Home
»
Measuring Corporate Default Risk
A01=Darrell Duffie
Age Group_Uncategorized
Age Group_Uncategorized
Author_Darrell Duffie
automatic-update
Category1=Non-Fiction
Category=GPQD
Category=KFFH
Category=KJMV1
COP=United Kingdom
Delivery_Delivery within 10-20 working days
eq_bestseller
eq_business-finance-law
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Language_English
PA=Available
Price_€20 to €50
PS=Active
softlaunch
Product details
- ISBN 9780199279241
- Weight: 210g
- Dimensions: 157 x 233mm
- Publication Date: 22 Sep 2022
- Publisher: Oxford University Press
- Publication City/Country: GB
- Product Form: Paperback
- Language: English
Delivery/Collection within 10-20 working days
Our Delivery Time Frames Explained
2-4 Working Days: Available in-stock
10-20 Working Days: On Backorder
Will Deliver When Available: On Pre-Order or Reprinting
We ship your order once all items have arrived at our warehouse and are processed. Need those 2-4 day shipping items sooner? Just place a separate order for them!
This book, based on the author's Clarendon Lectures in Finance, examines the empirical behaviour of corporate default risk. A new and unified statistical methodology for default prediction, based on stochastic intensity modeling, is explained and implemented with data on U.S. public corporations since 1980. Special attention is given to the measurement of correlation of default risk across firms. The underlying work was developed in a series of collaborations over roughly the past decade with Sanjiv Das, Andreas Eckner, Guillaume Horel, Nikunj Kapadia, Leandro Saita, and Ke Wang. Where possible, the content based on methodology has been separated from the substantive empirical findings, in order to provide access to the latter for those less focused on the mathematical foundations.
A key finding is that corporate defaults are more clustered in time than would be suggested by their exposure to observable common or correlated risk factors. The methodology allows for hidden sources of default correlation, which are particularly important to include when estimating the likelihood that a portfolio of corporate loans will suffer large default losses. The data also reveal that a substantial amount of power for predicting the default of a corporation can be obtained from the firm's "distance to default," a volatility-adjusted measure of leverage that is the basis of the theoretical models of corporate debt pricing of Black, Scholes, and Merton. The findings are particularly relevant in the aftermath of the financial crisis, which revealed a lack of attention to the proper modelling of correlation of default risk across firms.
Darrell Duffie is the The Adams Distinguished Professor of Management and Professor of Finance at Stanford Graduate School of Business and has been writing about financial markets since 1984. He is a fellow and member of the Council of the Econometric Society, a research fellow of the National Bureau of Economic Research, and a fellow of the American Academy of Arts and Sciences. Duffie was the 2009 president of the American Finance Association. In 2014, he chaired the Market Participants Group, charged by the Financial Stability Board with recommending reforms to Libor, Euribor, and other interest rate benchmarks. Duffie's recent books include How Big Banks Fail (Princeton University Press, 2010), Measuring Corporate Default Risk (Oxford University Press, 2011), and Dark Markets (Princeton University Press, 2012).
Qty:
