Financial Crisis Warning Research Based On Neural Network Model

The enterprise’s finance condition is the reflection of business performance.Monitoring and forecasting financial statement can assist managers avoiding financialcrisis. This becomes the hot spot of theory and practice research. This paper usesneural network as financial early warning method as it has strong learning andfault-tolerant abilities.There are six chapters in the paper. The first chapter is the introduction. In thischapter, the paper introduced the background and the significance of the study offinancial crisis warning. The second chapter is literature review. The papersummarizes and analyzes the literature of neural network both in domestic andinternational, which lay the foundation for further study. The third chapter is thedefinition and sample selection. In this chapter, the paper clarify the definition offinancial crisis, the sample and duration of the research. The fourth chapter is to buildfinancial forecasting index system. In this chapter, the paper select the index by themethod of statistics and rough set. The fifth chapter is to construct financial warningmodel. The paper build neural network model by using the above warning indexes.And the last chapter is conclusion.In order to improve the accuracy of warning, the research uses the statisticalmethod and rough theory to select the warning indexes. Through the empiricalresearch, the paper proves that the warning indexes pretreatment will improve theaccuracy of warning. Meanwhile, through the comparison of different methods ofpretreatment, the research also proves that the accuracy of warning by rough theory isbetter than it by statistical method.