Replace day-trading bot with long-term accumulation signal model.
Predicts optimal BUY times using forward return analysis at 7d/30d/90d
horizons, scoring each candle 0-100. Primary metric is now
cost_basis_improvement_pct (model buy price vs DCA).
- train_and_backtest.py: regression models (XGBoost/LSTM hybrid),
accumulation-focused features (price position, momentum, volatility,
volume, cycle), forward return targets, signal quality backtesting
- orchestrator.py: cost improvement scoring, signal count validation
- analyzer.py: accumulation-focused LLM system prompt
- dashboard: cost improvement display, signal metrics table
- config: new accumulation-focused parameters
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
FastAPI dashboard on port 3088 with live iteration tracking,
Sharpe ratio chart, LLM analysis panel, config editor, and
download links. Orchestrator refactored to support library
usage with run_optimization_loop(), stop_flag, and callbacks.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
