{ "info": { "author": "Stephanie Toper, Andrey Kostin, Aleksey Zemnitskiy", "author_email": "stephanie.toper@portfolioeffect.com, andrey.kostin@portfolioeffect.com, aleksey.zemnitskiy@portfolioeffect.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Topic :: Office/Business :: Financial :: Investment" ], "description": "# Portfolioeffect hft Package for Python \n\nPython API to PortfolioEffect cloud service for backtesting high frequency trading (HFT) strategies, \nintraday portfolio analysis and optimization. Includes auto-calibrating model pipeline for market\nmicrostructure noise, risk factors, price jumps/outliers, tail risk (high-order moments) and price \nfractality (long memory). Constructed portfolios could use client-side market data or access HF \nintraday price history for all major US Equities.\n\n## Package Installation\n\n\tpython setup.py install\n\n## License\n\nThis package is released under the GPLv3 license. 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