Telfer Research Seminar Series and AGRC - Greg Saxton

***M.Sc. Students, this event can count towards one of the six mandatory Research Seminars Series needed to attend (MGT 6191/ MGT 6991 / MHS 6991).***

Greg Saxton, PhD

Networks pervade our social and professional lives, ranging from golfing partnerships and lunch ties to inter-locking board-of-director relations, Facebook friendships, and LinkedIn connections. A core premise of the field of social network analysis is that information flows and network outcomes are heavily influenced by network structure, including the extent to which the network is dominated by a few key actors, how inter-connected network members are, and the prevalence of sub-groups and cliques. We apply this logic to the stock market, analyzing the ego network structure of Twitter cashtag discussion networks for stocks in the S&P 1,500 index in 2018. We posit that the structure of these Twitter cashtag networks – specifically, their centralization, density, clustering, and prevalence of isolates – affects market reactions to quarterly earnings announcements. We find that abnormal market returns are negatively associated with the degree of centralization and density and positively associated with the extent of sub-groups or cliques and the prevalence of unconnected “isolates.” These results highlight the importance of understanding network structures in predicting stock market movements, offering novel insights into the behavioral aspects of financial markets.