victor aft hk iqpc conf nov 2007 vf

Commodity Indexing: Is this The Next Important Trend?

Innovator in alternative investment products

by Victor Sperandeo

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Will commodities be the preferred risk management tool as well as a source of returns?

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Understanding the source of commodities returns

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How correlated are the components of a commodity index?

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Second and Third Generation commodity indexes: Beyond long only

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Analyzing the value of commodities in a portfolio allocation


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60% Stocks40% Bonds

55% Stocks35% Bonds10% Commodities



7% 8% 9% 10% 11% 12%

11.7%

11.6%

11.5%

11.4%

11.3%

11.2%

11.0%

Annu

aliz

ed R

etur

n

Annualized Standard Deviation

Stocks: S&P 500 Index, Bonds: Lehman Aggregate Bond Index, Commodities: GSCI

Source; Alpha Financial Technologies, LLC.


Source; Goldman Sachs.Correlations between quarterly returns of the S&P GSCITM

in local currency and the financial asset. For bonds: 10y swap rates converted into total returns of the respective country in local currency. For Equity: S&P500 Total Return Index, Toronto 300TR, Nikkei 225, CAC 40, DAX, Amsterdam Stock Exchange

Index (AMS), SBC Index & Zurich Stock Exchange Index (SMI), FTSE -

UK all share.

Negative Correlation

S&P GSCITM

Correlation with Global Financial Assets Dec 1987 –

Sep 2007 Quarterly Correlations


-2.0%

-19.7%

-17.6%

-15.5%

-10.8%

-20.0%

5.1%

16.6%

5.2%

-10.0%

-25.0% -20.0% -15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0%

GSCITR

Bonds

Cash

NAREIT Real Estate

World Equity

Australian Equities

Canadian Equities (TSE)

Small Cap Stocks

S&P 500

60/40 Portfolio

Commodities Perform Best When the Financial Portfolio Performs Worst

1970-Oct 2007

Source; Goldman Sachs.1. Unless otherwise specified, underlying data begins in January

1970 Australian Equities data starts in January 1971, World Equity data in December 1973 and NAREIT data in December 1972

Will Commodities be the preferred Risk Management Tool as well as a Source of Returns

55% S&P 50035% Lehman Agg

1986-2006 10% GSCI S&P 500 Lehman Agg Bond GSCI TR

Compound Annual 11.54% 12.95% 8.33% 9.47%Annualized STD 8.78% 14.88% 4.35% 18.49%Sharpe Ratio 0.74 0.53 0.79 0.24Maximum Drawdown -19.41% -44.73% -5.15% -48.26%

Annual Stats

Commodities are an Under Recognized Source of Returns

Commodities SHOULD BE

the preferred Risk Management Tool

Commodities are significantly negatively correlated to stocks, bonds & real estate►This implies that portfolio volatility can be significantly reduced by allocating to commodities

Commodities provide a hedge against rising inflation

Commodities perform Best when other asset classes perform Worst►commodities have the largest impact on a portfolio when the other asset classes experience their

worst returns

Commodities are the most directly tied to “current”

Economic conditions►The expected returns of Financial assets tend to fall in high levels of economic activity while

commodities tend to perform best in periods of high economic activity

Source; Alpha Financial Technologies, LLC.

Understanding the Source of commodity Returns

Commodity Index returns are derived from 5 sources:►Excess Return►Collateral Yield►Roll Return (risk transfer premium)►Rebalancing►Diversification

Excess Return:●

Excess return is the change in price of a commodity futures contract. For example an oil contract purchased at $89 and sold at $93 would produce a return of 4.49%.

Roll Return:●

Roll return occurs as a result of selling a futures contract (typically the near or current month) and purchasing a longer dated contract. This is referred to as rolling a futures position.

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If the contract price selling is priced above

the contract your purchasing, this creates a Positive Roll. A profit is achieved from simply rolling from the near month to a longer dated contract.

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If the contract your selling is below

the contract your purchasing, this creates a Negative Roll Yield

Collateral Yield:●

Unlike stocks, futures contracts are not purchased using cash but rather some for of collateral. A fraction of the notional amount is typically posted as

collateral in the form of (T Bills). The interest earned on the T Bills in this example is referred to as Collateral Yield.

How Correlated are the components in a Commodity Index

Sugar Cotton Cocoa Coffee Grains Livestock Energy Ind. Met Prec Met

Sugar 1.00 -0.01 0.08 -0.04 0.18 -0.05 -0.10 0.10 -0.00

Cotton -0.01 1.00 0.10 -0.03 0.18 0.05 0.06 0.24 0.09

Cocoa 0.08 0.10 1.00 0.02 -0.05 -0.04 0.08 0.09 0.13

Coffee -0.04 -0.03 0.02 1.00 0.06 -0.07 -0.05 0.07 0.02

Gains 0.18 0.18 -0.05 0.06 1.00 0.11 0.00 0.13 0.02

Livestock -0.05 0.05 -0.04 -0.07 0.11 1.00 0.02 -0.03 0.03

Energy -0.10 0.06 0.08 -0.05 0.00 0.02 1.00 -0.00 0.18

Ind Met 0.10 0.24 0.09 0.07 0.13 -0.03 -0.00 1.00 0.14

Prec Met -0.00 0.09 0.13 0.02 0.02 0.03 0.18 0.14 1.00

Based on month-end price changes for the period 1985 - March 31, 2003

Stocks within a Portfolio are approximately 0.65 Correlated to Commodities

Second and third generation Commodity Indexes –

Beyond Long Only

Commodity Facts:●

Commodities are Cyclical●

Commodities Trend Differently than stocks●

As proven by Claude B. Erb and Campbell R. Harvey in their paper

entitled “The Tactical and Strategic Value of Commodity Futures, the median compound annual excess return of individual commodity futures has been close to zero.

Heightened awareness and demand for commodities has caused a race to construct a “Better Commodity Index”

by most major investment banks and index companies. A sample includes:●

JP Morgan IGAR●

UBS Constant Maturity Index●

S&P Commodity Trends Indicator

These second and third generation commodity indexes allow investors to:●

Take advantage of the

Cyclicality of commodity futures by going both Long and Short●

Exploit futures prices at different points of the time curve●

Take advantage of certain commodities which are exhibiting greater positive price momentum than others

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Avoid steep losses in the event of a prolonged sell off in a certain commodity

Is there a Sound Reason to go Beyond Long Only?

$1 Invested In commodities in 1920 is worth about $1 Today

2.20

1.80

1.40

1.00

0.601920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Above represents the 17 commodities of the CRB Index adjusted for inflation


Beyond Long Only

Commodities are Cyclical

Stocks Exhibit a Substantially Different Historical PatternNotice the Line is upward sloping over longer periods: Exhibits No Real

Cyclicality


Beyond Long Only


Beyond Long Only

There Has To Be A Better Way! Looking back on the Corn Chart we see:●

Most Commodities Have Demonstrated Distinct, Polonged

Cycleswith prolonged periods of Negative Return

4 Years 4 Years

Some Second and Third generation Commodity Indexes are designed to take advantage of this:●

Cyclicality ●

Loss prevention (lower StDev)


Beyond Long Only

For simplicity, lets compare the S&P GSCI vs. S&P CTI.●

The S&P GSCI

is a long only commodity index and can only increase in value as commodities rise.

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The S&P CTI

is a long and short rules based commodity index (technically called an indicator by S&P)and it can increase in value regardless of whether commodities are rising or falling.

-60.00%

-40.00%

-20.00%

0.00%

20.00%

40.00%

60.00%

80.00%

Feb-

00

Jun-

00

Feb-

03

Nov

-00

May

-00

Aug-

00

Oct

-00

Jan-

00

Dec

-00

Oct

-04

Jan-

03

Sep-

04

Nov

-96

Jun-

96

Sep-

00

Nov

-98

Oct

-98

Aug-

98

Dec

-98

Jan-

99

Feb-

99

Sep-

98

Nov

-01

Dec

-01

Jul-9

8

Jan-

02

Feb-

02

May

-98

Jun-

98

Oct

-01

GSCI S&P CTI

15 Best & Worst performing rolling 12-month periods, 1991-2006

Best Periods Worst Periods

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S&P GSCI

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S&P Commodity Trends Indicator (S&P CTI)


Beyond Long Only

Statistics 1991-Sept 2007

S&P CTI PR S&P GSCI PR

Compound Annual 6.13% 2.04%Annualized STD 10.17% 18.70%Sharpe Ratio 0.2 -0.1Maximum Drawdown -18.57% -52.52%

Median 1-mo Return 0.30% 0.35%Avg 1-mo Return 0.54% 0.31%Raw Monthly STD 2.93% 5.40%# of Monthly Profits 110 108# of Monthly Losses 91 93% Wins 54.73% 53.73%Avg 1-mo Loss -1.94% -4.18%Worst 1-mo Period -5.71% -14.49%

Median 12-mo Return 5.50% 0.88%Avg 12-mo Return 7.24% 4.22%# of 12-mo Profits 138 99# of 12-mo Losses 52 91% Wins 72.63% 52.11%Avg 12-mo Loss -3.93% -14.58%Worst 12-mo Period -14.11% -42.02%

Annual Stats

Monthly Stats

Rolling 12-month Stats

Long/Short Long Only

Compounded Returns 6.13% 2.04%


Beyond Long Only

Annual Returns: 1991-Sept 2007

Significant long only out performance in these years still resulted in lower annualized returns due to significant losses incurred in 93, 97, 98, 01 & 06

S&P CTI PR S&P GSCI PRDec-91 -5.49% -11.19%Dec-92 6.72% 0.81%Dec-93 1.99% -14.98%Dec-94 9.17% 0.82%Dec-95 6.57% 13.76%Dec-96 26.16% 27.18%Dec-97 -5.44% -18.41%Dec-98 3.63% -38.83%Dec-99 7.10% 34.38%Dec-00 19.96% 41.10%Dec-01 -4.35% -34.31%Dec-02 -4.64% 29.93%Dec-03 4.54% 19.49%Dec-04 32.07% 15.64%Dec-05 9.33% 21.61%Dec-06 5.23% -19.07%Sep-07 -1.69% 15.00%

Long/Short Long Only


Beyond Long Only

Why the Significant Difference in Volatility and Return between Long only and Long & Short

A

B

Somewhere between Points A & B, the long/short index will get short (usually closer to A than B) and actually profit or rise in value from the down trend while the long only index can only lose in this precipitous decline

Summary

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Commodities are a significant source of portfolio Diversification

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Commodities Perform Best When the Financial Portfolio Performs Worst

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Commodities Provide a Hedge against Rising Inflation

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Commodities are Cyclical

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Some Second and Third Generation Commodity Indexes take advantage of this Cyclicality

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Long and Short Commodity Indexes can profit in both rising

and falling

commodity prices

victor aft hk iqpc conf nov 2007 vf

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