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Structural Credit Risk Models with Subordinated Processes

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  • Martin Gurny
  • Sergio Ortobelli Lozza
  • Rosella Giacometti

Abstract

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.

Suggested Citation

  • Martin Gurny & Sergio Ortobelli Lozza & Rosella Giacometti, 2013. "Structural Credit Risk Models with Subordinated Processes," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-12, August.
    • Handle: RePEc:hin:jnljam:138272
    DOI: 10.1155/2013/138272
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