Credit Risk Modeling: Theory and Applications

David Lando

ISBN 10: 0691089299 / ISBN 13: 9780691089294

Verlag: Princeton University Press, 2004

Beschreibung

Series: Princeton Series in Finance. Num Pages: 328 pages, 45 line illus. 30 tables. BIC Classification: KFFL; PBW. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 246 x 167 x 26. Weight in Grams: 634. . 2004. First Edition. Hardcover. . . . .

Bestandsnummer des Verkäufers V9780691089294

Bibliografische Details

• Titel: Credit Risk Modeling: Theory and Applications
• Verlag: Princeton University Press
• Erscheinungsjahr: 2004
• Sprache: Englisch
• ISBN-10: 0691089299
• ISBN-13: 9780691089294
• Einband: Hardcover
• Auflage: 1. Auflage
• Zustand: New

Über diesen Titel

Inhaltsangabe

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.

Über die Autorin bzw. den Autor

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.