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Financial time series representation using multiresolution important point retrieval method

Phetking, Chaliaw and Md. Sap, Mohd. Noor and Selamat, Ali (2008) Financial time series representation using multiresolution important point retrieval method. Jurnal Teknologi Maklumat, 20 (1). pp. 106-119. ISSN 0128-3790

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Financial time series analysis usually conducts by determining the series important points. These important points which are the peaks and the dips indicate the affecting of some important factors or events which are available both internal factors and external factors. The peak and the dip points of the series may appear frequently in multiresolution over time. However, to manipulate financial time series, researchers usually decrease this complexity of time series in their techniques. Consequently, transfonning the time series into another easily understanding representation is usually considered as an appropriate approach. In this paper, we propose a multiresolution important point retrieval method for financial time series representation. The idea of the method is based on finding the most important points in multiresolution. These retrieved important points are recorded in each resolution. The collected important points are used to construct the TS-binary search tree. From the TS-binary search tree, the application of time series segmentation is conducted. The experimental results show that the TS-binary search tree representation for financial time series exhibits different performance in different number of cutting points, however, in the empirical results, the number of cutting points which are larger than 12 points show the better results.

Item Type:Article
Uncontrolled Keywords:financial time series, multiresolution , TS-binary search tree, SB-binary search tree, segmentation
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:10370
Deposited By: Zalinda Shuratman
Deposited On:15 Oct 2010 07:49
Last Modified:01 Nov 2017 04:17

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