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Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations

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  • Enrique Sentana

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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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Bibliographic Info

Paper provided by Financial Markets Group in its series FMG Discussion Papers with number dp502.

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Date of creation: Jun 2004
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Handle: RePEc:fmg:fmgdps:dp502

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