• DocumentCode
    3415898
  • Title

    Stocks scanner evaluator for stocks or options

  • Author

    Paraschiv, D. ; Raghavendra, S. ; Vasiliu, L.

  • Author_Institution
    CIMRU, Nat. Univ. of Ireland, Galway
  • fYear
    2009
  • fDate
    March 30 2009-April 2 2009
  • Firstpage
    28
  • Lastpage
    35
  • Abstract
    This paper introduces a stock scanner evaluator for stocks and options. In the presented work the scanner picks from thousands of stocks the most suitable stocks for an options or stocks investor. The proposed stocks scanner evaluator suggests the stocks that have the largest positive near future change (for purchasing stocks or calls) and the stocks that have the largest negative near future change (for purchasing puts). The scanner uses a neural network to rank the stocks and the neural network is trained using parallel genetic algorithm. Related work is provided as well as model framework, neural network and parallel genetic algorithm, results testing and evaluation together with future work.
  • Keywords
    genetic algorithms; investment; neural nets; neural network; parallel genetic algorithm; stocks scanner evaluator; Economic forecasting; Economic indicators; Error correction; Financial management; Genetic algorithms; Investments; Neural networks; Stability; Stock markets; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Financial Engineering, 2009. CIFEr '09. IEEE Symposium on
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    978-1-4244-2774-1
  • Type

    conf

  • DOI
    10.1109/CIFER.2009.4937499
  • Filename
    4937499