基于KMV模型的上市公司债务违约概率度量与实证分析

Measurement and Empirical Analysis of Listed Companies Debt Default Probability via KMV Model

摘要: 如何准确度量上市公司债务的违约风险一直是企业债务风险管理的研究热点。本文运用KMV模型，通过分析我国上市公司发布的财务报表，就它们的债务违约概率问题进行了相关研究。本文建立了基于KMV模型的上市公司债务违约概率，应用模型实际度量了2012年我国证券市场上41家上市公司的违约概率。同时，将41家上市公司分行业进行同类分析以及类间分析。实证结果表明，当企业的资产负债比大于80%时，无论其净资产负债比率高低，均具有较高的信用风险，而当企业的资产负债比率低于50%，那么只要没有出现负净资产收益率，则公司违约的可能性较低。

Abstract: How to measure the default risk of debt of listed companies has always been a hot topic in risk management. In this paper, KMV model is used to analyze relevant data of financial statements issued by listed companies in China, and the probability of their debt default is studied. The default probability of debt of listed companies based on KMV model is established, and the default probability of 41 listed companies in China’s securities market in 2012 is measured by the model. Meanwhile, 41 listed companies were divided into industries for similar analysis and inter-class analysis. The empirical results show that when the company’s asset-liability ratio is higher than 80%, regardless of its net asset liability ratio, it has a high credit risk, while when the company’s asset-liability ratio is lower than 50%, as long as there is no negative return on equity, the company is less likely to default.