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Journal of Applied Mathematics
Volume 2013, Article ID 138272, 12 pages
Research Article

Structural Credit Risk Models with Subordinated Processes

1Department of Management, Economics and Quantitative Methods, University of Bergamo, Via dei Caniana 2, 24127 Bergamo, Italy
2Department of Applied Finance and Actuarial Studies, Macquarie University, Eastern Road, North Ryde, NSW 2109, Australia
3Department of Finance, Faculty of Economics, VŠB-Technical University of Ostrava, Sokolská 33, 70121 Ostrava, Czech Republic

Received 31 January 2013; Accepted 15 July 2013

Academic Editor: Xiaoning Zhang

Copyright © 2013 Martin Gurny et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.