Modest means
Credit loss models typically calibrate default separate from loss given default. Here, Jon Frye calibrates simultaneously, using credit loss data. This produces a surprising test result: the credit loss models do not significantly outperform a statistical distribution
This study highlights a mistake that is long overdue for correction. Credit loss models have not been protected against type-I error, that of falsely rejecting a simple model. As such, they can mislead their users. It is shown here that type-I error can be controlled in a credit loss model.
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Modest means
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