Finding Strong Relationships of stock prices using blockwise symbolic representation with dynamic time warping

Thunchira Thongmee, Hiroto Suzuki, Takahiro Ohno, Udom Silparcha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes the Blockwise Strong Relationship (BSR) method that calculates the degree of relationship between any pair of stocks based on only their prices. Our method deploys the data transformation adapted from the symbolic aggregation approximation (SAX) and the distance measure using dynamic time warping (DTW). We propose that the time series data should be processed in blocks of some appropriate size rather than the whole series at once. The experiment was done using IMI Energy indices. The result shows that our method can accurately draw the strongest related pair of stocks out of those that all look related on the surface.

Original languageEnglish
Title of host publicationINISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings
PublisherIEEE Computer Society
Pages104-109
Number of pages6
ISBN (Print)9781479930197
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014 - Alberobello, Italy
Duration: 2014 Jun 232014 Jun 25

Publication series

NameINISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings

Conference

Conference2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications, INISTA 2014
CountryItaly
CityAlberobello
Period14/6/2314/6/25

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Keywords

  • Dynamic time warping
  • Symbolic representation
  • Time series

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

Cite this

Thongmee, T., Suzuki, H., Ohno, T., & Silparcha, U. (2014). Finding Strong Relationships of stock prices using blockwise symbolic representation with dynamic time warping. In INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings (pp. 104-109). [6873604] (INISTA 2014 - IEEE International Symposium on Innovations in Intelligent Systems and Applications, Proceedings). IEEE Computer Society. https://doi.org/10.1109/INISTA.2014.6873604