16 Commits (main)

Author SHA1 Message Date
I Luk Kim e46395bfeb Backfill: renormalize 1,069 historical oracle-fallback rows
Apply libs.parser.event_type_normalizer (added in commit 722e5cf) to
existing events whose parser_version LIKE 'oracle-fallback%' so historical
rows match the forward-going normalization wired into the parser.

Implementation:
 - New renormalize_oracle_fallback_events() in apps/pipeline/event_parser/main.py
 - SELECT filter Event.parser_version.like("oracle-fallback%") — broader
   than a hardcoded IN list, so already-aligned values skip naturally and
   future additions to _ORACLE_TO_STRATEGY get picked up automatically
 - New --renormalize-oracle-fallback CLI flag, chainable with --reparse
 - JobRun row written (job_name=event_parser_renormalize_oracle)
 - Per-row renormalize_event_updated INFO log + final renormalize_done
   summary with transition counters

Live DB run: seen=2937 / updated=1069 / skipped=1868 / errors=0.
Wall ~2 sec (pure DB UPDATEs, no Oracle calls).
Transitions:
  earnings_result          -> earnings_release        : 412
  shareholder_vote         -> other_material_event    : 409
  regulation_fd            -> guidance_update         : 237
  acquisition_disposition  -> other_material_event    :   7
  other                    -> other_material_event    :   4

Unmapped Oracle values (financial_obligation 225, articles_amendment 81,
contract_termination 48, etc.) preserved verbatim — honest filter-drop.

Stale-by-design (mirrors existing reparse_events convention):
 - Event.event_id PK still embeds old raw event_type substring
 - EventParse.output_json["event_type"] still carries raw Oracle value
Strategies read Event.event_type, not those fields. Avoids cascading
PK rewrites across event_parses/feature_snapshots/event_labels tables.

Integration test: tests/integration/test_renormalize_oracle_fallback.py
inserts 4 fixtures, drives _apply_oracle_renormalization() against the
rolled-back db_session, asserts updated/skipped/error counts and final
row state.

Snapshot rebuild not run — nightly auto-rebuild picks up normalized
values incrementally.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
3 months ago
I Luk Kim 722e5cf6a9 Add Oracle event_type vocabulary normalizer for fallback path
When the rule parser can't classify an 8-K and falls back to Stock Oracle's
filing-events API, Oracle's vocabulary (e.g. earnings_result, shareholder_vote,
regulation_fd) was being written verbatim into events.event_type. The DB has
no CHECK constraint (libs/db/models.py:189), so 22 distinct Oracle values
silently leaked into a column the strategy's engine filters expect to be in
its 4-event vocabulary. Result: ~1,069 live rows silently dropped from
strategy candidate pool.

Files:
 - NEW libs/parser/event_type_normalizer.py: normalize_oracle_event_type()
   with conservative synonym map; normalize_oracle_event() additionally
   uses _classify_event_type from rule_parser when an item_number is
   present (item-code path is more reliable than Oracle's event taxonomy)
 - MOD apps/pipeline/event_parser/main.py: oracle-fallback branch (~line
   140) now calls normalize_oracle_event before writing to DB; emits
   oracle_event_type_normalized log event when value changes
 - NEW tests/unit/test_event_type_normalizer.py: 60 tests covering
   identity, synonyms, case/separator insensitivity, None/empty,
   non-string, item_number-precedence

Mapping highlights (justifications in test docstrings):
 earnings_result/earnings_announcement/earnings -> earnings_release
 guidance_revision/guidance_change/regulation_fd -> guidance_update
 material_definitive_agreement/definitive_agreement -> material_contract
 shareholder_vote/acquisition_disposition/bankruptcy/other -> other_material_event

Reg FD -> guidance_update mirrors rule_parser's Item 7.01 mapping for
internal consistency. Debatable but auditable.

Conservative pass-through for ambiguous values (financial_obligation,
articles_amendment, contract_termination, etc., 14 distinct values).
Visible filter-drop > silent re-tag.

Live DB counts that would reclassify on a future --reparse pass:
 412 earnings_result -> earnings_release
 409 shareholder_vote -> other_material_event
 237 regulation_fd -> guidance_update
   7 acquisition_disposition -> other_material_event
   4 other -> other_material_event
TOTAL 1,069 rows currently in oracle-fallback dead-zone.

60/60 normalizer tests pass; combined parser+schema validator suite 86/86.

Follow-up flagged: run --reparse on historical oracle-fallback rows after
extending reparse_events() to also re-normalize known oracle-fallback
values (currently only re-parses event_type='unknown').

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
3 months ago
I Luk Kim 27de44c8d8 Fix label_price_unavailable: preserve future entry_dates as pending
Pre-market label_generator runs request future-dated price windows from
Stock Oracle, which correctly returns 404 because the data does not yet
exist. The labeler was swallowing this as label_status='unavailable' with
entry_date=None. Snapshot export then filtered these rows out, so live
PEAD trading silently lost candidates whose entry_dates fell on
later trading days (e.g., post-market 8-K filings late Friday → Monday
open entry). This explains today's missed RKLB/SNDK/AKAM/MNST/AMD/MRNA
even though their 8-Ks parsed correctly.

Changes:
 - libs/labeler/label_generator.py: in 404/empty-bars path, when
   entry_date >= today, preserve entry_date and mark label_status='pending'.
   New log event label_price_pending_future_window distinguishes from real
   data-unavailable failures (past dates still log label_price_unavailable).
 - libs/export/snapshot_export.py: include 'pending' in the
   label_status filter so today's not-yet-labeled events flow into the
   live snapshot.
 - apps/pipeline/label_generator/main.py: regeneration logic also
   retries existing 'unavailable' rows whose entry_date is null or future
   to recover events already mis-labeled in the DB.
 - tests/unit/test_labeler.py: regression test reproducing the
   RKLB/SNDK/AKAM failure mode and asserting label_status='pending' with
   entry_date preserved.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
3 months ago
I Luk Kim 2b6cea57b2 Paper trader Phase 1 fixes: multi-session isolation, pipeline halt, snapshot refresh unblock
- v7.356 config: swap dataset_snapshot_id from manual_only ftb_fix_v2 to
  auto_full_rebuild base canonical so paper trader can refresh snapshot
  (root cause of processed_events=0 for 30 days)
- Multi-session order isolation (1.A.2/1.A.3): tag client_order_id with
  pt-{session_id[:8]}-{uuid} prefix on all entry orders; _cancel_stale_orders
  filters by own session prefix so one session no longer ghost-cancels another's
  orders on shared Alpaca account
- Pipeline halt on failure (1.B.1): _run_pipeline returns bool and stops on
  first subprocess failure instead of silently progressing with stale data
- Daemon restart window skip (2.2): run_open/run_close only marked completed
  if processed_phases DB confirms prior execution — no more trading-less days
  after mid-day restart
- event_parser: periodic batch commits every 500 docs (hypothesis fix for
  3h hangs; unverified — may just be slow serial Oracle calls)
- Tests updated for _verify_order_fill tuple return + new cross-session
  isolation test; all 23 paper_trader unit tests green

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 9095b376d9 Clean up superseded configs and commit accumulated R&D infrastructure
Key changes:
- Delete superseded strategy configs: orb_gainers safe_v2-v9, orb_pullback, vwap_reclaim, hypergap, leader_safe
- Add V46 prior_event_types param to domain.py + run.py event type wiring
- Major simulator.py enhancements: sector thrust sleeve, sector proxy mapping, helper functions
- Improve screener.py with better scoring/filtering
- Add new test coverage: test_simulator.py (776 lines) + test_screener.py (313 lines)
- Add V24.1 research candidate configs (w002/w003/w004/entrycap/losscap010 variants)
- Add leader momentum research configs and sweep files
- Update configs/snapshots/registry.json with new strategy registrations
- Add docs/leader_intraday_momentum_workflow.md

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 5ea8850ac2 Fix paper trader startup: run missed run_open if market still open; improve poll_error logging
- AutoScheduler._run_catchup: if server starts after 9:35 AM ET but before
  market close (16:00 ET), and run_open hasn't already run today
  (checked via processed_phases), run it immediately instead of silently
  skipping it — prevents AVGO/event entries being missed on late starts

- filing_poller: log exc_type alongside error so empty-string exceptions
  (e.g. HTTPError()) are still identifiable by their type

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim b3ba914a8d Optimize v7 strategy: v7.356 achieves CW 2159% + SQS 90.7 (Pareto improvement over v7.314)
Key changes from v7.314 baseline (CW 2012%, SQS 90.0):
- max_position_value_pct 15→25, non_a_tier_target_1_fraction 0.2→0
- max_daily_new_risk_pct 30→50 (via v7.330, CW champion 2148%)
- bullish_raised_recovery per_trade_risk_pct 0.71→0.55 (DD improvement)
- bullish_raised_recovery max_holding_days 12→10 (sweet spot, +98pp CW)

Result: v7.356 CW 2159% (+147pp), SQS 90.7 (+0.7), risk 66.2 (+2.9), robustness 94.3 (+0.5)
All metrics improved simultaneously — return increase AND DD reduction achieved.

Also includes: web UI updates, pipeline scripts, v16/v17/v18/v19 experiment pruning,
Form4 preset additions, snapshot registry updates, domain.py enhancements.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
4 months ago
I Luk Kim 5496059b6c Add v7.120 composed GLD experiment updates 4 months ago
I Luk Kim 2aba6418e6 Add overlay engine, ranking models, snapshot pipelines, and research tools
New libs: overlay curve builder, ranking models, continuation/merged
snapshot export, intraday features. New tools: overlay evaluator,
ranking model builder, deep evaluation, fullsplit batch runner.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
5 months ago
I Luk Kim 57d38ecfe0 Add earnings surprise feature pipeline and snapshot export improvements
Adds earnings surprise extraction to parser/features/labeler pipeline,
improves filing fetcher robustness, and extends snapshot export with
new field support.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
5 months ago
I Luk Kim 2395a0c0c3 feat: PEAD mid-cap strategy + pipeline hardening + README cleanup
- 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
I Luk Kim d4ae900286 feat: expand data pipeline and integrate event features into scoring
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
I Luk Kim 9d3427e24e fix: disable Qwen3.5 thinking mode and switch OllamaClient to sync httpx
- Add `think: False` and `num_ctx: 8192` to Ollama payload:
  Qwen3.5 extended thinking mode generated 1300+ internal reasoning
  tokens before each response, adding 30-60s latency per LLM call.
  Disabling it reduces parse time from 600s timeout to ~13s.

- Rewrite OllamaClient to use sync httpx.Client inside asyncio.to_thread():
  Async httpx inside an active asyncpg SQLAlchemy session context on
  Python 3.13 hung indefinitely. Synchronous httpx in a thread pool
  completely isolates Ollama I/O from the asyncio event loop.

- Fix filing_poller to set issuer_id/symbol_id on Document records:
  Missing FK caused feature_builder to reject all events with
  event_no_symbol warning. Now looks up IssuerMaster/SymbolMaster
  by ticker before creating Document rows.

- Update test_llm_client to mock _sync_call instead of _client attr.
- Raise ollama_timeout default to 600s for large document processing.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 months ago
I Luk Kim bbe0e31150 feat: implement Phase 3 -- LLM enrichment, labeler, review queue, dataset export
- 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 38ac53b597 implement Phase 2 gap items: backfill CLI, retry, financial features
- filing_poller: add --start-date/--end-date CLI args for historical backfill
  (defaults to 7 days ago when omitted)
- OracleClient.get/post: apply with_retry(max_attempts=3) so transient
  connection errors, timeouts, and 5xx responses are automatically retried
  with exponential backoff (0.1s→0.2s→fail)
- financial_features: new compute_financial_features() extracting latest_eps,
  latest_gross_margin, latest_operating_margin, eps_growth_qoq,
  revenue_growth_qoq from FinancialDataResponse
- feature_builder: wire FinancialService into build_features_for_event(),
  persisting financial_v1 FeatureSnapshot (non-fatal if unavailable)
- tests: 94 pass (81→89 unit + 5 replay); +8 new tests covering financial
  features and retry success path

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
5 months ago
I Luk Kim 0471018dd8 feat: implement ACE-F v1 Phase 1 -- Stock Oracle 기반 이벤트 파이프라인
Stock Oracle (localhost:18001)을 단일 데이터 소스로 사용하는 미국 주식
이벤트 스윙 트레이딩 시스템의 Phase 1 구현체.

주요 구성:
- libs/oracle_client/: Stock Oracle REST 클라이언트 (filings, price, financial, fred, finra)
- libs/common/: config, logging, time_utils, ids, retries, file_store
- libs/db/: SQLAlchemy 2.0 모델 12개 + Alembic 마이그레이션 0001
- libs/parser/: 규칙 기반 파서 (텍스트 정규화, JSON Schema 검증, LLM 스텁)
- libs/features/: 시장/이벤트 피처 계산기
- apps/pipeline/: filing_poller → filing_fetcher → event_parser → feature_builder
- apps/sync/: macro_sync (FRED), short_volume_sync (FINRA), issuer_sync
- tests/: 단위 81개 + 리플레이 5개 전체 통과, lint clean

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