Reconstructing the Emergent Organization of Information Flows in International Stock Markets: A Computational Complex Systems Approach

Paolo Massimo Buscema (), Francesca Della Torre (), Giulia Massini (), Guido Ferilli and Pier Luigi Sacco ()
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Paolo Massimo Buscema: Semeion, Research Center of Sciences of Communication
Francesca Della Torre: Semeion Research Center
Giulia Massini: Semeion Research Center
Pier Luigi Sacco: IULM University

Computational Economics, 2023, vol. 62, issue 1, No 3, 49-89

Abstract: Abstract In this paper we study the interdependences between the dynamics of the stock market indexes of 30 different stock markets across 29 different countries to analyze the nonlinear dynamics of their information flows. We find that the system exhibits complex dynamic properties that go beyond what has been generally found in the previous literature, suggesting that the structure of information flows is regulated by subtle homeostatic forces that cause the roles of the single markets in the whole network to evolve in unexpected ways. We present a toolkit of ANN-based methods that can be systematically deployed to analyze different aspects of such dynamics.

Keywords: Stock market indexes; Global financial markets; Information flows; Artificial Neural Networks; Complex economic dynamics (search for similar items in EconPapers)
JEL-codes: C45 C63 G17 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10614-022-10267-1

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