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fast and scalable design of risk parity portfolios with TensorFlow 2.0
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README.md

riskparity.py

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riskparityportfolio provides tools to design risk parity portfolios. In its simplest form, we consider the convex formulation with a unique solution proposed by Spinu (2013) and use a cyclical method inspired by Griveau-Billion (2013). For more general formulations, which are usually nonconvex, we implement the successive convex approximation method proposed by Feng & Palomar (2015).

Documentation: https://mirca.github.io/riskparity.py

R version: https://mirca.github.io/riskParityPortfolio

Installation

$ git clone https://github.com/dppalomar/riskparity.py.git
$ cd riskparity.py
$ pip install -e .

License

Copyright 2019 Ze Vinicius and Daniel Palomar

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 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 and are intended as educational material.

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