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

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.

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Year of publication:	2009-09-20
Authors:	Ardia, David
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	GARCH \| Bayesian \| MCMC \| Student-t \| R software

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C52 - Model Evaluation and Testing ; C22 - Time-Series Models ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C11 - Bayesian Analysis
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005015589