Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/237268 
Year of Publication: 
2021
Citation: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 7 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2021 [Pages:] 1-22
Publisher: 
Springer, Heidelberg
Abstract: 
This study proposes a non-homogeneous continuous-time Markov regenerative process with recurrence times, in particular, forward and backward recurrence processes. We obtain the transient solution of the process in the form of a generalized Markov renewal equation. A distinguishing feature is that Markov and semi-Markov processes result as special cases of the proposed model. To model the credit rating dynamics to demonstrate its applicability, we apply the proposed stochastic process to Standard and Poor's rating agency's data. Further, statistical tests confirm that the proposed model captures the rating dynamics better than the existing models, and the inclusion of recurrence times significantly impacts the transition probabilities.
Subjects: 
Credit ratings
Default distribution
Markov renewal equation
Non-homogeneous Markov regenerative process
Recurrence times
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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