tvgarch: Time Varying GARCH Modelling

Simulation, estimation and inference for 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. The TV long-term component, as in the multiplicative TV-GARCH model of Amado and Ter\"asvirta (2013) <doi:10.1016/j.jeconom.2013.03.006>, introduces non-stationarity in the variance process, where the GARCH-X short-term component describes conditional heteroscedasticity. Maximisation by parts leads to consistent and asymptotically normal estimates.

Version: 1.0
Depends: R (≥ 3.5.0), garchx, hier.part, matrixStats, numDeriv, zoo
Published: 2021-02-05
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

Downloads:

Reference manual: tvgarch.pdf
Package source: tvgarch_1.0.tar.gz
Windows binaries: r-devel: tvgarch_1.0.zip, r-release: tvgarch_1.0.zip, r-oldrel: tvgarch_1.0.zip
macOS binaries: r-release: tvgarch_1.0.tgz, r-oldrel: tvgarch_1.0.tgz

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