[2026-05-28] 운영 문서 최신화
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# Implementation Log
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## 2026-05-28
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- Applied the approved 2026-05-28 strategy update:
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- `ENTRY_START` changed from `"09:15"` to `"09:20"`.
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- `FORCE_EXIT = "14:50"` was verified unchanged.
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- Fixed the `avoid_sectors` runtime bug:
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- `app/main.py` now passes `sector` into `VolatilityBreakout.check_entry()`.
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- Added `ticker_sectors` cache support from ranking rows when sector fields exist.
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- Added conservative name-based avoid-sector hints for cases such as construction names when no sector field is available.
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- Repaired the external-data pretraining path:
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- `scripts/collect_daily_features.py` now falls back to KIS daily OHLCV when pykrx fails.
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- `scripts/collect_minute_data.py` excludes ETF/ETN by default and collects multiple intraday windows from 09:30 to 14:00.
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- `scripts/build_external_training_dataset.py` now uses prior daily OHLCV rows for breakout targets instead of same-day OHLCV.
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- `scripts/run_training_pipeline.ps1` builds external rows with `--all-minutes` for pretraining.
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- Removed model leakage:
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- Excluded future/outcome columns from training features: `price_*`, `ret_*`, `mfe_*`, `mae_*`, `pnl`, and `exit_price`.
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- Fixed PowerShell training pipeline execution:
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- Replaced `$Args` parameter usage with `$StepArgs` to avoid PowerShell automatic-variable collision.
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- Prevented nonzero stderr output from stopping required exit-code handling.
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- Normalized Python step logging to UTF-8 append.
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- Removed unused helper:
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- `scripts/_send_midday_discord.py`.
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Validation performed:
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- `python -m compileall app scripts` passed.
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- Manual external daily collection passed through KIS fallback.
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- Manual KIS minute collection saved 11 regular-stock CSV files for 2026-05-28.
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- `data/external_training_dataset.csv` generated 3,146 rows.
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- `data/training_dataset.csv` generated 10 bot-trade rows.
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- `python scripts/train_ai_model.py` generated `models/scalping_model.joblib` and metrics.
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- `powershell -ExecutionPolicy Bypass -File scripts\run_training_pipeline.ps1` passed end-to-end.
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Latest training metrics:
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- `label_stop_loss`: rows 3,156, accuracy 0.750, precision 0.450, ROC-AUC 0.851.
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- `label_win`: rows 3,156, accuracy 0.635, precision 0.492, ROC-AUC 0.719.
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Open risks:
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- AI remains observation-only and must not block entries, resize trades, or override exits.
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- Training is still dominated by external pretraining rows; actual bot-labeled rows are only 10.
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- Same-day pykrx data may fail; KIS fallback is active but index rows can be empty.
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- Real-cash trading remains unapproved.
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## 2026-05-27
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- Reviewed the stock scalping bot structure and moved it toward an AI-training-ready paper-trading platform.
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