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 componen
Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies across global equities, futures, and cryptocurrencies. It integrates an event-driven backtesting engine, a multi-market execution gateway for order routing, and a quantitative data pipeline for ingesting and storing multi-asset market data. The system features a Rust-accelerated financial library that utilizes Apache Arrow for high-performance technical indicator calculation and zero-copy data processing. It provides a containerized infrastructure model designed for orchestrati
This project provides technical documentation and reference guides for spot trading, including specifications for REST, WebSocket, and FIX protocols. It serves as a comprehensive resource for integrating with spot trading endpoints to execute trades, query account data, and fetch market statistics. The project distinguishes itself by supporting institutional-grade connectivity through the Financial Information eXchange standard and simple binary encoding to reduce latency and payload size. It also includes a dedicated sandbox environment for validating trading logic and strategies without fin
pyalgotrade is a Python algorithmic trading library designed for developing, backtesting, and executing automated trading strategies. It provides a comprehensive framework for financial strategy backtesting, a technical analysis library for computing mathematical indicators, and connectors for cryptocurrency exchange integration. The project distinguishes itself by supporting sentiment-based trading through the integration of real-time social media feeds and keyword streams. It features a quantitative trading visualization tool for plotting price action and portfolio equity curves, along with