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Systemic liquidity contagion in the European interbank market
Authors:Macchiati  Valentina  Brandi  Giuseppe  Di Matteo  Tiziana  Paolotti  Daniela  Caldarelli  Guido  Cimini  Giulio
Affiliation:1.Scuola Normale Superiore, 56126, Pisa, Italy
;2.Department of Mathematics, King’s College London, WC2R 2LS, London, UK
;3.Complexity Science Hub Vienna, 1080, Vienna, Austria
;4.Data Science for Social Impact, ISI Foundation, 10126, Turin, Italy
;5.DSMN, University of Venice Ca’ Foscari, 30172, Venice, Italy
;6.Dipartimento di Fisica and INFN, Università degli Studi di Roma Tor Vergata, 00133, Rome, Italy
;7.Centro Ricerche Enrico Fermi, 00184, Rome, Italy
;8.IMT School for Advanced Studies, 55100, Lucca, Italy
;9.Institute for Complex Systems (ISC-CNR) UoS Sapienza, 00185, Rome, Italy
;10.European Centre for Living Technology, 30124, Venice, Italy
;
Abstract:

Systemic liquidity risk, defined by the International Monetary Fund as “the risk of simultaneous liquidity difficulties at multiple financial institutions,” is a key topic in financial stability studies and macroprudential policy-making. In this context, the complex web of interconnections of the interbank market plays the crucial role of allowing funding liquidity shortages to propagate between financial institutions. Here, we introduce a simple yet effective model of the interbank market in which liquidity shortages propagate through an epidemic-like contagion mechanism on the network of interbank loans. The model is defined by using aggregate balance sheet information of European banks, and it exploits country and bank-specific risk features to account for the heterogeneity of financial institutions. Moreover, in order to obtain the European-wide topology of the interbank network, we define a block reconstruction method based on the exchange flows between the various countries. We show that the proposed contagion model is able to estimate systemic liquidity risk across different years and countries. Results suggest that our effective contagion approach can be successfully used as a viable alternative to more realistic but complicated models, which not only require more specific balance sheet variables with high time resolution but also need assumptions on how banks respond to liquidity shocks.

Keywords:
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