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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...
This paper aims to solve the multi-project multi-item investment combination under stochastic surroundings. A new stochastic chance-constrained programming model for investigating its problem will be presented, in which there are three objectives with some stochastic constraints to construct a 0-1 integer programming model, and demonstrate how to use PSO to solve the optimization model with a small...
In this paper, we investigate the statistical properties of fluctuations of Chinese stock index. According to the theory of artificial neural network, a stochastic time effective function is introduced in the forecasting model of the index in the present paper, which gives an improved neural network - the stochastic time effective neural network model. In this model, a promising data mining technique...
Corporate credit ratings are important financial indicators of investment risks. Traditional credit rating models employ classical econometrics methods with heteroscedasticity adjustments across various industries. In this paper, we propose using machine learning techniques in predicting corporate ratings and demonstrate, empirically, that multiclass machine learning algorithms outperform traditional...
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