24 Jan 2024 4 min read

The evolution of commodity investing: the power of marginal gains

By Tobias Merfeld , Michael Stewart

Second-generation broad commodity indices aim to maintain the underlying characteristics of their predecessors while extracting greater value from futures markets. Here's how they work.


At the 2004 Summer Olympics the UK won two cycling gold medals, the country’s best performance since 1908. This marked the start of a decade of remarkable success in British cycling, guided by the philosophy of ‘marginal gains’.

British Cycling Performance Director Dave Brailsford described it as follows: “The whole principle came from the idea that if you broke down everything you could think of that goes into riding a bike, and then improved it by 1%, you will get a significant increase when you put them all together.”1

In part one of this blog we covered the development of the first generation of broad commodity indices, and showed how mechanically rolling into the earliest available month of the futures curve acted as a drag on returns over the past decade. At around the same as the renaissance of British cycling, a new generation of commodity indices would find inspiration from the concept of marginal gains.

Longer-dated commodity indices

Building on academic research2 finding first-generation commodity indices could be expected to suffer negative roll yield when the futures curve is in contango, the search began for potential optimisations.

An obvious place to start was shifting the futures contracts from the front or second month (the front of the curve) to longer-dated months.

Historically, broad commodity indices investing in futures with expiry dates marginally further into the future than those found in the first-generation indices have increased stability and a better risk-adjusted return over over the long term.


A new generation arrives

Second-generation indices aim to break down the commodities conundrum into smaller parts to optimise the potential return at each stage. Building on standard indices, there are a number of potential enhancements that can be applied in order to seek improved long-term risk/return characteristics.

In standard indices, the weighting of constituents such as grains, crude oil or soybeans is typically determined by global production volumes and the liquidity of futures markets and is fixed annually and then allowed to drift.

By contrast, enhanced commodity indices may choose to tilt their weighting to overweight those commodities showing the highest level of backwardation, aiming to extract additional value from the shape of the futures curve.

Changing with the seasons

Another strategy that could be employed by the new generation of commodity indices is to use the seasonality of certain energy commodities such as natural gas, gasoil and heating oil to select the optimal point of the futures curve, based on historical trends.

Although there is no guarantee that the futures curve for any particular commodity in any particular year will match that seen in prior years, the underlying supply and demand drivers of cold weather during winter months and warmer weather in summer act as structural drivers for these commodities.

For agriculture and livestock, a strategy may aim to dynamically allocate to parts of the futures curve that have historically outperformed. Again, this does not guarantee additional returns, but the long history of commodity markets provides a rich seam of historical data on which to base assumptions.

Interestingly, certain commodities have proved resistant to optimisations. Markets for precious metals, for instance, are typically highly efficient, so modern commodity indices will often adopt a beta strategy here.

The road ahead

Academic research3 has found that the ability of newer broad commodity indices to select futures contracts from different parts of the curve can potentially lead to improved performance without diluting the inflation-hedging and diversification4 properties of the asset class.

Of course, this doesn’t mean the end of the commodities story. As the volume of commodities data and our ability to process this data grows every year, the search for additional enhancements continues.


1. Source: Olympics cycling: Marginal gains underpin Team GB dominance - BBC Sport

2. Source: Daal, E., Farhat, J. & Wei, P., 2006. Does futures exhibit maturity effect? New evidence from an extensive set of US and foreign futures contracts. Review of Financial Economics, 15, pages 113-128

3. Source: Rallis, G., Miffre, J. & Fuertes, A.-M., 2010. Strategic and Tactical Roles of Enhanced-Commodity Indices (February 1, 2012). Journal of Futures Markets 33(10), pages 965-992.

4. It should be noted that diversification is no guarantee against a loss in a declining market.

Tobias Merfeld

Senior ETF Investment Strategist

Tobias joined LGIM as an ETF Investment Strategist in 2019.

Tobias Merfeld

Michael Stewart

Head of Pooled Index Strategy

Michael focuses on the creation and ongoing support of investment strategies for LGIM's ETFs as well as the strategic role for ETFs within the business. Before joining us in 2019, Michael worked in ETF product development at Invesco, developing and supporting a wide range of ETFs across all asset classes. He holds an MBA from Bayes Business School (formerly Cass), University of London, and is a CFA Charterholder. When he’s not studying investment strategies, Michael likes running, vegan cooking and European train travel. 

Michael Stewart