Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations
AbstractWe 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 InfoPaper provided by Financial Markets Group in its series FMG Discussion Papers with number dp502.
Date of creation: Jun 2004
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Web page: http://www.lse.ac.uk/fmg/
Other versions of this item:
- Mencía, Javier & Sentana, Enrique, 2005. "Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations," CEPR Discussion Papers 5177, C.E.P.R. Discussion Papers.
- Francisco Javier Mencía & Enrique Sentana, 2004. "Estimation And Testing Of Dynamic Models With Generalised Hyperbolic Innovations," Working Papers wp2004_0411, CEMFI.
- Javier F. Mencia & Enrique Sentana, 2004. "Estimation and testing of dynamic models with generalised hyperbolic innovations," LSE Research Online Documents on Economics 24742, London School of Economics and Political Science, LSE Library.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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