Multi-Period Corporate Default Prediction With Stochastic Covariates

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. Variation in a firm?s distance to default has a substantially greater eect 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.

"Multi-Period Corporate Default Prediction With Stochastic Covariates"

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.

EQUILIBRIUM IN INCOMPLETE MARKETS: I. A BASIC MODEL OF GENERIC EXISTENCE

This paper demonstrates the generic existence of general equilibria in incomplete markets. Our economy is a model of two periods, with uncertainty over the state of nature to be revealed in the second period. Securities are claims to commodity bundles in the second period that are contingent on the state of nature, and are insufficient in number to span all state contingent claims to value, regardless of the announced spot commodity prices. Under smooth preference assumptions, equilibria exist except for an exceptional set of endowments and securities, a closed set of measure zero. The paper includes partial results for fixed securities, showing the existence of equilibria except for an exceptional set of endowments

Multi-Period Corporate Default Prediction With Stochastic Covariates

We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of ?rm-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. 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-samplepredictive performance of the model is an improvement over that of other available models

Multi-Period Corporate Default Prediction With Stochastic Covariates

We provide maximum likelihood estimators of term structures of conditional probabilities of corporate default, incorporating the dynamics of ?rm-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\u27s distance to default (a volatility-adjusted measure of leverage), on the firm\u27s trailing stock return, on trailing S& P 500 returns, and on U.S. interest rates, among other covariates. Variation in a firm\u27s 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-samplepredictive performance of the model is an improvement over that of other available models.本文フィルはリンク先を参照のこ