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

Baltakienė, Margarita and Kanniainen, Juho and Baltakys, Kęstutis, Identification of Information Networks in Stock Markets (December 22, 2020). Journal of Economic Dynamics and Control, Vol. 131, No. 104217, 2021, Available at SSRN: https://ssrn.com/abstract=3750035 or http://dx.doi.org/10.2139/ssrn.3750035

Margarita Baltakienė (Contact Author)

Tampere University

Korkeakoulunkatu 1
Tampere, 33720
Finland

Juho Kanniainen

Tampere University ( email )

P.O. 541, Korkeakoulunkatu 8 (Festia building)
Tampere, FI-33101
Finland

HOME PAGE: http://https://sites.google.com/site/juhokanniainen/

Kęstutis Baltakys

Tampere University ( email )

Tampere, FIN-33101
Finland

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