Darrel Duffie (Graduate School of Business, Stanford University) Leandro Saita (Graduate School of Business, Stanford University) Ke Wang (Faculty of Economics, University of Tokyo)
Abstract
We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of firm-specific and m acroeconomic covariates. For U.S. Industrial firms, based on over 390,000 firm-months of data spanning 1979 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 effection 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. Theout-of-sample predictive performance of the model is an improvement over that of other available models.
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Publisher Info
Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number
CIRJE-F-373.
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