riskParityPortfolio:风险平价投资组合设计

# riskParityPortfolio [](https://CRAN.R-project.org/package=riskParityPortfolio) [](https://CRAN.R-project.org/package=riskParityPortfolio) [](https://CRAN.R-project.org/package=riskParityPortfolio) [](http://www.rcpp.org/) [](https://codecov.io/gh/mirca/riskParityPortfolio) [](https://travis-ci.org/mirca/riskParityPortfolio) [](https://ci.appveyor.com/project/mirca/riskparityportfolio/branch/master) [](https://circleci.com/gh/mirca/riskParityPortfolio) [](https://hub.docker.com/r/mirca/riskparityportfolio/) [](https://dev.azure.com/jvmirca/riskParityPortfolio/_build/latest?definitionId=1&branchName=master) **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)](https://dx.doi.org/10.2139/ssrn.2297383) and use a cyclical method inspired by [Griveau-Billion (2013)](https://arxiv.org/pdf/1311.4057.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). The latest stable version of **riskParityPortfolio** is available at https://CRAN.R-project.org/package=riskParityPortfolio. The latest development version of **riskParityPortfolio** is available at https://github.com/dppalomar/riskParityPortfolio. **Check out the documentation here: [https://mirca.github.io/riskParityPortfolio](https://mirca.github.io/riskParityPortfolio).** ## Installation To install the latest stable version of **riskParityPortfolio** from CRAN, run the following commands in R: ```r > install.packages("riskParityPortfolio") ``` To install the development version of **riskParityPortfolio** from GitHub, run the following commands in R: ```r > install.packages("devtools") > devtools::install_github("dppalomar/riskParityPortfolio") ``` To get help: ```r > library(riskParityPortfolio) > help(package = "riskParityPortfolio") > package?riskParityPortfolio > ?riskParityPortfolio ``` Please cite **riskParityPortfolio** in publications: ```r > citation("riskParityPortfolio") ``` You can also get **riskParityPortfolio** from Docker as follows: ``` $ docker pull mirca/riskparityportfolio ``` #### Microsoft Windows On MS Windows environments, make sure to install the most recent version of **Rtools**. ### Python A Python3 implementation of this package is currently under development at [https://github.com/dppalomar/riskparity.py](https://github.com/dppalomar/riskparity.py). Its stable version is available in PYPI and can be installed as follows: ``` $ pip install riskparityportfolio ``` Alternatively, the development version can be installed as ``` $ git clone https://github.com/dppalomar/riskparity.py $ cd python $ pip install -e . ``` ## Basic usage ```r library(riskParityPortfolio) set.seed(42) # create covariance matrix N <- 5 V <- matrix(rnorm(N^2), ncol = N) Sigma <- cov(V) # risk parity portfolio res <- riskParityPortfolio(Sigma) names(res) #> [1] "w" "relative_risk_contribution" #> [3] "is_feasible" res$w #> [1] 0.32715962 0.27110678 0.14480081 0.09766356 0.15926922 # risk budgeting portfolio res <- riskParityPortfolio(Sigma, b = c(0.4, 0.4, 0.1, 0.05, 0.05)) res$relative_risk_contribution #> [1] 0.40 0.40 0.10 0.05 0.05 ``` ## Documentation For more detailed information, please check the [vignette](https://CRAN.R-project.org/package=riskParityPortfolio/vignettes/RiskParityPortfolio.html). ## Citation If you find this package useful in your research, please consider citing the following works: - J. V. de M. Cardoso and D. P. Palomar (2019). riskParityPortfolio: Design of Risk Parity Portfolios. R package version 0.2.1. <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> ## Contributing We welcome all sorts of contributions. Please feel free to open an issue to report a bug or discuss a feature request. ## Links Package: [CRAN](https://CRAN.R-project.org/package=riskParityPortfolio) and [GitHub](https://github.com/dppalomar/riskParityPortfolio). README file: [GitHub-readme](https://github.com/dppalomar/riskParityPortfolio/blob/master/README.md). Vignettes: [CRAN-vignette](https://CRAN.R-project.org/package=riskParityPortfolio/vignettes/RiskParityPortfolio.html), [slides R/Finance 2019](https://docs.google.com/viewer?url=https://github.com/dppalomar/riskParityPortfolio/raw/master/vignettes/RFinance2019-slides.pdf), [slides RPP - Convex Optimization Course (HKUST)](https://docs.google.com/viewer?url=https://github.com/dppalomar/riskParityPortfolio/raw/master/vignettes/slides-ConvexOptimizationCourseHKUST.pdf), [slides HKML meetup 2020](https://speakerdeck.com/mirca/breaking-down-risk-parity-portfolios-a-practical-open-source-implementation), and [tutorial - Data-driven Portfolio Optimization Course (HKUST)](https://www.youtube.com/watch?v=xb1Xxf5LQks) ## 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.