The Application of Neuron Network in the Forecast of the Stock Price
Since the stock price is affected by many factors, we should consider it in different aspects when we forecast. The Artificial Neural Network (ANN) has the characters of adaptiveness, parallel process etc., which applied well in forecast. When using ANN for forecasting, the selection of the input nodes directly determines the operation efficiency and calculation precision of the network. In this paper,we lowered the dimension of the parameters which influence the forecast. When processing with the data, we compared the principal component analysis and other methods. We found that the network which took principal components as input nodes had a higher rate convergence, less error, more exact forecast result.
Neuron network Forecast Stock price
XUE Li_Ming CHEN Yan
School of Economics & Management,Dalian Maritime University,P.R.China,116026
国际会议
2006 International Conference on Management Science and Engineering(2006管理科学与工程国际学术研讨会)
武汉
英文
712-715
2006-11-08（万方平台首次上网日期，不代表论文的发表时间）