Applied research on stock forcasting model based on BP neural network

Yue Ma, Chang Yu, Chunyu Xia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of 2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011
Pages4578-4580
Number of pages3
DOIs
StatePublished - 2011
Event2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011 - Harbin, China
Duration: 12 Aug 201114 Aug 2011

Publication series

NameProceedings of 2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011
Volume9

Conference

Conference2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011
Country/TerritoryChina
CityHarbin
Period12/08/1114/08/11

Keywords

  • BP neural network
  • function approximability
  • stock forcasting

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