 Bayesian Analysis for Hybrid MSF-SBEKK Models of Multivariate VolatilityJacek Osiewalski and Anna Pajor Central European Journal of Economic Modelling and Econometrics, 2009, vol. 1, issue 2, 179-202 Abstract: The aim of this paper is to examine the empirical usefulness of two new MSF - Scalar BEKK(1,1) models of n-variate volatility. These models formally belong to the MSV class, but in fact are some hybrids of the simplest MGARCH and MSV specifications. Such hybrid structures have been proposed as feasible (yet non-trivial) tools for analyzing highly dimensional financial data (large n). This research shows Bayesian model comparison for two data sets with n = 2, since in bivariate cases we can obtain Bayes factors against many (even unparsimonious) MGARCH and MSV specifications. Also, for bivariate data, approximate posterior results (based on preliminary estimates of nuisance matrix parameters) are compared to the exact ones in both MSF-SBEKK models. Finally, approximate results are obtained for a large set of returns on equities (n = 34). Keywords: Bayesian econometrics; Gibbs sampling; time-varying volatility; multivariate GARCH processes; multivariate SV processes (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:psc:journl:v:1:y:2009:i:2:p:179-202 Access Statistics for this article More articles in Central European Journal of Economic Modelling and Econometrics from Central European Journal of Economic Modelling and Econometrics |
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