# Riskfolio-Lib
**Quantitative Strategic Asset Allocation, Easy for Everyone.**
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[](https://github.com/dcajasn/Riskfolio-Lib/stargazers)
[](https://pepy.tech/project/riskfolio-lib)
[](https://riskfolio-lib.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/dcajasn/Riskfolio-Lib/blob/master/LICENSE.txt)
[](https://mybinder.org/v2/gh/dcajasn/Riskfolio-Lib/HEAD)
## Description
Riskfolio-Lib is a library for making quantitative strategic asset allocation
or portfolio optimization in Python made in Peru 🇵🇪. Its objective is to help students, academics and practitioners to build investment portfolios based on mathematically complex models with low effort. 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 functionalities that Riskfolio-Lib offers:
* Mean Risk Portfolio optimization with 4 objective functions:
* Minimum Risk.
* Maximum Return.
* Maximum Utility Function.
* Maximum Risk Adjusted Return Ratio.
* Mean Risk Portfolio optimization with 13 convex risk measures:
* Standard Deviation.
* Semi Standard Deviation.
* Mean Absolute Deviation (MAD).
* First Lower Partial Moment (Omega Ratio)
* Second Lower Partial Moment (Sortino Ratio)
* Conditional Value at Risk (CVaR).
* Entropic Value at Risk (EVaR).
* Worst Case Realization (Minimax Model)
* Maximum Drawdown (Calmar Ratio)
* Average Drawdown
* Conditional Drawdown at Risk (CDaR).
* Entropic Drawdown at Risk (EDaR).
* Ulcer Index.
* Risk Parity Portfolio optimization with 10 convex risk measures:
* Standard Deviation.
* Semi Standard Deviation.
* Mean Absolute Deviation (MAD).
* First Lower Partial Moment (Omega Ratio)
* Second Lower Partial Moment (Sortino Ratio)
* Conditional Value at Risk (CVaR).
* Entropic Value at Risk (EVaR).
* Conditional Drawdown at Risk (CDaR).
* Entropic Drawdown at Risk (EDaR).
* Ulcer Index.
* Worst Case Mean Variance Portfolio optimization.
* Portfolio optimization with Black Litterman model.
* Portfolio optimization with Risk Factors model.
* Portfolio optimization with Black Litterman Bayesian model.
* Portfolio optimization with Augmented Black Litterman model.
* Portfolio optimization with constraints on tracking error and turnover.
* Portfolio optimization with short positions and leveraged portfolios.
* Tools to build efficient frontier for 13 risk measures.
* Tools to build linear constraints on assets, asset classes and risk factors.
* Tools to build views on assets and asset classes.
* Tools to build views on risk factors.
* Tools to calculate risk measures.
* Tools to calculate risk contributions per asset.
* Tools to calculate uncertainty sets for mean vector and covariance matrix.
* Tools to estimate loadings matrix (Stepwise Regression and Principal Components Regression).
* Tools to visualizing portfolio properties and risk measures.
* Tools to build reports on Jupyter Notebook and Excel.
* Option to use commercial optimization solver like MOSEK or GUROBI for large scale problems.
## 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 3.7+.
Installation requires:
* [numpy](http://www.numpy.org/) >= 1.17.0
* [scipy](https://www.scipy.org/) >= 1.1.0
* [pandas](https://pandas.pydata.org/) >= 1.0.0
* [matplotlib](https://matplotlib.org/) >= 3.3.0
* [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
* [arch](https://bashtage.github.io/arch/) >= 4.15
* [xlsxwriter](https://xlsxwriter.readthedocs.io) >= 1.3.7
## 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
## RoadMap
The plan for this module is to add more functions that will be very useful
to asset managers.
* Add Hierarchical Equal Risk Contribution portfolio and other risk parity portfolios based on vanilla risk parity model.
* Add functions to estimate Duration, Convexity, Key Rate Durations and Convexities of bonds without embedded options (for loadings matrix).
* Add more functions based on suggestion of users.
Riskfolio-Lib:Python中的投资组合优化和定量战略资产分配
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Riskfolio-Lib:Python中的投资组合优化和定量战略资产分配 （107个子文件） 
make.bat 756B biblio.bib 27KB setup.cfg 38B assets_data.csv 18.19MB .DS_Store 10KB .DS_Store 6KB .DS_Store 6KB .DS_Store 6KB .DS_Store 6KB .DS_Store 6KB .DS_Store 6KB .gitattributes 66B Tutorial 18.ipynb 1.71MB Tutorial 8.ipynb 803KB Tutorial 7.ipynb 750KB Tutorial 5.ipynb 726KB Tutorial 1.ipynb 690KB Tutorial 2.ipynb 643KB Tutorial 12.ipynb 621KB Tutorial 16.ipynb 527KB Tutorial 21.ipynb 497KB Tutorial 9.ipynb 411KB Tutorial 3.ipynb 403KB Tutorial 11.ipynb 378KB Tutorial 6.ipynb 370KB Tutorial 19.ipynb 363KB Tutorial 14.ipynb 354KB Tutorial 15.ipynb 354KB Tutorial 10.ipynb 351KB Tutorial 20.ipynb 338KB Tutorial 4.ipynb 277KB Tutorial 13.ipynb 231KB Tutorial 17.ipynb 60KB Makefile 7KB Makefile 584B README.md 5KB
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