QuantRocket
A Python-based platform, QuantRocket equips users with robust tools for researching, backtesting, and executing quantitative trading strategies. Its JupyterLab environment allows seamless integration of data and supports diverse backtesting libraries, including Zipline and Moonshot. The open architecture empowers customization, making it ideal for tailored trading solutions.
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Top QuantRocket Features
- Multiple backtesting libraries support
- Fast backtesting speeds
- Extensive data library access
- Custom script integration capabilities
- JupyterLab user interface
- Comprehensive auto-complete documentation
- Real-time market data flexibility
- Docker-based deployment
- Machine learning strategy support
- Survivorship bias-free historical data
- Unrestricted access to selected symbols
- Event-driven or factor-based strategies
- Intuitive API for data handling
- Sample data for learning
- Code example library
- Cross-sectional equity strategy support
- Custom indicators calculation
- Automated daily script scheduling
- Flexible trading strategy customization
- Free tier for learning.
