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Optimal Hedging with a Subjective View: An Empirical Bayesian Approach

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  • Wei Shi
  • Scott H. Irwin

Abstract

The standard optimal hedging model has been the preferred theoretical model of normative hedging behavior. In empirical applications, the model is often implemented with the parameter certainty equivalent (PCE) procedure. However, the PCE procedure completely ignores parameter estimation risk and subjective views. We develop an “empirical” Bayesian optimal hedging model that not only effectively accommodates parameter estimation risk, but also provides hedgers with a theoretically intuitive yet quantitatively rigorous framework to blend their subjective views and a “marketwide” or “firmwide” consensus in determining optimal hedging positions (ratios). Copyright 2005, Oxford University Press.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:ajagec:v:87:y:2005:i:4:p:918-930
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2005.00778.x
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    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. 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.
    3. 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.
    4. Giulio Palomba, 2008. "Multivariate GARCH models and the Black-Litterman approach for tracking error constrained portfolios: an empirical analysis," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 10(4), pages 379-413.

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