chore: backtest engine fee model, metrics, and strategy fixes

- main.py: add IBKR-style tiered fee schedule (fee_base + fee_per_share),
  PIT universe support, and open-to-close execution improvements
- metrics.py: add raw_summary helper for JSON-safe metric export
- Misc strategy fixes: deprecation warnings, NaN handling

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

metrics.py

@@ -52,6 +52,21 @@ def win_rate(returns: pd.Series) -> float:
     return (active > 0).sum() / len(active)
 
 
+def raw_summary(equity: pd.Series) -> dict:
+    """Return numeric metrics suitable for JSON serialization."""
+    returns = equity.pct_change().dropna()
+    return {
+        "totalReturn": float(total_return(equity)),
+        "annualizedReturn": float(annualized_return(equity)),
+        "annualizedVolatility": float(annualized_volatility(returns)),
+        "sharpeRatio": float(sharpe_ratio(returns)),
+        "sortinoRatio": float(sortino_ratio(returns)),
+        "maxDrawdown": float(max_drawdown(equity)),
+        "calmarRatio": float(calmar_ratio(equity)),
+        "winRate": float(win_rate(returns)),
+    }
+
+
 def summary(equity: pd.Series, name: str = "Strategy") -> dict:
     returns = equity.pct_change().dropna()
     metrics = {