feat: backtesting engine — historical replay with shared strategies

backtester/config.py

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+"""Backtest configuration."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import datetime
+
+
+@dataclass
+class BacktestConfig:
+    """Configuration for a single backtest run.
+
+    Attributes
+    ----------
+    start_date:
+        Inclusive start of the replay window.
+    end_date:
+        Inclusive end of the replay window.
+    initial_capital:
+        Starting cash balance in USD.
+    commission_per_trade:
+        Fixed commission charged per order (Alpaca is commission-free,
+        so the default is 0.0).
+    slippage_pct:
+        Simulated slippage as a fraction of price (0.001 = 0.1%).
+    strategy_weights:
+        Mapping of strategy name to weight.  If empty, strategies
+        receive equal weight (0.333...).
+    max_position_pct:
+        Maximum fraction of equity per position (default 5%).
+    signal_threshold:
+        Minimum combined signal strength to trigger a trade (default 0.3).
+    """
+
+    start_date: datetime
+    end_date: datetime
+    initial_capital: float = 100_000.0
+    commission_per_trade: float = 0.0
+    slippage_pct: float = 0.001
+    strategy_weights: dict[str, float] = field(default_factory=dict)
+    max_position_pct: float = 0.05
+    signal_threshold: float = 0.3