Text mining approaches for stock market prediction

Author

Nikfarjam, Azadeh ; Emadzadeh, Ehsan ; Muthaiyah, Saravanan

Author_Institution

Fac. of IT, MMU, Cyberjaya, Malaysia

Volume

4

fYear

2010

fDate

26-28 Feb. 2010

Firstpage

256

Lastpage

260

Abstract

Stock market prediction is an attractive research problem to be investigated. News contents are one of the most important factors that have influence on market. Considering the news impact in analyzing the stock market behavior, leads to more precise predictions and as a result more profitable trades. So far various prototypes have been developed which consider the impact of news in stock market prediction. In this paper, the main components of such forecasting systems have been introduced. In addition, different developed prototypes have been introduced and the way whereby the main components are implemented compared. Based on studied attempts, the potential future research activities have been suggested.

Keywords

data mining; stock markets; forecasting system; news contents; stock market behavior analysis; stock market prediction; text mining approach; Data mining; Economic forecasting; Genetic algorithms; Investments; Neural networks; Prediction methods; Prototypes; Stock markets; Support vector machines; Text mining; News Mining; data mining; knowledge discovery; stock market prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-5585-0

Electronic_ISBN

978-1-4244-5586-7

Type

conf

DOI

10.1109/ICCAE.2010.5451705

Filename

5451705