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hal.structure.identifierDauphine Recherches en Management [DRM]
dc.contributor.authorDarolles, Serge
hal.structure.identifierDauphine Recherches en Management [DRM]
dc.contributor.authorLe Fol, Gaëlle
hal.structure.identifierCentre d'Economie de l'Université Paris Nord [CEPN]
dc.contributor.authorLu, Yang
HAL ID: 15957
ORCID: 0000-0002-7141-1048
hal.structure.identifierDauphine Recherches en Management [DRM]
dc.contributor.authorSun, Ran
dc.date.accessioned2019-04-20T09:52:52Z
dc.date.available2019-04-20T09:52:52Z
dc.date.issued2019
dc.identifier.issn0047-259X
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/18731
dc.language.isoenen
dc.subjectCompound autoregressive processen
dc.subjectMemory persistenceen
dc.subjectMutual fundsen
dc.subjectNon-Linear forecastingen
dc.subject.ddc657en
dc.subject.classificationjelG.G2.G23en
dc.subject.classificationjelC.C5.C53en
dc.subject.classificationjelC.C3.C32en
dc.titleBivariate integer-autoregressive process with an application to mutual fund flowsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe propose a new family of bivariate nonnegative integer-autoregressive (BINAR) models for count process data. We first generalize the existing BINAR(1) model by allowing for dependent thinning operators and arbitrary innovation distribution. The extended family allows for intuitive interpretation, as well as tractable aggregation and stationarity properties. We then introduce higher order BINAR() and BINAR() dynamics to accommodate more flexible serial dependence patterns. So far, the literature has regarded such models as computationally intractable. We show that the extended BINAR family allows for closed-form predictive distributions at any horizons and for any values of , which significantly facilitates non-linear forecasting and likelihood based estimation. Finally, a BINAR model with memory persistence is applied to open-ended mutual fund purchase and redemption order counts.en
dc.relation.isversionofjnlnameJournal of Multivariate Analysis
dc.relation.isversionofjnlvol173en
dc.relation.isversionofjnlissueSeptember 2019en
dc.relation.isversionofjnldate2019-09
dc.relation.isversionofjnlpages181-203en
dc.relation.isversionofdoi10.1016/j.jmva.2019.02.015en
dc.contributor.countryeditoruniversityotherFRANCE
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelComptabilité (recherche et théorie)en
dc.relation.forthcomingnonen
dc.relation.forthcomingprintouien
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2019-04-02T13:58:19Z
hal.identifierhal-02105203*
hal.version1*
hal.author.functionaut
hal.author.functionaut
hal.author.functionaut
hal.author.functionaut


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