Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations

Javier Mencia () and Enrique Sentana

Working Papers from CEMFI

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
New Economics Papers: this item is included in nep-ecm and nep-fin
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Citations: View citations in EconPapers (9)

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https://www.cemfi.es/ftp/wp/0411.pdf (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:cmf:wpaper:wp2004_0411

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