Build robust trading strategies with comprehensive overfitting protection
From data validation to model deployment, every step is designed to prevent overfitting and ensure robust, reproducible trading strategies.
Automated OHLCV validation, quality scoring, and repair with 100% data integrity.
Safe, declarative strategy language with static analysis and leakage detection.
Reinforcement learning with PPO, early stopping, and hybrid strategy support.
Comprehensive overfitting protection with PSR/DSR, Reality Check, and risk scoring.
Jump right into building and testing your strategies
Every component is designed with overfitting prevention in mind
Rolling and anchored window validation with strict temporal separation
CPCV implementation prevents data leakage in time series
PSR/DSR and White's Reality Check for multiple testing correction
Static analysis catches look-ahead bias and future references
Composite overfit risk score blocks deployment of risky models
Stress tests with fee shocks, regime shifts, and data quality issues