Pattern Recognition in Financial Data Using Association Rule

The paper is devoted to study patterns between the world’s financial markets. The classical Association Rules method was adopted to study the relations between time series of stock market indices. One revealed the comovement patterns are predominant over the anti comovement ones. The strength of the...

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Bibliographic Details
Published inComputer Vision and Graphics Vol. 11114; pp. 512 - 521
Main Authors Karpio, Krzysztof, Łukasiewicz, Piotr
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2018
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Association rules
Data mining
Pattern recognition
Stock market indices
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Summary:The paper is devoted to study patterns between the world’s financial markets. The classical Association Rules method was adopted to study the relations between time series of stock market indices. One revealed the comovement patterns are predominant over the anti comovement ones. The strength of the relations depends on the distance between markets. One extracted the strongest patterns what allowed to distinguishing the groups of financial markets. The strongest links between Polish and other stock markets were discovered.
ISBN:3030006913
9783030006914
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-00692-1_44