Interbank markets and multiplex networks: centrality measures and statistical null models

TL;DR

This paper reviews the empirical structure of interbank multiplex networks and explores how centrality measures vary across layers and compare with null models, enhancing understanding of systemic risk.

Contribution

It introduces a multiplex network framework for interbank markets and analyzes centrality measures across layers with null models, advancing systemic risk assessment methods.

Findings

Multiplex structure captures diverse interbank link types.

Centrality measures vary significantly across layers.

Null models help identify systemic importance.

Abstract

The interbank market is considered one of the most important channels of contagion. Its network representation, where banks and claims/obligations are represented by nodes and links (respectively), has received a lot of attention in the recent theoretical and empirical literature, for assessing systemic risk and identifying systematically important financial institutions. Different types of links, for example in terms of maturity and collateralization of the claim/obligation, can be established between financial institutions. Therefore a natural representation of the interbank structure which takes into account more features of the market, is a multiplex, where each layer is associated with a type of link. In this paper we review the empirical structure of the multiplex and the theoretical consequences of this representation. We also investigate the betweenness and eigenvector centrality of a bank in the network, comparing its centrality properties across different layers and with Maximum Entropy null models.