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Risk aversion is a key element of utility maximizing hedge strategies;however, it has typically been assigned an arbitrary value in the literature.This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate atime-varying measure of risk aversion that is based on the observed riskpreferences of energy hedging market participants. The resulting estimates areapplied to derive explicit risk aversion based optimal hedge strategies forboth short and long hedgers. Out-of-sample results are also presented based ona unique approach that allows us to forecast risk aversion, thereby estimatinghedge strategies that address the potential future needs of energy hedgers. Wefind that the risk aversion based hedges differ significantly from simpler OLShedges. When implemented in-sample, risk aversion hedges for short hedgersoutperform the OLS hedge ratio in a utility based comparison.

Time Varying Risk Aversion: An Application to Energy Hedging