IDEAS home Printed from
   My bibliography  Save this paper

Optimal Hedging With Views: A Bayesian Approach


  • Shi, Wei
  • Irwin, Scott H.


The optimal hedging model has become the standard theoretical model of normative hedging behavior due to its intuitive tradeoff of expected return with risk, its effcient use of information and its easy implementation. In practice, the model can be easily implemented with the Parameter Certainty Equivalent procedure, which substitutes sample estimates for the true but unknown model parameters. But subjective views, which refer to opinions concerning the directions of market returns of the assets involved in hedging decisions, are either completely ignored or handled in an ad hoc and unsatisfactory manner within the optimal hedging model. Given the widespread use of subjective views in hedging practice and the potential economic benefit of selective hedging, the lack of accommodation of subjective views in the optimal hedging model is a serious problem and could hamper the model's application in risk management practice. With an empirical Bayesian approach adopted, this study proposes an alternative Bayesian optimal hedging model, in which a hedger can adjust his/her optimal hedging position (ratio) according to his/her view(s) on the expected returns of assets under consideration. Like Lence and Hayes' Bayesian optimal hedging model (1994a, 1994b), the optimal hedging position is also determined by mean-variance optimization conditioned on the predictive expectation vector and predictive covariance matrix of asset returns, but unlike their model, the number and type of subjective views that can be expressed is quite flexible because of the adoption of an empirical Bayesian approach. The empirical Bayesian optimal hedging model provides practitioners with a theoretically intuitive yet quantitatively rigorous framework to blend subjective views and the market consensus estimated from sample data according to their relative confidence levels.

Suggested Citation

  • Shi, Wei & Irwin, Scott H., 2004. "Optimal Hedging With Views: A Bayesian Approach," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19009, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:ncrfou:19009

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
    2. Thomas V. Greer & B. Wade Brorsen & Shi-Miin Liu, 1992. "Slippage Costs in Order Execution for a Public Futures Fund," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 14(2), pages 281-288.
    3. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2003. "Forecast evaluation with shared data sets," International Journal of Forecasting, Elsevier, vol. 19(2), pages 217-227.
    4. B. Wade Brorsen, 1989. "Liquidity costs and scalping returns in the corn futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 9(3), pages 225-236, June.
    5. Levich, Richard M. & Thomas, Lee III, 1993. "The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach," Journal of International Money and Finance, Elsevier, vol. 12(5), pages 451-474, October.
    6. Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
    7. LeBaron, Blake, 1999. "Technical trading rule profitability and foreign exchange intervention," Journal of International Economics, Elsevier, vol. 49(1), pages 125-143, October.
    8. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    9. Ferguson, Michael F & Mann, Steven C, 2001. "Execution Costs and Their Intraday Variation in Futures Markets," The Journal of Business, University of Chicago Press, vol. 74(1), pages 125-160, January.
    10. Kidd, Willis V. & Brorsen, B. Wade, 2004. "Why have the returns to technical analysis decreased?," Journal of Economics and Business, Elsevier, vol. 56(3), pages 159-176.
    11. Scott H. Irwin & B. Wade Brorsen, 1985. "Public futures funds," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 5(3), pages 463-485, September.
    12. Leuthold, Raymond M, 1972. "Random Walk and Price Trends: The Live Cattle Futures Market," Journal of Finance, American Finance Association, vol. 27(4), pages 879-889, September.
    13. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    14. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    15. Szakmary, Andrew C. & Mathur, Ike, 1997. "Central bank intervention and trading rule profits in foreign exchange markets," Journal of International Money and Finance, Elsevier, vol. 16(4), pages 513-535, August.
    16. Lukac, Louis P & Brorsen, B Wade, 1990. "A Comprehensive Test of Futures Market Disequilibrium," The Financial Review, Eastern Finance Association, vol. 25(4), pages 593-622, November.
    17. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    18. Dale, Charles & Workman, Rosemarie, 1981. "Measuring patterns of price movements in the Treasury bill futures market," MPRA Paper 48639, University Library of Munich, Germany.
    19. Neftci, Salih N, 1991. "Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis."," The Journal of Business, University of Chicago Press, vol. 64(4), pages 549-571, October.
    20. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance,in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974 Elsevier.
    21. Bong-Chan, Kho, 1996. "Time-varying risk premia, volatility, and technical trading rule profits: Evidence from foreign currency futures markets," Journal of Financial Economics, Elsevier, vol. 41(2), pages 249-290, June.
    22. Thompson, Sarahelen R. & Eales, James S. & Seibold, David, 1993. "Comparison Of Liquidity Costs Between The Kansas City And Chicago Wheat Futures Contracts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(02), December.
    23. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    24. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
    25. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    26. Thompson, Sarahelen R. & Waller, Mark L., 1987. "The Execution Cost of Trading in Commodity Futures Markets," Food Research Institute Studies, Stanford University, Food Research Institute, issue 02.
    27. Olson, Dennis, 2004. "Have trading rule profits in the currency markets declined over time?," Journal of Banking & Finance, Elsevier, vol. 28(1), pages 85-105, January.
    28. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    29. Bhattacharya, Mihir, 1983. "Transactions data tests of efficiency of the Chicago board options exchange," Journal of Financial Economics, Elsevier, vol. 12(2), pages 161-185, August.
    30. Schroeder, Ted C. & Parcell, Joseph L. & Kastens, Terry L. & Dhuyvetter, Kevin C., 1998. "Perceptions Of Marketing Strategies: Producers Versus Extension Economists," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(01), July.
    31. Brorsen, B. Wade & Anderson, Kim B., 1999. "Agricultural Economics Research And Extension Marketing Programs: How Well Are They Integrated?," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 17(2).
    Full references (including those not matched with items on IDEAS)

    More about this item




    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:ags:ncrfou:19009. 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: (AgEcon Search). 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.