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Mixture of Distribution Hypothesis: Analyzing daily liquidity frictions and information flows

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.identifierFondation MINES ParisTech [FI3M]
dc.contributor.authorMero, Gulten
dc.date.accessioned2017-09-26T09:14:13Z
dc.date.available2017-09-26T09:14:13Z
dc.date.issued2017
dc.identifier.issn0304-4076
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16734
dc.language.isoenen
dc.subjectC52en
dc.subjectC51en
dc.subjectStrategic liquidity tradingen
dc.subjectmarket efficiencyen
dc.subjectmixture of distributionhypothesisen
dc.subjectinformation-based tradingen
dc.subjectextended Kalman Filteren
dc.subjectG12en
dc.subjectG14en
dc.subject.ddc658.1en
dc.subject.classificationjelC.C5.C51en
dc.subject.classificationjelC.C5.C52en
dc.subject.classificationjelG.G1.G14en
dc.subject.classificationjelG.G1.G12en
dc.titleMixture of Distribution Hypothesis: Analyzing daily liquidity frictions and information flowsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenThe mixture of distribution hypothesis (MDH) model offers an appealing explanation for the positive relation between trading volume and volatility of returns. In this specification, the information flows constitute the only mixing variable responsible for all changes. However, this single static latent mixing variable cannot account for the observed short-run dynamics of volume and volatility. In this paper, we propose a dynamic extension of the MDH that specifies the impact of information arrival on market characteristics in the context of liquidity frictions. We distinguish between short-term and long-term liquidity frictions. Our results highlight the economic value and statistical accuracy of our specification. First, based on some goodness of fit tests, we show that our dynamic two-latent factor model outperforms all competing specifications. Second, the information flows latent variable can be used to propose a new momentum strategy. We show that this signal improves once we allow for a second signal – the liquidity frictions latent variable – as the momentum strategies based on our model present better performance than the strategies based on competing modelsen
dc.relation.isversionofjnlnameJournal of Econometrics
dc.relation.isversionofjnldate2017
dc.relation.isversionofdoi10.1016/j.jeconom.2017.08.014en
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelOrganisation et finances d'entrepriseen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2017-09-25T09:28:33Z
hal.identifierhal-01593402*
hal.version1*
hal.author.functionaut
hal.author.functionaut
hal.author.functionaut


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