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中国信用债违约风险的重新测度:基于行业敏感性的独特视角 被引量:4

Reconstructing China’s Credit Default Risk Prediction Model: Based on the Perspective of Industry Sensitivity
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摘要 近年来,中国信用债违约风险事件集中爆发,仅2018年就有124只债券违约。因此,剖析中国信用债违约的特征,选择恰当的指标体系就信用债的违约风险开展科学预测,对于信用债市场的健康发展至关重要。有鉴于此,利用截至2018年9月末中国债券市场全样本信用债数据,基于行业敏感性的独特视角,重新构建债券违约风险的预测模型,可实现对全市场信用债违约风险的模拟和演绎,并从相关结果中挖掘出中国信用债违约风险的特征,即近年来金融、地产等行业的企业违约风险大幅度提升,违约风险空间分布明显向南部地区转移,地方企业是信用风险较大的发债主体。 In recent years,China’s credit default risk incidents have erupted,with 124 bonds defaulted in 2018 alone. Therefore,it is significant for the market development to examine the characteristics of China’s credit default and select appropriate index system to scientifically predict credit default risk. Using the whole sample credit data in China’s bond market by the end of September 2018 and taking the perspective of industry sensitivity,this paper reconstructs a credit default risk prediction model,which can simulate and deduce the whole market credit default risk. It also finds out the features of China’s credit default risk: first,the default risk of enterprises in finance and real-estate industries is sharply increasing;second,the spatial layout of default risk presents southwards;third,local enterprises are bond issue bodies at greater risks.
作者 蓝发钦 燕群 谢东辉 LAN Fa-qin;YAN Qun;XIE Dong-hui
出处 《华东师范大学学报(哲学社会科学版)》 CSSCI 北大核心 2020年第1期179-186,200,共9页 Journal of East China Normal University(Humanities and Social Sciences)
基金 国家自然科学基金青年项目“混业经营背景下我国商业银行非利息业务发展及其影响研究”(项目编号:71603085)
关键词 信用债 违约风险模型 行业敏感性 credit default default risk model industry sensitivity
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  • 1梁琪.企业经营管理预警:主成分分析在logistic回归方法中的应用[J].管理工程学报,2005,19(1):100-103. 被引量:36
  • 2巴塞尔委员会.有效银行监管的核心原则[Z].1997.
  • 3张文彤.SPSS11统计分析教程高级篇[Z].2002.
  • 4Altman,E. Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy [J].Journal of Finance,1965,23 (Sept.).
  • 5Aharony J., Jones C. P. and Swary I. An Analysis of Risk and Return Characteristics of Corporate Bankruptcy Using Capital Market Data[J].Journal of Finance,1980,35(Sept.)6.
  • 6Erkki. K. Laitinen. Predicting a Corporate Credit Analyst's Risk Estimate by Logistic and Linear Models[J].International Review of Financial Analysis,1999,8.
  • 7Sjur. Westgaard et. Al. Default Probabilities in a Corporate Bank Portfolio: A Logistic Model Approach [J].European Journal of Operational Research,2001,(135).
  • 8Eisenbeis R A. Pitfalls in the application discriminant analysis in business and economics[J]. The Journal of Finance,1997,32: 875~900.
  • 9Tam K Y, Kiang M. Managerial application of neural networks: the case of bank failure prediction[J]. Management Sciences, 1992,38(1): 926~947.
  • 10Frydman H ,Altman E I, Li Kaoduen. Introducing recursive partitioning for financial classification: the case of financial distress[J]. The Journal of Finance,1985,40(1): 269~291.

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