2395a0c0c3
feat: PEAD mid-cap strategy + pipeline hardening + README cleanup
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- Implement PEAD 7% Long+Short strategy with mid-cap universe expansion
- Add Stock Oracle screener/company clients, text sentiment features
- Enhance backtest engine: short-side execution, walk-forward CV, MFE/MAE analysis
- Harden pipeline: sequential Oracle API calls, scoring recalibration (event_quality 65%)
- Add experiment configs for 60+ strategy variants and journal tracking
- Add review/analysis CLI tools
- Remove obsolete dev/phase0-4 design documents and analysis scripts
- Clean README to reflect only implemented features (remove unbuilt adapters/engines)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
5 months ago
d4ae900286
feat: expand data pipeline and integrate event features into scoring
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Data expansion:
- Poll SEC 8-K filings from 2025-10-01 to 2026-03-12 (was ~2 months)
- Pipeline: 36 new filings → 24 new events → total 44 events, 15 symbols
- Re-export with merged features (market_v1+event_v1+financial_v1)
- Parquet columns: 7 → 41 (adds signal_strength, guidance_direction,
document_quality, oneoff_penalty, eps_growth_qoq, etc.)
Score model v2:
- Add event quality component (15% weight): signal_strength_score,
guidance_direction_score, document_quality_score
- Add risk penalty component (10% weight): inverted oneoff_penalty
- Rebalance market weights: reaction 25%, close 25%, volume 15%, gap 10%
- Graceful degradation when event features are absent (returns 0.5)
Export pipeline:
- Add --feature-versions CLI flag to merge multiple feature types
- export_dataset_snapshot() accepts feature_versions list parameter
- Groups features by event_id and merges feature_json dicts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
5 months ago
bbe0e31150
feat: implement Phase 3 -- LLM enrichment, labeler, review queue, dataset export
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- libs/llm/: OllamaClient (httpx async, retry), LLMCacheStore (SHA-256 DB cache),
prompt registry (event_classifier_v1), LLMParser (cache→prompt→validate→repair)
- libs/parser/merger.py: rule+LLM canonical merge with provenance tracking,
conflict detection (both confident + disagree), should_queue_for_review()
- libs/db/models.py: LLMCallCache, ReviewItem, EventLabel 3개 ORM 모델 추가
- libs/db/migrations/versions/0002_phase3_tables.py: Phase 3 Alembic migration
- libs/labeler/: filing_time_bucket→reaction_date, 1D/3D/5D fwd return, MFE/MAE
- libs/review/queue.py: create(dedup)/resolve/list ReviewItem
- libs/export/snapshot_export.py: temporal split + Parquet + manifest.json
- apps/: label_generator, dataset_export, review CLI, gold set evaluator
- 42개 신규 테스트 추가 (unit 32 + integration 4 + replay 1) — 152/152 통과
- libs/common/config.py: OLLAMA_URL/MODEL/TIMEOUT 설정 추가
- libs/common/logging.py: bugfix — add_logger_name incompatible with PrintLoggerFactory
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 months ago
I Luk Kim