THE EMPIRICAL MINIMUM-VARIANCE HEDGE

Decision making under unknown true parameters (estimation risk) is dis cussed along with Bayes' and parameter certainty equivalent (PCE) crit eria. Bayes' criterion incorporates estimation fisk in a manner consis tent with expected utility maximization. The PCE method, which is the most commonly used, is not consistent with expected utility maximizati on. Bayes' criterion is employed to solve for the minimum-variance hed ge ratio. Empirical application of Bayes' minimum-variance hedge ratio is addressed and illustrated. Simulations show that discrepancies bet ween prior and sample parameters may lead to substantial differences b etween Bayesian and PCE minimum-variance hedges.