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Credit rating score analysis

Author

Listed:
  • Härdle, Wolfgang Karl
  • Fai, Phoon-kok
  • Lee, David Kuo Chuen

Abstract

We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity. A principal component analysis of the data reveals that based on the chosen risk factors alone we cannot identify a single underlying latent source of risk in the data. Conversely, the chosen complexity factors are clearly related to one or two underlying sources of complexity. For the sample we find a clear positive relation between the first principal component and the total expert score. An attempt to match the securities' expert score by linear projection of their individual factor scores yields a best case correlation between expert score and projection of 0.9952. However, the sum of squared differences is, at 46.5552, still notable.

Suggested Citation

  • Härdle, Wolfgang Karl & Fai, Phoon-kok & Lee, David Kuo Chuen, 2016. "Credit rating score analysis," SFB 649 Discussion Papers 2016-046, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2016-046
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    More about this item

    Keywords

    Credit risk; Principal Components Analysis; Credit Rating Score;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • G00 - Financial Economics - - General - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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