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Insights on...COMMODITY INDEX DESIGN
Jordan Dekhayser, CFAPortfolio Manager,
Global Index Management
Institutional investors generally hold commodities either to diversify their equity and
fixed-income holdings or to protect against inflation. One way to gain this exposure is
through futures-based commodity indexes.
Over the last few years, increasing amounts of assets have been benchmarked to commodity
futures-based indexes1, whose performance is subject to variables such as changing spot prices
and a futures-specific return component called roll yield.
First-generation commodity indexes such as the DJ-UBS Commodity Index and S&P
Goldman-Sachs Commodity Index (GSCI) were innovative when they were conceived because
they provided investors with a broad, measurable and investable benchmark for a relatively
inaccessible asset class. They were developed using methodology similar to that of prevailing
equity or fixed-income indexes: define the universe; choose a metric to weight each commoditybased on its relative importance in the marketplace; and create an index. Additionally, com-
modity indexes hold futures contracts that expire periodically, presenting another decision
factor when creating an index. First-generation indexes generally did not explicitly incorporate
other sources of return in commodity futures, such as momentum and alternative roll meth-
odologies. Considering these features collectively, we arrive at a set of key variables to analyze a
commodity index: commodity selection and weighting, dynamic versus static allocation and
roll methodology.
In recent years, a number of commodity indexes were created that seek to improve upon the
design of first-generation indexes. One example is the ABCI, which is constructed to maintain
exposure to the desirable characteristics of commodities and to provide a high correlation to first-
generation commodity indexes. The latter feature may be important for investors using either the
DJ-UBS or S&P GSCI as their stated commodities benchmark. Furthermore, the ABCI is designedto minimize exposure to undesirable
characteristics of commodity indexes and
to incorporate new and desirable features.
The actual, in-sample results including
risk-adjusted returns, volatility and down-
side protection compare favorably with
first-generation indexes.
C O M M O D I T Y I N D E X E S : D E S I G N M A T T E R S
ALTERNATIVE BENCHMARK COMMODITY INDEX
Northern Trust uses the Alternative Benchmark Commodity Index (ABCI) to
offer clients exposure to commodities. This index, which tracks 19 different
energy, metals and agricultural commodities, is well-aligned with our proprietary
Intelligent Indexingprocess that preserves wealth by managing risks, liquidity
and transactions costs.
Pursuant to an exemption from the Commodity Futures Trading Commission in connection with accounts of qualified eligible persons, this brochure is not required t o be, and hasnot been filed with the Commission. The Commodity Futures Trading Commission does not pass upon the merits of participating in a trading program or upon the adequacy oraccuracy of commodity trading advisor disclosure. Consequently, the Commodity Futures Trading Commission has not reviewed or approved this trading program or this brochure.
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COMMODITIES: KEY TERMS FOR INVESTORS
Total return:The risk-free rate (typically the three-month U.S. Treasury bill rate) plus an
excess return. Excess return:The spot return plus the roll yield.2
Spot return:The return of the active futures contract. During a roll period, the active
futures contract changes to the contract being rolled into.*
Roll yield: The return generated from moving out of an expiring contract and into a new
contract. This may be either positive or negative and is affected by borrowing costs, storage
costs and convenience yield.
Borrowing and storage costs: Charges related to holding the physical commodity. Also
known as the cost-of-carry. All else being equal, futures prices will trade higher than spot
prices due to these costs.
Convenience yield:The benefit of having supplies available for commercial purposes.
When supplies are tight, this benefit tends to be high. When supplies are ample, this
benefit tends to be low. The convenience yield interacts with borrowing and storage
costs to determine whether the futures curve is in contango or backwardation.
Contango: A curve shape where the commodity futures price is higher than the spot
price (Chart 1).
Backwardation:A curve shape where the futures price is lower than its spot price
(Chart 1).
CurrentSpot Price
Time to Expiration
Futures
Price
CurrentSpot Price
Time to Expiration
Futures
Price
Source: Northern Trust
CONTANGO: FUTURES > SPOT BACKWARDATION: FUTURES < SPOT
CHART 1: TERM STRUCTURE: CONTANGO VS. BACKWARDATION
*In commodity indexes the spot return generally refers to a futures contract and not the commodity for immediatedelivery. This is unlike indexes in other asset classes where the spot return typically refers to the physical securities.
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FUTURES CURVE SHAPES
The futures curves shape is important to investors because it can create a hurdle that the spot
return must overcome to create positive excess return. In some instances, the curve can be so steep
that it is unlikely that the spot return will exceed this hurdle, making it questionable whether onewants to hold that specific commodity at full index weight. Furthermore, futures curves can change
their shapes, moving from contango to backwardation (sidebar, p. 2) or vice versa, creating a key
risk to certain strategies that seek to capitalize on the current shape of the curve.
The spot markets outlook also is critical. In fact, the correlations between the spot return and
the roll yield tend to be negative, indicating that a commodity with a negative roll yield tends to
have a positive spot return and vice versa (Table 1). Lastly, in addition to the curves slope, the
degree of its concavity or convexity is important in determining where on the curve is the optimal
point to hold futures positions in order to maximize roll yield. Merely holding longer-dated futures
contracts does not necessarily increase investor roll returns. Regardless of whether a strategy
is algorithmically positioned to maximize the roll yield or simply holds longer-dated futures
contracts, the greatest liquidity and open interest generally concentrate in the front months,
potentially reducing the size of roll-yield positioning opportunities.For investors, this ultimately means that the way a commodity or commodity index invest-
ment is made can significantly affect final investment results. For example, in 2012, the roll yield
of natural gas was 42% in the DJ-UBS Index.3
An index with a static allocation would be
unable to incorporate this information into the
commoditys weighting in the index. However,
an index that is designed to incorporate this
information contemporaneously can help
investors reduce the impact from a negative
roll yield (high hurdle rate).
COMMODITIES DIVERSIFICATIONAND INFLATION PROTECTION
The two commonly cited reasons for commodi-
ties investing are diversification and inflation
protection. Diversification is provided through
low correlations to other asset classes (equity
and fixed income, Table 2). For example, the
commodity indexes in Table 2 have a correlation
between 0.36 and 0.49 to the Standard & Poors
(S&P) 500. This diversification can help improve
the efficient frontier of a multi-asset-class portfolio.
TABLE 1: CORRELATION OF SPOT RETURN VS. ROLL YIELD (DJ-UBS INDEX)
Agriculture Energy
Industrial
Metals Livestock
Precious
Metals
0.30 0.16 0.07 0.48 0.13
Sources: S&P Dow Jones, Bloomberg, Northern Trust.
Correlations reflect 10-year monthly return data thru 12/31/2012.
TABLE 2: COMMODITY INDEX CORRELATIONS TO OTHER ASSET CLASSES
10-Year Correlation Matrix
ABCI DJ-UBS S&P GSCI S&P 500
Barclays
US Agg
ABCI 1.00 0.93 0.94 0.36 0.03
DJ-UBS 0.93 1.00 0.89 0.49 0.06
S&P GSCI 0.94 0.89 1.00 0.42 0.03
S&P 500 0.36 0.49 0.42 1.00 0.04
BarclaysUS Agg
0.03 0.06 0.03 0.04 1.00
Sources: S&P Dow Jones, AIA, Bloomberg, Northern Trust.Correlations reflect 10-year monthly return data thru 12/31/2012.
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Furthermore, individual commodity sectors have relatively low correlations to each other,
underscoring the importance of maintaining broad-based commodity exposure in an index. As a
frame of reference, the average pair-wise correlation between the five commodity sectors detailed
in Table 3 is 0.25, as opposed to a value of 0.61 for S&P 500 sectors.
4
Low sector correlations incommodities are due to the disparate risk exposures of each commodity sector, as well as the lack
of a unifying source of return across all commodities such as exists for equities (market beta). For
example, agricultural prices are driven by, among other factors, weather in their specific growing
regions.5The price of gold, however, relates more to global macroeconomic factors such as real
interest rates and expected inflation rather than industrial demand and thus can help diversify
against the risk of depreciating and potentially devalued currencies. Having a meaningful exposure
to each commodity sector can thus add desirable diversification properties to an investors overall
asset allocation and within the commodity allocation.
Inflation protection is particularly relevant, given
concerns that loose U.S. monetary policy and highcommodities demand from developing countries could
spur inflation. Commodity indexes have a high correla-
tion to inflation, currently around 0.61 0.68 (Table 4),
providing some level of protection against higher prices.
The reason for this is rather straightforward. The U.S.
Consumer Price Index (CPI) includes exposure to many
of the raw commodities that comprise commodity bench-
marks. For example, food and energy make up around
25% of CPI on a value-weighted basis but can account for
more than half of the indexs volatility.6Holding exposure
to some of the inputs to CPI via a commodity index can
help mitigate the deleterious impact of inflation on pur-chasing power, or more directly, on CPI-linked liabilities.
TABLE 3: COMMODITY SECTOR CORRELATION MATRIX (SPOT RETURNS FOR DOW JONES-UBS
COMMODITY SECTOR)
Spot ReturnCorrelations Agriculture Energy
Industrial
Metals Livestock
Precious
Metals
Agriculture 1.00 0.28 0.41 0.04 0.42
Energy 0.28 1.00 0.44 0.07 0.30
Industrial Metals 0.41 0.44 1.00 0.12 0.42
Livestock 0.04 0.07 0.12 1.00 0.11
Precious Metals 0.42 0.30 0.42 0.11 1.00
Sources: S&P Dow Jones, Bloomberg. Correlations reflect 10-year monthly return data 12/31/2002 12/31/2012.
TABLE 4: INDEX CORRELATIONS
TO CPI
CPI
ABCI 0.65
DJ-UBS 0.61
S&P GSCI 0.68
S&P 500 0.27
Barclays US Agg 0.00
Sources: S&P Dow Jones, AIA, BLS, Bloomberg,Northern Trust. Correlations reflect 10-yearmonthly return data 12/31/2002
12/31/2012. CPI lagged 1 month.
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COMMODITY SELECTION AND WEIGHTING
Every benchmark methodology, regardless of asset class, must specify which positions to hold
and in what weights. For equities and fixed income, there is a general consensus on construction
of a beta index. The instruments included are representative of the asset class and are sufficientlyliquid to maintain a substantial amount of assets that may be benchmarked to them. In this vein,
commodity indexes look to include commodities that are economically significant and have
enough open interest and trading volume to build investable benchmarks. However, commodity
indexes differ dramatically from their equity and fixed-income brethren in that they can have
substantially different weights for specific commodities and commodity sectors (Chart 2) while
still claiming to represent the asset class.
An individual stocks weight in an equity index is typically driven solely by the stocks free-float
market capitalization as a percentage of the entire indexs free-float market cap (static weighting).
However, to determine an individual commoditys weight within a commodity index, most indexes
use some combination of production and liquidity measures (static weighting). Furthermore, some
commodity indexes impose artificial caps on the weight assigned to commodities and commodity
sectors. These measures can result in drastically different commodity weights depending on howthey are incorporated. For example, depending on which commodity index they choose, an investor
would receive an energy allocation of either 69% (S&P GSCI) or 32% (DJ-UBS).
0%
10%
20%
30%
40%
50%
60%
70%
80%
Agriculture Energy Industrial Metals Precious Metals Livestock
31%
16%
23%
32%
69%
42%
19%
7%10%
13%
4%
19%
6% 5% 5%
DJ-UBS S&P GSCI ABCI (Max)
Sources: S&P Dow Jones, AIA, Bloomberg, Northern Trust. Data as of 12/31/2012.
CHART 2: COMMODITY SECTOR WEIGHTS
Investors can
receive drastically
different exposure to
commodities, depending
on the benchmark.
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The construction of the ABCI incorporates some of the uniqueness of commodities. Though the
weight of a commodity in, for example, the S&P GSCI depends solely by its relative production,
the weight of an individual commodity in the ABCI hinges not only on production and liquidity
but also on recent momentum. Table 5 highlights key distinctions between index methodologies.
DYNAMIC VS. STATIC ALLOCATION: THE CASE FOR MOMENTUM IN COMMODITIES
Momentum is important to all asset classes but is uniquely important to commodities because
many commodities are consumable assets with both a limited shelf life and a limited supply.
For example, adjusting wheat production to counter a supply shortage is impossible until the
following years harvest. Thus, the price of wheat can be persistently strong in a market that is
undersupplied in the short- to intermediate-term. Another example would be a market that is
oversupplied, which could lead to a large amount of contango as supplies are placed in inven-tory. During 2012, this was the situation in the natural gas market, which had a highly negative
roll yield. Depending on ones outlook for the natural gas market, an investor could reasonably
conclude that the expected return on a long futures position in natural gas may be negative.
The momentum approach of the ABCIs commodity-by-commodity dynamic allocation is a
look-back strategy. To determine the sign of a momentum signal, the ABCI methodology looks
to a futures index series incorporating the excess return (spot plus roll) of each commodity. The
strategy will compare each indexs current value to three trailing periods and create an index position
with a target weight equal to 40%, 60%, 80% or 100% of the maximum weights in Chart 2.
The economic rationale discussed here for momentum in commodities is not relevant to, say,
equity investors whose expectedreturns are generally positive. When commodity market dynamics
create a hurdle rate that is either insurmountable or extremely high, less exposure to that particular
commodity may make sense. The spot dynamics, however, must also be considered to determinewhether to increase or decrease exposure to a commodity futures contract. By using thefutures
index series to determine the momentum signals, which ultimately determine the weight of
individual commodities, the ABCI captures the interaction of spot return and roll yield. The
index does not distinguish which source of return is dominant, but the result will be an index that,
all else equal, will allocate away from commodities with negative roll yields (contango) and toward
TABLE 5: INDEX METHODOLOGY HIGHLIGHTS
Commodity Weighting
Method Exposure Caps
Resulting Energy Weight as
of 12/31/2012
DJ-UBS Static. Liquidity (2/3weight) and production(1/3 weight)7
Exposures capped at thecommodity group, sectorand single commoditylevel (33%, 25% and15%, respectively
32%
S&P GSCI Static.Production-weighted
None 69%
ABCI Dynamic. Liquidity (2/3weight) and production(1/3 weight) determinemaximum weights
Sector minimum andmaximum exist, but nonecurrently affect weights
42%
Sources: S&P Dow Jones, AIA, Bloomberg, Northern Trust.
Momentum in
commodities is unlike
that of other investable
asset classes due to supply
and demand dynamics.
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commodities with positive spot returns. Relying on only spot orroll ignores the relationship of the
two and can lead to a sub-optimal commodity allocation.
The ABCI incorporates these momentum signals, acknowledging fundamental and technical
reasons for the persistence of momentum in the short- to intermediate-term in spot and futuresmarkets (Gunzberg and Kaplan [2007], Schneeweis et al. [2008]). From a technical standpoint,
momentum is a popular strategy employed by active managers (Asness et al. [2012]). The ABCI
seeks to capture the return associated with momentum in a rules-based approach, which may
result in a more cost-effective solution for investors trying to capture this source of return.
Incrementally, the dynamic asset allocation strategy that ABCI employs has added 2.5% to
annual returns with a factor volatility of 3.6% (Sharpe Ratio of 0.75).8Furthermore, the return
attributed to dynamic weighting has been positive for 17 of the 19 commodities included in the
index, suggesting these results are significant (Chart 3).
Importantly, the dynamic asset allocation of the index is implemented concurrently with a cash
position. At the aggregate level, the dynamic asset allocation and defensive cash position in the
ABCI result in an index expected to have a long-run average of 70% exposure to commodities
and 30% exposure to cash. Since 2005, ABCI has had an actual allocation to commodity futures
and cash averaging 72% and 28%, respectively. Two-thirds of the time, the commodity exposure
was between 58% and 85%. Rarely does the index go above 90% or below 50% (Chart 4, p. 8).
Taken together, these features historically have resulted in lower volatility and improved risk-
adjusted returns (Table 6, p. 10). Investors who make asset allocation decisions on a risk-weighted
basis may find benefits because they can increase risk-based allocations to other strategies.
2
0
2
4
6
8
10
C
omposite
Energy
BrentCrude
Gasoil
HeatingOil
Na
turalGas
Unleaded
W
TICrude
Metals
A
luminum*
Copper
Gold
Nickel*
Silver
A
griculture
Cattle
Coffee
Corn
Hogs
Soybeans
Cotton
Sugar
Wheat
3.9
2.5
4.7
3.7
2.7
6.7
2.9
3.6
2.01.9
4.4
8.4
0.1
0.9
1.2
0.7
2.01.8
2.5
0.6
1.3
4.7
0.7
January 1991 May 2012; *January 2002 May 2012
Source: AIA.
CHART 3: DYNAMIC ASSET ALLOCATION INVESTMENT RESULTS
The ABCI provides
access to additional
sources of return, such as
momentum and relative
roll, beyond traditional
commodity indexes.
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ROLL METHODOLOGY
Roll yield is a very important concept for commodity index investors since the rolling of futures
contracts directly affects their total return. Over short periods of time, the spot return tends to
dominate due to its higher volatility. However, over long time periods, the rolling of futures can
significantly affect the total return of a commodity portfolio. Therefore, understanding the roll
methodology employed, as well as its effect on risk and return, is critical.
DJ-UBS and S&P GSCI roll their contracts from the expiring contract to the next active
contract during a concentrated five-day window near the beginning of the month. The index
provider specifies these periods; therefore, with an accurate estimate of assets benchmarked toeach index, one can predict the volumes that passive indexers must trade in order to track the
benchmark. This feature can be a double-edged sword. On one hand, this volume advertising
can allow for other participants to enter the market to offset the index supply and demand. On
the other hand, non-index market participants may incorrectly forecast anticipated trade volumes
and either exacerbate or even invert the expected index effect. Regardless, the fewer days in the
roll period, the more impact a price event that unevenly affects contracts being rolled on one
of those days will have on the index. The ABCI employs a daily roll methodology designed to
completely allocate exposure away from the nearby futures contract before some of the common
indexes start their rolls. Furthermore, by rolling a small amount of the position held each day,
investors tracking the ABCI may have less market impact than with a concentrated roll cycle.
The other result of the ABCI daily roll is that the index has a longer average maturity than
an index that holds similar contracts. In other words, the ABCI relative to its peers becomes
underweight the contract that is most active in other commodity benchmarks and overweight
the next contract month. Historically, ABCIs relative roll strategy has added 1.5%9to its annual
returns versus indexes with roll cycles like DJ-UBS or S&P GSCI. The volatility around this
factor is 1.0%, leading to a Sharpe Ratio of 1.58 for the relative roll factor. The positive relative
roll factor in 18 of the indexs 19 commodities indicates that this factor as well as the
momentum factor is significant.
1/2/2006 1/2/2007 1/2/2008 1/2/2009 1/2/2010 1/2/2011 1/2/2012 12/31/12
40%
50%
60%
70%
80%
90%
100%
Futures Allocation Average Allocation
Sources: AIA, Northern Trust.
Two thirds of the time, the %allocation to commodities isbetween the green lines.
CHART 4: PERCENT OF ABCI HELD IN COMMODITIES (VERSUS CASH)Over long time periods,
the rolling of futures can
significantly affect the total
return of a commodity
portfolio. Therefore,
understanding the roll
methodology employed,
as well as its effect on risk
and return, is critical.
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DYNAMIC ALLOCATION AND ROLL METHODOLOGY MANAGING TURNOVER
The interaction of dynamic allocation and roll methodology plays a unique role in the ABCI.
Intuitively, one associates dynamic strategies as having higher turnover. One important feature
of all commodity benchmarks is that due to the expiration of their holdings, high turnover is
common and expected. ABCI is designed with a unique feature, however, to keep turnover at
a manageable level to control transaction costs. To accomplish this, the index incorporates the
changing asset allocations with the daily rolls of futures contracts. For example, on a given day,
the index may be rolling five contracts of WTI crude oil futures out of the nearby contract and
into the next active contract. On the same day, crude prices drop, requiring a smaller position inWTI crude oil. In this case, the index may roll out of the five nearby contracts but not buy five
contracts in the next active month. In addition to this feature, not being a fully invested index
also reduces the overall turnover of the ABCI, all else equal. A comparison of index turnover
shows that ABCI has turnover in line with its peers and falls in between the turnover of DJ-UBS
and S&P GSCI. ABCI historically has had about 10% more turnover than DJ-UBS and around
30% less turnover than the S&P GSCI.
COMMODITY INDEXES RESULTS
Over the last five years as of December 31, 2012, the ABCI outperformed DJ-UBS by 6.4% and S&P
GSCI by 9.3% per annum while delivering lower risk over the same period (15.5% versus 21.9%
for DJ-UBS and 27.4% for S&P GSCI). Taken together, this led to a Sharpe Ratio of 0.07 for ABCI
versus 0.24 for DJ-UBS and 0.30 for S&P GSCI. Table 6 shows a snapshot of risk and return
characteristics as of December 31, 2012, and Table 7 details historic returns beginning in 2002.10
-1
0
1
2
3
4
5
6
Composite
Energy
BrentCrude
Gasoil
HeatingOil
NaturalGas
Unleaded
WTICrude
Metals
Aluminum*
Copper
Gold
Nickel*
Silver
Agriculture
Cattle
Coffee
Corn
Hogs
Soybeans
Cotton
Sugar
Wheat
1.5
1.10.8
0.5
1.4
0.10.2
1.5
4.3
0.6
1.2
0.3
2.01.7
2.0
5.4
0.4
2.0
0.6
1.71.7
0.0
1.8
1.3
January 1991 May 2012; *January 2002 May 2012
Source: AIA.
CHART 5: RELATIVE ROLL FACTOR INVESTMENT RESULTSOne important feature of
all commodity benchmarks
is that due to the expiration
of their holdings, high
turnover is common and
expected. ABCI is designed
with a unique feature,
however, to keep turnover
at a manageable level to
control transaction costs.
ABCI has delivered higher
annual returns on both an
absolute and risk-adjusted
basis over the past five
years, outperforming
DJ-UBS and S&P GSCI
by 6.4% and 9.3% per
annum, respectively.
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END NOTES
Asness, C. et al. (2012) Value and Momentum Everywhere, preprint.
Gunzberg, J., and Kaplan, P., 2007, The Long and Short of Commodity Futures Index Investing: The Morningstar Commodity Index Family, in H. Till and J. Eagleeye (eds)
Intelligent Commodity Investing: New Strategie s and Practical Insights for Informed Decision Making, pp 241 274 (Risk Books).Greer, R. J., 2012, Intelligent Commodity Indexing: A P ractical Guide to Investing in Commodities, McGraw-Hill.
Schneeweis, T., Kazemi H., and Spurgin, R., 2008. Momentum in Asset Returns: Are Commodity Returns a Special Case? The Journal of Alternative Investments, 10 (4).
Spurgin R., Schneeweis, T., Kazemi, H., and Martin, G., (Revised 2012), The Alternative Benchmark Commodity Index: A Factor-based Approach to CommodityInvestment, AIA Research Report.
Jordan Dekhayser, CFA, is a member of t he Index Advisory Committee (IAC) of the ABCI.
The methodology of, and intellectual property rights in, the Alternative Benchmark Commodity Index is owned by Alternative Investment Analytics LLC, and may be coveredby one or more pending patent applications.
FOOTNTOES
1 As of 8/31/2012, there was $287 billion and $209 billion in gross and net notional index investment, respectively
http://www.cftc.gov/ucm/groups/public/@marketreports/documents/file/indexinvestment0812.pdf.2 For a detailed recap of the history of commodity research and how it relates to roll yield, see Intelligent Commodity Investing: New Strategies and Practical Insights
for Informed Decision Making, Section 2: Research Perspective, H. Till and J. Eagleeye.
3 S&P Dow Jones, Bloomberg, Northern Trust.
4 Source: Northern Trust, S&P Dow Jones, Bloomberg
5 U.S. Department of Agriculture, National Agricultural Statistics Service
6 Greer, R. J., 2012, Intelligent Commodity Indexing: A Practical Guide to Investing in Commodities, McGraw-Hill. p. 41.
7 Production data is received from various sources depending on the individual commodity. For example, the source used by DJ-UBS for crude oil production is the IndustrialCommodity Statistics Yearbook (ICSY) see DJ-UBS Commodity Index Handbook. Liquidity is typically defined as open interest of futures contracts.
8 From January 1991 through May 2012 (the period for aluminum and nickel is January 2002 through May 2012).
9 From January 1991 through May 2012 (the period for aluminum and nickel is January 2002 through May 2012). See The ABCI: A Factor-Based Approach to Commodity
Investment, Spurgin, Schneeweis, et al., (2012).
10 Alternative Benchmark Commodity Index returns prior to February 2007 are based on simulated or hypothetical performance that has certain inherent limitations.Unlike the results shown in an actual performance record, all index-related results presented do not represent actual trading performance. Also, because these tradeshave not been executed, these results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity, trading expenses,management, administrative or other fees or costs associated with actual performance. No representation is being made that any account will or is likely to achieve profitsor losses similar to the ones shown above as past performance is not indicative of future results.
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northern trust 2013
Q 53195 (3/13)
Important Information
There are risks involved in investing including possible loss of principal. There is no guarantee that the investment objectives of any fund or strategy will be met.Risk controls and models do not promise any level of performance or guarantee against loss of principal. This material is directed to eligible counterparties and
professional clients only and should not be relied upon by retail investors. The information in this report has been obtained from sources believed to be reliable,but its accuracy and completeness are not guaranteed. Opinions expressed are current as of the date appearing in this material only and are subject to c hangewithout notice. This report is provided for informational purposes only and does not constitute investment advice or a recommendation of any security or productdescribed herein. Indices and trademarks are the property of their respective owners. All rights reserved.
Information intended for use with institutional investors only.Not to be distributed to or relied upon by retail investors. Past performance is not necessarily a guide to the future. Index performance returns do not reflect anymanagement fees, transaction costs or expenses. One cannot invest directly in an index. Index performance is based upon information provided by the indexproviders. Indexes and trademarks are the property of their respective owners, all rights reserved. There are risks involved with investing, including possible lossof principal. For Asia Pacific markets, this material is directed to institutional investors, expert investors and professional investors only and should not be reliedupon by retail investors. This information is provided for informational purposes only and does not constitute a recommendation for any investment strategy orproduct described herein. This information is not intended as investment advice and does not take into account an investors individual circumstances. Opinionsexpressed herein are subject to change at any time without notice. Information has been obtained from sources believed to be reliable, but its accuracy andinterpretation are not guaranteed.
Asset management at Northern Trust comprises Northern Trust Investments, Inc., Northern Trust Global Investments Ltd., Northern Trust Global Investments
Japan, K.K., The Northern Trust Company of Connecticut and its subsidiaries, including NT Global Advisors, Inc., and investment personnel of The Northern TrustCompany. Northern Trust Global Investments Japan, K.K. is regulated by the Japan Financial Services Agency. The Northern Trust Company has a branch in Chinamainly regulated by the China Banking Regulatory Commission, Peoples Bank of China and State Administration of Foreign Exchange. The Northern Trust Companyof Hong Kong Limited is regulated by the Hong Kong Securities and Futures Commission. In Singapore, Northern Trust Global Investments Limited (NTGIL),Northern Trust Investments, Inc. and The Northern Trust Company of Connecticut (NTCC) are exempt from the requirement to hold a Financial Advisers Licenseunder the Financial Advisers Act and a Capital Markets Services License under the Securities and Futures Act with respect to the provision of certain financialadvisory services, and fund management activities. In Australia, NTGIL is exempt from the requirement to hold an Australian Financial Services License under theCorporations Act 2001 in respect to the provision of financial services. Issued by NTGIL. NTGIL is authorised and regulated by the Financial Services Authorityunder UK laws, which may differ from Australian laws.
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