.. module:: zipline
Python is quickly becoming the glue language which holds together data science and related fields like quantitative finance. Zipline is a new, BSD-licensed quantitative trading system which allows easy backtesting of investment algorithms on historical data. The system is fundamentally event-driven and a close approximation of how live-trading systems operate. Moreover, Zipline comes "batteries included" as many common statistics like moving average and linear regression can be readily accessed from within a user-written algorithm. Input of historical data and output of performance statistics is based on Pandas DataFrames to integrate nicely into the existing Python eco-system. Furthermore, statistic and machine learning libraries like matplotlib, scipy, statsmodels, and sklearn support development, analysis and visualization of state-of-the-art trading systems.
Zipline is currently used in production as the backtesting engine powering quantopian.com -- a free, community-centered platform that allows development and real-time backtesting of trading algorithms in the web browser.
- Ease of use: Zipline tries to get out of your way so that you can focus on algorithm development. See below for a code example.
- Zipline comes "batteries included" as many common statistics like moving average and linear regression can be readily accessed from within a user-written algorithm.
- Input of historical data and output of performance statistics is based on Pandas DataFrames to integrate nicely into the existing Python eco-system.
- Statistic and machine learning libraries like matplotlib, scipy, statsmodels, and sklearn support development, analysis and visualization of state-of-the-art trading systems.
.. toctree:: :maxdepth: 4 manifesto.rst installation.rst quickstart.rst contributing.rst modules.rst