Flexible and robust estimation and inference of generalised autoregressive conditional heteroscedasticity (GARCH) models with covariates ('X') based on the results by Francq and Thieu (2018) <doi:10.1017/S0266466617000512>. Coefficients can straightforwardly be set to zero by omission, and quasi maximum likelihood methods ensure estimates are generally consistent and inference valid, even when the standardised innovations are non-normal and/or dependent over time.
Version: | 1.3 |
Depends: | R (≥ 3.4.0), zoo |
Published: | 2021-07-15 |
Author: | Genaro Sucarrat [aut, cre] |
Maintainer: | Genaro Sucarrat <gsucarrat at gmail.com> |
BugReports: | https://github.com/gsucarrat/garchx/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | http://www.sucarrat.net/ |
NeedsCompilation: | yes |
Materials: | NEWS |
In views: | Finance |
CRAN checks: | garchx results |
Reference manual: | garchx.pdf |
Package source: | garchx_1.3.tar.gz |
Windows binaries: | r-devel: garchx_1.3.zip, r-release: garchx_1.3.zip, r-oldrel: garchx_1.3.zip |
macOS binaries: | r-release (arm64): garchx_1.3.tgz, r-oldrel (arm64): garchx_1.3.tgz, r-release (x86_64): garchx_1.3.tgz, r-oldrel (x86_64): garchx_1.3.tgz |
Old sources: | garchx archive |
Reverse depends: | tvgarch |
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