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

Authors

David Ardia, University of Fribourg
Lennart F. Hoogerheide, Erasmus University Rotterdam

Date of this Version

12-2010

Document Type

Article

Citation

The R Journal (December 2010) 2(2)

Comments

Copyright 2010, The R Foundation. Open access material. License: CC BY 3.0 Unported

Abstract

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