A Numerical Method to Price Defaultable Bonds Based on the Madan and Unal Credit Risk Model
AbstractWe propose a numerical method to price corporate bonds based on the model of default risk developed by Madan and Unal. Using a perturbation approach, we derive two semi-explicit formulae that allow us to approximate the survival probability of the firm issuing the bond very efficiently. More precisely, we consider both the first- and second-order power series expansions of the survival probability in powers of the model parameter c. The zero-order coefficient of the series is evaluated using an exact analytical formula. The first- and second-order coefficients of the series are computed using an approximation algorithm based on the Laplace transform. Extensive simulation is carried out on several test cases where the parameters of the model of Madan and Unal are chosen from Grundke and Riedel, and bonds with different maturities are considered. The numerical experiments performed reveal that the numerical method proposed in this paper is accurate and computationally efficient.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Mathematical Finance.
Volume (Year): 16 (2009)
Issue (Month): 1 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RAMF20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.