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基于修正的KMV模型我国上市公司信用风险评估
Credit Risk Assessment of Listed Companies in China Based on the Modified KMV Model

DOI: 10.12677/orf.2024.142139, PP. 332-339

Keywords: KMV模型,股权价值,违约点,信用风险
KMV Model
, Equity Value, Default Point, Credit Risk

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Abstract:

KMV模型作为上世纪90年代以美国股市为基础而设计的信用风险衡量方法,对于今天中国上市公司价值的衡量缺乏可靠性的市场基础,尤其对于非流通股价值的衡量缺乏西方发达市场的信用风险考量机制,因此本文结合前人的研究基础,对KMV模型中股权价值的计算公式、股权价值波动率的衡量方法,以及违约点在流动负债和长期负债两个维度的权重作出新的衡量标准,并通过python统计软件随机挑选我国股市10家上市公司进行实证检验,研究发现:1) 负债结构对于上市公司的违约风险有较大影响。2) 公司组织管理框架、行业竞争水平、市场饱和程度、战争政治等因素是公司股权价值的影响因素。3) 监管当局创新信用监管体制十分重要,除了站位公司角度进行资金与信用管理之外,应建立企业间的信息交流平台。
As a credit risk measurement method designed based on the U.S. stock market in the 90s of the last century, the KMV model lacks a reliable market basis for measuring the value of listed companies in China today, especially for the measurement of the value of non-tradable shares, and lacks the credit risk consideration mechanism of Western developed market. Therefore, based on the previous research basis, this paper makes a new measurement standard for the calculation formula of equity value, the measurement method of equity value volatility, and the weight of default point in the two dimensions of current liabilities and long-term liabilities based on the previous research. Through Python statistical software, 10 listed companies in China’s stock market are randomly selected for empirical testing, and the results show that: 1) The debt structure has a great impact on the default risk of listed companies. 2) Factors such as the company’s organizational management framework, industry competition level, market saturation, and war politics are the influencing factors of the company’s equity value. 3) It is very important for the regulatory authorities to innovate the credit supervision system, in addition to the perspective of the company to carry out capital and credit management, the information exchange platform between enterprises should be established.

References

[1]  Xu, F. (2020) Bifractional Black-Scholes Model for Pricing European Options and Compound Options. Journal of Systems Science and Information, 8, 346-355.
https://doi.org/10.21078/JSSI-2020-346-10
[2]  Merton, R.C. (1974) On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. Journal of Finance, 29, 449-470.
https://doi.org/10.1111/j.1540-6261.1974.tb03058.x
[3]  Zuo, J. (2023) Research on the Credit Risk of Listed Companies Based on KMV Model—Taking Gree Electric Appliances as an Example. Academic Journal of Business Management, 5, 25-29.
https://doi.org/10.25236/AJBM.2023.051004
[4]  Wang, X.C. and Xu, K. (2023) Credit Risk Evaluation of Real Estate Industry Based on GA-GARCH-KMV Model. Journal of Risk Analysis and Crisis Response, 13, 288-300.
https://doi.org/10.54560/jracr.v13i4.413
[5]  Allen, D.E. and Powell, R.J. (2016) Take It to the Limit: Innovation CVATR Applications to Extreme Credit Risk Measurement. European Journal of Operational Research, 249, 456-475.
https://doi.org/10.1016/j.ejor.2014.12.017
[6]  许嘉和. 银行过度授信解决路径[J]. 中国金融, 2015(20): 60-61.
[7]  扶明高. 探索授信总额联合管理机制前瞻性防控信用风险[J]. 金融纵横, 2015(11): 4-7.
[8]  蒋代明. 区域过度授信评价指标体系研究——基于S省的实证分析[J]. 金融监管研究, 2018(9): 65-80.
[9]  霍勤. 审计监督、公司内外部治理与企业债务融资成本[J]. 财会通讯, 2019(19): 33-38.
[10]  李延喜, 曾伟强, 马壮, 陈克兢. 外部治理环境、产权性质与公司投资效率[J]. 南开管理评论, 2015, 18(1): 25-36.
[11]  Charitou, A., Clubb, C. and Andreou, A. (2022) The Value Relevance of Earnings and Cash Flows: Empirical Evidence for Japan. Journal of International Financial Management & Accounting, 11, 1-22.
https://doi.org/10.1111/1467-646X.00053
[12]  Carey, M. and Hrycay, M. (2021) Parameterizing Credit Risk Models with Rating Data. Journal of Banking & Finance, 25, 197-270.
https://doi.org/10.1016/S0378-4266(00)00124-2
[13]  李绍荣, 刘星洋. 城投债信用风险的压力测试: 基于优化后的KMV模型[J]. 新视野, 2023(6): 79-87.
[14]  李宾, 覃子岳. 上市全国性股份制商业银行信用风险度量——基于KMV模型[J]. 经济研究参考, 2022(12): 125-136.
https://doi.org/10.16110/j.cnki.issn2095-3151.2022.12.017
[15]  陈延林, 吴晓. A股上市公司ST风险预警——基于KMV模型的大样本经验实证[J]. 华南师范大学学报(社会科学版), 2014(4): 92-99 182.
[16]  李朝辉, 张明洁, 杨帆, 等. 基于修正KMV模型的商业银行信用风险研究[J]. 金融发展研究, 2023(7): 89-92.
https://doi.org/10.19647/j.cnki.37-1462/f.2023.07.011
[17]  王佳, 曹琼予. 基于跳跃-扩散KMV模型的上市公司信用风险评估[J]. 技术经济, 2022, 41(1): 160-168.
[18]  关晓宇, 韩淑亚, 周昊明. 环境违规披露对企业债务违约的影响研究[J]. 税务与经济, 2023(3): 99-105..
[19]  赵浩, 鲁亚军, 胡赛. 基于改进型KMV模型的中国公司信用风险度量研究[J]. 征信, 2018, 36(7): 6-12.
[20]  孙亮, 吕丹妮. 我国共享经济企业信用风险度量的案例分析——基于KMV修正模型的实证研究[J]. 技术经济, 2021, 40(6): 132-139.
[21]  冯敬海, 田婧. 基于遗传算法KMV模型的最优违约点确定[J]. 大连理工大学学报, 2016, 56(2): 181-184.

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