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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.
- Sales Rank: #2138310 in Books
- Published on: 2007-06-05
- Original language: English
- Number of items: 1
- Dimensions: 9.98" h x .81" w x 6.93" l, 1.55 pounds
- Binding: Hardcover
- 280 pages
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.
Most helpful customer reviews
0 of 0 people found the following review helpful.
But there is companion website to use which is great. The are few appendices at the end of ...
By Ana Zargham
There is no DVD in the book. But there is companion website to use which is great. The are few appendices at the end of the book that provide a crash course in preliminary topics needed to understand the technical content of the book. Depending on the reader's background you may need other sources first as a refresher for understanding statistical analysis topic like "Maximum Likelihood estimation"
3 of 3 people found the following review helpful.
Practical, but not superficial
By E. Chen
Clearly, Excel is not even remotely the best platform to perform large scale credit risk modeling or analysis. However, Excel is probably the most concise, neutral platform from which to demonstrate the techniques involved in implementing the models discussed in the book.
** Note, please do not rely on this book as your main source for learning the mathematical and economical nuances of these models.
2 of 2 people found the following review helpful.
A very good book. Rich in theory and application
By Mohammad
A very good book. Rich in theory and application. Very useful for people who study finance or fields that are related to risk analysis. Adequate training in mathematics, statistics and VBA code is essential.
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