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This paper applies DEA model to a sample of 58 power plate listed companies in the securities market in China in 2008, with a view to identifying the financial risk companies and non-financial risk companies, instead of using ST in the past. Then, after comparing logit regression model and neural network LVQ in predicting the company financial risks, the conclusion was drawn that neural network LVQ...
Nowadays, personal credit scoring models have played a vitally important part for many organizations in keeping away from credit risks. This paper establishes a personal credit scoring model via one of data mining approaches-genetic algorithm, which is a useful method applied to solve credit scoring problems. And the experiment of this model is proved to its high efficiency and evaluated its significant...
In this paper, using factor analysis to study the sources of China's financial risk, concluded that the major factor of the financial risks is macroeconomic risk, foreign investment risk, banking risk and the stock market risk; using BP artificial neural network model for the establishment of early warning and training and testing the sample data with it, and then prediction the state of the financial...
This paper presents a new stochastic chance-constrained 0-1 integer programming model for investigating the investment combination problem in multi-project multi-item investment combination. The proposed model includes two objectives with stochastic constraints to construct a 0-1 integer programming model. On the one hand, the risk value will be measured by negative entropy; on the other hand, the...
Credit scoring models are very important tools for credit granting institutions to assess the credit risk of their customers. Most previous researches focus on improving predictive accuracy of models. In this research, a weighted LS-SVM credit scoring model with Area under ROC curve maximization is proposed and optimized by direct search. The tests on two real-world datasets show that it is effective...
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