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Equilibrium Data Mining and Data Abundance

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Date
2020
Dewey
Etudes et analyses des marchés
Sujet
Asset price informativeness; Big data; Information processing; Markets; G14,D4,L15
JEL code
L.L1.L15; D.D4.D40; G.G1.G14
Conference name
47th European Finance Association (EFA) Annual Meeting
Conference date
08-2020
Conference city
Helsinki
Conference country
Finland
URI
https://basepub.dauphine.fr/handle/123456789/20975
Collections
  • DRM : Publications
Metadata
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Author
Dugast, Jérôme
1032 Dauphine Recherches en Management [DRM]
Foucault, Thierry
1738 Groupement de Recherche et d'Etudes en Gestion à HEC [GREGH]
Type
Communication / Conférence
Abstract (EN)
We model of the search for predictors by speculators (active asset managers) and use it to analyze how the improvement in data processing power and the growth in available data (“data abundance”) affect the diversity of trading signals used by speculators, the dispersion of their profits and the similarities of their holdings. Our central message is that data abundance and computing power do not have the same effects. In particular, an improvement in computing power always raises the bar for the quality of predictors that managers consider good enough to exploit while more data lower it when data becomes sufficiently abundant. When this happens, the diversity of speculators’ signals and the dispersion of their trading profits increase in equilibrium while their holdings become less correlated.

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