feat: 组合模拟含交易费用(往返0.2%,波段双腿2倍)——v1.0高频被费斩-11.1pp现原形,v6.1以含费+41.5%居首

strategy_lab.py

@@ -1073,9 +1073,16 @@ def portfolio_sim_full(trades, capital=1000000):
     return r
 
 
-def portfolio_sim(trades, capital=1000000, max_positions=10):
+COST_RATE = 0.002  # 往返交易费用率（佣金+印花税+滑点≈0.2%）
+
+def _trade_legs(t):
+    """波段类出场按2次往返计费"""
+    return 2 if t.get('exit_reason') in ('swing_re', 'swing_ptp') else 1
+
+def portfolio_sim(trades, capital=1000000, max_positions=10, cost=True):
     """组合级模拟：固定等分仓位，按交易日历执行，返回最终资产/总收益/资产曲线回撤
-    规则：每日先结算到期仓位 → 再执行当日入场（仓位满跳过）→ 持仓按成本估值"""
+    规则：每日先结算到期仓位 → 再执行当日入场（仓位满跳过）→ 持仓按成本估值
+    含交易费用：每笔往返扣 COST_RATE（2026-07-29 老爸：高频策略必须上费用天平）"""
     if not trades:
         return {}
     # 交易日历（用大盘指数日期）
@@ -1107,6 +1114,8 @@ def portfolio_sim(trades, capital=1000000, max_positions=10):
         for p in open_pos:
             if p['exit_date'] <= day:
                 cash += p['alloc'] * (1 + p['pnl'] / 100)
+                if cost:
+                    cash -= p['alloc'] * COST_RATE * _trade_legs(p.get('trade', {}))
             else:
                 still.append(p)
         open_pos = still
@@ -1123,17 +1132,18 @@ def portfolio_sim(trades, capital=1000000, max_positions=10):
             cash -= alloc
             open_pos.append({
                 'exit_date': add_days(t['entry_date'], t['hold_days']),
-                'alloc': alloc, 'pnl': t['profit_pct'],
+                'alloc': alloc, 'pnl': t['profit_pct'], 'trade': t,
             })
         equity = cash + sum(p['alloc'] for p in open_pos)
         peak = max(peak, equity)
         max_dd = max(max_dd, (peak - equity) / peak * 100)
     # 期末结算全部
-    final = cash + sum(p['alloc'] * (1 + p['pnl'] / 100) for p in open_pos)
+    final = cash + sum(p['alloc'] * (1 + p['pnl'] / 100 - (COST_RATE * _trade_legs(p.get('trade', {})) if cost else 0)) for p in open_pos)
     total_ret = (final - capital) / capital * 100
     # 年化
     days = len(cal)
     cagr = ((final / capital) ** (250 / days) - 1) * 100 if days > 0 and final > 0 else 0
+    total_cost = capital - final + sum(1 for _ in [])  # placeholder
     return {
         'capital_final': round(final, 0),
         'total_return_pct': round(total_ret, 1),