Quantifying systemic risk using Bayesian networks

Open Access
Authors
Publication date 03-2020
Publisher Risk.net
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract We develop a novel framework using Bayesian networks to capture distress dependence in the context of counterparty credit risk. Then, we apply this methodology to a wrong-way risk model and stress-scenario testing. Our results show that stress propagation in an interconnected financial system can have a significant impact on counterparty credit exposures
Document type Web publication or website
Note In section Cutting Edge, the quantitative finance section of Risk.net.
Language English
Published at https://www.risk.net/7462701
Downloads
rtp_sourabh_0320_web (Final published version)
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