garchx: Flexible and Robust GARCH-X Modeling

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.

Genaro Sucarrat

CRAN packages used

tseries, fGarch, rugarch, xts, zoo, microbenchmark

CRAN Task Views implied by cited packages

Finance, TimeSeries, Econometrics, Environmetrics, MissingData, SpatioTemporal


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For attribution, please cite this work as

Sucarrat, "The R Journal: garchx: Flexible and Robust GARCH-X Modeling", {The R Journal}, 2020

BibTeX citation

  author = {Sucarrat, Genaro},
  title = {The R Journal: garchx: Flexible and Robust GARCH-X Modeling},
  journal = {{The R Journal}},
  year = {2020},
  note = {},
  doi = {10.32614/RJ-2021-057},
  volume = {13},
  issue = {1},
  issn = {2073-4859},
  pages = {276-291}