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Bayesian estimation of the GARCH(1,1) model with Student-t innovations in R

David Ardia & Lennart Hoogerheide

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
   
Citation Ardia, D., & Hoogerheide, L. (2010). Bayesian estimation of the GARCH(1,1) model with Student-t innovations in R. The R Journal, 2(2), 41-47.
   
Type Journal article (English)
Date of appearance 2010
Journal The R Journal
Volume 2
Issue 2
Pages 41-47
URL https://journal.r-project.org/archive/2010-2/RJournal_201...
Related project Bayesian estimation of regime-switching GARCH models