- Series: Chapman and Hall/CRC Financial Mathematics Series (Book 19)
- Hardcover: 384 pages
- Publisher: Chapman and Hall/CRC; 2 edition (June 2, 2010)
- Language: English
- ISBN-10: 1584889926
- ISBN-13: 978-1584889922
- Product Dimensions: 6.1 x 0.9 x 9.2 inches
- Shipping Weight: 1.6 pounds (View shipping rates and policies)
- Average Customer Review: 10 customer reviews
- Amazon Best Sellers Rank: #981,462 in Books (See Top 100 in Books)
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Introduction to Credit Risk Modeling, Second Edition (Chapman and Hall/CRC Financial Mathematics Series) 2nd Edition
Use the Amazon App to scan ISBNs and compare prices.
Fulfillment by Amazon (FBA) is a service we offer sellers that lets them store their products in Amazon's fulfillment centers, and we directly pack, ship, and provide customer service for these products. Something we hope you'll especially enjoy: FBA items qualify for FREE Shipping and Amazon Prime.
If you're a seller, Fulfillment by Amazon can help you increase your sales. We invite you to learn more about Fulfillment by Amazon .
"Rebound" by Kwame Alexander
Don't miss best-selling author Kwame Alexander's "Rebound," a new companion novel to his Newbery Award-winner, "The Crossover,"" illustrated with striking graphic novel panels. Pre-order today
Frequently bought together
Customers who bought this item also bought
Customers who viewed this item also viewed
… this is a concise book for exploring the limitations of credit risk models and, to a lesser degree, asset valuation models. Read this book for a companionable journey through some of the limiting assumptions that make the models tractable. … it may be the first one [book] that wastes no time in getting to the point, and moving on.
―Annals of Actuarial Science, Vol. 5, June 2011
Bluhm, Overbeck, and Wagner offer help to mathematicians and physicists leaving the academy to work as risk or portfolio managers. For this introduction, they focus on main themes rather than details, and on portfolio rather than single obligor risk. … this second [edition] takes account of problems in the banking industry [from] 2007-09.
―SciTech Book News, February 2011
Having a valid and up-to-date credit risk model (or models) is one of the most important aspects in today’s risk management. The models require quite a bit of technical as well as practical know-how. Introduction to Credit Risk Modeling serves this purpose well. … it would best fit the practitioner’s needs. For students it can also be of great use, as an introductory course for credit risk models. A great first step into credit risk modeling. … The book provides a nice coherent overview of the methods used in capital allocation. … The book is written in a mixture of theorem-proof and applied styles. … I find this rather pleasing, as it gives the reader the edge of theoretical exposition, which is extremely important. … One really useful side of the book is that it provides step-by-step guide to methods presented. This should be really appreciated in industry and among students. …
―MAA Reviews, January 2011
Praise for the First Edition
This is an outstanding book on the default models that are used internally by financial institutions. This practical book delves into the mathematics, the assumptions and the approximations that practitioners apply to make these models work.
―Glyn A. Holton, Contingency Analysis
There are so many financial tools available today and numbers are likely to grow in the future. If you work in this field of credit risk modelling it is worth looking at the theoretical background, and this book is a well-rounded introduction.
―Journal of the Operational Research Society
As an introductory survey it does an admirable job. … this book is an important guide into the field of credit risk models. Mainly for the practitioner … It is well written, fairly easy to follow.
―Horst Behncke, Zentralblatt MATH
About the Author
Over the years, Christian Bluhm has worked for Deutsche Bank, McKinsey, HypoVereinsbank’s Group Credit Portfolio Management, and Credit Suisse. He earned a Ph.D. in mathematics from the University of Erlangen-Nürnberg.
Ludger Overbeck is a professor of probability theory and quantitative finance and risk management in the Institute of Mathematics at the University of Giessen. During his career, he worked for Deutsche Bundesbank, Deutsche Bank, HypoVereinsbank/UniCredit, DZBank, and Commerzbank. He earned a Ph.D. in mathematics from the University of Bonn.
Christoph Wagner has worked for Deutsche Bank, Allianz Group Center, UniCredit/HypoVereinsbank, and Allianz Risk Transfer. He earned a Ph.D. in statistical physics from the Technical University of Munich.
Author interviews, book reviews, editors picks, and more. Read it now
Top customer reviews
There was a problem filtering reviews right now. Please try again later.
Nearly every paragraph cites multiple references, and claims the topic is outside the scope of the book and the reader should refer to some other book. It seems that most everything the book covers is in some way or another "out of the scope" of the book.
The flow is incoherent. Chapters 1 and 2 frequently cite figures and sections in chapter 4 and beyond.
The book has overview of the most popular portfolio models and excellent description of Bernuolli and Poisson mixture models.
The book has good introductionary chapters about credit derivatives, but for deep understanding of the matter, you have to read specialized books.
Therefore, I highly recommend this book to beginners and practitioners in risk-modelling of banking book portfolios in commercial banks.
This text explains concepts very well and is FULL of examples. I mean literally 3/4 of the book, maybe more, is examples. Every chapter also has a section of problems that have partial solutions, which can come in very handy. This is pretty much all that is good about this text, but keep in mind that explaination is the most important part of any textbook.
The proofs skip plenty of steps. And I mean plenty, so much that a proof in the book would take 5 lines but when my professor proved it in class it would take him nearly 15. Also while there are tonnes of examples, too many are theoretical and very hard. The book costs a hefty amount of change and is suprisingly small, Author couldl have given few more examples to make it interesting. However the worst thing about this book is how the author leaves important things in with the text often. However most these things are small, and overall the text is a good intro to probability theory.
Although short in comparison to most books on financial modeling and financial engineering, this book gives a sound overview of some of the more popular approaches to credit risk modeling, with references included for those readers who need more details. The authors' emphasis is on the conceptual background, and so a lot of the more straightforward computational routines are left out. In particular, even though the authors mention Monte Carlo simulations they are not performed explicitly in the book. Proofs of some of the main results are also left to the references. In addition, it is a monograph rather than a textbook, so no exercises will be found. Instructors who intend to use the book in an actual course on credit risk modeling will have to devise their own.
The book's unique feature, and one that it is widely cited for, is that it includes detailed discussion of correlated defaults. Some other features of the book that make it stand out include: 1. For those interested in Basel II, included is a discussion of the `exposure at default' (EAD), which is defined simply as the sum of the outstanding balances and a fraction of the loan commitments. This fraction is the expectation value of the random variable that governs the fluctuations of the utilization of the loan commitment. 2. The discussion of `copula functions' and their use in risk management. A copula is simply a multivariate distribution that is constructed so that it has standard uniform marginal distributions. Their use has exploded in credit risk modeling, mostly in the area of credit derivatives, which the author devotes a chapter to in the book. The authors discuss their use in the CreditMetrics/KMV model, with emphasis on the ability of copulas to manipulate the tail dependence of multivariate distributions. The authors point to the need for a calibration methodology for fitting copulas to credit portfolios. 3. The superb discussion on alternative risk measures via the concept of a `coherent' risk measure. Most interesting is the discussion on `expected shortfall' and its comparison with VAR (which is not a coherent risk measure). Also of great interest, and very well written, is the treatment of the variance/covariance approach, which as the authors remark is similar to beta-factor models and can be validated in much the same way. 4. The treatment of the term structure of default probabilities, which follows in much the same way the methodologies and concepts in interest rate modeling. The authors' discussions of this topic lead one to believe that a kind of `unified' theory of credit and interest rate modeling is viable, and in fact there are signs in some commercial products, such as CreditMetrics/KMV, of this unification.