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Journal of Indexes

Better Beta In Commodities Indexing

Related ETFs: OIL
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BetterBetaInCommoditiesIndexing

Investor interest in commodities indexing has increased dramatically over the past decade due to the increased adoption of alternative investments and the need for exposure to asset classes that are not correlated with stocks and bonds. Still, commodities indexing is in the early stages (relative to other asset classes) and since these indexes are composed of futures contracts, unique challenges have been identified regarding investments that seek to replicate these indexes. These "commodities specific" challenges include:

    • Negative roll yield associated with rolling positions into flat or "contango" futures price curves
    • Inconsistent component inclusion among various commodities indexes
    • Inconsistent weightings mechanisms among various commodities indexes
    • High index-replication costs


Commodities indexing (by necessity) involves a process called "rolling," in which a futures contract must be sold prior to expiration and the next futures contract bought in order to maintain a position within the index. This introduces an interesting wrinkle, as the price for each progressive contract delivery month is different from every other month. The futures price curve can be upward sloping (i.e., "contango"), flat or downward sloping (i.e., "backwardation"). When a commodities index rolls its positions into a contangoed curve, it experiences a loss, while a roll into a backwardated curve results in a gain. This is called "roll yield" and can be either positive or negative.

The shape of futures price curves fluctuate from time to time due to seasonal factors, news events, supply disruptions, geopolitical factors, etc. Some commodities, like gold, tend to be in contango all the time, while others (particularly in the energy and agriculture sectors) are more prone to occasional backwardation. However, contango is the more prevalent curve shape due to the estimated cost of storage, insurance, spoilage and other relevant factors specific to each commodity embedded in the price. Within a broadly diversified and well-balanced commodities index application, contango is consistently the more dominant curve across the components and the majority of market environments. Therefore, aggregate negative roll yield is a frequent challenge.

Index Purpose: Academic Measure Vs. Investability
The oldest commodities indexes—the S&P GSCI and DJ-UBS—were originally designed to be trading tools and/or academic benchmarks, not as a basis for investment products. As such, these indexes hold positions in the "nearby" delivery period (within the next three months) and roll these positions every month. However, it is possible to design an index that measures the longer end of the price curve, maintains the position for a significantly longer time frame and rolls minimally (see Figure 1).


Longview Funds Management

Most commodities indexes roll with a single objective—to avoid delivery and thereby maintain a long position in the nearby contract of the index component. The rolling process involves selling something that you own and buying something that you need. Most investors would agree that rolling simply to avoid delivery, while necessary, does not fully address investors' objectives of selling well and buying intelligently.

For an example of how corrosive to returns frequent rolls can be, one need look no further than the iPath S&P GSCI Crude Oil Total Return Index ETN (NYSE Arca: OIL). OIL tracks the West Texas Intermediate crude oil futures contract by following the S&P SGCI's index rules—monthly rolls into the nearby contracts. Therefore, OIL began 2010 holding the February Crude Oil contract and rolled this position 12 times during 2010 at some point in the middle of each month. For simplicity's sake, we modeled a full roll occurring as close to the 15th of each month as practical.

The price of nearby Crude Oil advanced 8.15 percent in 2011 yet OIL lost -1.91 percent. Why such a wide disparity in expected results? By far the biggest culprit was the cost of frequent rolls, which in this case erased the entire year's return in crude oil. (See Figure 2.)


iPath S&P GSCI Crude Oil

The price of long-dated crude oil advanced 3.8 percent in 2011. Using a roll methodology that minimizes the frequency of rolls mitigates negative roll yield and captured more of crude oil's performance for investors. (See Figure 3.)


Long contract Roll Model

Because they roll frequently, most commodities indexes suffer unnecessarily high aggregate negative roll yield for no other reason than the necessity of avoiding delivery and maintaining nearby positions. This is appropriate for an index designed to measure nearby price action for short-term trading purposes but is not necessarily in line with long-term investor objectives.

By implementing a dedicated use of long-dated contracts combined with a minimal roll protocol, one can also incorporate a "buy low/sell high" bias into the index. Generally speaking, speculative involvement in the commodities futures markets is highest in the nearby period, as evidenced by the higher volume and volatility. The further out the maturity curve one goes, producer/user ("hedger") participation is more pronounced relative to speculative influence. We suggest that hedgers, by virtue of the fact that they are participating in the commodities markets largely to manage margins, have a more rational pricing objective. As a result, indexes that buy with hedgers and hold these longer-dated contracts until they are approaching the nearby period when speculative volume and open interest are increasing are more optimal. This may be viewed as a built-in demand for the contracts as they approach the roll period.

Trading volume and open interest are not equally distributed across every contract in the futures curve. (See Figures 4a and 4b.) Since hedgers are generally focused on managing margins, the fiscal accounting cycle may exert influence on their contract preferences. This may explain the distinct concentration of trading volume and open interest in the midyear and year-end contracts further out the curve. This is a consistent attribute for most commodities, other seasonal factors notwithstanding. For this reason, indexes that seek to go further out on the curve should include volume and liquidity screens for contract selection. Those that do not consider this may have difficulty identifying capacity constraints and/or exposure to illiquidity during high redemption periods. They may also experience higher index tracking error as a result of frequent rolls in lower-volume contracts.


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