Title: 產業網絡風險與違約預測
Industry Network Risk and Corporate Default Prediction
Authors: 黃木楠
Huang, Mu-Nan
Lee, Han-Hsing
Keywords: CoVaR;違約預測;特徵向量中心性;遠期強度模型;體系風險;CoVaR;Default prediction;Eigenvector centrality;Forward intensity model;Systemic risk
Issue Date: 2017
Abstract: 過去文獻指出跨產業的報酬與尾端風險具可預測性。因此本研究使用Duan et al. (2012)提出的遠期強度模型,來分析產業報酬與尾端風險對違約預測的影響。除控制違約預測文獻中常使用的總體與公司變數外,我們加入了產業位置(中心性)、產業連結性(體系風險)與產業報酬,來探究這些產業層級變數是否影響公司之違約機率。整體而言,我們的實證結果支持加入上述產業變數能幫助解釋公司之違約機率。
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
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