Can Bank-Specific Variables Predict Contagion Effects?

Quantitative Finance 17(12):1805-1832

47 Pages Posted: 10 Feb 2016 Last revised: 24 Jun 2018

See all articles by Christoph Siebenbrunner

Christoph Siebenbrunner

University of Oxford - Mathematical Institute

Michael Sigmund

Oesterreichische Nationalbank (OeNB)

Stefan Kerbl

Oesterreichische Nationalbank (OeNB)

Date Written: February 10, 2016

Abstract

Assessing the systemic risk a bank poses to the system has become a central part in regulating its capital requirements (e.g. the buffer for global or domestic systemically important banks). As with conventional risk types, systemic risks need to be quantified. Currently global regulators propose a range of bank-specific indicators that measure size and interconnectedness to proxy systemic risk. In this study we gauge the capacity of such indicators to explain contagion losses triggered by realizations of sizeable idiosyncratic shocks. We study contagion impact through different channels, separating these effects into first-round, nth-round, asset fire sale and mark-to-market losses. We provide constructive proofs for the existence of clearing payment vectors and associated market equilibria for these contagion channels in a model of interlinked balance sheets. We provide algorithms that converge to the greatest market equilibrium in a finite number of steps. We evaluate the predictive power of models selected by best-subset selection and Lasso by applying 10-fold panel cross validation. Our empirical results suggest that the Basel III indicator set performs well in comparison to alternative data sets of bank-specific indicators. We also find, however, that the proposed data sets without bank dummies do not perform well in capturing the relevance of the average network position for predicting contagion effects.

Keywords: systemic risk, financial stability, financial contagion

Suggested Citation

Siebenbrunner, Christoph and Sigmund, Michael and Kerbl, Stefan, Can Bank-Specific Variables Predict Contagion Effects? (February 10, 2016). Quantitative Finance 17(12):1805-1832. Available at SSRN: https://ssrn.com/abstract=2730552 or http://dx.doi.org/10.2139/ssrn.2730552

Christoph Siebenbrunner (Contact Author)

University of Oxford - Mathematical Institute ( email )

Andrew Wiles Building,
Radcliffe Observatory Quarter, Woodstock Rd
Oxford, OX2 6GG
United Kingdom

Michael Sigmund

Oesterreichische Nationalbank (OeNB) ( email )

Otto-Wagner-Platz 3, PO Box 61
Vienna,
1010 Vienna, A-1011
Austria

Stefan Kerbl

Oesterreichische Nationalbank (OeNB) ( email )

Otto-Wagner-Platz 3, PO Box 61
Vienna,
1010 Vienna, A-1011
Austria

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