DocumentCode :
575087
Title :
Dimensional ranking and reduction approach for finding optimal stock price influencing factors: An empirical study
Author :
Ahmad, F. ; Ku-Mahamud, K.R. ; Din, A. Mohamed ; Mohsin, M. F Mohamad
Author_Institution :
Sch. of Comput., Univ. Utara Malaysia, Sintok, Malaysia
fYear :
2011
fDate :
Nov. 29 2011-Dec. 1 2011
Firstpage :
788
Lastpage :
791
Abstract :
A limited number of factors in critical areas are necessary to identify the sustainability of companies [30]. It was found that three factors were commonly used [2] and a maximum of seven factors was recommended [2]. In order to identify the optimal factors, we propose a method based on rough set theory that consisted of five main steps. These were data cleansing and preparation, dimensional reduction, ranking selected factors, optimal factor extraction, and rules generation and evaluation. Dimensional reduction was conducted using rough set theory where the set of factors were identified from the set of reducts that produce highest classification accuracy. These factors were first ranked through computation of its occurrences in reduct sets and then selected based on highest occurrences. The major contribution of this work is the reduced factors shows competitive results in classifying new cases and therefore keeping the quality of knowledge.
Keywords :
rough set theory; stock markets; classification accuracy; company sustainability; data cleansing; data preparation; dimensional ranking; dimensional reduction; optimal factor extraction; optimal stock price influencing factors; rough set theory; rule evaluation; rule generation; selected factor ranking; Accuracy; Companies; Data mining; Educational institutions; Rough sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
Conference_Location :
Seogwipo
Print_ISBN :
978-1-4577-0472-7
Type :
conf
Filename :
6316723
Link To Document :
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