Please use this identifier to cite or link to this item:
https://doi.org/10.1016/j.jfds.2021.05.001
DC Field | Value | |
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dc.title | Enhanced PD-implied ratings by targeting the credit rating migration matrix | |
dc.contributor.author | Duan, Jin-Chuan | |
dc.contributor.author | Li, Shuping | |
dc.date.accessioned | 2022-10-11T07:52:23Z | |
dc.date.available | 2022-10-11T07:52:23Z | |
dc.date.issued | 2021-11-01 | |
dc.identifier.citation | Duan, Jin-Chuan, Li, Shuping (2021-11-01). Enhanced PD-implied ratings by targeting the credit rating migration matrix. Journal of Finance and Data Science 7 : 115-125. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jfds.2021.05.001 | |
dc.identifier.issn | 2405-9188 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/232002 | |
dc.description.abstract | A high-quality and granular probability of default (PD) model is on many practical dimensions far superior to any categorical credit rating system. Business adoption of a PD model, however, needs to factor in the long-established business/regulatory conventions built around letter-based credit ratings. A mapping methodology that converts granular PDs into letter ratings via referencing the historical default experience of some credit rating agency exists in the literature. This paper improves the PD implied rating (PDiR) methodology by targeting the historical credit migration matrix instead of simply default rates. This enhanced PDiR methodology makes it possible to bypass the reliance on arbitrarily extrapolated target default rates for the AAA and AA+ categories, a necessity due to the fact that the historical realized default rates on these two top rating grades are typically zero. © 2021 The Authors | |
dc.publisher | KeAi Communications Co. | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Scopus OA2021 | |
dc.subject | Default | |
dc.subject | Other-exit | |
dc.subject | Rating stickiness | |
dc.subject | Sequential Monte Carlo | |
dc.type | Article | |
dc.contributor.department | RISK MANAGEMENT INSTITUTE | |
dc.contributor.department | ASIAN INSTITUTE OF DIGITAL FINANCE | |
dc.description.doi | 10.1016/j.jfds.2021.05.001 | |
dc.description.sourcetitle | Journal of Finance and Data Science | |
dc.description.volume | 7 | |
dc.description.page | 115-125 | |
Appears in Collections: | Staff Publications Elements |
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