We examine the accuracy and contribution of the default forecasting model based on Merton's (1974) bond pricing model and developed by the KMV corporation. Comparing the KMV-Merton model to a similar but much simpler alternative, we find that it performs slightly worse as a predictor in hazard models and in out of sample forecasts. Moreover, several other forecasting variables are also important predictors, and fitted hazard model values outperform KMV-Merton default probabilities out of sample. Implied default probabilities from credit default swaps and corporate bond yield spreads are only weakly correlated with KMV-Merton default probabilities after adjusting for agency ratings, bond characteristics, and our alternative predictor. We conclude that the KMV-Merton model does not produce a sufficient statistic for the probability of default, and it appears to be possible to construct such a sufficient statistic without solving the simultaneous nonlinear equations required by the KMV-Merton model.
We include the SAS code we use to calculate KMV-Merton default probabilities in an appendix.
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The SAS code used to calculate iterate KMV-Merton default probabilities (using the algorithm applied in the paper) can be downloaded here.