RQAlpha is a Python-native quantitative trading backtesting framework and live trading execution system. It provides an event-driven engine for simulating trading strategies against historical market data, with realistic transaction costs, slippage models, and corporate action handling. The platform supports multi-asset class trading including stocks, futures, options, and REITs, with separate sub-accounts for different asset types and configurable margin requirements.
The framework distinguishes itself through a plugin-based extensible architecture that allows users to swap out core components like data sources, order matching models, and risk controls through modular mods and plugins. It includes a broker-integrated live trading execution system that routes strategy signals to real markets for order placement and trade management during market hours. The platform also offers persistent state serialization for pause-and-resume across sessions, a risk validation pipeline for pre-trade checks, and the ability to schedule recurring tasks programmatically.
Beyond backtesting and live trading, RQAlpha provides comprehensive performance analytics including alpha, beta, Sharpe ratio, and drawdown calculations, with exportable reports and equity curve visualizations. The system supports multiple time frames from daily to tick-level data, algorithmic order types like TWAP and VWAP, and can be driven from custom data sources. Users can run strategies from Python code, CLI commands, or packaged mods distributed via PyPI.