Myths of Commodity InvestmentNovember 2009

Myths of Commodity Investment

Institute for Global Asset and Risk Management

Truth is not hard to kill and that a lie told well is immortal.

Mark Twain, Advice to Youth

This presentation is furnished for educational purposes only and is subject to completion or amendment. This presentation is not an offer to buy or sell, nor a solicitation of an offer to buy or sell, any security or other financial instrument. The presentation is based on information obtained from sources that the Institute for Global Asset and Risk Management, Inc., considers to be reliable; however, Institute for Global Asset and Risk Management, Inc., makes no representation as to, and accepts no responsibility for, the accuracy or completeness of the information. PAST PERFORMANCE IS NOT AN INDICATION OF FUTURE RESULTS. Institute for Global Asset and Risk Management, Inc., 100 University Drive, Amherst, Massachusetts 01002, Tel: 413-548-7950, Fax: 413-549-0327. Email: info@ingarm.org . WEB: www.ingarm.org.

© 2009 CORTLAND ADVISORY GROUP. ALL RIGHTS RESERVED.

Answer: While few investors would question if stocks are riskier than bonds (although incertain market environments such as high interest rate volatility some bonds are expectedto be riskier than some stocks), most investors believe that direct commodity investmentis by nature riskier than investment in stocks. Research results show that, over the period1991-2008, a Composite Commodity Index* had an annual volatility (15.7%) similar tothat of the S&P 500 (14.4%) and a maximum drawdown (-48.8%) roughly equal to that ofthe S&P 500 (-44.7%).

Myth 1: Commodity Based Investments Are Riskier Than Stock Investments.

*The Composite Commodity Index is an equally weighted portfolio of three major commodity indices (SP GSCI, DJ-UBS, and Bache Indices).

Standard Deviation and Maximum Drawdown (1991-2008)

-60.0%

-50.0%-40.0%

-30.0%-20.0%

-10.0%

0.0%10.0%

20.0%

S&P 500 14.4% -44.7%

Composite Commodity Index 15.7% -48.8%

Annualized Standard Deviation Maximum Drawdown

3

Myth 2: Commodities Add Few Diversification Benefits To Non Commodity Portfolios.

Answer: Investment theory has shown that assets should be considered not as standalone vehicles but on their impact on a risk-adjusted basis (e.g., mean return/standarddeviation) when added to an existing portfolio. Academic research has shown thatcommodities increased the return to risk tradeoff (e.g., information ratios) when added toa traditional stock and bond portfolio and/or a portfolio of traditional and non traditionalassets.

P or t fo l ios A B C D

Annual i zed Ret ur ns 7.73% 7.70% 8.51% 8.39%St andard Deviat ion 7.64% 7.25% 7.66% 7.38%Informat ion Rat io 1.01 1.06 1.11 1.14Maximum Drawdown -20.98% -21.19% -24.84% -24.69%Cor r elat ion wi t h CCI 0.13 0.21

P or t fo l io A Equal Weight s S&P 500 and Barclays Capi t al Bond Aggregat e

P or t fo l io B 90% P or t fo l io A and 10% Commodi t ies

P or t fo l io C 75% P or t fo l io A and 25% HF /CTA/P r ivat e Equi t y/Real Est at eP or t fo l io D 90% P or t fo l io C and 10% Commodi t ies

A B C DInformation Ratio 1.01 1.06 1.11 1.14

0.940.960.981.001.021.041.061.081.101.121.141.16

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Myth 3: Commodities Provide Few Benefits In An Extreme Market Environment.Answer: While commodity based index products may provide risk diversification andreturn opportunities to existing portfolios, many investors do not believe their addition toexisting asset portfolios justify their inclusion in a stock or bond portfolio. The ability ofcommodity products to trade in multiple commodity markets with multiple strategies(e.g., different role, commodity weightings) creates the basis for the ability ofcommodities to provide positive returns in just those market conditions which are mostdifficult for equity based or fixed income security investment.

Average Monthy Return: Ranked on S&P 500 (1991-2008)

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

S&P 500 Total Return Index -3.8% 1.1% 4.8%

Commodity Index: Composite 0.1% 0.9% 0.8%

Average Monthly Return (Worst 72

months)

Average Monthly Return (Middle 72

months)

Average Monthly Return (Best 72

months)

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Average Monthy Return: Ranked on Barclays U.S. Aggregate (1991-2008)

-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

Lehman U.S. Aggregate -0.7% 0.6% 1.7%

Commodity Index: Composite 0.9% -0.2% 1.1%

Average Monthly Return (Worst 72

months)

Average Monthly Return (Middle 72

months)

Average Monthly Return (Best 72

months)

Myth 4: Commodity “Futures” Products Are Riskier Than Commodity “Physical” Products.

Answer: Commodity index products are created using futures contracts instead of actualownership of the underlying physical commodity. In many ways, futures are less risky thanholding an underlying asset directly. First, there is little counterparty risk (you don’t haveto worry that the individual will deliver) since the exchange acts to ensure delivery or toensure daily margin payments on the change in the daily value of your contracted position.Second, futures contracts permit you to manage the ownership of your position, since onecan easily sell one’s contract in an open market rather than in the less transparent andliquid cash market. Lastly, one must remember that futures contracts represent actualownership of the underlying physical asset, but with a future contracted delivery. Thus,while a futures contract may not equal today’s cash price, it will equal the cash price atdelivery.

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Sample Spot and Futures Prices: Months to Delivery

90.0100.0110.0120.0130.0140.0150.0

12 11 10 9 8 7 6 5 4 3 2 1 0

Months To Delivery

Futures Contract Spot asset

Myth 5: Last Year’s Performance Is Indicative Of Next Year’s Performance.Answer: As for traditional stock and bond mutual funds, hedge funds, and CTAs,investment in commodities is often based on past performance. However, for traditionalstock and bond funds as well as various alternative investments such as hedge funds,private equity research has shown that recent past performance provides little evidence asto near term performance. In short, performance persistence does not exist for traditionalassets. Performance persistence does not exist for commodities (the correlation betweenthe annual returns for the Commodity Index Composite in year t and year t+ 1 is -.26 forthe years (1991-2007).

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Commodity Index Composite Return: Annual Return in Year t and Year t+1

-40.00%

-30.00%

-20.00%

-10.00%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year t

Annu

al re

turn

Composite Commodity Index Year t Composite Commodity Index Year t+1

Myth 6: One Commodity Benchmark Is As Good As Another.Answer: Indices are commonly used in studies of investment performance to provide aperformance benchmark which reflects the particular style of an investment manager. Whilebenchmark indices are common in the areas of stock and bond investment, many investors arenot familiar with various benchmark indices in the commodities area. As in the traditionalasset area, there exists no one benchmark which reflects the performance of the asset class.Each commodity index (e.g., Bache Commodity Index, Dow Jones-UBS, and SP GSCI) hasunique weighting, composition, and structural issues (near term/far term futures contracts)just as equity indices (S&P 500, DJ) have their own unique weighting and asset composition.Each commodity index does capture the fundamental benchmark requirements ofinvestibility, systematic, reproducible…

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Return and Risk: 2001-2008 Annualized StandardReturn Deviation

Bache Commodity Index 8.3% 15.0%Diapason Commodity 4.4% 20.8%Dow Jones - UBS Commodity 2.5% 17.9%Rogers International Commodity 6.8% 19.3%SP GSCI 2.3% 25.3%UBS Bloomberg CMCI Composite - 3 Month 8.7% 18.1%

Myth 7: A Single Commodity Index Is Sufficient To Capture Commodity Returns.

Answer: Many commodity investors often choose just one commodity index among thedifferent commodity indices available. Even within an asset class, academic research has neverrecommended holding just one security. For instance, past research has shown that an equallyweighted diversified portfolio of 5-10 randomly selected equity securities will result in aportfolio standard deviation similar to that of the population from which it is drawn. Similarly,an equally weighted portfolio of major commodity indices will have a more consistent returnpattern than any individual index (NOTE WIDELY VARYING DIFFERENTIAL RETURNSYEAR TO YEAR).

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Individual Commodity Index Annual Return Differences From Average Annual Return of Cited

Indices

-15.0%-10.0%-5.0%0.0%5.0%

10.0%15.0%20.0%25.0%

2001 2002 2003 2004 2005 2006 2007 2008

Annu

al R

etur

n Di

ffere

nce

Bache Commodity Index Diapason Commodity

Dow Jones - UBS Commodity Rogers International Commodity

SP GSCI UBS Bloomberg CMCI Composite - 3 Month

Myth 8: Factor Based Return Analysis Provides Little Insight Into Commodities.

Answer: For traditional as well as many alternative investment markets, a set of factorsexist which help to explain returns. These factors are based on the characteristics of thetrading style and the unique asset markets traded. While traditional market factorsprovide little explanatory power, the inclusion of various momentum (e.g. MFSBPhysical) factors does raise the explanatory power.

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T:STAT: Market Factors (1994-10/2008)

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

SP GSCI 1.35 -1.37 2.05 0.88 0.11 0.03

Dow Jones - UBS 1.80 -0.56 1.27 0.28 0.91 0.03

Bache Commodity Index 3.37 -1.17 1.65 0.12 0.38 0.02

Intercept S&P 500 russell 2000Barclays U.S. Government

Barclays U.S. Corporate High

YieldR2

T-Stat: MarketF actors and Momentum (1994-10/2008)

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

SP GSCI 0.66 -1.53 2.26 0.83 0.01 0.17 1.03 2.09 -1.60 0.06

Dow Jones - UBS 0.83 -0.55 1.49 0.03 1.03 0.46 1.11 3.37 -0.87 0.09

Bache Commodity Index 2.27 -1.24 1.95 -0.05 0.44 0.15 1.18 3.90 -1.34 0.11

Intercept S&P 500russell 2000

Barclays U.S.

Governme

Barclays U.S.

Corporate

MFSB Currency Subindex

MFSB Interest

Rate

MFSB Physicals Subindex

MFSB Stock

SubindexR2

Myth 9: Commodity “Futures” Products Have Similar Performance As Commodity Firms.

Answer: Direct investment in commodity based equities is often viewed as an alternativeto investment in commodity index products. In addition, many investors believe theequity based commodity investment is less risky than direct commodity investment. Infact, research has shown that equity based commodity investment often has a higherstandard and drawdown than direct commodity investment through commodity indexproducts.

Comparison Risk and Return Measures: 1991-2008

-60.0%

-40.0%

-20.0%

0.0%

20.0%

40.0%

60.0%

Composite Commodity Indices (Energy, IndustrialMetals, Precious Metals)

7.3% 14.5% 0.50 -42%

Composite S&P 500 Indices (Energy, Metals, Gold) 4.9% 23.0% 0.21 -52%

Annualized Total Return Annualized Standard Deviation

Information Ratio Maximum Draw dow n

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Myth 10: Commodity “Futures” Products Track Those Of Similar Commodity Firms.

Answer: Direct investment in commodity based equities is often viewed as analternative to investment in commodity index products. While a correlation doesexist between commodity indices and their related equity based investments, thecorrelation is often below .60.

Correlation (Three Year Rolling): Composite Equity Commodity Index and Composite Commodity Index

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Dec

-93

Jun-

94

Dec

-94

Jun-

95

Dec

-95

Jun-

96

Dec

-96

Jun-

97

Dec

-97

Jun-

98

Dec

-98

Jun-

99

Dec

-99

Jun-

00

Dec

-00

Jun-

01

Dec

-01

Jun-

02

Dec

-02

Jun-

03

Dec

-03

Jun-

04

Dec

-04

Jun-

05

Dec

-05

Jun-

06

Dec

-06

Jun-

07

Dec

-07

Jun-

08

Dec

-08

12

Myth 11: Commodities Have the Same Benefits As Commodity Firms in Extreme Markets.

Answer: While commodity sub indices and equity based investments which emphasizesimilar commodities are often regarded as substitutes, the real issue is their relativeperformance in extreme markets. Research has shown that unlike an equity based commodityindex (which performs poorly when equity markets perform poorly) a commodity portfoliowhich reflects investment in similar assets does well when the S&P 500 performs poorly andparticipates in up markets when the S&P performs well.

Ranked Returns on S&P 500

-5.0%-4.0%-3.0%-2.0%-1.0%0.0%1.0%2.0%3.0%4.0%5.0%6.0%

Average Monthly Return (Worst 72months)

Average Monthly Return (Middle 72months)

Average Monthly Return (Best 72 months)

S&P 500Composite S&P 500 Indices (Energy, metals, gold)Composite Commodity Indices (Energy, Industrial Metals, Precious Metals)

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Myth 12: A Single Commodity Is Sufficient To Capture Commodity Returns.Answer: When investing in commodities, many investors limit themselves to a singlecommodity such as gold or oil, in the belief that, if one commodity increases in value,other commodities will change in value likewise. Research has shown that an equalweighted portfolio of major commodity indices will have a lower standard deviation(10.4%) and a more consistent return pattern than any individual commodity index.

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Performance 1991-2008Annualized

ReturnStandard Deviation

Information Ratio

Maximum Drawdown

Average of Commodity Subindex Composites 5.4% 10.4% 0.52 -36.0%Commodity Index: Agriculture 1.7% 14.1% 0.12 -48.5%Commodity Index: Energy 7.6% 28.1% 0.27 -59.7%Commodity Index: Industrial Metals 5.8% 18.6% 0.31 -51.6%Commodity Index: Precious Metals 4.9% 14.1% 0.35 -30.6%Commodity Index: Livestock 1.4% 12.6% 0.11 -35.6%

Myth 13: Commodity Indices Offer A Hedge For Inflation.

Answer: Historically commodities have been described as a hedge against inflation. Asmodern economies have evolved inflation and as firms have used modern riskmanagement tools (e.g., futures) to reduce exposure to price increases, the relationshipbetween inflation and commodity price increases may have decreased. While researchmay indicate little immediate impact between inflation and commodity prices, longerterm (twelve months) periods with the highest inflation often reported positive CCIreturns while periods with the lowest inflation often had periods of low CCI returns.

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Annual Inflation and CCI returns: Ranked on Annual Inflation

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

2008 2001 1998 1997 2003 2002 1995 2006 1994 1999 1993 1992 1991 2004 1996 2005 2000 2007

CPI for all urban consumers MoM: All items SA Commodity Index: Composite

Myth 14: Commodity Indices Do Contain Backfill Or Survivor Bias.Answer: Each commodity index was created at a point in time and each with uniquecharacteristics to benefit in certain market environments. Survivor bias exists primarily inthat some commodity indices that were created historically are no longer in existence or arelittle known (e.g., JPMorgan, LMEX); as a result current commodity indices reflect thosewhich have met investors expectations. Backfill bias (a recently constructed index may havebeen created to do well historically over a certain past period) does exist before the date ofinception. Most current indices have been in existence since 2006. The actual benefits ofvarious indices are dependent on the current economic conditions and the unique structureand composition of each contract (e.g., SP GSCI/high energy weights, DJ-UBS/low energyweights, Bache/systematic rebalancing).

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Annual Returns: Comparison Investment Periods

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

Annualized Return Annualized Return

2001-2006 2007-2008

Bache Commodity Index Diapason Commodity

Dow Jones - UBS Commodity Rogers International Commodity

SP GSCI UBS Bloomberg CMCI Composite - 3 Month

Myth 15: Commodity Indices’ Historical Return Reflects Current Potential Return.

Answer: Again, each commodity index was created at a point in time and each withunique characteristics to benefit in certain market environments. Over time variousaspects of each commodity have changed (additional commodities were added, weightshave changed…) such that today’s index may have different composition and weightingstructure than those that existed historically. In short, in order to determine the historicalcharacteristics of today’s index one alternative is to estimate today’s index constructionand use historical commodity returns to determine how today’s index should haveperformed in the past.

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Historical and Current Weight SP GSCI Index Growth

0

100

200

300

400

500

600

Jan-

91

Jan-

92

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

Jan-

01

Jan-

02

Jan-

03

Jan-

04

Jan-

05

Jan-

06

Jan-

07

Jan-

08

SP GSCI Current Sector Weights SP GSCI Historical Index

Myth 16: The Measurement Interval (Monthly, Annual…) Does Not Impact Risk Measurement.

Answer: Many investors believe that investment reports based on annual data providesimilar information as to the performance characteristics of commodity benchmarks overmonthly data. Research has shown that the pattern of inter-year returns (e.g., meanreversion etc.) may result in monthly data not reflecting the risk and return characteristicfrom the use of annual data.

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Comparison S&P 500 Correlations (1991-2008): Annual and Monthly Returns

(0.20)

(0.10)

0.00

0.10

0.20

0.30

0.40

CompositeCommodity

Index

CommodityIndex:

Agriculture

CommodityIndex:Energy

CommodityIndex:

IndustrialMetals

CommodityIndex:

PreciousMetals

CommodityIndex:

Livestock

CommodityIndex:Grains

CommodityIndex: Softs

Monthly Data Annual Data

Myth 17: Commodities Are Speculative Investments.Answer: Commodities are often described as speculative investments in which theunderlying producers of the product often obtain excessive return to risk tradeoff. Ifcommodity investors are speculators, there is little evidence of proper return received forthe risk taken.

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Comparison of Commodity sub index Returns (1991-2008)

Annualized Total Return

Standard Deviation

Information Ratio

Commodity Index: Composite 6.1% 15.7% 0.39 Commodity Index: Agriculture 1.7% 14.1% 0.12 Commodity Index: Energy 7.6% 28.1% 0.27 Commodity Index: Industrial Metals 5.8% 18.6% 0.31 Commodity Index: Precious Metals 4.9% 14.1% 0.35 Commodity Index: Livestock 1.4% 12.6% 0.11 Commodity Index: Grains 1.1% 18.2% 0.06 Commodity Index: Softs 0.4% 17.6% 0.02

S&P 500 Total Return Index 7.9% 14.4% 0.55 Barclays Capital Bond Aggregate 7.0% 3.9% 1.81

Myth 18: Socially Responsible Commodity Products Do Not Exist.Answer: Many commodities indices are not regarded as socially responsibleinvestments in that certain commodities such as coal and oil are regarded bysome as destructive to the natural environment. While there are many sides tothis debate, commodity indices do exist which are structured in such a way asto provide investment into a select set of commodities which are generallyregarded as “Green”. In this, commodity products exist which may be regardedas socially responsible just as there exist equity indices and products marketedas socially responsible.

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Green Indices Jan 07 - May 09 Annualized

ReturnStandard Deviation

Information Ratio

Maximum Drawdown S&P 500

Barclays Capital Bond Aggregate

Bache Commodity Green Index 5.8% 27.4% 0.21 -48.7% 0.54 0.35

Biofuel Indices Bunge Four Blend Biofuel Price Index 1.8% 33.9% 0.05 -60.2% 0.48 0.09 MLCX - Biofuels TR Index 8.1% 29.2% 0.28 -44.0% 0.38 0.30 S&P GSCI Biofuel TR Index -1.8% 28.6% -0.06 -44.5% 0.29 0.34

UBS Diapason Global Biofuel TR Index -2.0% 27.1% -0.07 -44.1% 0.34 0.37

Average Biofuel Indices 1.5% 29.7% -48.2% 0.37 0.27Avg. of S&P Global/Wilderhill Clean Energy Index -17.6% 44.9% -0.39 -75.9% 0.89 0.29

Correlation with

Selected References

Erb C. and C. Harvey, “The Tactical and Strategic Value of Commodity Futures,” Financial Analysts Journal,Volume 62, Number 2, (2006).

Fama, E. and K. French, “Commodity Future Prices: Some Evidence of Forecast Power, Premiums, and theTheory of Storage,” Journal of Business, Volume 60, Number 1, (1987), pp. 55-73.

Fama, E. and K. French, “Business Cycles and The Behavior of Metals Prices,” Journal of Finance, Volume 43,(1988), pp. 1075-1093.

Geman, H. Commodities and Commodity Derivatives. Wiley Finance. 2005.

Gorton, Gary B. and Rouwenhorst, K. Geert, “Facts and Fantasies about Commodity Futures,” Yale ICF WorkingPaper No. 04-20, (2005).

Schneeweis, T., R. Spurgin, and H. Kazemi, “Momentum in Commodity Indices,” Journal of AlternativeInvestments, Spring, (2008).

Schneeweis, Thomas, “The Benefits of Commodities,” INGARM, May, 2009.

Schneeweis, T., A Review of Commodity Indices, AIA, (2007).

Williams, Jeffrey, The Economic Functions of Futures Markets, Cambridge University Press, (1986).

Williams, J. and B. Wright, Storage and Commodity Markets, Cambridge University Press, (1991).

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