Equilibrium Data Mining and Data Abundance
Résumé
We study, using a noisy rational expectations framework, how the availability of new data to forecast asset payoffs ("data abundance") affect the capital allocated to quantitative asset managers ("data miners") relative to other active asset managers, the mean and the cross-sectional dispersion of their performance, and price informativeness. Data miners search for predictors of asset payoffs and trade when they find one with a sufficiently high precision. Data abundance raises the precision of the best predictors. Yet, it eventually induces data miners to lower the bar for their signal precision. Then, their performance becomes more dispersed, and they receive less capital. Overall, data abundance is both a catalyst and an impediment to the rise of quant funds.
Domaines
Gestion et managementOrigine | Fichiers produits par l'(les) auteur(s) |
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