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Smooth Transition Garch Models: a Bayesian Perspective

Published online by Cambridge University Press:  17 August 2016

Michel Lubrano
Michel Lubrano*
Affiliation:
GREQAM-CNRS, CORE
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Summary

This paper proposes a new kind of asymmetric GARCH where the conditional variance obeys two different regimes with a smooth transition function. In one formulation, the conditional variance reacts differently to negative and positive shocks while in a second formulation, small and big shocks have separate effects. The introduction of a threshold allows for a mixed effect. A Bayesian strategy, based on the comparison between posterior and predictive Bayesian residuals, is built for detecting the presence and the shape of non-linearities. The method is applied to the Brussels and Tokyo stock indexes. The attractiveness of an alternative parameterisation of the GARCH model is emphasised as a potential solution to some numerical problems.

Résumé

Résumé

Ce papier propose un nouveau type de modèle GARCH asymétrique où la variance conditionnelle suit deux régimes avec changement graduel. Dans une des deux formulations, la variance conditionnelle réagit différemment aux chocs négatifs et aux chocs positifs, tandis que dans l’autre les gros chocs et les petits chocs ont des effets séparés. L’introduction d’un paramètre de seuil permet de combiner les deux effets. Une stratégie Bayésienne de recherche de spécification pour détecter la présence et la forme de la non-linéarité est construite sur la base d’une comparaison entre les résidus Bayésiens prédictifs et les résidus a posteriori. La méthode est appliquée aux index boursiers de Bruxelles et de Tokyo. Une paramétrisation alternative du modèle GARCH s’avère fort utile pour résoudre certains problèmes numériques.

Keywords

C11C22C51G14C11C22C51G14
Type
Research Article
Information
Recherches Économiques de Louvain/ Louvain Economic Review , Volume 67 , Issue 3 , 2001 , pp. 257 - 287
Copyright
Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 2001 

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Footnotes

*

GREQAM-CNRS, 2 rue de la Charité, 13002 Marseille, France and CORE, 34 voie du Roman Pays, B-1348 Louvain la Neuve, Belgique, email: lubrano@ehess.cnrs-mrs.fr

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