按比例
+                    _coverage = min(_univ_years / 3.0, 1.0)
+                    # 稳定性：有效年占比
+                    _stability = _univ_valid / _univ_years
+                    _univ_score = round(100 * _coverage * _stability)
+                    # 特例剔除：去掉最好一年的平均收益，剩余平均是否仍 > 0
+                    _avgs = sorted((_d["avg"] for _d in _stat_years.values()), reverse=True)
+                    if len(_avgs) >= 2:
+                        _univ_leave1 = round(sum(_avgs[1:]) / (len(_avgs) - 1), 2)
             conn.execute(
                 """INSERT OR REPLACE INTO strategy_regime_perf_by_period
                    (strategy, market, regime, period_tag, trades, win_rate, avg_pnl, avg_hold_days,
                     total_return_pct, cagr_pct, portfolio_max_dd_pct, capital_final,
-                    positions_taken, sharpe_ratio, profit_factor, universality_months, universality_score, updated_at)
-                   VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""",
+                    positions_taken, sharpe_ratio, profit_factor, universality_months, universality_years,
+                    universality_valid_years, universality_score, universality_leave1, updated_at)
+                   VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""",
                 (v, market, reg, period_tag, len(reg_trades),
                  extra.get("win_rate"), extra.get("avg_pnl"), extra.get("avg_hold_days"),
                  ret, cagr, sim.get("portfolio_max_dd_pct"),
                  sim.get("capital_final"), sim.get("positions_taken"),
                  extra.get("sharpe_ratio"), extra.get("profit_factor"),
-                 _uniq_months, _univ_score, now))
+                 _uniq_months, _univ_years, _univ_valid, _univ_score, _univ_leave1, now))
             written += 1
     return written