Supports teaching methods of estimating and testing time series
factor models for use in robust portfolio construction and analysis. Unique
in providing not only classical least squares, but also modern robust model
fitting methods which are not much influenced by outliers. Includes
returns and risk decompositions, with user choice of standard deviation,
value-at-risk, and expected shortfall risk measures. "Robust Statistics
Theory and Methods (with R)", R. A. Maronna, R. D. Martin, V. J. Yohai,
M. Salibian-Barrera (2019) <doi:10.1002/9781119214656>.
| Version: |
1.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
boot, data.table, lars, lattice, leaps, PerformanceAnalytics, PortfolioAnalytics, R.cache, corpcor, methods, quadprog, RobStatTM, robustbase, sandwich, sn, xts, zoo |
| Suggests: |
corrplot, HH, lmtest, R.rsp, rugarch, strucchange, tinytest |
| Published: |
2023-11-09 |
| DOI: |
10.32614/CRAN.package.facmodTS |
| Author: |
Doug Martin [cre, aut],
Eric Zivot [aut],
Sangeetha Srinivasan [aut],
Avinash Acharya [ctb],
Yi-An Chen [ctb],
Kirk Li [ctb],
Lingjie Yi [ctb],
Justin Shea [ctb],
Mido Shammaa [ctb],
Jon Spinney [ctb] |
| Maintainer: |
Doug Martin <martinrd3d at gmail.com> |
| License: |
GPL-2 |
| URL: |
https://github.com/robustport/facmodTS |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
facmodTS results |