Commodities as Asset Class

8/3/2019 Commodities as Asset Class

1/24

For Institutional Investo

Use Only. Not for Publi

Distribution.

Vanguard research March 201

Investment case

or commodities?

Myths and reality

Author

Geetesh Bhardwaj, Ph

Executive summary. Commodities are one o the least understood

asset classes. Some investors wonder how owning a chunk o steel

or a bushel o corn could provide them with any real return, particularly

in times o deation. Still others contend that the high historical returns

or commodities are primarily the result o two commodity bubbles, and

that, excluding those abnormal periods, commodities have had only poor

results. Then, too, some see commodities as highly volatile and as too

risky or most investors.

This paper describes the undamental properties o commodities to

help institutional investors evaluate the case or investing in them.

One challenge in understanding commodities as an asset class is theabsence o a long data series on the past perormance o commodity

utures.1 To address this problem, Vanguard has recently constructed

an equally weighted, well-diversifed commodities return series, using

1 For example, historical data on the well-diversified DJ (Dow Jones) -UBS Commodity Index (hencefort h, DJ-UBSCI) are available

only since 1991 (also, since the index was launched in 1998, it has a significant backfill).

Connect with Vanguard > www.vanguard.com

> global.vanguard.com (non-U.S. investors)


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2 Our commodities return series represents the broad commodity market; given equal weights, no one single commodity or sector can drive the results.

3 We believe that one needs a long historical data record to understand the fundamental properties of anyasset class.

2

long historical commodity utures data beginning in 1959.2 Our aim here is to

describe the basic properties o commodities, and not to provide an investable

alternative to existing commodity indexes.3 But, as with historical analysis o

any asset class (e.g., stocks, bonds, or short-term debt), it is difcult to know

how the existence o a large and institutionally dominated market would haveaected past returns; or similar reasons, investors need to be mindul that past

returns do not guarantee uture perormance.

Can commodities rightfully be considered an

asset class? Can a commodities investor expect

to earn any real return, or were the two historical

bubbles in commodities their only periods ofoutperformance? Are commodities too volatile

for most investors to touch?

This paper addresses these and other questions

as it seeks to separate myth rom reality in helping

investors evaluate the case or commodity investing.

For instance, as we describe, an investor actually

gains exposure to commodities as an asset class

by investing in commodity futures, and not by

investing in physical commodities. The undamental

economic reason long-only investors in commodity

utures have historically been expected to earn a

risk premium is that long investors have provided

price insurance to producers o commodities, who

hedge price risk by taking the short side o positions

in the utures market. Moreover, commodity utures

have, in act, experienced long periods o signiicant

returns or investors, as well as sequences o booms

and busts similar to equities; there is thus little merit

in the argument that relatively high long-term averagereturns o commodity utures are solely a result o a

ew brie abnormal periods o high returns.

First, we introduce the concept o commodity

utures and explore the theoretical oundations o

why a long-only investor may expect to earn a return

or taking such a position. We then construct a

commodities return series or a long-only investment

in commodities utures, including detailed analysis o

the data. Next, we compare the results o investing

in commodity utures versus physical commodities,

as well as the historical perormance o commodity

uture returns versus equity returns. Finally, we look

at the diversiication beneits o commodity utures

rom a portolio perspective.

Notes on risk: All investments are subject to risk. Investments in bonds are subject to interest rate, credit,

and inflation risk. Foreign investing involves additional risks, including currency fluctuations and political

uncertainty. Diversification does not ensure a profit or protect against a loss in a declining market. Past

performance is no guarantee of future returns. The performance of an index is not an exact representationof any particular investment, as you cannot invest directly in an index.


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Basics of commodity investment

A commodity utures contract is a standardized

agreement to buy (or sell) a prespeciied amount

o a commodity at a uture date, called the maturity

date. The price o the contract (the utures price) is

eectively the price that the seller o the commodity

will receive at the maturity date, and is determined

on a utures exchange by the orces o demand

and supply.4

As stated early in this paper, its important

to appreciate that commodity utures do not

necessarily represent direct exposures to actual

commodities. A long investor who agrees to buy

a physical commodity at a uture date may not

have the commodity actually delivered to him or

her, because the investor has the option to sellthe utures contract beore the actual date o

physical delivery.

Determining the futures price

To understand how commodity utures returns are

derived, one must irst understand how a utures

price is determined. The most important element

making up the utures price is the spot price, that

is, the price that market participants expect to

prevail when a utures contract matures. I market

participants expect the uture spot price to be much

higher than the current spot price (due to utureexpected demand and supply or the commodity),

then the utures price will be higher than the current

spot price; otherwise, the utures price willbe lower

than the current spot price (all else being equal). It

is important to emphasize here that the utures price

is set in relation to the spot price that is expected

to prevail at the time o the maturity o the utures

contract, and not the current spot price.

A spot prices deviation at maturity rom what was

expected when the utures contract was issued is

by deinition subject to risk, and this is the risk that

all utures investors ace. I the realized spot price at

maturity ends up higher than the utures price, then

the long investor will make a proit; otherwise, he or

she aces a loss.

So how can long-only investors consistently earna risk premium in this market? The only way this is

likely to happen is i the utures price, on average,

is set below the expected spot price that obtains

at maturity. We would expect this to occur i there

are sellers o commodity utures in the market that

are willing to systematically accept a lower-than-

expected price or the underlying commodity, in

exchange or the utures buyers assurance o a

certain price at maturity. These sellers are willing

to pay a premium to insure against the price risk.

This premium can be thought o as equaling the

dierence between the utures price at which they

sell in the utures market, and the uture spot price

they would otherwise expect to be paid. Much

academic work has been done on this concept

since the 1930s, when both Keynes (1930) and

Hicks (1939) developed the theory o normal

backwardation, which holds that utures prices

are set below expected uture spot prices.

To understand Keynes and Hickss theory, consider

a producer o corn who wants to insure against the

risk that prices could all at harvest time (such a

participant is called a hedger). The corn producer

can obtain such insurance by selling corn utures

to lock in a predetermined price or his crops.

Participating on the other side o the trade are long

investors (called speculators) who provide the

insurance or the price o corn by buying utures

contracts. These long investors, however, demand

a risk premium or bearing the risk o uture price

luctuations. Thus, the long investors would require

that the utures price be set at least somewhat

below the expected uture spot price.

4 At the end of each trading day, gains and losses during the day are settled by the two parties to the contract via transfers from t heir margin accounts,

through daily mark to market. To understand the ac counting, consider the hypothetical example of a buyer and seller entering into an oil futur es contract.

Suppose the current fut ures price of oil for delivery the subsequent mon th is $70 (U.S. dollars). At the time of deliver y, if the spot price turns out to be

$100 dollars, the seller of the commodity will receive $100 for oil. However the seller, through daily mark to market, would have paid the buyer $ 30, thus

effectively exchanging oil at $70. On the f lip side, if at the time of delivery the spot price is $ 50, the seller of the commodity w ill receive $50 for oil. Further,

the seller, through daily mark to market, would also have received $20 f rom the buyer, again effectively exchanging oil at $70.


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The normal backwardation theory implicitly

assumes that the number o producers requiring

hedging outweighs the number o consumers

requiring similar hedging in the market. For example,

suppose iron ore were produced only by mining

companies and used as an input only by steelmakers.I the hedging demands o both types o irms were

equal, there would be no reason to assume one side

o the utures contracting arrangement (long or short)

would receive a premium or buying or selling an

iron-ore uture. However, i one side o the market

(either the producer or consumer) is more risk-averse

than the other, the more risk-averse side clearly

would be willing to provide an insurance premium

to the other side o the transaction.

Gorton and Rouwenhorst (2006) have also recently

studied this topic, and summarized the undamentals

o commodity utures returns as ollows:

1. The expected return to the long investor in

commodity utures in excess o the risk-ree rate

o return is the risk premium. The return realized

by the long investor is the risk-ree rate, plus the

(insurance) risk premium, plus any unexpected

deviation o the uture spot price rom the

expected uture spot price at the time the long

position was established.

2. A long position in utures is expected to earn a

positive risk premium as long as the utures price

is below the expected spot price at maturity. A

risk premium may exist and be earned regardless

o whether the utures price is higher or lower

than the current spot price or the commodity

in question.

3. Expected trends in spot prices are not a source

o return to an investor in utures, because that

would assume successul market-timing on the

part o the utures investor.

Confusion about terminology.Backwardation and

another term, contango, have oten been used to

characterize the current state o the utures market.

Yet, use o these terms has resulted in some

conusion. Contangocommonly reers to a market

in which utures prices are higherthan the current

spot pricethat is, the term structure o the utures

curve is upward sloping. In backwardation, utures

prices are lowerthan the current spot, and the term

structure o the utures curve is downward sloping.

The deinitions just cited, as well as those used by

the U.S. Commodity Futures Trading Commission,5

reer to the slope o the utures curve at a point in

time, and not to the movement o utures prices over

the lie o a contract. However, as stated earlier, the

theory o normal backwardation contends that

utures prices are set below expected spotprices at

maturity. This theory is about utures prices relative

to expected spot prices. However, the prevailing

terminology describes utures markets by reerring

to utures prices relative to the current spot. The

use o the term backwardation to characterize the

state o the utures market vis--vis the current

spot price has led to a widespread, but alse, belie

that the theory somehow implies that a commodity

utures return premium exists only when markets

are in backwardation. As emphasized earlier in this

discussion, however, this is not the case.

Further, given the preceding deinitions o contango

and backwardation as relative to the current spot

price, the natural state o virtually all (historically,

this has actually occurred close to 70% o the time)

commodity utures markets is reasonably expected

to be in contango. This is implied by the existence o

a cost o carry, according to which those holding

a physical commodity must pay or storage and

other expenses, coupled with a simple arbitrage.

Arbitrage in this case is a inancially equivalent

alternative to buying a commodity uture and selling

it at expiry. In an arbitrage transaction, the investor

buys the underlying physical commodity now in

the spot market, stores it until the utures contract

maturity date, and then sells it in the spot market. Ithe commodity is costly to store (there is a cost o

carry), then investors ability to make this alternative

trade should tend to push utures prices higher than

the current spot price, all else equal, which would

5 The U.S. Commodity Futures Trading Commission (CFTC ) defines these market conditions as: Backwardation: Market situation in which futures prices ar e

progressively lower in the distant delivery mon ths and Contango: Market situation in which prices in succeeding delivery months are pr ogressively higher

than in the nearest delivery month. Source: http://www.cftc.gov/educationcenter/glossary/glossary_b.html.

4


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imply contango. This logic, coupled with a mistaken

belie that commodities-utures risk premiums cannot

exist when markets are in contango, has led some to

conclude that all commodities utures returns come

rom the ew market events when the market is in

backwardation (relative to the current spot price).

This argument ails to recognize that prevailing

terminology compares utures prices with current

spot prices, whereas the theory o normalbackwardation suggests a relationship between the

utures price and the expected spot price at maturity.

To illustrate how a risk premium can potentially be

obtained when the market is in contango, consider

the ollowing hypothetical example (see Figure 1).

Suppose the current spot price is $100 and the

expected spot price is $110. The theory o normal

backwardation suggests that the utures price

should be less than the expected spot price. Thus,

suppose the utures price is $105. This implies that

the expected risk premium is $5 ($110 $105 =$5). Notice, however, that the market is in contango:

that is, the utures price is greater than the current

spot price. This example shows that normal

backwardation can be present while a utures market

is in contango; the long-only investor would expect

to earn a premium o $5, although the realized return

will o course be dierent rom $5 i the spot price at

maturity is dierent rom the expected $110.

Now consider an example in which the utures

markets are in backwardation (see Figure 2).

Suppose the current spot price is $115 and that the

expected spot price is $110. The theory o normal

backwardation suggests that the utures price shouldbe less than the expected spot price. Suppose

the utures price is $105thus, the expected risk

premium would be $5. This example also illustrates

a market condition in which there is delationary

pressure, since the spot price is actually declining

rom $115 to $110; however, the utures investors

are expected to get a positive risk premium as a

result o normal backwardation.

In summary, a long-only utures investor in a

commodity market can expect to earn a positive

risk premium by providing valuable insurance, iproducers or other risk hedgers are willing to pay

or such insurance regardless o whether markets

are in backwardation or contango. The positive risk

premium is the reward or assuming the price risk.

Commodity risk premium in a

contango market

Figure 1.

Note: This hypothetical illustration does not represent the return on

any particular investment.

Source: Vanguard.

Inception (t) Expiration (T)

Expectedspot pricerise, $10

Expected riskpremium, $5

$110: Expected

spot price (ST)

$100: Currentspot price (St)

$105: Futuresprice (Ft)

Commodity risk premium in a

backwardation market

Figure 2.

Note: This hypothetical illustration does not represent the return on


Source: Vanguard.

Inception (t) Expiration (T)

Expectedspot pricedecline, $5

Expected riskpremium, $5

$110: Expectedspot price (ST)

$115: Currentspot price (St)

$105: Futuresprice (Ft)


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6

Historical data and construction

of commodities return series

Unortunately, a long historical data series on the

perormance o commodity utures as an asset class

is not available. For example, historical data on the

well-diversiied DJ (Dow Jones) -UBS Commodity

Index (henceorth, the DJ-UBSCI) are available only

rom 1991. Yet, we believe that to ully understand

an asset classs undamental properties, longer-term

historical data are necessary. Thereore, to carry

out a robust historical analysis o the behavior o

commodity utures markets, we have constructed a

commodities return series extending back in history

to August 31, 1959.

Figure 3 lists the commodities that make up our

return series and the inception dates o uturescontracts or each. In all, the return series contains

30 commodities, broadly characterized in seven

sectors (energy, precious metals, grains, animal

products, sots, industrial materials, and industrial

metals). Figure 3 also reports the cumulative

annualized excess returns (beyond the 3-month

U.S. Treasury bill return) or each commodity since

the start o its utures contract through April 30,

2009. The last column reports t-statistics denoting

signiicance o the average excess return. Thus, we

tested or the statistical hypothesis that, on average,

the excess returns were positive. We ound thisto be true or only 5 out o the 30 commodities

(at a 95% signiicance levelsee the asterisked

commodities in the igure)a result that supports

the well-documented high volatility o individual

commodity utures returns.

Our commodities return series is an equally

weighted average o these 30 commodities; the

series is well-diversiied and represents the broad

commodity market. The accompanying Appendix

summarizes the steps we used in constructing

the return series and the details o our analysis.Given the return series diversiied nature, no single

commodity or sector can drive the results. To derive

the total returns that would result rom holding a

ully collateralized commodity utures position (we

ruled out use o leveraging), we incorporated the

3-month U.S. Treasury bill return into the price return.

Numerous academic studies have analyzed the

commodity markets using equally weighted returns

o a commodity basket. For example, Bodie and

Rosansky (1980) constructed an equally weightedcommodities return series using quarterly data rom

1950 through 1976. Fama and French (1987) reported

average monthly excess returns or 21 commodities

as well as or an equally weighted portolio. Unless

otherwise noted, rom here on, when reerring to

commodities utures returns, we are reerring to

returns as measured by the perormance o our

newly constructed commodities return series.

Commodity futures versus spot returns:

Case for insurance-risk premium

The previous section included a hypothetical

example o how an investor in commodity utures

could potentially expect to earn a positive return

when commodity prices are alling. To illustrate the

impact o an insurance-risk premium in a delationary

market, consider the crude oil market. Figure 4, on

page 8, compares the cumulative returns o a ully

collateralized investment in crude oil utures with

that o physical crude oil rom April 30, 1983, through

April 30, 2009. Taking a conservative approach, we

ignored the costs o physical storage, insurance,

and shipping, and so on, which would otherwisehave reduced the returns o the physical crude.

Nevertheless, despite a high monthly correlation

between spot and utures returns (0.97), the total

average annual return or a spot investment (2.1%)

was but a raction o the utures average annual

return (11.6%). In act, or a signiicant portion o

this time (April 30, 1983December 31, 1998), spot

oil prices were actually declining. For the ull, nearly

16-year, period, active spot investment produced

an annual total return o 5.7%, while the annual

return o utures investments over the same period

was 7.1%. This example illustrates the case or an

insurance-risk premium or long-only investors in

commodity utures, even during delationary

market conditions.


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Commodity futures and coverage data for our commodities return seriesFigure 3.

Cumulative annualized

Contracts excess returns (inception

Name start date Sector through April 30, 2009) t-Statistic

Aluminum 6/1/1987 Industrial metals 2.7% 0.02

Coal 7/12/2001 Energy 6.1% 0.18

Cocoa 7/1/1959 Sots 0.4% 0.98

Coee 8/16/1972 Sots 0.4% 1.17

Copper 7/1/1959 Industrial metals 7.7% 2.83*

Corn 7/1/1959 Grains 5.4% 0.89

Cotton 7/1/1959 Industrial materials 1.2% 0.47

Crude oil 3/30/1983 Energy 6.4% 1.78

Feeder cattle 11/30/1971 Animal products 1.5% 1.08

Gold 12/31/1974 Precious metals 1.4% 0.15

Heating oil 11/14/1978 Energy 5.5% 1.76

Lean hogs 2/28 /1966 Animal products 2.5% 1.49

Live cattle 11/30/1964 Animal products 4.4% 2.21*

Lumber 10/1/1969 Industrial materials 7.9% 0.81

Natural gas 4/4/1990 Energy 13.5% 0.08

Nickel 4/23/1979 Industrial metals 0.9% 1.04

Oats 7/1/1959 Grains 6.3% 0.58

Orange juice 2/1/1967 Sots 0.4% 0.89

Palladium 1/3/1977 Precious metals 0.3% 1.08

Platinum 3/4/1968 Precious metals 0.5% 1.03

Propane 8/21/1987 Energy 13.5% 2.16*

Rough rice 8/20 /1986 Grains 7.8% 0.89

Silver 6/12/1963 Precious metals 1.7% 0.66

Soybean meal 7/1/1959 Grains 3.8% 1.88

Soybean oil 7/1/1959 Grains 0.9% 1.13

Soybeans 7/1/1959 Grains 4.6% 2.01*

Sugar 1/4/1961 Sots 3.6% 0.83

Unleaded gasoline 12/3/1984 Energy 11.2% 2.33*

Wheat 7/1/1959 Grains 4.4% 0.52

Zinc 1/3/1977 Industrial metals 0.5% 0.54

Notes: The second column provides the date w hen price quotes were first available for various commodities. The fourth column reports cumulative annualized excess

returns (over the 3-month Treasury bill return). T he last column reports t-statistics for testing the statistical significance of the average excess return (the five

commodities found to have significant excess returns are denoted by an asterisk).

Sources: Vanguard calculations, based on Commodity Research Bureau; Datastream, Thomson Reuters.


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8

Cumulative returns of long crude oil futures versus long crude oil (log scale):

April 30, 1983, through April 30, 2009

Figure 4.

Cumulative returns

10

100

1,000

10,000

1983 1985 1987 1989 20091991 1993 1995 1997 1999 2001 2003 2005 2007

Crude oil futures Crude oil spot

Sources: Vanguard calculations, based on Commodity Research Bureau data.

Year

Cumulative real returns of historical commodity futures and equities (inflation-adjusted):

August 31, 1959, through April 30, 2009

Figure 5.

Cumulative real returns

0

500

1,000

1,500

2,000

2,500

3,000

1959 1964 1969 1979 1984 1989 1994 1999 20041974

Year

Commodities Equities

Note: Equity returns for this and subsequent figures in this paper are based on the following equity series: pre-1971: Standard & Poors 500

Index; 1971 through April 22, 2005, Dow Jones Wilshire 5000 Index; April 23, 2005, through April 30, 2009, MSCI US Broad Market Index.



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Bursting the commodities bubbles?

As noted early in this paper, some investors hold

that commodities high historical returns can be

attributed primarily to two commodity bubbles,

and that, outside o those periods, returns are

unattractive. This sections discussion reveals that

this argument is alse, based on an analysis o the

historical record.

For the period August 31, 1959, through April 30,

2009, commodity utures (i.e., our commodities

return series) have produced an average annual

return o 9.8%, which is comparable to the 9.0%

average annual return or U.S. equities or the same

period. Figure 5 plots the cumulative real returns

(net o inlation) o commodities and equities or

August 31, 1959, through April 30, 2009.

Identifying historical subperiods

for the commodities return series

To isolate historical episodes or commodity

returns, we divided the 51-year period covered by

our commodities return series into ive subperiods,

to capture the dierent cycles experienced by the

commodity utures markets. Figure 6 plots these

subperiods and the corresponding annual returns

or investors. Over the irst subperiodAugust 31,

1959, through December 31, 1971the average

annual return or commodity utures was 7.7%,

similar to the 8.0% average annual return o U.S.equities or the same period. The next subperiod

January 31, 1972, through December 31, 1973

saw commodities utures return 58.5%. Clearly,

this was a time o abnormally high returns or

commodities, particularly compared with the 2.0%

return o U.S. equities or the same period. Over

the third subperiodJanuary 31, 1974, through

December 31, 2003commodity utures returned

9.1%, a ew points below the corresponding equities

result o 12.3%. For the next subperiodJanuary 31,

2004, through June 30, 2008commodity utures

advanced 19.5%, a high result compared with the

corresponding equities return o 6.0%. Over the inal

subperiod analyzedJuly 31, 2008, through April

30, 2009commodity utures returned 51.5%, a

low result compared with the corresponding equities

return o 35.1%. (Note: All returns in this paragraph

are average annual returns or the periods stated.)

High historical real returns for commodities: A result of two commodity bubbles?

(August 31, 1959, through April 30, 2009)

Figure 6.

Cumulative real returns

0

500

1,000

1,500

2,000

2,500

3,000

1959 1964 1969 1979 1984 1989 1994 1999 20041974

Year

Note: Return figures are average annual nominal returns for the period.


August 31, 19591971: 7.7%

January 31, 19721973: 58.5%

January 31, 19742003: 9.1%

January 31, 2004June 30, 2008: 19.5% July 31, 2008April 30, 2009:51.5%


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The bubble of the early 1970s

As stated, it has been argued that two o the

ive subperiods19721973 and 20042008

are commodity bubbles. To analyze this historical

phenomenon urther, we examined these two

periods more closely.

The irst period, January 31, 1972, through

December 31, 1973, can be associated with two

major events in the history o inance. The irst

event was the all o the Bretton Woods monetary

management system. It should be noted, however,

that the high returns o commodities or this period

cannot be attributed directly to luctuations in the

price o gold, as gold utures contracts were not

introduced until 1975 and thus were not part o

the equally weighted commodities return seriesin 19721973.6

The other major historical event o 19721973 was

the irst oil shock: In October 1973, members o the

Organization o Arab Petroleum Exporting Countries

(OAPEC, consisting o the Arab members o OPEC

plus Egypt and Syria) proclaimed an oil embargo.

Again, as in the case o gold, no energy utures were

traded in the 1970s; as indicated in Figure 3, crude

oil contracts were not available until 1983. Thus, to

claim that the high prices o gold and energy were

responsible or commodity utures returns in the

period is incorrect.

To better understand the period, we looked at the

average annual returns o individual commodities or

the two years (see Figure 7). As the igure shows,

no single commodity caused the high returns. Wheat

garnered the best return, but other grains also

experienced unusually high results. Gorton, Hayashi,

and Rouwenhorst (2008) postulated that these

high returns were generated by broad inventory

shortages in a number o commodities, which led

to higher uncertainty in the market, greater risk or

long investors to insure, and temporarily higher risk

premiums or long investors. Thus, according to this

theory, these exceptional returns were the result o

undamental actors, and were not speculative in

nature. Supporting the view that this isolated period

o rocketing returns was not a bubble is that there

was no corresponding correction, no subsequent

crash in returns to support the notion o a bubble

to begin with.

6 Even after adjusting for inflation, the overall return for commodities for the period was 50.1%.

10

Selected individual commodity returns:

19721973

Figure 7.

Average annual returns

(January 31, 1972, through

Commodity December 31, 1973)Silver 52%

Platinum 18%

Live cattle 17%

Lean hogs 46%

Feeder cattle 36%

Corn 51%

Soybeans 70%

Soybean oil 82%

Wheat 113%

Soybean meal 81%

Oats 29%Cocoa 81%

Coee 4%

Sugar 38%

Orange juice 16%

Cotton 99%

Lumber 56%

Copper 59%

Sources: Vanguard calculations, based on Commodity Research Bureau;

Datastream, Thomson Reuters.


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The bubble of the early 2000s

Over the second historical period (January 31,

2004, through June 30, 2008 ), commodities

experienced annual returns o 19.5%. Figure 8

reports selected commodity-level average annual

returns or this period. Clearly, the returns weredominated by the energy sector; however, copper,

oats, soybean oil, silver, and platinum also had

impressive returns. In contrast to the 1970s,

commodity utures returns underwent a dramatic

correction during the period July 2008 through

April 2009, which strongly suggests that there was

a signiicant bubble component to the 20042008

returns. Nevertheless, i we ignore the period o

the irst bubble (January 31, 1972December 31,

1973), commodity utures produced a solid average

annual return o 8.7% or the period August 31,

1959December 31, 2003. I we urther ignore both

bubbles rom the sample (while retaining the

recent 20082009 correction), commodity utures

have produced an average annual return o 7.1% or

the period August 31, 1959, through April 30, 2009

(taking out 19721973 and January 31, 2004, through

June 30, 2008). These data support the view that

high historical returns or commodities cannot just be

attributed primarily to two commodity bubbles, and

that, outside o those periods, long-only investors

still have earned signiicant positive returns.

Commodity futures versus equities:

Comparing returns and volatility

As the preceding analysis suggests, there is little

validity to the claim that a ew historical periods have

determined returns or commodities utures. In act,

investors can point to a long period o substantial

returns rom commodities utures. Clearly, the

early 1970s was a unique time or commodities.

Although we have reuted the notion that 1972 and

1973 represented a bubble, one still has to question

whether that kind o return can happen again.

1

Selected individual commodity returns:

20042008

Figure 8.

Average annual returns

(January 31, 2004, through

Commodity June 30, 2008Crude oil 33%

Heating oil 36%

Natural gas 19%

Gasoline 33%

Coal 26%

Propane 38%

Gold 19%

Silver 26%

Platinum 27%

Palladium 19%

Live cattle 11%Lean hogs 2%

Feeder cattle 15%

Corn 8%

Soybeans 17%

Soybean oil 20%

Wheat 6%

Soybean meal 13%

Oats 23%

Rough rice 12%

Cocoa 18%

Coee 10%Sugar 8%

Orange juice 12%

Cotton 9%

Lumber 14%

Copper 49%

Zinc 16%

Nickel 16%

Aluminum 15%




12/24

I we ignore the high returns o the 1970s, the

period January 31, 1980, through April 30, 2009,

provided average annual commodity returns o

6.2%, as opposed to 10.3% or U.S. equities;

however, during this period, our analysis shows that

commodities had 25% lower volatility than

equities (sources: calculations based on CommodityResearch Bureau; Datastream, Thomson Reuters).

This brings us to a more in-depth look at returns

and volatility or commodity utures versus equities.

As reported in the previous section, average annual

historical returns or commodity utures (9.8%) and

U.S. equities (9.0%) are comparable. To compare the

perormance o the two asset classes more closely,

Figure 9 plots their historical 12-month returns rom

May through April (that is, the irst 12-month period

is deined as beginning on May 31, 1960, and the

inal 12-month period ends on April 30, 2009, just

to include the last data point in our sample, which

is April 2009; the results are similar, however, i we

deine the 12 months as the calendar year). This

graph is also important to address the myth that

commodities have returns only once in 20 years,

and then only poor returns or the next 20 years.

At irst glance, its diicult to tell in Figure 9 which

plotted time series is commodities utures and which

one is equities. The giveaway is the outlier in 1972

and 1973, in which commodities had returns o more

than 50% in one year. The igure reveals that both

commodities and equities have had multiple years

o returns in the 20%40% range. These multiyear

runs contradict the view that one has to endure zero

returns or decades beore experiencing any positive

returns in commodities.

12

Twelve-month returns for commodity futures versus equities: May 31, 1960, through April 30, 2009Figure 9.

Returns

April1961

April1965

April1969

April1973

April1977

April1985

April1989

April1993

April1997

April2005

April2009

April2001

April1981

60

40

20

0

20

40

60%

Commodities Equities



13/24

Figure 10 plots a histogram o monthly returns or

commodities and equities, and Figure 11 shows

summary statistics o the monthly data. Several

things stand out: First, equities have a slightly longer

negative tail, and commodities have a slightly longer

positive tail. Second, while equities have returns

that are comparable to those o commodities utures,they have had higher volatility. Third, commodities

utures have positive skewness, while equities have

negative skewness.

Potential diversification benefits

of commodity futures

Advocates o commodity utures have argued that

commodities provide diversiication because o their

low correlation with equities and bonds, while critics

point out that the historical diversiication argument

is no longer valid, since the correlations have

increased signiicantly; urther, they claim there are

no diversiication beneits during deep recessions.

1

Histogram of commodity futures and equity monthly returns: August 31, 1959, through April 30, 2009Figure 10.

Returns

< 20% > 20%20%, 15% 15%, 10% 10%, 5% 5%, 0% 5%, 10% 10%, 15% 15%, 20%0%, 5%

0

20

40

60%

Volatility

Commodities: slightly longer positive tailEquities: slightly longer negative tail


Comparing commodity futures and

equity monthly returns: Summary statistics

(August 1959 through April 2009)

Figure 11.

Commodity

utures Equities

Monthly average returns 0.85% 0.82%

Standard deviation 3.70% 4.40%

Skewness 0.26 0.66




14/24

During negative shocks for equities

This section irst addresses the potential

diversiication beneits o commodities during

negative shocks or equities, when the diversiication

beneits really matter. Figure 12 reports the average

monthly returns or domestic equities, commodities,

and international equities or months when these

securities experienced extreme negative and/or

positive shocks. The analysis covers two timeperiods: the ull historical sample rom August 31,

1959, through April 30, 2009 (the igure doesnt

include international equity returns or this period),

and the inal decade starting January 31, 1999.

For the longer historical period, while the average

monthly return or the worst 12 domestic-equity

months was 12.6%, commodities utures declined

at a much smaller average monthly rate o 1.1%.

The relative picture is not as clear over the inal

decade: The worst 12-month average monthly

return or domestic equities was 9.6% (international

equities, 9.7%), while or the same 12 months,

commodities lost an average o 2.7% per month.

Figure 12 indicates that even though commodities

experienced modest declines or the worst months

o domestic equities, commodities still provided

some diversiication beneit, since or the same

months international equities declined 9.7% permonth. O course, commodities have not always

perormed well during equity-market downturns;

thus, or investors concerned about worst-case

outcomes, diversiiers such as cash may be more

eective. However, the signiicantly lower overall

returns or holding cash make the reliable protection

it oers more costly over time.

14

Worst 12 equity months Best 12 equity months

Domestic Commodity International Domestic Commodity International

Period equity returns utures returns equity returns equity returns utures returns equity returns

August 31, 1959April 30, 2009 12.6% 1.1% 11.7% 0.7%

January 31, 1999April 30, 2009 9.6% 2.7% 9.7% 7.5% 1.6% 6.6%

Worst 12 commodity utures months Best 12 commodity utures months

Domestic Commodity International Domestic Commodity International

Period equity returns utures returns equity returns equity returns utures returns equity returns

August 31, 1959April 30, 2009 4.0% 9.8% 1.4% 12.2%

January 31, 1999April 30, 2009 4.9% 7.4% 7.1% 0.1% 6.9% 1.5%

Notes: International equities are represented by the MSCI EAFE + EM Index. As this index does not go back to the 1950s, the international equity returns are reported

only for the more recent sample.


Average monthly returns for domestic equities, commodity futures, and international equities

during their 12-worst and 12-best months (selected periods)

Figure 12.


15/24

Correlation of U.S. equities

with commodities versus international stocks

What about the correlation o monthly U.S. equity

returns and commodity utures returnsand,

or urther comparison, o domestic equities and

international equities? The results o our analysisin Figure 13show that the historical correlation

o U.S. equity and commodity utures returns has

been very low; or the period August 31, 1959,

through April 30, 2009, the correlation was only 0.13.

However, the correlation has risen steadily over time.

For January 31, 2001, through April 30, 2009, the

correlation was much higher, at 0.37. Many investors

conidently include exposure to international equities

or diversiication purposes; however, the correlation

o international equity returns with U.S. equities

has also increased over time. From January 31,

2001, through April 30, 2009, the correlation o

international equity returns with U.S. equities was

0.90, ar higher than the 0.37 or commodity utures.

The purpose o this analysis is not to suggest that

investors should abandon international stocks as

potential diversiiers in avor o commodities; ater

all, commodities have been experiencing increasing

correlation with equities over time.

Commodity futures can lessen volatility

of all-equity andstock/bond portfolios

Another way to characterize the diversiicationbeneits o commodity utures is to analyze

the impact o including commodities utures on

the historical volatility o a diversiied portolio.

Figure 14, on page 16, reports the average

annualized change in portolio volatility as commodity

utures are added to the asset mix. We considered

two hypothetical base portolios, one all equities and

the other 60% equities/40% bonds (in the second

example, as we added commodities to the portolio,

we assumed the mix o stocks and bonds in the rest

o the portolio was let constant, at 60%/40%).

Figure 14 is based on data rom January 31, 1974,through April 30, 2009 (however, results are similar

or the ull historical period beginning in 1959). For

this exercise, we excluded the market conditions

o the early 1970s to show that, as with returns,

diversiication beneits are not dependent on a

ew historical periods. In our hypothetical example,

adding commodities to the portolio clearly had the

potential to reduce the portolios volatility. Even or

the 60% stocks/40% bonds portolio, which has

much lower volatility than the all-equity portolio,

1

Comparing correlation of domestic equities

with commodities, international equities

(selected periods)

Figure 13.

Correlation

Correlation of U.S. equities with commodities

Correlation of U.S. equities with international equities

Sources: Vanguard calculations, based on Commodity Research

Bureau; Datastream, Thomson Reuters.

0

20

40

60

80

100%

Aug. 1959April 2009

Jan. 1971April 2009

Jan. 1981April 2009

Jan. 1991April 2009

Jan. 2001April 2009


16/24

16

signiicant diversiication gains could have resulted

rom adding commodities. For example, adding

10%20% commodities would potentially have

reduced volatility in the 60%/40% portolio by about

1 percentage point and almost twice that or the

all-equity portolio (see Figure 14).

Figure 15 reports the hypothetical impact o a 20%

exposure to commodities on portolio returns andvolatility. The irst two columns report total returns,

standard deviations, and Sharpe ratios or the all-

equity and 60%/40% equity/bond portolios. The

next two columns report total returns or these

two portolios ater adding a 20% exposure to

commodities. In this hypothetical example, the

eect on perormance o adding commodities tothe portolio was marginal; average returns improved

by roughly 50 basis points. However, the potential

impact on volatility was highly signiicant. Adding

commodities to the all-equity portolio increased the

Sharpe ratio rom 0.29 to 0.35. Another interesting

comparison is 100% equity exposure versus 80%

exposure to the 60% equity/40% bond portolio and

20% commodity exposure. The returns o the two

portolios are comparable (equity portolio returns

are potentially higher by 11 basis points), while the

diversiied portolio potentially has 41% less volatility.

To urther understand the undamental source o

diversiication beneits o commodity utures, we

compared the equity and commodity utures returns

during dierent stages o the business cycle.

Adding commodity futures can benefit

during different stages of business cycle

It is also instructive to look at the relationship o

commodity utures returns and equities over a

typical business cycle. As identiied by the National

Bureau o Economic Research (NBER), the businesscycle can be divided into our stages: late expansion,

early recession, late recession, and early expansion.

Figure 16 illustrates these patterns using the

historical record.

As shown in Figure 16, during late expansion and

beore the onset o recession, the equity market

has tended to experience low returns, which

continue during the early part o the recession.

Further, because equities are a leading indicator

o the business cycle, equity markets tend to

recover beore a recession is over; also, during

the late-recession period, equities have typically

Average annualized change in portfolio

volatility as a result of adding commodities:

January 31, 1974, through April 30, 2009

Figure 14.

Annualized volatility change relative

to no-commodities portfolio

100% equities 60% equities/40% bonds

Percentage of portfolio in commodities

100%90%0% 10% 20% 30% 40% 50% 60% 70% 80%

6

4

2

0

2

4%

Notes: This hypothetical illustration does not represent the return on


Corporate bond returns for this and subsequent figures in this paper

are based on the following series: before 1968, Standard & Poors

High Grade Corporate Index; 19691972, Citigroup High Grade Index;

and January 1, 1973, through April 30, 2009, Barclays Capital U.S.

Credit Bond Index.




17/24

7 For details, see Gorton et al. (2008).

experienced higher returns. Commodities utures,

however, have behaved very dierently rom equitiesover the course o the business cycle. Commodity

utures returns are plausibly linked to the state o

inventories in the economy,7 and their returns can

thereore be expected to be a lagging indicator

o recession.

Thus, during the late-expansion period (anticipating a

recession), while equity markets tend to experience

relatively poor returns, low inventory levels would

imply that commodity utures are experiencing

higher-than-normal returns. Further, because o

inertia in inventories, it is not until a recession sets

in that commodities experience low returns. As

stated, coming out o a recession, equities have

tended to revive beore the recession ends, while

commodities utures returns have tended to improve

only ater the early expansion period has begun.

To deine earlyand laterecession, we divided

each o the eight recessions rom 1959 through

2009 into two equal halves. For example, or the

2001 recession that lasted rom April to November,

we deined the period o April 2001 through

July 2001 as early recession, and August 2001

through November 2001 as late recession. For the

current recession, we deined the irst 12 months

(January 2008 through December 2008) as earlyrecession, and January 2009 through April 2009

as late recession. For the expansionary period, the

12 months beore a recession were deined as late

expansion, and the 12 months ater a recession as

early expansion.

1

80% (60% equities/

60% equities/ 80% equities/ 40% bonds)/

100% equities 40% bonds 20% commodities 20% commoditiesTotal return 9.05% 8.45% 9.51% 8.94%

Standard deviation 15.34% 10.46% 12.86% 8.98%

Sharpe ratio 0.29 0.31 0.35 0.40

Note: This hypothetical illus tration does not represent the return on any particular investment. The first t wo columns report total returns, standard deviations,

and Sharpe ratios for the all-equity and 60%/40% equity/bond port folio. The next two columns report the same for these two portfolios after adding a 20% exposure to

commodities.


Effects on portfolio returns and Sharpe ratios of adding commodities to portfolio:


Figure 15.

Potential diversification benefits of

integrating commodities with equities during

different stages of business cycle

Figure 16.

Note: NBER, National Bureau of Economic Research.

Source: Vanguard.

Late expansion(High commodityreturns, lowequity returns)

Early recession

Earlyexpansion

Late recession(Low commodityreturns, high equityreturns)

NBER Peak

NBER Trough


18/24

Figure 17 reports equity and commodity utures

returns during the dierent stages o the business

cycle: We analyzed the eight recessions since 1959,and we also segregated the last three recessions (all

three occurring ater 1990). During the late-recession

period, the average annual return or equities was

32.39%, while commodities declined 1.14%. During

the late-expansion period, although equities had

started their decline and experienced average annual

returns o 1.72%, commodity utures markets were

actually booming, with average annual returns o

22.67%. These results were robust, and the pattern

persisted or the shorter period o three recessions

since 1990, including the current recession. In the

current recession, equities peaked in October 2007,beore the start o the recession, and commodities

peaked in June 2008, six months ater the economy

was in recession. For the period November 2007 to

June 2008, the average monthlyreturn or equities

was 1.98%, while that or commodities was 3.11%.

The results o this section suggest that

commodities can have diversiication beneits

because commodities behave undamentally

dierently than equities at dierent stages o the

business cycle. Note, however, that this analysis can

only become clear in hindsight. Predicting periods o

outperormance or underperormance or any asset

class can be extremely diicult, i not impossible.

Commodity futures returns and inflation

Inlation is a serious concern or investors who care

about the real purchasing power o their returns.Given the relationship between commodity utures

returns and the stages o the business cycle, it

is instructive to explore the relationship between

commodity returns and inlation. Many traditional

asset classes are a poor hedge against inlation

at least over short- and medium-term horizons.

Figure 18, which reports the correlation o inlation

with commodity utures, equities, and bond returns,

suggests that commodity utures might be a slightly

better inlation hedge than stocks or bonds. We

calculated correlations at monthly as well as rolling

quarterly and annual horizons.

18

Eight recessions since 1959 Last three recessions, since 1990

Equities Bonds Commodities Equities Bonds Commodities

Late expansion 1.72% 1.01% 22.67% 5.40% 7.84% 10.74%

Early recession 25.04% 3.03% 4.48% 27.88% 1.57% 18.05%

Late recession 32.39% 20.30% 1.14% 14.62% 9.41% 14.74%

Early expansion 13.68% 8.64% 5.48% 0.09% 9.37% 7.91%

Note: This table reports equity and commodity futures returns during different stages of the business cycle. To define early and late recession, we divided each of

the historical recessions into two equal halves. The 12-month period before a recession was defined as late expansion, and the 12-month period after a recession

was defined as early expansion. All returns are average annualized returns.


Business cycle and diversification benefits of commoditiesFigure 17.

Correlation of equities, bonds, and

commodity return series with inflation:


Figure 18.

Equities Bonds Commodities

Monthly requency 0.09 0.10 0.08

Quarterly requency 0.05 0.14 0.25

Annual requency 0.10 0.25 0.34




19/24

Although it appears that commodity utures come

out in ront o equities and bonds as an inlation

hedge, the asset class is not a perect hedge or

inlation. To the extent that commodity utures

represent a bet on commodity prices, they are

directly linked to the undamental components oinlation. However, they do not provide a hedge

against certain other components o inlation, such

as increasing health cost. Further, because utures

prices include inormation about oreseeable trends

in commodity prices, commodity utures returns are

likely to rise and all with unexpected components

o inlation. A detailed analysis o the relationship

o commodity utures returns to inlation is beyond

the scope o this paper, and is a subject o uture

research. I the investors primary objective is

to obtain an inlation hedge, then, clearly, TIPS

(Treasury Inlation Protected Securities) would be

a much better option.

Conclusion

This paper has addressed the attractiveness o a

broadly diversiied portolio o commodity utures

as an asset class. It is critical to understand that

an investment in commodity utures does not

represent direct exposure to physical commodities.

Commodities utures prices are set in relation to

expected spot prices at maturity, and not to current

spot prices. A historical analysis o commoditiesutures return patterns suggests there is little

merit in the argument that relatively high long-term

average commodities utures returns are solely a

result o a ew brie abnormal periods o high

returns. Commodities utures have experienced long

periods o signiicant returns or investors, as well as

sequences o booms and busts similar to equities.

Historically, commodity utures returns and equity

returns have had very low correlation, and although

this correlation has risen over time, recent data

suggest the correlation between equities and

commodities utures is lower than that between

equities and other broadly accepted diversiiers,

such as international equity. In addition, while

equities are leading indicators o the business

cycle, commodity utures have tended to be lagging

indicators. There is no reason to expect that this

relationship to the business cycle will change.

This would suggest that uture corrections between

equities and commodity utures could remain

relatively low, oering potential diversiication

beneits to investors who are willing to accept the

unique risks and opportunities o this asset class.

References

Bodie, Zvi, and Victor Rosansky, 1980. Risk and

Return in Commodity Futures. Financial Analysts

Journal(May/June): 2739.

Davis, Joseph H., and Roger Aliaga-Daz, 2009.

The Global Recession and International Investing.

Valley Forge, Pa.: Vanguard Investment Counseling

& Research, The Vanguard Group.

Fama, Eugene F., and Kenneth R. French, 1987.

Commodity Futures Prices: Some Evidence on

Forecast Power, Premiums, and the Theory o

Storage. Journal of Business60: 5573.

Gorton, Gary, and K. Geert Rouwenhorst, 2006.

Facts and Fantasies about Commodity Futures.

Financial Analysts Journal62(2): 4768.

Gorton, Gary, Fumio Hayashi, and K. Geert

Rouwenhorst, 2008. The Fundamentals of

Commodity Futures Returns. Yale ICF WorkingPaper No. 07-08. New Haven, Conn.:

Yale University.

Hicks, John R., 1939. Value and Capital. Oxord:

Oxord University Press.

Keynes, John M., 1930. A Treatise on Money,

vol. 2. London: Macmillan Publishers.

Santos, Joseph, 2008. A History o Futures Trading

in the United States. In EH.Net Encyclopedia of

Economic and Business History, edited by Robert

Whaples, March 16; available at http://eh.net/

encyclopedia/article/Santos.utures.

Working, Holbrook, 1960. Speculation on

Hedging Markets. Food Research Institute

Studies1: 185220.

1


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Appendix. Construction and methodology

of the commodities return series

We ollowed the methodology o Gorton and

Rouwenhorst (2006) in constructing our equally

weighted commodities return series. The steps in

constructing the return series were:

1. For each month, we constructed price returns on

each commodity uture using the nearest contract

not expiring in that month.

2. For a mechanical trading strategy, on the last

business day o the month beore the expiration

date o a utures contract, we rolled the contract

into the next nearest utures contract.

3. Using monthly returns or each commodity utures

contract, we constructed the return series by

adding the monthly returns together or eachmonth and then dividing them by the number o

commodities in the return series or that month.

Thus, we essentially have an equally weighted

indexing approach with monthly rebalancing.

4. A commodity enters the return series on the

last business day o the month ollowing its

introduction date.

5. Finally, to obtain the total returns o holding a

ully collateralized commodity utures position,

we added to the price returns the 3-month U.S.

Treasury bill return.8

Selection of commodities

The list o 30 commodities that were selected or

this study is based on most o the 23 commodities

eligible for inclusion in the DJ-UBS Commodity

Index (DJ-UBSCI). We augmented this list with nine

more commodities: coal, eeder cattle, lumber, oats,

orange juice, palladium, propane, rough rice, and

soybean meal. Also, because o data limitations, we

did not include tin and lead;9 tin and lead are part o

the eligiblecommodities, but are not in the inal list

o 19 commodities currentlyin the DJ-UBSCI.

The reason we included the additional nine

commodities was to broaden our commodities

universe. Some o the commodities, like oats and

soybean meal, have long trading histories going

back to 1959. These additional nine commodities

represent broad sectors o the commodities

universe: energy (coal and propane), grains (oats,

soybean meal, and rough rice), sots (orange juice),

industrial materials (lumber), animal products (eeder

cattle), and precious metals (palladium).

To test the impact o membership o these

30 commodities in our commodities return series,

we constructed three series o returns, using

the ive steps just described. The irst series is

based on the 19 commodities currently in the

DJ-UBSCI. The second series is based on just the

21 commodities (not including tin and lead) eligible

or inclusion in the DJ-UBSCI. The third series

represents our broad-based commodities return

series, which includes all 30 commodities listed

in the text in Figure 3. Figure A-1 cites the total

8 Source: http: //research.stlouisfed.org/fred2 /.

9 These commodities are traded on the London Metal Exchange, and their data are not covered by the Commodity Research Bureau, our primary data source.

20

Commodity futures returns:

Summary statistics (August 31, 1959,

through April 30, 2009)

Figure A-1.

Commodities universe

All 30DJ-UBSCI: DJ-UBSCI: commodities

19 current 21 eligible in our

commodities commodities* return series

Total returns 10.52% 10.23% 9.85%

Volatility 13.84% 13.58% 12.79%

Sharpe ratio 0.40 0.39 0.38

Correlation

with equities 0.11 0.12 0.13

*Does not include tin and lead (for explanation, see Appendix text).




21/24

returns, volatility, Sharpe ratios, and correlation

with equities or the three commodity return

series rom August 31, 1959, through April 30,

2009. The results were very similar or all three

measures. The volatility o our commodities return

series, however, was the lowest, because o theimpact o greater diversiication. Given this papers

objective to study the behavior o commodities as

a broad asset class, we thus avored the equally

weighted return series based on all 30 commodities.

Why equally weighted returns?

Since our commodities return series is an

equally weighted average o individual commodity

returns, it is well-diversiied and represents the

broad commodities market. Given equal weights,

no one single commodity or sector can drive the

results. However, one can still question whether

the results o our analysis are conditional on

the commodities return series. Recall the two

components o our return series construction:

equal weighting and monthly rebalancing (an

outcome o the equally weighted average). Gorton

and Rouwenhorst (2006) have shown that returns

and volatility properties o commodity utures are

robust to annual rebalancing as well. An alternative

to equal weighting would be a weighting scheme

such as that adopted by the DJ-UBSCI, whose

weights are based on the production volume and/or liquidity o individual commodities. Serious data

restrictions apply, however, in constructing such an

index; urther, such backill could arguably amount to

or lead to a data-mining eort; the agnostic, equally

weighted approach has the virtue o simplicity and

transparency. Later in this Appendix we nonetheless

compare our commodities return series with both

the DJ-UBSCI and the S&P-GSCI over the time

period common to all three.

Investability

Could an investor have actually earned the returns

shown by our return series? Like other indexes, the

equally weighted return series results do not relect

any transaction costs, which would apply in the real

world. However, clearly, commodity utures marketshistorically have had the depth that an investable

strategy requires. As documented by Santos (2008)

and numerous others, the commodities markets in

the United States have a long history, with trading

in agricultural commodities voluminous even in the

19th century. Santos reported that between 1884

and 1888, the volume o grain (wheat, corn, oats,

barley, and rye) utures traded in the U.S. market

was eight times the average annual amount o crops

produced. For cotton, by 1879 utures volume had

outnumbered production by a actor o ive. Working

(1960) estimated that or the period 19541958,

the average dollar value o short hedging contracts

or cotton, wheat, soybean, corn, and soybean oil

was close to $500 million. Certainly a relatively

small investor could have bought the contracts

listed and analyzed in our commodities return series

and endeavored to replicate the equal weighted

methodology. But as with historical analysis o

any asset class (e.g., stocks, bonds, or short-term

debt), it is diicult, i not impossible, to know how

the hypothetical development o a large, liquid, and

institutionally dominated market would have aected

past returns.

Comparing commodities return series

with DJ-UBSCI and S&P-GSCI

DJ-UBSCI data are available rom 1991, and the

index itsel was launched in 1998. S&P-GSCI

data are available rom 1970, and the index was

launched in 1992. This section compares the

perormance o these two indexes with our equally

weighted commodities return series on a number

o parameters over the period common to all three

2


22/24

22

measures: January 31, 1991, through April 30,

2009. For this period the DJ-UBSCI and the

commodities return series had a high correlation

o 0.91 at monthly requency; the correlation

with the S&P-GSCI was much lower, at 0.75 (see

Figure A-2). As the igure shows, the commodities

return series had a marginally higher correlation with

domestic equities than did the DJ-UBSCI. In terms

o inlation and bond returns, the DJ-UBSCI was

correlated almost exactly (inlation) or exactly (bond

returns) with the commodities return series.

The DJ-UBSCI is well recognized as a broad-based

commodities index, while the weighting structure

o the S&P-GSCI makes it primarily an energy index.

As o April 30, 2009, the energy subsector weightingin the S&P-GSCI was more then 70%, whereas the

energy sector weighting in the DJ-UBSCI is capped

at 33%. The DJ-UBSCIs greater diversiication

makes it much less volatile than the S&P-GSCI.

However, as shown in Figure A-3, the commodities

return series is clearly the least volatile o the

three measures; this is to be expected, given the

equally weighted nature o the return series and the

embedded diversiication beneits. Figure A-4 plots

the cumulative returns o the three measures.

Composition of commodities return series

The composition o the commodities return series

as constructed here changed signiicantly rom the

1960s to the 1990s as dierent contracts were

added to the return series. For example, or the irstsubperiod identiied in this paper (19591971), there

were no energy utures contracts. It is possible that

the historical return and diversiication properties

o the return series are distorted owing to its

composition.

To address the issue o composition, we considered

three subperiods (see Figure A-5). During the irst

subperiod (1959 through 1971), commodities in the

return series were cocoa, copper, corn, cotton, oats,

soybean meal, soybean oil, soybeans, wheat, sugar,

silver, live cattle, lean hogs, orange juice, platinum,

and lumber. These commodities represented the

ollowing sectors: sots, grains, industrial metals,

industrial materials, animal products, and precious

Commodities

Domestic equities Inlation Bonds return series

Commodities return series 0.28 0.22 0.16

DJ-UBSCI 0.23 0.23 0.16 0.91

S&P-GSCI 0.17 0.28 0.11 0.75


Commodities return series, DJ-UBSCI, and S&P-GSCI: Correlation with domestic equities, inflation, and bonds

(January 31, 1991, through April 30, 2009)

Figure A-2.

Commodities return series, DJ-UBSCI,

and S&P-GSCI: Summary statistics

(January 31, 1991, through April 30, 2009)

Figure A-3.

Commodities

return series DJ-UBSCI S&P-GSCI

Average 0.51% 0.44% 0.36%

Variance 0.11% 0.17% 0.37%

Skewness 0.95 0.66 0.46

Kurtosis 5.65 3.16 1.88




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metals. Notable exceptions were gold and energy

products, both o which were introduced in the

second subperiod, 1975 through April 30, 2009;

natural gas was added in 1990, and coal in 2001. The

last subperiod, 1988 through April 30, 2009, included

almost all o the energy contracts as well.

For the irst subperiod, 1959 through 1971, the

commodities return series had no energy or gold

utures contracts; yet, it produced a return o 7.74%

with a volatility o 8.68%; this was nearly equal to

the 8.02% return o equities, which had a volatility

o 12.92%. The higher volatility o the second and

third subperiods has not just been a characteristic

o commodities, however; all the asset classes have

had higher volatility.

2

Commodities return series, DJ-UBSCI, and S&P-GSCI:

Cumulative returns (January 31, 1991, through April 30, 2009)

Figure A-4.

Cumulative returns


S&P-GSCICommodities return series DJ-UBSCI

0

100

200

300

400

500

600

Year20081990 1992 1994 1996 1998 2000 2002 2004 2006

Commodities

Equities (%) Inlation (%) Bonds (%) return series (%)

19591971 8.02 (12.92) 2.81 (0.7) 3.52 (5.38) 7.74 (8.68 )

1975April 30, 2009 11.45 (15.84) 4.19 (1.14) 8.66 (7.3) 8.08 (12.45)

1988April 30, 2009 8.57 (15.03) 2.90 (0.93) 7.35 (5.28) 6.86 (11.53)


Total returns (volatility) for equities, inflation, bonds, and commodities return series: Subperiod analysisFigure A-5.


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Commodities as Asset Class