Abstract
In this thesis I develop a model for describing the dynamic behavior of Credit Migration Matrices under a Point-in-time Rating Philosophy. Characteristics of the yearly Migration Matrices following a Point-in-Time Philosophy are presented. Through the introduction of the concept of Rating Migration Velocity, the characteristics can be summarized with one quantity. Which is specified by the direction and the speed of the migrations. The direction of a migration matrix is the difference between the upgrades and the downgrades. The speed capture the magnitude of the migrations, high speed leads to migrations over several rating classes and low speed leads to migrations that are close to the diagonal of the migration matrix. The model I introduce is an Affine Markov Chain Model with Regime Shifting Migration Matrices that extends the Affine Markov Chain Model of Hurd and Kuznetsov (2006a). The model can be separated into a two-dimensional Markov Chain, with two time-homogeneous Markov Chains, driven by stochastic time changes \tau_G \tau_B. The shift between the chains are govern by a regime shifting parameter qt, depending on the status of the economic cycle. Under this new framework I give analytical solutions for Credit Derivatives ranging from Defaultable Bonds to CDSs and CDOs.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
