Crowdsourced Financial Analysis and Information Asymmetry at Earnings Announcements
44 Pages Posted: 8 Nov 2018 Last revised: 7 Dec 2018
Date Written: November 2018
We investigate whether a relatively new phenomenon, crowdsourced financial analysis, helps level the playing field among investors at earnings announcements. Earnings announcements precipitate high information flows that yield significant information advantages for more-sophisticated investors, resulting in heightened information asymmetry. We predict and find that more crowdsourced financial analysis during the weeks before an earnings announcement significantly mitigates this increase in information asymmetry. Further, we find this effect is stronger for firms operating in poorer information environments (lower press coverage and analyst following) and for firms failing to provide voluntary earnings guidance. Additional analyses reinforce our primary inferences by indicating that crowdsourced financial analysis (1) is most useful to less- sophisticated investors and (2) reduces opinion divergence at earnings announcements. Overall, our evidence suggests the crowds play an important role in leveling the playing field among investors.
Keywords: Social Media, Crowdsourcing, Information Asymmetry, Earnings Announcements, Bid-ask Spreads
JEL Classification: M41, M21, G00, G12, O33
Suggested Citation: Suggested Citation