Using Artificial Neural Networks to Evaluate the Grading of Stock Based on the Principle of Information Spread
Jingjing Li · Zhongguo guanli kexue · 2004
This paper proposed the method of applying artificial neural Networks to evaluate the grading of stock.At first,we establish the criteria system to evaluate the grading of stock,and then evaluate the stock index of training sample in ANN.Second,optimize the result based on information spread and use the optimized result to train neural networks with the back propagation.When arriving the necessary precision,the training will be stopped.The artificial neural networks may evaluate the grading of stock.In the end of this paper,we give a practical example and the detailed calculation steps,to explain this method and the grading results of stock.Using this method to evaluate the grading of stock will be helpful to reduce the influences of subjectivity and the market changes.