Equilibrium Data Mining and Data Abundance

Jérôme Dugast (1) , Thierry Foucault (2)

1 DRM - Dauphine Recherches en Management
2 HEC Paris - Recherche - Hors Laboratoire

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.

Mots clés: Alternative Data; Price Informativeness; Search for Information

Domaines: Gestion et management

Jérôme Dugast, Thierry Foucault. Equilibrium Data Mining and Data Abundance. 2020. ⟨hal-03053967⟩