About Finance: Credit Risk Modeling using Excel and VBA (The Wiley Finance Series)

In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit.

Credit Risk Modeling using Excel and VBA with DVD provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO’s. The final chapters address modeling issues associated with the new Basel Accord.

Editorial Reviews

From the Inside Flap
Credit risk modelling using Excel and VBA

From the Back Cover
This book provides practitioners and students with an intuitive, hands-on introduction to modern credit risk modeling. A typical chapter starts with an approachable presentation of the methodology. Step by step, the authors then show how to implement the methods in Excel and Visual Basic for Applications. Focusing on risk management issues, the book covers default probability estimation (scoring, structural models, and transition matrices), correlation and portfolio analysis, validation, as well as credit default swaps and structured finance. Several appendices and videos increase ease of access.

The authors present a host of applications – many of which go beyond standard Excel or VBA usages. For example, they show how to estimate logit models with maximum likelihood, or how to conduct large-scale Monte Carlo simulations in little time. Even to experienced modelers the book can serve as a toolbox and source of inspiration.

"In one place, Löffler and Posch provide all that is needed to install state-of-the-art risk management system, including a broad understanding of different risk management frameworks, detailed estimation techniques for deriving PD, LGD, and correlation parameters, and programing tools for putting these methods into practice."
—Richard Cantor, Managing Director, Credit Policy Research, Moody’s Investors Service

"I read this book cover-to-cover and recommend it heartily. For each topic, there is straightforward explanation, practical examples, and implementable coding. This book would have saved me months of effort many times over with its full ‘toolset’ of Excel/VBA code. I have immediate plans to reread sections and incorporate sections of code into my own spreadsheets."
—Greg M. Gupton, Fitch Ratings & DefaultRisk.com

About the Author
GUNTER LÖFFLER is professor of finance at the University of Ulm in Germany. His current research interests are on credit risk and empirical finance. Previously, Gunter was assistant professor at Goethe University Frankfurt, and served as an internal consultant in the asset management division of Commerzbank. His Ph.D. in finance is from the University of Mannheim. Gunter has studied at Heidelberg and Cambridge Universities.

PETER N. POSCH is PhD student in finance at the chair of Gunter Löffler. His current research focus is on credit risk and financial econometrics. Peter studied philosophy and economics and holds a Diplom, M.Sc. equivalent, in economics from the University of Bonn.

Customer Reviews

very good guide to credit risk modeling
Finally a book came out that concerns the "normal" credit risk modeling as opposed to just credit risk pricing of derivatives and structured products. This book is excellent. I give it 4 stars because of the choice of the software, i.e. Excel. Almost everyone who is doing this kind of analysis is not doing it in Excel (from experience) but rather S-PLUS, R or SAS. But ok, not that big of a problem.
I would say that this is a good guide to credit risk modeling, but the reader should fill quite a lot for him/herself, but this will come from practice. Overall, the authors present the problems and solutions in a intuitive way and quite narrative, which makes it an easy read. They also explain the Excel and VBA code rather than just presenting it, which enables the reader to reproduce it easier.
Overall, I would recommend this book to anyone in credit risk management and especially to universities and students as often they come unprepared to the real world of credit risk modeling.

Good book guiding credit risk model
This book introduces credit risk model with Excel example. It is not just the math formula. author use tangible Excel examples to explain how to do it and make us easily unstanding. This book is versy suitable for people who is interesting in credit risk field.

Credit Risk Modeling using Excel and VBA
The book is a very good guide for anyone who is not familiar with Excel, VBA and or credit risk modelling. Even for the more experienced practitioner there is something to learn. For anyone wanting a practical guide I would thoroughly recommend this book.