Stock-trading-programming/reports/implementation_log.md

Implementation Log

2026-05-28

• Applied the approved 2026-05-28 strategy update:
  • ENTRY_START changed from "09:15" to "09:20".
  • FORCE_EXIT = "14:50" was verified unchanged.
• Fixed the avoid_sectors runtime bug:
  • app/main.py now passes sector into VolatilityBreakout.check_entry().
  • Added ticker_sectors cache support from ranking rows when sector fields exist.
  • Added conservative name-based avoid-sector hints for cases such as construction names when no sector field is available.
• Repaired the external-data pretraining path:
  • scripts/collect_daily_features.py now falls back to KIS daily OHLCV when pykrx fails.
  • scripts/collect_minute_data.py excludes ETF/ETN by default and collects multiple intraday windows from 09:30 to 14:00.
  • scripts/build_external_training_dataset.py now uses prior daily OHLCV rows for breakout targets instead of same-day OHLCV.
  • scripts/run_training_pipeline.ps1 builds external rows with --all-minutes for pretraining.
• Removed model leakage:
  • Excluded future/outcome columns from training features: price_*, ret_*, mfe_*, mae_*, pnl, and exit_price.
• Fixed PowerShell training pipeline execution:
  • Replaced $Args parameter usage with $StepArgs to avoid PowerShell automatic-variable collision.
  • Prevented nonzero stderr output from stopping required exit-code handling.
  • Normalized Python step logging to UTF-8 append.
• Removed unused helper:
  • scripts/_send_midday_discord.py.

Validation performed:

• python -m compileall app scripts passed.
• Manual external daily collection passed through KIS fallback.
• Manual KIS minute collection saved 11 regular-stock CSV files for 2026-05-28.
• data/external_training_dataset.csv generated 3,146 rows.
• data/training_dataset.csv generated 10 bot-trade rows.
• python scripts/train_ai_model.py generated models/scalping_model.joblib and metrics.
• powershell -ExecutionPolicy Bypass -File scripts\run_training_pipeline.ps1 passed end-to-end.

Latest training metrics:

• label_stop_loss: rows 3,156, accuracy 0.750, precision 0.450, ROC-AUC 0.851.
• label_win: rows 3,156, accuracy 0.635, precision 0.492, ROC-AUC 0.719.

Open risks:

• AI remains observation-only and must not block entries, resize trades, or override exits.
• Training is still dominated by external pretraining rows; actual bot-labeled rows are only 10.
• Same-day pykrx data may fail; KIS fallback is active but index rows can be empty.
• Real-cash trading remains unapproved.

2026-05-27

• Reviewed the stock scalping bot structure and moved it toward an AI-training-ready paper-trading platform.
• Added database tables for AI training:
  • entry_snapshots
  • post_entry_snapshots
• Added entry-time data capture after successful buys.
• Added post-entry sampling at 60s, 180s, 300s, and 600s.
• Fixed partial-exit accounting so partial TP1 exits no longer close the whole trade row.
• Relaxed strict entry-limit enforcement during paper-trading data collection while preserving warning logs.
• Added daily/export training scripts:
  • scripts/export_training_dataset.py
  • scripts/collect_daily_features.py
  • scripts/collect_minute_data.py
  • scripts/build_external_training_dataset.py
• Added ML training and runtime support:
  • app/ml/features.py
  • app/ml/predictor.py
  • scripts/train_ai_model.py
• Added observation-only AI scoring:
  • Runtime scores are recorded only when a trained model exists.
  • AI scores do not block entries, change sizing, or override exits.
• Added daily training pipeline:
  • scripts/run_training_pipeline.ps1
• Registered and verified Windows Scheduler tasks:
  • StockBot_Morning
  • StockBot_Watchdog
  • StockBot_Midday
  • StockBot_Evening
  • StockBot_Training
• Rewrote scheduler setup to avoid hardcoded broken Korean paths:
  • scripts/setup_scheduler.ps1
• Rewrote watchdog wrapper with trading-day and time-window checks:
  • scripts/run_watchdog.ps1
• Added dependency portability:
  • Root requirements.txt
  • scripts/install_dependencies.ps1
  • scripts/download_dependencies.ps1
  • vendor/wheels wheelhouse for Windows/Python 3.11
• Updated operational docs:
  • README.md
  • CLAUDE.md
  • reports/daily/2026-05-27.md

Validation performed:

• Python compile check passed.
• DB migration checked.
• AI score snapshot insert checked with a temporary DB.
• Training script checked with empty dataset.
• Scheduler registration checked.
• PowerShell script parse check passed.

Open risks:

• KIS minute endpoint still needs live response verification.
• Early model quality is expected to be weak until enough labeled rows exist.
• External minute data is useful for pretraining, not final bot-trade truth.
• Real-cash trading still needs stronger fill, partial-fill, unfilled-order, cancel/replace, and recovery handling.
• Raspberry Pi dependency packaging needs a Linux/ARM-specific setup.
• Approved and applied ENTRY_START = "09:15" after the 2026-05-27 evening review.
• Reason: 09:05-09:06 generated four immediate SL trades and most of the daily loss.
• Time-based sizing and time-based SL changes remain deferred.

2026-05-27 Strategy Approval Log

• User approved Claude Evening Proposal 1.
• Changed app/config.py:
  • Before: ENTRY_START = "09:05"
  • After: ENTRY_START = "09:15"
• Rationale:
  • Four immediate SL trades occurred from 09:05:03 to 09:05:49.
  • Those four trades lost about -183,969 KRW.
  • This represented about 74.5% of the daily loss.
• Deferred:
  • Time-based position-size reduction.
  • Time-based stop-loss adjustment.
• Verification:
  • Python compile check passed.
  • Runtime import confirmed ENTRY_START == "09:15".