The Credit Market Handbook: Advanced Modeling Issues

Introduction

Credit analysis is undergoing a dramatic transformation owing to rigorous quantitative treatment. Probability theory, statistical modeling, and the modern theories of finance are being applied to help establish the critical function of how to determine credit risk. This book showcases a series of papers drawn from the published works in the archives of the Journal Of Investment Management (JOIM). Our intent is to bring together noted authors and their work to provide a rich framework of research in the credit analysis area.

Our first chapter, “Estimating Default Probabilities Implicit in Equity Prices,” by Janosi, Jarrow, and Yildirim, focuses on the use of equity prices as input in the probability of default measure. Leland, in “Predictions of Default Probabilities in Structural Models of Debt,” evaluates alternative structural model methodologies. Das, in “Recovery Risk,” reviews the literature for estimating recovery (loss given default). “Non-Parametric Analysis of Rating Transition and Default Data,” by Fledelius, Lando, and Nielsen, illustrates the use of non-parametric and smoothing methods for analyzing rating transitions. Ho and Lee of term structure fame provide a model for high-yield bond valuation. Jarrow and Protter provide new insights into the comparison of structural versus reduced-form models in “Structural versus Reduced-Form Models: A New Information-Based Perspective.” This topic is further explored by Arova and Bohn in “Reduced-Form versus Structural ...