我国林业上市公司信用风险研究——基于KMV模型

Research on Credit Risk of the Forestry Industry Listed Company in China——Based on KMV Model

文章以我国沪深两市A股林业上市公司为研究对象,选取2007-2012年首次成为ST的8家公司和对应的8家非ST公司为研究样本,运用KMV模型研究我国林业上市公司信用风险。实证过程中,文章根据我国林业公司特点研究确定KMV模型中各参数的计算方法,计算出在不同违约点下各个样本的违约距离,主要结论:财务危机前非ST公司与ST公司的违约距离表现出显著差异,运用KMV模型能够有效识别我国林业上市公司的信用风险状况;我国林业上市公司的违约点应设定为短期负债加上50%长期负债;在研究连续两年违约距离的基础上,构建了我国林业上市公司两级信用风险预警体系。

This paper uses the KMV model to analyze the credit risk of the forestry industry listed company in China. The resea- rch sample includes 8 special treatment（ST） companies and 8 non-defauh companies in Shanghai and Sheuzhen stock markets which from 2007 to 2012. The empirical research first selects appropriate methods according to the characters of the forestry industry company. Then distance to default（DD） is calculated for each company based on KMV model. The results displayed that the KMV mo- del can be well applied to assess the credit risk status of the current forestry listed companies in China. After the modification of the model, a proper default point 50% was found according to the practical situation. With the use of KMV model, a credit risk early warning system was established, which is, when the distance to default of a certain company has declined to a certain point, conclu- sion can be made that this company will probably be plunged into a financial crisis, and thus should be supervised closely by the management as well as the banks.