The R Journal: article published in 2021, volume 13:1

garchx: Flexible and Robust GARCH-X Modeling
Genaro Sucarrat , The R Journal (2021) 13:1, pages 276-291.

Abstract 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.

Received: 2020-06-03; online 2021-06-22, supplementary material, (3.4 KiB)
CRAN packages: tseries, fGarch, rugarch, xts, zoo, microbenchmark
CRAN Task Views implied by cited CRAN packages: Finance, TimeSeries, Econometrics, Environmetrics, MissingData, SpatioTemporal

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-057,
  author = {Genaro Sucarrat},
  title = {{garchx: Flexible and Robust GARCH-X Modeling}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-057},
  url = {https://doi.org/10.32614/RJ-2021-057},
  pages = {276--291},
  volume = {13},
  number = {1}
}