• DocumentCode
    2910405
  • Title

    An empirical study of collaboration methods for coevolving technical trading rules

  • Author

    Adamu, Kamal ; Phelps, Steve

  • Author_Institution
    Center for Comput. Finance & Economic Agents, Univ. of Essex, Colchester, UK
  • fYear
    2010
  • fDate
    8-10 Sept. 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Coevolutionary algorithms employ collaboration methods in assessing the fitness of solutions. In this paper, we explore four different collaboration methods for coevolving technical trading rules for entering, and exiting long and short positions, and stop loss rules for long and short positions respectively. Our results show that our problem is sensitive to the collaboration method being used and that an averaging method with more than one collaborator from each species is most efficient for our problem.
  • Keywords
    financial data processing; groupware; coevolving technical trading rule; collaboration method; stop loss rules; Collaboration; Companies; Genetics; Grammar; Security; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2010 UK Workshop on
  • Conference_Location
    Colchester
  • Print_ISBN
    978-1-4244-8774-5
  • Electronic_ISBN
    978-1-4244-8773-8
  • Type

    conf

  • DOI
    10.1109/UKCI.2010.5625600
  • Filename
    5625600