Randomized structural models of credit spreads
AbstractWe propose to randomize the initial condition of a generalized structural model, where the solvency ratio instead of the asset value is modeled explicitly. This initial randomization assumption is motivated by the fact that market players cannot observe the solvency ratio accurately. We find that positive short spreads can be produced due to imperfect observation of the risk factor. The two models we have considered, the Randomized Merton (RM) and the Randomized Black--Cox (RBC) models, both have explicit expressions for the Probability of Default (PD) and Credit Spreads (CS). In the RM model, both PD and LGD are found to be of order , as the maturity T approaches zero. It therefore provides an example that has no well-defined default intensity but still admits positive short spreads. In the RBC model, the positive short spread is generated through the positive default intensity of the model. Because explicit formulas are available, these two Randomized Structure (RS) models are easily implemented and calibrated to market data. This is illustrated by a calibration exercise on Credit Default Swap (CDS) spread data of the Ford Motor Corporation.
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.
Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Quantitative Finance.
Volume (Year): 11 (2011)
Issue (Month): 9 (July)
Contact details of provider:
Web page: http://taylorandfrancis.metapress.com/link.asp?target=journal&id=111405
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
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.