Equilibrium Data Mining and Data Abundance
47 Pages Posted: 27 Jan 2021 Last revised: 8 Apr 2021
Date Written: April 04, 2021
We analyze how computing power and data abundance affect speculators' search for predictors. In our model, 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, and therefore price informativeness, 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. In the former (latter) case, price informativeness increases (decreases) with data abundance. We derive implications of these effects for the distribution of asset managers' skills and trading profits.
Keywords: [comma Alternative Data; Data Abundance; Data Mining; Price Informativeness; Search for Information]
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