IDEAS home Printed from
   My bibliography  Save this article

A New Genetic Algorithm To Solve Knapsack Problems


  • Derya TURFAN

    () (Hacettepe University, Faculty of Science, Department of Statistics, Ankara, Turkey)

  • Cagdas Hakan ALADAG

    () (Hacettepe University, Faculty of Science, Department of Statistics, Ankara, Turkey)

  • Ozgur YENIAY

    () (Hacettepe University, Faculty of Science, Department of Statistics, Ankara, Turkey)


The volatility of currency exchange rates can be considered as an useful measure of uncertainty about the economic environment of a country.The paper aims to investigate the evolution of the daily RON/EURO exchange rate between January 5th, 2009 and October 12, 2012. Several appropriate models are used and discussed, from ARCH, GARCH models to EGARCH and TGARCH models, trying to capture the main features of the analysed data. The periods of low and high volatility are discussed and analysed in correlation to the negative and positive shocks. The used models are able to model asymmetries in volatility forecasts allowing for asymmetric responses in volatility to the positive and negative shocks.

Suggested Citation

  • Derya TURFAN & Cagdas Hakan ALADAG & Ozgur YENIAY, 2012. "A New Genetic Algorithm To Solve Knapsack Problems," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 1(2), pages 40-47, DECEMBER.
  • Handle: RePEc:aes:jsesro:v:1:y:2012:i:2:p:40-47

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Genetic algorithms; Mean-variance optimization; Portfolio analysis; knapsack problem;

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions


    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:aes:jsesro:v:1:y:2012:i:2:p:40-47. 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: (Bogdan-Vasile Ileanu). 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.