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tvgarch  

Time Varying GARCH Modelling
View on CRAN: Click here


Download and install tvgarch package within the R console
Install from CRAN:
install.packages("tvgarch")

Install from Github:
library("remotes")
install_github("cran/tvgarch")

Install by package version:
library("remotes")
install_version("tvgarch", "2.4.3")



Attach the package and use:
library("tvgarch")
Maintained by
Susana Campos-Martins
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-05
Latest Update: 2025-09-03
Description:
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.
How to cite:
Susana Campos-Martins (2021). tvgarch: Time Varying GARCH Modelling. R package version 2.4.3, https://cran.r-project.org/web/packages/tvgarch. Accessed 26 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:15), 1.0 (2021-02-05 10:00), 2.0 (2021-04-16 17:50), 2.1 (2021-09-02 08:20), 2.2 (2021-12-21 11:30), 2.3 (2023-01-28 10:50), 2.4.1 (2023-10-01 11:40), 2.4.2 (2024-04-05 01:30), 2.4 (2023-03-08 12:10)
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