• DocumentCode
    2902942
  • Title

    Mining Better Technical Trading Strategies with Genetic Algorithms

  • Author

    Ni, Jiarui ; Zhang, Chengqi

  • Author_Institution
    Univ. of Technol., Sydney, NSW
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    26
  • Lastpage
    33
  • Abstract
    Technical analysis is one of the two main schools of thought in the analysis of security prices. It is widely believed and applied by many professional and amateur traders. However, it is often criticized for lacking scientific rigour or worse, for lacking any basis whatsoever. We propose to explore the feasibility and/or limitation of technical analysis by the optimization of technical trading strategies over historical stock data with genetic algorithms. This paper presents the optimization problem in detail and discusses the potential problems to be tackled during the optimization. Preliminary experiments show that it can identify the limitations quickly
  • Keywords
    data mining; genetic algorithms; pricing; data mining; genetic algorithm; historical stock data; optimization problem; security prices; technical analysis; technical trading strategy; Algorithm design and analysis; Australia; Economic forecasting; Educational institutions; Genetic algorithms; History; Pattern analysis; Profitability; Security; Stock markets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Integrating AI and Data Mining, 2006. AIDM '06. International Workshop on
  • Conference_Location
    Hobart, Tas.
  • Print_ISBN
    0-7695-2730-2
  • Type

    conf

  • DOI
    10.1109/AIDM.2006.12
  • Filename
    4030709