Financial crisis early warning analysis is a matter of grave social and economic concern. It is important for enterprises, commercial banks and various investors. This is an exploratory study to determine if financial ratios of crisis companies differ from those of no crisis companies. The crisis firms (n=63) were then matched with no crisis firms on the basis of firm size, time period, and industry. Using this matched-pairs design, choose 63 listed companies, which are marked ST companies because of abnormal financial standing in Shanghai and Shenzhen in 2006, form the financial crisis samples, and choose some similar sized listed companies in same industry as matching samples, Taking the index of property liabilities ratio, audit opinion, finance lever ratio, gross property net profit ratio, sales revenue growth ratio and cash flux to current liability ratio as the final variants, set up the discriminant model by Fisher’ coefficient, conduct the case analysis of financial crisis early warning. These results provide empirical evidence of the limited ability of financial ratios to detect and predict crisis financial reporting.
The Establishment of a Financial Crisis Early Warning System for Domestic Listed Companies Based on Two Neural Network Models in the Context of COVID-19
