Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations in R

David Ardia

MPRA Paper from University Library of Munich, Germany

Abstract: This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns.

Keywords: GARCH; Bayesian; MCMC; Student-t; R software (search for similar items in EconPapers)
JEL-codes: C11 C15 C22 C52 (search for similar items in EconPapers)
Date: 2009-09-20
New Economics Papers: this item is included in nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

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https://mpra.ub.uni-muenchen.de/17414/1/MPRA_paper_17414.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/27853/3/MPRA_paper_27853.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/30122/2/MPRA_paper_30122.pdf revised version (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:17414

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