Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We identify long-lived pricing errors through a model in which inattentive investors arrive stochastically to trade. The model’s parameters are structurally estimated using daily NYSE market-maker inventories, retail order flows, and prices. The estimated model fits empirical variances, autocorrelations, and cross-autocorrelations among our three data series from daily to monthly frequencies. Pricing errors for the typical NYSE stock have a standard deviation of 3.2 percentage points and a half-life of 6.2 weeks. These pricing errors account for 9.4, 7.0, and 4.5 of the respective daily, monthly, and quarterly idiosyncratic return variances.