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حسابداری و مالی::
نکول مشترک
The basic reason for this feature is that large losses of a credit portfolio occur when several loans default together, but lack of default data implies that these joint probabilities are very hard to specify2 (joint defaults are "rare events").
Hence, sharpening the VaR bounds by considering the presence of dependence informa- tion (constrained case) is of great practical relevance but also difficult to do because, as pointed out before, knowledge of the joint default probabilities is not in reach practically.
In fact, lack of sufficient default statistics (joint defaults are rarely observed) makes it hard, if not impossible, to specify the probabilities that several loans default together so that the joint distribution of (I1, I2, . . .
12The basic reason is that in the case of (scaled) Bernoulli distributions, knowledge of pairwise correlations and single default probabilities implies knowledge of the (pairwise) joint default probabilities, and thus also knowledge of the distribution of partial sums that only involve two components.
The high degree of model uncertainty for credit risk models is a natural phenomenon in the sense joint defaults are rarely observed, but Credit VaRs are driven by joint defaults.
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