IDEAS home Printed from https://ideas.repec.org/p/isu/genres/693.html
   My bibliography  Save this paper

Parameter-Based Decision Making Under Estimation Risk: An Application to Futures Trading

Author

Listed:
  • Lence, Sergio H.
  • Hayes, Dermot J.

Abstract

This study shows how the standard portfolio model of futures trading should be modified when there is less than perfect information about the relevant parameters (estimation risk). The standard and the optimal decision rules for futures trading in the presence of estimation risk are compared and discussed. An operational model of futures trading for use under estimation risk is advanced. In the presence of relevant prior and sample information, the model can be used to optimally blend both types of information. Copyright 1994 by American Finance Association.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Lence, Sergio H. & Hayes, Dermot J., 1994. "Parameter-Based Decision Making Under Estimation Risk: An Application to Futures Trading," Staff General Research Papers Archive 693, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:693
    as

    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.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Shi, Wei & Irwin, Scott H., 2005. "A Bayesian Implementation of the Standard Optimal Hedging Model: Parameter Estimation Risk and Subjective Views," 2005 Annual meeting, July 24-27, Providence, RI 19155, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Wang, Xuecai & Dorfman, Jeffrey H. & McKissick, John & Turner, Steven C., 2001. "Optimal Marketing Decisions for Feeder Cattle under Price and Production Risk," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 33(3), pages 431-443, December.
    3. Power, Gabriel J. & Vedenov, Dmitry V., 2008. "The Shape of the Optimal Hedge Ratio: Modeling Joint Spot-Futures Prices using an Empirical Copula-GARCH Model," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37609, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    4. Raphael Markellos & Terence Mills, 2003. "Asset pricing dynamics," The European Journal of Finance, Taylor & Francis Journals, vol. 9(6), pages 533-556.
    5. David J. Pannell & Getu Hailu & Alfons Weersink & Amanda Burt, 2008. "More reasons why farmers have so little interest in futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 39(1), pages 41-50, July.
    6. Rahman, Shaikh Mahfuzur & Dorfman, Jeffrey H. & Turner, Steven C., 2004. "A Bayesian Approach to Optimal Cross-Hedging of Cottonseed Products Using Soybean Complex Futures," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(2), pages 1-16, August.
    7. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    8. Zhenyu Cui & Majeed Simaan, 2021. "The opportunity cost of hedging under incomplete information: Evidence from ETF/Ns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1775-1796, November.
    9. Hiroyuki Kashima, 2005. "An application of a minimax Bayes rule and shrinkage estimators to the portofolio selection problem under the Bayesian approach," Statistical Papers, Springer, vol. 46(4), pages 523-540, October.
    10. Lence, Sergio H. & Hayes, Dermot J., 1995. "Land Allocation In The Presence Of Estimation Risk," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 20(1), pages 1-15, July.
    11. Bessler, Wolfgang & Leonhardt, Alexander & Wolff, Dominik, 2016. "Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 239-256.
    12. Wei Shi & Scott H. Irwin, 2005. "Optimal Hedging with a Subjective View: An Empirical Bayesian Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 918-930.
    13. Marcos Escobar & Sven Panz, 2016. "A Note on the Impact of Parameter Uncertainty on Barrier Derivatives," Risks, MDPI, vol. 4(4), pages 1-25, September.

    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:isu:genres:693. 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: Curtis Balmer (email available below). General contact details of provider: https://edirc.repec.org/data/deiasus.html .

    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.