This repository is a curated list of open-source libraries, packages, and resources for systematic (quantitative) trading across various financial markets like stocks, crypto, futures, and options. It aims to provide a comprehensive and organized collection for quantitative traders, researchers, and developers interested in building and implementing algorithmic trading strategies.

How It Works

The repository categorizes resources into logical sections, covering AI-powered systems, backtesting frameworks, general-purpose components, data sources, analytic tools, and machine learning libraries. Projects are selected based on their relevance to systematic trading, coding style, and development activity, prioritizing quality and promise over sheer quantity.

Quick Start & Requirements

This is a curated list, not a runnable project. To use any of the listed tools, refer to their individual repositories for installation and usage instructions.

Highlighted Details

• Extensive coverage of Python-based quantitative trading frameworks, including popular choices like backtrader, zipline, vectorbt, and QUANTAXIS.
• Significant focus on AI and Machine Learning applications in trading, featuring libraries like FinRL, FinGPT, and QLib.
• Includes resources for various asset classes (stocks, crypto, futures, options) and trading styles (arbitrage, trend following, market making).
• Provides a broad spectrum of fundamental libraries for data analysis, computation, and visualization, such as Pandas, NumPy, SciPy, and Matplotlib.

Maintenance & Community

The repository is community-driven, encouraging contributions via Pull Requests to add new projects or update existing ones. Links to specific community channels are not provided within the README.

Licensing & Compatibility

Projects listed vary in their licensing. The repository itself grants open access under MIT or CC-BY licenses. Users must verify the licenses of individual projects for compatibility with commercial or closed-source applications.

Limitations & Caveats

Some older projects, particularly in crypto arbitrage, are noted as not actively maintained. The breadth of the list means users must independently vet each tool for suitability, performance, and current support status.