Abstract Despite the rapid growth of podcasts as a source of investment information, we know little about their potential capital market effects. We find that the release of podcasts that provide listeners with firm-specific investment analysis is associated with significant increases in trading activity, particularly among retail investors. When released following earnings announcements, investing podcasts appear to provide information to less-informed investors that helps them better process the news, as podcast discussion is associated with reductions in information asymmetry. This effect is stronger for podcasts that include guests, have greater narrative distinctiveness across speakers, convey information more rapidly, and focus more on fundamental analysis. Podcast discussion is also associated with faster price formation and heightened earnings response coefficients, with no evidence of return reversals. Overall, our results are consistent with investing podcasts helping investors to better process information and provide novel evidence on how this emerging technology impacts capital markets.

ABSTRACT We provide the first comprehensive analysis of the properties of investment recommendations generated by “Robo-Analysts,” which are human analyst-assisted computer programs conducting automated research analysis. Our results indicate that Robo-Analyst recommendations differ from those produced by traditional “human” research analysts across several important dimensions. First, Robo-Analysts produce a more balanced distribution of buy, hold, and sell recommendations than do human analysts and are less likely to recommend “glamour” stocks and firms with prospective investment banking business. Second, automation allows Robo-Analysts to revise their recommendations more frequently than human analysts and incorporate information from complex periodic filings. Third, while Robo-Analysts' recommendations exhibit weak short-window return reactions, they have long-term investment value. Specifically, portfolios formed based on the buy recommendations of Robo-Analysts significantly outperform those of human analysts. Overall, our results suggest that automation in the sell-side research industry can benefit investors. JEL Classifications: G14; G24.