Microblogging Metrics and Stock Return Comovement

Abstract

Stock return comovement analysis is important to financial analysts, decision makers, and academic researchers, in many financial implications, such as, portfolio management, style investing, and market risk detecting. This paper examines firms’ social media, in particular, microblogging metrics’ role on analyzing stock return comovement. Social media allows firms to proactively connect with public users, customers, suppliers, and other business partners. It also provides us a large-scale and free data set to automatically and quickly uncover firms’ social media metrics’ influence on financial outcomes. Most prior studies of social media metrics focused on overall firm metrics and their predictability on stock returns. However, the role of firms proactive activities has been omitted. This paper filled this gap by using cross-sectional data from the US and China to investigate on how firm-specific social media metrics make an impact to the stock return comovement. The results show starting with the four-digit Global Industry Classification Standard (GICS) system, the stock groups that are divided by firms’ effect microblogging metrics, have a higher comovement than six-digit GICS groups.