Multi-Period Corporate Failure Prediction With Stochastic Covariates

by Darrell Duffie of Stanford University,
Leandro Saita of Stanford University, and
Ke Wang of the University of Tokyo

March 2007

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 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. The out-of-sample predictive performance of the model is an improvement over that of other available models.

JEL Classification: C41, G33, E44.

Keywords: default, bankruptcy, duration analysis, doubly stochastic, distance to default.

Published in: Journal of Financial Economics, Vol. 83, No. 3, (March 2007), pp. 635–665.

Books Referenced in this Paper:  (what is this?)

Download paper (482K PDF) 32 pages

[Home] [Credit Modeling Papers]

[ Home ] [ Up ]

Please contact me with problems or suggestions.
Copyright © 2000-2008 DefaultRisk.com
Last modified: May 15, 2008