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...

We propose a network model with communities to study the stock co-jump dependency. To estimate the community structure, we extend the SCORE algorithm in Jin (2015) and develop a Spectral Clustering On Ratios-of-Eigenvectors for networks with Dependent Multivariate Poisson edges (SCORE-DMP)...

Purpose: In order to investigate community structure of the component stocks of SSE (Shanghai Stock Exchange) 180-index, a stock correlation network is built to find the intracommunity and inter-community relationship. Design/methodology/approach: The stock correlation network is built taking...