A Comparison of k-means and Fuzzy c-means Clustering Methods for a Sample of Gulf Cooperation Council Stock Markets

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...

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Published inFolia oeconomica stetinensia Vol. 14; no. 2; pp. 19 - 36
Main Authors Al-Augby, Salam, Majewski, Sebastian, Majewska, Agnieszka, Nermend, Kesra
Format Journal Article
LanguageEnglish
Published Wydawnictwo Naukowe Uniwersytetu Szczecińskiego 01.12.2014
Szczecin University Press
De Gruyter Open
Sciendo
Subjects
A12
A13
Banking
C02
C63
Cluster analysis
Correlation
Economy
Energy market
Financial Markets
fuzzy c-means
G11
GCC
k-means
news
Statistical analysis
Stock exchange
stock market
news
stock market
kmeans
GCC
fuzzy cmeans
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1730-4237
1898-0198
1898-0198
DOI:10.1515/foli-2015-0001