QuantumAlpha is a cutting-edge AI-driven hedge fund platform that combines machine learning, deep learning, and reinforcement learning techniques with alternative data sources to generate alpha in financial markets. This comprehensive documentation covers all aspects of the platform, from installation to advanced usage.
- Installation Guide - Setup instructions for all platforms
- Quick Start - Basic usage patterns and workflows
- Configuration - Environment variables and configuration files
- Architecture - System design and component mapping
- Feature Matrix - Complete feature overview with examples
- API Reference - Public API endpoints and parameters
- CLI Reference - Command-line interface documentation
- Examples - Working code examples
- Troubleshooting - Common issues and solutions
- Contributing - Development guidelines
# 1. Clone the repository
git clone https://github.com/quantsingularity/QuantumAlpha.git && cd QuantumAlpha
# 2. Setup environment
./scripts/setup_env.sh
# 3. Start the platform
docker-compose upAccess the dashboard at http://localhost:3000 and API at http://localhost:8080.
| Feature | Description |
|---|---|
| AI Models | LSTM, XGBoost, BERT sentiment analysis, reinforcement learning agents |
| Alternative Data | News sentiment, satellite imagery, supply chain indicators |
| Risk Management | Bayesian VaR, stress testing, Kelly criterion position sizing |
| Execution | Smart order routing, TWAP/VWAP algorithms, broker integration |
| Monitoring | Real-time P&L dashboard, risk alerts, model performance tracking |
QuantumAlpha consists of five primary microservices:
| Service | Port | Description |
|---|---|---|
| Data Service | 8081 | Market data ingestion and alternative data processing |
| AI Engine | 8082 | Model training, prediction generation, RL agents |
| Risk Service | 8083 | Risk calculation, stress testing, position sizing |
| Execution Service | 8084 | Order management, broker integration, execution algorithms |
| API Gateway | 8080 | Unified API endpoint and request routing |
- Backend: Python 3.10+, Flask, TensorFlow, PyTorch, scikit-learn
- Frontend: React, TypeScript, Material-UI, D3.js, Plotly
- Databases: PostgreSQL (TimescaleDB), Redis, InfluxDB, MongoDB
- Messaging: Apache Kafka, Redis Streams
- Infrastructure: Docker, Kubernetes, Prometheus, Grafana
- GitHub Repository: https://github.com/quantsingularity/QuantumAlpha
- Issue Tracker: https://github.com/quantsingularity/QuantumAlpha/issues
- License: MIT
Throughout this documentation:
code blocksrepresent commands, code snippets, or configuration- Bold text highlights important concepts or warnings
- Italic text denotes file paths or variable names
- Tables provide structured reference information
Next Steps: Start with the Installation Guide to set up your development environment.
See ML_MODEL_PERFORMANCE.md for full model evaluation results.