Statistics/Mathematical Economics
A new nonlinear formulation for GARCH models
[Une nouvelle formulation non linéaire pour des modèles GARCH]
Comptes Rendus. Mathématique, Tome 351 (2013) no. 5-6, pp. 235-239.

Dans cette note, on déduit une nouvelle représentation mathématique, basée sur une formulation espace–état en temps discret non linéaire, pour caractériser le modèle GARCH. Lʼobjectif poursuivi dans ce travail est dʼutiliser les modèles présentés ici afin de développer des techniques dʼestimation qui soient aussi valables dans des situations où des données sont manquantes.

In this note we deduce a new mathematical representation, based on a discrete-time nonlinear state–space formulation, to characterize Generalized AutoRegresive Conditional Heteroskedasticity (GARCH) models. The purpose pursued by this article is to use the models presented herein to develop estimation techniques which are also valid in the situation when observations are missing.

Reçu le :
Accepté le :
Publié le :
DOI : 10.1016/j.crma.2013.02.014
Ossandón, Sebastian 1 ; Bahamonde, Natalia 2

1 Instituto de Matemáticas, Pontificia Universidad Católica de Valparaíso, Casilla 4059, Valparaíso, Chile
2 Instituto de Estadística, Pontificia Universidad Católica de Valparaíso, Casilla 4059, Valparaíso, Chile
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Ossandón, Sebastian; Bahamonde, Natalia. A new nonlinear formulation for GARCH models. Comptes Rendus. Mathématique, Tome 351 (2013) no. 5-6, pp. 235-239. doi : 10.1016/j.crma.2013.02.014. http://www.numdam.org/articles/10.1016/j.crma.2013.02.014/

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[7] S. Ossandón, N. Bahamonde, On the nonlinear estimation of GARCH models using an extended Kalman filter, in: Lectures Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2011, WCE 2011, 6–8 July 2011, London, UK, pp. 148–151.

[8] S. Ossandón, N. Bahamonde, Nonlinear parameter estimation for state–space ARCH models with missing observations, in: Recent Advances in Systems Science & Mathematical Modelling: Proceedings of the 3rd International Conference on Mathematical Models for Engineering Science, MMESʼ12, 2–4 December 2012, Paris, France, 2012, pp. 258–263.

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