The level of systemic risk in economic and financial systems is strongly determined by the structure of the underlying networks of interdependent entities that can propagate shocks and stresses. Since changes in network structure imply changes in risk levels, it is important to identify structural transitions potentially leading to system-wide crises. Methods have been proposed to assess whether a real-world network is in a (quasi-)stationary state by checking the consistency of its structural evolution with appropriate maximum-entropy ensembles of graphs. While previous analyses of this kind have focused on dyadic and triadic motifs, hence disregarding higher-order structures, here we consider closed walks of any length. Specifically, we study the ensemble properties of the spectral radius of random graph models calibrated on real-world evolving networks. Our approach is shown to work remarkably well for directed networks, both binary and weighted. As illustrative examples, we consider the Electronic Market for Interbank Deposit (e-MID), the Dutch Interbank Network (DIN) and the International Trade Network (ITN) in their evolution across the 2008 crisis. By monitoring the deviation of the spectral radius from its ensemble expectation, we find that the ITN remains in a (quasi-)equilibrium state throughout the period considered, while both the DIN and e-MID exhibit a clear out-of-equilibrium behaviour. The spectral deviation therefore captures ongoing topological changes, extending over all length scales, to provide a compact proxy of the resilience of economic and financial networks.

Spectral signatures of structural change in financial networks

Macchiati, Valentina;Mazzarisi, Piero;
2025

Abstract

The level of systemic risk in economic and financial systems is strongly determined by the structure of the underlying networks of interdependent entities that can propagate shocks and stresses. Since changes in network structure imply changes in risk levels, it is important to identify structural transitions potentially leading to system-wide crises. Methods have been proposed to assess whether a real-world network is in a (quasi-)stationary state by checking the consistency of its structural evolution with appropriate maximum-entropy ensembles of graphs. While previous analyses of this kind have focused on dyadic and triadic motifs, hence disregarding higher-order structures, here we consider closed walks of any length. Specifically, we study the ensemble properties of the spectral radius of random graph models calibrated on real-world evolving networks. Our approach is shown to work remarkably well for directed networks, both binary and weighted. As illustrative examples, we consider the Electronic Market for Interbank Deposit (e-MID), the Dutch Interbank Network (DIN) and the International Trade Network (ITN) in their evolution across the 2008 crisis. By monitoring the deviation of the spectral radius from its ensemble expectation, we find that the ITN remains in a (quasi-)equilibrium state throughout the period considered, while both the DIN and e-MID exhibit a clear out-of-equilibrium behaviour. The spectral deviation therefore captures ongoing topological changes, extending over all length scales, to provide a compact proxy of the resilience of economic and financial networks.
2025
Settore STAT-04/A - Metodi matematici dell'economia e delle scienze attuariali e finanziarie
Settore PHYS-02/A - Fisica teorica delle interazioni fondamentali, modelli, metodi matematici e applicazioni
Financial networks; Spectral properties; Systemic risk
   PNRR Infrastrutture di Ricerca - SoBigData.it - Strengthening the Italian RI for Social Mining and Big Data Analytics.
   SoBigData.it
   Ministero della pubblica istruzione, dell'università e della ricerca
   IR0000013

   NetRes - ‘Network analysis of economic and financial resilience’,
   Italian Ministry of University and Research (MUR)
   CUP D67G22000130001

   ‘Reconstruction, Resilience and Recovery of Socio-Economic Networks’
   European Union - Next Generation EU
   RECON-NET EP_FAIR_005 - PE0000013 ‘FAIR’ -

   RE-Net: Reconstructing economic networks: from physics to machine learning and back
   European Union - Next Generation EU
   CUP D53D23002330006

   C2T - From Crises to Theory: towards a science of resilience and recovery for economic and financial system
   European Union - Next Generation EU
   CUP: D53D23019330001
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/151523
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