IDEAS home Printed from
   My bibliography  Save this paper

Genetic Algorithms and Trading Strategies: New Evidences from Financially Interesting Time Series


  • Chueh-Inong Taso

    () (National Chengchi University)


In this paper, the performance of canonical GA-based trading strategies are evaluated under different time series. The time series considered include a variety of financial time series, ranging from linear and nonlinear stationary time series to chaotic time series. Unlike many existing applications of computational intelligence in financial engineering, for each performance criterion, we provide rigourous asymptotic statistical tests based on a Monte Carlo simulation. In addition, the criteria chosen are much more extensive than in the existing literature. These include the profit ratio, risk, the Sharpe ratio, maximum drawdown, and the luck coefficient. As a result, this study provides a thorough understanding of the effectiveness of canonical GAs for generating trading strategies under different financial time series.

Suggested Citation

  • Chueh-Inong Taso, 1999. "Genetic Algorithms and Trading Strategies: New Evidences from Financially Interesting Time Series," Computing in Economics and Finance 1999 552, Society for Computational Economics.
  • Handle: RePEc:sce:scecf9:552

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sce:scecf9:552. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.