We study the out‐of‐sample and post‐publication return predictability of 97 variables shown to predict cross‐sectional stock returns. Portfolio returns are 26% lower out‐of‐sample and 58% lower post‐publication. The out‐of‐sample decline is an upper bound estimate of data mining effects. We estimate a 32% (58%–26%) lower return from publication‐informed trading. Post‐publication declines are greater for predictors with higher in‐sample returns, and returns are higher for portfolios concentrated in stocks with high idiosyncratic risk and low liquidity. Predictor portfolios exhibit post‐publication increases in correlations with other published‐predictor portfolios. Our findings suggest that investors learn about mispricing from academic publications.

We show that venture capitalists' (VCs) on‐site involvement with their portfolio companies leads to an increase in both innovation and the likelihood of a successful exit. We rule out selection effects by exploiting an exogenous source of variation in VC involvement: the introduction of new airline routes that reduce VCs' travel times to their existing portfolio companies. We confirm the importance of this channel by conducting a large‐scale survey of VCs, of whom almost 90% indicate that direct flights increase their interaction with their portfolio companies and management, and help them better understand companies' activities.