Multi-Period Corporate Default Prediction With Stochastic Covariates / Darrell Duffie, Leandro Siata, Ke Wang.

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Duffie, Darrell

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w11962.Publication details: Cambridge, Mass. National Bureau of Economic Research 2006.Description: 1 online resource: illustrations (black and white)Subject(s):

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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 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. Distance to default is the most influential covariate. 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.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w11962 (Browse shelf(Opens below))	Not For Loan

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January 2006.

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 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. Distance to default is the most influential covariate. 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.