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hal.structure.identifierDauphine Recherches en Management [DRM]
dc.contributor.authorDugast, Jérôme
hal.structure.identifierHEC Paris - Recherche - Hors Laboratoire
dc.contributor.authorFoucault, Thierry
dc.date.accessioned2020-12-11T10:36:57Z
dc.date.available2020-12-11T10:36:57Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/21288
dc.language.isoenen
dc.subjectAlternative Dataen
dc.subjectPrice Informativenessen
dc.subjectSearch for Informationen
dc.subject.ddc332en
dc.subject.classificationjelG.G1.G14en
dc.subject.classificationjelD.D8.D84en
dc.titleEquilibrium Data Mining and Data Abundanceen
dc.typeDocument de travail / Working paper
dc.description.abstractenWe analyze how computing power and data abundance affect speculators' search for predictors. In our model, speculators search for predictors through trials and optimally stop searching when they find a predictor with a signal-to-noise ratio larger than an endogenous threshold. Greater computing power raises this threshold, and therefore price informativeness, by reducing search costs. In contrast, data abundance can reduce this threshold because it intensifies competition among speculators and it increases the average number of trials to find a predictor. In the former (latter) case, price informativeness increases (decreases) with data abundance. We derive implications of these effects for the distribution of asset managers' skills and trading profits.en
dc.identifier.citationpages49en
dc.relation.ispartofseriestitleHEC Paris Research Paperen
dc.relation.ispartofseriesnumberFIN-2020-1393en
dc.subject.ddclabelOptimisation mathématique – Analyse financièreen
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2020-11-30T14:52:25Z
hal.identifierhal-03053967*
hal.version1*
hal.update.actionupdateFiles*
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