Abstract
In this paper an Association Rules data mining technique is adopted to explore the co-movement between sector indices listed on the Warsaw Stock Exchange. The sector indices describe various parts of the Polish economy as well as Ukrainian companies and are not as sensitive to individual random events as single companies are. The measures describing discovered rules are calculated and strong rules are selected. Based on the strong rules the relations between parts of the Polish economy are presented. The interesting mutual interrelations between parts of Polish and Ukrainian economies are also observed.
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References
Huang, Z., Lu, X., Duan, H.: Mining association rules to support resource allocation in business process management. Expert Syst. Appl. 38(8), 9483–9490 (2011)
Kamsu-Foguem, B., Rigal, F., Mauget, F.: Mining association rules for the quality improvement of the production process. Expert Syst. Appl. 40(4), 1034–1045 (2013)
Srisawat, A.: An application of association rule mining based on stock market. In: 3rd International Conference on Data Mining and Intelligent Information Technology Applications, pp. 259–262 (2011)
Na, S.H., Sohn, S.Y.: Forecasting changes in Korea composite stock price index (KOSPI) using association rules. Expert Syst. Appl. 38, 9046–9049 (2011)
Pan, Y., Haran, E., Manago, S., Hu, Y.: Co-movement of European stock markets based on association rule mining. In: Third International Conference on Data Analytics, pp. 54–58 (2014). ISBN: 978-1-61208-358-2
Karpio, K., Łukasiewicz, P., Orłowski, A.: Price-volume relationship in polish stock market. Acta Phys. Pol. A 121(2-B), B61–B66 (2012)
Karpio, K., Łukasiewicz, P., Orłowski, A.: Stock indices for emerging markets. Acta Phys. Pol., A 117(4), 619–622l (2010)
Karpio, K., Łukasiewicz, P., Orłowski, A., Ząbkowski, T.: Mining associations on the warsaw stock exchange. Acta Phys. Pol., A 123(3), 553–559 (2013)
Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: International Conference on Management of Data. ACM SIGMOD, pp. 207–216 (1993)
Azevedo, P.J., Jorge, A.M.: Comparing rule measures for predictive association rules. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladenič, D., Skowron, A. (eds.) ECML 2007. LNCS (LNAI), vol. 4701, pp. 510–517. Springer, Heidelberg (2007)
Agrawal, R., Shafer, J.: Parallel mining of association rules. IEEE Trans. Knowl. Data Eng. 8(6), 962–969 (1996)
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Karpio, K., Łukasiewicz, P., Orłowski, A. (2016). Associations Rules Between Sector Indices on the Warsaw Stock Exchange. In: Řepa, V., Bruckner, T. (eds) Perspectives in Business Informatics Research. BIR 2016. Lecture Notes in Business Information Processing, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-319-45321-7_22
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DOI: https://doi.org/10.1007/978-3-319-45321-7_22
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