Research On Credit Rating Optimization And Influencing Factors Of Chinese Mining Enterprises

The number and scale of default bonds in China’s bond market are increasingly showing an upward trend.In 2020,the bond market suffered a significant impact due to the continuous fermentation of Yongmei incident.As a result,the secondary market sold bonds at low prices one after another,and some credit bonds in the primary market were forced to cancel their issuance,causing panic in the bond market and even affecting the stock market.In this situation,investors are cautious about the ratings given by relevant institutions,and it also causes people to think about China’s credit rating market.First of all,there is the possibility of falsely high rating;Secondly,the default probability of some highly rated bonds in the market is higher,and the default amount is larger;In addition,there is a time lag in credit rating,which often leads to the "diving" of bond rating on the day of default.By reading the relevant credit rating theory and literature at home and abroad,this paper summarizes the important achievements and shortcomings of the credit rating system constructed by previous scholars,and combs the important influencing factors and default mechanism of mining industry default risk,which is necessary to find theoretical support for the optimization of mining industry enterprise credit rating.This paper uses the AHP and factor analysis to get the weight of financial indicators.The crawler technology transforms the qualitative part of the index system into the quantitative part,and initially constructs the enterprise credit rating system for the mining industry.After the credit score of issuers is obtained by using the system,the rating distribution of issuers is formed by cluster analysis.At the same time,the effectiveness of the rating system is tested by comparing the rating results of the existing institutions and the optimized ones.According to the simulation test results,the current model has a good risk warning and warning effect on default bonds.According to the above-mentioned rating results,the more stable enterprises in the first,second and third quarters of 2020 are selected as the samples of empirical research,and the high rating group and low rating group are formed.On this basis,an empirical model is built to verify which factors are more important in the sub financial indicators and news evaluation.The empirical results show that external news evaluation,gross profit margin,ROA,accounts receivable turnover and other financial indicators are more worthy of attention.According to the research conclusions,this paper puts forward relevant suggestions.