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The Score of Condionally Heteroskedastic Dynamic Regression Models with Student T Innovations, and an LM Test for Multivariate Normality

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Author Info
Fiorentini, G.
Sentana, E.
Calzolari, G.

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Abstract

We provide numerically reliable analytical expressions for the score of conditionally heteroskedastic dynamic regression models when the conditional distribution is multivariate t. We also derive one-sided and two-sided LM tests for multivariate normality versus multivariate t based on the first two moments of the norm of the standardised innovations evaluated at the Gaussian quasi-ML estimators of the conditional mean and variance parameters. We reinterpret them as specification tests for multivariate excess kurtosis, and show that they have power against lepkurtic alternatives. Finally, we analyse UK stock returns, and confirm that their conditional distribution has fat tails.

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Publisher Info
Paper provided by Centro de Estudios Monetarios Y Financieros- in its series Papers with number 0007.

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Length: 29 pages
Date of creation: 2000
Date of revision:
Handle: RePEc:fth:cemfdt:0007

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Related research
Keywords: MODELS ; TESTS ; DISTRIBUTION;

Find related papers by JEL classification:
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

Cited by:
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  1. Marie-Claude Beaulieu & Jean-Marie Dufour & Lynda Khalaf, 2002. "Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors: an Exact Simulation-Based Approach," CIRANO Working Papers 2002s-85, CIRANO. [Downloadable!]
    Other versions:
  2. Christian Bontemps & Nour Meddahi, 2002. "Testing Normality: A GMM Approach," CIRANO Working Papers 2002s-63, CIRANO. [Downloadable!]
  3. Josep Pijoan-Mas, 2003. "Precautionary Savings Or Working Longer Hours?," Working Papers wp2003_0311, CEMFI. [Downloadable!]
    Other versions:
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This page was last updated on 2009-10-24.

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