Estimation de modèles ARMA à changements de régime récurrents

Christian Francq; Antony Gautier

doi:10.1016/j.crma.2004.04.014

Estimation de modèles ARMA à changements de régime récurrents

Translated title of the contribution: Estimating ARMA models with recurrent regime changes

Christian Francq
, Antony Gautier

Université de Lille

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

Abstract

This Note considers estimation of time-varying ARMA models. We focus on models with recurrent but non-periodic changes in regime. Conditions ensuring the consistency and the asymptotic normality of two sequences of least squares estimators are given. These conditions are made explicit when the regime generated process is a Markov chain.

Translated title of the contribution	Estimating ARMA models with recurrent regime changes
Original language	French
Pages (from-to)	55-58
Number of pages	4
Journal	Comptes Rendus Mathematique
Volume	339
Issue number	1
DOIs	https://doi.org/10.1016/j.crma.2004.04.014
Publication status	Published - 1 Jul 2004
Externally published	Yes

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10.1016/j.crma.2004.04.014

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title = "Estimation de mod{\`e}les ARMA {\`a} changements de r{\'e}gime r{\'e}currents",

abstract = "This Note considers estimation of time-varying ARMA models. We focus on models with recurrent but non-periodic changes in regime. Conditions ensuring the consistency and the asymptotic normality of two sequences of least squares estimators are given. These conditions are made explicit when the regime generated process is a Markov chain.",

author = "Christian Francq and Antony Gautier",

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N2 - This Note considers estimation of time-varying ARMA models. We focus on models with recurrent but non-periodic changes in regime. Conditions ensuring the consistency and the asymptotic normality of two sequences of least squares estimators are given. These conditions are made explicit when the regime generated process is a Markov chain.

AB - This Note considers estimation of time-varying ARMA models. We focus on models with recurrent but non-periodic changes in regime. Conditions ensuring the consistency and the asymptotic normality of two sequences of least squares estimators are given. These conditions are made explicit when the regime generated process is a Markov chain.

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DO - 10.1016/j.crma.2004.04.014

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JO - Comptes Rendus Mathematique

JF - Comptes Rendus Mathematique

IS - 1

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Estimation de modèles ARMA à changements de régime récurrents

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