A comparison of Bayesian model selection based on MCMC with an application to GARCH-type models

Miazhynskaia, Tatiana and Frühwirth-Schnatter, Sylvia and Dorffner, Georg (2003) A comparison of Bayesian model selection based on MCMC with an application to GARCH-type models. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 83. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.

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Abstract

This paper presents a comprehensive review and comparison of five computational methods for Bayesian model selection, based on MCMC simulations from posterior model parameter distributions. We apply these methods to a well-known and important class of models in financial time series analysis, namely GARCH and GARCH-t models for conditional return distributions (assuming normal and t-distributions). We compare their performance vis--vis the more common maximum likelihood-based model selection on both simulated and real market data. All five MCMC methods proved feasible in both cases, although differing in their computational demands. Results on simulated data show that for large degrees of freedom (where the t-distribution becomes more similar to a normal one), Bayesian model selection results in better decisions in favour of the true model than maximum likelihood. Results on market data show the feasibility of all model selection methods, mainly because the distributions appear to be decisively non-Gaussian.

Item Type: Paper
Keywords: Bayesian inference / Bayesian model selection / GARCH models / Markov Chain Monte Carlo (MCMC) / model likelihood
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Marketing > Service Marketing und Tourismus
Depositing User: Repository Administrator
Date Deposited: 11 Nov 2003 10:46
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/586

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