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Estimation and testing of dynamic models with generalised hyperbolic innovations

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  • Javier F. Mencia
  • Enrique Sentana

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.

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File URL: http://eprints.lse.ac.uk/24742/
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Bibliographic Info

Paper provided by London School of Economics and Political Science, LSE Library in its series LSE Research Online Documents on Economics with number 24742.

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Length: 40 pages
Date of creation: Jun 2004
Date of revision:
Handle: RePEc:ehl:lserod:24742

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Keywords: Inequality constraints; Kurtosis; Multivariate normality test; Skewness; Student t; Tail dependence;

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