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Measures of Predictive Success for Rating Functions

Author

Listed:
  • Sebastian Ostrowski

    (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)

  • Peter Reichling

    (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)

Abstract

Aim of our paper is to develop an adequate measure of predictive success and accuracy of rating functions. At first, we show that the common measures of rating accuracy, i.e. area under curve and accuracy ratio, respectively, lack of informative value of single rating classes. Selten (1991) builds up an axiomatic framework for measures of predictive success. Therefore, we introduce a measure for rating functions that fulfills the axioms proposed by Selten (1991). Furthermore, an empirical investigation analyzes predictive power and accuracy of Standard & Poor's and Moody's ratings, and compares the rankings according to area under curve and our measure.

Suggested Citation

  • Sebastian Ostrowski & Peter Reichling, 2010. "Measures of Predictive Success for Rating Functions," FEMM Working Papers 100018, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    • Handle: RePEc:mag:wpaper:100018
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    More about this item

    Keywords

    Accuracy Measure; Rating Functions; Predictive Success; Discriminative Power;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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