This paper investigates the time-series predictability of commodity futures excess returns from factor models that exploit two risk factors – the equally weighted average excess return on long positions in a universe of futures contracts and the return difference between the high- and low-basis portfolios. Adopting a standard set of statistical evaluation metrics, we find weak evidence that the factor models provide out-of-sample forecasts of monthly excess returns significantly better than the benchmark of random walk with drift model. We also show, in a dynamic asset allocation environment, that the information contained in the commodity-based risk factors does not generate systematic economic value to risk-averse investors pursuing a commodity stand-alone strategy or a diversification strategy.
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