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

TL;DR

This paper introduces GIFsentiment, a novel visual-based investor sentiment index derived from GIF posts, which correlates with market behavior and predicts future stock returns, volatility, and trading activity.

Contribution

It presents a new sentiment measure based on GIF images, demonstrating its predictive power for market movements and investor behavior beyond traditional sentiment indicators.

Findings

GIFsentiment correlates with seasonal mood and COVID lockdown severity.

It predicts stock returns up to four weeks ahead.

It is associated with increased trading volume and market volatility.

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.