A dynamic network model to measure exposure diversification in the Austrian interbank market

TL;DR

This paper introduces a statistical dynamic network model to measure exposure diversification in the Austrian interbank market, capturing temporal dependencies and analyzing changes during financial crises.

Contribution

It presents a novel Markov-based model for weighted temporal networks to assess financial institutions' diversification levels over time.

Findings

Increasing trend in network homogeneity during crises

Core banks tend to diversify exposures more equally

Model effectively captures temporal dependencies in financial networks

Abstract

We propose a statistical model for weighted temporal networks capable of measuring the level of heterogeneity in a financial system. Our model focuses on the level of diversification of financial institutions; that is, whether they are more inclined to distribute their assets equally among partners, or if they rather concentrate their commitment towards a limited number of institutions. Crucially, a Markov property is introduced to capture time dependencies and to make our measures comparable across time. We apply the model on an original dataset of Austrian interbank exposures. The temporal span encompasses the onset and development of the financial crisis in 2008 as well as the beginnings of European sovereign debt crisis in 2011. Our analysis highlights an overall increasing trend for network homogeneity, whereby core banks have a tendency to distribute their market exposures more equally across their partners.