fix: 年化用回测区间年数(修复交易聚集爆炸)+资本基数统一913k

strategy_lab.py

@@ -680,7 +680,7 @@ def has_breakout_dna(bars, i, lookback=10):
     return False
 
 
-def run_backtest(strategy_version, start_date, end_date, capital=1000000, save=True, universe='all', period_tag='2y'):
+def run_backtest(strategy_version, start_date, end_date, capital=913000, save=True, universe='all', period_tag='2y'):
     strat = get_strategy(strategy_version)
     cfg = strat['config']
     entry_cfg, exit_cfg = cfg['entry'], cfg['exit']
@@ -1044,6 +1044,10 @@ def run_backtest(strategy_version, start_date, end_date, capital=1000000, save=T
 
     summary = calc_summary(trades, capital)
     if summary:
+        # 年化统一用回测区间年数（修复交易聚集导致年化爆炸）
+        _y0 = datetime.strptime(start_date, '%Y-%m-%d')
+        _y1 = datetime.strptime(end_date, '%Y-%m-%d')
+        _bt_years = max((_y1 - _y0).days / 365.0, 0.5)
         # 信念缩放（通用，2026-07-29验证全策略+7~16pp）：动量基因票默认×2.5
         boost_k = cfg.get('exit', {}).get('dna_boost', 2.5)
         for t in trades:
@@ -1054,6 +1058,11 @@ def run_backtest(strategy_version, start_date, end_date, capital=1000000, save=T
         summary['sizing_slots'] = slots
         # 全参与可行仓位（公平基线：单仓≥5万地板，消除上车运气）
         summary['portfolio_full'] = portfolio_sim_full(trades, capital)
+        # cagr 统一用回测区间年数覆盖（portfolio_sim里按交易跨度算的会爆炸）
+        _tr = summary['portfolio'].get('total_return_pct', 0) / 100
+        _tf = summary['portfolio_full'].get('total_return_pct', 0) / 100
+        summary['portfolio']['cagr_pct'] = round((((1 + _tr) ** (1 / _bt_years)) - 1) * 100, 1)
+        summary['portfolio_full']['cagr_pct'] = round((((1 + _tf) ** (1 / _bt_years)) - 1) * 100, 1)
     result = {
         'strategy': strat['version'],
         'strategy_name': strat['name'],