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Distress propagation in complex networks: the case of non-linear DebtRank

Preis, Tobias, Bardoscia, Marco, Caccioli, Fabio, Perotti, Juan Ignacio, Vivaldo, Gianna and Caldarelli, Guido (2016) Distress propagation in complex networks: the case of non-linear DebtRank. PLOS ONE, 11 (10). e0163825. ISSN 1932-6203

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Identification Number: 10.1371/journal.pone.0163825


We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a one-parameter family of non-linear propagation functions. As a case study, we apply this algorithm to a data-set of 183 European banks, and we study how the stability of the system depends on the non-linearity parameter under different stress-test scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall stability of the system increases between 2008 and 2013.

Item Type: Article
Official URL:
Additional Information: © 2016 The Authors © CC BY 4.0
Divisions: Systemic Risk Centre
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
H Social Sciences > HG Finance
Sets: Research centres and groups > Systemic Risk Centre
Date Deposited: 12 Dec 2016 15:35
Last Modified: 20 Aug 2021 01:00
Projects: 317532, 610704, 640772, ES/K002309/1, 654024, 676547
Funders: FP7-ICT, FP7-ICT, Horizon 2020, Economic and Social Research Council, Horizon 2020, CoEGSS

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