Contagion in Financial Systems: A Bayesian Network Approach

SIAM Journal on Financial Mathematics, accepted for publication, 2017.

26 Pages Posted: 6 Jul 2016 Last revised: 17 Jul 2017

See all articles by Carsten Chong

Carsten Chong

Technische Universität München (TUM) - Chair of Mathematical Statistics

C. Klüppelberg

Technische Universität München (TUM)

Date Written: May 14, 2017

Abstract

We develop a structural default model for interconnected financial institutions in a probabilistic framework. For all possible network structures we characterize the joint default distribution of the system using Bayesian network methodologies. Particular emphasis is given to the treatment and consequences of cyclic financial linkages. We further demonstrate how Bayesian network theory can be applied to detect contagion channels within the financial network, to measure the systemic importance of selected entities on others, and to compute conditional or unconditional probabilities of default for single or multiple institutions.

Keywords: Bayesian Network; Financial Contagion; Measure of Systemic Risk; Multivariate Default Risk; Probability of Default; Structural Default Risk Model; Systemic Risk

JEL Classification: C11, C62, C63, D85, G01, G32

Suggested Citation

Chong, Carsten and Kluppelberg, Claudia, Contagion in Financial Systems: A Bayesian Network Approach (May 14, 2017). SIAM Journal on Financial Mathematics, accepted for publication, 2017., Available at SSRN: https://ssrn.com/abstract=2804291 or http://dx.doi.org/10.2139/ssrn.2804291

Carsten Chong (Contact Author)

Technische Universität München (TUM) - Chair of Mathematical Statistics ( email )

Boltzmannstr. 3
Garching, 85748
Germany

Claudia Kluppelberg

Technische Universität München (TUM) ( email )

Center for Mathematical Sciences
D-80290 Munich
Germany

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