Fast and scalable design of risk parity portfolios
riskParityPortfolio is a software tool focused on the design of risk parity portfolios using fast, accurate, state-of-the-art optimization methods.
The R version of riskParityPortfolio is build on top of awesome R packages including Rcpp, RcppEigen, quadprog, alabama, and nloptr. All these packages can be installed via CRAN.
The Python version depends on numpy.
- The stable R version can be installed via CRAN as
- The development R version can be installed via GitHub as
You must have previously installed the devtools package.
- The stable Python version can be installed via pip as
$ pip install riskparityportfolio
- The development Python version can be installed via GitHub as
$ git clone https://github.com/dppalomar/riskParityPortfolio $ cd python $ pip install -e .
- See the package vignette for a detailed description of the mathematical methods that are available in riskParityPortfolio.
About the project
riskParityPortfolio is distributed by an GPL 3.0 License.
We welcome all sorts of contributions. Please feel free to open an issue to report a bug or discuss a feature request in our GitHub repo.
If this package has been useful to you in any way, give us a star on GitHub :) Additionally, if you’ve used riskParityPortfolio on your research, please consider citing the following resources:
- J. V. de M. Cardoso and D. P. Palomar (2019). riskParityPortfolio: Design of Risk Parity Portfolios. R package version 0.1.1. https://CRAN.R-project.org/package=riskParityPortfolio
- Y. Feng, and D. P. Palomar (2015). SCRIP: Successive Convex Optimization Methods for Risk Parity Portfolio Design. IEEE Trans. on Signal Processing, vol. 63, no. 19, pp. 5285-5300. https://doi.org/10.1109/TSP.2015.2452219
- F. Spinu (2013). An Algorithm for Computing Risk Parity Weights. https://dx.doi.org/10.2139/ssrn.2297383
- T. Griveau-Billion, J. Richard, and T. Roncalli (2013). A fast algorithm for computing high-dimensional risk parity portfolios. https://arxiv.org/pdf/1311.4057.pdf