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Un test d'hétéroscédasticité conditionnelle inspiré de la modélisation en termes de réseaux neuronaux artificiels

Author

Listed:
  • Renaud Caulet

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Anne Peguin-Feissolle

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Ce papier considere un test d'heteroscedasticite conditionnelle basee sur la methode des reseaux neuronaux artificiels et en compare les performances avec des test standards, a l'aide de simulations de Monte-Carlo. L'hypothese alternative d'heteroscedasticite conditionnelle est representee par une variance conditionnelle de forme neuronale: le test du Multiplicateur de Lagrange qui en decoule permet de detecter une grande variete de formes d'heteroscedasticite conditionnelle. Les resultats des simulations, presentes sous forme graphique, montrent que ce test est relativement performant.

Suggested Citation

  • Renaud Caulet & Anne Peguin-Feissolle, 2000. "Un test d'hétéroscédasticité conditionnelle inspiré de la modélisation en termes de réseaux neuronaux artificiels," Post-Print halshs-00390155, HAL.
    • Handle: RePEc:hal:journl:halshs-00390155
    DOI: 10.2307/20076247
    as

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    Cited by:

    1. Anne Péguin-Feissolle & Bilel Sanhaji, 2016. "Tests of the Constancy of Conditional Correlations of Unknown Functional Form in Multivariate GARCH Models," Annals of Economics and Statistics, GENES, issue 123-124, pages 77-101.
    2. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," Working Papers halshs-01133751, HAL.

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