ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. Resource summary: network-wide resource summary, practical cases, paper interpretation, and code implementation.
Features
- Extensive knowledge base delivered via Markdown and Jupyter Notebooks (AI foundations, trading concepts, etc.)
- Multiple strategy examples including traditional, machine learning, deep learning, reinforcement learning, graph neural networks, and high-frequency trading
- Integrated factor mining and quantitative analytics in Python
- Support for C++ deployment and live trading simulations
- Tutorials and hands-on examples for real-world strategy implementation
- Designed for both beginners and advanced users to learn, simulate, and deploy strategies
Project Samples
