More on commodity returns and macro drivers - Use the forward curve

 

The paper "Commodity Return Predictability" combines the basis and forward curve with macro variables to make effective predictions on commodity returns.  We know that when commodity markets are in strong backwardation or contango the future prices have important information that can be exploited. If the commodity curve is inverted, in backwardation, current prices are higher than future prices and the curve suggests there is strong commodity demand. On the other hand, if the market is in contango, current prices are lower than future prices and there is likely less current demand. This current demand is also related to the business cycle and suggests that commodity price moves are pro-cyclical. 

The author of this paper shows that combining the shape of the forward curve along with macro information can be effectively used to explain commodity returns both in-sample and out-of-sample. It is not enough to just look at the basis over one month, rather it is more valuable to look at the whole futures curve and account for the level, slope and curvature of this forward curve just like the yield curve. A close look at the data will find that the curvature of the forward curve provides strong added information. Forward factor regressions have been used to show that the shape of the yield curve can be used to predict bond returns, so the same methodology can be applied to commodity forward curves, and it also is effective. The key is looking at the longer-dated basis and not just the nearby futures. 

Additionally, the shape of the curve and the basis is related to the business cycle, so factors that account for the business cycle like, industrial production, the composite leading indicators, business confidence, and trade will also have an impact on commodity returns. What is very interesting is that the out-of-sample forecasts with macro variables alone are not very effective. 

Finally, the author tests some other variables known to have some predictive power from past tests and finds the growth in open interest is also a useful predictor. If the futures are being used to hold position exposure, it is a sign that returns are moving higher. 

The combination of endogenous information embedded in the yield curve along with exogenous macro information, especially in the case of composite leading indicators, will be a useful for making commodity return forecasts. Nevertheless, there is a concern that the majority of the forecasting gains are associated with the super-cycle extremes of 2008. The gains during other periods are more modest.