Add ADX (Average Directional Index) with period 14 to calculate_all()
for sideways market filtering. Includes test verifying the adx column
exists and contains non-negative values.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
바이낸스 OI 히스토리 API가 최근 30일치만 제공하는 제약을 우회하기 위해
upsert_parquet() 함수를 추가. 매일 실행 시 기존 parquet의 oi_change/funding_rate가
0.0인 구간만 신규 값으로 덮어써 점진적으로 과거 데이터를 채워나감.
--no-upsert 플래그로 기존 덮어쓰기 동작 유지 가능.
Made-with: Cursor
- _fetch_market_microstructure: oi_val > 0 체크 후에만 _calc_oi_change 호출하여
API 실패(None/Exception) 시 0.0으로 폴백하고 _prev_oi 상태 오염 방지
- README: ML 피처 수 오기재 수정 (25개 → 23개)
- tests: _calc_oi_change 첫 캔들 및 API 실패 시 상태 보존 유닛 테스트 추가
Made-with: Cursor
- Add asyncio import to bot.py
- Add _prev_oi state for OI change rate calculation
- Add _fetch_market_microstructure() for concurrent OI/funding rate fetch with exception fallback
- Add _calc_oi_change() for relative OI change calculation
- Always call build_features() before ML filter check in process_candle()
- Pass oi_change/funding_rate kwargs to build_features() in both process_candle() and _close_and_reenter()
- Update _close_and_reenter() signature to accept oi_change/funding_rate params
Made-with: Cursor
- Updated README.md to reflect new features including dynamic margin ratio, model hot-reload, and multi-symbol streaming.
- Modified bot logic to ensure raw signals are passed to the `_close_and_reenter` method, even when the ML filter is loaded.
- Introduced a new script `run_tests.sh` for streamlined test execution.
- Improved test coverage for signal processing and re-entry logic, ensuring correct behavior under various conditions.
- Added `_close_and_reenter` method to handle immediate re-entry after closing a position when a reverse signal is detected, contingent on passing the ML filter.
- Updated `process_candle` to call `_close_and_reenter` instead of `_close_position` for reverse signals.
- Enhanced test coverage for the new functionality, ensuring correct behavior under various conditions, including ML filter checks and position limits.
- Added a new design document outlining the integration of BTC/ETH candle data as additional features in the XRP ML filter, enhancing prediction accuracy.
- Introduced `MultiSymbolStream` for combined WebSocket data retrieval of XRP, BTC, and ETH.
- Expanded feature set from 13 to 21 by including 8 new BTC/ETH-related features.
- Updated various scripts and modules to support the new feature set and data handling.
- Enhanced training and deployment scripts to accommodate the new dataset structure.
This commit lays the groundwork for improved model performance by leveraging the correlation between BTC and ETH with XRP.
- Added MLFilter class to load and evaluate LightGBM model for trading signals.
- Introduced retraining mechanism to update the model daily based on new data.
- Created feature engineering and label building utilities for model training.
- Updated bot logic to incorporate ML filter for signal validation.
- Added scripts for data fetching and model training.
Made-with: Cursor
