Testing the martingale hypothesis for futures prices: Implications for hedgers

The martingale hypothesis for futures prices is investigated using a nonparametric approach where it is assumed that the expected futures returns depend (nonparametrically) on a linear combination of predictors. We first collapse the predictors into a single-index variable where the weights are identified up to scale, using the average derivative estimator proposed by T. Stoker (1986). We then use the Nadaraya-Watson kernel estimator to calculate (and visually depict) the relationship between the estimated index and the expected futures returns. An application to four agricultural commodity futures illustrates the technique. Out-of-sample results indicate that for soybeans, wheat, and oats, the estimated index contains statistically significant information regarding the expected futures returns. We discuss implications of this finding for a noninfinitely risk-averse hedger. (C) 2008 Wiley Periodicals, Inc.