Price Shock Detection With an Influence-Based Model of Social Attention

Abstract

There has been increasing interest in exploring the impact of human behavior on financial market dynamics. One of the important related questions is whether attention from society can lead to significant stock price movements or even abnormal returns. To answer the question, we develop a new measurement of social attention, named periodic cumulative degree of social attention , by simultaneously considering the individual influence and the information propagation in social networks. Based on the vast social network data, we evaluate the new attention measurement by testing its significance in explaining future abnormal returns. In addition, we test the forecasting ability of social attention for stock price shocks, defined by the cumulative abnormal returns. Our results provide significant evidence to support the intercorrelated relationship between the social attention and future abnormal returns. The outperformance of the new approach in predicting price shocks is also confirmed by comparison with several benchmark methods.