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.
CITATION STYLE
Karpio, K., & Łukasiewicz, P. (2018). Pattern recognition in financial data using association rule. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11114 LNCS, pp. 512–521). Springer Verlag. https://doi.org/10.1007/978-3-030-00692-1_44
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