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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. 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.
    2. R. Winkler & Javier Muñoz & José Cervera & José Bernardo & Gail Blattenberger & Joseph Kadane & Dennis Lindley & Allan Murphy & Robert Oliver & David Ríos-Insua, 1996. "Scoring rules and the evaluation of probabilities," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 1-60, June.
    3. Hauck, Achim & Neyer, Ulrike, 2014. "Disagreement between rating agencies and bond opacity: A theoretical perspective," Economics Letters, Elsevier, vol. 123(1), pages 82-85.
    4. 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.
    5. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    6. 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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