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Härdle, Wolfgang
Fai, Phoon-kok
Lee, David Kuo Chuen
Year of Publication: 
Series/Report no.: 
SFB 649 Discussion Paper 2016-046
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.
Credit risk
Principal Components Analysis
Credit Rating Score
Document Type: 
Working Paper

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