Mining Associations on the Warsaw Stock Exchange

• Authors: K. Karpio , P. Łukasiewicz , A. Orłowski , T. Ząbkowski
• Languages of publication: EN

Abstracts

EN

Identification of patterns in stock markets has been an important subject for many years. In the past, numerous techniques, both technical and econometric, were used to predict changes in stock markets, but dependences among all the companies listed on a stock market were considered in a limited extent. Numerous studies confirm that larger stocks items appear to influence smaller ones and that, on a global level, most of the world's stock markets are integrated. Therefore, this study implements the association rules using a data mining approach to explore the co-movement between stock items listed on the Warsaw Stock Exchange. We believe that in order to describe and to understand market's behavior, data mining techniques are more flexible in use than for instance pricing models based on a finance theory. The former seems to be more effective for explaining market behavior without making particular assumptions.

Keywords

EN

89.65.Gh; 07.05.Kf; 07.05.Rm

Discipline

• 07.05.Rm: Data presentation and visualization: algorithms and implementation
• 89.65.Gh: Economics; econophysics, financial markets, business and management(for economic issues regarding production and use of renewable energy, see 88.05.Lg)
• 07.05.Kf: Data analysis: algorithms and implementation; data management(for data analysis in nuclear physics, see 29.85.-c)

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2013
• Volume: 123
• Issue: 3
• Pages: 553-559

Dates

published

2013-03

Contributors

author

K. Karpio

• Department of Informatics, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-776 Warsaw, Poland

author

P. Łukasiewicz

• Department of Informatics, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-776 Warsaw, Poland

author

A. Orłowski

• Department of Informatics, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-776 Warsaw, Poland

author

T. Ząbkowski

• Department of Informatics, Warsaw University of Life Sciences (SGGW), Nowoursynowska 159, 02-776 Warsaw, Poland

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Identifiers

DOI

10.12693/APhysPolA.123.553