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Folia Oeconomica Stetinensia

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A Comparison Of K-Means And Fuzzy C-Means Clustering Methods For A Sample Of Gulf Cooperation Council Stock Markets

Salam Al-Augby / Sebastian Majewski
  • University of Szczecin, Faculty of Economics and Management, Institute of Finance, Department of Insurance and Capital Markets, Mickiewicza 64, 71-101 Szczecin, Poland
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/ Agnieszka Majewska
  • University of Szczecin, Faculty of Economics and Management, Institute of Finance, Department of Insurance and Capital Markets, Mickiewicza 64, 71-101 Szczecin, Poland
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/ Kesra Nermend
  • University of Szczecin, Faculty of Economics and Management, Institute of IT in Management, Department of Computer Methods in Experimental Economics, Mickiewicza 64, 71-101 Szczecin, Poland
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Published Online: 2015-06-03 | DOI: https://doi.org/10.1515/foli-2015-0001


The main goal of this article is to compare data-mining clustering methods (k-means and fuzzy c-means) based on a sample of banking and energy companies on the Gulf Cooperation Council (GCC) stock markets. We examined these companies for a pattern that reflected the effect of news on the bank sector’s stocks throughout October, November, and December 2012. Correlation coefficients and t-statistics for the good news indicator (GNI) and the bad news indicator (BNI) and financial factors, such as PER, PBV, DY and rate of return, were used as diagnostic variables for the clustering methods.

Keywords: news; k-means; GCC; stock market; fuzzy c-means

JEL classification: A12; A13; C02; C63; G11


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About the article

Received: 2014-02-03

Accepted: 2014-10-24

Published Online: 2015-06-03

Published in Print: 2014-12-01

Citation Information: Folia Oeconomica Stetinensia, Volume 14, Issue 2, Pages 19–36, ISSN (Online) 1898-0198, DOI: https://doi.org/10.1515/foli-2015-0001.

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