Cliometrics of world stock markets evolving networks

This article crosses two fields: financial cliometrics and networks graphs. The results illustrate that the field of application of operations research methods on graphs is very broad. We assess how the web of global stock markets linkages has changed over 1960-2018. We compute minimum spanning trees and hierarchical trees using six institutional sub-periods, and document the long term evolution of network patterns using different network metrics. Then we analyse the time dynamics of linkages, focusing on the most connected nodes. Finally, we analyse the effect of the network structure on system resilience. We highlight two main contributions of network graphs and operations research methods to financial cliometrics. First, we highlight a long term evolution of stock market network patterns from a monostar to a multistar network. This structural shift is associated to a greater connectivity of the hubs, leading to less resilience of the system. The sharp decrease in local path lengths strengthens this effect. Our second major outcome is that network graphs provide a methodological corpus to explain the role of path dependence in financial history. This is particularly true to explain the persistent centrality of a small number of hubs of world stock markets networks.

Automated summary

This article examines the application of operations research methods on network graphs in financial cliometrics. The results demonstrate the broad field of application for these methods. Through analyzing the evolution of the global stock market network and its impact on system resilience, the study highlights the role of network structure and path dependence in financial history.