fix: 普适指标真实化——trades月份去重/温区总月份(原信号÷3估算使s2_panic虚高100分)

deploy/profile-scripts/regime_perf_by_period.py

@@ -56,6 +56,8 @@ def create_table(conn):
             positions_taken INTEGER,
             sharpe_ratio REAL,
             profit_factor REAL,
+            universality_months INTEGER,
+            universality_score REAL,
             updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
             PRIMARY KEY (strategy, market, regime, period_tag)
         )
@@ -158,17 +160,24 @@ 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）
+            _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
             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, updated_at)
-                   VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)""",
+                    positions_taken, sharpe_ratio, profit_factor, universality_months, universality_score, 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"), now))
+                 extra.get("sharpe_ratio"), extra.get("profit_factor"),
+                 _uniq_months, _univ_score, now))
             written += 1
     return written
 

server.py

@@ -60,7 +60,8 @@ def _compute_regime_winrates_cached(pt, _approx_univ):
         for _r in _c.execute(
             "SELECT 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 FROM strategy_regime_perf_by_period "
+            "positions_taken, sharpe_ratio, profit_factor, universality_months, universality_score "
+            "FROM strategy_regime_perf_by_period "
             "WHERE period_tag=? ORDER BY strategy, market, regime",
             (_pt_use,)).fetchall():
             _ver, _mkt, _reg = _r[0], _r[1], _r[2]
@@ -71,6 +72,8 @@ def _compute_regime_winrates_cached(pt, _approx_univ):
             _pt_v = _r[12]
             _sh_v = _r[13]
             _pf_v = _r[14]
+            _umon = _r[15]
+            _uscore = _r[16]
             _regime_winrates.setdefault(_ver, {})[_reg] = {
                 "trades": _r[4], "win_rate": _r[5], "avg_pnl": _r[6],
                 "avg_hold_days": _r[7],
@@ -83,7 +86,7 @@ def _compute_regime_winrates_cached(pt, _approx_univ):
                               "portfolio_max_dd_pct": _dd_v, "capital_final": _cf_v,
                               "positions_taken": _pt_v, "sharpe_ratio": _sh_v,
                               "profit_factor": _pf_v},
-                "universality": _approx_univ(_ver, _reg, _r[4]),
+                "universality": _approx_univ(_ver, _reg, _r[4], _umon, _uscore),
             }
         _c.close()
     except Exception:
@@ -625,8 +628,11 @@ def get_tracking():
 @app.route("/api/research/strategies")
 def api_research_strategies():
     """策略版本列表（含回测结果摘要，支持 period_tag 区间过滤）"""
-    def _approx_regime_universality(strategy, regime, trades):
-        """温区级普适近似：温区内信号月份≈trades/温区月均笔数，温区总月份占比（避免逐笔遍历性能问题）"""
+    def _approx_regime_universality(strategy, regime, trades, umon=None, uscore=None):
+        """温区级普适：优先用预计算真实值（trades entry_date 去重月份/温区总月份），
+        缺失时退回旧近似（信号数÷3估算，2026-08-16 修复——原估算对集中信号虚高）"""
+        if umon is not None and uscore is not None:
+            return {"months": umon, "score": uscore, "regime_total_months": 0}
         try:
             import sqlite3 as _sq6
             _c6 = _sq6.connect(str(DATA_DIR / "mofin.db"), timeout=10)