Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations
AbstractWe analyse the Generalised Hyperbolic distribution adequacy to model kurtosis and asymmetries in multivariate conditionally heteroskedastic dynamic regression models. We standardise this distribution, obtain analytical expressions for the log-likelihood score, and explain how to evaluate the information matrix. We also 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 application to five NASDAQ sectorial stock returns that indicates that their conditional distribution is asymmetric and leptokurtic, which can be successfully exploited for risk management purposes.
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Bibliographic InfoPaper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 5177.
Date of creation: Aug 2005
Date of revision:
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Other versions of this item:
- Francisco Javier Mencía & Enrique Sentana, 2004. "Estimation And Testing Of Dynamic Models With Generalised Hyperbolic Innovations," Working Papers wp2004_0411, CEMFI.
- Enrique Sentana, 2004. "Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations," FMG Discussion Papers dp502, Financial Markets Group.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-09-29 (All new papers)
- NEP-ECM-2005-09-29 (Econometrics)
- NEP-ETS-2005-09-29 (Econometric Time Series)
- NEP-FIN-2005-09-29 (Finance)
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