collateralized commodity futures - research affiliatesjul 01, 2015 · commodities. as we’ve...

COLLATERALIZED COMMODITY FUTURES

Methodology Overview

TABLE OF CONTENTSOVERVIEW .................................................................... 1

What is This Document? ..................................................1Time Horizon ......................................................................2Model Changes ..................................................................2

COLLATERALIZED COMMODITY FUTURES ...... 3Asset Class Overview ......................................................3Expected Return Methodology ......................................4

Yield: Collateral Return + Roll Yield ...........................5Collateral Return ....................................................5Roll Yield...................................................................6

Valuation Change ...........................................................8Rebalance Return ........................................................10

Results ................................................................................. 11REFERENCES ............................................................................................................. 13

REVISION DATE: 7/1/2015

“We understand that some of our insights will never find their way into products, but we provide them in support of investors and the finance community.”

— ROB ARNOTTCHAIRMAN & CEO

COLLATERALIZED COMMODITY FUTURES | 1

OVERVIEWWhat is This Document?

This is one in a series of plain-language white papers setting forth Research Affiliates’ building block approach to developing long-term capital market expectations by asset class. (For information about the objectives and

guiding principles of our asset allocation initiative, please refer to “Capital Market Expectations: Methodology Overview,” the first of these white papers.) In working out our risk and return forecasts and making them publicly available, we keep three criteria in mind: transparency, robustness, and timeliness. By describing the conceptual framework and calculations behind the projected asset class risks, returns, and correlations in these papers, we hope to achieve a meaningful level of transparency without excessive details. By constructing simple, economically sound models for major asset classes, we strive to achieve a fitting standard of robustness for forecasting to a 10-year horizon. By initially refreshing our expectations on a quarterly basis, we seek to provide information that is updated with useful frequency. We will continue to refine our methods, extend the scope of our capital market expectations, and improve this documentation over time.The remainder of this document addresses how we think about asset class risk, and provides transparency into the methods employed to develop these risk forecasts.

2 | COLLATERALIZED COMMODITY FUTURES

Time Horizon

One of the major considerations when embarking on the journey to generate asset class return expectations is the consideration of time horizon. Because the focus here is on generating capital market expectations for

strategic asset allocation, and not tactical overlays, we selected a 10-year time horizon.

The 10-year time horizon, is not meant to imply a 10-year buy-and-hold strategy, but instead incorporates a strategy consisting of asset classes each with a constant duration target. Said another way, asset classes with shorter durations (e.g., fixed income), need to be periodically rebalanced to maintain a constant duration. The rebalance period chosen is 1-year which means that a 2-year bond, for example, will be held for 1 year, at which time the 1-year bond will be sold and the proceeds used to purchase a new 2-year bond. Asset classes with significantly long duration (e.g., equities), can be considered buy-and-hold because the change in duration from the passage of 1, 2, or even 10 years on these types of assets is minimal.

Model Changes

The current update to Q2 2015 capital market expectations includes some modifications to our model for commodities. As we’ve stated since the launch of our Asset Allocation site, we are continually doing research

into ways to improve our models and will share applicable findings with you.

The major model changes address the steady-state level of roll yields and the speed of mean reversion captured in the change in valuation buildings block. After further research, we’ve observed that roll yields have been consistently dropping over time and the rolling 10-year average is a better steady-state value than the longer trend used in the previous model. In addition, when looking at commodity indices, the choice of contracts affects the amount of roll yield that can be captured. For example, the Bloomberg Commodity Index invests strictly in front month contracts, and in general, the slope at the short end of the term structure is steeper than with longer maturities. Therefore, because we measure individual commodity roll yield based on the entire term structure, when calculating roll return for an index, we provide an offset to capture the specific contracts selected by each particular index.

Finally, in further analyzing the reversion of commodity prices, we see that commodities tend to revert at a faster rate than previously calculated. Thus, in the updated model, prices fully revert to their average price over the subsequent 10-year period.

With these changes, the expected returns at an index level are actually very similar to those in the prior model. This result, however, is mere coincidence; we believe these changes make the model much more responsive to changes in the markets.


Collateralized Commodity FuturesAsset Class Overview

Commodities are derivative securities, specifically futures contracts that represent claims on consumable or precious assets, as opposed to claims on the future cash flows of a company. The futures contract documents a

claim to pay a predetermined price for the asset at some time in the future. Because the buyer does not have to pay at contract inception, the cash needed to fund the transaction can be placed in other assets in order to earn a return for the life of the contract. Although collateral investment can differ for different investors in different situations, for the purpose here, all contracts are assumed to be fully collateralized. This means the futures buyer invests the full notional amount of the contracts as collateral.

For a particular commodity, futures contracts exist that mature at different times, forming a term structure of contracts, similar to the term structure that exists for fixed income instruments. Although contracts can exist well into the future, the contracts that are relevant from an expected returns perspective are the ones that have a deep tradable market. For most commodities this usually describes contracts expiring over the next year.

Just like the fixed income term structure, the commodity term structure can be upward or downward sloping. In equilibrium, storable commodities ( e.g., base metals) often have an upward sloping term structure, because the futures price equals the current spot price plus any costs associated with holding the physical goods, such as storage and insurance. Commodities with an upward sloping term structure are said to be in contango.

It is also common to see a downward sloping term structure in commodity markets. Lower future prices versus the spot price can occur when inventory is low, causing those who need the commodity to bid up the near-term contracts to ensure supply when they need it. Commodities with a downward sloping term structure are said to be in backwardation (also known as trader’s backwardation).

Similar in name, but different in meaning, to trader’s backwardation is what John Maynard Keynes termed “normal backwardation.” In Keynes’s model, owners of commodities sell futures as a form of insurance on the future price of the commodity. For example, a wheat farmer who wants to lock in his price in advance of the harvest might offer

futures at a discounted price to entice speculators to offer the insurance. The speculators enter the market with the expectation that the future spot

price will be higher than the current future price, and the contract value will rise as the contract nears maturity.1

For many years, commodities were somewhat controversial from an asset allocation perspective. Many scholars and practitioners questioned whether they belonged in an investor’s portfolio or not. Now, many investors consider commodities and other real asset investments to be a core part of their portfolios. Often they hold commodities with the objectives of diversifying against traditional stocks and bonds and hedging against inflation risk. The ability for commodities to hedge inflation risk was quantified, for instance, by

Gorton and Rouwenhorst (2006).

1Normal backwardation is specific to commodity futures markets and not to securities futures markets (e.g., S&P 500 Index futures), and is due to the fact that shorting of commodities is very difficult. Therefore it is necessary to entice speculators into the market.

“It is also common to see commodity markets where the slope of the term structure is downward sloping and the futures price is less than the spot price.”


Asset Class InflationChange in Expected Inflation

Unexpected Inflation

Stocks –0.19 –0.10 –0.23

Bonds –0.22 –0.51 –0.35

Commodity Futures 0.14 0.22 0.25

Source: Gorton and Rouwenhorst (2006)

As shown in Table 1, commodity futures are positively correlated to inflation and provide a hedge against both expected and surprise changes in inflation. A key point is that commodities provide short-term inflation hedging, which does not occur with other asset classes.

Expected Return Methodology

The real commodity return is calculated as the sum of the collateral return, roll yield, and change in spot value:

The collateral is often invested in short-term fixed income instruments, generating a short-term bond return. The roll yield component captures the return from the movement in the price of the futures contract toward the spot price over time, and is similar to the roll yield seen with fixed income instruments. The final component is the change in the spot price over the investment horizon.2

The overall objective here is to forecast the return of commodity indices such as the Bloomberg Commodity Index (formerly the Dow Jones/UBS Commodity Index)3 and the S&P/GSCI Commodity Index. Consistent with our building block approach, however, forecasting is done at the individual commodity level, and the results are then aggregated based on target weights in each index. The 21 commodities listed in Table 2 are used in the forecast; collectively, they provide 90%+ coverage of each index.

2 Spot prices of commodities are difficult to obtain and often are biased by the location where the commodity is held. To alleviate this and other issues, and to model instruments available to all investors, the front month contract is used to proxy spot prices for all commodities.3 The Dow Jones/UBS Commodity Index has been purchased by Bloomberg and rebranded the Bloomberg Commodity Index.

TABLE 1Correlation of Asset Classes to Components of Inflation (1959–2004)

Real Commodity Return Collateral Return Roll Yield Spot Value= + + ∆


TABLE 1Correlation of Asset Classes to Components of Inflation (1959–2004)

Source: Research Affiliates, LLC

At the index level, rebalance return also comes into play. This additional component of return takes into account the fact that, because a portfolio of commodities is essentially a basket of uncorrelated, or lightly correlated, assets, a disciplined rebalance strategy will likely result in long-term excess returns (Greer, Johnson, and Worah, 2013).

YIELD: COLLATERAL RETURN + ROLL YIELDCOLLATERAL RETURN

The collateral return is a function of how the collateral is invested. For near term contracts, the collateral is often short-term U.S. T-bills that mature as the contracts expire and can thereupon be

rolled into new T-bills if new contracts are purchased. Therefore, the forecasted return on the collateral in this model is expected to be the average U.S. cash rate over the futures investment horizon.4

4See the currency and cash rates methodology document for a description of forecasting cash rates.

TABLE 2 Commodities covered in this modeling

Aluminum Heating Oil Copper Nickel Coffee Sugar Soybean Oil

Brent Crude Oil Wheat Corn Silver Lean Hogs Zinc Soybean

Meal

Cotton WTI Crude Oil Gold Soybeans Live Cattle Natural Gas Unleaded

Gasoline

Collateral Return = forecast, USDr


ROLL YIELD

Roll yield captures the differential pricing along the commodity term structure. Because a commodity futures contract has a limited life, at some point the counterparties will need to settle up, either exchanging the physical

commodity for payment, or settling the transaction with cash.5 Most investors, however, would like to maintain exposure to the commodity for longer than the duration of a single contract, prompting the investor to continue to purchase the next contract when the current one expires.

This movement in price of the current contract along the commodity term structure generates a gain (loss) for the investor, depending on whether the next shortest contract is less (more) expensive than the current contract. Roll yield captures this price differential assuming the term structure does not change. In this way it can be thought of as the carry return for holding the contract. Said another way, if the commodity term structure is in contango (upward sloping), investors lose money because the next contract is more expensive than the current contract. Conversely, they make money on commodities in backwardation.

Below is the basic equation used to calculate roll yield. In this equation, T represents the time horizon and for the purpose of the modeling here will be set to unity in order to annualize results. F represents the value of the next contract to be purchased, and S represents the value of the spot commodity (or front month contract).

Commodity futures represent a claim on real assets, which means the underlying asset is assumed to hold its value with inflation, in the same manner as inflation-protected bonds. In modeling the roll yield, it is therefore important not to model the roll yield independently, but to actually model the yield component as a whole (i.e., including the implied collateral). We will back out collateral at the end in order to display these components separately for the purpose of greater transparency.

In modeling roll yield, it is possible to choose any liquid futures contract to compare to the spot price. However, instead of choosing one contract, the method here is to look at the entire term structure for each commodity. The slope of the term structure, when viewed on a log scale, then represents the roll return.

In addition, because the term structure slope can often change, the current term structure is only partially helpful in estimating long-term returns. Therefore, shrinkage is employed between the current term structure slope and the long-term steady state slope of each commodity. Finally, because we modeled yield, we subtract the real collateral return in order to isolate the roll yield.

Figure 1 and Figure 2 illustrate the calculation of roll return for two different commodities.

5For simplicity, the role of the clearinghouse is ignored here.

1 FRoll Yield lnT S

= −

[ ]Roll Return = 15% × 1 × Collateralized Term Structure + 85%

× 1 × Collateralized Term Structure Real Collateral Return

−

− −

Current

10 Yr Avg


FIGURE 1Convenience Yield for LME Aluminum, April 2014

-15%

-10%

-5%

0%

5%

10%

15%

20%

YIE

LD

YIELD AVERAGE

-1.2%

Source: Research Affiliates, LLC, based on data from Bloomberg

Figure 1 shows the yield of aluminum measured as the negative slope of the collateralized term structure since 1997. The horizontal line shows the average yield (–1.2%) for the last 10 of the 18 total years.


FIGURE 2Convenience Yield for Soy Beans, April 2014

-20%

-10%

0%

10%

20%

30%

40%

YIE

LD

YIELD AVERAGE

-1.8%


Figure 2 shows the average collateralized roll yield of soy bean oil is –1.8% over the last 10 years (2005–2014).

As mentioned previously, when dealing with commodity indices, a roll yield offset is applied to account for the fact that commodity indices follow predefined rules as to which commodity contracts they can purchase. This is often the front month contract only, although some indices, such as the Credit Suisse Commodity Index, are structured to use more than just the front month contract. The offset is on the order of –2% and is rolled into the roll return of the index.

VALUATION CHANGE

Because commodities are hard assets, they also serve as stores of value that should keep up with inflation over the long term. Another way of saying this is that real commodity prices should remain flat over time. From a real

perspective, it is possible to deflate commodity prices by the consumer price index (CPI), as is done with other asset classes. Here, however, the producer price index (PPI) is used, because so many commodities are used as inputs to the production cycle rather than as goods for end consumers.


The requirement of flat real commodity prices through time seems to be overly stringent, however, because changes in the production cycle can lead to an increase or decrease in intrinsic commodity value over time. Therefore, instead of assuming that commodity prices will revert to their long-term real average price, the model posits that commodity prices will revert to their real average price of the previous 10 years.

Figure 3 and Figure 4 show the relationship between future 10-year commodity returns and the ratio of average previous 10-year real prices to the current real price. As can be seen in the figures, the relationship is positive, which provides evidence of the reversion in real commodity prices over time. Although only corn and WTI crude oil are shown here, the same results are seen with other commodities as well. Similar findings have been noted by Erb (2014).

FIGURE 3Corn Prices vs. Future 10-Year Return

-15%

-10%

-5%

0%

5%

10%

15%

0 0.5 1 1.5 2 2.5

FUTU

RE E

XCE

SS 10

-YR

RETU

RN

AVG PRICE LAST 10 YRS/PRICE


( ) ( )Valuation 1 /10 ln Real Price - ln Avg Real Price ∆ = − × Prev10 Years


REBALANCE RETURN

When individual commodities are included in a basket, or index, an extra portfolio return can be obtained if the portfolio is rebalanced to target weights in such a way that commodities which rise in price are sold and

those which fall in price are purchased (Greer, Johnson, and Worah, 2013; Willenbrock, 2011). This return has been called rebalance return or diversification return. Willenbrock (2011) proposed a method to quantify the amount of rebalance return.

Willenbrock’s approach is similar to calculations done by other researchers. It is important to note that not all commodity indices realize rebalance returns. Some indices, such as the Bloomberg Commodity Index and the Credit Suisse Commodity Index, have strict rebalancing routines built into the index methodology and earn a rebalance premium on the order of 2–3% per annum. Other indices, such as the S&P GSCI, are reconstituted annually but do not rebalance to target weights. For these indices, an expectation of a rebalance premium is not justified.

FIGURE 4Gold Prices vs. Future 10-Year Return

-10%

-5%

0%

5%

10%

15%

20%

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

FUTU

RE E

XCES

S 10

-YR

RETU

RN

AVG PRICE LAST 10 YRS/PRICE


( )21Rebalance Return2 i i ip

i

w σ σ= −∑


FIGURE 5Dow Jones/UBS Annual Realized and Forecasted 10-Year Real Return

Results

Applying the methodology described in this white paper to each of the 21 commodities and aggregating the results based on the annual target weights of the Bloomberg and S&P GSCI commodity indices provides index-

level expected return forecasts. Building up index level forecasts in this way ensures there is consistency in the forecasting between different indices because the underlying components are the same, and only the individual commodity weights differ. Figure 5 and Figure 6 show the annual forecasted real return for each index along with the annual realized return since 1998.

-0.1%

-4.9%

2.8%

3.1% 0.9%

2.1%

-6.0%

-5.0%

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

COLLATERAL ROLL REBALANCE VALUATION TOTAL FORECAST ACTUAL

HISTORICAL1998 - 2014

RETURNFORECAST



FIGURE 6S&P GSCI Annual Realized and Forecasted 10-Year Real Return

-0.1%

-5.3% 0%

4.3%-1.1%

-6.00%

-5.00%

-4.00%

-3.00%

-2.00%

-1.00%

0.00%

1.00%

2.00%

COLLATERAL ROLL REBALANCE VALUATION TOTAL FORECAST ACTUAL


RETURNFORECAST


0.9%


It is readily apparent that in real terms the expected returns of commodities are close to zero for both indices. But nominal returns could be significantly different, especially in the presence of high inflation. This underscores the idea that commodity allocations should be viewed as hedges against future inflation. Although bets on individual commodities can provide outsized real returns, such strategies trade off some of the benefits of diversification provided by the entire index.


REFERENCES

Erb, Claude. 2014. “Commodity ‘CAPE Ratios.’” Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2499076.

Gorton, Gary, and K. Geert Rouwenhorst. 2006. “Facts and Fantasies about Commodity Futures.” Financial Analysts Journal, vol. 62, no. 2 (March/April):47–67.

Greer, Robert, Nic Johnson, and Mihir P. Worah. 2013. Intelligent Commodity Indexing. New York: McGraw-Hill.

Willenbrock, Scott. 2011. “Diversification Return, Portfolio Rebalancing, and the Commodity Return Puzzle.” Financial Analysts Journal, vol.67, no. 4 (July/August):42–49.


DISCLAIMER

The information contained herein regarding Asset Allocation and Expected Returns may represent real return forecasts for several asset classes and not for any Research Affiliates (“RA”) fund or strategy. These forecasts are forward-looking statements based upon the reasonable beliefs of RA and are not a guarantee of future performance. Forward-looking statements speak only as of the date they are made, and RA assumes no duty to and does not undertake to update forward-looking statements. Forward-looking statements are subject to numerous assumptions, risks, and uncertainties, which change over time. Actual results may differ materially from those anticipated in forward-looking statements.

All projections provided are estimates and are in U.S. dollar terms, unless otherwise specified. Given the complex risk-reward trade-offs involved, one should always rely on judgment as well as quantitative optimization approaches in setting strategic allocations to any or all of the above asset classes. Please note that all information shown is based on qualitative analysis. Exclusive reliance on the above is not advised. This information is not intended as a recommendation to invest in any particular asset class or strategy or as a promise of future performance. Note that these asset class and strategy assumptions are passive only–they do not consider the impact of active management. References to future returns are not promises or even estimates of actual returns a client portfolio may achieve. Assumptions, opinions and estimates are provided for illustrative purposes only. They should not be relied upon as recommendations to buy or sell any securities, commodities, derivatives or financial instruments of any kind. Forecasts of financial market trends that are based on current market conditions or historical data constitute a judgment and are subject to change without notice. We do not warrant its accuracy or completeness. This material has been prepared for information purposes only and is not intended to provide, and should not be relied on for, accounting, legal, tax, investment or tax advice. There is no assurance that any of the target prices mentioned will be attained. Any market prices are only indications of market values and are subject to change.

Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading, but are based on the historical returns of the selected investments, indices or investment classes and various assumptions of past and future events. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. Also, since the trades have not actually been executed, the results may have under or over compensated for the impact of certain market factors. In addition, hypothetical trading does not involve financial risk. No hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of the trading losses are material factors which can adversely affect the actual trading results. There are numerous other factors related to the economy or markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results, all of which can adversely affect trading results.

The asset classes are represented by broad-based indices which have been selected because they are well known and are easily recognizable by investors. Indices have limitations because indices have volatility and other material characteristics that may differ from an actual portfolio. For example, investments made for a portfolio may differ significantly in terms of security holdings, industry weightings and asset allocation from those of the index. Accordingly, investment results and volatility of a portfolio may differ from those of the index. Also, the indices noted in this presentation are unmanaged, are not available for direct investment, and are not subject to management fees, transaction costs or other types of expenses that a portfolio may incur. In addition, the performance of the indices reflects reinvestment of dividends and, where applicable, capital gain distributions. Therefore, investors should carefully consider these limitations and differences when evaluating the index performance.

No investment process is risk free and there is no guarantee of profitability; investors may lose all of their investments. No investment strategy or risk management technique can guarantee returns or eliminate risk in any market environment. Diversification does not guarantee a profit or protect against loss. Investing in foreign securities presents certain risks not associated with domestic investments, such as currency fluctuation, political and economic instability, and different accounting standards. This may result in greater share price volatility. The prices of small- and mid-cap company stocks are generally more volatile than large-company stocks. They often involve higher risks because smaller companies may lack the management expertise, financial resources, product diversification and competitive strengths to endure adverse economic conditions.

Bond prices fluctuate inversely to changes in interest rates. Therefore, a general rise in interest rates can result in the decline of the value of your investment. High-yield bonds, also known as junk bonds, are subject to greater risk of loss of principal and interest, including default risk, than higher-rated bonds. Investing in fixed-income securities involves certain risks such as market risk if sold prior to maturity and credit risk especially if investing in high-yield bonds which have lower ratings and are subject to greater volatility. All fixed-income investments may be worth less than original cost upon redemption or maturity. Income from municipal securities is generally free from federal taxes and state taxes for residents of the issuing state. While the interest income is tax-free, capital gains, if any, will be subject to taxes. Income for some investors may be subject to the federal alternative minimum tax (AMT).

There are special risks associated with an investment in real estate, including credit risk, interest-rate fluctuations and the impact of varied economic conditions. Distributions from REIT investments are taxed at the owner’s tax bracket.


Hedge funds or alternative investments are complex, speculative investment vehicles and are not suitable for all investors. They are generally open to qualified investors only and carry high costs and substantial risks and may be highly volatile. There is often limited (or even nonexistent) liquidity and a lack of transparency regarding the underlying assets. They do not represent a complete investment program. The investment returns may fluctuate and are subject to market volatility so that an investor’s shares, when redeemed or sold, may be worth more or less than their original cost. Hedge funds are not required to provide investors with periodic pricing or valuation and are not subject to the same regulatory requirements as mutual funds. Investing in hedge funds may also involve tax consequences. Speak to your tax advisor before investing. Investors in funds of hedge funds will incur asset-based fees and expenses at the fund level and indirect fees, expenses and asset-based compensation of investment funds in which these funds invest. An investment in a hedge fund involves the risks inherent in an investment in securities as well as specific risks associated with limited liquidity, the use of leverage, short sales, options, futures, derivative instruments, investments in non-U.S. securities, junk bonds and illiquid investments. There can be no assurances that a manager’s strategy (hedging or otherwise) will be successful or that a manager will use these strategies with respect to all or any portion of a portfolio. Please carefully review the Private Placement Memorandum or other offering documents for complete information regarding terms, including all applicable fees, as well as other factors you should consider before investing.

Buying commodities allows for a source of diversification for those sophisticated persons who wish to add commodities to their portfolios and who are prepared to assume the risks inherent in the commodities market. Any purchase represents a transaction in a non-income producing commodity and is highly speculative. Therefore, commodities should not represent a significant portion of an individual’s portfolio. Buying gold, silver, platinum and palladium allows for a source of diversification for those sophisticated persons who wish to add precious metals to their portfolios and who are prepared to assume the risks inherent in the bullion market. Any bullion or coin purchase represents a transaction in a non-income-producing commodity and is highly speculative. Therefore, precious metals should not represent a significant portion of an individual’s portfolio.

Trading foreign exchange involves a high degree of risk. Exchange rates between foreign currencies change rapidly do to a wide range of economic, political and other conditions, exposing one to risk of exchange rate losses in addition to the inherent risk of loss from trading the underlying financial product. If one deposits funds in a currency to trade products denominated in a different currency, one’s gains or losses on the underlying investment therefore may be affected by changes in the exchange rate between the currencies. If one is trading on margin, the impact of currency fluctuation on that person’s gains or losses may be even greater.

Investments that are concentrated in a specific sector or industry increase their vulnerability to any single economic, political or regulatory development. This may result in greater price volatility.

This information has been prepared by RA based on data and information provided by internal and external sources. While we believe the information provided by external sources to be reliable, we do not warrant its accuracy or completeness.

The trademarks Fundamental Index™, RAFI™, Research Affiliates Equity™ and the Research Affiliates™ trademark, RAE™, and corporate name and all related logos are the exclusive intellectual property of Research Affiliates, LLC and in some cases are registered trademarks in the U.S. and other countries.

Various features of the Fundamental Index™ methodology, including an accounting data-based non-capitalization data processing system and method for creating and weighting an index of securities, are protected by various patents, and patent-pending intellectual property of Research Affiliates, LLC. (See all applicable US Patents, Patent Publications, Patent Pending intellectual property and protected trademarks located at http://www.researchaffiliates.com/Pages/legal.aspx#d, which are fully incorporated herein.) Any use of these trademarks, logos, patented or patent pending methodologies without the prior written permission of Research Affiliates, LLC, is expressly prohibited. Research Affiliates, LLC, reserves the right to take any and all necessary action to preserve all of its rights, title, and interest in and to these marks, patents or pending patents.

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