The R Journal: accepted article

This article will be copy edited and may be changed before publication.

garchx: Flexible and Robust GARCH-X Modelling PDF download
Genaro Sucarrat

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 standardised 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 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
CRAN packages: tseries, fGarch, rugarch, garch, xts, zoo, microbenchmark
CRAN Task Views implied by cited CRAN packages: Finance, TimeSeries, Econometrics, Environmetrics, MissingData, SpatioTemporal

CC BY 4.0
This article is licensed under a Creative Commons Attribution 4.0 International license.

  author = {Genaro Sucarrat},
  title = {{garchx: Flexible and Robust GARCH-X Modelling}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-057},
  url = {}