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        "author": "Xavier Bruhiere",
        "author_email": "xavier.bruhiere@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Topic :: Office/Business :: Financial",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: System :: Distributed Computing"
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        "description": "Portfolio\n=========\n\n[![Build Status](https://api.shippable.com/projects/53ce99a67c72335f045a19bb/badge/master)](https://www.shippable.com/projects/53ce99a67c72335f045a19bb)\n[![Coverage Status](https://img.shields.io/coveralls/intuition-io/portfolio.svg)](https://coveralls.io/r/intuition-io/portfolio)\n[![Code Health](https://landscape.io/github/intuition-io/portfolio/master/landscape.png)](https://landscape.io/github/intuition-io/portfolio/master)\n[![Requirements Status](https://requires.io/github/intuition-io/portfolio/requirements.png?branch=master)](https://requires.io/github/intuition-io/portfolio/requirements/?branch=master)\n[![License](https://pypip.in/license/intuition/badge.png)](https://pypi.python.org/pypi/intuition/)\n[![Gitter chat](https://badges.gitter.im/intuition-io.png)](https://gitter.im/intuition-io)\n\n> [Zipline][1] compatible extension of Portfolio, with analytics superpowers.\n> Inspired by [PortfolioAnalytics][6] R package.\n\nThe project provides several portfolio optimizations that compute optimal\nassets allocation regarding a various set of factors and constraints. Currently\nyou will get the following implementations :\n\n* [General optimization problem with solvers][7]\n* [Global Minimum Variance][8]\n* [Kelly criterion][9]\n\nTo learn more about the API, check [the full documentation][3].\n\nThis project is currently part of the **intuition project**, signup for [the\nprivate beta][2] and/or [clone your own hedge fund][4].\n\nFinally, the whole thing is compatible with [zipline backtester][1].\n\n\nInstall\n-------\n\n```\n$ # Before I setup a package on pypi, yo can get it from source\n$ git clone https://github.com/intuition-io/portfolio\n$ cd portfolio && make\n... blablabla it compiles a lot of maths ...\n```\n\nA taste of it\n-------------\n\n```python\n# Download some historical data\nfrom pandas.io.data import get_data_google\nohlc_data = get_data_google(['adsk', 'ctxs', 'fb', 'nflx', 'qcom'], start='2013/01/01', end='2013/12/01')\ndata = ohlc_data['Close']\n\n# Now let's optimize our portfolio weights\nfrom portfolio.optimizations.solvers import SolverPortfolio\nimport portfolio.objectives as objective\nimport portfolio.constraints as constraint\n\nportfolio = SolverPortfolio(objective.risk)\n# Forbid short positions\nportfolio.add_constraint(constraint.long_only())\n# Invest every cent of our cash\nportfolio.add_constraint(constraint.full_investment())\n\n# Get optimal weights in %\npf.optimize(['ctxs', 'fb', 'nflx', 'qcom', 'adsk'], data)\nOut[66]:\n{'adsk': 0.49,\n 'ctxs': 0.04,\n 'fb': 0.17,\n 'nflx': 0.0,\n 'qcom': 0.29}\n```\n\nContributing\n------------\n\nContributors are happily welcome, [here is a place to start][10].\n\n\nLicense\n-------\n\nCopyright 2014 Xavier Bruhiere.\n\n*Portfolio* is available under the [Apache License, Version 2.0][5].\n\n\n[1]: https://github.com/quantopian/zipline\n[2]: http://intuition.io\n[3]: http://doc.intuition.io\n[4]: https://github.com/intuition-io/intuition\n[5]: http://www.apache.org/licenses/LICENSE-2.0.html\n[6]: https://r-forge.r-project.org/R/?group_id=579\n[7]: http://docs.scipy.org/doc/scipy/reference/optimize.html\n[8]: http://www.investopedia.com/terms/p/portfolio-variance.asp\n[9]: http://www.investopedia.com/articles/trading/04/091504.asp\n[10]: http://doc.intuition.io/articles/contributors.html",
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