The Listed Company Credit Risk Measurement Based On Kmv Model Research

Credit risk has always been the core of risk management, and the ability to conduct effective credit risk management has been considered the key of financial industry, or even a country’s financial system. In the field of modern credit risk management, quantitative risk management is undoubtedly the foundation; therefore, from the1990s, a number of new risk measurement methods began to appear, in which the most revolutionary production is VaR methods. In Europe and other developed countries, it has ordered that banks and other financial institutions must implement VaR approach to manage risk; it can be said that, VaR technology has become a standard of credit risk measure in the international industry. But because of missing data, the VaR-based risk management models, which are widely used in the developed countries, are not feasible in our country, then, how can the VaR methodology applied to our risk management practice becomes the problem this article explores solution.This paper introduces the calculation of credit spreads to build a model based on KMV model, which can directly measure the samples’ VaR, VaR and CVaR. The advanced KMV model can be applied to not only qualitative risk assessment, but also quantify management from the perspective of direct measurement of credit losses.Based on the real estate industry companies, this empirical study validate the use of the advanced KMV model. Studies have shown that, first, the default distance can accurately reflects the sample’s exposure to credit risk, which means that KMV model can accurately measure the credit risk of China’s listed companies. Second, the historical simulation method at a lower confidence level may underestimate the risk, but at a higher confidence level would overestimate the risk. At the same time, compared with VaR, CVaR can better deal with the phenomenon of loss distribution of the thick tail. Third, this improvement based on credit spread has ensured the validity of the model. This empirical examination has not used the parameters with industry characteristics; therefore, this improvement of the KMV model, and the conclusions of this study can also be extended to any other industries.