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The credit risk models we have examined thus far in this book have all focused on single default events, or on the likelihood that a given firm will default on its financial obligations within a given period of time. We shall now shift gears, so to speak, and take a quick tour of approaches and techniques that are useful for modeling credit risk in a portfolio setting. As we saw in Chapters 9, 10, and 14, two key concepts in the modeling of portfolio credit risk are default correlation and the loss distribution function. The basic model discussed in this chapter allows us to take a closer quantitative look at these concepts.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |