Credit rating score analysis

Wolfgang Härdle, Phoon-kok Fai and David Kuo Chuen Lee

No 2016-046, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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.

Keywords: Credit risk; Principal Components Analysis; Credit Rating Score (search for similar items in EconPapers)
JEL-codes: C01 G00 G17 G24 (search for similar items in EconPapers)
Date: 2016
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