Term structures of conditional probabilities of corporate default in an incomplete information setting

With the emergence and expansion of credit derivatives, which are financial instruments that are based on corporate bonds and provide their holders a protection against default, the importance of estimating probabilities of default has reached an unprecedented level. We have developed a Bayesian model to estimate term structures of conditional probabilities of corporate default, in an incomplete information setting. In such settings, investors do not have a complete picture of the economy nor of the true financial status of a firm. Therefore, we introduce a stochastic frailty to capture this unobservable source of uncertainty and to model default clustering. Frailty is found to have an impact on conditional default probabilities and on the default correlation between firms. The resulting values are well above those predicted by observable stochastic covariates: US interest rates, US Personal Income and a firm's distance-to-default.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Engineering

Grantor

Rice University

Year dc:date.issued

2008

Author dc:creator

• Jabri, Hanane

Advisor dc:contributor.advisor

• Riedi, Rudolf H.

• Statistics
• Economics
• Finance

Statement dc:rights

• Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1911/22240

OAI identifier oai:identifier

oai:repository.rice.edu:1911/22240