The predictability of futures returns is investigated using a semiparametric approach where it is assumed that the expected returns depend non parametrically on a combination of predictors. We first collapse the forecasting variables into a single index variable where the weights are identified up to scale, using the average derivative estimator proposed by Stoker (1986). We then use the Nadaraya-Watson kernel estimator to calculate (and visually depict) the relation between the estimated index and the expected futures returns. An application to four agricultural commodity futures illustrates the technique. The results indicate that for each of the commodities considered, the estimated index contains statistically significant information regarding the expected futures returns. Economic implications for a non-infinitely risk averse hedger are also discussed.