- Add payoff_ratio and max_consecutive_losses to backtester summary
- Add compare_symbols.py: per-symbol parameter sweep for candidate evaluation
- Add position_sizing_analysis.py: robust Monte Carlo position sizing
- Fetch historical data for SOL, LINK, AVAX candidates (365 days)
- Update existing symbol data (XRP, TRX, DOGE)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
_handle_close was not clearing _current_positions when no matching OPEN
trade was found in DB, causing all subsequent entries for the same
symbol+direction to be silently skipped. Also add PYTHONUNBUFFERED=1
and python -u to make log parser crashes visible in docker logs.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The combined summary (PF, MDD, win_rate) was indirectly reconstructed
from per-symbol averages using round(win_rate * n), which introduced
rounding errors. MDD was max() of individual symbol MDDs, ignoring
simultaneous drawdowns across the correlated crypto portfolio.
Now computes all combined metrics directly from the trade list:
- PF: sum(wins) / sum(losses) from actual trade PnLs
- MDD: portfolio equity curve from time-sorted trades
- Win rate: direct count from trade PnLs
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Increased ATR_SL_MULT_TRXUSDT from 1.0 to 2.0 and adjusted ADX_THRESHOLD_TRXUSDT from 30 to 25 in README.
- Added new weekly report files in HTML and JSON formats for 2026-03-15, including detailed backtest summaries and trade data for XRPUSDT, TRXUSDT, and DOGEUSDT.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
MARKET orders can fill in multiple trades (PARTIALLY_FILLED → FILLED).
Previously only the last fill's rp/commission was captured, causing
under-reported PnL. Now accumulates rp and commission across all
partial fills per order_id and sums them on final FILLED event.
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>
1. Margin ratio calculated on per_symbol_balance instead of total balance
— previously amplified margin reduction by num_symbols factor
2. Replace Algo Order API (algoType=CONDITIONAL) with standard
futures_create_order for SL/TP — algo API is for VP/TWAP, not
conditional orders; SL/TP may have silently failed
3. Fallback PnL (SYNC close) now sums all recent income rows instead
of using only the last entry — prevents daily_pnl corruption in
multi-fill scenarios
4. Explicit state transition in _close_and_reenter — clear local
position state after close order to prevent race with User Data
Stream callback on position count
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Nginx caches DNS at startup, so when dashboard-api restarts and gets
a new container IP, the proxy breaks with 502. Use Docker's embedded
DNS resolver (127.0.0.11) with a variable-based proxy_pass to
re-resolve on every request.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Add UNIQUE(symbol, entry_time, direction) constraint to trades table
and use INSERT OR IGNORE to skip duplicates. Includes auto-migration
to clean up existing duplicate entries on startup.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When the position monitor detects a missed close via API fallback, it
now queries Binance futures_income_history to get the real realized PnL
and commission instead of logging zeros. Exit price is estimated from
entry price + PnL/quantity. This ensures the dashboard records accurate
profit data even when WebSocket events are missed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The position monitor now checks Binance API every 5 minutes to verify
the bot's internal state matches the actual position. If the bot thinks
a position is open but Binance shows none, it syncs state and logs a
SYNC close event. This prevents the bot from being stuck in a phantom
position when User Data Stream misses a TP/SL fill event.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Added entries to .gitignore for node_modules and dist directories in the dashboard UI.
- Updated log file pattern in log_parser.py to match 'bot*.log' instead of 'bot_*.log'.
- Introduced package-lock.json for the dashboard UI to manage dependencies.
- Updated CLAUDE.md to reflect the status of code review improvements.
- Added new weekly report files in HTML and JSON formats for 2026-03-07.
- Updated binary parquet files for dogeusdt, trxusdt, and xrpusdt with new data.
Changed _init_db() from DROP+CREATE to CREATE IF NOT EXISTS so that
trade history, candle data, and daily PnL survive container restarts.
Previously all tables were dropped on every parser start, losing
historical data if log files had been rotated.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The /api/symbols endpoint only returned symbols that had a :last_start
key, which requires the log parser to catch the bot start log. If the
dashboard was deployed after the bot started, the start log was already
past the file position and symbols showed as 0. Now extracts symbols
from any colon-prefixed key in bot_status.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Parse position monitor logs (5min interval) to update current_price,
unrealized_pnl and unrealized_pnl_pct in bot_status. Position cards
now display USDT amount and percentage, colored green/red. Falls back
to entry/current price calculation if monitor data unavailable.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Hardcoded round(qty, 1) caused -1111 Precision errors for TRXUSDT and
DOGEUSDT (stepSize=1, requires integers). Now lazily loads quantityPrecision
and pricePrecision from Binance futures_exchange_info per symbol. SL/TP
prices also use symbol-specific precision instead of hardcoded 4 decimals.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
_fetch_oi_hist and _fetch_funding_rate had no retry logic, causing
crashes on rate limit (429) or transient errors during weekly report
data collection. Added _get_json_with_retry helper (max 3 attempts,
exponential backoff). Updated code-review docs to reflect completion.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
useCallback dependency on `symbols` state caused fetchAll to recreate
on every call (since it sets symbols), triggering useEffect to restart
the interval immediately. Use symbolsRef to break the cycle.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- #1: OI division by zero — already fixed (prev_oi == 0.0 guard exists)
- #2: cumulative trade count used max() instead of sum(), breaking ML trigger
- #4: fetch_history API calls now retry 3x with exponential backoff
- #5: parquet upsert now deduplicates timestamps before sort
- #6: record_pnl() is now async with Lock for multi-symbol safety
- #8: exit_price=0.0 skips close handling with warning log
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
get_signal() now returns (signal, detail) tuple with long/short scores,
ADX value, volume surge status, and HOLD reason for easier diagnosis.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Revised the architecture document to enhance clarity on system overview, trading decision process, and technical stack.
- Updated the README to emphasize the bot's operational guidelines and risk management features.
- Added new sections in the architecture document detailing the trading decision gates and data pipeline flow.
- Improved the table of contents for better navigation and understanding of the bot's architecture.
- Added functionality to fetch live trade data from the dashboard API.
- Implemented weekly report generation that includes backtest results, live trade statistics, and performance trends.
- Enhanced error handling for API requests and improved logging for better traceability.
- Updated tests to cover new features and ensure reliability of the report generation process.
8-task plan covering: data fetch, WF backtest, log parsing, trend tracking,
ML re-trigger check, degradation sweep, Discord formatting, CLI orchestration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Added a new CLI tool `scripts/strategy_sweep.py` for executing parameter sweeps.
- Updated `get_signal()` and `_calc_signals()` methods to accept `signal_threshold`, `adx_threshold`, and `volume_multiplier` parameters for improved signal processing.
- Fixed a bug in `WalkForwardBacktester` that prevented proper propagation of signal parameters, ensuring accurate backtesting results.
- Updated documentation to reflect changes in parameter sweeps and results.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Introduced multiple JSON files containing results from walk-forward backtests with varying configurations.
- Added strategy sweep results for different parameter combinations, showcasing performance metrics such as total trades, total PnL, win rate, and more.
- Enhanced the overall testing framework for better analysis of trading strategies.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
WF backtester always passed trained models to Backtester.run(ml_models=...),
overriding ml_filters even when use_ml=False. This caused 0 trades in
--no-ml mode because underfitted models (trained on ~27 samples) blocked
all entries with proba < 0.55 threshold.
- Skip model training when use_ml=False (saves computation)
- Only inject ml_models when use_ml=True
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Fix LightGBM predict_proba ValueError by filtering FEATURE_COLS and casting to float64
- Extract BTC/ETH correlation data from embedded parquet columns instead of missing separate files
- Disable ONNX priority in ML filter tests to use mocked LightGBM correctly
- Add NO_ML_FILTER=true to .env.example (ML adds no value with current signal thresholds)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Updated the change detection script to compare the current commit with the previous successful build, falling back to HEAD~5 if no previous commit exists.
- Enhanced logging to indicate the base commit used for comparison.
- Added support for multi-symbol trading (XRP, TRX, DOGE) in the dashboard.
- Updated bot log messages to include [SYMBOL] prefix for better tracking.
- Enhanced log parser for multi-symbol state tracking and updated database schema.
- Introduced new API endpoints and UI components for symbol filtering and display.
- Added new model files and backtest results for multi-symbol strategies.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add [SYMBOL] prefix to all bot/user_data_stream log messages
- Rewrite log_parser.py with multi-symbol regex, per-symbol state tracking, symbol columns in DB schema
- Rewrite dashboard_api.py with /api/symbols endpoint, symbol query params on all endpoints, SQL injection fix
- Update App.jsx with symbol filter tabs, multi-position display, dynamic header
- Add tests for log parser (8 tests) and dashboard API (7 tests)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Updated .gitignore to include .venv and .worktrees.
- Removed symlink for the virtual environment.
- Added new parquet files for dogeusdt, trxusdt, and xrpusdt datasets.
- Introduced model files and training logs for dogeusdt, trxusdt, and xrpusdt.
- Enhanced fetch_history.py to support caching of correlation symbols.
- Updated train_and_deploy.sh to manage correlation cache directory.
