[IamJasonBian]

Summary

• Backtesting suite: Full BTC DCA simulation engine with options hedging (protective puts, collars), drawdown strategies (cash reserve, trailing stop, adaptive sizing), and SPY/QQQ buy-and-hold benchmarks — generates a 31-page comparison PDF with charts, risk analysis, and limitations
• Parameter optimization: Grid search over stop_offset × buy_offset × coverage_threshold (75+ combos), rolling 21-day metrics, drift detection, and volatility regime classification. Strategy defaults updated to optimized values: stop=1.25%, buy=$0.50, coverage=25%, lot_size=200
• Drift metrics in state snapshot: Each run_once() cycle now computes rolling Sharpe, volatility, regime, and suggested params — uploaded to Netlify Blobs alongside the order book for dashboard consumption
• Order management improvements: Cancel-before-replace logic, Order entity extended with side/order_id/created_at, cancel_order_by_id with state verification, Slack oncall summaries
• Housekeeping: Replace emoji with text indicators for CI compatibility, add IWM to symbol map, add strategy docs

Test plan

• Run python -m trading_system.backtests.strategy_comparison_backtest — verify 31-page PDF generates with all sections
• Run pytest tests/ — verify all unit tests pass (order entities, state manager, momentum DCA, simulation, order replacement)
• Dry-run the trading system and verify drift_metrics appears in local state log JSON
• Verify strategy defaults match optimized values (stop=0.0125, buy=0.50, coverage=0.25)

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