Systemic liquidity contagion in the European interbank market

被引:0
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作者
Valentina Macchiati
Giuseppe Brandi
Tiziana Di Matteo
Daniela Paolotti
Guido Caldarelli
Giulio Cimini
机构
[1] Scuola Normale Superiore,Department of Mathematics
[2] King’s College London,Data Science for Social Impact
[3] Complexity Science Hub Vienna,DSMN
[4] ISI Foundation,Dipartimento di Fisica and INFN
[5] University of Venice Ca’ Foscari,undefined
[6] Università degli Studi di Roma Tor Vergata,undefined
[7] Centro Ricerche Enrico Fermi,undefined
[8] IMT School for Advanced Studies,undefined
[9] Institute for Complex Systems (ISC-CNR) UoS Sapienza,undefined
[10] European Centre for Living Technology,undefined
关键词
Financial contagion; Liquidity shocks; Epidemic model; European Interbank market; C63; G01; G15; G21;
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学科分类号
摘要
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.
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页码:443 / 474
页数:31
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