Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns

Abstract

The constantly increasing utilization of social media as the alternative information channel, e.g., Twitter, provides us a unique opportunity to investigate the dynamics of the financial market. In this paper, we employ the daily happiness sentiment extracted from Twitter as the proxy for the online sentiment dynamics and investigate its association with the skewness of stock returns of 26 international stock market index returns. The empirical results show that: (1) by dividing the daily happiness sentiment into quintiles from the least to the most happiness days, the skewness of the Most-happiness subgroup is significantly larger than that of the Least-happiness subgroup. Besides, there exist significant differences in any pair of subgroups; (2) in an event study methodology, we further show that the skewness around the highest happiness days is significantly larger than the skewness around the lowest happiness days.