IDEAS home Printed from
   My bibliography  Save this paper

Nonstationary Optimization Approach for Finding Universal Portfolios


  • Gaivoronski, A
  • Stella, F


The definition of universal portfolio was introduced in the nancial literature in order to describe the class of portfolios which are constructed directly from the available observations of the stocks behavior without any assumptions about their statistical properties. Cover has shown that one can construct such portfolio using only observations of the past stock prices which generates the same asymptotic wealth growth as the best constant rebalanced portfolio which is constructed with the full knowledge of the future stock market behavior. In this paper we construct universal portfolios using totally different set of ideas drawn from nonstationary stochastic optimization. Also our portfolios yield the same asymptotic growth of wealth as the best constant rebalanced portfolio constructed with the perfect knowledge of the future, but they are less demanding computationally. Besides theoretical study, we present computational evidence using data from New York Stock Exchange which shows, among other things, superior performance of portfolios which explicitly take into account possible nonstationary market behavior.

Suggested Citation

  • Gaivoronski, A & Stella, F, 2000. "Nonstationary Optimization Approach for Finding Universal Portfolios," MPRA Paper 21913, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:21913

    Download full text from publisher

    File URL:
    File Function: original version
    Download Restriction: no

    References listed on IDEAS

    1. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
    2. John M. Mulvey & Hercules Vladimirou, 1992. "Stochastic Network Programming for Financial Planning Problems," Management Science, INFORMS, vol. 38(11), pages 1642-1664, November.
    3. Farshid Jamshidian, 1992. "Asymptotically Optimal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 2(2), pages 131-150.
    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. Fabio Stella & Alfonso Ventura, 2011. "Defensive online portfolio selection," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 2(1/2), pages 88-105.
    2. Sjur Flåm, 2010. "Portfolio management without probabilities or statistics," Annals of Finance, Springer, vol. 6(3), pages 357-368, July.
    3. repec:kap:compec:v:50:y:2017:i:1:d:10.1007_s10614-016-9585-0 is not listed on IDEAS
    4. Bin Li & Steven C. H. Hoi, 2012. "On-Line Portfolio Selection with Moving Average Reversion," Papers 1206.4626,
    5. Bin Li & Steven C. H. Hoi, 2012. "Online Portfolio Selection: A Survey," Papers 1212.2129,, revised May 2013.
    6. James DiLellio, 2015. "A Kalman filter control technique in mean-variance portfolio management," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(2), pages 235-261, April.

    More about this item


    universal portfolios; constant rebalanced portfolios; portfolio selection;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • 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:pra:mprapa:21913. 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: (Joachim Winter) or (Rebekah McClure). 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.