An Empirical Study On Enterprise Financial Early Warning Based On Kalman Filtering

Since the outbreak of the Wall Street financial crisis in the United States in 2008,the global economy has been in a downward state and has shown a continuous trend.In the downward international economic environment,the economy of our country is also in a weak trend.As the heart and aorta of economic growth,the development of the power industry is largely related to the growth capacity of the national economy.Taking into account the power of large-scale investment enterprises,high technical requirements,construction of large,slow recovery of investment,a wide range of impacts,the forecast of the financial crisis of electric power enterprises is the necessary guarantee to ensure the steady growth of the electric power industry.Therefore,the financial early warning capability of the power industry is just the key to help the power industry to prevent or find the uncertainties in the environment as soon as possible,and to ensure that the development of the power industry is on an increasing trend.Domestic and foreign literatures show that although the financial forecasting has many achievements both in the forecasting method and the early warning theory,the current financial forecasting is still a kind of static early-warning theory and tends to treat the financial early warning in a static and isolated way.And corporate financial early warning often does nothing.To this end,this paper firstly sort out the current financial early warning theory and literature,combined with the characteristics and types of financial risk of power enterprises,analysis of the current financial enterprises early warning model and index system defects.By using evolutionary game theory,this paper discusses the characteristics and changes of financial behavior of power enterprises.On this basis,the introduction of Kalman filter method,use its dynamic and high-frequency characteristics,which will be applied to financial warning in power enterprises.Constructing a dynamic financial early warning model based on the Kalman filter and a financial early warning indicator system based on cash flow,and conducting empirical research.Taking 30 Shanghai-Shenzhen ST listed power companies and 30 non-ST listed power companies in 2015-2017 as financial crisis samples and financial health samples respectively,the feasibility of forecasting based on the financial early-warning model and indexes is proved.The main innovations of this paper are as follows:(1)Combining with the development process of power industry,define the types and characteristics of financial risk of electric power enterprises;(2)Analyze the incentive behavioral factors of electric power enterprises with evolutionary game model;(3)Construct the financial early warning model based on Kalman filtering,improve the financial index system based on financial flow to enhance the power enterprise financial early warning system's substantive effect.The shortcomings of this paper:(1)I experience is still shallow and my knowledge reserved are limited,so some of the problems in the study may be biased;(2)Limited by the availability of data,research samples are only from China's Shanghai and Shenzhen listed power companies.