Credit Risk Modeling: Theory and Applications

Lando, David

ISBN 10: 0691089299 / ISBN 13: 9780691089294

Published by Princeton University Press, Princeton, 2004

About this Item

Sewn binding. Cloth over boards. With dust jacket. 328 p. Contains: Illustrations, black & white. Princeton Finance. Audience: General/trade. Fine in very good dust jacket. excellent book in a jacket with light shelfwear and an inch long closed tear to the back of the jacket, no ownership marks.

Seller Inventory # Alibris.0028059

Bibliographic Details

• Title: Credit Risk Modeling: Theory and Applications
• Publisher: Princeton University Press, Princeton
• Publication Date: 2004
• Language: English
• ISBN 10: 0691089299
• ISBN 13: 9780691089294
• Binding: Hard cover
• Dust Jacket Condition: Dust Jacket Included

About this title

Synopsis

Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk.


David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations. The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.

About the Author

David Lando is Professor of Finance at the Copenhagen Business School. He is an associate editor of three finance journals and a member of Moody's Academic Advisory and Research Committee.