Thierry Foucault

Equilibrium Data Mining and Data Abundance

Abstract
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 greater 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 reduces rents from informed trading, except for the best informed speculators and (ii) it increases the average number of trials to find a predictor. We study implications of these findings for active asset managers' performance, the similarity of their signals and positions and the informativeness of asset prices.