Analysis on the Financal Pre-warning in Listed Company based on the Logit Mode
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The financial pre-warning in listed companies proved to be good reference to the rational investors. Based on the Logit nonlinear mode, also with the consideration of available of public information, the paper efforts on an empirical test on all data using several financial indexes, constructs the financial pre-warning logit mode, and predicts the companies which could be denounced as Special Treat.Keywords:
Mode (computer interface)
Listed company
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Considering the deficiencies in the field of researches on financial crisis prediction for the present, this paper build financial early warning model for manufacturing listed companies, using quarterly time serials data three years before special treatment (ST). We find out that the predictive validity of logistic financial early warning system based on time serials data is better than that based on cross-section data; logistic financial early warning is better than fisher multivariate discriminant analysis; corporate profitability, earnings per share (EPS) and general manager stake which significantly affect the financial distress.
Key words: Financial distress, Logistic model, Global principal component analysis.
Financial Distress
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Listed companies are open, complex nonlinear system. Based on the theory of entropy, the paper select a total of 126 companies that is the 2008–2010 ST companies and non-ST companies as the sample, propose the 30 financial and non-financial indicators with the actual situation of the listed companies financial crisis, use SPSS13.0 software for non parametric text and factor analysis to process a series of data and calculate entropy weights of the sample. The empirical results show that there are a significant difference between ST companies and non-ST companies. Early warning model of ST companies reach 80.95% of accuracy rate, which shows that the model is prediction accuracy and stability. The model has wide application space and can be applied to the prediction of financial crisis of listed companies.
Sample (material)
Empirical Research
Listed company
Financial Stability
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The article selects 12 financial indicators from the six aspects of listed companies' profitability, operating capacity, solvency, growth capacity, cash flow and capital structure to construct Probit model and Logit model to study the financial difficulties of listed companies in China. The results show that earnings per share, equity ratio, interest protection multiples and inventory turnover ratio have a significant early warning effect on the financial distress of listed companies in China. The Probit model has a prediction accuracy rate of 78.31% for whether the company will fall into financial difficulties, and the Logit model has a prediction accuracy rate of 92.18%. The Logit model's prediction ability is significantly better than the Probit model.
Probit
Ordered probit
Multivariate probit model
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The recent studies on financial distress are mostly confined to static econometric or statistical methods based on cross-sectional financial data ,and it is ignored that the variation of companies' financial status is a dynamic process. In order to show the change of companies in financial position, this study constructed the financial distress prediction model based on panel logit. On the selection of variables,we select not only financial ratios,but also indexes on ownership concentration, corporate governance and audit opinion. Empirical results indicate that the probabilistic predictions generated by the panel logit model can provide a measure of the company's financial position.
Financial Distress
Position (finance)
Ordered logit
Proxy (statistics)
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60 listed companies in the same size at Shenzhen Stock Exchanges are sampled. Possibilities of financial risks of those companies in 2013 are predicted by their financial data in 2010. Key elements of financial condition are analyzed and a prediction model is developed. The study finds that the prediction model is quite accurate in forecasting financial risks to accuracy rate of 86.67% as it can allocate weight to key elements objectively and reflect financial conditions of the listed companies. The model can be used to forecast and evaluate financial risks of listed companies and provide management and investor with references.
Predictive modelling
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The recent studies on financial distress are mostly confined to static econometric and statistical method based on cross-sectional financial data,and ignore the fact that the companies' financial status is a dynamic process.In order to show the change of companies in financial position,the paper established the financial distress prediction model based on panel logit.Empirical Results indicate that the forecast accuracy of panel logit model is better than ordinary logit model.
Financial Distress
Ordered logit
Position (finance)
Panel analysis
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Based on calculating the company efficiency index by using stochastic frontiers,this paper establishes the credit risk assessment model for IT industry and pharmaceutical and biological products industry by using logit regression.The research results show that the company efficiency has stronger ability for the long-term prediction of credit risk,which illustrates that the enterprise should take simultaneously the financial indexes and non-financial indexes such as the company efficiency into consideration in the course of the credit risk assessment so as to strengthen the effectiveness of financial early-warning system.
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In this paper,the listed companies of China from 2005 to 2007 are studied,the Logit model is used to conduct an empirical analysis of financial early-warning for listed enterprises,and then the effect of the models are tested.The results show that the logit model can be used to predict if there is a financial crisis for the listed companies one year later.
Listed company
Ordered logit
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The recent studies on financial distress are mostly confined to static econometric method based on cross-sectional financial data,and ignore the fact that the companies' financial status is a dynamic process.In order to show the change of companies in financial position,the paper established the financial distress prediction model based on panel Logit.On the selection of variables,we select not only financial ratios,but also indexes on ownership concentration, corporate governance and audit opinion.Empirical Results indicate that the forecast accuracy of panel Logit model is very high,so we can forecast the financial distress probability of next year by the current year's data.
Financial Distress
Ordered logit
Position (finance)
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