• DocumentCode
    2325518
  • Title

    Objective function design in a grammatical evolutionary trading system

  • Author

    Bradley, Robert ; Brabazon, Anthony ; O´Neill, Michael

  • Author_Institution
    Natural Comput. Res. & Applic. Group, Univ. Coll. Dublin, Dublin, Ireland
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Designing a suitable objective function is an essential step in successfully applying an evolutionary algorithm to a problem. In this study we apply a grammar-based Genetic Programming algorithm called Grammatical Evolution to the problem of trading model induction. A number of experiments were performed to assess the effect of objective function design on the trading characteristics of the evolved trading strategies. Empirical results suggest that the choice of objective function has a significant impact. The paper concludes with in and out-of-sample results, and indicates a number of avenues of future work.
  • Keywords
    commerce; genetic algorithms; evolved trading strategies; grammar-based genetic programming; grammatical evolutionary trading system; objective function design; trading model induction; Algorithm design and analysis; Biological system modeling; Data models; Evolutionary computation; Mathematical model; Measurement; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2010 IEEE Congress on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6909-3
  • Type

    conf

  • DOI
    10.1109/CEC.2010.5586020
  • Filename
    5586020