A Comparison of K-Means and Fuzzy C-Means Clustering Methods for a Sample of Gulf Cooperation Council Stock Markets

• Autorzy: Salam Al-Augby , Sebastian Majewski , Agnieszka Majewska , Kesra Nermend
• Języki publikacji: EN

Abstrakty

EN

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.(original abstract)

Słowa kluczowe

PL

Metoda k-średnich; Giełda papierów wartościowych; Data Mining

EN

K-means methods; Stock market; Data Mining

• Czasopismo: Folia Oeconomica Stetinensia
• Rocznik: 2014
• Tom: 14
• Numer: nr 2
• Strony: 19-36

Twórcy

autor

Salam Al-Augby

• University of Szczecin, Poland; University of Kufa, Iraq

autor

Sebastian Majewski

• University of Szczecin, Poland

autor

Agnieszka Majewska

• University of Szczecin, Poland

autor

Kesra Nermend

• University of Szczecin, Poland

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Identyfikatory

DOI

10.1515/foli-2015-0001