
Equilibrium Data Mining and Data Abundance
Dugast, Jérôme; Foucault, Thierry (2020), Equilibrium Data Mining and Data Abundance. https://basepub.dauphine.fr/handle/123456789/21288
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Type
Document de travail / Working paperDate
2020Series title
HEC Paris Research PaperSeries number
FIN-2020-1393Pages
49
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Show full item recordAuthor(s)
Dugast, JérômeDauphine Recherches en Management [DRM]
Foucault, Thierry
HEC Paris - Recherche - Hors Laboratoire
Abstract (EN)
We 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.Subjects / Keywords
Alternative Data; Price Informativeness; Search for InformationRelated items
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