Abstract
The ASFR model computes a credit value at risk for a given default probability and asset correlation. Since the default probability is usually estimated from historical default data, the value at risk may also be considered to be an estimate, based on the same data. We demonstrate that even if the default probability is estimated without bias, the value at risk estimation will be biased due to the non-linearity of the VaR function. The bias is negative so that the value at risk is underestimated systematically. We suggest how to compute a correction term which reduces the bias. This may be interpreted as including 'estimation risk' into the risk calculation.
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