International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2557

Full Length Research Paper

Companies’ performance in stock exchanges: Using sequential patterns-algorithm

Hameed Ullah Khan, Zahid Ullah and Maqsood Mahmud*          
Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.  
Email: [email protected]

  •  Accepted: 14 October 2011
  •  Published: 02 January 2012


This paper communicates the overall behaviour of the stock exchange. Basically, stock exchange is marketing for companies/group(s) assets to sell their shares and in-return generates revenues to invest and grow their company/business. The attitude of giant investors keeps on changing their move to destabilise the market so that the trivial investors cannot become stable/grow and compel to sell their shares on less profit margin to the giant investors. These giant investors try to manipulate/capture the market and try to establish their monopoly/control over the market without strong competition. The relative performance of companies in various stock exchanges around the world is studied, graphs plotted with reference to dates on quarterly and monthly basis are drawn and patterns are analyzed. The stability of companies has been determined by using sequential patterns-algorithm. This algorithm maneuver is followed as a continued process until the surpassed results have yield.


Key words: Currency conversion, databases, decision graph, stock exchanges index, electronic commerce.


Abbreviations: RBFNN, Radial basis function neural networks; L-GEM, localized generalization error model; EMH, efficient market hypothesis; NASDAQ, National Association of Securities Dealers Automated Quotations; MCS, multiple classifier system.