Dimensions of Credit Risk and Their Relationship to Economic Capital Requirements

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Abstract
This chapter uses the Monte Carlo resampling method of Carey (1998) to provide nonparametric empirical evidence about the practical importance to portfolio bad-tail loss rates of several different asset and portfolio characteristics. This bootstrap-like method simulates the likely range of loss experience of a portfolio manager who randomly selects assets from those available for investment, while at the same time causing his portfolio to conform to specified targets and limits. The chapter is organized as follows. Section 6.1 describes the data, and Section 6.2 describes some details of the resampling method. Sections 6.3 through 6.9 report results, while Section 6.10 offers concluding comments. The study shows that credit risk is substantially influenced by the following factors: borrower default ratings, estimates of likely loss given a default, and measures of portfolio size and granularity (the extent to which loans to a few borrowers make up a large fraction of the portfolio). In addition, the linear structure that is inherent in the internal ratings approach seems to produce reasonable estimates of overall credit risk for the bank. A commentary and discussion summary are also included at the end of the chapter.

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