On Uniqueness of Moving Average Representations of Heavy-tailed Stationary Processes

Christian Gouriéroux; Jean Michel Zakoïan

doi:10.1111/jtsa.12139

On Uniqueness of Moving Average Representations of Heavy-tailed Stationary Processes

Christian Gouriéroux
, Jean Michel Zakoïan

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

The paper solves the open problem of identification of two-sided moving average representations with i.i.d. summands, for stationary processes in non-Gaussian domains of attraction of α-stable laws. This shows the possibility to identify nonparametrically both the sequence of two-sided moving average coefficients and the distribution of the underlying heavy-tailed i.i.d. process.

langue originale	Anglais
Pages (de - à)	876-887
Nombre de pages	12
journal	Journal of Time Series Analysis
Volume	36
Numéro de publication	6
Les DOIs	https://doi.org/10.1111/jtsa.12139
état	Publié - 1 nov. 2015
Modification externe	Oui

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10.1111/jtsa.12139

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title = "On Uniqueness of Moving Average Representations of Heavy-tailed Stationary Processes",

abstract = "The paper solves the open problem of identification of two-sided moving average representations with i.i.d. summands, for stationary processes in non-Gaussian domains of attraction of α-stable laws. This shows the possibility to identify nonparametrically both the sequence of two-sided moving average coefficients and the distribution of the underlying heavy-tailed i.i.d. process.",

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N2 - The paper solves the open problem of identification of two-sided moving average representations with i.i.d. summands, for stationary processes in non-Gaussian domains of attraction of α-stable laws. This shows the possibility to identify nonparametrically both the sequence of two-sided moving average coefficients and the distribution of the underlying heavy-tailed i.i.d. process.

AB - The paper solves the open problem of identification of two-sided moving average representations with i.i.d. summands, for stationary processes in non-Gaussian domains of attraction of α-stable laws. This shows the possibility to identify nonparametrically both the sequence of two-sided moving average coefficients and the distribution of the underlying heavy-tailed i.i.d. process.

KW - Domain of attraction

KW - Identification

KW - Infinite moving average

KW - Linear process

KW - Mixed causal/noncausal process

KW - α-stable distribution

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On Uniqueness of Moving Average Representations of Heavy-tailed Stationary Processes

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