标题: | 产业网络风险与违约预测 Industry Network Risk and Corporate Default Prediction |
作者: | 黄木楠 李汉星 Huang, Mu-Nan Lee, Han-Hsing 财务金融研究所 |
关键字: | CoVaR;违约预测;特征向量中心性;远期强度模型;体系风险;CoVaR;Default prediction;Eigenvector centrality;Forward intensity model;Systemic risk |
公开日期: | 2017 |
摘要: | 过去文献指出跨产业的报酬与尾端风险具可预测性。因此本研究使用Duan et al. (2012)提出的远期强度模型,来分析产业报酬与尾端风险对违约预测的影响。除控制违约预测文献中常使用的总体与公司变数外,我们加入了产业位置(中心性)、产业连结性(体系风险)与产业报酬,来探究这些产业层级变数是否影响公司之违约机率。整体而言,我们的实证结果支持加入上述产业变数能帮助解释公司之违约机率。 Previous literature has documented the cross-industry return and tail risk predictability, especially during financial crisis. This study investigates the effects of inter-industry return and tail risk in the context of default prediction using forward intensity approach of Duan et al. (2012). Controlling for commonly used macro and firms-specific variables in default analysis, we incorporate industries’ position, connectedness and return to examine whether these industry-level variables affect corporate default probabilities. Overall, our empirical results support that these industry variables can help explain corporate default probabilities. |
URI: | http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070453923 http://hdl.handle.net/11536/141094 |
显示于类别: | Thesis |