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Identifying zigzag based perceptually important points for indexing financial time series

Phetking, Chaliaw and Md. Sap, Mohd. Noor and Selamat, Ali (2009) Identifying zigzag based perceptually important points for indexing financial time series. In: 2009 8th IEEE International Conference on Cognitive Informatics. Article number 5250725 . IEEE, pp. 295-301. ISBN 978-142444642-1

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Official URL: http://dx.doi.org/10.1109/COGINF.2009.5250725


Financial time series often exhibit high degrees of fluctuation which are considered as noise in time series analysis. To remove noise, several lower bounding the Euclidean distance based dimensionality reduction methods are applied. But, however, these methods do not meet the constraint of financial time series analysis that wants to retain the important points and remove others. Therefore, although a number of methods can retain the important points in the financial time series reduction, but, however, they loss the nature of financial time series which consist of several uptrends, downtrends and sideway trends in different resolutions and in the zigzag directions. In this paper, we propose the Zigzag based Perceptually Important Point Identification method to collect those zigzag movement important points. Further, we propose Zigzag based Multiway Search Tree to index these important points. We evaluate our methods in time series dimensionality reduction. The results show the significant performance comparing to other original method.

Item Type:Book Section
Uncontrolled Keywords:dimensionality reduction, financial time series analysis, important points, time series indexing, Zigzag base perceptually important points, ZIP based multi-way search tree
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:14923
Deposited By: Zalinda Shuratman
Deposited On:30 Sep 2011 15:12
Last Modified:08 Oct 2017 06:43

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