Fast design of risk parity portfolios for financial investment.
The goal of the risk parity portfolio formulation is to equalize or distribute
the risk contributions of the different assets, which is missing if we simply
consider the overall volatility of the portfolio as in the mean-variance
Markowitz portfolio. In addition to the vanilla formulation, where the risk
contributions are perfectly equalized subject to no shortselling and budget
constraints, many other formulations are considered that allow for box
constraints and shortselling, as well as the inclusion of additional
objectives like the expected return and overall variance. See vignette for
a detailed documentation and comparison, with several illustrative examples.
The package is based on the papers:
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. <doi:10.1109/TSP.2015.2452219>.
F. Spinu (2013), An Algorithm for Computing Risk Parity Weights.
<doi:10.2139/ssrn.2297383>.
T. Griveau-Billion, J. Richard, and T. Roncalli (2013). A fast algorithm for computing
High-dimensional risk parity portfolios. <arXiv:1311.4057>.
bookdown, knitr, numDeriv, prettydoc, rmarkdown, R.rsp,
testthat
bookdown, knitr, prettydoc, rmarkdown, R.rsp

knitr, ggplot2, numDeriv, pagedown, prettydoc, rmarkdown,
R.rsp, testthat, viridisLite

knitr, ggplot2, numDeriv, pagedown, portfolioBacktest,
prettydoc, rmarkdown, R.rsp, testthat, viridisLite

knitr, ggplot2, numDeriv, portfolioBacktest, prettydoc,
rmarkdown, R.rsp, testthat, viridisLite

Assessing Risk Predictions for Clustered Data
c(
person("Bernard", "Rosner", role=c("aut", "ctb"),
email = "stbar@channing.harvard.edu"),
person("Weiliang", "Qiu", role=c("aut", "cre"),
email = "Weiliang.Qiu@gmail.com"),
person("Meiling T.", "Lee", role = c("aut", "ctb"),
email = "MLTLEE@umd.edu")
)
Assessing and comparing risk prediction rules for clustered data. The method is based on the paper: Rosner B, Qiu W, and Lee MLT.(2013) <doi: 10.1007/s10985-012-9240-6>.
Bernard Rosner [aut, ctb],
Weiliang Qiu [aut, cre],
Meiling T. Lee [aut, ctb]