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A Bayesian Implementation of the Standard Optimal Hedging Model: Parameter Estimation Risk and Subjective Views

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  • Shi, Wei
  • Irwin, Scott H.

Abstract

We develop a Bayesian implementation of the standard optimal hedging model to analyze the impact of hedgers' subjective views on their hedging behavior. The results show the subjective views have a substantial impact on hedgers' optimal positions, explaining the large cross-sectional and time series variation of hedging positions in practice.

Suggested Citation

  • 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).
    • Handle: RePEc:ags:aaea05:19155
    DOI: 10.22004/ag.econ.19155
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    References listed on IDEAS

    as
    1. Anderson, Ronald W & Danthine, Jean-Pierre, 1980. "Hedging and Joint Production: Theory and Illustrations," Journal of Finance, American Finance Association, vol. 35(2), pages 487-498, May.
    2. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    3. Frost, Peter A. & Savarino, James E., 1986. "An Empirical Bayes Approach to Efficient Portfolio Selection," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(3), pages 293-305, September.
    4. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    5. Jorion, Philippe, 1986. "Bayes-Stein Estimation for Portfolio Analysis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(3), pages 279-292, September.
    6. Leland L. Johnson, 1960. "The Theory of Hedging and Speculation in Commodity Futures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 27(3), pages 139-151.
    7. Lence, Sergio H & Hayes, Dermot J, 1994. "Parameter-Based Decision Making under Estimation Risk: An Application to Futures Trading," Journal of Finance, American Finance Association, vol. 49(1), pages 345-357, March.
    8. Ľuboš Pástor, 2000. "Portfolio Selection and Asset Pricing Models," Journal of Finance, American Finance Association, vol. 55(1), pages 179-223, February.
    9. Sergio H. Lence & Dermot J. Hayes, 1994. "The Empirical Minimum-Variance Hedge," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 94-104.
    10. 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.
    11. Robert J. Myers & Stanley R. Thompson, 1989. "Generalized Optimal Hedge Ratio Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 858-868.
    12. Polson, Nicholas G & Tew, Bernard V, 2000. "Bayesian Portfolio Selection: An Empirical Analysis of the S&P 500 Index 1970-1996," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 164-173, April.
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