Skip to main content

Riskfolio-Lib

Quantitative Strategic Asset Allocation, Easy for Everyone.

Buy Me a Coffee at ko-fi.com

GitHub stars Downloads Documentation Status GitHub license Binder

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 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 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.

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

Dependencies

Riskfolio-Lib supports Python 3.7+.

Installation requires:

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.

Metadata

Release files for riskfolio-lib 0.1.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for riskfolio-lib 0.1.5
File Size Uploaded
Riskfolio-Lib-0.1.5.tar.gz 4.2 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for riskfolio-lib 0.1.5
File Interpreter ABI Platform
Riskfolio_Lib-0.1.5-py3-none-any.whl Python 3 none any Details

Total release size: 4.3 MB

Release files / Riskfolio-Lib-0.1.5.tar.gz

Download URL Riskfolio-Lib-0.1.5.tar.gz
Size 4.2 MB
Tags Source
SHA-256 checksum
How to use checksums
3c3e6a0418535dcdc1475f3205ed07bd57f9ec198e99d7b26366b3b1783dc9d7
BLAKE2b-256 checksum
How to use checksums
017a7a0a50793e579a631d684704fc1893eda2e19d9cc20225d353a98a0a04bb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/51.3.3.post20210118 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5

Release files / Riskfolio_Lib-0.1.5-py3-none-any.whl

Download URL Riskfolio_Lib-0.1.5-py3-none-any.whl
Size 45.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1d73e0b5a8886b7c455026f8186caa72d8fe6555835baaa294bf88fb564cc755
BLAKE2b-256 checksum
How to use checksums
f67c791813216506f50d4342cd13784221f8adad303799a6ed0014cc968a4b8e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/51.3.3.post20210118 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5

Release history Release notifications | RSS feed

7.3.0

26 release files

7.2.1

31 release files

7.1.0

26 release files

7.0.0

26 release files

6.2.3

21 release files

6.2.2

21 release files

6.2.0

21 release files

6.1.1

26 release files

6.1.0

26 release files

5.0.1

20 release files

4.4.0

20 release files

4.1.0

20 release files

4.0.3

2 release files

4.0.2

2 release files

4.0.1

2 release files

4.0.0

2 release files

3.3.0

2 release files

3.2.0

2 release files

3.1.1

2 release files

3.1.0

2 release files

3.0.2

2 release files

3.0.1

2 release files

3.0.0

2 release files

2.0.0

2 release files

1.0.2

2 release files

1.0.1

2 release files

1.0.0

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.0

2 release files

This release

0.1.5 This release

2 release files

0.1.4

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

0.0.7

2 release files

0.0.6

2 release files

0.0.5

2 release files

0.0.4

2 release files

0.0.3

2 release files

0.0.2

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page