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https://github.com/convexfi/riskparity.py

Fast and scalable construction of risk parity portfolios
https://github.com/convexfi/riskparity.py

finance optimization portfolio-optimization risk-parity

Last synced: about 1 month ago
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Fast and scalable construction of risk parity portfolios

Host: GitHub
URL: https://github.com/convexfi/riskparity.py
Owner: convexfi
License: mit
Created: 2019-07-13T21:30:55.000Z (almost 5 years ago)
Default Branch: main
Last Pushed: 2024-03-02T00:05:14.000Z (3 months ago)
Last Synced: 2024-04-13T21:04:02.124Z (about 1 month ago)
Topics: finance, optimization, portfolio-optimization, risk-parity
Language: Python
Homepage: https://mirca.github.io/riskparity.py/
Size: 3.61 MB
Stars: 273
Watchers: 13
Forks: 64
Open Issues: 4
Metadata Files:
- Readme: README.md
- License: LICENSE

Lists

awesome-quant - riskparity.py - fast and scalable design of risk parity portfolios with TensorFlow 2.0 (Python / Trading & Backtesting)

README

        # riskparity.py

[![PyPI version](https://badge.fury.io/py/riskparityportfolio.svg)](https://badge.fury.io/py/riskparityportfolio)

[![Downloads](https://pepy.tech/badge/riskparityportfolio)](https://pepy.tech/project/riskparityportfolio)

[![codecov](https://codecov.io/gh/mirca/riskparity.py/branch/master/graph/badge.svg)](https://codecov.io/gh/mirca/riskparity.py)

**riskparityportfolio** provides solvers to design risk parity portfolios.

In its simplest form, we consider the convex formulation with a unique solution proposed by

[Spinu (2013)](https://dx.doi.org/10.2139/ssrn.2297383) and use cyclical methods inspired by

[Griveau-Billion et al. (2013)](https://arxiv.org/pdf/1311.4057.pdf)

and [Choi & Chen (2022)](https://www.emerald.com/insight/content/doi/10.1108/JDQS-12-2021-0031/full/pdf). For more general formulations,

which are usually nonconvex, we implement the successive convex approximation

method proposed by [Feng & Palomar (2015)](https://doi.org/10.1109/TSP.2015.2452219).

**Documentation:** [**https://mirca.github.io/riskparity.py**](https://mirca.github.io/riskparity.py)

**R version:** [**https://mirca.github.io/riskParityPortfolio**](https://mirca.github.io/riskParityPortfolio)

**Rust version:** [**https://github.com/mirca/riskparity.rs**](https://github.com/mirca/riskparity.rs)

**Talks**: [**slides HKML meetup 2020**](https://speakerdeck.com/mirca/breaking-down-risk-parity-portfolios-a-practical-open-source-implementation),

[**tutorial - Data-driven Portfolio Optimization Course (HKUST)**](https://www.youtube.com/watch?v=xb1Xxf5LQks)

## Installation

* **development version**

```

$ git clone https://github.com/dppalomar/riskparity.py.git

$ cd riskparity.py

$ pip install -e .

```

* **stable version**

```

$ pip install riskparityportfolio

```

### Windows requirements

Make sure to install [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/)

prior to ``riskparityportfolio``.

``riskparityportfolio`` depends on ``jaxlib`` which can be installed following these

[instructions](https://github.com/cloudhan/jax-windows-builder).

## References

* Spinu, Florin. An Algorithm for Computing Risk Parity Weights (July 30, 2013). Available at SSRN: [https://ssrn.com/abstract=2297383](https://ssrn.com/abstract=2297383).

* Griveau-Billion, Théophile et al. A Fast Algorithm for Computing High-dimensional Risk Parity Portfolios. [https://arxiv.org/abs/1311.4057](https://arxiv.org/abs/1311.4057)

* Feng, Yiyong et al. SCRIP: Successive Convex Optimization Methods for Risk Parity Portfolio Design.

IEEE Transactions on Signal Processing, 2015. [https://ieeexplore.ieee.org/document/7145485](https://ieeexplore.ieee.org/document/7145485)

* Choi, J., & Chen, R. (2022). Improved iterative methods for solving risk parity portfolio. Journal of Derivatives and Quantitative Studies 30(2), 114–124. [https://doi.org/10.1108/JDQS-12-2021-0031](https://doi.org/10.1108/JDQS-12-2021-0031)

## License

Copyright 2022 [Ze Vinicius](https://mirca.github.io) and [Daniel Palomar](https://www.danielppalomar.com)

This project is licensed under the terms of the MIT License.

## Disclaimer

The information, software, and any additional resources contained in this repository are not intended as,

and shall not be understood or construed as, financial advice. Past performance is not a reliable indicator

of future results and investors may not recover the full amount invested.

The [authors](https://github.com/dppalomar/riskParityPortfolio/blob/master/AUTHORS.md) of this repository

accept no liability whatsoever for any loss or damage you may incur.  Any opinions expressed in this repository

are from the personal research and experience of the

[authors](https://github.com/dppalomar/riskParityPortfolio/blob/master/AUTHORS.md) and are intended as

educational material.