DP16019 | Equilibrium Data Mining

Publication Date

04/09/2021

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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 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.