Mean Variance Portfolio
MV Port is a Python package to perform Mean-Variance Analysis. It provides a Portfolio class with a variety of methods to help on your portfolio optimization tasks.
Free software: MIT license
Documentation: https://mvport.readthedocs.io.
Features
Easy portfolio setup
Portfolio evaluation
Random portfolio allocation
Minimum Variance Portfolio optimization
Efficient Frontier evaluation
Tangency Portfolio for a given risk free return rate
Installation
To install MV Port, run this command in your terminal:
$ pip install mvportCheck here for further information on installation.
Basic Usage
Instantiate a portfolio and add some stock and evaluate it given a set of weights:
>>> import mvport as mv
>>> p = mv.Portfolio()
>>> p.add_stock('AAPL', [.1,.2,.3])
>>> p.add_stock('AMZN', [.1,.3,.5])
>>> mean, variance, sharp_ratio, weights = p.evaluate([.5, .5])
>>> print '{} +- {}'.format(mean, variance)
0.25 +- 0.0225Check here for further information on usage.
History
1.0.0 (2018-06-28)
First release on PyPI.
Stock class implemented.
Portfolio class implemented.
Minimum Variance Portfolio optimization
Efficient Frontier evaluation
Tangency Portfolio for a given risk free return rate
1 maintainer
Metadata
1 maintainer
Release files for mean-variance-portfolio 1.0.0
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| File | Interpreter | ABI | Platform | Actions Reset |
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Total release size: 22.2 kB
Release files / mean-variance-portfolio-1.0.0.tar.gz
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Release files / mean_variance_portfolio-1.0.0-py2.py3-none-any.whl
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