DocumentCode :
2604778
Title :
Research on predicting stock price by using fuzzy rough set
Author :
Xiao-feng, Hui ; Song-song, Li
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol., Harbin, China
fYear :
2010
fDate :
24-26 Nov. 2010
Firstpage :
1124
Lastpage :
1130
Abstract :
With the aim of getting more accurate and more reliable stock price predicted results, this paper proposes an effective method which is fuzzy rough set and data mining technology. Firstly, stock prices were classified to some groups according to their different time attribute by using fuzzy set and rough set means. Then we calculated truth values of these groups respectively based on the given fuzzy relation, and derived some candidates of regulations by data mining method. In the end, we chose the useful regulations corresponding the time period and predicted the trend of stock price during the certain time period. This study shows that the method, which using fuzzy rough set and dada mining could make the predicted results is more effective.
Keywords :
data mining; fuzzy set theory; rough set theory; stock markets; data mining technology; fuzzy rough set; stock price prediction; Approximation methods; Biological system modeling; Data mining; Databases; Set theory; Stock markets; data mining; fuzzy rough set; stock price; truth value;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering (ICMSE), 2010 International Conference on
Conference_Location :
Melbourne, VIC
ISSN :
2155-1847
Print_ISBN :
978-1-4244-8116-3
Type :
conf
DOI :
10.1109/ICMSE.2010.5719937
Filename :
5719937
Link To Document :
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