Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/237268 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Financial Innovation [ISSN:] 2199-4730 [Volume:] 7 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2021 [Pages:] 1-22
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
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.
Schlagwörter: 
Credit ratings
Default distribution
Markov renewal equation
Non-homogeneous Markov regenerative process
Recurrence times
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