Metadata-Version: 2.1
Name: Riskfolio-Lib
Version: 0.0.3
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
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
Requires-Dist: numpy (>=1.17.0)
Requires-Dist: scipy (>=1.0.1)
Requires-Dist: pandas (>=1.0.0)
Requires-Dist: matplotlib (>=3.0.0)
Requires-Dist: cvxpy (>=1.0.25)
Requires-Dist: scikit-learn (>=0.22.0)
Requires-Dist: statsmodels (>=0.10.1)

# 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


