• Media type: E-Book
  • Title: Self-Consistency, Subjective Pricing, and a Theory of Credit Rating
  • Contributor: Guo, Nan [Author]; Kou, Steven [Other]; Wang, Bin [Other]; Wang, Ruodu [Other]
  • Published: [S.l.]: SSRN, [2020]
  • Extent: 1 Online-Ressource (47 p)
  • Language: English
  • DOI: 10.2139/ssrn.3504065
  • Identifier:
  • Keywords: Credit ratings ; Structured finance ; Dodd-Frank ; Axiomatic characterization
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 14, 2019 erstellt
  • Description: We propose a theory for rating financial securities based on a concept of self-consistency, which does not allow issuers to gain, by tranching financial securities, from investors who rely on the rating criterion. While the expected loss criterion used by Moody's satisfies self-consistency, the probability of default criterion used by S&P does not. We find empirical evidences in the post-Dodd-Frank period (i.e., after July 2010) that the issuers may take advantage of the absence of self-consistency. We further propose a concept of scenario-relevance which reflects practical evaluation procedures of potential losses from defaultable securities. Our main theoretical results show that a self-consistent rating measure admits a Choquet integral representation, and this representation is also analytically tractable if one further takes economic scenarios into account. We suggest new examples of self-consistent and scenario-based rating criteria, such as ones based on the VaR and the Expected Shortfall
  • Access State: Open Access