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[2026-05-28] 운영 문서 최신화

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jongjae
2026-05-28 20:39:37 +09:00
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- Parameter changes must be written to `reports/proposals/YYYY-MM-DD_strategy_proposal.md` with evidence and manual approval required.
- `FORCE_EXIT = "14:50"` remains immutable.
## Current implementation status - 2026-05-27
## Current implementation status - 2026-05-28
- Mode: paper trading / dry-run focused. Real-cash trading is not approved yet.
- Approved strategy change applied: `ENTRY_START = "09:20"`.
- `FORCE_EXIT = "14:50"` remains unchanged.
- `avoid_sectors` runtime bug fixed: `main.py` now passes sector context into `check_entry()`.
- Sector handling now keeps a `ticker_sectors` cache when available and uses name-based hints for known avoid-sector cases.
- Data layer: `entry_snapshots` and `post_entry_snapshots` are active for training data.
- Post-entry sampling: 60s, 180s, 300s, and 600s after successful entry.
- Training data export: `scripts/export_training_dataset.py`.
- External data collection:
- Daily market features: `scripts/collect_daily_features.py`.
- KIS minute bars: `scripts/collect_minute_data.py`.
- External dataset builder: `scripts/build_external_training_dataset.py`.
- Daily market features: `scripts/collect_daily_features.py` with KIS fallback when pykrx fails.
- KIS minute bars: `scripts/collect_minute_data.py`, default ETF/ETN exclusion, multi-window collection from 09:30 to 14:00.
- External dataset builder: `scripts/build_external_training_dataset.py`, using prior daily OHLCV for breakout targets.
- ML engine:
- Training: `scripts/train_ai_model.py`.
- Model output: `models/scalping_model.joblib`.
- Metrics output: `models/scalping_model.metrics.json`.
- Runtime loader: `app/ml/predictor.py`.
- Latest training run: 2026-05-28 20:24, 3,156 rows total (`external_training_dataset.csv` 3,146 + bot dataset 10).
- Latest metrics: `label_stop_loss` ROC-AUC 0.851, `label_win` ROC-AUC 0.719.
- Training features exclude future/outcome leakage columns such as `ret_*`, `mfe_*`, `mae_*`, `price_*`, `pnl`, and `exit_price`.
- AI runtime mode: observation only. If a model exists, entry-time scores are logged and saved to `entry_snapshots`; they do not block or resize trades.
- Training schedule: `StockBot_Training` runs at 16:00 on trading days via `scripts/run_training_pipeline.ps1`.
- Training schedule: `StockBot_Training` runs at 16:00 on trading days via `scripts/run_training_pipeline.ps1`; the pipeline was end-to-end verified on 2026-05-28.
- Dependency install:
- `requirements.txt` includes `app/requirements.txt`.
- `scripts/install_dependencies.ps1` installs from `vendor/wheels` when available.
- `scripts/download_dependencies.ps1` builds the local wheelhouse.
## Current operational risks - 2026-05-27
## Current operational risks - 2026-05-28
- KIS minute-bar endpoint must be verified with live response logs.
- Early ML models may be meaningless until enough labeled rows exist.
- Model is still observation-only and is dominated by external pretraining rows; bot-trade labels are only 10 rows.
- KIS minute-bar collection is verified for same-day windows, but historical depth and ticker coverage remain limited.
- External minute data is pretraining data, not actual bot-trade data.
- pykrx daily feature collection can fail for same-day data; KIS fallback is active.
- Real-cash mode still needs stronger fill, partial-fill, unfilled-order, cancel/replace, and recovery logic.
- Existing logs and older docs contain encoding damage; new operational notes should stay ASCII unless the file encoding is intentionally cleaned.