Risk Assessment of Local Government Debt based on KMV Model: A Case Study of Hangzhou, Zhejiang Province

The present government debt governance focuses on calculating, preventing, and controlling local government debt risk. The default probability of local government debt in Hangzhou, Zhejiang Province, is calculated using a modified “Kealhofer, McQuown, and Vasicek” (KMV) model. The findings reveal that Hangzhou’s debt risk in the next three years is usually manageable, but that debt risk will progressively emerge in the coming years when the debt payback cycle begins.

Research on Modeling of Government Debt Risk Comprehensive Evaluation Based on Multidimensional Data Mining

In order to solve the problems of low accuracy of data mining, high relative error rate of evaluation and long time of evaluation in traditional government debt risk evaluation methods, this paper proposes a modeling method of government debt risk comprehensive evaluation based on multidimensional data mining. The MAFIA algorithm is used for multidimensional mining of government debt risk data, and K-means clustering algorithm is used for clustering processing of mined data. According to the clustering results, the KMV model is constructed, and the uncertainty factor is used to modify the model, so as to realize the comprehensive evaluation of government debt risk by using the modified KMV model. The experimental results show that the accuracy rate of government debt risk data mining is always above 91%, the relative error rate of evaluation is always below 3.4%, and the average evaluation time is 0.71s, the practical application effect is good.

Research on Countermeasures and Financing Risk of Small and Medium-Sized Enterprises in China

SMEs have played an important role in deepening of construction of socialist market economy in China. Their contribution rate to our country's economy is rising continuously, they also stimulate technical innovation. However, because of their small scale, credit margin and other factors and imperfect market mechanism, SMEs are facing a severe situation in the process of financing, the huge financing risk has become the core problem restricting the development of SMEs. This paper employed the KMV model to make an empirical analysis. Then, the author puts forward corresponding suggestions for the financing of SMEs in the future.

Research on Optimal Allocation Strategy of Bank Credit Funds Based on KMV Model and Logit Model

Using KMV model, normal Copula function, K-means cluster analysis and logit model, this paper constructs the enterprise credit risk assessment model, bank credit fund optimal allocation model, banking risk index system, and synthetically uses software such as MATLAB、SPSS to solve the problem of credit fund distribution strategy for small and medium-sized enterprises, and draws the conclusion that the loan interest rate classification of enterprise credit risk assessment, the weight of bank to credit fund distribution, and the change of bank risk index weight in sudden situation.Finally, the above model provides the strategy for bank credit fund allocation and gives the test and evaluation. The outstanding features of this paper are: using the KMV model and the normal Copula function, combining the enterprise credit rating and default times to establish a linear model to quantify the enterprise credit risk, will not beeasy to calculate the industry violation probability quantitative analysis, also get the bank credit annual interest rate fordifferent industries and levels of enterprises, and through the representative industries of the optimal loan weight calculation, so that the bank decision has the characteristics of the least unit risk. This paper also establishes a banking risk index system with emergency factors, which is of practical significance to make decision analysis of emergency events.

COVID-19’s influence on the credit risks and enterprise innovation of the Guangxi manufacturing——Based on the measure of KMV model

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.