I Luk Kim
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126445ae0e
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Promote v9.5.36 PEAD champion + prune experiments to 3-tier set; ORB soft-day parity; TGTC infra
- v9.5.36 promoted: megacap reaction_min 0.02→0.03 on v9.5.20 cap=0.70 base; Full 13,244%/MDD 11.67%/Sharpe 3.579/OOT 304%; clean Pareto win
- Pruned 130 experiment configs → keep 3 (v9.4.5 max-return, v9.5.36 balanced/champion, v9.5.18 cap=0.55 conservative); rebuilt index
- PEAD engine probes: low_vol anomaly + breakout_52w (retained as falsification probes; not promoted)
- Risk analysis: 11.67% MDD confirmed structurally HYMC (6-day giveback, not controllable); per-name cap sweep on next_open_long/reaction_close falsified (0 MDD impact)
- ORB: port soft-day primary-trigger filter to live engine (6-gate parity with simulator)
- TGTC trader infrastructure + advisor service (new)
- ORB v46/v49 sweep configs, intraday scripts, docs
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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3 months ago |
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I Luk Kim
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e38c314a09
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Add ownership/risk-off sleeves, v17-v19 experiments, and web app restructure
New features:
- Ownership 13D/13G residual-cash sleeve with PIT calendar and quality filters
- Risk-off alpha sleeve (GLD/DBC rotation on crisis regime signals)
- Crisis relay target in parking: evaluates before defensive relay
- Bearish symbol allocation split (bearish_alloc_pct + sgov remainder)
- Alternative defensive ETF candidate (cash_parking_defensive_alt_symbol)
- Composite eval and engine ablation tools
- experiment and overfit CLI apps
New experiments:
- v17.x series (v17.1 champion SQS 78.4; v17.5–v17.129 exhausted)
- v18.x and v19.x families from v12.8 OOT defense branch
- v7.119 composed variants (idle alpha + ownership + risk-off sleeves)
- parking_only configs: bufb, jepq, merix, regime_tiered
- empty_strategy baseline config
Web app:
- Restructured into routers/services modules (experiments, leaderboard, runs, sqs, docs)
- Ownership sleeve and risk-off sleeve controls in backtest UI
- Frontend: ComposeStrategy page, tradeSleeves lib, idle decomposition display
Research tools:
- Ownership 13D/13G probe and PIT cache builder
- Dividend capture probe and cache builder
- Insider Form4 idle alpha probe
- Alternative ETF parking probe, put-spread overlay probe
- Wikimedia low-attention and peer-relative idle alpha probes
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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4 months ago |
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I Luk Kim
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2f4d9f61f7
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feat: implement Phase 4 -- event-driven backtester
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>
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5 months ago |