Financial risk prediction for listed companies using IPSO-BP neural network

Abstract

Manufacturing is an important part of the market economy. Judgment and analysis of financial risks in the manufacturing industry help promote the healthy development of the real economy. A sample of manufacturing companies for the period 2015-2017 is selected. First, the financial indicators of the companies are screened using principal component analysis. Second, Back Propagation (BP) neural network parameters are optimized using improved particle swarm optimization (IPSO), and a financial risk early warning model based on IPSO-BP is constructed. Finally, an empirical analysis is performed. The analysis results reveal that the model can accurately predict the financial risks of manufacturing companies and provide valuable guidance in the form of a company financial risk warning.