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Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations Author info | Abstract | Publisher info | Download info | Related research | Statistics Mencía, Javier
Sentana, Enrique
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We 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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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number
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Date of creation: Aug 2005Date of revision:
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Keywords: inequality constraints ; Kurtosis ; Multivariate Normality Test ; skewness ; student t ; Supremum Test ; tail dependence ; Other versions of this item:
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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