Analysis On The Finance Early-warning System Of The Listed Companies

Enierprises are threated by financial distress in the fierce market now.If enierprises can't take precaution against the financial distress in time,they will get in to trouble.But enterprises are not powerless in the face of such a predicament,the financial distress can be predieted in advance. Thus,essential analysis based on setting up the financial distress early warning index system which is disrelated and covered amountofinformation, and building up a financial distress early warning model,has great practical significance to stock market investors and the company's management.Mostof the prior researches were concerned with the establishment of corporate failure prediction models based on only financial ratios,or join few non-financial variables just with subjective judgement.This paper makes use of the financial statements of listed companies in China Stock Exehange and adds some non-financial variables into the model,such as equity structure,board governance and important matters.Using SPSS statistical analysis software,and build a successful model for corporate failure discrimination with factor analysis and Logistic regression analysis.Comparing former researeh,the main characteristic of this paper lies in four aspects: Firstly,using t-3 data unless t-1or t-2 data because of these two-year data has direct relationship with ST companies. Secondly,introducing more non-financial information to make the warning indicator system more comprehensive.Finally,dividing listed companies into manufacturing and non-manufacturing to establish different sectors warning model.Through the article we can find:(l)The majority state indicators of listed companies can not pass the significant test,do not obey normal distribution,(2)Factors which lead the manufacturing and non-manufacturing listed companies in financial difficulty are different;Financial and non-financial both have important impact to listed companies involving financial distress,Using factor analysis,principal component analysis and Logistic the hybrid model has been made better prediction。...