Research On Financial Crisis Early Warning Of Listed Companies In Information Technology Industry Based On BP Neural Network

Uncertainty risks in business operations increase with the increasingly complex market environment,and financial crises occur from time to time.The financial crisis often indicates that the enterprise may have a comprehensive crisis,once the enterprise is deep in the financial crisis,it may not be able to guarantee the normal capital chain of the enterprise,and when serious,it may affect the continuous operation of the enterprise and even make the enterprise bankrupt and liquidated.The characteristics of high growth,high risk,and high returns of the information technology industry make the industry more likely to have a financial crisis,and the occurrence of a financial crisis will make companies in the industry change more frequently and be more harmful.Therefore,it is necessary to establish an effective financial crisis early warning model to prevent and control the occurrence of financial crisis risks.BP neural network can highly fit non-linear functional relationships,has good learning adaptability,high parallel computing and information processing ability,and applies BP neural network to early warning of financial crisis.It can quickly adapt to the impact of changes in the economic environment.The accuracy of prediction results is relatively high.This paper chooses all listed companies in China's information technology industry as the research object,draws lessons from domestic and foreign scholars' research and information technology industry characteristics,and establishes a financial early warning index system with remarkable industry characteristics.There are many indicators reflecting the financial crisis,the relationship between the indicators is complex,and it is difficult to carry out the early warning work of the financial crisis,so it should be preliminarily screened and optimized.And BP neural network method has the characteristics of high classification accuracy and strong learning ability,which makes it have certain potential in financial early warning.By using BP neural network,the financial risk warning model of listed companies in information industry is constructed and tested by simulation.BP the accuracy of neural network in early warning financial crisis,in order to expect the information technology industry early warning financial crisis to provide ideas.The panel data of the companies in the first 3years of financial crisis were used as a sample for early warning.The results show that the BP neural network early warning information technology industry has better modeltraining performance,higher test accuracy and stronger recognition ability.Whether it is a financial crisis company or a financial health company,the accuracy of the test of the BP neural network model constructed by the index data of t-1 years is higher than the test accuracy of t-2 and t-3.The comprehensive correct rates for years t-3,t-2,and t-1were 87.74%,91.51%,and 95.28%.It can be seen that the BP neural network for early warning of financial crisis has good applicability.The accuracy of the model are higher than 85%.The closer to the year of financial crisis,the more warning information contained in the indicator data,the better the warning effect.