A Bayesian methodology for systemic risk assessment in financial networks

Axel Gandy and Luitgard A. M. Veraart

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We develop a Bayesian methodology for systemic risk assessment in financial networks such as the interbank market. Nodes represent participants in the network and weighted directed edges represent liabilities. Often, for every participant, only the total liabilities and total assets within this network are observable. However, systemic risk assessment needs the individual liabilities. We propose a model for the individual liabilities, which, following a Bayesian approach, we then condition on the observed total liabilities and assets and, potentially, on certain observed individual liabilities. We construct a Gibbs sampler to generate samples from this conditional distribution. These samples can be used in stress testing, giving probabilities for the outcomes of interest. As one application we derive default probabilities of individual banks and discuss their sensitivity with respect to prior information included to model the network. An R-package implementing the methodology is provided.

Keywords: Financial network; unknown interbank liabilities; systemic risk; Bayes; MCMC; Gibbs sampler; power law (search for similar items in EconPapers)
JEL-codes: F3 G3 (search for similar items in EconPapers)
Date: 2017-12-01
New Economics Papers: this item is included in nep-ban, nep-net and nep-rmg
References: Add references at CitEc
Citations: View citations in EconPapers (31)

Published in Management Science, 1, December, 2017, 63(12), pp. 4428 -4446. ISSN: 0025-1909

Downloads: (external link)
http://eprints.lse.ac.uk/66312/ Open access version. (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:66312

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager (lseresearchonline@lse.ac.uk).