Structural credit risk models with subordinated processes

We discuss structural models based on merton's framework. first,we observe that the classical assumptions of the merton model are generally rejected. secondly,we implement a structural credit risk model 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. © 2013 martin gurny et al.