- fix(data_stream): add reconnect loop to MultiSymbolStream matching UserDataStream pattern
Prevents bot-wide crash on WebSocket disconnect (#3 Critical)
- fix(data_stream): increase buffer_size 200→300 and preload 200→300
Ensures z-score window (288) has sufficient data (#5 Important)
- fix(bot): sync risk manager when Binance has no position but local state does
Prevents ghost entries in open_positions blocking future trades (#1 Critical)
- fix(ml_filter): add np.nan_to_num for ONNX input to handle NaN features
Prevents all signals being blocked during initial ~2h warmup (#2 Critical)
- fix(bot): replace _close_handled_by_sync with current_trade_side==None guard
Eliminates race window in SYNC PnL double recording (#4 Important)
- feat(bot): add _ensure_sl_tp_orders in _recover_position
Detects and re-places missing SL/TP orders on bot restart (#6 Important)
- feat(exchange): add get_open_orders method for SL/TP verification
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
5. Add daily PnL reset loop — UTC midnight auto-reset via
_daily_reset_loop in main.py, prevents stale daily_pnl accumulation
6. Fix set_base_balance race condition — call once in main.py before
spawning bots, instead of each bot calling independently
7. Remove realized_pnl != 0 from close detection — prevents entry
orders with small rp values being misclassified as closes
8. Rename xrp_btc_rs/xrp_eth_rs → primary_btc_rs/primary_eth_rs —
generic column names for multi-symbol support (dataset_builder,
ml_features, and tests updated consistently)
9. Replace asyncio.get_event_loop() → get_running_loop() — fixes
DeprecationWarning on Python 3.10+
10. Parallelize candle preload — asyncio.gather for all symbols
instead of sequential REST calls, ~3x faster startup
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Log current price and unrealized PnL every 5 minutes while holding a position,
using the existing kline WebSocket's unclosed candle data for real-time price updates.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Introduced a new markdown document detailing the plan to transition the entire pipeline from a 1-minute to a 15-minute timeframe, aiming to improve model AUC from 0.49-0.50 to over 0.53.
- Updated key parameters across multiple scripts, including `LOOKAHEAD` adjustments and default data paths to reflect the new 15-minute interval.
- Modified data fetching and training scripts to ensure compatibility with the new timeframe, including changes in `fetch_history.py`, `train_model.py`, and `train_and_deploy.sh`.
- Enhanced the bot's data stream configuration to operate on a 15-minute interval, ensuring real-time data processing aligns with the new model training strategy.
- Updated training logs to capture new model performance metrics under the revised timeframe.
- 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.
