Title :
The Prediction of Dow Jones Cbn China 600 Inde Based on “Most Updated” GM(1,1) Model and Grey Dynamic Neural Network
Author :
Chen, Yitao ; Tao, Li ; Li, Haibo
Author_Institution :
China Univ. of Min. & Technol., CUMT, Xuzhou, China
Abstract :
Dow Jones Cbn China 600 Inde is a measure of an indicator of the stock which China\´s domestic investors can invest in. Through the prediction of the Dow Jones Cbn China 600 Inde, we can predict the future development trend of China\´s Stock Market. In this paper, we established prediction models based on "most updated" GM(1,1) model and grey dynamic neutral network. The Dow Jones Cbn China 600 Inde is divided into trend item and fluctuation item, which are predicted by "most updated" GM(1,1) model and grey dynamic neutral network respectively. Consequently, we get the prediction result of Dow Jones Cbn China 600 Inde, and find this method has a high accuracy.
Keywords :
economic indicators; grey systems; neural nets; stock markets; China stock market; Dow Jones Cbn China 600 Inde prediction; GM(1,1) model; domestic investors; grey dynamic neural network; stock indicator; Accuracy; Cities and towns; Code standards; Computer networks; Finance; Fluctuations; Neural networks; Predictive models; Random processes; Stock markets; ¡°Most updated¡± GM(1; 1) model; Dow Jones Cbn China 600 Inde; Grey Dynamic Neural Network;
Conference_Titel :
Information and Computing (ICIC), 2010 Third International Conference on
Conference_Location :
Wuxi, Jiang Su
Print_ISBN :
978-1-4244-7081-5
Electronic_ISBN :
978-1-4244-7082-2
DOI :
10.1109/ICIC.2010.284
