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. 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 Ter{\"a}svirta (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:	2.2
Depends:	R (≥ 3.5.0), garchx, zoo, numDeriv, hier.part
Published:	2021-12-21
Author:	Susana Campos-Martins [aut, cre], Genaro Sucarrat [ctb]
Maintainer:	Susana Campos-Martins <susana.martins at nuffield.ox.ac.uk>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://sites.google.com/site/susanacamposmartins
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	tvgarch results

Documentation:

Reference manual:

tvgarch.pdf

Downloads:

Package source:	tvgarch_2.2.tar.gz
Windows binaries:	r-devel: tvgarch_2.2.zip, r-release: tvgarch_2.2.zip, r-oldrel: tvgarch_2.2.zip
macOS binaries:	r-release (arm64): tvgarch_2.2.tgz, r-oldrel (arm64): tvgarch_2.2.tgz, r-release (x86_64): tvgarch_2.2.tgz, r-oldrel (x86_64): tvgarch_2.2.tgz
Old sources:	tvgarch archive

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