A Comparison Of K-Means And Fuzzy C-Means Clustering Methods For A Sample Of Gulf Cooperation Council Stock Markets-Reference-Cited by-同舟云学术

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

Published:2014-12-01 Issue:2 Volume:14 Page:19-36
ISSN:1898-0198
Container-title:Folia Oeconomica Stetinensia
language:en
Short-container-title:

Author:

Al-Augby Salam¹,Majewski Sebastian²,Majewska Agnieszka²,Nermend Kesra³

Affiliation:

1. University of Kufa, Research and Information Qualifying Centre, Kufa, P.O. Box (21), Najaf Governorate, Iraq

2. University of Szczecin, Faculty of Economics and Management, Institute of Finance, Department of Insurance and Capital Markets, Mickiewicza 64, 71-101 Szczecin, Poland

3. 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

Abstract

Abstract 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.

Publisher

Walter de Gruyter GmbH

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