A new nonlinear formulation for GARCH models

Sebastian Ossandón; Natalia Bahamonde

doi:10.1016/j.crma.2013.02.014

A new nonlinear formulation for GARCH models

Sebastian Ossandón, Natalia Bahamonde

Research output: Contribution to journal › Article › peer-review

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Abstract

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.

Original language	English
Pages (from-to)	235-239
Number of pages	5
Journal	Comptes Rendus Mathematique
Volume	351
Issue number	5-6
DOIs	https://doi.org/10.1016/j.crma.2013.02.014
State	Published - Mar 2013

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10.1016/j.crma.2013.02.014

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title = "A new nonlinear formulation for GARCH models",

abstract = "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.",

author = "Sebastian Ossand{\'o}n and Natalia Bahamonde",

note = "Funding Information: This research was partially supported by grants FONDECYT 11121531 and ECOS/CONICYT C10E03.",

year = "2013",

month = mar,

doi = "10.1016/j.crma.2013.02.014",

language = "English",

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pages = "235--239",

journal = "Comptes Rendus Mathematique",

issn = "1631-073X",

publisher = "Academie des sciences",

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T1 - A new nonlinear formulation for GARCH models

AU - Ossandón, Sebastian

AU - Bahamonde, Natalia

N1 - Funding Information: This research was partially supported by grants FONDECYT 11121531 and ECOS/CONICYT C10E03.

PY - 2013/3

Y1 - 2013/3

N2 - 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.

AB - 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.

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U2 - 10.1016/j.crma.2013.02.014

DO - 10.1016/j.crma.2013.02.014

M3 - Article

AN - SCOPUS:84878141607

SN - 1631-073X

VL - 351

SP - 235

EP - 239

JO - Comptes Rendus Mathematique

JF - Comptes Rendus Mathematique

IS - 5-6

ER -

A new nonlinear formulation for GARCH models

Abstract

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