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Comparing Default Predictions in the Rating Industry for Different Sets of Obligors

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  • Walter Kraemer
  • Simon Neumärker

Abstract

We generalize the refinement ordering for well calibrated probability forecasters to the case were the debtors under consideration are not necessarily identical. This ordering is consistent with many well known skill scores used in practice. We also add an illustration using default predictions made by the leading rating agencies Moody’s and S&P.

Suggested Citation

  • Walter Kraemer & Simon Neumärker, 2016. "Comparing Default Predictions in the Rating Industry for Different Sets of Obligors," CESifo Working Paper Series 5768, CESifo.
    • Handle: RePEc:ces:ceswps:_5768
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp5768.pdf
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    References listed on IDEAS

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    1. Boumparis, Periklis & Milas, Costas & Panagiotidis, Theodore, 2015. "Has the crisis affected the behavior of the rating agencies? Panel evidence from the Eurozone," Economics Letters, Elsevier, vol. 136(C), pages 118-124.
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    4. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    5. Czarnitzki, Dirk & Kraft, Kornelius, 2004. "Innovation indicators and corporate credit ratings: evidence from German firms," Economics Letters, Elsevier, vol. 82(3), pages 377-384, March.
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    Cited by:

    1. Krämer, Walter & Neumärker, Simon, 2019. "Skill Scores and modified Lorenz domination in default forecasts," Economics Letters, Elsevier, vol. 181(C), pages 61-64.

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    More about this item

    Keywords

    Moody's; S&P; probability forecasts;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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