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Rating the credit rating agencies

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  • Dror Parnes
  • Sagi Akron

Abstract

We offer herein several policy tools that can assist the new Office of Credit Ratings within the Securities and Exchange Commission in assessing the quality of past credit ratings and thus measuring the inclusive competency of credit rating agencies. We propose to weigh the degrees of accuracy, consistency and total synchronization between a tested sample of past ratings and a benchmark array of flawless ratings. We also discuss various techniques to handle major discrepancies between these two arrays of credit ratings. We further explain and demonstrate the importance of different sample sizes. In addition, we present a simple approach to estimate the probability of convergence between the two matched sets of ratings under specified governing thresholds. Lastly, we illustrate the bulk of the theory with a concise empirical investigation.

Suggested Citation

  • Dror Parnes & Sagi Akron, 2016. "Rating the credit rating agencies," Applied Economics, Taylor & Francis Journals, vol. 48(50), pages 4799-4812, October.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:50:p:4799-4812
    DOI: 10.1080/00036846.2016.1164826
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    References listed on IDEAS

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    1. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
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    Cited by:

    1. Wai Choi Lee & Jianfu Shen & Tsun Se Cheong & Michal Wojewodzki, 2021. "Detecting conflicts of interest in credit rating changes: a distribution dynamics approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    2. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Efterpi Doumpa & Maria Stefanidou, 2020. "Forecasting Credit Ratings of EU Banks," IJFS, MDPI, vol. 8(3), pages 1-15, August.

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