GIFfluence: A Visual Approach to Investor Sentiment and the Stock Market

Ming Gu, David Hirshleifer, Siew Hong Teoh and Shijia Wu

No 34636, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We study dynamic visual representations as a proxy for investor sentiment about the stock market. Our sentiment index, GIFsentiment, is constructed from millions of posts in the Graphics Interchange Format (GIF) on a leading investment social media platform. GIFsentiment correlates with seasonal mood variations and the severity of COVID lockdowns. It is positively associated with contemporaneous market returns and negatively predicts returns for up to four weeks, even after controlling for other sentiment and attention measures. These effects are stronger among portfolios that are more susceptible to mispricing. GIFsentiment positively predicts trading volume, market volatility, and flows toward equity funds and away from debt funds. Our evidence suggests that GIFsentiment is a proxy for misperceptions that are later corrected.

JEL-codes: C53 D84 D85 D91 G12 G14 G4 G41 (search for similar items in EconPapers)
Date: 2026-01
Note: AP
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Working Paper: GIFfluence: A Visual Approach to Investor Sentiment and the Stock Market (2025)
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