A Study Of The Coal Bonds Issuing Companies' Credit Risk Prediction Based On BP Neural Network

Coal industry is the upstream industry of electric power,iron and steel,cement and chemical industry.China is a country which is rich of coal,but lack of oil and gas.As a result,the coal industry occupies an important position in the national economy.However,in recent years its downstream industry is downturn in demand,and the production of the coal industry is excess.The profit margins of coal bonds issuing companies continue to shrink.Chinese coal industry is faced at present with an unprecedented credit crisis because of large losses.At the same time,credit rating agencies have downgraded the credit grades of lots of coal enterprises,which also provides the data support for research on the coal bonds issuing companies' credit risk prediction and meets the needs of investors,rating agencies and regulators.In all,it is of great practical significance.In this article,BP neural network is applied to the coal bonds issuing companies' credit risk prediction.First,the credit risk has been defined and the factors of credit risk have been described.After that,the working principles of neural network and BP neural network model are introduced.Secondly,we make a comprehensive analysis on the factors of the risk of coal bonds issuing companies,on the basis of' which we build the credit risk early warning indicator system for BP neural network.Finally,85 bond issuing companies in the coal industry are selected as the research sample.After screening and processing the index data of the sample,the BP neural network is trained.Then we test the accuracy of the result of the simulation with the selected samples.It is proved that the model works well.The selected indicator system can be able to reflect the credit risk of coal bonds issuing companies.The credit risk prediction model based on BP neural network is effective.