A Bayesian methodology for systemic risk assessment in financial networks

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Title: A Bayesian methodology for systemic risk assessment in financial networks
Authors: Gandy, A
Veraart, LAM
Item Type: Journal Article
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.
Issue Date: 6-Oct-2017
Date of Acceptance: 1-Apr-2016
ISSN: 1526-5501
Publisher: INFORMS (Institute for Operations Research and Management Sciences)
Start Page: 4428
End Page: 4446
Journal / Book Title: Management Science
Volume: 63
Issue: 12
Copyright Statement: This article may be used only for the purposes of research, teaching, and/or private study. Commercial use or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publisher approval, unless otherwise noted. For more information, contact Copyright © 2016, INFORMS
Keywords: Social Sciences
Science & Technology
Operations Research & Management Science
Business & Economics
financial network
unknown interbank liabilities
systemic risk
Gibbs sampler
power law
08 Information And Computing Sciences
15 Commerce, Management, Tourism And Services
Operations Research
Publication Status: Published
Appears in Collections:Mathematics
Faculty of Natural Sciences

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