The Credit Market Handbook: Advanced Modeling Issues

CHAPTER 4

Non-Parametric Analysis of Rating Transition and Default Data

Peter Fledelius,^a David Lando,^b,* and Jens Perch Nielsen^a

We demonstrate the use of non-parametric intensity estimation—including construction of pointwise confidence sets—for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move but that this dependence vanishes after 2–3 years.

1. INTRODUCTION

The key purpose of rating systems is to provide a simple classification of default risk of bond issuers, counterparties, borrowers, and so on. A desirable feature of a rating system is, of course, that it is successful in ordering firms so that default rates are higher for lower-rated firms. However, this ordering of credit risk is not sufficient for the role that ratings are bound to play in the future. A rating system will be put to use for risk management purposes, and the transition and default probabilities associated with different ratings will have concrete implications for internal capital allocation decisions and for solvency requirements put forth by regulators. The accuracy of these decisions and requirements depends critically on a solid understanding of the statistical properties of the rating systems employed.

It is widely documented that the evolution of ratings displays different types of non-Markovian behavior. Not only do there seem to be cyclical components but there is also evidence ...