Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction

Stewart Jones, David A. Hensher

• Publisher: Cambridge University Press
• Year: 2008
• Print ISBN: 9780521869287
• eBook ISBN: 9780511426827
• Topic: Business
• Subtopic: Finance
• Index: Business

The field of credit risk and corporate bankruptcy prediction has gained considerable momentum following the collapse of many large corporations around the world, and more recently through the sub-prime scandal in the United States. This book provides a thorough compendium of the different modelling approaches available in the field, including several new techniques that extend the horizons of future research and practice. Topics covered include probit models (in particular bivariate probit modelling), advanced logistic regression models (in particular mixed logit, nested logit and latent class models), survival analysis models, non-parametric techniques (particularly neural networks and recursive partitioning models), structural models and reduced form (intensity) modelling. Models and techniques are illustrated with empirical examples and are accompanied by a careful explanation of model derivation issues. This practical and empirically-based approach makes the book an ideal resource for all those concerned with credit risk and corporate bankruptcy, including academics, practitioners and regulators.

Table of contents

• Cover
• Half-title
• Title
• Copyright
• Contents
• Figures
• Tables
• Contributors
• Advances in the modelling of credit risk and corporate bankruptcy: Introduction
• 1 A statistical model for credit scoring
• 2 Mixed logit and error component models of corporate insolvency and bankruptcy risk
• 3 An evaluation of open- and closed-form distress prediction models: The nested logit and latent class models
• 4 Survival analysis and omitted dividends
• 5 Non-parametric methods for credit risk analysis: Neural networks and recursive partitioning techniques
• 6 Bankruptcy prediction and structural credit risk models
• 7 Default recovery rates and LGD in credit risk modelling and practice: An updated review of the literature and empirical evidence
• 8 Credit derivatives: Current practices and controversies
• 9 Local government distress in Australia: A latent class regression analysis
• 10 A belief-function perspective to credit risk assessments
• Index