Product Information
What is Quantrocket?
QuantRocket is a Python-based platform for researching, testing, and trading quantitative strategies. It offers a JupyterLab environment, provides a suite of data integrations, and supports multiple backtesters: Zipline, the open-source backtester originally powering Quantopian; Alphalens, a library for alpha factor analysis; Moonshot, a pandas-based backtester; and MoonshotML, a machine learning backtester. Built on Docker, QuantRocket can be deployed locally or in the cloud, featuring a flexible and scalable open architecture.
How to use Quantrocket?
QuantRocket is a Python-based platform for researching, backtesting, and trading quant strategies, offering flexible, scalable solutions for data-driven traders.
Core Functions of Quantrocket
Trading platform
Python-Based
Algorithmic Trading
Quantitative Data Analysis
Python Integrated Development Environment
Quantitative Data Analysis
Usage Scenarios of Quantrocket
- Research quantitative trading strategies
- Backtest quantitative trading strategies
- Trade quantitative trading strategies
- Use Pipeline to screen and analyze large volumes of securities
- Conduct factor analysis
- Execute automated or manual real-time trading
Common Questions about Quantrocket
What does QuantRocket do?
How do I use QuantRocket?
What are the core features of QuantRocket?
What are the application scenarios of QuantRocket?
