Riskfolio-Lib: Quantitative Strategic Asset Allocation, easy for you
Quantitative Strategic Asset Allocation, easy for you.
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.
Online documentation is available at Documentation.
The docs include a tutorial with examples that shows the capacities of Riskfolio-Lib.
Riskfolio-Lib supports Python 3.6+.
- numpy >= 1.17.0
- scipy >= 1.0.1
- pandas >= 1.0.0
- matplotlib >= 3.0.0
- cvxpy >= 1.0.15
- scikit-learn >= 0.22.0
- statsmodels >= 0.10.1
The latest stable release (and older versions) can be installed from PyPI:
pip install riskfolio-lib
Riskfolio-Lib development takes place on Github: https://github.com/dcajasn/Riskfolio-Lib
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size Riskfolio_Lib-0.0.3-py3-none-any.whl (29.2 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size Riskfolio-Lib-0.0.3.tar.gz (3.1 MB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for Riskfolio_Lib-0.0.3-py3-none-any.whl