.png){kind=icon}
返回
A varying-coefficient default model
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ijforecast.2011.11.006.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, a default prediction method based on the discrete-time varying-coefficient hazard model (DVHM) is proposed. The new model is constructed by replacing the constant coefficients of firm-specific predictors in the discrete-time hazard model (DHM; see Shumway, 2001; and Chava & Jarrow, 2004) with the smooth functions of macroeconomic variables. Thus, it allows the effects of those firm-specific predictors on the default prediction to change with the macroeconomic dynamics (Pesaran, Schuermann, Treutler, & Weiner, 2006). The coefficient functions in the new model are estimated by a local likelihood approach. One real panel dataset is used to illustrate the proposed methodology. Using an expanding rolling window approach, the empirical results confirm that DVHM has a better and more robust performance than the usual DHM, in the sense that it yields more accurate predicted numbers of defaults and predictive intervals through out-of-sample analysis. Thus, the proposed model is a useful alternative for studying default losses on portfolios. (c) 2012 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keyword:
Discrete-time hazard model
Local likelihood
Expanding rolling window approach
Predicted number of defaults
Predictive interval
Varying-coefficient model
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.1
论文数:
3.1K
被引数:
9.9K
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏
查看更多内容