The garchx package provides a user-friendly, fast, flexible, and robust framework for the estimation and inference of GARCH(\(p,q,r\))-X models, where \(p\) is the ARCH order, \(q\) is the GARCH order, \(r\) is the asymmetry or leverage order, and ‘X’ indicates that covariates can be included. Quasi Maximum Likelihood (QML) methods ensure estimates are consistent and standard errors valid, even when the standardized innovations are non-normal or dependent, or both. Zero-coefficient restrictions by omission enable parsimonious specifications, and functions to facilitate the non-standard inference associated with zero-restrictions in the null-hypothesis are provided. Finally, in the formal comparisons of precision and speed, the garchx package performs well relative to other prominent GARCH-packages on CRAN.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2021-057.zip
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For attribution, please cite this work as
Sucarrat, "garchx: Flexible and Robust GARCH-X Modeling", The R Journal, 2021
BibTeX citation
@article{RJ-2021-057,
author = {Sucarrat, Genaro},
title = {garchx: Flexible and Robust GARCH-X Modeling},
journal = {The R Journal},
year = {2021},
note = {https://doi.org/10.32614/RJ-2021-057},
doi = {10.32614/RJ-2021-057},
volume = {13},
issue = {1},
issn = {2073-4859},
pages = {335-350}
}