Concluded hypotheses already live in concluded/ — keeping them in active.json
causes the registry to grow unboundedly. Runner now removes them at the end
of each cycle. Also cleaned up the existing social_dd concluded entry.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Analysis of 25 picks reveals 60% 30d win rate (+2.32%) vs 41.7% 7d (-1.92%).
Score suppression is not the primary issue (avg score 71.5, 22/25 >= 65).
Root cause is evaluation horizon mismatch — ranker calibrated on 7d outcomes.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements ShortSqueezeScanner wrapping existing get_short_interest() in finviz_scraper.py.
Research finding: raw high SI predicts negative long-term returns (academic); edge is using
SI as a squeeze-risk flag when combined with earnings_calendar or options_flow catalysts.
Directly addresses earnings_calendar pending hypothesis (APLD 30.6% SI was strongest setup).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- active.json: updated days_elapsed from hypothesis runner
- hypotheses.py: black formatting applied by pre-commit hook
- .gitignore: local additions
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Pending hypotheses queue by priority and promote when a slot opens,
rather than pausing a running experiment mid-streak.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Covers 5 tasks: knowledge base structure, /iterate command,
/research-strategy command, and two GitHub Actions workflows with
rolling PR logic.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
At most one open PR per skill at any time. Daily runs push onto the
existing branch and update the PR description. Merging resets the cycle.
Prevents PR accumulation from unreviewed automated runs.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Scanners and strategies are 1:1 in the current codebase — separate folder
was artificial. Each scanner file now captures both implementation and thesis.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds daily /iterate and weekly /research-strategy cron workflows to the
spec — full autonomous loop with PR-gated merges, no auto-merge to main.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Defines /iterate and /research-strategy skills + docs/iterations/ folder
structure for a generic learn-improve-repeat cycle, demonstrated with the
trading agent discovery pipeline.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Documents the approved plan to fix signal quality issues in all 9
existing scanners and add 3 new scanners (analyst upgrades, technical
breakout, sector rotation).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Major additions:
- ML win probability scanner: scans ticker universe using trained
LightGBM/TabPFN model, surfaces candidates with P(WIN) above threshold
- 30-feature engineering pipeline (20 base + 10 interaction features)
computed from OHLCV data via stockstats + pandas
- Triple-barrier labeling for training data generation
- Dataset builder and training script with calibration analysis
- Discovery enrichment: confluence scoring, short interest extraction,
earnings estimates, options signal normalization, quant pre-score
- Configurable prompt logging (log_prompts_console flag)
- Enhanced ranker investment thesis (4-6 sentence reasoning)
- Typed DiscoveryConfig dataclass for all discovery settings
- Console price charts for visual ticker analysis
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Youssef Aitousarrah
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