我国上市公司信用违约风险的实证检验
Empirical Test of Credit Default Risk of Listed Companies in China
DOI: 10.12677/FIN.2013.34006, PDF, HTML, XML,  被引量 下载: 8,823  浏览: 26,377 
作者: 唐绍欣, 田广健, 刘 蕾*:山东大学经济研究院,济南;王小娇:中国银行山东省分行,青岛
关键词: 信用风险KMV模型违约距离 Credit Risk; KMV Model; Default Distance
摘要: 上市公司信用违约风险度量的技术在西方已经比较成熟,信用风险度量的方法和模型在理论上和实践中都形成了一套完整的体系。而我国的信用违约风险度量还刚刚起步,对于信用评级还处于探索阶段,远不能达到商业银行对于贷款安全管理的要求。而本文所讨论的KMV模型作为现代四大信用风险度量模型之一,相较于其他三种方法,所需要的参数在中国目前的数据库建设下相对可以获得,其计算方法也有强大的理论依据做支撑,通过计算得到的数值相比传统的信用风险度量方法有更强的说服力,更有利于银行管控风险和上市公司进行诚信建设,促进金融市场发展。结论表明,我国上市公司存在信用违约的风险与模型的实际检验基本一致。因此通过研究信用违约风险度量模型,结合我国金融市场的现状,探索出适合我国信用违约风险度量的模型具有理论和现实意义。
Abstract: The credit default risk measurement technology of listed Corporation is so mature in the west that a complete system of methods and models of credit risk measurement are formed in theory and practice. But in China, the measurement of credit default risk is still in its infancy and the credit rating is still in the exploratory stage, which can’t meet the needs of commercial bank loans for safety management requirements. As one of modern four major credit risk measurement models, KMV parameters can be obtained in the Chinese current database which is under construction now, and its calculation methods have strong theoretical bases to support itself. The calculated data is more convincing than that from the traditional credit risk measurement methods, which can help the banks to control the risks and the listed corporations to build its integrity, promoting the financial market. The results show that credit default risk of listed Chinese companies is almost consentaneous to this empirical test of models. Thus, through the research of credit default risk measurement models, exploring the Chinese credit default model has significance both in theory and practice.
文章引用:唐绍欣, 王小娇, 田广健, 刘蕾. 我国上市公司信用违约风险的实证检验[J]. 金融, 2013, 3(4): 41-49. http://dx.doi.org/10.12677/FIN.2013.34006

参考文献

[1] J. P. Morgan. Credit metrics——Technical documentation. City: Publishing house, 1997.
[2] KMV Corporation. Credit monitor overview. San Francisco, California, 1993.
[3] W. H. Beaver. Financial ratios as predictors of failure. Journal of Accounting Research, 1966, 71-111.
[4] J. O. Horrigan. The determinants of long term credit standing with financial ratios, empirical research in accounting; selected studies. Supplement to Accounting Research, 1966, 44-62.
[5] E. I. Altman. Financial ratio, discriminant analysis and prediction of corporate bankruptcy. Journal of Finance, 1968, 23(4): 589-610.
[6] E. B. Deakin. A discriminate analysis of predictors of business failure. Journal of Accounting Research, 1972, 3:167-169.
[7] J. Ohison. Financial ratios and the probabilistic prediction of bankruptcy. The Journal of Accounting Research, 1980, Berlin: Spring, 109-130.
[8] E. I. Altman, G. Marco and F. Varetto. Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience). The Journal of Banking and Finance, 1994, 18: 505-529.
[9] 张维, 李玉霜. 商业银行信用风险分析综述[J].管理科学学报, 1998, (3).
[10] 吴军,张继宝,信用风险量化模型比较分析,国际金融研究. 2004(8).
[11] 董颖颖, 薛锋, 关伟. KMV模型在我国证券市场的适用性分析及改进[J]. 生产力研究, 2004, 8: 116-117.
[12] 王春峰,万海晖,张维,商业银行信用风险评估及其实证研究,管理科学学报,1998(1).
[13] 方洪全, 曾勇. 银行信用风险评估方法实证研究及比较分析[J]. 金融研究, 2004(1): 62-69.
[14] 阎庆民.我国商业银行信用风险VaR的实证分析[J],金融研究,2004(6):31-33.
[15] 惠晓峰, 孙嘉鹏. 商业银行信用风险识别: 信用矩阵的实证应用研究[J]. 国际金融研究, 2004, (9): 11-13.
[16] 张玲,杨贞柿,陈收. KMV模型在上市公司信用风险评价中的应用研究[J]. 系统工程, 2004, 1:84-89
[17] 胡文彬. 新巴塞尔协议内部评级法探析及相关实证[J]. 浙江大学学报, 2007, 5.
[18] 鲁炜,刘冀云. KMV模型关系函数推测及其在中国股市的验证[J]. 运筹与管理,2003, 6: 43-48.
[19] 翟东升、张娟、曹运发,KMV模型在上市公司信用风险管理中的应用,工业技术经济,2007年1月.