Estimating a Credit Rating for Accounting Purposes: A Quantitative Approach

  1. DAVID DELGADO-VAQUERO 2
  2. JOSÉ MORALES-DÍAZ 1
  1. 1 Instituto de Estudios Bursátiles
  2. 2 EY Corporate Treasury
Revista:
Estudios de economía aplicada

ISSN: 1133-3197,  1697-5731

Año de publicación: 2018

Título del ejemplar: Efectos de las Normas Internacionales de Información Financiera (NIIF) en los estados financieros de las empresas

Volumen: 36

Número: 2

Páginas: 459-488

Tipo: Artículo

DOI: 10.25115/EEA.V36I2.2539 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Estudios de economía aplicada

Resumen

Under IFRS accounting standards, there are many situations in which the credit quality of a counterparty must be estimated. These include, for example, credit value adjustment of derivatives under IFRS 13; expected loss provisioning under IFRS 9; or own borrowing rate estimation under IFRS 16. In many cases, the inputs needed (generally a conditional probability of default (PD) or a yield to maturity (YTM) can be directly observed in the market or inferred from the quoted price of financial/credit instruments (e.g. liquid par CDSs or bonds), but in other cases this information is not available. With regard to the latter, we propose two models for internally estimating the credit quality of a counterparty as a basis (a first step) for obtaining the corresponding PD or YTM for said counterparty. The models (Financial Ratios Scoring and Merton KMV Structural Model) are based in part on previous literature, but they are more “universal” and better adapted to accounting purposes. For inputs, the models use public information about the counterparty (primarily financial information obtained from financial statements and other market inputs), and comparable companies

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