Munich Personal RePEc Archive

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

Ardia, David and Hoogerheide, Lennart F. (2009): Bayesian estimation of the GARCH(1,1) model with Student-t innovations. Published in: The R Journal , Vol. 2, No. 2 (31. December 2010): pp. 41-47.

This is the latest version of this item.

[img]
Preview
PDF
MPRA_paper_30122.pdf

Download (508kB) | Preview

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.

Available Versions of this Item

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.