Establishing Financial Crisis Early Warning Models for Listed Companies

2011 ◽  
Author(s):  
Dai Wei
Keyword(s):  
Financial Crisis ◽  
Early Warning ◽  
Listed Companies

The Research on Long-Term Financial Early-Warning System of Listed Companies

2013 ◽  
Vol 670 ◽  
pp. 216-221 ◽  
Author(s):  
Wei Ming Mou ◽  
Shui Bin Gu
Keyword(s):  
Financial Crisis ◽  
Early Warning ◽  
Early Warning System ◽  
Stock Exchange ◽  
Warning System ◽  
Listed Companies ◽  
Special Treatment ◽  
Warning Model ◽  
First Time

The article takes listed companies as research samples. Firstly, it selects 36 ST or *ST companies listed in Shanghai and Shenzhen Stock Exchange Market, who received special treatment during 2007 to 2009 for the first time and it also chooses another 36 normal companies as paired ones. Then, after using Factor analysis for identifying indexes, the paper go on with utilizing logistic to structure a financial long-term warning model. To verify the effectiveness of the model, the paper selects another 12 financial crisis companies and 12 financial fit companies to test. The results come out to show that establishing an effective long-term financial early-warning system helps enterprises to avoid financial crisis.

An Empirical Study on Predicting Financial Risk of Listed Companies

2010 ◽  
Vol 108-111 ◽  
pp. 1267-1271 ◽  
Author(s):  
Yan Li Chen ◽  
Li Hui Chen
Keyword(s):  
Financial Crisis ◽  
Financial Reporting ◽  
Early Warning ◽  
Financial Risk ◽  
Listed Companies ◽  
Financial Ratios ◽  
Growth Ratio ◽  
Revenue Growth ◽  
Discriminant Model ◽  
Set Up

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.

scholarly journals 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

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Feixiong-Ma ◽  
Yingying-Zhou ◽  
Xiaoyan-Mo ◽  
Yiwei-Xia
Keyword(s):  
Neural Network ◽  
Financial Crisis ◽  
Early Warning ◽  
Comprehensive Evaluation ◽  
Warning System ◽  
Listed Companies ◽  
Support Vector ◽  
Stable Operation ◽  
Social Significance ◽  
Neural Network Models

In the context of COVID-19, many companies have been affected by the financial crisis. In order to carry out a comparative study on the accuracy of the company’s financial crisis early warning method, this study used RPROP artificial neural network and support vector machine, with 162 listed companies’ two-year panel financial indicator data as a model sample, and the test sample established a financial crisis early warning model. The theory of comprehensive evaluation combining two kinds of neural network methods is put forward innovatively. The predicted results can strengthen the supervision of the listed companies with risks by themselves and others and have important economic and social significance to ensure the stable operation of the listed companies, the securities market, and the national economy.

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