| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w11962 |
| 来源ID | Working Paper 11962 |
| Multi-Period Corporate Default Prediction With Stochastic Covariates | |
| Darrell Duffie; Leandro Siata; Ke Wang | |
| 发表日期 | 2006-01-23 |
| 出版年 | 2006 |
| 语种 | 英语 |
| 摘要 | 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. |
| 主题 | Econometrics ; Estimation Methods ; Financial Economics ; Corporate Finance ; Macroeconomics ; Money and Interest Rates |
| URL | https://www.nber.org/papers/w11962 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/569613 |
| 推荐引用方式 GB/T 7714 | Darrell Duffie,Leandro Siata,Ke Wang. Multi-Period Corporate Default Prediction With Stochastic Covariates. 2006. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w11962.pdf（388KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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