Title :
Text mining approaches for stock market prediction
Author :
Nikfarjam, Azadeh ; Emadzadeh, Ehsan ; Muthaiyah, Saravanan
Author_Institution :
Fac. of IT, MMU, Cyberjaya, Malaysia
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;
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
DOI :
10.1109/ICCAE.2010.5451705
