Nothing
sparseIndexTracking: Design of Portfolio of Stocks to Track an Index
Computation of sparse portfolios for financial index tracking, i.e., joint selection of a subset of the assets that compose the index and computation of their relative weights (capital allocation). The level of sparsity of the portfolios, i.e., the number of selected assets, is controlled through a regularization parameter. Different tracking measures are available, namely, the empirical tracking error (ETE), downside risk (DR), Huber empirical tracking error (HETE), and Huber downside risk (HDR). See vignette for a detailed documentation and comparison, with several illustrative examples. The package is based on the paper: K. Benidis, Y. Feng, and D. P. Palomar, "Sparse Portfolios for High-Dimensional Financial Index Tracking," IEEE Trans. on Signal Processing, vol. 66, no. 1, pp. 155-170, Jan. 2018. <doi:10.1109/TSP.2017.2762286>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Konstantinos Benidis [aut], Daniel P. Palomar [cre, aut] |
| Maintainer | Daniel P. Palomar <daniel.p.palomar@gmail.com> |
| License | GPL-3 | file LICENSE |
| Version | 0.1.1 |
| URL | https://CRAN.R-project.org/package=sparseIndexTracking https://github.com/dppalomar/sparseIndexTracking https://www.danielppalomar.com https://doi.org/10.1109/TSP.2017.2762286 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the sparseIndexTracking package in your browser
Any scripts or data that you put into this service are public.
