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

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

Author(s): Salam Al-Augby, Sebastian Majewski, Agnieszka Majewska, Kesra Nermend
Subject(s): Economy, Financial Markets
Published by: Wydawnictwo Naukowe Uniwersytetu Szczecińskiego
Keywords: news; k-means; GCC; stock market; fuzzy c-means

Summary/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.

  • Issue Year: 14/2014
  • Issue No: 2
  • Page Range: 19-36
  • Page Count: 18
  • Language: English