This repository provides a comprehensive, one-stop platform for AI-driven quantitative trading, targeting both institutional and retail traders, including those with and without programming experience. It aims to simplify the entire trading workflow from learning and strategy development to simulation and live deployment, covering diverse markets like stocks, funds, and cryptocurrencies.

How It Works

The platform integrates a wide array of quantitative trading methodologies, including traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, and high-frequency trading. It emphasizes practical application with numerous examples and code implementations, facilitating factor mining, text analysis for market sentiment, and large language model integration for financial market analysis. The architecture supports local deployment across Python and C++ environments, with options for CPU and GPU acceleration.

Quick Start & Requirements

• Install dependencies: pip install -r requirements.txt
• Requires Python. Specific version not stated.
• Links to documentation and examples are provided within the README for each specific strategy.

Highlighted Details

• Features reinforcement learning strategies with reported 53% annualized returns on US stocks.
• Includes machine learning for automatic mining of 5000 factors and stock trend prediction.
• Offers StructBERT for market sentiment analysis.
• Provides examples for local simulation using Wind data and integration with online platforms like JoinQuant.

Maintenance & Community

The project is actively maintained by charliedream1. Further community engagement and support are available via Github Discussions and Issues. Paid resources are offered through "Knowledge Planets" for more in-depth tutorials and support.

Licensing & Compatibility

The repository's primary license is not explicitly stated in the README. However, the inclusion of specific platform code (e.g., JoinQuant) may be subject to those platforms' terms of service. Commercial use compatibility is not detailed.

Limitations & Caveats

A significant portion of advanced code and tutorials are exclusively available through paid "Knowledge Planets," with the public repository serving as a partial showcase. Some strategy examples are noted as not having undergone full-cycle validation or optimization, requiring caution for live trading.