Identification of Information Networks in Stock Markets
15 Pages Posted: 12 Jan 2021 Last revised: 13 Oct 2021
Date Written: December 22, 2020
Abstract
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.
Keywords: information channels, information transfer, investor network, network inference, private information, public information
JEL Classification: D8, G10
Suggested Citation: Suggested Citation