The Research Of Financial Risk Assessment And Early Warning Of Electric Power Listed Companies

Electric power industry is the important basic energy industry of national economy. It plays a significant role in the national economic development strategy. Electricity listed companies as the most dynamic and the most potential for development enterprise of the power industry, its finances received extensive attention of investors and creditors. With the development of economic globalization, the Chinese listed companies faced with superior opportunity of development and great challenge at the same time. Listed electric power company as a member of the listed company also faces fierce competition and the risk of diversification, and financial risk is one of the most important risk that enterprises are facing in the process of development. In recent years, listed electric power companies have high asset-liability ratio, debt service pressure and financial risk. Therefore, it is of great significance for listed electric power companies to grasp the company’s current financial risk level and warn the risk effectively to enterprises’ability of resist financial risk.Firstly, this paper lists the related concepts of financial risk warning, introduces the theory of company’s financial risk assessment and warning. Secondly, this paper analyses the characteristics and risks of electric power industry. In reference to the research achievements of predecessors and combining the characteristics of listed electric power companies, this paper constructs a risk evaluation index system of listed electric power company from profitability, debt paying ability, development capability and growth ability. Considering the multi-collinearity problem of evaluation index, this paper uses the principal component TOPSIS method to do the comprehensive evaluation analysis, namely selects the principal component of evaluation index and use TOPSIS to evaluate the risk level comprehensively. Then use the support vector machine (SVM) with genetic algorithms (GA) to do the financial risk warning analysis of listed companies using Java programming. Then we found that the GA-SVM warning model compared with the traditional Logistic model has better discriminant accuracy. Finally, this paper put forward a financial risk control and management method of electric power listed companies.