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Statistics & Risk Modeling

with Applications in Finance and Insurance

Editor-in-Chief: Stelzer, Robert

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Volume 33, Issue 3-4

Issues

Leveraging the network: A stress-test framework based on DebtRank

Stefano Battiston
  • Corresponding author
  • Department of Banking and Finance, University of Zurich, Plattenstrasse 14,8032 Zürich, Switzerland
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/ Guido Caldarelli
  • IMT Alti Studi Lucca, ISC-CNR, Rome, Italy; and LIMS London, United Kingdom of Great Britain and Northern Ireland
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/ Marco D’Errico / Stefano Gurciullo
Published Online: 2016-08-19 | DOI: https://doi.org/10.1515/strm-2015-0005

Abstract

We develop a novel stress-test framework to monitor systemic risk in financial systems. The modular structure of the framework allows to accommodate for a variety of shock scenarios, methods to estimate interbank exposures and mechanisms of distress propagation. The main features are as follows. First, the framework allows to estimate and disentangle not only first-round effects (i.e. shock on external assets) and second-round effects (i.e. distress induced in the interbank network), but also third-round effects induced by possible fire sales. Second, it allows to monitor at the same time the impact of shocks on individual or groups of financial institutions as well as their vulnerability to shocks on counterparties or certain asset classes. Third, it includes estimates for loss distributions, thus combining network effects with familiar risk measures such as VaR and CVaR. Fourth, in order to perform robustness analyses and cope with incomplete data, the framework features a module for the generation of sets of networks of interbank exposures that are coherent with the total lending and borrowing of each bank. As an illustration, we carry out a stress-test exercise on a dataset of listed European banks over the years 2008–2013. We find that second-round and third-round effects dominate first-round effects, therefore suggesting that most current stress-test frameworks might lead to a severe underestimation of systemic risk.

Keywords: Systemic risk; leverage network; stress-test

MSC 2010: 91B30

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About the article

Received: 2015-02-27

Revised: 2016-02-22

Accepted: 2016-07-26

Published Online: 2016-08-19

Published in Print: 2016-12-01


Funding Source: European Commission

Award identifier / Grant number: FET Open project SIMPOL nr. 610704

Award identifier / Grant number: FET Open DOLFINS nr. 640772

Award identifier / Grant number: ERC grant RMAC nr. 249415

SB and MD acknowledge support from the European Commission FET Open project SIMPOL nr. 610704, the European Commission FET Open DOLFINS nr. 640772, the European Commission ERC grant RMAC nr. 249415, and the Swiss National Science Foundation (SNF) Professorship grant no. PP00P1-144689.


Citation Information: Statistics & Risk Modeling, Volume 33, Issue 3-4, Pages 117–138, ISSN (Online) 2196-7040, ISSN (Print) 2193-1402, DOI: https://doi.org/10.1515/strm-2015-0005.

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