Orth, Walter (2010): The predictive accuracy of credit ratings: Measurement and statistical inference.
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Credit ratings are ordinal predictions for the default risk of an obligor. To evaluate the accuracy of such predictions commonly used measures are the Accuracy Ratio or, equivalently, the Area under the ROC curve. The disadvantage of these measures is that they treat default as a binary variable thereby neglecting the timing of the default events and also not using the full information from censored observations. We present an alternative measure that is related to the Accuracy Ratio but does not suffer from these drawbacks. As a second contribution, we study statistical inference for the Accuracy Ratio and the proposed measure in the case of multiple cohorts of obligors with overlapping lifetimes. We derive methods that use more sample information and lead to more powerful tests than alternatives that filter just the independent part of the dataset. All procedures are illustrated in the empirical section using a dataset of S\&P Long Term Credit Ratings.
|Item Type:||MPRA Paper|
|Original Title:||The predictive accuracy of credit ratings: Measurement and statistical inference|
|Keywords:||Ratings; predictive accuracy; Accuracy Ratio; Harrell's C; overlapping lifetimes|
|Subjects:||C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C41 - Duration Analysis; Optimal Timing Strategies
G - Financial Economics > G3 - Corporate Finance and Governance > G32 - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
G - Financial Economics > G2 - Financial Institutions and Services > G24 - Investment Banking; Venture Capital; Brokerage; Ratings and Ratings Agencies
|Depositing User:||Walter Orth|
|Date Deposited:||14. Apr 2011 21:09|
|Last Modified:||12. Feb 2013 16:37|
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