Structural Credit Risk Models with Subordinated Processes
Martin Gurny,
Sergio Ortobelli Lozza and
Rosella Giacometti
Journal of Applied Mathematics, 2013, vol. 2013, issue 1
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.
Date: 2013
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1155/2013/138272
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2013:y:2013:i:1:n:138272
Access Statistics for this article
More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().