7 Commits (08e41831bc961c4b6a77ba91168ae7b9440d7482)

Author SHA1 Message Date
I Luk Kim 08e41831bc Promote ORB Gainers V46: PEAD prior-event signal (D-7 lookback, w=0.12)
V24 → V46 via PEAD (Post-Earnings Announcement Drift) signal. Stocks with
earnings_release or guidance_update in prior 7 calendar days show +14.5pp
win rate improvement and +0.348R advantage on ORB breakouts.

Phase 1 diagnostic (291 V24 200d trades):
  Pearson=+0.135, Δ=+0.348R, WR gap=+14.5pp — all gates pass.

Phase 2 validation (w=0.12, Pareto-optimal from sweep):
  200d: V46 +114.60% / -11.83% / 3.21  vs  V24 +94.78% / -11.29% / 2.83
  400d: V46 +173.78% / -14.11% / 2.60  vs  V24 +162.1% / -13.70% / 2.471

Code changes:
- libs/intraday/domain.py: add prior_event_lookback_days: int = 0 param
- libs/intraday/orb_simulator.py: fix bug — weight_event_catalyst now wired
  for gainers_leader engine (was restricted to stocks_in_play_dual_regime only)
- apps/intraday_bt/run.py: _prefetch_prior_event_features_db() helper +
  DB routing in both catalyst trigger blocks when prior_event_lookback_days>0

V24 → status: superseded. V46 → status: live_champion.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 16f49411cb Add V34-V44 ORB diagnostic scripts; wire obv_slope_5 + min_obv_slope_20d infra
Signal axes tested (V34-V44, all failed G2 ≥ 0.30R gate):
- V34 obv_slope_5 (5d): G2=0.083R (null)
- V35 obv_slope composite (5d+20d): regime artifact (200d +18pp, 400d -12pp)
- V36 RSI-14: G2=0.148R, G5a=0.742 (redundant with OBV)
- V37 BB %B / BB width: G2=0.186R
- V38 dollar_vol_trend / sleep_streak / prior_day / vol_trend: all fail G2
- V39 premarket acceleration + hold ratio: G2=0.013R (null)
- V40 prior-day market breadth: G2=0.008R (null)
- V41 min_obv_slope_20d=0.0 hard filter: -15pp (OBV as gate too aggressive)
- V42 52w-high proximity + range position: G2=0.200R (best near-miss, fails)
- V43 30-min ORB window: -14.79% (catastrophic)
- V44 trailing multiplier sweep 0.6-1.0: 0.80 confirmed global optimum

Infrastructure added (backward-compatible, V24 parity preserved):
- features.py: obv_slope_5 enrichment key
- domain.py: weight_obv_slope_5=0.0, min_obv_slope_20d=None
- orb_simulator.py: 5 wiring sites for obv_slope_5; min_obv_slope_20d gate

V24 remains live champion. 20 signal axes exhausted.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 557d54921a V31 gap-zscore signal test: FAILED on both hard gate and negative weight
V31 research findings (2026-04-22):
- Hard gate (max_gap_zscore_20d=1.0): 45.2% vs V24 95.3% — catastrophically bad.
  All three terciles are profitable; hard rejection removes positive-EV trades.
- Negative weight (weight_gap_zscore=-0.05): 90.6% DD-12.33% Sh=2.649.
  Signal too weak (G2 failed at 0.181R < 0.30R threshold). G2 ≥ 0.30R
  validated as reliable promotion gate: OBV-slope (G2=0.394R) passed; all
  signals below 0.30R failed in backtest.

All 7 signal axes exhausted — V24 is the peak for current feature library.
domain.py: add max_gap_zscore_20d param (no-op at None default)
orb_simulator.py: add gainers_leader hard-gate (no-op at None default)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 4b8a157a67 Promote V24 ORB Gainers: add OBV-slope(20d) accumulation quality weight
Phase 1 diagnostic (diag_orb_quality_features.py) on V23 200d trade set found
obv_slope_20 passes all edge gates: Pearson=+0.2349 with r_multiple, top-tercile
WR 75% vs bottom 59.4% (+15.6pp), avg_R gap +0.394R. Hurst_60 and OU-θ_60 failed.

Weight sweep: 0.05 is Pareto-dominant (0.10/0.15 blow DD).

200d (same window): V24 +94.8% DD-11.3% Sharpe 2.83 vs V23 +85.0% DD-11.6% Sharpe 2.66
400d (same window): V24 +162.1% DD-13.7% Sharpe 2.47 vs V23 +149.4% DD-13.7% Sharpe 2.36
V24 Pareto-dominates V23 on both windows. V23 marked superseded.

Code changes:
- libs/intraday/features.py: add compute_obv_slope_approx() + enrich_daily_bars field
- libs/intraday/domain.py: add weight_obv_slope field to ORBStrategyParams
- libs/intraday/orb_simulator.py: wire obv_slope_20 read/store/score in gainers_leader branch
- configs: orb_gainers_v24_quality_overlay.yaml (new champion, live_readiness: experimental)
- configs: orb_gainers_v23.yaml status → superseded

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 9e622c6614 Investigate compound mode: V23 is absolute champion in all modes
- V23 pure compound (live-equivalent): 200d +148.13% DD-14.23%, 400d +209.41% DD-17.35%
- Hybrid V2 compound tested: 200d +175.41% looks promising but 400d +181.71% DD-23.72%
  loses to V23 by -27.7pp return AND -6.4pp worse DD → rejected
- Safe v9 compound 400d: +128.49% DD-14.43% — better DD but -81pp return vs V23 → rejected
- V23 tight governor compound 400d: +192.54% DD-17.32% — marginal gain, not worth config
- Live paper trader uses compound mode (engine.py:1816 session_equity = initial_equity + P&L)
- All improvement axes exhausted; V23 daily_reset declared TERMINAL

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim d7bfda039b Add expanded ORB simulator features and metrics
- orb_simulator.py: min_abs_gap_pct filter, premarket dollar vol filter,
  rolling_loss circuit breaker, drawdown_governor, streak_sizing,
  trailing_tighten_at_r, allow_doji/red_to_green breakout, abs_gap scoring
  for gainers_leader, ORBSimulationState, run_orb_simulation_with_state API
- metrics.py: loss_containment_score and related metrics
- features.py: enrich_daily_bars with gap_zscore, ATR ratio, range compression
- domain.py: extended ORBStrategyParams with new fields
- cache.py: DailyBarCache with merged parquet storage and coverage metadata
- simulator.py: base simulator updates for new entry/exit mechanics
- configs/intraday: updated orb_gainers_v23.yaml with canonical params
- Added BLD to midlarge symbol snapshot

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 564bcba27c Add ORB pre-market screening and fix Oracle/Alpaca reliability bugs
- Add run_pre_screen() at 9:20 ET: fetch daily bars + enrichment + quality filter
  before market open, narrowing universe for faster orb_detect intraday fetch
- run_orb_detection() uses cached pre-screen data when available; falls back to
  full pipeline if pre_screen missed (late start, failure)
- Add _last_trading_day() helper to skip weekends/holidays for bars_end,
  preventing Alpaca 502 on Mondays (today-1 = Sunday was causing failures)
- Fix Oracle client chunk_size 300→75: Alpaca rejects 100+ ticker URL requests
- Add pre_screen event to build_schedule() at 9:20 ET and dispatch in _run_trading()
- run_session_now() runs pre_screen before orb_detect for efficiency
- Add ORB daemon, engine, models, state, screener, and intraday strategy configs
- Add intraday library (libs/intraday/) and web routes for ORB/intraday trading

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago