近两年中国上市公司由于受到新的冠状物疫情的冲击,经济增速放缓,面临种种危机,信用风险受到很大考验,而规避违约风险对公司未来的发展不仅有好处,而且在制度稳定性方面也将起到明显的作用。因此,我们选择了KMV模型与GARCH模式和SV模式相结合,对上市公司的股票收益波动率进行重新拟合和估算,以此来衡量上市公司的资信管理,采用调整后的GARCH-KMV模型和SV-KMV模型,对上市公司中的9家ST企业与9家非ST企业的信用风险进行了对比研究。结果显示,传统的KMV可以更好地衡量上市公司的信用风险,在结合GARCH模型和SV模型后也可以衡量上市公司的信用风险,但SV模型对于信用风险的解释效果要好于GARCH模型。Impacted by the COVID-19 pandemic, the growth rate of China’s economy has slowed down, and listed companies in China are facing various crises. Credit risk is under significant testing, and avoiding default risk is not only beneficial for the future development of companies but also crucial for the stability of the system. Therefore, this study employs the KMV model to measure the credit quality of listed companies and combines the GARCH and SV models to re-estimate the volatility of equity value for these companies. The revised GARCH-KMV model and SV-KMV model are then applied to compare and analyze the credit risk of 9 ST companies and 9 non-ST companies in the listed market. The results indicate that the traditional KMV model can effectively measure the credit risk of listed companies, and incorporating the GARCH and SV models improves its credit risk measurement. Furthermore, the SV-KMV model demonstrates a better explanatory effect on credit risk compared to the GARCH-KMV model.
