The Impact of Public Mood on the Cross-Section of Stock Returns

Abstract

This paper studies the impact of public mood, measured by Twitter messages, on the cross-section of U.S. stock returns. Our Twitter-based mood measure is free of endogeneity from financial market influence and distinct from the weather proxy or sentiment indices more commonly used in existing studies. We show that moody stocks that are more sensitive to public mood earn a higher expected excess return than less mood-sensitive sober stocks. Sorting stocks to construct the risk factor portfolio based on mood betas as sensitivity to mood risk, we are the first to quantify the risk premium (0.56% per month) by holding stocks subject to mood risk. Our results are consistent with the theoretical arguments that investors mistakenly use mood as information that biases investors' decision making and trading behaviors, thereby inducing mispricing in asset valuation.

Keywords: mood beta, sentiment, stock returns, risk premium, asset pricing

JEL Classification: G12, G14, G41