Hedging effectiveness is the proportion of price risk removed through hedging. Empirical
hedging studies typically estimate a set of risk minimizing hedge ratios, estimate the hedging
effectiveness statistic, apply the estimated hedge ratios to a second group of data, and examine
the robustness of the hedging strategy by comparing the hedging effectiveness for this "out-of-sample"
period to the "in-sample" period. This study focuses on the statistical properties of the
in-sample and out-of-sample hedging effectiveness estimators. Through mathematical and
simulation analysis we determine the following: (a) the R2 for the hedge ratio regression will
generally overstate the amount of price risk reduction that can be achieved by hedging, (b) the
properly computed hedging effectiveness in the hedge ratio regression will also generally
overstate the true amount of risk reduction that can be achieved, (c) hedging effectiveness
estimated in the out-of-sample period will generally understate the true amount of risk reduction
that can be achieved, (d) for equal numbers of observations, the overstatement in (b) is less that
the understatement in (c), (e) both errors decline as more observations are used, and (f) the most
accurate approach is to use all of the available data to estimate the hedge ratio and effectiveness
and to not hold any data back for hedge strategy validation. If structural change in the hedge
ratio model is suspected, tests for parameter equality have a better statistical foundation that do
tests of hedging effectiveness equality.

Details

Title
The Relative Performance of In-Sample and Out-of-Sample Hedging Effectiveness Indicators