Full Bayesian Inference for GARCH and Egarch Models

A full Bayesian analysis of GARCH and EGARCH models is proposed consisting of parameter estimation, model selection and volatility prediction. The Bayesian paradigm is implemented via Markov-chain Monte Carlo methodologies. We provide implementation details and illustrations using the General index of the Athens stock exchange

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Year of publication:	2004
Authors:	Vrontos, Ioannis D. ; Dellaportas, Petros ; Politis, Dimitris N.
Publisher:	[S.l.] : SSRN
Subject:	Theorie \| Theory \| Bayes-Statistik \| Bayesian inference \| ARCH-Modell \| ARCH model \| Aktienindex \| Stock index \| Griechenland \| Greece
Description of contents:	Abstract [papers.ssrn.com]

Extent:	1 Online-Ressource
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: Journal of Business and Economics Statistics, Vol. 18, No. 2, pp. 187-198, 2000 Volltext nicht verfügbar
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014068929