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Article: Global self-weighted and local quasi-maximum exponential likelihood estimators for arma-garch/igarch models

TitleGlobal self-weighted and local quasi-maximum exponential likelihood estimators for arma-garch/igarch models
Authors
KeywordsStrong consistency
ARMA-GARCH/IGARCH model
Global self-weighted/local quasi-maximum exponential likelihood estimator
Asymptotic normality
Issue Date2011
Citation
Annals of Statistics, 2011, v. 39, n. 4, p. 2131-2163 How to Cite?
Abstract© Institute of Mathematical Statistics, 2011.This paper investigates the asymptotic theory of the quasi-maximum exponential likelihood estimators (QMELE) for ARMA-GARCH models. Under only a fractional moment condition, the strong consistency and the asymptotic normality of the global self-weighted QMELE are obtained. Based on this self-weighted QMELE, the local QMELE is showed to be asymptotically normal for the ARMA model with GARCH (finite variance) and IGARCH errors. A formal comparison of two estimators is given for some cases. A simulation study is carried out to assess the performance of these estimators, and a real example on the world crude oil price is given.
Persistent Identifierhttp://hdl.handle.net/10722/230907
ISSN
2015 Impact Factor: 2.78
2015 SCImago Journal Rankings: 6.653

 

DC FieldValueLanguage
dc.contributor.authorZhu, Ke-
dc.contributor.authorLing, Shiqing-
dc.date.accessioned2016-09-01T06:07:07Z-
dc.date.available2016-09-01T06:07:07Z-
dc.date.issued2011-
dc.identifier.citationAnnals of Statistics, 2011, v. 39, n. 4, p. 2131-2163-
dc.identifier.issn0090-5364-
dc.identifier.urihttp://hdl.handle.net/10722/230907-
dc.description.abstract© Institute of Mathematical Statistics, 2011.This paper investigates the asymptotic theory of the quasi-maximum exponential likelihood estimators (QMELE) for ARMA-GARCH models. Under only a fractional moment condition, the strong consistency and the asymptotic normality of the global self-weighted QMELE are obtained. Based on this self-weighted QMELE, the local QMELE is showed to be asymptotically normal for the ARMA model with GARCH (finite variance) and IGARCH errors. A formal comparison of two estimators is given for some cases. A simulation study is carried out to assess the performance of these estimators, and a real example on the world crude oil price is given.-
dc.languageeng-
dc.relation.ispartofAnnals of Statistics-
dc.subjectStrong consistency-
dc.subjectARMA-GARCH/IGARCH model-
dc.subjectGlobal self-weighted/local quasi-maximum exponential likelihood estimator-
dc.subjectAsymptotic normality-
dc.titleGlobal self-weighted and local quasi-maximum exponential likelihood estimators for arma-garch/igarch models-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1214/11-AOS895-
dc.identifier.scopuseid_2-s2.0-84869388467-
dc.identifier.volume39-
dc.identifier.issue4-
dc.identifier.spage2131-
dc.identifier.epage2163-

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