tvgarch: Time Varying GARCH Modelling

Simulation, estimation and inference for univariate and multivariate TV(s)-GARCH(p,q,r)-X models, where s indicates the number and shape of the transition functions, p is the ARCH order, q is the GARCH order, r is the asymmetry order, and 'X' indicates that covariates can be included; see Campos-Martins and Sucarrat (2024) <doi:10.18637/jss.v108.i09>. In the multivariate case, variances are estimated equation by equation and dynamic conditional correlations are allowed. The TV long-term component of the variance as in the multiplicative TV-GARCH model of Amado and Terasvirta (2013) <doi:10.1016/j.jeconom.2013.03.006> introduces non-stationarity whereas the GARCH-X short-term component describes conditional heteroscedasticity. Maximisation by parts leads to consistent and asymptotically normal estimates.

Version: 2.4.2
Depends: R (≥ 3.5.0), garchx, zoo, numDeriv
Published: 2024-04-04
DOI: 10.32614/CRAN.package.tvgarch
Author: Susana Campos-Martins [aut, cre], Genaro Sucarrat [ctb]
Maintainer: Susana Campos-Martins <scmartins at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: tvgarch citation info
Materials: NEWS
CRAN checks: tvgarch results


Reference manual: tvgarch.pdf


Package source: tvgarch_2.4.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): tvgarch_2.4.2.tgz, r-oldrel (arm64): tvgarch_2.4.2.tgz, r-release (x86_64): tvgarch_2.4.2.tgz, r-oldrel (x86_64): tvgarch_2.4.2.tgz
Old sources: tvgarch archive

Reverse dependencies:

Reverse suggests: garchx


Please use the canonical form to link to this page.