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

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:	2019
Authors:	Ardia, David ; Hoogerheide, Lennart F.
Publisher:	[S.l.] : SSRN
Subject:	Bayes-Statistik \| Bayesian inference \| ARCH-Modell \| ARCH model \| Schätztheorie \| Estimation theory \| Innovation

Extent:	1 Online-Ressource (7 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: The R Journal, Vol. 2, No. 2, pp. 41–47, 2010 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 21, 2009 erstellt
Classification:	C11 - Bayesian Analysis ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C22 - Time-Series Models ; C52 - Model Evaluation and Testing
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014203852