Modelling Correlations in Portfolio Credit Risk

TL;DR

This paper introduces a factorial model for estimating correlations in credit portfolio risk, improving the reliability of economic capital estimates by addressing estimation errors from limited data.

Contribution

It proposes a new parameter estimation method within the CreditRisk+ framework that better captures correlation risk, reducing underestimation issues.

Findings

PD correlations are well described by a factorial model

The new estimation method increases the reliability of capital estimates

Empirical evidence supports the model's effectiveness

Abstract

The risk of a credit portfolio depends crucially on correlations between the probability of default (PD) in different economic sectors. Often, PD correlations have to be estimated from relatively short time series of default rates, and the resulting estimation error hinders the detection of a signal. We present statistical evidence that PD correlations are well described by a (one-)factorial model. We suggest a method of parameter estimation which avoids in a controlled way the underestimation of correlation risk. Empirical evidence is presented that, in the framework of the CreditRisk+ model with integrated correlations, this method leads to an increased reliability of the economic capital estimate.