Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns

Lei, I. L. and Teh, Phoey Lee * and Si, Yain-Whar (2021) Direct least squares fitting of ellipses segmentation and prioritized rules classification for curve-shaped chart patterns. Applied Soft Computing, 107. p. 107363. ISSN 1568-4946

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Official URL: http://doi.org/10.1016/j.asoc.2021.107363

Abstract

In financial markets, appearances of chart patterns in time series are commonly considered as potential signals for imminent change in the direction of price movement. To identify chart patterns, time series data is usually segmented before it can be processed by different classification methods. However, existing segmentation methods are less effective in classifying 16 curve-shaped chart patterns from financial time series. In this paper, we propose three novel segmentation methods for classification of curveshaped chart patterns based on direct least squares fitting of ellipses. These methods are implemented based on the principles of sliding windows, turning points, and bottom-up piece wise linear approximation. To further enhance the efficiency of classifying chart patterns from real-time streaming data, we propose a novel algorithm called Accelerating Classification with Prioritized Rules (ACPR). Experiments based on real datasets from financial markets reveal that the proposed approaches are effective in classifying curveshaped patterns from time series. Experiment results reveal that the proposed segmentation methods with ACPR can significantly reduce the total execution time.

Item Type: Article
Uncontrolled Keywords: Financial time series; Segmentation; Sliding window; Chart patterns; Direct least squares fitting of ellipses.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Others > Non Sunway Academics
Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 22 Apr 2021 03:46
Last Modified: 22 Apr 2021 03:46
URI: http://eprints.sunway.edu.my/id/eprint/1746

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