DocumentCode
2328389
Title
Stock Trading Rule Discovery based on temporal data mining
Author
Galib, A.A. ; Alam, Mahbub ; Hossain, Nowshad ; Rahman, Rashedur M.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., North South Univ., Dhaka, Bangladesh
fYear
2010
fDate
18-20 Dec. 2010
Firstpage
566
Lastpage
569
Abstract
One of the major tasks in stock market analysis is the discovery of specific events that give rise to a particular event. In this research we emphasize on temporal data mining with a time dimensional approach. This has led us to the discovery of sequential continuous patterns. The patterns serve as rules that enable us to determine the occurrence of an event on a particular stock-transaction day. In our paper, we have proposed and implemented the STRDTM (Stock Trading Rule Discovery by Temporal Mining) algorithm with real life data from Dhaka Stock Exchange as input.
Keywords
data mining; financial data processing; stock markets; Dhaka Stock Exchange; particular stock transaction; sequential continuous patterns discovery; specific events discovery; stock market analysis; stock trading rule discovery; temporal data mining; temporal mining algorithm; Datamining; association rule mining; frequent sets; temporal datamining sequential pattern discovery;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering (ICECE), 2010 International Conference on
Conference_Location
Dhaka
Print_ISBN
978-1-4244-6277-3
Type
conf
DOI
10.1109/ICELCE.2010.5700755
Filename
5700755
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