Stock trend forecasting method based on sentiment analysis and system similarity model

Author

Kaihui Zhang ; Lei Li ; Peng Li ; Wenda Teng

Author_Institution

Coll. of Econ. & Manage., Harbin Univ. of Sci. & Technol., Harbin, China

Volume

2

fYear

2011

fDate

22-24 Aug. 2011

Firstpage

890

Lastpage

894

Abstract

This paper combine sentiment analysis based on system similarity model and Bayesian classification model to design a prediction system for the stock plate price trend analysis according to the Internet stock news and information. This system can automatically classified the stock news on the web and apply sentiment analysis to judge related comments and predict the price movements. By the way of cross-rotation test show that the system can effectively predict and analyze the stock market and have good stability.

Keywords

Bayes methods; Internet; economic forecasting; pricing; stock markets; Bayesian classification model; Internet stock information; Internet stock news; cross-rotation test; prediction system; price movements; sentiment analysis; stock plate price trend analysis; stock trend forecasting method; system similarity model; Analytical models; Bayesian methods; Internet; Predictive models; Stability analysis; Stock markets; Training; Bayesian model; sentiment analysis; stock prediction; system similarity model;

fLanguage

English

Publisher

ieee

Conference_Titel

Strategic Technology (IFOST), 2011 6th International Forum on

Conference_Location

Harbin, Heilongjiang

Print_ISBN

978-1-4577-0398-0

Type

conf

DOI

10.1109/IFOST.2011.6021163

Filename

6021163