Atlantis Press Paper Details: SBT-QL: A Stock Time Series Query Language based on Specialized Binary Tree Representation

Stock time series query is one of the fundamental components in technical analysis. Technical analysts would like to query either a whole time series or a segment of a time series in different resolutions for long-term or short-term investigations. Moreover, unnecessary data points should be filtered during the query process for easy analysis. In this paper, query approaches for both the whole stock time series and a subsequence of the stock time series based on the SB-Tree representation scheme are proposed. An approximate approach is proposed to improve the performance of the subsequence query process. Moreover, the local and global pruning methods are suggested to filter the unimportant data points. Besides studying these various query methods, an user-oriented query language, called SBT-QL, is proposed for: using easily, implementing efficiently and providing the ability to specify the query conditions to limit the retrieved data. The efficiency and effectiveness of the proposed approach are shown by the experiments.

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title:		SBT-QL: A Stock Time Series Query Language based on Specialized Binary Tree Representation
publication:		JCIS-2006 Proceedings
part of series:		Advances in Intelligent Systems Research
ISBN:		978-90-78677-01-7
ISSN:		1951-6851
DOI:		doi:10.2991/jcis.2006.30 (how to use a DOI)
author(s):		Tak-chung Fu, Fu-lai Chung, Robert Luk, Man-yee Au, Chak-man Ng
corresponding author:		Tak-chung Fu
publication date:		October 2006
keywords:		stock time series, subsequence searching, query language, technical analysis
abstract:		Stock time series query is one of the fundamental components in technical analysis. Technical analysts would like to query either a whole time series or a segment of a time series in different resolutions for long-term or short-term investigations. Moreover, unnecessary data points should be filtered during the query process for easy analysis. In this paper, query approaches for both the whole stock time series and a subsequence of the stock time series based on the SB-Tree representation scheme are proposed. An approximate approach is proposed to improve the performance of the subsequence query process. Moreover, the local and global pruning methods are suggested to filter the unimportant data points. Besides studying these various query methods, an user-oriented query language, called SBT-QL, is proposed for: using easily, implementing efficiently and providing the ability to specify the query conditions to limit the retrieved data. The efficiency and effectiveness of the proposed approach are shown by the experiments.
copyright:		© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
full text:		JCIS06-CIEF-5.pdf (3710 K)