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Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations

Enrique Sentana ()

FMG Discussion Papers from Financial Markets Group

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.

Date: 2004-06
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Related works:
Working Paper: Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations (2005) Downloads
Working Paper: Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations (2004) Downloads
Working Paper: Estimation and testing of dynamic models with generalised hyperbolic innovations (2004) Downloads
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