Metadata-Version: 1.1
Name: portfolio-analytics
Version: 0.0.1
Summary: Keep calm and optimize.
Home-page: https://github.com/intuition-io/portfolio
Author: Xavier Bruhiere
Author-email: xavier.bruhiere@gmail.com
License: Apache 2.0
Description: Portfolio
        =========
        
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        > [Zipline][1] compatible extension of Portfolio, with analytics superpowers.
        > Inspired by [PortfolioAnalytics][6] R package.
        
        The project provides several portfolio optimizations that compute optimal
        assets allocation regarding a various set of factors and constraints. Currently
        you will get the following implementations :
        
        * [General optimization problem with solvers][7]
        * [Global Minimum Variance][8]
        * [Kelly criterion][9]
        
        To learn more about the API, check [the full documentation][3].
        
        This project is currently part of the **intuition project**, signup for [the
        private beta][2] and/or [clone your own hedge fund][4].
        
        Finally, the whole thing is compatible with [zipline backtester][1].
        
        
        Install
        -------
        
        ```
        $ # Before I setup a package on pypi, yo can get it from source
        $ git clone https://github.com/intuition-io/portfolio
        $ cd portfolio && make
        ... blablabla it compiles a lot of maths ...
        ```
        
        A taste of it
        -------------
        
        ```python
        # Download some historical data
        from pandas.io.data import get_data_google
        ohlc_data = get_data_google(['adsk', 'ctxs', 'fb', 'nflx', 'qcom'], start='2013/01/01', end='2013/12/01')
        data = ohlc_data['Close']
        
        # Now let's optimize our portfolio weights
        from portfolio.optimizations.solvers import SolverPortfolio
        import portfolio.objectives as objective
        import portfolio.constraints as constraint
        
        portfolio = SolverPortfolio(objective.risk)
        # Forbid short positions
        portfolio.add_constraint(constraint.long_only())
        # Invest every cent of our cash
        portfolio.add_constraint(constraint.full_investment())
        
        # Get optimal weights in %
        pf.optimize(['ctxs', 'fb', 'nflx', 'qcom', 'adsk'], data)
        Out[66]:
        {'adsk': 0.49,
         'ctxs': 0.04,
         'fb': 0.17,
         'nflx': 0.0,
         'qcom': 0.29}
        ```
        
        Contributing
        ------------
        
        Contributors are happily welcome, [here is a place to start][10].
        
        
        License
        -------
        
        Copyright 2014 Xavier Bruhiere.
        
        *Portfolio* is available under the [Apache License, Version 2.0][5].
        
        
        [1]: https://github.com/quantopian/zipline
        [2]: http://intuition.io
        [3]: http://doc.intuition.io
        [4]: https://github.com/intuition-io/intuition
        [5]: http://www.apache.org/licenses/LICENSE-2.0.html
        [6]: https://r-forge.r-project.org/R/?group_id=579
        [7]: http://docs.scipy.org/doc/scipy/reference/optimize.html
        [8]: http://www.investopedia.com/terms/p/portfolio-variance.asp
        [9]: http://www.investopedia.com/articles/trading/04/091504.asp
        [10]: http://doc.intuition.io/articles/contributors.html
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: System :: Distributed Computing
