Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations
Enrique Sentana ()
FMG Discussion Papers from Financial Markets Group
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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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:fmg:fmgdps:dp502
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