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
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;
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
DOI :
10.1109/EMEIT.2011.6023120
