Research On The Financial Crisis Early Warning In Chinese Wholesale And Retail Listed Companies

In a highly competitive market environment, enterprises may occur crisis at any time due to the restriction and influence of all kinds of financial risk and the economic environment uncertainty, especially, the financial crisis. In order to ensure survival and continued development in the fierce competition, enterprises need to have a sense of crisis in the daily operation and management, and establish a scientific, reasonable and effective financial crisis early warning model.Since China’s reform and opening up, wholesale and retail trade in China has developed rapidly, and become one of the leading industries of the national economy. However, some operators blindly expand enterprise scale, leading to increase business risk and financial risk. Because of too much debt, too much operating costs and too much loss, enterprises’ overall profitability is poor. Finally, the financial crisis happen due to being unable to repay debts. Therefore, financial crisis early warning model for wholesale and retail company is imperative, but research on wholesale and retail financial crisis early warning is rare, relative to other industry.Firstly, through reading a large number of relevant financial crisis early warning research literature at home and abroad, the thesis generalizes from the concept, form, reason and early warning model of financial crisis.Secondly, the thesis constructs the initial early-warning index system, from the solvency, profitability, operation, development, cash flow, corporate governance, market value and risk level. Using SPSS 17.0, adopting the nonparametric test method and factor analysis method screens and optimizes index. Based on the BP neural network, this thesis builds the wholesale and retail financial crisis early warning model by making use of MATLAB software.Finally, using financial crisis early warning model, the thesis forecast the financial conditions of "Sanlian Trading Company" in 2009-2014.Results show:BP network model predict healthy financial situations as crisis financial situations in 2012; prediction results of other years are same to the real financial condition of company.