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Article: Diagnostic checking for non-stationary ARMA models with an application to financial data

TitleDiagnostic checking for non-stationary ARMA models with an application to financial data
Authors
KeywordsResidual ACFs
Nonstationary ARMA
Portmanteau test
Squared residual ACFs
Issue Date2013
Citation
North American Journal of Economics and Finance, 2013, v. 26, p. 624-639 How to Cite?
AbstractThis paper first derives the limiting distributions of the residual and the squared residual autocorrelation functions of the nonstationary autoregressive moving-average model, respectively. We then use them to construct two portmanteau statistics for testing the adequacy of the fitted model. Simulation results show that the tests have reasonable empirical sizes and powers in the finite samples. Finally, we use the daily SP500 data to illustrate our theory and approach. © 2013 Elsevier Inc.
Persistent Identifierhttp://hdl.handle.net/10722/230943
ISSN
2015 Impact Factor: 1.36
2015 SCImago Journal Rankings: 0.578

 

DC FieldValueLanguage
dc.contributor.authorLing, Shiqing-
dc.contributor.authorZhu, Ke-
dc.contributor.authorYee, Chong Ching-
dc.date.accessioned2016-09-01T06:07:13Z-
dc.date.available2016-09-01T06:07:13Z-
dc.date.issued2013-
dc.identifier.citationNorth American Journal of Economics and Finance, 2013, v. 26, p. 624-639-
dc.identifier.issn1062-9408-
dc.identifier.urihttp://hdl.handle.net/10722/230943-
dc.description.abstractThis paper first derives the limiting distributions of the residual and the squared residual autocorrelation functions of the nonstationary autoregressive moving-average model, respectively. We then use them to construct two portmanteau statistics for testing the adequacy of the fitted model. Simulation results show that the tests have reasonable empirical sizes and powers in the finite samples. Finally, we use the daily SP500 data to illustrate our theory and approach. © 2013 Elsevier Inc.-
dc.languageeng-
dc.relation.ispartofNorth American Journal of Economics and Finance-
dc.subjectResidual ACFs-
dc.subjectNonstationary ARMA-
dc.subjectPortmanteau test-
dc.subjectSquared residual ACFs-
dc.titleDiagnostic checking for non-stationary ARMA models with an application to financial data-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.najef.2013.02.025-
dc.identifier.scopuseid_2-s2.0-84888436689-
dc.identifier.volume26-
dc.identifier.spage624-
dc.identifier.epage639-

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