As commodities become more mainstream, Iain Morse
wades through the various indices on offer
Commodities have followed hedge funds and private equity into the mainstream – and the asset class is now witnessing a further evolution. An increasing number of fund managers have launched actively managed commodity funds that target relative or absolute returns and claim to be able to generate alpha (higher returns due to a manager’s skill).
However, sceptics argue that the best way to gain commodity exposure is by buying market beta, and that managers cannot generate alpha with any consistency from commodities. PGGM, a Dutch pension scheme, for example, does not try to trade commodities actively.
The issue is
confused by the profusion of commodity indices currently on offer. There are at least seven major ones and each is used to generate families of sub-indices.
There are some well known brands battling for a share of this market: Dow Jones-AIG, S&P (which bought the Goldman Sachs Commodity Index in January this year), Reuters Jeffries CRB, UBS Bloomberg and Deutsche Bank.
There is no authoritative data on the amount of money in commodity futures and swaps, but best estimates are that funds passively replicating the movement of one or more of these indices currently attract around $100bn. Approximately 95% of this total is presently invested in funds replicating either the DJ-AIG or the S&P GSCI of which about one-third is benchmarked to the DJ-AIG and two-thirds to the S&P GSCI.
With so much money behind the two leading indices their construction deserves more detailed examination. The S&P GSCI was the first to be launched in 1991. It seeks to approximate the economic value of the amounts of each major commodity in production. The index weight given to each commodity is therefore determined by the economic value put on them in the real world. Production weighting is defined as the average world production quantities over the past five years. The index has five constituent commodity sectors: energy (75.02% of total as January 2007), industrial metals with 9%, precious metals 2.09%, agriculture at 9.88% and livestock on 4.04%.
Unlike the S&P GSCI, the DJ-AIGCI imposes a priori limits on each commodity sector regardless of
whether their production values exceed these limits; none can exceed 33%. It has the same set of five main commodity sectors but these deconstruct into only 19 sub-sectors. The most obvious difference with the S&P GSCI is that as energy comprises only 33% of the index by value this increases the allocations to the other commodity sectors. Industrial metals account for 18.09% of the index, precious metals for 8.22%, agriculture for no less than 30.24% and livestock for 10.45%. The arguments between these indices are fundamental in character. Proponents of the S&P GSCI argue that its construction and energy weighting optimises the correlation benefits of investing commodities.
The argument behind this is that in an overheated economy, where financial assets begin to underperform,
commodities like oil will outperform. Commodities that make up a smaller share of the index are less likely to outperform relative to energy. The argument in favour of the DJ-AIG or any other capped weight index can only be based on the relative diversification resulting from these caps. “Our index gives more diversified exposure,” argues John Prestbo, managing director at DJ-AIG. “The asset allocation decision is a form of active risk built into the index.”
Over ten years the S&P GSCI shows a negative correlation of -0.01, the DJ-AIG a positive correlation of 0.10. S&P GSCI also argues that the energy sector of its index shows a negative correlation of -0.04 to the S&P 500 against a positive correlation of 0.20 between the non-energy sectors of the index with the S&P 500. There are other differences between each index – for example the S&P GSCI rolls its energy futures every month, while DJ-AIG rolls its energy every other month. These differences
impact on the transaction costs and relative volatility of each index.
The difference in the frequency with which energy contracts are rolled is important. Energy has been in contango for some years. Contango describes a state where the price of a commodity for future delivery is higher than the current price. Both indices, and the S&P GSCI particularly, have been affected by the negative roll yield. The S&P GSCI has incurred high costs because contango implies that when rolling contracts, the new contracts must cost more.
“Nevertheless we tend to prefer the S&P GSCI,” says Alistair Lowe, of State Street Global Advisers. “It is more volatile but has a lower correlation with other asset classes.”
Some of the new commodity indices
are designed to avoid these problems by effectively extending the forward duration of the contracts rolled to avoid contango. They also make capped or fixed allocations to sets of commodities intended to refine the volatility and return characteristics of both the S&P GSCI
and DJ-AIG. A typical example is the Deutsche Bank Liquid Commodity Index-Optimum Yield, which tries to accomplish a wide range of objectives in its construction. It includes only six commodities, including crude oil and corn. Each of these is selected to optimise its low-to-negative correlation with other asset classes. This is a radically different portfolio to the S&P GSCI with far higher weightings to metals and agriculture.
“The design also tries to negate the consequences of contango in the oil market by extending the average duration of energy futures in the index,” says Petra Lottig, managing director with global responsibility for commodity products at Deutsche Bank. This is done by permitting the purchase of futures contracts going out up to 13 months to optimise yield.
Trading for alpha
Needless to say, exposure to this index can be achieved by buying an ETF licensed by Deutsche Bank. The same is true of all the other indices. In addition to ETFs there are some very large passive unitised funds from the likes of PIMCO which accept relatively small investment premiums from institutions. Large pension funds, insurance companies and corporates can also run their own in-house programmes of rolling future contracts or buying swaps via one of the investment banks.
Until a few years ago there was widespread scepticism that commodities could be traded consistently for alpha. Recently there has been a dramatic change of thought on this with managers launching funds which have performance targets based either on a relative or absolute return basis. For instance, the DWS Active Commodity Alpha Fund is a relative return fund using the DJ-AIG CI Excess Return as a benchmark, with a 3.50% outperformance target.
By contrast, the Goldman Sachs Commodity Opportunities Fund has an absolute return target of 1-month LIBOR plus 500 to 800 basis points of alpha.
© fe July 2007