Regular marked price: $80.00Discount Price: $50.40
Cost Savings: $29.60 (37%)Price fluctuation possible.
How soon does it ship: Normal ship time within one day
Shipping? Absolutely FREE if you qualify for Super Saver Shipping.
Type of bind: Hardcover
Dewey Decimal Number: 332.63244
EAN num: 9780470243664
ISBN number: 047024366X
Label: Wiley
Manufacturer: Wiley
Quantity: 1
Page Count: 334
Printing Date: June 30, 2008
Publishing house: Wiley
Sale Popularity Level: 135638
Studio: Wiley
Other books you might be interested in perusing:
Editor's Notes and Comments:
Product Description:
Mortgage credit derivatives are a risky business, especially of late. Written by an expert author team of UBS practitioners-Laurie Goodman, Shumin Li, Douglas Lucas, and Thomas Zimmerman-along with Frank Fabozzi of Yale University, Subprime Mortgage Credit Derivatives covers state-of-the-art instruments and strategies for managing a portfolio of mortgage credits in today's volatile climate.
Divided into four parts, this book addresses a variety of important topics, including mortgage credit (non-agency, very first and second lien), mortgage securitizations (alternate structures and subprime triggers), credit default swaps on mortgage securities (ABX, cash synthetic relationships, CDO credit default swaps), and much more. In addition, the authors outline the origins of the subprime crisis, showing how during the 2004-2006 period, as housing became less affordable, origination standards were stretched-and when home price appreciation then turned to home price depreciation, defaults and delinquencies rose across the board.
The recent growth in subprime lending, along with a number of other industry factors, has made the demand for timely knowledge and solutions greater than ever before, and this guide contains the information financial professionals need to succeed in this challenging field.
User popularity level:
Rated by buyers 
-
This book provides an excellent and very practical approach to analyzing and interpreting subprime instrumnents. Fabozzi is a very clear and thorough academic, in the best way. The co-authors are all from UBS, which lost a ton of money in the subprime meltdown.
I have to admit that I was a little skeptical about being told how to, in essence, analyze risk from risk managers who presumably helped UBS lose over $40 billion. But then again, they should understand the market.
If there is any weakness in their analysis it is that it is subsequent to impossible to conduct any sort of statistical sampling when so many loan applications were fraudulent.
Still, all-in-all, I highly recommend this book. Oh, and don't let the term derivatives scare you, the authors used virtually no mathematics to explain these complex instruments. The only thing I would like to have seen was an Excel disk with their models on it, or at least an appendix with more details on how to do their analysis.
Rated by buyers 
-
This book is a purely descriptive overview of subprime mortgage credit derivatives and thus will suit the needs of readers who do not want to get into the sometimes sophisticated mathematical formalism that can be associated with the modeling of credit derivatives. For this reason, experienced financial modelers may be disappointed with the book, but there is enough discusion on modeling to make it keep the attention of such readers. Its size makes the book more manageable for those facing time constraints, but the book also has some shortcomings with respect to the quality of the graphs that are presented. The absence of colour in these graphs probably reflects the decision to keep the price of the book down, but the graphs can be difficult to read because of this omission. But even with these shortcomings the book can be read profitably by anyone interested in the subject or possibly wanting to gain insight into what has been called the "subprime meltdown." Most of the press, including the financial press, is blaming the subprime mortgage markets for the current global financial difficulties. It remains to be seen whether this is really true, so this book could also be viewed as an investigative tool for those individuals who are attempting to find out the real causes behind these difficulties.
Chapters 10 and 11 should be of interest to financial modelers since the authors endeavor to forecast cumulative losses not only for subprime and Alt-A loans but also for second lien (fixed rate home equity (HELOAN) and variable rate (HELOC) loans. The modeling of performance and severity in mortgage portfolios is typically done in a `competing risk' framework, wherein the probabilities of default and prepayment are entangled with each other and are of course dependent not only on the values of the individual credit variables in each loan of the portfolio, but also macroeconomic variables such as house price appreciation and mortgage interest rates. The probabilities of default are updated whenever a prepayment occurs and the probabilities of prepayment are updated whenever defaults occur. This updating gives competing risk models a Bayesian flair, and in fact they can be cast entirely in such a Bayesian framework. The authors do not mention competing risk models in this book, but interestingly reject the use of econometric models to estimate losses due in their words to their non-Bayesian nature. In their place they use what they call an "autopilot" model to estimate collateral losses, which makes use of `default timing' and `default factor' curves. The shapes of these curves (called "S-curves" by some analysts because of their shape) should be very familiar to anyone who has analyzed mortgage portfolios, or even those based on automobile securitizations. Unfortunately the authors do their calculations using curves generated by a particular vendor, leaving the reader hanging as to just how to choose a theoretical loss curve. One simple way to do this, which the authors do not mention, is to use S-curves based on parameters. There are many choices that can be made here, going by the names of logistic, Gompertz, and Michaelis-Menten growth curves. Fitting the loss data to these curves using nonlinear root-finding algorithms allows one to find the point in time where the loss rates are maximum, at least for vintages that are suitably old. This approach, although simple, has also been used in the modeling of structured securities with some degree of success. This reviewer has used this approach to get rough estimates of (cumulative) gross credit losses in second lien mortgage portfolios, i.e. the case where recoveries in defaulted loans are omitted in the analysis. And this approach, if done more carefully does allow one to study, via a certain interpretation the effects of macroeconomic shocks (i.e. interest rates and housing price indices) on defaults. The authors state that this cannot be done using their loss curve approach. As the authors are aware of though, the use of these loss curves is problematic if one wants to take prepayments into account. They assume the existence of stable prepayment speeds, and so the authors propose using a default "factor" curve instead. In this case the timing or aging variable is replaced by the `pool factor' (i.e. the collateral balance divided by the original balance), and so the cumulative losses go from 0 to 100 as the pool pays down.
Chapter 6 will be of interest to those readers who are relatively new to the study of credit derivatives with special attention paid to credit default swaps on asset backed securities (ABS). The reader will also get some insight into the controversial nature of credit default swaps as related to the time at which the credit protection seller must compensate the credit protection buyer. There has been some grumbling in the financial literature on just what constitutes a `credit event'. The authors discuss in detail six different ... Read More
Find other books like this one:
