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Article: A bootstrapped spectral test for adequacy in weak ARMA models

TitleA bootstrapped spectral test for adequacy in weak ARMA models
Authors
Zhu, KLi, WK
KeywordsBlock-wise random weighting method
Diagnostic checking
Least squares estimation
Spectral test
Weak ARMA models
Wild bootstrap
Issue Date2015
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jeconom
Citation
Journal of Econometrics, 2015, v. 187 n. 1, p. 113-130 How to Cite?
DOI: http://dx.doi.org/10.1016/j.jeconom.2015.02.005
AbstractThis paper proposes a Cramér-von Mises (CM) test statistic to check the adequacy of weak ARMA models. Without posing a martingale difference assumption on the error terms, the asymptotic null distribution of the CM test is obtained. Moreover, this CM test is consistent, and has nontrivial power against the local alternative of order n-1/2. Due to the unknown dependence of error terms and the estimation effects, a new block-wise random weighting method is constructed to bootstrap the critical values of the test statistic. The new method is easy to implement and its validity is justified. The theory is illustrated by a small simulation study and an application to S&P 500 stock index. © 2015 Elsevier B.V.
Persistent Identifierhttp://hdl.handle.net/10722/214576
ISSN
0304-4076
2022 Impact Factor: 6.3
2020 SCImago Journal Rankings: 3.769
ISI Accession Number ID
WOS:000356194000008

 

DC FieldValueLanguage
dc.contributor.authorZhu, K-
dc.contributor.authorLi, WK-
dc.date.accessioned2015-08-21T11:38:49Z-
dc.date.available2015-08-21T11:38:49Z-
dc.date.issued2015-
dc.identifier.citationJournal of Econometrics, 2015, v. 187 n. 1, p. 113-130-
dc.identifier.issn0304-4076-
dc.identifier.urihttp://hdl.handle.net/10722/214576-
dc.description.abstractThis paper proposes a Cramér-von Mises (CM) test statistic to check the adequacy of weak ARMA models. Without posing a martingale difference assumption on the error terms, the asymptotic null distribution of the CM test is obtained. Moreover, this CM test is consistent, and has nontrivial power against the local alternative of order n-1/2. Due to the unknown dependence of error terms and the estimation effects, a new block-wise random weighting method is constructed to bootstrap the critical values of the test statistic. The new method is easy to implement and its validity is justified. The theory is illustrated by a small simulation study and an application to S&P 500 stock index. © 2015 Elsevier B.V.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jeconom-
dc.relation.ispartofJournal of Econometrics-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License-
dc.subjectBlock-wise random weighting method-
dc.subjectDiagnostic checking-
dc.subjectLeast squares estimation-
dc.subjectSpectral test-
dc.subjectWeak ARMA models-
dc.subjectWild bootstrap-
dc.titleA bootstrapped spectral test for adequacy in weak ARMA models-
dc.typeArticle-
dc.identifier.emailLi, WK: hrntlwk@hkucc.hku.hk-
dc.identifier.authorityLi, WK=rp00741-
dc.description.naturepostprint-
dc.identifier.doi10.1016/j.jeconom.2015.02.005-
dc.identifier.scopuseid_2-s2.0-84929617322-
dc.identifier.hkuros248603-
dc.identifier.volume187-
dc.identifier.issue1-
dc.identifier.spage113-
dc.identifier.epage130-
dc.identifier.isiWOS:000356194000008-
dc.publisher.placeNetherlands-
dc.identifier.issnl0304-4076-

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