Mood Swings and Insufficient Information Acquisition: A Study on Cross-Section of Stock Returns

Abstract

This paper studies mood, measured by Twitter messages, which causes investors' insufficient acquisition of information about assets and the implications of asset pricing. Using a Twitter-based mood measure, we find that mood swings are negatively predictive of investors' acquisition of earnings-related information when seeking to learn about companies' performance. Therefore, we argue that this bias effect contributes to the explanation of classical (unconditional) pricing models' failures. Conducting tests on cross-sectional stock returns, we show that stocks that are more sensitive to mood earn a higher expected excess return than less mood-sensitive 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 prediction that investors mistakenly use mood as information rather than learning enough fundamental information about assets, thereby inducing mispricing in asset valuation.

Keywords: Information Acquisition; Mood; Mood Beta; Risk Premium; Anomalies

JEL Classification: G12, G14, G41