Riskfolio-Lib

Quantitative Strategic Asset Allocation, Easy for Everyone.

Description

Riskfolio-Lib is a library for making quantitative strategic asset allocation or portfolio optimization in Python made in Peru 🇵🇪. It is built on top of cvxpy and closely integrated with pandas 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 11 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).
  • Worst Case Realization (Minimax Model)
  • Maximum Drawdown (Calmar Ratio)
  • Average Drawdown
  • Conditional Drawdown at Risk (CDaR).
  • Ulcer Index.

• Risk Parity Portfolio optimization with 8 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).
  • Conditional Drawdown at Risk (CDaR).
  • Ulcer Index.

• Worst Case Mean Variance Portfolio optimization.

• 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 leveraged portfolios.

• Tools for build efficient frontier for 11 risk measures.

• Tools for build linear constraints on assets, asset classes and risk factors.

• Tools for build views on assets and asset classes.

• Tools for calculate risk measures.

• Tools for calculate risk contributions per asset.

• Tools for calculate uncertainty sets for mean vector and covariance matrix.

• Tools for estimate loadings matrix (Stepwise Regression and Principal Components Regression).

• Tools for visualizing portfolio properties and risk measures.

Documentation

Online documentation is available at Documentation.

The docs include a tutorial with examples that shows the capacities of Riskfolio-Lib.

Dependencies

Riskfolio-Lib supports Python 3.7+.

Installation requires:

• numpy >= 1.17.0
• scipy >= 1.1.0
• pandas >= 1.0.0
• matplotlib >= 3.3.0
• cvxpy >= 1.0.15
• scikit-learn >= 0.22.0
• statsmodels >= 0.10.1
• arch >= 4.15

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.

• Mean Entropic Risk Optimization Portfolios.
• 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.