Estimation and testing of dynamic models with generalised hyperbolic innovations

Javier Mencia () and Enrique Sentana

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We analyse the Generalised Hyperbolic distribution as a model for fat tails and asymmetries in multivariate conditionally heteroskedastic dynamic regression models. We provide a standardised version of this distribution, obtain analytical expressions for the log-likelihood score, and explain how to evaluate the information matrix. In addition, we derive tests for the null hypotheses of multivariate normal and Student t innovations, and decompose them into skewness and kurtosis components, from which we obtain more powerful one-sided versions. Finally, we present an empirical illustration with UK sectorial stock returns, which suggests that their conditional distribution is asymmetric and leptokurtic.

Keywords: Inequality constraints; Kurtosis; Multivariate normality test; Skewness; Student t; Tail dependence (search for similar items in EconPapers)
JEL-codes: C22 C32 C52 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2004-06-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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http://eprints.lse.ac.uk/24742/ Open access version. (application/pdf)

Related works:
Working Paper: Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations (2005)
Working Paper: Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations (2004)
Working Paper: Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:24742

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