Identification of information networks in stock markets
提出一种新方法识别股票市场中的信息网络，考虑公共信息对投资者交易决策的影响，发现该方法能更精确地揭示投资者网络中心性与收益之间的关系。
We introduce a novel method to identify information networks in stock markets, which explicitly accounts for the impact of public information on investor trading decisions. We show that public information has a clear effect on the empirical investor networks’ topology. Most importantly, our method strengthens the identified relationship between investors’ network centrality and returns. Furthermore, when less significant links are removed, the association between centrality and returns becomes statistically and economically stronger. Findings suggest that our approach leads to a more precise representation of the information network.