Social Media Analysts' Skill: Evidence from Text-Implied Beliefs

Abstract

This paper documents that 56% of nonprofessional social media investment analysts (SMAs) are skilled and declare beliefs that generate positive abnormal returns, while 44% produce negative abnormal returns. 13% of all SMAs are high-skill type and produce a one-week three-factor alpha of 61 bps, while the remaining 87% generate only 6 bps. The distinctive features of high-skill SMAs are primarily firm and industry specializations. Although SMAs tend to extrapolate and herd, their expectations are not systematically wrong. For higher-skilled SMAs compared to the less-skilled ones, extrapolation fades more quickly, and herding is lower, consistent with theory.

Keywords: Nonprofessional analysts, Expectation formation, Social networks, Social finance, Machine learning, Textual analysis

JEL Classification: G11, G12, G14