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Improving performance of corporate rating prediction models by reducing financial ratio heterogeneity

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  • Niemann, Martin
  • Schmidt, Jan Hendrik
  • Neukirchen, Max

Abstract

We introduce a new approach to improve the performance of rating prediction models for multinational corporations. In this segment, the low number of defaults poses a challenge, as it prevents rating models to be constructed for individual industry sectors or regions. We show that reducing group-level heterogeneity in financial ratios results in a rating prediction model with better performance than both unadjusted models and models adjusted by including industry dummies or other simpler procedures. Our approach fills a gap in cases where a limited dataset does not permit the construction of separate models for individual industries or regions.

Suggested Citation

  • Niemann, Martin & Schmidt, Jan Hendrik & Neukirchen, Max, 2008. "Improving performance of corporate rating prediction models by reducing financial ratio heterogeneity," Journal of Banking & Finance, Elsevier, vol. 32(3), pages 434-446, March.
    • Handle: RePEc:eee:jbfina:v:32:y:2008:i:3:p:434-446
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    Cited by:

    1. Martin Kukuk & Michael Rönnberg, 2013. "Corporate credit default models: a mixed logit approach," Review of Quantitative Finance and Accounting, Springer, vol. 40(3), pages 467-483, April.
    2. Jaekyung Lee & Hyunwoo Kim & Hyungkyoo Kim, 2021. "Commercial Vacancy Prediction Using LSTM Neural Networks," Sustainability, MDPI, vol. 13(10), pages 1-17, May.
    3. David Ficbauer & Mária Režňáková, 2014. "Holding Company and Its Performance," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 62(2), pages 329-337.
    4. Michal Karas & Mária Režňáková, 2017. "The Potential of Dynamic Indicator in Development of the Bankruptcy Prediction Models: the Case of Construction Companies," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(2), pages 641-652.
    5. Alexander Karminsky, 2016. "Rating models: emerging market distinctions," Papers 1607.02422, arXiv.org.
    6. So Sohn & Yoon Kim, 2013. "Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking," Small Business Economics, Springer, vol. 41(4), pages 931-943, December.

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