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Thomas Wiecki
65 lines
2.4 KiB
ReStructuredText
65 lines
2.4 KiB
ReStructuredText
.. Zipline documentation master file, created by
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sphinx-quickstart on Wed Feb 8 15:29:56 2012.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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.. module:: zipline
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****************************************************
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Zipline: Financial Backtester for Trading Algorithms
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****************************************************
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Python is quickly becoming the glue language which holds together data science
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and related fields like quantitative finance. Zipline is a new, BSD-licensed
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quantitative trading system which allows easy backtesting of investment
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algorithms on historical data. The system is fundamentally event-driven and a
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close approximation of how live-trading systems operate. Moreover, Zipline
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comes "batteries included" as many common statistics like
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moving average and linear regression can be readily accessed from within a
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user-written algorithm. Input of historical data and output of performance
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statistics is based on Pandas DataFrames to integrate nicely into the existing
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Python eco-system. Furthermore, statistic and machine learning libraries like
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matplotlib, scipy, statsmodels, and sklearn support development, analysis and
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visualization of state-of-the-art trading systems.
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Zipline is currently used in production as the backtesting engine
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powering `quantopian.com <https://app.quantopian.com>`_ -- a free, community-centered
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platform that allows development and real-time backtesting of trading
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algorithms in the web browser.
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Features
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========
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* Ease of use: Zipline tries to get out of your way so that you can focus on
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algorithm development. See below for a code example.
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* Zipline comes "batteries included" as many common statistics like moving
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average and linear regression can be readily accessed from within a
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user-written algorithm.
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* Input of historical data and output of performance statistics is based on
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Pandas DataFrames to integrate nicely into the existing Python eco-system.
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* Statistic and machine learning libraries like matplotlib, scipy, statsmodels,
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and sklearn support development, analysis and visualization of
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state-of-the-art trading systems.
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Contents
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========
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.. toctree::
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:maxdepth: 4
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manifesto.rst
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installation.rst
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quickstart.rst
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contributing.rst
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modules.rst
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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