Social dynamics of financial networks

Teruyoshi Kobayashi,Taro Takaguchi

doi:10.1140/epjds/s13688-018-0143-y

Abstract

Recurrent interactions between agents play an essential role in the organization of a dynamic complex system. While intensive researches have been done on social systems formed by human interactions, dynamical rules are not well understood in economic systems. Here we study the evolution of financial networks and show that repeated interactions between financial institutions taking place at the daily scale are characterized by social communication patterns of humans emerging at higher time scales. The “social” dynamics of financial interactions are highly stable and little affected by external shocks such as the occurrence of the global financial crisis. A dynamic network model based on random pairwise matching accurately explains the observed daily dynamical patterns. The observed similarity between social and financial interactions gives us previously unknown stylized facts about a financial system, which could lead to a deeper understanding of the fundamental source of systemic risk.

Highlights

Financial systemic risk is one of the most serious threats to the global economy
2 Results The dataset to be analyzed in this work is the time series of daily networks identified from the time-stamped data of interbank transactions conducted in the Italian interbank market during 2000–2015
One may regard the amount of funds transferred from a lender to a borrower as edge weights, but here we regard the daily networks as unweighted, since we found that the dynamics of edge weights can be understood independently from the edge dynamics themselves

Summary

Introduction

Financial systemic risk is one of the most serious threats to the global economy. The global financial crisis of 2007–2009 showed that a failure of one bank can lead to a financial contagion through a complex web of financial linkages, which are created by everyday transactions among financial institutions [1,2,3,4,5,6]. Many previous studies attempt to assess systemic risk by simulating different scenarios of cascading bank failures on both real [16,17,18,19,20] and synthetic interbank credit networks [15, 21,22,23,24,25,26]. Since the great majority of real-world interbank transactions are overnight [13, 28], interbank networks should be treated as dynamical systems with their structure changing on a daily basis. This temporal nature of real interbank networks inevitably limits the practical usefulness of the conventional static approach to systemic risk. The current lack of studies on the mechanics of real interbank networks is in stark contrast to the abundance of research on their static property [16, 19, 31,32,33,34]

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Conclusion