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