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The Empirical Minimum‐Variance Hedge
Author(s) -
Lence Sergio H.,
Hayes Dermot J.
Publication year - 1994
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1243924
Subject(s) - bayes' theorem , minimum variance unbiased estimator , variance (accounting) , hedge , econometrics , maximization , bayesian probability , statistics , mathematics , bayes estimator , economics , mathematical optimization , mean squared error , ecology , accounting , biology
Decision making under unknown true parameters (estimation risk) is discussed along with Bayes' and parameter certainty equivalent (PCE) criteria. Bayes' criterion incorporates estimation risk in a manner consistent with expected utility maximization. The PCE method, which is the most commonly used, is not consistent with expected utility maximization. Bayes' criterion is employed to solve for the minimum‐variance hedge ratio. Empirical application of Bayes' minimum‐variance hedge ratio is addressed and illustrated. Simulations show that discrepancies between prior and sample parameters may lead to substantial differences between Bayesian and PCE minimum‐variance hedges.