Edhec has constructed a long/short commodity strategy capturing the risk premium in commodity futures markets and that can be used to design a third generation commodity index.

There are many reasons why commodity indexes are useful tools for strategic asset allocation. First, their risk-return trade-off has been shown to be comparable to that of equity indexes (Erb and Harvey, 2006; Gordon and ­Rouwenhorst, 2006).

Second, they have low return correlation with traditional asset classes and so are useful tools for risk diversification (Erb and Harvey, 2006; Gordon and Rouwenhorst, 2006).

Third, unlike stocks and bonds, commodity prices rise in inflationary periods, making commodity indexes natural hedges against inflation (Bodie and Rosansky, 1980; Bodie, 1983).

Fourth, unlike commodity trading advisers (CTAs), commodity indexes are completely transparent, cheap to trade and liquid (at least when nearby contracts are traded).

This can explain why commodities have now turned into an asset class per se with an estimated $174 billion of assets under management (AUM) in indexes as of 2009 (Stoll and Whaley, 2010). At present the first-generation indexes (for example, S&P-GSCI, DJ-UBSCI) still dominate commodity markets.

These are fully collateralised futures investments that provide passive long-only exposure to commodities. They typically rebalance infrequently, hold contract at the front end of the term structure of commodity prices and fail to recognise the natural propensity of commodity futures contracts to be either in backwardation or in contango.

Generational innovation
In an attempt to remedy these grievances, second and third-generation commodity indexes have recently been introduced. These indexes have in common that they attempt to outperform their first-generation counterparts by exploiting momentum or term structure signals and by trading contracts in the mid to far end of the price curve1. The main difference between the two comes from the index providers’ mandate: long-only in the case of second-generation indexes; long/short in the case of third-generation indexes.

Research at Edhec-Risk Institute on commodity investing shows that first and second-generation indexes are sub­optimal. Due to their long-only nature, they fail to recognise the full potential of backwardation and contango. Backwardation occurs when commodity producers are more prone to hedge than commodity consumers. Their net short positions in commodity futures markets create an imbalance between supply and demand that is restored by the intervention of net long speculators.

Speculators will only go long if the futures price is expected to rise as maturity approaches. The opposite happens in a contangoed market: commodity consumers outnumber commodity producers, leading to an excess demand for hedging and thus to the essential intervention of short speculators.

Speculators will go short if the futures price is expected to fall with maturity. It follows from the fundamentals of commodity futures pricing that in order to earn a positive risk premium investors should take long positions in backwardated markets and short positions in contangoed markets.

In two recent papers (Basu and Miffre, 2011; Miffre, 2011), we design a long/short commodity strategy that captures the risk premium present in commodity futures markets and that can be used to design a new third-generation commodity index.

Our approach explicitly takes into account the demand for hedging of commodity producers and consumers by buying backwardated futures (when hedgers are net short and speculators are net long) and shorting contangoed futures (when hedgers are net long and speculators are net short).

The dataset spans the period October 2, 1992 to March 25, 2011 and includes Friday settlement prices on 27 commodity futures. The frequency, time series and cross-section are chosen based on the availability of positions of commercial traders (also often termed ‘hedgers’) and non-commercial traders (also often referred to as ‘speculators’) in the Commodity Futures Trading Commission (CFTC) commitment of traders report.

These positions are essential to calculating two measures, called hedging pressure, one for hedgers and one for speculators. The hedging pressure of, say, speculators is calculated as the number of long positions divided by the total number of positions taken by large non-commercial traders over the ­previous week.

Similarly, the hedging pressure of hedgers is defined as the number of long positions divided by the total number of positions taken by large commercial traders over the ­previous week.

For example, a hedging pressure of 0.2 for hedgers means that over the previous week 20% of hedgers were long and thus 80% were short, a sign of a backwardated market. Vice versa, a hedging pressure of 0.2 for speculators means that over the previous week 20% of speculators were long and thus 80% were short, a sign of a contango market.

Capturing the risk premium
To capture the risk premium present in commodity futures markets, we use a double-sort strategy that combines the positions of hedgers and speculators as follows. The available cross section is first split using the 50% breakpoint into a backwardated portfolio (called LowHedg) and a contangoed portfolio (called HighHedg) based on the mean hedging pressure of hedgers over the previous R weeks.

LowHedg is presumably made of backwardated commodities whose prices are expected to appreciate and HighHedg is presumably made of contangoed commodities whose prices are expected to depreciate.

We then combine the positions of hedgers with those of speculators by buying the 30% of LowHedg for which speculators have high hedging pressure and selling the 30% of HighHedg for which speculators have low hedging pressure over the previous R weeks. The double-sort portfolio holds the long/short positions over the next H weeks.

The ranking period (R) over which hedging pressure is averaged and the holding period (H) over which the long/short portfolios are held are set to either four, 13, 26 or 52 weeks. So we end up with 16 long, 16 short and 16 long/short portfolios, where these 16 series come from the permutation of 4 ranking and 4 holding periods. In line with, among others, Erb and Harvey (2006) or Miffre and Rallis (2007), the constituents of the long and short portfolios are equally weighted.

Our long/short commodity indexes are fully collateralised. This means that half of the trading capital is invested in risk-free interest-bearing accounts for the long portfolios and likewise for the short portfolios. Investors therefore earn half of the returns of the longs and half of the returns of the shorts.

To ease presentation the performance measures presented are based on excess returns. Should the risk-free rate be proxied by the three-month US Treasury bill rate, the mean return of the collateral over the period considered stands at 3.25%. Assuming no margin calls, the performance of the unlevered portfolios reported hereafter is understated by that amount.

Table 1, Panel A reports summary statistics for the excess returns of the unlevered long, short and long/short commodity portfolios based on the hedging pressure of, first, hedgers and, second, speculators.

Table 1, Panel B presents similar information for two long-only indexes: the S&P-GSCI and a long-only equally-weighted portfolio that includes all commodities.

Altogether the results highlight the importance of taking a long/short approach to commodity investing. The superiority of our hedging pressure-based approach is reflected in Sharpe ratios that range from 0.2539 to 0.7883 and far exceed those of long-only benchmarks (0.1965 for the S&P-GSCI and 0.0529 for the long-only equally weighted portfolio).

Because of their failure to acknowledge the natural propensity of commodity futures to switch between contango and backwardation, long-only commodity portfolios (like all first and second-generation indexes) are inadequate at capturing the risk premium present in commodity futures markets.

Passive vs active
So far the Edhec analysis focuses on the positions of commercial (hedgers) and non-commercial (speculators) market participants as reported in the Commitment of Traders (COT) report. We treat as ‘hedgers’ both pure hedgers (producers, processors, merchants and users of the physical commodity) and swap dealers.

Similarly, we treat ‘speculators’ as both pure speculators (professional money managers such as CTAs, CPOs and hedge funds) and other non-commercial traders not classified as professional money managers (for example, pension funds, long-only indexers).

Strictly speaking, swap dealers are not pure hedgers since they do not have a position in the underlying commodity, while pension funds are not pure Keynesian speculators since they merely seek passive exposure to commodities as part of their strategic asset allocation.

Bearing these distinctions in mind, we reiterate our analysis using as signals the hedging pressure of pure hedgers and pure speculators (professional money managers). These disaggregated data are only available since June 2006, restricting accordingly our dataset.

The evidence is reported in Table 2 for the disaggregated and aggregated COT reports over the sample July 14, 2006 to March 25, 2011. The results highlight the importance of taking long as well as short positions in commodity futures markets.

Over this shorter sample, the Sharpe ratios of the long/short portfolios systematically and substantially exceed those of long-only portfolios, which happen to be negative and as low as negative 0.1484 in the case of the S&P-GSCI. The best performance is achieved using the disaggregated COT report and when the ranking period is set to 52 weeks and the holding period to 13 weeks. The Sharpe ratio then equals 1.3150. The mean excess return stands at 15.77% significant at the 1% level, which compares favourably to the negative (albeit insignificant) mean excess returns of long-only benchmarks.

The strategic decision to invest into commodities depends on the risk-return trade-off that commodities offer, as captured by the hedging pressure-based time-varying risk premium presented in Tables 1 and 2. That decision also breaks down to the risk diversification and inflation hedging properties of ­commodities.

Figures 1 and 2 report correlations between the total returns of long/short hedging pressure-based portfolios and those of two traditional asset classes (Barclays Capital US Aggregate Bond Index and S&P 500 Composite Index).

Figure 3 reports the correlations between unexpected inflation and the total returns of either long/short or long-only commodity indexes. The idea is to test whether the hedging pressure-based risk premiums serve as better tools for risk diversification and inflation hedging than long-only commodity portfolios (such an equally-weighted portfolio of all commodities or the S&P‑GSCI).

According to Figure 1 the correlations between bond and long-only commodity futures returns, albeit a bit lower at an average of negative 4.74%, are of similar magnitude to those measured relative to long/short commodity indexes (at minus 0.47% on average).

Figure 2 shows that the correlations between the S&P 500 index and long/short commodity portfolios (at minus 2% on average) are much lower than those measured relative to long-only commodity indexes (at 23.7% on average). Altogether this shows that, while both types of commodity indexes act as good diversifiers to fixed income risk, the diversification benefits of including commodity futures in an equity portfolio are stronger if we take a long/short approach to commodity investing than if we are long-only.

When it comes to inflation hedging, however, long-only commodity indexes present a clear advantage relative to their long/short counterparts.

Figure 3 indeed shows that the correlations between the hedging pressure-based risk premiums and unexpected inflation average out at negative 6.2%, while the correlation between the long-only benchmarks and unexpected inflation exceed 26%. This suggests the incremental performance and the added diversification benefits of hedging pressure-based indexes come at the cost of losing the inflation hedge that is naturally provided by commodities.

This article was written by Joëlle Miffre, professor of finance, Edhec Business School and member of Edhec-Risk Institute.

Footnote
1 An increasing literature documents that commodity futures contracts can be traded actively to generate abnormal performance. Signals such as momentum (Erb and Harvey, 2006; Miffre and Rallis, 2007; Szakmary, Shen and Sharma, 2010), term structure (Erb and Harvey, 2006; Gorton and Rouwenhorst, 2006; Mouakhar and Roberge, 2010) used in isolation or in conjunction (Fuertes, Miffre and Rallis, 2010) materialize in sizeable alphas. Likewise, speculators and hedgers positions and inventory levels can be used as tactical signals to model the time-varying risk premium that agents demand for investing into commodity futures markets (Basu and Miffre, 2011; Gorton, Hayashi and Rouwenhorst, 2008).

References
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