IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v85y1999i0p193-22510.1023-a1018969727211.html
   My bibliography  Save this article

Growth versus security tradeoffs indynamic investment analysis

Author

Listed:
  • Leonard MacLean
  • William Ziemba

Abstract

This paper presents an approach to the problem of optimal dynamic choice in discrete orcontinuous time where there is a direct tradeoff of growth versus security. In each period,the investor must allocate the available resources among various risky assets. The maximizationof the expected logarithm of the period‐by‐period wealth, called the capital growthor the Kelly criterion, has many desirable properties such as maximizing the asymptoticrate of asset growth. However, this strategy has low risk aversion and typically has verylarge wagers which yield high variance of wealth. With uncertain parameters, this can leadto overbetting and loss of wealth. Using fractional Kelly strategies leads to a less volatileand safer sequence of wealth levels with less growth. The investor can choose a desirabletradeoff of growth and security appropriate for the problem under consideration. Thisapproach yields simple two‐dimensional graphs analogous to static mean variance analysisthat capture the essence of the dynamic problem in a form useful for sound investmentanalysis. Use of the approach in practice is illustrated on favorable investments in blackjack,horse racing, lotto games, index and commodity futures and options trading. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • Leonard MacLean & William Ziemba, 1999. "Growth versus security tradeoffs indynamic investment analysis," Annals of Operations Research, Springer, vol. 85(0), pages 193-225, January.
  • Handle: RePEc:spr:annopr:v:85:y:1999:i:0:p:193-225:10.1023/a:1018969727211
    DOI: 10.1023/A:1018969727211
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018969727211
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1018969727211?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Grant, Andrew & Johnstone, David, 2010. "Finding profitable forecast combinations using probability scoring rules," International Journal of Forecasting, Elsevier, vol. 26(3), pages 498-510, July.
    2. Rose D. Baker & Ian G. McHale, 2013. "Optimal Betting Under Parameter Uncertainty: Improving the Kelly Criterion," Decision Analysis, INFORMS, vol. 10(3), pages 189-199, September.
    3. David J Johnstone, 2023. "Capital budgeting and Kelly betting," Australian Journal of Management, Australian School of Business, vol. 48(3), pages 625-651, August.
    4. G. Bottazzi & D. Giachini, 2019. "Far from the madding crowd: collective wisdom in prediction markets," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1461-1471, September.
    5. Tiago P. Filomena & Miguel A. Lejeune, 2014. "Warm-Start Heuristic for Stochastic Portfolio Optimization with Fixed and Proportional Transaction Costs," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 308-329, April.
    6. Bin Li & Steven C. H. Hoi, 2012. "Online Portfolio Selection: A Survey," Papers 1212.2129, arXiv.org, revised May 2013.
    7. David J. Johnstone, 2007. "The Parimutuel Kelly Probability Scoring Rule," Decision Analysis, INFORMS, vol. 4(2), pages 66-75, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:spr:annopr:v:85:y:1999:i:0:p:193-225:10.1023/a:1018969727211. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.