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2f4d9f61f7
Full backtesting engine that reads Parquet snapshots and simulates a swing-trading strategy with no look-ahead bias. ## New modules (libs/backtest/) - domain.py: All Pydantic v2 models (Candidate, PlannedOrder, FilledTrade, OpenPosition, DailyPortfolioState, MetricsBundle, BacktestConfig, etc.) - calendar.py: Thin wrappers over time_utils + reaction_date - manifests.py: Config load/deep-merge/validate, run-ID generation - metrics.py: 21 pure-function metrics (no pandas, stdlib statistics only) - selector.py: build_candidate(), rank_candidates() (score↓ ADV↓ symbol↑) - allocator.py: 7-gate run_entry_gates(), ATR stop, floor() shares - execution.py: simulate_entry/exit(), update_trailing_stop() (ratchet-up only) - splits.py: Walk-forward windows, year/regime split utilities - snapshot_store.py: Sync load() → asyncio.run(_async_load()), no look-ahead - artifacts.py: Full run-dir writer (Parquet, CSV, JSON) ## App modules (apps/backtester/) - run.py: BacktestRunner (exit-first→entry simulation, 25% kill switch) + CLI - replay.py: Double-run determinism checker ## Config files - configs/backtest/defaults.json: Base strategy defaults - configs/experiments/baseline_v1.json: First experiment manifest ## Tests: 142 new tests, all passing - 132 unit tests (no DB/HTTP required) - 8 integration tests (synthetic SnapshotStore) - 3 backtest determinism/replay tests Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
5 months ago | |
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| .. | ||
| manifest.json | 5 months ago | |
| train.parquet | 5 months ago | |