
 Forecasting Default with the KMVMerton Model by Sreedhar T. Bharath of the University of Michigan, and December 17, 2004 Abstract: 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 KMVMerton 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 KMVMerton default probabilities out of sample. Implied default probabilities from credit default swaps and corporate bond yield spreads are only weakly correlated with KMVMerton default probabilities after adjusting for agency ratings, bond characteristics, and our alternative predictor. We conclude that the KMVMerton 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 KMVMerton model. Books Referenced in this paper: (what is this?) 