This repository curates a comprehensive collection of resources for systematic trading, targeting quantitative traders, researchers, and beginners. It provides access to libraries, strategies, books, videos, blogs, and courses, aiming to facilitate the discovery, development, and execution of algorithmic trading strategies.

How It Works

The repository is structured as an "awesome list," categorizing and linking to a wide array of open-source libraries, academic papers, and educational materials. It covers various aspects of quantitative trading, including backtesting frameworks (event-driven and vector-based), trading bots, analytics tools, broker APIs, data sources, and machine learning applications. The content is organized by asset class and functionality, offering a broad overview of the ecosystem.

Quick Start & Requirements

This is a curated list, not a runnable software package. To utilize the listed libraries, users must refer to the individual project repositories for installation and usage instructions. Many libraries are Python-based, often requiring dependencies like NumPy, Pandas, and potentially specialized hardware (e.g., GPUs for ML-heavy tasks) or specific Python versions.

Highlighted Details

• Features over 97 libraries and packages for research and live trading, 40+ described strategies, 55 books, and numerous videos, blogs, and courses.
• Includes detailed categorizations for backtesting frameworks (e.g., backtrader, vectorbt, vnpy), trading bots (e.g., Freqtrade, Hummingbot), and data sources (e.g., yfinance, ccxt).
• Lists academic strategies with performance metrics like Sharpe Ratio and Volatility, categorized by asset class.
• Provides extensive lists of books and video resources for learning quantitative trading and machine learning applications.

Maintenance & Community

The repository is community-driven, encouraging contributions via issue submissions. It links to paperswithbacktest.com for exclusive content and mentions a Chinese version. Specific maintainers or community channels (like Discord/Slack) are not explicitly detailed in the README.

Licensing & Compatibility

The repository itself is a list and does not have a specific license. However, the individual libraries and resources linked within it are subject to their own licenses. Users must consult the licenses of each referenced project for compatibility and usage restrictions, particularly for commercial applications.

Limitations & Caveats

Some listed trading bots and strategies may be outdated or unmaintained, as noted in the README. The repository is a directory of resources, not a unified platform, requiring users to navigate and integrate individual components. Performance metrics for strategies are provided but may vary based on implementation and data.