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Modern credit risk modeling (e.g., Merton, 1974) increasingly relies on advanced mathematical, statistical and numerical echniques to measure and manage risk in redit portfolios
This gives rise to model risk (OCC 201116) and the possibility of nderstating nherent dangers stemming from very rare yet plausible occurrencs perhaps not in our eference datasets International supervisors have recognized the importance of stress testing credit risk in the Basel framework (BCBS, 2009)
It can and has been argued that the art and science of stress testing has lagged in the domain of credit, vs. other types of risk (e.g., market), and our objective is to help fill this vacuum
We aim to present classifications & established techniques that will help practitioners formulate robust credit risk stress tests
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