Social media information diffusion and excess stock returns co-movement

Abstract

This research investigates the dynamic interplay between information diffusion on social media platforms and the co-movement of excess stock returns through a comprehensive methodology encompassing the multilayer complex network analysis, panel vector autoregression (PVAR) modeling, and the thermal optimal path (TOP) approach. Utilizing weekly data spanning from January 1, 2016, to December 31, 2021, our research finds a significant interrelationship between information diffusion and excess co-movement, notably shaped by exogenous shocks, such as the COVID-19 outbreak. We investigate the microcosmic mechanism, revealing that variations in excess co-movement significantly impact the information interaction behaviors of individual investors within sub-forums, subsequently influencing their trading activities across related stocks. Moreover, stocks characterized by a heightened strength of information diffusion exhibit swifter responsiveness to new information and demonstrate superior performance in hedging strategies involving the IC500 stock index futures. These findings hold potential to aid regulators and investors in comprehending risk transmission within the stock market and refining portfolio management. A heightened understanding of the role played by information interaction among individual investors via social media in the co-movement of excess stock returns empowers informed decision-making and risk mitigation.