Quantifying systemic risk using Bayesian networks
| Authors |
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| Publication date | 03-2020 |
| Publisher | Risk.net |
| Organisations |
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| 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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