MSGARCH: Markov-Switching GARCH Models

Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.

Version: 2.42
Imports: Rcpp, coda, methods, zoo, expm, fanplot, MASS, numDeriv
LinkingTo: Rcpp, RcppArmadillo
Suggests: mcmc, testthat
Published: 2020-04-20
Author: David Ardia ORCID iD [aut], Keven Bluteau ORCID iD [aut, cre], Kris Boudt ORCID iD [ctb], Leopoldo Catania ORCID iD [aut], Alexios Ghalanos [ctb], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]
Maintainer: Keven Bluteau <Keven.Bluteau at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: see file COPYRIGHTS
NeedsCompilation: yes
Citation: MSGARCH citation info
Materials: NEWS
In views: Finance
CRAN checks: MSGARCH results


Reference manual: MSGARCH.pdf
Package source: MSGARCH_2.42.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: MSGARCH_2.42.tgz, r-oldrel: MSGARCH_2.42.tgz
Old sources: MSGARCH archive

Reverse dependencies:

Reverse imports: MSGARCHelm, SBAGM


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