Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/17880

TitleOn the extremal behavior of a Pareto process : an alternative for ARMAX modeling
Author(s)Ferreira, Marta Susana
KeywordsExtreme value theory
Markov chains
Autoregressive processes
Tail dependence
Issue date2012
PublisherInstitute of Information Theory and Automation of Academy of Sciences of the Czech Republic
JournalKybernetika
Abstract(s)In what concerns extreme values modeling, heavy tailed autoregressive processes defined with the minimum or maximum operator have proved to be good alternatives to classical linear ARMA with heavy tailed marginals (Davis and Resnick , Ferreira and Canto e Castro). In this paper we present a complete characterization of the tail behavior of the autoregressive Pareto process known as \emph{Yeh-Arnold-Robertson Pareto(III)} (Yeh et al.). We shall see that it is quite similar to the first order max-autoregressive ARMAX, but has a more robust parameter estimation procedure, being therefore more attractive for modeling purposes. Consistency and asymptotic normality of the presented estimators will also be stated.
TypeArticle
URIhttp://hdl.handle.net/1822/17880
ISSN0023-5954
Publisher versionhttp://www.kybernetika.cz/content/2012/1/31/paper.pdf
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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