Credit Risk Modeling using Excel and VBA (The Wiley Finance Series) | 
 enlarge | Authors: Gunter Loeffler, Peter N. Posch
Publisher: Wiley
Category: Book
List Price: $120.00
Buy New: $65.52
You Save: $54.48 (45%)
New (29) Used (7) from $64.99
Rating:  7 reviews
Sales Rank: 29434
Media: Hardcover
Edition: Har/DVD
Pages: 280
Number Of Items: 1
Shipping Weight (lbs): 1.6
Dimensions (in): 9.8 x 6.9 x 1
ISBN: 0470031573
Dewey Decimal Number: 332.70285554
EAN: 9780470031575
ASIN: 0470031573
Publication Date: June 4, 2007
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
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Product Description
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.
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| Customer Reviews: Read 2 more reviews...
 useful book April 12, 2008
Curio (NYC, USA)
this is a good book and the associated CD shows how things are done in Excel in a detailed manner. very practically oriented.
Good book guiding credit risk model March 15, 2008
Alfred Wu (Taiwan)
3 out of 3 found this review helpful
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.
 good for professional risk managers too February 29, 2008
Salman Qutb (Pakistan)
3 out of 3 found this review helpful
An extensive primer that gives a thorough understanding of Conditional Volatility models. Also great in letting the reader understand influence of asymmetry and correlations concepts on risk modelling. It is useful even if Excel or VBA is not your choice modelling application (whcih in most cases is not). More content in future editions on controlling the volatility of different forcast techniques would be a beneficial addition.
Useful and down-to-earth guide November 13, 2007
Antonio Esteban Alvarez (Sevilla, Spain)
2 out of 2 found this review helpful
This book describes useful approaches to anyone interested in credit risk modeling, in particular the first chapter devoted to logit models, the best way to measure probability of default of SMS firms with litte or no data on market value of debt.
very good guide to credit risk modeling August 10, 2007
stat
11 out of 11 found this review helpful
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.
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