Abstract
This paper develops a new risk efficiency model: Mean-Separated Target Deviations (MSTD). Conventional measures of risk do not distinguish between below-target and above-target outcomes, or else impose risk neutrality for above-target outcomes. The model is motivated by the intuition that although investors are comfortable with expected value as a measure of return, they respond in different ways to potential outcomes below a target return than to potential outcomes above a target return. The measure of risk is a weighted sum of below-target deviations and above-target deviations, and reflects skewness in the return distribution. The investor's risk attitude determines the weights. MSTD is a special case of a von Neumann-Morgenstern expected utility function. With restrictions on parameters, it is a special case of stochastic dominance. Unlike the mean-variance criterion, the MSTD model considers skewness in ranking alternatives. The model is then used to select among alternative means of hedging hard red winter wheat. The additional restrictions of MSTD are successful in producing a smaller efficient set than other criteria.
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