Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/47024
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dc.contributor.authorPérez Rodríguez, Jorge Vicenteen_US
dc.contributor.authorAndrada Félix, Juliánen_US
dc.date.accessioned2018-11-23T10:14:41Z-
dc.date.available2018-11-23T10:14:41Z-
dc.date.issued2013en_US
dc.identifier.issn0943-4062en_US
dc.identifier.urihttp://hdl.handle.net/10553/47024-
dc.description.abstractTaking into account that the BDS test-which is used as a misspecification test applied to standardized residuals from the GARCH(1,1) model-is characterized by size distortion and departure from normality in finite samples, this paper obtains the critical values for the finite sample distribution of the BDS test. We focus on bootstrap simulation to avoid the sampling uncertainty of parameter estimation and make use of estimated response surface regressions (RSR) derived from the experimental results. We consider an extensive grid of models to obtain critical values with the results of the bootstrap experiments. The RSR used to estimate them is an artificial neural network (ANN) model, instead of the traditional linear regression models. Specifically, we estimate critical values by using a bootstrap aggregated neural network (BANN) and by employing functions of the sample size and parameters used in the experiment as the embedding dimension and proximity parameters in the BDS statistic, GARCH parameters and even the q-quantiles of the BDS distributions. The main results confirm that the sample size and BDS parameters play a role in size distortion. Finally, an empirical application to three price indexes is performed, to highlight the differences between decisions made using the asymptotic or our predicted critical values for the BDS test in finite samples.en_US
dc.languageengen_US
dc.publisher0943-4062-
dc.relation.ispartofComputational Statisticsen_US
dc.sourceComputational Statistics[ISSN 0943-4062],v. 28, p. 701-734en_US
dc.subject5302 Econometríaen_US
dc.subject.otherTeroría del caosen_US
dc.subject.otherSeries temporalesen_US
dc.subject.otherNonlinearityen_US
dc.titleEstimating critical values for testing the i.i.d. in standardized residuals from GARCH models in finite samplesen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1007/s00180-012-0325-1
dc.identifier.scopus84875415765-
dc.identifier.isi000316755900018
dc.contributor.authorscopusid56216749800-
dc.contributor.authorscopusid6505916889-
dc.description.lastpage734-
dc.description.firstpage701-
dc.relation.volume28-
dc.investigacionCiencias Sociales y Jurídicasen_US
dc.type2Artículoen_US
dc.contributor.daisngid1615612
dc.contributor.daisngid3014920
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Perez-Rodriguez, JV
dc.contributor.wosstandardWOS:Andrada-Felix, J
dc.date.coverdateEnero 2013
dc.identifier.ulpgces
dc.description.sjr0,414
dc.description.jcr0,345
dc.description.sjrqQ3
dc.description.jcrqQ4
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR Finanzas Cuantitativas y Computacionales-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.deptGIR Finanzas Cuantitativas y Computacionales-
crisitem.author.deptDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.orcid0000-0002-6738-9191-
crisitem.author.orcid0000-0001-8598-3234-
crisitem.author.parentorgDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.parentorgDepartamento de Métodos Cuantitativos en Economía y Gestión-
crisitem.author.fullNamePérez Rodríguez, Jorge Vicente-
crisitem.author.fullNameAndrada Félix, Julián-
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