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
Date Written: May 14, 2017
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
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