Thunchira Thongmee, Hiroto Suzuki, T. Ohno, U. Silparcha
{"title":"Finding Strong Relationships of stock prices using blockwise symbolic representation with dynamic time warping","authors":"Thunchira Thongmee, Hiroto Suzuki, T. Ohno, U. Silparcha","doi":"10.1109/INISTA.2014.6873604","DOIUrl":null,"url":null,"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.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2014.6873604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
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.