Structural Credit Risk Models with Subordinated Processes

We discuss structuralmodels based onMerton’s framework. First, we observe that the classical assumptions of theMertonmodel are generally rejected. Secondly, we implement a structural credit riskmodel based on stable non-Gaussian processes as a representative of subordinated models in order to overcome some drawbacks of the Merton one. Finally, following the KMV-Merton estimation methodology, we propose an empirical comparison between the results obtained from the classical KMV-Merton model and the stable Paretian one. In particular, we suggest alternative parameter estimation for subordinated processes, and we optimize the performance for the stable Paretian model.