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Un test d'heteroscedasticite conditionnelle inspire de la modelisation en termes de reseaux neuronaux artificiels

Listed author(s):
  • Caulet, R.
  • Peguin-Feissolle, A.

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.

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Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 99a23.

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Length: 23 pages
Date of creation: 1999
Handle: RePEc:fth:aixmeq:99a23
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