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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Book 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.
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Additional material, including slide sets and exercises for lecturers, is available on our homepage loeffler-posch.com.
--This text refers to an alternate
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Credit risk modelling using Excel and VBA
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Most Helpful Customer Reviews
24 of 24 people found the following review helpful:
4.0 out of 5 stars
very good guide to credit risk modeling,
By
This review is from: Credit Risk Modeling using Excel and VBA (The Wiley Finance Series) (Hardcover)
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.
7 of 7 people found the following review helpful:
5.0 out of 5 stars
good for professional risk managers too,
By Salman Qutb (Pakistan) - See all my reviews
This review is from: Credit Risk Modeling using Excel and VBA (The Wiley Finance Series) (Hardcover)
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.
7 of 7 people found the following review helpful:
5.0 out of 5 stars
Credit Risk Modeling using Excel and VBA,
By
This review is from: Credit Risk Modeling using Excel and VBA (The Wiley Finance Series) (Hardcover)
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.
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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credit risk modeling, portfolio loan, annual transition matrices, asset value approach, average capital requirement, credit portfolio risk, asset value model, individual default probabilities, joint default probability, investment grade defaults, portfolio notional, approximate generator, default probability estimates, credit indices, conditional default probability, low default probability, average default rate, accuracy ratio, asset correlation, portfolio loss distribution, portfolio credit risk, default correlation, cohort approach, credit risk models, mezzanine tranche Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, End If Next, Basel Committee, Goal Seek, End Function, The Structural Approach, Measuring Credit Portfolio Risk, Banking Supervision, Working Paper, Journal of Risk, Confidence Loss, General Motors, Estimating Credit Scores, Princeton University Press, False Application, Journal of Finance, Credit Rkk, Journal of Derivatives, The Halton, Rating Default, Journal of Fixed Income, Cumulative Accuracy Profile, Default Prediction Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
credit risk modeling, portfolio loan, annual transition matrices, asset value approach, average capital requirement, credit portfolio risk, asset value model, individual default probabilities, joint default probability, investment grade defaults, portfolio notional, approximate generator, default probability estimates, credit indices, conditional default probability, low default probability, average default rate, accuracy ratio, asset correlation, portfolio loss distribution, portfolio credit risk, default correlation, cohort approach, credit risk models, mezzanine tranche Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, End If Next, Basel Committee, Goal Seek, End Function, The Structural Approach, Measuring Credit Portfolio Risk, Banking Supervision, Working Paper, Journal of Risk, Confidence Loss, General Motors, Estimating Credit Scores, Princeton University Press, False Application, Journal of Finance, Credit Rkk, Journal of Derivatives, The Halton, Rating Default, Journal of Fixed Income, Cumulative Accuracy Profile, Default Prediction Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
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