Volume 15 | Issue 2 | Article 1
Next Article >>
Back To: Table of Contents
Generalized Hedge Ratio Estimates with an Unknown Model
Myers and Thompson (1989) pioneered the concept of a generalized approach to estimating hedge ratios, pointing out that the model specification could have a large impact on the hedge ratio estimated. While a huge empirical literature exists on estimating hedge ratios, the literature is lacking a formal treatment of model specification uncertainty. This research accomplishes that task by taking a Bayesian approach to hedge ratio estimation, where specification uncertainty is explicitly modeled. Specifically, we present a Bayesian approach to hedge ratio estimation that integrates over model specification uncertainty. It yields a hedge ratio estimator that is robust to possible model specification because it is an average across a set of hedge ratios conditional on different models. Model specifications vary by exogenous variables (such as exports, stocks, and interest rates) and lag lengths included. The method is applied to data on hedging of corn and soybeans and on cross-hedging of corn oil using soybean oil futures. Results show the potential benefits and insights gained from such an approach.
