IDEAS home Printed from
   My bibliography  Save this paper

Genetic Algorithm Optimisation for Finance and Investment


  • Robert Pereira

    () (Department of Economics and Finance, La Trobe University)


This paper provides an introduction to the use of genetic algo- rithms for financial optimisation. The aim is to give the reader a basic understanding of the computational aspects of these algorithms and how they can be applied to decision making in finance and investment. Genetic algorithms are especially suitable for complex problems char- actised by large solution spaces, multiple optima, non differentiability of the objective function, and other irregular features. The mechanics of constructing and using a genetic algorithm for optimisation are illustrated through a simple example.

Suggested Citation

  • Robert Pereira, 2000. "Genetic Algorithm Optimisation for Finance and Investment," Working Papers 2000.02, School of Economics, La Trobe University.
  • Handle: RePEc:ltr:wpaper:2000.02

    Download full text from publisher

    File URL:
    File Function: First version, 2000.02.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    2. Hinich, Melvin J & Patterson, Douglas M, 1985. "Evidence of Nonlinearity in Daily Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(1), pages 69-77, January.
    3. L. Ingber, 1989. "Very fast simulated re-annealing," Lester Ingber Papers 89vf, Lester Ingber.
    4. L. Ingber, 1996. "Statistical mechanics of nonlinear nonequilibrium financial markets: Applications to optimized trading," Lester Ingber Papers 96nf, Lester Ingber.
    5. Dorsey, Robert E & Mayer, Walter J, 1995. "Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 53-66, January.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Slimane Sefiane & Mohamed Benbouziane, 2012. "Portfolio Selection Using Genetic Algorithm," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 2(4), pages 1-9.
    2. Sinha, Pankaj & Chandwani, Abhishek & Sinha, Tanmay, 2013. "Algorithm of construction of Optimum Portfolio of stocks using Genetic Algorithm," MPRA Paper 48204, University Library of Munich, Germany.

    More about this item


    Optimization; Financial Market; Investments EDIRC Provider-Institution: RePEc:edi:smlatau;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G0 - Financial Economics - - General


    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:ltr:wpaper:2000.02. 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: (Stephen Scoglio). 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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.