feat: v_next3生产落地——板块ADX入板块上下文+行业牛杠杆接入position_advice

deploy/profile-scripts/strategy_lifecycle.py

@@ -1040,6 +1040,27 @@ def reassess_strategy(code, name, price, cost, shares, current_action,
 
     print(f"  分类: {stock_category} | {time_horizon} | {position_advice}")
 
+    # ── v_next3行业牛杠杆: 行业确认牛(行业ADX>25)时升一档仓位（2026-07-30落地）──
+    try:
+        _sec_adx = 0
+        try:
+            from strategy_lab import sector_ctx, prepare_sector_context
+            from datetime import timedelta as _td
+            _end = datetime.now().strftime('%Y-%m-%d')
+            _start = (datetime.now() - _td(days=200)).strftime('%Y-%m-%d')
+            prepare_sector_context(_start, _end)
+            _sc = sector_ctx(code, _end)
+            _sec_adx = _sc.get('adx') or 0
+        except Exception:
+            _sec_adx = 0
+        if _sec_adx > 25:
+            _upgrade = {"小仓快进快出": "中等仓位", "中等仓位": "重仓", "正常配置": "重仓"}
+            if position_advice in _upgrade:
+                print(f"  [行业牛杠杆] 行业ADX={_sec_adx:.0f}>25 → 仓位{position_advice}→{_upgrade[position_advice]}", flush=True)
+                position_advice = _upgrade[position_advice]
+    except Exception as _e:
+        print(f"  [行业牛杠杆] 评估异常(跳过): {_e}", flush=True)
+
     # ----- 短炒+强趋势检测：短炒分类但多周期多头时用移动止损代替弱支撑止损 -----
     is_short_term_strong_trend = False
     if stock_category == "短炒":

strategy_lab.py

@@ -552,17 +552,21 @@ def prepare_sector_context(start_date, end_date):
     try:
         # 1. 板块指数历史（全周期）
         try:
-            idx_rows = conn.execute("""
+            idx_rows = conn.execute(
-                SELECT sector, date, close, change_pct FROM sector_index_daily
+                "SELECT sector, date, close, change_pct, high, low FROM sector_index_daily "
-                WHERE date >= ? AND date <= ? ORDER BY sector, date
+                "WHERE date >= ? AND date <= ? ORDER BY sector, date",
-            """, (start_date, end_date)).fetchall()
+                (start_date, end_date)).fetchall()
         except sqlite3.OperationalError:
             idx_rows = []
         # 每板块计算 MA20 和斜率
         from collections import defaultdict
         by_sector = defaultdict(list)
-        for sec, d, close, chg in idx_rows:
+        sec_hl = defaultdict(list)
+        for row in idx_rows:
+            sec, d, close, chg = row[0], row[1], row[2], row[3]
             by_sector[sec].append((d, close, chg))
+            if len(row) >= 6:
+                sec_hl[sec].append((d, row[4], row[5]))
         for sec, series in by_sector.items():
             closes = [c for _, c, _ in series]
             for i, (d, close, chg) in enumerate(series):
@@ -574,8 +578,19 @@ def prepare_sector_context(start_date, end_date):
                         ma20_5 = sum(closes[i-24:i-4]) / 20
                         if ma20_5 > 0:
                             slope = round((ma20 - ma20_5) / ma20_5 * 100, 3)
+                _adx = None
+                _hl = sec_hl.get(sec, [])
+                if len(_hl) >= 20 and i >= 14:
+                    from backtest_framework import calc_trend_strength
+                    _hs = [x[1] for x in _hl]
+                    _ls = [x[2] for x in _hl]
+                    _cs = [c for _, c, _ in series]
+                    if len(_cs) == len(_hl):
+                        _av = calc_trend_strength(_hs, _ls, _cs, 14)
+                        if i < len(_av):
+                            _adx = _av[i]
                 _SECTOR_CTX.setdefault(d, {})[sec] = {
-                    'change': chg, 'above_ma20': above, 'slope': slope,
+                    'change': chg, 'above_ma20': above, 'slope': slope, 'adx': _adx,
                 }
         # 2. sector_snapshots 补充净流入和涨幅（近期，THS命名）
         snap_rows = conn.execute("""