This project provides a comprehensive, production-ready quantitative trading system designed for traders and quantitative analysts. It offers an end-to-end pipeline from data collection and AI-powered analysis to strategy execution and risk management, aiming to deliver high-performance, low-latency trading capabilities.

How It Works

The system employs a hybrid architecture, with a Python layer handling data services, AI/ML integration, factor analysis, backtesting, and visualization. A C++ core engine is responsible for low-latency order execution, risk management, and portfolio operations. This separation allows for optimized performance in critical execution paths while leveraging Python's extensive libraries for data science and AI.

Quick Start & Requirements

• Installation: pip install -e .[ai,visualization,realtime,web]
• Prerequisites: Python 3.8+, C++17 compatible compiler, CMake 3.12+. Optional API keys for Binance, OpenAI, and Alpha Vantage.
• Running: python run_dashboard.py or python run_web_interface.py.
• Documentation: Module Documentation

Highlighted Details

• Integrates OpenAI GPT for market analysis and strategy recommendations.
• Features a C++ core engine for high-performance, low-latency order execution.
• Supports real-time market data via WebSocket connections.
• Includes 8+ built-in quantitative strategies and an extensible strategy framework.
• Offers interactive dashboards using Streamlit and a FastAPI-based web interface.

Maintenance & Community

The project is community-driven, with a call for contributions. Details on development setup and testing are provided.

Licensing & Compatibility

Licensed under the MIT License, permitting commercial use and closed-source linking.

Limitations & Caveats

The project is intended for educational and research purposes; trading involves substantial risk. API keys are optional but required for full functionality with specific data sources and AI features.