Abstract

http://ssrn.com/abstract=903784
 
 

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Multi-Period Corporate Default Prediction with Stochastic Covariates


Darrell Duffie


Stanford University - Graduate School of Business

Leandro Saita


Independent

Ke Wang


University of Tokyo - Faculty of Economics

September 2005

FDIC Center For Financial Research Working Paper No. 2006-05

Abstract:     
We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of firm-specific and macroeconomic covariates. For U.S. Industrial firms, based on over 390,000 firm-months of data spanning 1980 to 2004, the level and shape of the estimated term structure of conditional future default probabilities depends on a firm's distance to default (a volatility-adjusted measure of leverage), on the firm's trailing stock return, on trailing S&P 500 returns, and on U.S. interest rates, among other covariates. Variation in a firm's distance to default has a substantially greater effect on the term structure of future default hazard rates than does a comparatively significant change in any of the other covariates. Default intensities are estimated to be lower with higher short-term interest rates. The out-of-sample predictive performance of the model is an improvement over that of other available models.

Number of Pages in PDF File: 44

Keywords: default, bankruptcy, duration analysis, doubly stochastic

JEL Classification: C41, G33, E44

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Date posted: May 23, 2006  

Suggested Citation

Duffie, Darrell and Saita, Leandro and Wang, Ke, Multi-Period Corporate Default Prediction with Stochastic Covariates (September 2005). FDIC Center For Financial Research Working Paper No. 2006-05. Available at SSRN: http://ssrn.com/abstract=903784 or http://dx.doi.org/10.2139/ssrn.903784

Contact Information

James Darrell Duffie
Stanford University - Graduate School of Business ( email )
518 Memorial Way
Stanford, CA 94305-5015
United States
650-723-1976 (Phone)
650-725-7979 (Fax)

Leandro Saita (Contact Author)
Independent
No Address Available
Ke Wang
University of Tokyo - Faculty of Economics ( email )
7-3-1 Hongo, Bunkyo-ku
Tokyo 113-0033
Japan
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