Title :
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
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;
Conference_Titel :
Strategic Technology (IFOST), 2011 6th International Forum on
Conference_Location :
Harbin, Heilongjiang
Print_ISBN :
978-1-4577-0398-0
DOI :
10.1109/IFOST.2011.6021163
