Abstract
The paper used the KMV model to manufacturing industry of Guangxi in China to concretely abstract the credit risk and enterprise innovation into a measurable quantitative index, and compare the changes in credit risk before and after COVID-19. This paper selects 17 Listed Companies in Guangxi manufacturing industry as empirical samples, and calculates the expected default rate of different companies by using the traditional and modified KMV models. The larger the index value is, the higher the credit risk is, And then affect the enterprise innovation activities. The results show that the overall credit risk management ability of Guangxi’s manufacturing industry is relatively high, but by the impact of COVID-19, credit risk has increased. If left unguarded, it will have an impact on enterprise innovation.
Highlights
This paper provides default risk indicators for Guangxi's manufacturing industry to compare the changes in credit risk before and after COVID-19
The structure of this paper is as follows: firstly, the KMV model is constructed from the preconditions and operation steps of the model; secondly, select the appropriate manufacturing listed companies in Guangxi as the sample empirical, with the help of MATLAB and other tools to get the results; we use regression analysis to revise the default point, which is an important parameter of KMV model, and re empirical, and compare with the previous empirical results; the rationality of the modified KMV model is tested and the final empirical conclusion is drawn
It can be seen that the trend is consistent with the empirical results of the traditional KMV model
Summary
This paper provides default risk indicators for Guangxi's manufacturing industry to compare the changes in credit risk before and after COVID-19. As for the measurement of credit risk, in the early days, it was mainly through the relevant financial data of enterprises to determine their credit degree and risk-taking ability This method of observing the static value has been used up to now. The contribution of this paper is that, in the context of COVID-19's impact on all walks of life in China, we use the revised KMV model and the actual situation of manufacturing companies in Guangxi to measure the credit risk before and after the outbreak. It provides a theoretical reference for financial risk prevention in Guangxi. The structure of this paper is as follows: firstly, the KMV model is constructed from the preconditions and operation steps of the model; secondly, select the appropriate manufacturing listed companies in Guangxi as the sample empirical, with the help of MATLAB and other tools to get the results; we use regression analysis to revise the default point, which is an important parameter of KMV model, and re empirical, and compare with the previous empirical results; the rationality of the modified KMV model is tested and the final empirical conclusion is drawn
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