In May, BNP Paribas changed the benchmark of its broad-basket commodity ETF, namely the S&P GSCI Capped Component 35/20 THEAM Easy ETF, for the sole purpose of complying with ESMA diversification guidelines.
The replacement index applies caps on a ‘component’ rather than a ‘commodity’ level, effectively reducing the index’s exposure to the energy sector.
This occurs because an index component such as oil, may include more than one, highly-correlated individual commodity such as Brent Crude, WTI Crude or Gasoil. Therefore a cap at component level restricts the combined weight, rather than individual weights, of commodities. Although this difference may appear subtle, the impact on returns to investors is anything but, as you can see in Chart 1.
For example, over 2013 the new index returned -7.4%, a much bigger loss than -1.3% for the old one. This dramatic difference is explained solely by a difference in index weightings, with the former allocating around 30% less of index weight to the energy sector.
The S&P GSCI Capped Component 35/20 THEAM Easy ETF serves as a prime example of how divergently even seemingly similar indices can perform.
More generally, there are two main types of differences between commodity indices: those concerning the index composition and those covering the treatment of futures within the index. In this article, I will focus on the former and compare the make-up of some of the most popular broad-basket commodity indices tracked by ETFs in Europe.
Unlike equity indices, commodity benchmarks don’t have an accepted ‘capital weighted’ market standard. The first launched investable commodity futures indices like the S&P GSCI Index are weighted based entirely on production figures, i.e. the average quantity of global production as per the last five years of available data. The issue with this approach is that it tends to heavily bias the energy sector, which accounts, for instance, for almost three quarters of the S&P GSCI Index.
To correct this sort of bias, more modern indices employ an array of constraints, including sector and single commodity caps and fixed-weight groupings. They also take into account additional factors such as liquidity and economic importance when selecting constituents.
Because weighting differences are likely to have the largest impact on returns, investors are urged to understand the weighting methodology of their chosen index and ensure its composition suits their needs. The differences between the major commodity indices are outlined in Table 1 and Chart 2.
The breadth of an index – the number and heterogeneity of its constituents – varies significantly between indices. Some index providers have even excluded certain commodity sectors from their indices altogether. As we can see from Chart 2, Deutsche Bank has excluded livestock from its DBLCI O– Y Balanced index for liquidity reasons.
In line with financial theory, the broader an index, the higher the potential diversification benefits. This is especially true of commodity indices as individual commodities tend to be comparatively volatile and exhibit low correlations with one another.
There is however a trade-off between the marginal benefits gained by adding another commodity and the cost of maintaining small levels of exposure to commodities whose futures may be less liquid. For this reason, the major indices tend to offer exposure to between 14 and 24 different commodities.
Investors should also be aware that rebalancing frequency, that is, how often the exposure to sectors or single commodities is reset to target, can also impact the performance of one index versus another.
All else held equal, investors will prefer those indices that rebalance more frequently and therefore deviate less from their assigned weights. Unfortunately, increasing rebalancing frequency also raises transactions costs, so an acceptable compromise must be found. With reference to Table 1, we can observe that the major indices rebalance on a frequency between monthly and annually.
