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Equilibrium Data Mining and Data Abundance

Dugast, Jérôme; Foucault, Thierry (2021), Equilibrium Data Mining and Data Abundance, 56th Annual Conference of the Western Finance Association (WFA), 2021-06, Online

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Dugast,_Foucault_-_Equilibrium_Data_Mining_and_Data_Abundance.pdf (1.037Mb)
Type
Communication / Conférence
Date
2021
Conference title
56th Annual Conference of the Western Finance Association (WFA)
Conference date
2021-06
Conference city
Online
Metadata
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Author(s)
Dugast, Jérôme
Dauphine Recherches en Management [DRM]
Foucault, Thierry
Groupement de Recherche et d'Etudes en Gestion à HEC [GREGH]
Abstract (EN)
We analyze how computing power and data abundance affect speculators’ search for predictors. 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 by reducing search costs. In contrast, data abundance can reduce this threshold because (i) it intensifies competition among speculators and (ii) it increases the average number of trials to find a predictor. We derive implications of these findings for the distribution of asset managers’ skills and trading profits and the informativeness of asset prices.
Subjects / Keywords
Alternative Data; Data Abundance; Price Informativeness; Search for information
JEL
D58 - Computable and Other Applied General Equilibrium Models
C53 - Forecasting and Prediction Methods; Simulation Methods

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    Equilibrium Data Mining and Data Abundance 
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