Metadata-Version: 2.1
Name: Riskfolio-Lib
Version: 0.0.1
Summary: Riskfolio-Lib: Quantitative Strategic Asset Allocation, easy for you
Home-page: https://riskfolio-lib.readthedocs.io/en/latest/
Author: Dany Cajas
Author-email: dany.cajas.n@uni.pe
Maintainer: Dany Cajas
Maintainer-email: dany.cajas.n@uni.pe
License: BSD (3-clause)
Download-URL: https://github.com/dcajasn/Riskfolio-Lib.git
Description: # Riskfolio-Lib
        
        **Quantitative Strategic Asset Allocation, easy for you.**
        
        <div class="row">
        <img src="https://raw.githubusercontent.com/dcajasn/Riskfolio-Lib/master/docs/source/images/MSV_Frontier.png" height="200">
        <img src="https://raw.githubusercontent.com/dcajasn/Riskfolio-Lib/master/docs/source/images/Pie_Chart.png" height="200">
        </div>
        
        
        ## Description
        
        Riskfolio-Lib is a library for making quantitative strategic asset allocation
        or portfolio optimization in Python. It is built on top of
        [cvxpy](https://www.cvxpy.org/) and closely integrated
        with [pandas](https://pandas.pydata.org/) data structures.
        
        Some of key functionality that Riskfolio-Lib offers:
        
        * Portfolio optimization with 4 objective functions (Minimum Risk, Maximum Return, Maximum Risk Adjusted Return Ratio and Maximum Utility Function)
        * Portfolio optimization with 10 convex risk measures (Std. Dev., MAD, CVaR, Maximum Drawdown, among others)
        * Portfolio optimization with Black Litterman model.
        * Portfolio optimization with Risk Factors model.
        * Portfolio optimization with constraints on tracking error and turnover.
        * Portfolio optimization with short positions and leverage.
        * Tools for construct efficient frontier for 10 risk measures.
        * Tools for construct linear constraints on assets, asset classes and risk factors.
        * Tools for construct views on assets and asset classes.
        * Tools for calculate risk measures.
        * Tools for visualizing portfolio properties and risk measures.
        
        
        ## Documentation
        
        Online documentation is available at [Documentation](https://riskfolio-lib.readthedocs.io/en/latest/).
        
        The docs include a [tutorial](https://riskfolio-lib.readthedocs.io/en/latest/examples.html)
        with examples that shows the capacities of Riskfolio-Lib.
        
        
        ## Dependencies
        
        Riskfolio-Lib supports Python 3.6+.
        
        Installation requires:
        * [numpy](http://www.numpy.org/) >= 1.17.0
        * [scipy](https://www.scipy.org/) >= 1.0.1
        * [pandas](https://pandas.pydata.org/) >= 1.0.0
        * [matplotlib](https://matplotlib.org/) >= 3.0.0
        * [cvxpy](https://www.cvxpy.org/) >= 1.0.15
        * [scikit-learn](https://scikit-learn.org/stable/) >= 0.22.0
        * [statsmodels](https://www.statsmodels.org/) >= 0.10.1
        
        ## Installation
        
        The latest stable release (and older versions) can be installed from PyPI:
        
            pip install riskfolio-lib
        
         
        ## Development
        
        Riskfolio-Lib development takes place on Github: https://github.com/dcajasn/Riskfolio-Lib
        
Platform: UNKNOWN
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Office/Business :: Financial
Classifier: Operating System :: Microsoft
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Requires-Python: >=3.6
Description-Content-Type: text/markdown
