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Based on financial information of listed manufacturing companies, the research aims at predicting financial distress using the integrated model of factor analysis and discriminant analysis to establish the model, and tests the prediction accuracy of the model. The results show that the model in this paper has higher discriminant precision, and it makes further explanation that the choice of financial...
The listed companies will be specially treated when their business performance is bad or there are serious accidents, which is a rule to reveal the investment risk of stock market. So it is very important to study the performance of listed companies under special treatment (ST companies) for the development of stock market in China. We choose 50 companies as the samples in the ST plate of 2006 in...
In order to study the early warning of companies' financial risk, this paper used two models based on factor analysis, which are logistic regression and BP neural network. Finally, for the warming accuracy, BP neural network model is better than logistic regression model.
SVM based model is constructed for predicting performances of Chinese listed companies. The paper firstly uses factor analysis, equal value difference test and correlation test to sieve the financial indicators and corporate governance variables separately for representative variables, and then uses the method of support vector machine for an empirical analysis. The research shows the model of SVM...
With 112 listed companies from A-share market in Chinese securities markets as research sample, authors selected 56 newly ST companies among 2007 and 2008 as distressed enterprises group, and other 56 non-ST companies as comparison group. 13 financial indicators of these companies at three year before being ST were screened out, and the factor analysis and logistic regression were conducted. It found...
Credit risk assessment of companies has been an important part of the study on risk management for a long time, especially for the default risk of companies with a high liability-to-asset rate. In this paper, we use factor analysis method to establish a logistic regression model and make an empirical analysis on the credit risk of listed companies of Capital-Intensive Industries. The results show...
Logistic regression is a very common method in financial prediction. In order to establish the more effective model, the paper introduces factor analysis into logistic regression to overcome multiple co-linearity among variables and meanwhile retain useful information of original variables. The result shows that this model has better predictive capability. This suggests that for policymakers and others...
Based on published financial data from property-liability insurance companies, the factor analysis was adopted in this paper to screen important variables to establish credit rating perspectives. In addition, the concept of normal distribution was used to establish objective and scientific credit rating model that match the conditions of property-liability insurance companies in Taiwan. Through proper...
Financial index is always an important approach to evaluate companiespsila financial condition. This paper, based on analysis of disadvantages of traditional financial index system, uses way of factor analysis, and extracts nine of the most important common factors from usual financial index, then verifies effectiveness of these common factors by using statistical method. At last, we select seven...
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