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Stock price forecasting based on BP neural network model of network public opinion

  • Computer Science Department of Inner Mongolian University

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

Abstract

with the development of Internet, many companies announced the stock information by various medium, and stock buyers comment that information as well as make rational investment strategies to maximize their profit. At present, many retail investors, who lack of channels to obtain real information, scarce professional knowledge of investment theory and easy to be affected by public opinion of Internet, make an irrational investment. This paper aims to combine the text analysis technique with comments on Vanke A (sz000002) from website to calculate the percentage of people with a positive view. This analysis method attempts to predict the impacts of investor sentiment on the stock market in the short term. Based on the network public opinion formation mode and technical indicators in stock market, this paper puts forward a BP neural network model. Then we improve the prediction accuracy of stock price by predicting the closing price.

Original languageEnglish
Title of host publication2017 2nd International Conference on Image, Vision and Computing, ICIVC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1058-1062
Number of pages5
ISBN (Electronic)9781509062379
DOIs
StatePublished - 18 Jul 2017
Externally publishedYes
Event2nd International Conference on Image, Vision and Computing, ICIVC 2017 - Chengdu, China
Duration: 2 Jun 20174 Jun 2017

Publication series

Name2017 2nd International Conference on Image, Vision and Computing, ICIVC 2017

Conference

Conference2nd International Conference on Image, Vision and Computing, ICIVC 2017
Country/TerritoryChina
CityChengdu
Period2/06/174/06/17

Keywords

  • BP neural network
  • Network public opinion
  • Stock price forecast
  • Text analysis

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