3 Commits (main)

Author	SHA1	Message	Date
I Luk Kim	236148de2e	Remove momentum breakout sleeve (overfitting, valid -31%) and revert related code ... - Delete v7.360-v7.363 experiment configs (rotation/momentum tests) - Remove _schedule_momentum_breakout_candidates() from backtester run.py - Remove MomentumBreakoutConfig from domain.py - Delete momentum_calendar.py, momentum_screener.py, build_momentum_calendar.py - Delete data/momentum_calendar/ parquet data Valid period performance was -31.36% vs +152.4% baseline — sleeve is not viable without walk-forward validation. Abandoning for now. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	4 months ago
I Luk Kim	e38c314a09	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>	4 months ago
I Luk Kim	090bfa8e36	Add contrarian feature analysis + v15 scoring (v6new.174-188) ... Data analysis revealed OBV Q1 (distribution) has 56.4% WR vs Q5 51.2% — contrarian signal confirmed. Previous OBV bonus was applied in wrong direction. Corrected with v15 scoring models. Best result: v6new.185 (entropy + risk 0.058) CW 274.4% but SQS 72.2, still below v6new.122 (72.4). WFV/robustness offsets CW gains. v6new.122 confirmed as optimal under current SQS v4 formula. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>	5 months ago