Measuring Corporate Default Risk
Series: Clarendon Lectures in Finance;
- Publisher's listprice GBP 25.49
-
12 177 Ft (11 597 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 1 218 Ft off)
- Discounted price 10 959 Ft (10 437 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
12 177 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Publisher OUP Oxford
- Date of Publication 22 September 2022
- ISBN 9780199279241
- Binding Paperback
- No. of pages128 pages
- Size 233x157x7 mm
- Weight 210 g
- Language English
- Illustrations 22 Figures, 13 Tables 248
Categories
Short description:
Based on the author's Clarendon Lectures in Finance, this book develops and implements statistical methods for modelling corporate credit risk.
MoreLong description:
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 has been a leader in the field of credit risk, both its theory and empirical implementation, for over a decade. This book is a brilliant presentation of the methods, many originated by Darrell himself, for estimating corporate default risk. It is a necessary reference for beginners and professionals alike. Anyone interested in measuring default risk should have this book on their bookshelf.
Table of Contents:
Objectives and Scope
Survival Modeling
How to Estimate Default Intensity Processes
The Default Intensities of Public Corporations
Default Correlation
Frailty-Induced Correlation
Empirical Evidence of Frailty
Time-Series Parameter Estimates
Residual Gaussian Copula Correlation
Additional Tests for Mis-Specified Intensities
Applying the Gibbs Sampler with Frailty
Testing for Frailty
Unobserved Heterogeneity
Non-Linearity Check
Bayesian Frailty Dynamics
Risk-Neutral Default Probabilities
