Multivariate GARCH models for large-scale applications: A survey

Kris Boudt*, Alexios Galanos, Scott Payseur, Eric Zivot

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review


This chapter provides a survey of various multivariate GARCH specifications that model the temporal dependence in the second moment of multivariate return series processes. The survey is focused on feasible multivariate GARCH models for large-scale applications, as well as on recent contributions in outlier-robust MGARCH analysis and the use of high-frequency returns or the score for covariance modeling. We discuss their likelihood-based estimation and application to forecasting and simulation with software implementations in the R-programming language.

Original languageEnglish
Title of host publicationConceptual Econometrics Using R
EditorsHrishikesh D. Vinod, C.R. Rao
PublisherElsevier Science B.V.
Number of pages50
ISBN (Electronic)9780444641533
ISBN (Print)9780444643117
Publication statusPublished - 2019

Publication series

NameHandbook of Statistics
ISSN (Print)0169-7161


  • Comovement
  • Distribution
  • Time series
  • Volatility


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