Early Warning of Systemic Risk In Global Banking: Eigen-Pair R Number for Financial Contagion and Market Price-based Methods

43 Pages Posted: 17 Jan 2017 Last revised: 22 Apr 2021

See all articles by Sheri M. Markose

Sheri M. Markose

University of Essex - Department of Economics

Simone Giansante

University of Palermo - Department of Economics, Business and Statistics; University of Bath - School of Management

Nicolas A. Eterovic

Central Bank of Chile

Mateusz Gatkowski

University of Essex - Centre for Computational Finance and Economic Agents

Date Written: December 30, 2020

Abstract

We analyse systemic risk in the core global banking system using a new network-based spectral eigen-pair method, which treats network failure as a dynamical system stability problem. This is compared with market price-based Systemic Risk Indexes (SRIs), viz. MES (Marginal Expected Shortfall), Delta Conditional Value-at-Risk (∆CoVaR), and Conditional Capital Shortfall Measure of Systemic Risk (SRISK) in a cross-border setting. Unlike paradoxical market price based risk measures, which underestimate risk during periods of asset price booms, the eigen-pair method based on bilateral balance sheet data gives early-warning of instability in terms of the tipping point that is analogous to the R number in epidemic models. For this regulatory capital thresholds are used. Furthermore, network centrality measures identify systemically important and vulnerable banking systems. Market price-based SRIs are contemporaneous with the crisis and they are found to covary with risk measures like VaR and betas.

Keywords: Global Financial Networks, Systemic Risk, Early Warning Signals, Eigen-Pair Analysis, Statistical Market Price-Based Risk Measures, Paradoxical Risk Measures.

JEL Classification: G21, G15, G28, E44, C63.

Suggested Citation

Markose, Sheri M. and Giansante, Simone and Eterovic, Nicolas A. and Gatkowski, Mateusz, Early Warning of Systemic Risk In Global Banking: Eigen-Pair R Number for Financial Contagion and Market Price-based Methods (December 30, 2020). Available at SSRN: https://ssrn.com/abstract=2899930 or http://dx.doi.org/10.2139/ssrn.2899930

Sheri M. Markose (Contact Author)

University of Essex - Department of Economics ( email )

Wivenhoe Park
Colchester CO4 3SQ
United Kingdom
01206 87 2742 (Phone)

Simone Giansante

University of Palermo - Department of Economics, Business and Statistics ( email )

Viale delle Scienze
Palermo, 90100
Italy

University of Bath - School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

HOME PAGE: http://people.bath.ac.uk/sg473/index.html

Nicolas A. Eterovic

Central Bank of Chile ( email )

Publicaciones
Huerfanos 1185
Santiago
Chile
956452658 (Phone)
7510138 (Fax)

HOME PAGE: http://https://www.bcentral.cl/web/banco-central/investigadores/nicolas-eterovic

Mateusz Gatkowski

University of Essex - Centre for Computational Finance and Economic Agents ( email )

Wivenhoe Park
Colchester, Essex CO4 3SQ
United Kingdom

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