Research On Financial Early Warning Of Internet Listed Companies Based On BP Neural Network Mode

With the rapid economic development,market competition is increasingly fierce.Enterprises are facing the threat of being eliminated.In order to seek a place in the economic market and to avoid being eliminated by the market,enterprises must always be vigilant to strengthen the management of financial management to prevent financial risks.Since the "Internet +" plan mentioned in the government report,it accelerated the development of the Internet industry,mainly for the combination of Internet companies and traditional industriesand then promote the development of e-commerce,industrial Internet and Internet finance.The Internet industry has become a force China's economic development can not be ignored.The existence of financial risk of Internet companies has a great impact on the healthy,stable and sustainable development of enterprises.It is because of the importance of the development of the Internet industry to the national economy and the particularity of the industry itself.It is of great value to construct the financial early warning model of Internet listed companies.First,this paper elaborates the theory of financial risk,financial early warning and the development of the Internet industry in China to analyze the necessity of financial early warning of the Internet industry.Secondly,combining with the "traffic" in the Internet,the light assets,low assets and liabilities,this paper constructs the financial early warning index system of Shanghai and Shenzhen listed companies.Then,combining with the theory and steps of BP neural network and the characteristics of Internet industry,the BP neural network is constructed,and the BP neural network is constructed.And then selecting 43 Internet companies listed in Shanghai and Shenzhen as the research samples,using SPSS 22 statistical software to optimize the indicators to determine the early warning interval,and then through the factor analysis method to get the score as an early warning model of the input variables,samples are trained and simulation test;Finally,the early warning results are analyzed.