DocumentCode
3354998
Title
Applied research on stock forcasting model based on BP neural network
Author
Yue Ma ; Yu Chang ; Chunyu Xia
Author_Institution
Coll. of Manage., Northwestern Polytech. Univ., Xi´an, China
Volume
9
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
4578
Lastpage
4580
Abstract
Making use of the function approximation and self-learning of BP neural network, we analyze the historical data in Shanghai Stock between June 2006 and November 2009, construct a stock forecasting model based on BP neural network, and verify the model through some test samples. Finally, we can use the Robust model to forcast the short-term stock. Matlab simulation experiments indicate that the model is feasible and effective in short-term stock forcasting.
Keywords
backpropagation; economic forecasting; function approximation; neural nets; stock markets; BP neural network; Matlab simulation; Shanghai stock; function approximation; robust forecast model; self-learning; stock forecasting model; Analytical models; Biological neural networks; Data models; Forecasting; Mathematical model; Predictive models; Training; BP neural network; function approximability; stock forcasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location
Harbin, Heilongjiang
Print_ISBN
978-1-61284-087-1
Type
conf
DOI
10.1109/EMEIT.2011.6023120
Filename
6023120
Link To Document