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Morningstar® Indexes2012 13 Yearbook

Volume Eight22 West Washington StreetChicago Illinois 60602

100055-BRC-LO

Presorted StandardU.S. Postage P A I DMorningstar, Inc.

01 Harvesting the Morningstar Investment Research EcosystemSanjay Arya, CFA

02 The Morningstar Investment Research Ecosystem

03 Successful Products Grow from the Morningstar Ecosystem

04 What Makes a Moat?Paul Larson

09 Heading Upstream: A Route to Commodities that Bypasses the Futures MarketElizabeth Collins, CFA

13 Safety First—A Prudent Path to Corporate CreditDavid Sekera, CFA

16 Northern Trust Collaborates with Morningstar Indexes to Bring Distinctive FlexShare Products to Life

19 The Commodity-Currency ConnectionMallory Horejs

22 A New Income Frontier in Multi-Asset InvestingDavid Blanchett, CFA; Hal Ratner; Brian Huckstep, CFA

25 How to Benchmark Target-Date Funds: A Case StudyThomas Idzorek, CFA; Jeremy Stempien

31 Morningstar Indexes: New and Noteworthy

1

Harvesting the Morningstar Investment Research Ecosystem

For half a century, the Capital Asset Pricing Model (CAPM) has guided the science of indexing and provided much of its foundation. When it comes to defining “market exposure” or beta, there is little ambiguity—regardless of which broad market index you choose, you end up with more or less the same risk and return outcome. At the same time, there are known anomalies (such as the size and value effects in equity markets) that seem to contradict the CAPM. Yet it takes diligent research to isolate noise from the systematic factors that show long-term persistence and lead to premiums. We call this the art of indexing. By intersecting science and art we are seeing stunning results.

Having access to some of the sharpest minds in security and portfolio research at Morningstar allows us to blend art with our knowledge of the scientific principles of indexing. We often turn to our team of approximately 265 equity, credit, and fund analysts for concepts in their research that we can apply to new indexes. For multi-asset class solutions, we tap 301 years of groundbreaking asset allocation research first developed by Ibbotson and now carried on in the work of the Morningstar Investment Management division. Being part of a thriving and prolific ecosystem gives us the ability to do some extraordinary things.

You will see some of that in this annual publication. We take you behind the scenes to show you the processes and people in our investment research ecosystem as we transform ideas into products. Within each article, we reveal the solid foundation of research that is essential to our work.

We take you through our journey as we joined forces with iShares® to solve a complex problem and deliver a quality

solution for income seekers and as we helped Northern Trust Global Investments launch several successful FlexShares® products. The Morningstar® Economic Moat™ Rating is one of the primary lenses designed by our equity and credit research teams to gauge the quality of a business by evaluating its sustainable competitive advantage. In ”What Makes a Moat?,” we present the theoretical research behind Morningstar’s Economic Moat Rating and how we use the systematic active return sources of Morningstar’s equity research to develop our family of Active Equity Indexes. In a related article, “Safety First—A Prudent Path to Corporate Credit,” we show how the Economic Moat Rating is used to create better bond indexes.

We are pleased to share with you just some of the ideas that have evolved from collaborations between indexing’s science and art. We invite you to join the conversation by contacting us at [email protected].

Sanjay Arya, CFASenior Vice President, Morningstar Indexes

32 Morningstar Indexes 2012 13

Morningstar® Indexes

Equity Research

Fixed-IncomeResearch

Fund Research

Asset AllocationResearch

QuantitativeResearch

Morningstar is one of the largest independent sources for equity research in the world, home to analysts named “Best on the Street” by The Wall Street Journal.

Our asset allocation knowledge is rooted in 301 years of work from Ibbotson. Now part of the Morningstar Investment Management division, these researchers continue to develop groundbreaking, patented investment concepts recognized by multiple Graham and Dodd awards.

Dedicated researchers throughout Morningstar work to establish proprietary metrics and quantitative methods to help investors better evaluate all types of investments.

Morningstar credit analysts bring transparency through quantitative and qualitative assessments of 7001 corporate bond issuers, reports on 1 million municipal bonds, and ratings and analysis of RMBS and CMBS.

Morningstar is a leader in independent analysis of funds, the first investments we covered at our start in 1984. Today we have one of the most comprehensive full-holdings databases, plus a network of fund analysts in local markets worldwide.

The Morningstar Investment Research EcosystemThe science and art of indexing began more than ten years ago in an environment that sets Morningstar® Indexes apart from all others—that’s the Morningstar Investment Research Ecosystem. We open this world to our clients, forming symbiotic relationships between our experts and theirs to create truly distinct investment solutions.

There’s diversity in our ecosystem. It offers resources such as investment research across asset classes and theories of portfolio construction, threaded together by quantitative analysis. It’s fed by access to one of the world’s largest investment databases, featuring capital markets information dating back to the 1920s. It includes accomplished analysts and researchers who work to understand not only our own ecosystem, but its relationships with the surrounding investing climate. The Morningstar Investment Research Ecosystem is a place where ideas continue to thrive, where we can offer a constant source of inspiration for new indexes.

The Morningstar Investment Management division is a division of Morningstar and includes Morningstar Associates, Ibbotson Associates, and Morningstar Investment Services, all registered investment advisors and wholly owned subsidiaries of Morningstar, Inc. All investment advisory services described herein are provided by one or more of the U.S. registered investment advisor subsidiaries.

3 3

Successful Products Grow from the Morningstar EcosystemA Case Study: iShares® and the Morningstar® Dividend Yield Focus IndexSM

In October 2010, iShares® brought a vexing issue to Morningstar Indexes. Based on advisor feedback, low interest rates, and volatile equity markets were adversely affecting client portfolios. The aspiration was to create a product that could provide consistent yield to investors through a dividend-focused strategy. Typical dividend strategies had not lived up to their potential. This is because many of their methodologies were focused only on dividend payout potential, leading to an overweighting of companies that underperformed in the financial crisis (such as banks).

Equity Research

Equity Research


Morningstar® Indexes Morningstar® Indexes

Equity Research

Equity Research


Morningstar® Indexes Morningstar® Indexes

At Morningstar, researching dividend-paying companies has long been an area of expertise. Our dedicated team of equity analysts monitors these companies.

Sanjay Arya, CFA, senior vice president for Morningstar Indexes, was tasked with finding and aligning the best resources from within the Morningstar Ecosystem to develop a solution for iShares. He brought together a cross-functional team to tackle this project: Josh Peters, CFA, director of equity-income strategy; Haywood Kelly, CFA, senior vice president of equity and credit research; Paul Kaplan, CFA, Ph.D, research director, and Matt Gries, director of product development, Morningstar® Indexes.

These experts formed a working group to identify possible Morningstar proprietary metrics believed to be key factors in isolating quality dividend-paying companies. These metrics became part of the index solution:

3 Morningstar® Economic Moat™ Rating 3 Distance to Default 3 Morningstar Uncertainty Rating

Ultimately, these gauges allowed Morningstar to select index constituents based on qualified income, company quality, and financial health. With these winning metrics and Morningstar’s expertise in building intelligent indexes, the outcome was a quality- and yield-focused index that included only the highest dividend payers.

Across iShares, individuals representing the client voice, product research and development, and portfolio management were also integral to the innovation process. Clear and frequent dialogue helped make sure our objectives were aligned. The final evaluation of index rules and data tests resulted in a viable index and an ETF product. Through this type of collaboration, the Morningstar® Dividend Yield Focus IndexSM was able to meet client needs, make good use of collective intellectual capital, and result in one of the most successful ETFs launched in 2011.

Morningstar’s Goal Identifying a Distinctive Solution Success Through Client Collaboration


What Makes a Moat?Paul Larson, Chief Equities Strategist and Chairman, Morningstar Economic Moat Committee

Economic moats represent sustainable competitive advantages that allow companies to protect their value and lead to the excess returns captured in the Morningstar® Wide Moat Focus Index.SM

Active equity returns drive a significant portion of active management returns. By representing the sources of these active returns in a rules-based process, we can offer the benefits of active management in a passive index structure. Our family of Active Equity Indexes does just this. It captures the systematic active return sources identified in Morningstar’s equity research in transparent, rules-based Indexes. This isn’t traditional indexing, but it’s not traditional active management either. A number of our Active Equity indexes rely on an important proprietary metric— the Morningstar® Economic Moat™ Rating—to identify the sustainable competitive advantages of companies that may be undervalued by the market.

To make money in today’s dynamic market environment, one needs to invest in companies that will perform in the face

of sustained competitive pressure. But how can you accurately identify companies that are great today and likely to remain great for many years to come? The answer to this question lies in competitive advantages, or economic moats. Just as moats were dug around medieval castles to keep the opposition at bay, economic moats protect the high returns on capital enjoyed by the world’s best companies.

Moats 101In a famous 1999 Fortune article, legendary investor Warren Buffett wrote, “The key to investing is…determining the competitive advantage of any given company and, above all, the durability of that advantage. The products or services that have wide, sustainable moats around them are the ones that deliver rewards to investors.” This idea, coined “economic moat,” refers to the sustainable advantages that protect

Figure 1. Fundamental Performance by Morningstar® Economic Moat™ Rating Wide moat firms are more profitable than narrow moat firms.

Return on Invested Capital

(%)

Return on Assets

(%)

Return on Equity

(%)

Operating Margin

(%)Net Margin

(%)

Wide Moat 16.3 9.3 18.6 24.1 17.0

Narrow Moat 11.6 5.1 13.0 15.5 10.8

No Moat 9.2 3.6 8.4 8.2 6.0

Median, 3-Year Historical Results Source: Morningstar Equity Analyst Discounted Cash-Flow Models. Data as of November 12, 2012.

What Makes a Moat? 5

a company against competitors—the way a moat protects a castle. While Warren Buffett may have developed the moat concept, Morningstar has taken the idea a step further.

Whenever a company develops a profitable product or service, it isn’t long before other firms try to capitalize on that opportunity by producing a similar—if not better—version. Basic economic theory says that in a perfectly competitive market, rivals will eventually eat up any excess profits earned by a successful business. In other words, profits attract competition, and competition makes it difficult for firms to generate strong growth and margins for long periods.

But looking at the history of firms, many companies earn high returns on capital for an extended period of time, in conflict with economic theory. Such companies are able to withstand the relentless onslaught of competition for long periods, and these are the wealth compounding machines. The explanation lies in structural characteristics known as economic moats.

Moats Determine the Size of Value CreationThe amount of value a company will create for itself and its shareholders is largely determined by two things: the amount of value currently being created and the sustainability of the excess returns on capital. The first factor is readily apparent to the market because it is in the financial statements. However, the second factor—which is not in the historical

financial statements and cannot readily be screened for— is just as important and is a function of the duration of the competitive advantage.

Here is another way to illustrate this idea: Take three companies, each with a similar value-creating return on invested capital (ROIC) today. The company that is able to sustain the ROIC the longest is going to be able to add the most value for itself over the coming years. In Figure 2, the company with the widest moat and the longest advantage period has the greatest value creation (area under the curve). In a nutshell, companies that have moats can create value for longer periods of time and are worth more, all else being equal.

Moat SourcesOver the years of looking at companies, Morningstar has identified five major sources of competitive advantage:

1. Switching Costs—Switching costs are those one-time inconve-niences or expenses a customer incurs to change from one product to another. Customers facing high switching costs often won’t switch unless they are offered a large improvement in either price or performance. Companies whose customers have switching costs can charge higher prices (and reap more profits) without the threat of losing business. Consider a firm like Oracle—the massive software giant that sells database programs to companies that store and retrieve vast amounts of data. Oracle’s databases are generally connected to other software programs, so if a company wants to change from an Oracle database, it would not only need to move all its data, but also reattach all the different programs that pull from Oracle. Therefore, companies tend not to switch, which is why businesses like Oracle have extraordinarily high renewal rates.

2. Network Effect—The network effect occurs when the value of a particular good or service increases for both new and existing users as more people use that good or service, often creating a virtuous circle that allows the strong to get stronger. Take eBay as an example—it has the most buyers on its platform, so it attracts the most sellers. Meanwhile, because it has the most sellers, it is the most compelling source for buyers looking for non-standard goods.

Figure 2. Moats Add Intrinsic Value Companies with the widest moats have the potential to create value for longer periods of time.

Wide Moat

Time Horizon (Years) 10 15 20

Retu

rn o

n In

vest

ed C

apita

l

Narrow MoatNo Moat


3. Intangible Assets—Intangible assets are things such as patents or government licenses that explicitly keep competitors at bay. Pharmaceutical firms such as Abbott or Pfizer certainly benefit from this. Another sort of intangible asset that can provide an advantage is a strong brand. Intangible assets can have a powerful connection with performance and market characteristics, as seen in Figure 3.

4. Cost Advantage—Firms that can figure out ways to provide goods or services at lower cost have an advantage because they can undercut their rivals on price. Alternatively, they may sell their products or services at the same prices as rivals, but achieve a fatter profit margin. Wal-Mart is a textbook

example of a low-cost producer because it can use its size to acquire and distribute merchandise on the cheap, passing part of the savings to its customers.

5. Efficient Scale—This is primarily a dynamic where there is a limited market size that is being effectively served by one or a small handful of companies. The companies that benefit from this phenomenon are efficiently scaled to fit a market that only supports one or a few competitors, limiting rivalry. International Speedway is a great example; there is simply not enough demand for more than a single NASCAR racetrack in any given city. Lockheed Martin is another good example as the country does not need more than one supplier of F-35 jets.

Figure 4. The Moat Assignment Process The Morningstar Moat assignment process is overseen by a committee of senior researchers. Steps include ensuring a company’s return on invested capital is in excess of its cost of capital and that it has a sustainable competitive advantage.

Has the firm historically generated solid returns on capital?

Is the firm’s future likely to be

different than its past?

How strong is the firm’s competitive

advantage? Is it likely to last a

long time or a relatively short time?

How many years will the firm’s

competitive advantage last?

Yes

No

No Moat

No No

No Moat No Moat

Narrow Moat

WideMoat

Yes

Does the firm have one or more of the

following competitive advantages?

– Switching Costs

– Network Effect

– Intangible Assets

– Cost Advantage

– Efficient Scale

1. Returns 3. Longevity2. Advantages

Figure 3. Characteristics by Source of Moat Different moat sources trade at different multiples of earnings and have varying growth rates.

Number of Firms

P/E 5-Yr Avg

(%)

Current P/E (%)

10-Yr Revenue Growth

(%)

Days to Cover

(%)

Market Cap

(USD Mil)

Forward Dividend

Yield (%)

Switching Costs 286 18.3 17.8 8.3 3.1 10,002 2.7

Network Effect 101 17.0 19.3 11.0 3.2 6,654 1.8

Intangible Assets 382 18.7 18.7 8.2 3.0 11,309 2.3

Cost Advantage 388 16.1 16.1 9.0 2.8 13,065 2.3

Efficient Scale 224 15.5 15.5 7.6 3.0 11,111 4.1

Source: Morningstar Direct.SM

What Makes a Moat? 7

Assigning Moat RatingsGiven the importance that the Economic Moat Rating has in Morningstar’s process and with a number of products, a committee of more than 15 senior Morningstar researchers oversees all of the individual ratings. When assigning Moat Ratings, Morningstar’s analysts and the committee first look for the attributes explained previously. But the proof should be in the pudding, namely, a company’s returns on invested capital; Morningstar looks for a company to achieve an ROIC in excess of its cost of capital. The size of ROIC-cost of capital spread is far less important than the expected duration of the excess profits. A company needs to have an expected competitive advantage period of at least 10 years to attain a narrow moat rating, and at least 20 years to attain a wide moat rating (see Figure 4).

Important to the ProcessBeyond its importance in valuation, analyzing moats can im-prove returns in two other ways. First, the market often does not perceive the additional value companies with high and sustain-able returns will generate. Simple math dictates that firms with economic moats should trade at significant premiums (e.g., higher multiples of earnings, cash flow, and book value) over those with no moats. But it takes time for a company’s moat to be confirmed, and the market—with all of its short-term incentives—is all too myopic in this day and age. In other words, the market is often much more homogenous than it should be. This is an inefficiency that can be exploited.

The second way that moats add value is when the market under-estimates the durability of advantaged companies (and also underestimates the fragility of firms with no moats), something that happens with surprising frequency. Investing in firms that hold the high ground is a sound strategy when periodic floods (recessions, crisis of confidence, and so on) are bound to hit.

Morningstar® Wide Moat Focus IndexSM In 2007, we introduced the Wide Moat Focus Index to capture the systemic sources of active returns resulting from the Economic Moat Rating outlined here. When constructing the Wide Moat Focus Index, we start with all U.S.-based and U.S.-traded corporations rated with a wide moat rating (excluding MLPs), yielding approximately 150 companies that are eligible for the index. Then the companies are sorted by market price relative to Morningstar fair value estimates and include the 20 securities trading at the largest discount to fair value. The holdings are equal-weighted, and the index is rebalanced and reconstituted quarterly.

Based on actual moat ratings assigned over the previous decade, the Morningstar Wide Moat Focus Index has back-tested results starting in mid-2002. As illustrated in Figure 6, the index has posted exceptionally strong performance, beating approximately 95% of large-cap active funds since inception.

Figure 5. The Morningstar® Wide Moat Focus IndexSM Construction Process

Morningstar® Wide Moat Focus IndexSMMorningstar Moat Assignment Process

3 Morningstar equity analyst assigns: – Wide moat rating – Fair value estimate3 Company cannot be under review at time of stock assignment.

Security Selection

3 The 20 securities with the lowest current market price/fair value estimate are selected for inclusion in the index.

Morningstar® US Market IndexSM

3 A broad market index, representing 97% of U.S. equity market cap.


Using Morningstar’s differentiated economic moat framework in combination with the stock valuations that are based on long-term projected cash flow, our process has produced excess returns that have persisted through different market environments. The strategies focused on economic moats have performed well over the last decade, which has seen two back-to-back commodity booms, a major financial crisis, a Great Recession, a boom-bust cycle in the housing markets, and a surprisingly strong rebound in corporate earnings. If a pre- requisite to properly evaluating an investment strategy is looking at it across a variety of market environments, the past decade certainly fits the bill.

ConclusionThe Wide Moat Focus Index validates Morningstar’s strategy to pay close attention to companies’ competitive advantages— the importance of which the market persistently underestimates. Morningstar’s equity research team has demonstrated a strong ability to identify the implications of economic moats when forecasting the long-run cash flows of businesses, increasing the probability of finding mispriced stocks and leading to a better investor experience. K

Figure 7. Morningstar® Wide Moat Focus IndexSM Style Trail The index is plotted with each quarterly portfolio on the Morningstar Style Box.™ The September 2012 portfolio is circled in black. Given that wide moat stocks tend to be larger caps, the index has generally landed in the large cap row over the past decade.

Deep Value Core Value Core Core Growth High Growth

Mic

roSm

all

Mid

Larg

eGi

ant

Morningstar Wide Moat FocusOct. 2002–Sep. 2012

Figure 6. Growth of a $10,000 Investment and Risk/Return: Sep. 20, 2002–Oct. 31, 2012

10,000

20,000

30,000

40,000

20052003 2004 2006 2007 2008 2009 2010 2011 2012

Morningstar® Wide Moat Focus IndexSM

39,730

Morningstar® US Market IndexSM

22,380

US Open End Large Blend Active Managers19,090

USD

Total Returns

3-Years (%)

5-Years (%)

10-Years (%)

Standard Deviation

(%)Sharpe

RatioBeta (%)

Max Drawdown

(%)

Morningstar Wide Moat Focus Index 15.17 8.00 13.12 20.00 0.69 1.17 -42.43

Morningstar US Market Index 13.71 0.79 7.70 15.55 0.49 1.02 -50.76

US Open End Large Blend Active Managers 11.19 -0.71 6.42 15.22 0.39 1.00 -50.79

9

Upstream and downstream producer equities offer the benefits of commodity investing while avoiding derivatives and futures curves, as seen in the Morningstar® Commodity Producers Index family and the Morningstar® Global Upstream Natural Resources Index.SM

Investors’ love affairs with commodities continues unabated. Whether they’re looking for diversification, an inflation hedge, or to speculate on rising prices, investors have plowed hundreds of billions of dollars into commodity-related offerings, including both mutual funds and exchange-traded funds. Investments in commodity mutual funds, for example, have grown to more than $137.6 billion by the end of 2011 from $9.2 billion at the end of 2002. The growth story for commodity-tracking ETFs is even more impressive—assets have skyrocketed to $150.4 billion from $770 million over the same period. Suffice it to say that we’ve come a long way since legendary investor and

commodity aficionado Jim Rogers lamented, “Commodities get no respect.”1 This statement would be far from the truth today.

Many Ways to Invest in Commodities There are three avenues to gain exposure to commodities: 1. Physically hold the commodity. Physically backed exposure offers perfect tracking (net a management fee) to the underlying commodity, since the investor actually owns the physical commodity. However, this is really only feasible for high value-to-weight ratio commodities such as gold.

Heading Upstream: A Route to Commodities that Bypasses the Futures MarketElizabeth Collins, CFA, Associate Director of Equity Research, Basic Materials

Figure 1. Total Assets in Commodity Mutual Funds and Exchange-Traded Funds (US) Commodity-related investment offerings have experienced rapid growth over the last decade.

50

100

150

200

250

300

350

USD

Billi

ons

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Commodity Futures & Physicals Mutual Funds

Commodity Futures & Physicals ETFs

Commodity Equities ETFs

Commodity Equities Mutual Funds

1. Rogers, Jim. Hot Commodities: How Anyone Can Invest Profitably in the World’s Best Market. 2004.


2. Buy commodity futures. In this strategy, the investor holds futures contracts that obligate the purchase or sale of a set quantity of a commodity, at a set date in the future, and at a set price. Historically, there have been three return drivers of futures-based investments: spot return, collateral yield, and roll yield. There are numerous vehicles available to invest in a futures-based strategy that attempt to optimize these three return drivers. But the futures market can be multifarious, requiring investors to have an understanding of how roll yield works (gains or losses incurred when a contract expires and is rolled into the next one). 3. Purchase equity of the producer. As a final option, one can choose to invest in equity-based products that provide underlying commodities exposure.

Equity-Based Exposure to CommoditiesInvesting in equity-based products to gain commodities exposure has broad appeal, as it offers: 3 Convenience: Equity vehicles, such as stocks, are convenient, easy to access, and are less complex than playing the futures market. 3 Wider selections: Using commodity equities also widens the opportunity set to gain exposure to the asset class. Not all commodities have futures associated with them, such as iron ore, timber, water, and coal. 3 Outperformance: It’s also feasible that commodity equities will outperform commodities themselves in a rising price environment. For any given percentage increase in price, a producer’s profits will increase by a greater percentage, all else equal. This leverage to commodity prices is greater for higher-cost producers (those with lower profit margins). Furthermore, higher prices usually mean that more of a company’s potential resources are economical to produce.

The investment growth perfor mance of AK Steel and Nucor during the runup in steel prices (which occurred between the recovery from the Asian financial crisis and the peak before the global financial crisis) illustrates the greater leverage to commodity prices for higher-cost produc ers. A $10,000 invest-ment in AK Steel in 2004 returned more than $190,000 by 2009 as compared to $70,000 for Nucor. AK Steel is one of the highest-cost steel producers in the United States. The company must purchase costly iron ore, and it has significant legacy and financial costs. In contrast, Nucor is one of the country’s most efficient steel producers. The firm has low-cost electric

arc furnaces and doesn’t need to purchase iron ore. It has no legacy liabilities and lower financial costs. While AK Steel’s disadvantaged cost position is a serious threat during weak industry conditions, its shareholders benefit from its high degree of leverage during boom times.

Commodity Producers—An Analyst’s View There are several considerations that are unique to this investment strategy, including: 3 Cost profiles: As the price of its product changes, a commodity producer’s position on its industry cost curve can have a tremendous effect on its financial performance, and hence the performance of its shares. Smaller, marginal producers with extremely unfavorable cost profiles will tend to see very volatile movements in their share prices from movements in the prices of their relevant commodities. This is because relatively small movements in the prices of the commodities (and in the company revenues) can have an outsized effect on these firms’ earnings. 3 Financial leverage: Highly indebted commodity producers (much like high-cost marginal producers) will tend to see more volatility in their share price performance in response to changing fundamentals. 3 Operational diversification: There are very few pure-play commodity producers in existence. Most producers will have diverse exposure to a number of different commodities or end markets. Take BHP Billiton, for example. The firm produces a wide variety of commodities ranging from coal to diamonds. An investment in a mega-miner such as BHP provides a degree of diversification across commodities and geographies, but still leaves one exposed to firm-specific risk—such as the potential for ill-timed, overpriced acquisitions, which were numerous during the most recent runup in commodity prices. Other company-specific risk factors, such as business and management risk, don’t exist when investing directly in commodities and also warrant consideration. 3 Hedging policies: Some commodity producers may take future price risk off the table by locking in selling prices today. If they do so, they may be either capping future upside in their earnings power, or mitigating potential downside should their product prices subsequently fall below these hedged prices.

Not All Commodity Companies Are Created EquallyNot all companies or investment options are equal when it comes to gaining exposure to commodities. In most cases, upstream producers—those directly involved in extracting or harvesting the resources from Mother Nature—are the ones that offer the highest leverage to commodities. Downstream companies—those that buy raw commodities and then process or refine them for end markets—tend to afford less leverage to commodities. The most important measure for determining whether a company is an upstream or downstream producer is to look at the correlation to the underlying commodity spot price itself. Upstream producers have higher correlations.

Exxon Mobil is a company that many investors might turn to for exposure to energy prices. Indeed, Exxon Mobil generates approximately 80% of its profits from upstream activities, or the actual production of oil and natural gas. These activities benefit from higher oil and gas prices. However, Exxon Mobil’s downstream activities in crude oil refining and chemical manufacturing can suffer from high energy prices, since these commodities are raw materials. In fact, the rise in energy prices has led to lower refined product demand in developed markets. In this way, higher energy prices hurt refining activities on both the cost and demand fronts. Pure exploration and produc-tion companies such as Occidental Petroleum, on the other hand, are more leveraged to energy prices than integrated firms such as Exxon Mobil. While the integrated business model affords less leverage to energy prices, this also means less volatility in earnings and equity valuation. We illustrate this in Figure 2.

Morningstar Index Solutions In an effort to provide investors with the greatest opportunity to leverage underlying commodities through an equity-based solution, Morningstar offers two differentiated ways to achieve investment exposure to commodity producer equities.

Morningstar® Global Upstream Natural Resources IndexSM The Morningstar Global Upstream Natural Resources Index was launched in 2011. This index measures the performance of stocks issued by companies that have significant business operations in the ownership, management, or production of natural resources in energy, agriculture, precious/industrial metals, timber, and water resources sectors. The index methodology uses a proprietary industry classification system to identify companies within these five natural resource categories. Individual stock weights, as well as category and regional exposure, are capped to promote diversified exposure. Figure 3 demonstrates the stock assignment process for the Morningstar Global Upstream Natural Resources Index.

Morningstar® Commodity Producers Index FamilyAn alternative approach is the Commodity Producers Index family, which is designed to offer a high correlation with underlying commodities while supplying upstream commodity exposure to companies that do not hedge against production, (excluding gold mining). The Commodity Producers Index family consists of distinct indexes covering agriculture, energy, metals and mining, and gold.

Heading Upstream: A Route to Commodities That Bypasses the Futures Market 11

Figure 2. Growth of a $10,000 Investment—Occidental Petroleum vs. Crude Oil vs. Exxon Mobil Pure exploration and production companies are more leveraged to energy prices than integrated firms.

Exxon Mobil

Occidental Petroleum

Crude Oil (Spot Price)

10,000

0

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

USD

2004 20052003 2006 2007 2008


Rather than embrace a standard market capitalization weighting system for these indexes, Morningstar’s weighting system assigns scores to each company based on its structural leverage to commodity prices and its market capitalization. The weighting schemes used in these indexes include sensitivity factors, as shown in Figure 4, placing higher weights on upstream companies within each index based on their structural leverage to commodities—agricultural inputs or oil and gas exploration, for example.

ConclusionInvestors interested in commodities face many investment options. Commodity equities provide investors with exposure to changes in spot commodity prices and expectations for future commodity prices. If investors choose equity-based commodity investing, Morningstar offers several solutions with the Morningstar® Global Upstream Natural Resources Index,SM and the Morningstar® Commodity Producers Index family. These unique index offerings, developed in conjunction with equity analysts, present indexes that are easy to invest in and based on transparent, noncomplex methodologies. K

Figure 4. Morningstar® Commodity Producer Index Family Construction Process

Investable securities from U.S., Developed Ex-U.S., and Emerging Market Countries

Agricultural Inputs 4

Farm & Construction Equipment 3

Farm Products 2

Confectioners 1

Float Market Cap

Sensitivity Factor

Industry/SensitivityFactor(4 = High,1 = Low)

Weighting:

Oil & Gas Exploration and Production 3

Integrated Oil & Gas 2

Coal & Consumable Fuels 1

Oil & Gas Refining & Marketing 1

Float Market Cap

Sensitivity Factor

Aluminum 1

Diversified Metals & Mining 1

Steel 1

Precious Metals & Minerals 1

Float Market Cap

Sensitivity Factor

Gold Mining Companies (Producers Only)4

Float Market Cap

Sensitivity Factor(based on hedging policies)

Global Equities Investable Universe

Developedand EmergingMarketCountries

Liquidity Screen

CommodityProducersScreen

MorningstarGlobal Equities Indexes

MorningstarCommodity Producer Indexes

GoldEnergyMetals & MiningAgriculture

Figure 3. Morningstar® Global Upstream Natural Resources IndexSM Stock Assignment

Agricultural Inputs

Farm Products

Chemicals

Specialty Chemicals

Diversified Industrials

Industry(SecondaryPriority)

Oil & Gas Exploration and Production

Integrated Oil & Gas

Coal & Consumable Fuels

Oil & Gas Refining & Marketing

Aluminum

Industrial Metals & Minerals

Gold

Utilities—Diversified

Utilities—Regulated Water

EnergyMetals & MiningAgriculture

Lumber & Wood Production

REITs

Paper & Paper Products

30 30 30 15 15Stock Limit

30 30 30 5 5Weight (%)

TimberWater

13

As investors search for yield in today’s low interest rate environment, the additional return provided by corporate bonds has become increasingly attractive. Considering that yields from U.S. Treasury bonds are near historic lows, the credit spread on corporate bonds provides investors with significantly higher income as a percentage of total return. However, the increased return comes with the added risk of potential default. Drawing on proprietary corporate credit research, Morningstar is developing a family of indexes to provide risk-averse investors with a methodology that uses forward-looking credit risk analysis to reduce exposure to default risk and volatility.

A Primer on Morningstar’s Credit Research MethodologyMorningstar began providing issuer-level credit ratings in December 2009 and currently provides credit research and analysis on approximately 700 companies. As an indepen-dent provider of corporate credit research, Morningstar is able to provide investors with an objective view on credit risk, free of any potential conflicts of interest. Morningstar’s credit rating process builds upon the knowledge we’ve gained from analyzing companies during the last decade. Just as Morningstar’s equity research methodology is forward-looking and based on fundamental company research, the credit rating methodology is prospective and focuses on expectations of future cash flows. This methodology applies a consistent approach to analyze credit risk across all sectors, and is fully transparent.

The four key components that drive Morningstar’s risk analysis contain both qualitative and quantitative assessments: 1. Business Risk: Encompasses company-specific and industry risk factors, as well as our proprietary Morningstar® Economic Moat™ and Uncertainty Ratings. For example, a firm such as Johnson & Johnson, has a wide economic moat, due to its diverse revenue base, strong pipeline, and robust cash-flow generation. In conjunction with the firm’s low uncertainty rating, J&J scores near the top of the range. 2. Morningstar Cash Flow Cushion:™ A set of proprietary, forward-looking measures based on analysts’ forecasts of cash flows and financial obligations. This estimates the amount of free cash flow that a firm will generate that is available to service all debt and debt-like commitments (including off- balance sheet items) over the next five years to identify any potential liquidity shortfalls in any one year. In addition, the Cash Flow Cushion is calculated over a cumulative, five- year time period to identify the likelihood that a firm will be able to access the public markets to refinance debt as it matures. A company such as Intel, which can cover its debt commitments by 800% over a five-year forecast period, scores extremely well in this category. 3. The Morningstar Solvency Score: Is a proprietary scoring system that measures a firm’s leverage, liquidity, and profitability. Morningstar quantitative analysts have back-tested numerous credit ratios and indicators across historical bankruptcies over the past ten years to determine those metrics that have the

Emphasizing long-term credit stability and reducing exposure to default risk, the Morningstar® Moat-Focused Corporate Bond Index family represents the interests of today’s risk-averse investor.

Safety First—A Prudent Path to Corporate CreditDavid Sekera, CFA, Bond Strategist


highest correlation—and greatest predictive ability—to identify future defaults. Based on financial projections, a firm such as RadioShack—which scores near the bottom of the list in this category, has a high debt leverage ratio1, and a moderate quick ratio2—will generate substandard returns on invested capital, and will have weak interest coverage.3 4. Distance to Default: A quantitative model that estimates the probability of a firm falling into financial distress based on the market value and volatility of its assets. As the market- implied valuation of a firm declines, the probability of default rapidly increases as the firm’s liabilities begin to outweigh its assets. This serves to provide analysts with an early warning signal that the rate of deterioration in a firm’s assets, based on market-implied valuations, is increasing. A firm such as Office Depot will score poorly in this category, due to the rapid decline in the firm’s equity valuation in light of the company’s highly leveraged balance sheet.

A company’s scores in each area culminate in a model- driven credit rating, which is then presented (in conjunction with any other qualitative credit risks not evidenced within the financial model) by the credit analyst to the Credit Rating Committee to vote on the final issuer-level credit rating. Underlying this Morningstar® Corporate Credit Rating™ is a fundamentally focused methodology, a standardized set of procedures, and core financial risk and valuation tools used by Morningstar’s securities analysts.

Economic Moats as a Differentiator“Economic moat” is a term used to describe the sustainability of a company’s future economic profits. Morningstar defines economic profits as returns on invested capital, or ROICs, over and above the estimate of a firm’s cost of capital, or weighted average cost of capital (WACC). Competitive forces in a free-market economy tend to chip away at firms that earn economic profits, because eventually competitors attracted to those profits will employ strategies to capture some of those excess returns, (see page 4, “What Makes a Moat?”).

Morningstar’s credit research team is leveraging this economic moat analysis to identify investment recommendations in corporate bonds. When it comes to company risk, the assess-ment of a firm’s economic moat is the most important factor. The concept of an economic moat plays a vital role not only in the qualitative assessment of a firm’s long-term cash

generation potential, but also in the actual calculation and evaluation of the credit rating.

The primary differentiating factors among firms is defined as the length of time they can hold competitors at bay. Only firms with economic moats—something inherent in their business model that rivals cannot easily replicate—can stave off compet-itive forces for an extended period. There are three possible economic moat ratings: none, narrow, or wide. There are two major requirements for firms to earn either a narrow or wide moat rating: the prospect of earning above-average returns on capital, and long-term, sustainable competitive advantages that prevent these returns from quickly eroding.

To assess the sustainability of excess profits, analysts perform ongoing assessments of “moat trend.” A firm’s moat trend is positive in cases where its competitive advantage is growing stronger, stable where there are not anticipated changes to the moat rating over the next several years, and negative when there are signs of deterioration. The assumptions that Morningstar makes about a firm’s economic moat play a vital role in determining the length of “economic outperformance” that is assumed in the cash-flow model.

It is expected that companies with wide or narrow economic moats should have lower default risk over a long time period. Buying a long-dated corporate bond entails risks above and beyond its price sensitivity to shifts in the yield curve, since the cumulative probability of default increases with time. Investors in a long-dated bond must consider how a company’s financial health may evolve over a very long time horizon. Those firms whose competitive advantages are expected to be sustained over a longer time frame are in the best position to weather economic storms.

Balance Between Bondholder Interests and Equity ReturnsIn addition to selecting those issuers that have long-term sustainable competitive advantages, Morningstar’s credit analysts also look to exclude firms that may attempt to generate shareholder value at the expense of bondholders’ interests. For example, many corporations have increased their share buyback programs in an attempt to reward shareholders. While using free cash flow to repurchase shares is a perfectly sensible capital structure allocation decision, Morningstar excludes companies that may increase debt leverage over and

1. Debt Leverage Ratio: total debt divided by EBITDA (earnings before interest, taxes, depreciation and amortization).

2. Quick Ratio: sum of (cash and marketable securities1 accounts receivable) divided by total current assets.

3. Interest Coverage: EBITDA divided by interest expense.

Safety First—A Prudent Path to Corporate Credit 15

above the level that would be prudent for the firm’s credit rating. As debt leverage increases, it may lead to a downgrade as the future probability of default increases, thus leading to credit spread widening, and a decrease in the value of the firm’s bonds. Also, Morningstar excludes issuers that may engage in major spin-offs or split-ups. Often these events cause the value of the firm’s bonds to decline, as the firm is left with fewer assets and free cash flow to support its debt load, or the issuer may saddle one entity with greater debt leverage.

Finally, in partnership with Morningstar equity analysts, credit analysts identify those firms that may be targets of leverage buyout offers. In those cases, private equity sponsors typically will incur a substantial amount of additional debt, which is often secured ahead of existing bondholders, placing existing bondholders at a disadvantage in recovering their principal if a company defaults on its obligations.

The Morningstar® Moat-Focused Corporate Bond Index FamilyThe Morningstar Moat-Focused Corporate Bond Index family is constructed based on a dual set of rules that focus indepen- dently on issuer selection and security selection. Issue selection draws upon Morningstar’s extensive expertise in creating nonoverlapping families of liquid, investable indexes. Once Morningstar’s credit research group has established the universe of issuers selected for the index, a set of rules-based criteria is applied to determine the specific securities to be included. All securities are drawn from the Morningstar® Corporate Bond Index.SM The Corporate Bond Index consists

of almost 2,800 investment-grade securities with an issue size of at least $500 million outstanding. The index is constrained so that it consists of only fixed-rate coupon securities without embedded options.

Several filters are applied to the Corporate Bond Index to arrive at the constituent securities to be included in the Morningstar® Moat-Focused Corporate Bond Index family. Securities must have a wide or narrow economic moat. A minimum maturity of two years at issuance is required for initial inclusion in the index, and a minimum remaining term of one year is required. The index is purposefully constructed to exhibit both the characteristics of the current interest rate environment and highly liquid securities. The index is further constrained so that each issuer is limited to its most recently issued security, known as the “on-the-run” security, at each of three maturities: short, intermediate, and long-term. The result is an index family composed of on-the-run securities that exhibit stable or improving credit characteristics, with a focus on investability.

ConclusionWith interest rates hovering near historic lows, the added yield presented by corporate bonds offers investors significantly higher income as a percentage of total return. Combining forward-looking credit research analysis with Morningstar’s methodology in selecting issuers results in an index family that provides the benefit of generating higher income levels with lower credit risk and reduced volatility. K

Figure 1. The Morningstar® Moat-Focused Corporate Bond Index Family Construction Process

Morningstar® Moat-Focused Corporate Bond Index FamilyMorningstar Proprietary Quality Screens

3 Wide or narrow moat rating3 Positive or stable moat trend3 Credit quality screens

Stratified Sampling

3 Maturities: Short, Intermediate, and Long3 Select “on-the-run”

Morningstar® CorporateBond IndexSM

3 Approximately 2,800 securities3 Mimimum issue size $500 mil3 Investment grade (In development. To be launched in Q1 2013.)

Arya: What was your vision behind the FlexShares business?Thomas: We’re very much an investor-centric organization. ETFs were becoming an increasingly important component to the in-vestment solutions our clients were dealing with. But we didn’t want to be a “me-too” provider. There are a lot of providers who have been successful with core beta solutions. We felt we had a unique opportunity to launch some distinctive products.

Arya: How does Northern Trust typically develop new products?Thomas: We look at a few things. One, what is our view from a macro standpoint about the persistent secular trends that we see in the marketplace? That’s the context investors operate in and we want to develop our investment products to help investors solve related challenges. Another thing we use is the

When Northern Trust creates products for its FlexShares® range of exchange-traded funds, it sees the value of involving outside experts who bring new perspectives to the table. In today’s crowded market, new ETFs must stand out by filling unmet investor needs. Northern Trust applies strong research and investment ideas from Morningstar® Indexes to back several of its investor-focused FlexShares funds. Following up on the launch of the ETFs created in collaboration with Morningstar, Shundrawn Thomas and Sanjay Arya discussed these products and other opportunities in the ETF space.

Northern Trust Collaborates with Morningstar® Indexes to Bring Distinctive FlexShares® Products to Life

1 Sanjay AryaSenior Vice President,Morningstar Indexes

7 Shundrawn ThomasManaging Director and Global Business Head, Exchange-Traded Funds Group, Northern Trust


information we gather from direct relationships with clients, whether they are on the institutional or private wealth side. What do our clients see as real and perceived gaps? Then we have our own specific investment strategies where we overlay our strongest capabilities with what we view as opportunities to serve investors. And finally, we turn to our external investment experts.

Arya: Why did Northern Trust choose to work with Morningstar?Thomas: We do not limit ourselves to our own perspective, but we tend to be very deliberate about who we choose to work with. When you look at the rich heritage Morningstar has built through its empirically based research, you see that it has a strong independent and objective voice in the marketplace. It’s great to know that we can team up with a company like Morningstar that is doing meticulous research and has a research staff dedicated to exploring investment strategies. Working with a strong firm like Morningstar helps us to bring our ideas to life.

Arya: What business challenges has Morningstar helped you solve? Thomas: The fundamental challenge you have is getting from concepts to commercialized products. And generally what’s going to happen is you may bring to bear a lot of ideas and expertise, but certainly they are not all commercially viable. Particularly in index-based or passive products, you need a strong strategy that holds its own in the marketplace. We view it as critical to the success of passive products to have an empirical underpinning with strong independent and objective research to support them. Without that, we’d face some very real challenges in terms of their reception in the market-place. Morningstar brings a depth of research and objective analysis that lends credibility to new products, which I think is critically important in this space.

Arya: How was your experience working with Morningstar to design your products?Thomas: If I had to pick a single word, “collaborative” would be the best way I would describe our relationship with Morningstar. An index provider typically brings a lot of intellectual property to the table—existing indexes that you can leverage and translate into products. We weren’t interested in finding someone who would just give us things off the shelf. In order to do that, you’ve got to find a provider that not only brings deep expertise, but

also is willing to collaborate with you and approach the market-place in a slightly different way. We definitely found that in Morningstar. And it’s that kind of relationship that gives you the best outcomes.

With any relationship, you come in with a perception of what each party brings to the table. The areas where we viewed Morningstar as having expertise, resources, and intellectual capital to bring to the table, we found that to be the case. That may seem like a small statement, but it’s an important one. Sometimes you don’t get the truth. Through the relationship, we’ve developed a greater appreciation for each other. We have uncovered other opportunities where we can engage.

Arya: How has your vision translated into the products you’ve brought to market in the first phase of your launch?Thomas: We think about the important things investors have to consider in a portfolio. For example, a lot of people are focused on how to get core exposure. That plays out in one of the products we had the privilege of working with Morningstar on—the FlexShares Morningstar US Market Factor Tilt Index Fund (TILT). There are a lot of ways investors today get core exposure to the U.S. equity market, and there are a lot of successful indexes. The marketplace is fairly well covered. But we saw an opportunity through an index product to provide unique, alternative exposure—and for some people, depending on their objectives, a more effective and efficient way to get at that exposure.

We looked at our research and compared notes with Morningstar. Morningstar research showed there was definitely a premium over time in the marketplace that’s provided by investment in small capitalization stocks and value stocks. In terms of the amount of market coverage, it’s deeper than most of the indexes out there and gives you that tilt to the small

“Morningstar brings a depth of research and objective analysis that lends credibility to new products, which I think is critically important in this space.”

Northern Trust Collaborates with Morningstar Indexes to Bring Distinctive FlexShares Products to Life 17


capitalization and value orientation in the marketplace. Our U.S. Market Factor Tilt product is an example of something we think we’re doing that’s additive and distinctive within the marketplace.

Arya: One of your other products offers exposure to commodities through natural resources. What are some of the philosophical nuances that make this different from existing products?Thomas: This is another great example of how we considered the desires of investors, along with their unmet needs. As we work with clients, we sometimes see a lack of understanding of the underlying instruments they were investing in to get expo-sure to commodities. They sometimes don’t see the associated challenges, whether they’re from a tax-efficiency or a regulatory standpoint. We also recognized both from our own experience and from conversations with investors that a lot of commingled products tend to skew toward energy. We viewed these challenges as opportunities. We asked ourselves whether we could do things better.

When you have a good relationship with your index provider, your collaborations come together well into a product. Morningstar had done a lot of great work on commodities in terms of industry classifications and deep research. We were able to combine these ideas in our distinctive FlexShares Morningstar Global Upstream Natural Resources Index Fund (GUNR).

We did two specific things with this product: We created balanced exposure and focused on natural resources. We have an index that’s designed to give equal exposures of 30% to each of the big sleeves of energy, agriculture, and metals (including precious and industrial metals). We also included exposures of 5% each to water and timber to give people access to what we see as a key trend in the expanding demand for global natural resources.

Arya: Shundrawn, are there any other new products you’d like to talk about today?Thomas: We have a couple of important ones that we worked on with Morningstar. We talked earlier about our U.S. Market Factor Tilt product and its ability to give core U.S. exposure while providing a tilt to both small capitalization and value stocks. Well, we recently launched the FlexShares

Morningstar Developed Markets ex-US Factor Tilt Index Fund (TLTD) and the FlexShares Morningstar Emerging Markets Factor Tilt Index Fund (TLTE). We’re excited about these, because investors are increasingly looking at their portfolios and thinking globally. Employing a similar type of investment approach both in developed ex-U.S. markets and emerging markets is very attractive to investors.

Arya: How do you see your relationship with Morningstar evolving?Thomas: We’re thinking about the kind of forums that Morningstar is involved in. Everybody in the industry ecosys-tem—whether it’s sponsors or index providers or others—should make a greater commitment to the education of the investing public. If you care about what you do—and we are really passionate and deeply care about our work—you have a responsibility to do something to enhance the understanding of what you are doing. Increasingly we see opportunities where we have complementary skills we could bring together, not just for our own business interests. Not only is this the right thing to do, it actually creates business opportunities.

Arya: Where do you see the FlexShares business going within the ETF space?Thomas: People can definitely expect more of what we’ve been doing. As the marketplace continues to evolve and inves-tors in ETFs are changing, we will have to be dynamic to adjust to investor needs. The providers we work with have to be able to do that as well. We want to continue to roll out distinctive products and build upon the early successes we’ve had to increase awareness of what we’re doing at FlexShares. We’re seeing signs of being picked up more in the marketplace. As we shine more light on what we’re doing, we believe investors will appreciate it.

Arya: I really want to thank you for taking the time this after-noon to share your vision for your business. K

About FlexShares® ETFs FlexShares® is a suite of ETF products designed to pursue real-world goals by evolving the process of ETF development, providing flexibility for meeting investor needs. FlexShares Funds are sponsored by Northern Trust, a leading provider of investment management, asset and fund administration, banking solutions, and fiduciary services for corporations, institutions, and affluent individuals worldwide.

19

The Commodity-Currency ConnectionMallory Horejs, Alternative Investments Analyst

Incorporating currencies with the Morningstar® Diversified Commodity Exposure IndexSM provides an alternative approach to diversifying your commodities bucket.

Due to amplified participation in the commodity futures market, the world is seeing increased integration with traditional stock and bond markets. This may result in the weakening of the diversification benefits from commodity investments, particularly the traditional long-only flavor.1 The rolling 36-month correlation between the Morningstar® Long-Only Commodity IndexSM and the U.S. equity market has risen sharply over the past decade. In the early 2000s, this figure hovered close to zero, indicating that commodities provided a source of return uncorrelated to investors’ traditional stock and bond investments. But correla-tions between all asset classes spiked during the financial crisis—as of May 2012, this figure stood at 0.70.

Fortunately for investors seeking diversification, the strategies used to gain commodity exposure continue to evolve. One of the most recent innovations in the commodity space, for example, is the availability of long/short indexes and strategies in mutual fund form. This alternative approach may provide a more appealing risk-return profile as well as a lower correlation to traditional market indexes. A second way to diversify the commodities allocation is by including “commodity currencies,” or currencies from countries that possess large quantities of commodities or natural resources. Including both long/short strategies and commodity currencies in one’s commodities allocation can provide more diversification benefits and draw-down protection than a traditional long-only portfolio.

The Draw of a Long/Short ApproachSeveral academic studies have demonstrated that when invest-ing in commodities, investors should take both long and short positions. The primary advantage to this alternative approach is the opportunities to generate profits in both rising and falling commodity markets.2 Long-only indexes simply aren’t able to capture excess returns when commodity prices are declining.

Furthermore, long/short strategies are better able better able to manage “roll yield.” (A futures strategy has three sources of return: changes in the commodity’s spot price, collateral yield, and roll yield. Roll yield refers to the gains or losses that result from replacing an expiring contract with a farther out contract to maintain a position while avoiding physical delivery.) When commodity markets are in contango, meaning that the futures price curve is positively sloped, long-only indexes must lock in roll-yield losses to maintain their positions. This means that long-only strategies may lose money even when commodity prices are rising.3

Benchmarks for Momentum-Based StrategiesTo benchmark momentum-based long/short commodity strategies, Morningstar created a family of indexes that includes combinations of long commodity futures, short commodity futures, and cash. The primary index, the Morningstar® Long/Short Commodity Index,SM invests both

1. Miffre, Joëlle. “Academic analysis supports Long/Short commodity investing without Regulatory Intervention.” Hedge Funds Review. January 4, 2012.

2. Schwartz, Jeremy and Jabara, Chris. “Managed Futures Strategies.” Journal of Indexes. May/June 2012.

3. Kaplan, Paul D. “Putting Momentum into Commodi-ties.” Morningstar Indexes 2011/12 Yearbook. Volume Seven. 2011.


4. Chen, Yu-chin and Rogoff, Kenneth. “Commodity Currencies.” Journal of Inter-national Economics. 2003.

long and short in the 20 most liquid U.S. commodities contracts based on momentum signals.

For each commodity, Morningstar calculates a “linked” price series that incorporates both price changes and roll yield. At each monthly rebalancing, if the linked price exceeds its 12-month moving average, the index takes the long side in the subsequent month. Conversely, if the linked price is below its 12-month moving average, the index takes the short side. Commodities in the energy sector are an exception—if the signal for a commodity in the energy sector is short, the weight of that commodity is moved into cash; that is, Morningstar takes a flat position. Energy is treated differently because its price is extremely sensitive to geopolitical events and not necessarily driven purely by demand-supply imbalances.

The long-term results through October 2012 appear positive. As illustrated in Figure 3, the Morningstar® Long/Short Commodity IndexSM has demonstrated better performance, lower volatility, and better downside protection than the major traditional long-only indexes: the Dow Jones-UBS Commodity Index and S&P GSCI Index. Morningstar’s Long/Short Commodity Index has generated returns that are virtually uncorrelated to equity markets—its 10-year correlation with the U.S. equity market is negative 0.07, (see Figure 1).

The Possibilities of Commodity Currencies Another innovative way to gain commodity exposure is through investing in “commodity currencies,” or currencies of countries where commodities constitute a significant share of exports. While this isn’t a “pure play” investment like long-only or long/short commodity futures strategies, it still provides direct exposure to price fluctuations. Most importantly, adding a new asset class (currency) to the commodities portfolio brings the possibility of enhanced diversification. Though this trading tactic has long been used on foreign exchange trading desks, it remains relatively unfamiliar to mainstream investors.

As a general rule, commodity currencies move in tandem with commodity prices—when prices are rising, the currencies of the commodity producers also strengthen. This is partially because when demand is high, commodity-producing nations usually grow rapidly, which can lead to high domestic interest rates. High interest rates can make these countries a popular target for currency carry trades, a strategy in which investors sell low-yielding currencies and reinvest proceeds in high-yielding currencies.

The most recognizable commodity currencies are the Australian, Canadian, and New Zealand dollars. Because commodities constitute a significant component of exports in these countries, world commodity price movements explain a major component of their exchange-rate fluctuations. A study by Yu-chin Chen and Kenneth Rogoff found the relationship between exchange rates and commodity prices to be strongest in Australia and New Zealand, where typical commodity price elasticity estimates are between 0.5 and 1.0.4 (For example, a 10% rise in the price of gold would lead to a 5% to 10% appreciation of the Australian dollar.)

Many emerging market currencies, such as the Brazilian real, Chilean peso, Russian ruble, and South African rand are also considered to be commodity currencies, though lower liquidity levels make some of them less appropriate for investing. Noticeably absent from many commodity currency trades are Middle Eastern countries, which account for a significant portion of global oil exports. Many currencies from oil-rich nations (the Saudi riyal, for example) are pegged, meaning they cannot float freely alongside the prices of their commodity exports.

Figure 1. Morningstar Commodity Exposure Indexes Correlation Matrix August 1999–July 2012 Commodity investment strategies provide low correlation with traditional asset classes such as stocks and bonds.

Morningstar Index

1. US Market (U.S. Equities) 1.00

2. Core Bond (U.S. Bonds) -0.16 1.00

3. Long-Only Commodity 0.34 0.00 1.00

4. Long/Short Commodity -0.07 -0.06 0.57 1.00

5. Diversified Commodity Exposure -0.07 -0.08 0.53 0.97 1.00

1 2 3 4 5

1.00 to 0.61Extreme Positive

0.60 to 0.21Positive

0.20 to -0.20 Moderate

-0.21 to -0.60Negative

-0.61 to -1.00Extreme Negative

The Commodity-Currency Connection 21

Morningstar® Diversified Commodity Exposure IndexSM

Morningstar has attempted to capture the benefits of both long/short commodity investing and commodity curency investing in its Morningstar® Diversified Commodity Exposure Index.SM The objective is to offer diversified exposure to commodities through a combination of exchange-listed commodity futures and commodity currencies. Launched in April 2010, this index allocates 75% of its assets to the Morningstar® Long/Short Commodity IndexSM and 25% to the Morningstar® Commodity Currency Index.SM

The Morningstar Diversified Commodity Exposure Index makes equal-weighted allocations, both long and short, to five major commodity currencies: the South African rand, Australian dollar, Brazilian real, Canadian dollar, and New Zealand dollar. These countries are all rich in natural resources and have liquid, freely floating currencies. This index uses the same construction rules as the Morningstar Long/Short Commodity Index. At each monthly rebalancing, if the linked price on the currency contract exceeds its 12-month moving average, the index takes the long side in the subsequent month. Conversely, if the linked price is below its 12-month moving average, the index takes the short side.

ConclusionAs seen in Figure 3, the combination of long/short commodity investing and commodity currency investing in the Morningstar Diversified Commodity Exposure Index has led to significantly better downside protection for investors. As a result, this index has produced a stronger risk-adjusted return profile through October 2012 than both long-only and stand alone long-short approaches. K

Figure 2. Index Construction The Morningstar® Diversified Commodity Exposure IndexSM offers exposure to commodities and helps limit risk through the flexibility of both long and short positions.

Currency (25%)South African Rand (ZAR)Australian Dollar (AUD)Brazilian Real (BRL)Canadian Dollar (CAD)New Zealand Dollar (NZD) M

omentum

Rule

Currency

Commodity

Commodity (75%)Includes the 20 most liquid contracts on U.S. commoditiesacross Agriculture, Energy,Livestock, and Metals

Figure 3. Morningstar® Diversified Commodity Exposure IndexSM Risk/Return Comparison

Index

Trailing Return

(%)

Standard Deviation

(%)

Maximum Drawdown

(%)Sharpe

Ratio

Morningstar US Market 3.47 16.21 -50.76 0.14

Morningstar Core Bond 5.99 3.65 -3.51 0.94

Morningstar Long-Only Commodity 11.74 18.54 -53.78 0.57

Morningstar Long/Short Commodity 9.91 12.73 -22.74 0.62

Morningstar Diversified Commodity Exposure

9.51 10.73 -17.22 0.68

Dow Jones-UBS Commodity 6.99 17.48 -54.26 0.34

S&P GSCI 6.75 24.23 -67.64 0.29

Data from August 1, 1999–October 31, 2012


Total return doesn’t entirely capture the risk preferences of income-focused investors, so we introduced a new optimization method for building income-efficient portfolios that’s reflected in the Morningstar® Multi-Asset High Income Index.SM

A New Income Frontier in Multi-Asset Investing David Blanchett, CFA, Head of Retirement ResearchHal Ratner, Chief Investment Officer, EuropeBrian Huckstep, CFA, Portfolio Manager

As more investors approach retirement, they seek solutions to help them generate income. Increasing levels of risk aversion due both to an investor’s life-stage and concerns about market volatility are pushing these investors toward less- risky options. Despite the potential appeal of income-focused products, there are few diversified options that currently exist in this space. While there are a variety of reasons why this is the case, a primary reason is likely the focus on total return as the basis of risk rather than income return. Total return serves as an obvious definition of risk for many investors, but it does not accurately capture the risk preferences for an investor who has an income return or yield focus. In response, Morningstar has developed the Morningstar® Multi-Asset High Income IndexSM to give investors access to a diversified, optimized solution with an income focus.

Optimal Income Return AllocationsThere is relatively little guidance on how to build an efficient income portfolio. Traditional portfolio optimization research has typically focused on total return strategies, which combine price return and income return. While it is possible to generate income from a portfolio focused on total return, this measure is an incomplete perspective for a retiree who wants to generate income and not liquidate principal. For example, long-term bonds have comparatively high price return volatility but very low income volatility. This suggests long-term bonds are more efficient from an income return perspective than

a price return (or total return) perspective. Among equities, higher-yielding securities tend to exhibit lower risk than their growth-oriented counterparts. Among fixed-income securities, the opposite tends to hold—higher-yielding bonds tend to come with increased volatility and an increased chance of loss of capital. It is difficult to strike an appropriate balance between adding relatively safe dividend-paying stocks and high risk/income bonds. Morningstar has developed a new utility function and optimization process to identify optimal income return portfolio allocations. The results suggest that investors with an income focus are likely better served using portfolios specifically constructed for this purpose, since income-efficient portfolios can be substantially different from total return efficient portfolios that happen to generate income.

Income vs. Total ReturnOne critique of building a portfolio based on income is that the approach will result in portfolios that are inefficient when viewed from a total portfolio framework. While this critique has some merit, it assumes that risk can be defined using some metric based on the total risk of the portfolio (such as standard deviation, downside risk, or conditional value at risk) and that the metric accurately reflects the risk preferences of the investor. If the investor is an “income investor” as opposed to the traditional total-return investor, this critique is misplaced.

A New Income Frontier in Multi-Asset Investing 23

Funds with a significant level of price risk but a relatively small amount of income risk can be attractive investments for an investor focused on income, but less so for an investor focused on total return. While some may argue this form of preference modeling is irrational, it is definitely a preference shared among many investors, especially retirees. In fact, it can be defended on economic as well as behavioral grounds. Because this preference cannot be captured by focusing on total return alone, a new measure of efficiency is required to build a portfolio for an income-focused investor.

Before continuing, it is important to note the relative compo-nents for an efficient total return portfolio can be decomposed into an income return and a price return. Given the relative risk and return of attributes typically included in a portfolio, as one moves “up” the efficient frontier the portfolio tends to focus more heavily on price return versus income return, which dominates the more conservative portfolios. This concept is illustrated in Figure 1.

The frontier in Figure 1 (the green line) is the traditional mean-variance efficient frontier that is created without regard to whether the return of the portfolio is income or price. Rather, the efficient frontier is simply concerned with maximizing the total return for each unit of total risk. The income return (blue line) and price return (red line) are simply the component parts that combine to be the total return of the portfolio. If the definition of “optimal” is changed to focus on income return (versus total return), a different efficient frontier results. This plots below the total return efficient frontier (when plotted in total return space), which is depicted in Figure 2.

Note that the income return frontier in Figure 2 is truncated. It only extends as far as the highest yielding investment, which is U.S. preferred stock (based on the opportunity set of investments included in the analysis). An investor seeking income greater than this amount (7.5% in this example) would need to liquidate some of the portfolio (e.g., dip into the price return) in order to achieve a given income objective.

The Income Return Utility Function in ActionThere are many portfolios that lie on the income return efficient frontier. When designing the Morningstar Multi-Asset High Income Index, it was therefore critical that the index select one portfolio from this frontier. As Figure 2 shows, there is a natural maximum income achievable by this type of strategy that does not include the most aggressive (highest risk and total return) asset classes. In practice, yields tend to shift slowly, making them easier to predict (and optimize) than total return. Historically, for securities in the United States, the maximum yield region of the income efficient frontier has typically been represented by multi-asset portfolios with 20% to 40% equity exposure. This is convenient, as many investors who are interested in income-efficient investing are also nearing retirement and prefer portfolios near this overall risk level. The Morningstar Multi-Asset High Income Index has been set up to maintain allocation weights at each rebalance of the following: 3 20% equity 3 60% fixed-income 3 20% alternative

Figure 1. Efficient Frontier Components These relative components make an efficient total return portfolio.

2

4

6

8

10

12

14

Retu

rn %

0Standard Deviation %

5 10 15 20 25 30 35

Income Return

Price Return

Total Return

Figure 2. Efficient Frontier: Total Return vs. Income Return What’s defined as “optimal” focuses on income return vs. total return.

2

4

6

8

10

12

14

0Standard Deviation %

5 10 15 20 25 30 35

Income ReturnEfficient Frontier

Total ReturnEfficient Frontier

Retu

rn %


The weight of each constituent in the Morningstar® Multi-Asset High Income IndexSM is given by meeting the high-level asset class targets listed above through use of this mean-variance optimization equation developed by Morningstar:

Where:

w � index weight� � optimizer scale factor set to 3.5y � 12-month yield for equities and current yield-to-maturity for fixed-income (less management fees)V � variance-covariance matrix of last 36 months of total returns

max f(w) � � w’ y � w’ Vw

There are additional constraints that aid diversification and avoid some of the issues that can arise with purely quantitative optimizers. (They can occasionally be sensitive to inputs and result in focused portfolios.)

ConclusionTypical portfolios focused on income likely use asset classes that may be ignored in traditional optimizations, such as preferred stock, long bonds, and emerging market bonds. Income-efficient portfolios may have asset allocations that vary considerably from traditional mean-variance portfolios (focused on total returns). Investors seeking income are likely best served using approaches or portfolios built with their goals in mind. The Morningstar Multi-Asset High Income Index introduces a new framework to determine how to build an asset allocation with an income focus. K

Figure 3. Morningstar® Multi-Asset High Income IndexSM Construction Process

Dividend-Paying ETFs

3 Minimum liquidity criteria: • 3-month average daily vol > 25k shares/day • fewer than 10 non-trading days in previous three months

Universe of all iShares U.S.-listed ETFs

3 History > 1 Year3 AUM >= $250 Mil.

Investable Universe

Includes:3 Equity3 Fixed-Income3 Alternative Income Sources (ETFs that hold securities with both equity and bond-like characteristics)

Morningstar® Multi-Asset High Income IndexSM

Asset class exposure set to the following to balance risk exposures:3 Equity: 20%3 Fixed-Income: 60%3 Alternative Income Sources: 20%

Figure 4. Morningstar® Multi-Asset High Income IndexSM Risk/Return

Trailing Returns

Index

1-Year %

3-Year %

Since Inception

%

12-Month Yield

%

Standard Deviation

%Sharpe

Ratio

Maximum Drawdown

%

Morningstar Multi-Asset High Income Index 11.11 15.72 22.22 5.43 8.97 2.34 -2.25

Morningstar Conservative Target Risk Index 3.77 7.19 2.40 2.28 4.17 2.06 -2.07

Morningstar US Market Index -1.33 15.55 8.03 2.12 17.27 1.28 -17.26

Morningstar Global ex-US Index -19.98 5.95 4.40 3.40 21.90 0.79 -22.67

FTSE NAREIT All Equity REITs Index 2.89 28.23 12.01 3.71 25.56 1.43 -17.68

Barclays Capital U.S. Aggregate Bond Index 7.12 7.12 8.28 2.43 2.65 2.67 -1.65

Data as of June 30, 2012.

25

How to Benchmark Target-Date Funds: A Case StudyThomas Idzorek, CFA, President, Morningstar Investment Management Division Jeremy Stempien, Director, Investments, Morningstar Investment Management Division, Retirement Solutions

By their very nature, target-date funds are complex investments. This complexity makes them especially challenging to bench-mark, with each fund containing unique attributes and features that ideally should be addressed individually based on the unique goals and situation of the potential investor. In this article, the assumption is that both a target-date fund family and a target-date benchmark have been selected (rightly or wrongly), and a target-date benchmark must now be used in the most appropriate manner possible. It is important to emphasize the word appropriate, because the use of target-date benchmarks for benchmarking target-date funds is significantly more nuanced than traditional benchmarking, requiring greater skill and interpretation.

In all cases, the target-date benchmark should not be unambiguously accepted as “good” (unless the fund complex licenses a specific target-date index, in which case the glide path and detailed asset class weightings are accepted as given). As such, the performance of a target-date fund relative to a target-date benchmark is open to interpretation. It’s important to understand the relative performance—the active return relative to the benchmark—and from there, determine meaning-ful insights. Understanding the causes of the relative performance of target-date funds is fundamentally more challenging than it is for traditional benchmarking.

Additionally, the scope of the problem goes well beyond the benchmarking of a single fund. Rather, the goal is typically to benchmark all of the five-to-12ish target-date funds that make up a target-date fund family, a process that requires one to analyze and benchmark the 10-to-50 or so sub-funds used within the family in hopes of making an assessment of the perfor-mance of the overall fund family.

A Case StudyThis case study focuses primarily on the complications associated with benchmarking the largest retail target-date fund family, the Fidelity Freedom Funds family, relative to the Morningstar® Lifetime Moderate Allocation Index family. This analysis focuses on the Fidelity Freedom 2030 fund, but the same process is repeated for each of the other 11 funds that make up the Fidelity Freedom Funds family.

Adjusting the BenchmarkFigure 1 includes a variety of annualized statistics based on five years of quarterly data for each of the funds that make up the Fidelity Freedom Funds family, the corresponding target-date indexes from the Morningstar Lifetime Moderate Allocation Index family, and the corresponding differences from October 2006 to September 2011. In practice, one would look at these statistics for various periods, such as 12 months, 60 months, 120 months, and since inception.

We look at a popular family of target-date funds and compare them with the Morningstar® Lifetime Asset Allocation Indexes, explaining how to interpret the performance of these important retirement vehicles.


Figure 1. Performance Comparison October 2006–September 2011 The Morningstar® Lifetime Moderate Allocation IndexSM had a better annualized arithmetic return, geometric return, standard deviation, and Sharpe ratio than the respective Fidelity Freedom Fund over this time period.

Arithmetic Mean

(%)

Geometric Mean

(%)

Standard Deviation

(%)Sharpe

RatioNumber of

Drawdowns Skewness Kurtosis

Fidelity Freedom 2050 1.05 -1.45 22.98 -0.02 1 -0.35 -0.36

Morningstar Lifetime Moderate 2050 3.35 1.02 22.53 0.08 2 -0.23 -0.42

Difference -2.30 -2.47 0.45 -0.10 -1 -0.12 0.06



Difference -1.94 -1.95 -0.26 -0.09 -1 -0.11 0.09



Difference -1.90 -1.89 -0.33 -0.09 -1 -0.11 0.14

Fidelity Freedom 2035 1.47 -0.64 21.17 0.00 1 -0.36 -0.30


Difference -1.81 -1.78 -0.46 -0.08 -1 -0.11 0.13



Difference -1.66 -1.67 -0.20 -0.08 -1 -0.11 0.23

Fidelity Freedom 2025 2.33 0.69 18.73 0.04 2 -0.33 -0.14


Difference -1.52 -1.59 0.20 -0.08 0 -0.12 0.29

Fidelity Freedom 2020 2.60 1.17 17.48 0.06 2 -0.32 0.00


Difference -1.71 -1.97 1.49 -0.11 0 -0.15 0.44



Difference -1.74 -1.93 1.27 -0.14 0 -0.13 0.46



Difference -1.87 -2.18 2.51 -0.18 0 -0.09 0.43



Difference -2.09 -2.42 2.96 -0.24 -1 -0.04 0.54



Difference -1.67 -1.57 -1.31 -0.15 0 0.04 1.03

Fidelity Freedom Income 3.51 3.28 7.12 0.28 3 -0.21 0.88

Morningstar Lifetime Moderate Income 5.00 4.67 8.42 0.41 4 -0.50 -0.03

Difference -1.49 -1.40 -1.30 -0.13 -1 0.29 0.92

Average Difference -1.81 -1.90 0.42 -0.12 -0.58 -0.06 0.39

Source: Morningstar® EnCorr.®

How to Benchmark Target-Date Funds: A Case Study 27

Figure 2. Beta-Adjusted Performance Comparison October 2006–September 2011 The beta-adjusted performance comparisons of Morningstar Lifetime Moderate Indexes and Fidelity Freedom Funds are closer than shown in Figure 1. This case study examines the Fidelity Freedom 2030 Fund’s underperformance of the Morningstar® Lifetime Moderate 2030 IndexSM by 82 bps.

Arithmetic Mean

(%)

Geometric Mean

(%)

Standard Deviation

(%)Sharpe

RatioNumber of

Drawdowns Skewness Kurtosis



Difference -1.72 -1.82 0.22 -0.08 0 -0.09 0.10



Difference -1.24 -1.32 0.22 -0.06 0 -0.08 0.13



Difference -1.07 -1.15 0.22 -0.05 0 -0.08 0.15



Difference -1.02 -1.10 0.25 -0.05 -1 -0.08 0.15



Difference -0.82 -0.89 0.23 -0.04 0 -0.08 0.21

Fidelity Freedom 2025 2.33 0.69 18.73 0.04 2 -0.33 -0.14


Difference -0.85 -1.00 0.76 -0.05 0 -0.09 0.34



Difference -0.97 -1.13 0.89 -0.06 0 -0.09 0.45



Difference -0.96 -1.13 1.17 -0.08 0 -0.04 0.48



Difference -1.37 -1.57 1.47 -0.12 0 0.00 0.45



Difference -1.52 -1.69 1.41 -0.14 0 0.12 0.34



Difference -0.26 -0.34 1.30 -0.09 0 0.18 0.90

Fidelity Freedom Income 3.51 3.28 7.12 0.28 3 -0.21 0.88

Morningstar Lifetime Moderate Income 3.73 3.58 5.76 0.38 3 -0.56 -0.03

Difference -0.22 -0.30 1.36 -0.10 0 0.35 0.92

Average Difference -1.00 -1.12 0.79 -0.08 -0.08 0.00 0.38



Over this five-year period, in almost all cases, the Morningstar® Lifetime Moderate Allocation IndexSM had a better annualized arithmetic return, geometric return, standard deviation, and Sharpe ratio than the respective Fidelity Freedom Fund. While this suggests poor relative performance for the Fidelity Freedom Funds over this particular time period, before reaching this conclusion one must dig deeper.

The final row of Figure 1 shows that, on average, the Fidelity Freedom Fund family underperformed the respective Morningstar Lifetime Moderate Allocation Index family by 181 basis points per year during this five-year analysis. Looking at the respective glide paths demonstrates where this difference comes from. This analysis revealed the varying level of equity exposure between the Fidelity Freedom funds and the Morningstar Lifetime Moderate Indexes. Almost all the Fidelity Freedom funds have less equity exposure than the corresponding target-date index.

Different equity exposure levels would typically lead one to expect different risk and return characteristics between the target-date fund and its corresponding index. It is widely recognized that the returns of a benchmark should be “risk- adjusted,” or more specifically, “beta-adjusted” so that the fund and benchmark in question have similar overall risk exposures (i.e., level the playing field). To do this, a rolling 12-month beta was calculated for each of the Fidelity Freedom Funds relative to their corresponding Morningstar Lifetime Moderate Allocation Index, and then a separate beta-adjusted return

series was created using these rolling betas for each of the Morningstar Lifetime Moderate Allocation Indexes. In Figure 2, the Fidelity Freedom funds were compared to each, relative to a beta-adjusted version of the Morningstar Lifetime Moderate Allocation Index.

In comparison to Figure 1, the beta-adjusted performance comparison in Figure 2 is much closer. For example, the average annual arithmetic return differential shrunk from 181 basis points of underperformance per year for the Fidelity Freedom Funds to 100 basis points of underperformance per year. Note the highlighted negative 82 basis points of underperfor-mance of the Fidelity Freedom 2030 fund. From a target-date benchmarking decomposition standpoint, Figure 2 provides us with a starting point: a return differential or active return between the fund in question and the corresponding beta- adjusted return of the benchmark that must be decomposed. More specifically, the quantity that must be decomposed and understood is the following:

(Formula A)

Fund Return 2 Beta-Adjusted Benchmark Return 5 Active Return

The active return is then decomposed into four parts— asset allocation, sub-fund alphas, glide path fee, and other—using Formula B.

Figure 3. Morningstar® Lifetime Moderate 2030 Fund Active Return Distribution, October 2006–September 2011 Active return attribution analysis for the Fidelity Freedom 2030 Fund leads back to the negative 82 bps annual return differential identified in Figure 2.

Dec 2006

Mar 2007

Jun 2007

Sep 2007

Dec 2007

Mar 2008

Jun 2008

Sep 2008

Dec 2008

Mar 2009

Jun 2009

Sep 2009

Dec 2009

Mar 2010

Jun 2010

Sep 2010

Dec 2010

Mar 2011

Jun 2011

Sep 2011 Average

Morningstar Lifetime Moderate 2030 (Beta-Adjusted) 7.28 2.37 5.78 2.46 -1.52 -7.41 -0.53 -12.25 -19.41 -9.20 17.53 15.49 4.08 4.01 -8.69 11.74 8.78 5.09 0.13 -12.68 0.65

Fidelity Freedom 2030 6.58 2.06 6.32 2.43 -1.69 -9.08 0.26 -12.36 -21.05 -8.09 17.41 15.92 4.38 3.87 -8.73 10.71 8.65 4.58 -0.29 -12.87 0.45

Active Return -0.70 -0.31 0.54 -0.03 -0.18 -1.67 0.79 -0.11 -1.64 1.10 -0.12 0.43 0.30 -0.13 -0.04 -1.03 -0.13 -0.51 -0.42 -0.18 -0.20


Fidelity Freedom 2030 Effective Asset Allocation Return 6.89 2.24 5.52 2.39 -1.83 -7.37 -0.43 -11.37 -20.10 -7.69 17.63 15.49 4.75 4.06 -8.04 11.04 8.80 4.75 -0.09 -12.51 0.71

(a) Asset Allocation -0.40 -0.13 -0.27 -0.07 -0.31 0.04 0.10 0.89 -0.69 1.51 0.11 0.00 0.67 0.05 0.65 -0.71 0.02 -0.34 -0.22 0.17 0.05

(b) Weighted Average Sub-Fund Alpha -0.32 -0.24 0.81 0.05 0.15 -1.69 0.65 -0.93 -0.92 -0.43 -0.31 0.41 -0.45 -0.18 -0.69 -0.33 -0.19 -0.11 0.02 -0.28 -0.25

Fidelity Freedom 2030 Overall Fund Fee 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.19

Weighted Average Sub-Fund Fees 0.1901 0.1945 0.1891 0.1792 0.1793 0.1879 0.1894 0.1843 0.1658 0.1892 0.1954 0.1967 0.1915 0.1868 0.1859 0.1884 0.1881 0.1659 0.1798 0.1778 0.19

(c) Glide Path Fee -0.0026 -0.0070 -0.0016 0.0083 0.0082 -0.0004 -0.0019 0.0032 0.0217 -0.0017 -0.0079 -0.0092 -0.0040 0.0007 0.0016 -0.0009 -0.0006 0.0216 0.0077 0.0097 0.00

(d) Other 0.02 0.06 0.00 -0.02 -0.02 -0.01 0.04 -0.06 -0.05 0.02 0.09 0.03 0.08 -0.01 -0.01 0.01 0.03 -0.09 -0.23 -0.08 -0.01


How to Benchmark Target-Date Funds: A Case Study 29

(Formula B) Active Return 5

Asset Allocation a) Return of the Effective Asset Allocation Fund 2 (Beta3Return of the Benchmark)

Sub-Fund Alphas b) 1 Weighted Average Pure (Net of Fee) Alphas of Sub-Funds

Glide Path Fee c) 2 (Overall Fund Fee 2 Weighted Average Fee of Sub-Funds)

Other d) 1 Other

The goal now is to estimate the inputs for the decomposition formula and then decompose the active returns relative to the benchmark period by period. This return attribution/decom-position framework was applied to the Fidelity Freedom 2030 fund in order to better understand the annual arithmetic return difference of negative 82 basis points between Fidelity Freedom 2030 fund and the Morningstar Moderate 2030 (beta-adjusted) series. Moving forward, quarterly data (corresponding to the quarterly reported holdings) was used, in an attempt to decompose the slightly more than negative 20 basis points of average quarterly underperformance.

Like most target-date funds, the Fidelity Freedom Funds are funds of funds. When looking at the evolving allocations to the underlying sub-funds that have made up the Fidelity Freedom 2030 fund during the past five years, an allocation at each point can be identified. The fewest number of sub-funds used during the analysis period was 21 and the most was 26.

To determine the effective asset allocation, each of the indivi-dual sub-funds was analyzed to establish their respective individual effective asset allocations and, eventually, the “pure

alphas” for each sub-fund. As part “a” of Formula B demonstrates, the active return from asset allocation is calcu-lated by comparing the weighted average performance of the effective asset class allocations of the Fidelity Freedom 2030 fund relative to the performance of the beta-adjust-ed benchmark.

When looking at the evolving estimated effective asset allocation of the Fidelity Freedom 2030 fund based on holdings- based style analysis and combining it with the quarterly returns associated with the appropriate asset class index, one is able to determine the period-by-period return of the fund’s effective asset allocation. On average, over a five-year period, the effective asset allocations of the Fidelity Freedom 2030 fund added approximately 5 basis points of excess return per quarter.

Sub-Fund AlphasTurning to the weighted-average alpha of the sub-funds, one should focus on part “b” of Formula B. Here the goal is to deter-mine the part of active return attributed to sub-fund alphas. More specifically, weighted-average, period-by-period alpha is estimated for each of the sub-funds for the given target-date fund. In this working example, the details for the sub-funds that make up the Fidelity Freedom 2030 fund are shown. Earlier the term “pure alpha” was used to emphasize that these are not alphas relative to a single-factor benchmark, such as the S&P 500, but alphas relative to a custom, evolving multi-asset class benchmark. A returns-based style analysis is completed for each sub-fund using a rolling 36-month window to create the

Figure 3. Morningstar® Lifetime Moderate 2030 Fund Active Return Distribution, October 2006–September 2011 Active return attribution analysis for the Fidelity Freedom 2030 Fund leads back to the negative 82 bps annual return differential identified in Figure 2.

Dec 2006

Mar 2007

Jun 2007

Sep 2007

Dec 2007

Mar 2008

Jun 2008

Sep 2008

Dec 2008

Mar 2009

Jun 2009

Sep 2009

Dec 2009

Mar 2010

Jun 2010

Sep 2010

Dec 2010

Mar 2011

Jun 2011

Sep 2011 Average


Fidelity Freedom 2030 6.58 2.06 6.32 2.43 -1.69 -9.08 0.26 -12.36 -21.05 -8.09 17.41 15.92 4.38 3.87 -8.73 10.71 8.65 4.58 -0.29 -12.87 0.45

Active Return -0.70 -0.31 0.54 -0.03 -0.18 -1.67 0.79 -0.11 -1.64 1.10 -0.12 0.43 0.30 -0.13 -0.04 -1.03 -0.13 -0.51 -0.42 -0.18 -0.20


Fidelity Freedom 2030 Effective Asset Allocation Return 6.89 2.24 5.52 2.39 -1.83 -7.37 -0.43 -11.37 -20.10 -7.69 17.63 15.49 4.75 4.06 -8.04 11.04 8.80 4.75 -0.09 -12.51 0.71

(a) Asset Allocation -0.40 -0.13 -0.27 -0.07 -0.31 0.04 0.10 0.89 -0.69 1.51 0.11 0.00 0.67 0.05 0.65 -0.71 0.02 -0.34 -0.22 0.17 0.05

(b) Weighted Average Sub-Fund Alpha -0.32 -0.24 0.81 0.05 0.15 -1.69 0.65 -0.93 -0.92 -0.43 -0.31 0.41 -0.45 -0.18 -0.69 -0.33 -0.19 -0.11 0.02 -0.28 -0.25

Fidelity Freedom 2030 Overall Fund Fee 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.1875 0.19

Weighted Average Sub-Fund Fees 0.1901 0.1945 0.1891 0.1792 0.1793 0.1879 0.1894 0.1843 0.1658 0.1892 0.1954 0.1967 0.1915 0.1868 0.1859 0.1884 0.1881 0.1659 0.1798 0.1778 0.19

(c) Glide Path Fee -0.0026 -0.0070 -0.0016 0.0083 0.0082 -0.0004 -0.0019 0.0032 0.0217 -0.0017 -0.0079 -0.0092 -0.0040 0.0007 0.0016 -0.0009 -0.0006 0.0216 0.0077 0.0097 0.00

(d) Other 0.02 0.06 0.00 -0.02 -0.02 -0.01 0.04 -0.06 -0.05 0.02 0.09 0.03 0.08 -0.01 -0.01 0.01 0.03 -0.09 -0.23 -0.08 -0.01



evolving custom multi-asset class benchmark. The period-by- period alpha of each fund is then estimated relative to its own custom benchmark.

Since 2007, the entire Fidelity Freedom Funds family has used 40 underlying funds, each of which must be analyzed individually. Coupling the quarter-by-quarter alphas with the weight of each sub-fund in the Fidelity Freedom 2030 fund, the quarter-by- quarter weighted average alpha can be calculated. This will provide the average quarterly alpha for each of the sub-funds, as well as the average for the weighted average quarterly alphas, which is negative 25 basis points. In contrast to the effective asset allocation decisions that added approximately 6 basis points, the sub-funds of Fidelity Freedom 2030 hurt performance by approximately 25 basis points per quarter. This analysis helps identify the quality of the underlying sub-funds, as each fund will be analyzed individually.

Glide Path FeeThe sub-fund alpha analysis was completed “net-of-fees” so that it could be determined whether or not the individual sub-funds were adding or detracting alpha after accounting for their individual fees. The underlying sub-fund fees were already accounted for. The weighted average quarterly sub-fund fees during this time period were 19 basis points.

For the purchaser of a target-date fund, the most transparent number is the “all-in” fund fee. To avoid potentially double- counting, in part “c” of Formula B, focus first on the “all-in” Fidelity Freedom 2030 fee (75 basis points per year, or 18.75 per quarter), and then subtract from the “all-in” fee the weighted average fee of the underlying sub-funds that were already accounted for. One might think of this remaining fund fee as the

“glide path fee.” For some fund families this “glide path fee” is extremely low or potentially negative, as the fund companies view the target-date fund family as a tool for driving assets to the sub-funds rather than an additional revenue source.

In the case of Fidelity Freedom 2030, the weighted average quarterly fee of the sub-funds comes extremely close to the 18.75 basis point “all-in” fund fee per quarter, indicating that there is virtually no additional “glide path” fee, and the “all-in” fund fee charged by the Fidelity Freedom 2030 fund is simply the weighted average fee of the underlying sub-funds.

The final part of Formula B, part “d,” represents “other.” It is a plug that allows the decomposition in each quarter to hold perfectly. It should be thought of as an error term resulting from estimation errors associated with parts “a” through

“c” of Formula B. For the Fidelity Freedom 2030 fund, the average value for “other” is nearly zero, indicating that over time the errors are cancelling each other out.

Putting the Pieces TogetherFigure 3 summarizes the active return attribution analysis for the Fidelity Freedom 2030 fund. Working with the return attribution framework developed in Formulas A and B, Figure 3 contains the following information:

3 Active Return 3 Asset Allocation 3 Weighted Average Sub-Fund Alphas

3 Weighted Average Sub-Fund Fees 3 Other

The final column of Figure 3 contains the averages for the vari-ous quarterly series, respectively. Annualizing these quarterly active returns leads back to the negative 82-basis-point annual arithmetic return differential identified earlier in Figure 2.

ConclusionThe importance of target-date funds to America’s retirement system is difficult to overstate. Yet, to date, the industry has lacked definitive guidance on how to benchmark target-date funds and target-date fund families. Frustratingly, benchmark-relative comparisons will not tell you if the glide path itself is “good.” With that in mind, Morningstar proposes a comprehensive framework for decomposing the active return of a fund relative to a benchmark into four components: asset allocation, sub-fund alphas, glide path fee, and other. The process is both data- and labor-intensive, though necessary given the importance of target-date funds. K

31

Morningstar® Factor Tilt Index FamilyThe Morningstar® Developed Markets ex-US Factor Tilt IndexSM and the Morningstar® Emerging Markets Factor Tilt IndexSM were added to the Morningstar Factor Tilt Index family in September 2012. These indexes offer alternative exposure to any given market (U.S., Developed ex-U.S., or Emerging) by tilting the portfolio to capture the size and value premium— taking advantage of market anomalies that the efficient market camp refers to as systematic exposure to undiversifiable risk. The Morningstar Factor Tilt Index family was first launched in 2011 with the introduction of the Morningstar® US Market Factor Tilt Index.SM

Morningstar® Ultimate Stock-Pickers IndexesMorningstar Indexes launched the Morningstar® Ultimate Stock-Pickers IndexSM in the first quarter of 2012. This index selects the top stocks bought by the industry’s top active managers, representing the best investment opportunities as identified by the most consistently outperforming portfolio managers across a diverse range of investment strategies. Two risk control variations of the Ultimate Stock-Pickers Index have also been developed, including the Morningstar® Ultimate Stock- Pickers Target Volatility 7 IndexSM and Morningstar® Ultimate Stock-Pickers Target Volatility 10 Index.SM

Morningstar® Emerging Markets Bond Index FamilyThe Morningstar® Emerging Markets Bond Index family was enhanced in early 2012. The family now consists of five indexes covering the corporate and sovereign debt of emerging markets. Indexes optimized for liquidity and investability in the family include the Morningstar® Emerging Markets Sovereign Bond IndexSM and Morningstar® Emerging Markets Corporate Bond Index.SM New indexes include the Morningstar® Emerging Markets High Yield Bond Index,SM Morningstar® Emerging Markets Investment Grade Bond Index,SM and Morningstar® Emerging Markets Composite Bond Index.SM

Morningstar® Canada Liquid Bond IndexSM

The Morningstar® Canada Liquid Bond Index SM was launched in July 2012. This index is designed to provide diversified exposure to Canadian dollar-denominated federal, provincial, government-guaranteed, and corporate debt with an eye toward liquidity.

Morningstar Canada Equity IndexesMorningstar launched a set of Canada Equity Indexes in 2012, including the Morningstar® Canada Value Index,SM Morningstar® Canada Momentum Index,SM and Morningstar® Canada Dividend Target 30 Index.SM These indexes were developed leveraging the expertise of Toronto-based CPMS, a Morningstar company.

Morningstar and First Asset rang the opening bell at the TSX for the launch of Canada Equity Factor Index-based ETFs.

Morningstar® Multi-Asset High Income IndexSM

Launched in January 2012, the Morningstar® Multi-Asset High Income IndexSM is a broadly diversified index that seeks to deliver a high level of current income while maintaining long-term capital appreciation. The index consists of a comprehensive set of income-producing ETFs that collectively target equity, fixed-income, and alternative asset classes.

Morningstar® Indexes: New and Noteworthy


Morningstar Real Asset IndexesThe Morningstar® Real Asset Index family offers diversified and optimal portfolios of liquid real assets such as inflation-linked bonds, commodities, real estate investment trusts (REITs), and commodity-related stocks that help investors access real assets in a transparent, rules-based, and cost-effective manner. The index family is designed to perform well in times of high inflation and provide low correlation with broad equity and fixed-income asset classes.

New Hire NewsMorningstar has appointed Robert Broadwell as director of business development for Morningstar Indexes in Europe, the Middle East, and Africa. In this role, Robert is responsible for institutional business development of Morningstar’s family of indexes to ETF providers, asset managers, and investment banks in those regions.

Elaine Orr has joined Morningstar as director of business development and is responsible for relationship management and development for strategic accounts across the globe. Both Robert and Elaine most recently held positions at BlackRock and have deep expertise in passive money management. K

Recently Launched Products Based on Morningstar® Indexes

Morningstar Index

Product Type Issuer Exchange Ticker

Ultimate Stock-Pickers Structured Note BNP Paribas — —

Ultimate Stock-Pickers Target Volatility Structured Note BNP Paribas — —

Emerging Markets Corporate Bond ETF BlackRock/iShares LSE EMCP

Emerging Markets High Yield Bond ETF BlackRock/iShares BATS EMHY

Multi-Asset High Income ETF BlackRock/iShares BATS IYLD

Dividend Yield Focus CAD-Hedged ETF BlackRock/iShares TSX XHD

Canada Dividend Target 30 ETF First Asset Funds TSX DXM

US Dividend Target 50 ETF First Asset Funds TSX UXM

Canada Momentum ETF First Asset Funds TSX WXM

Canada Value ETF First Asset Funds TSX FXM

Emerging Markets Composite Bond ETF First Asset Funds TSX EXM

Wide Moat Focus Target Volatility 5 Structured Note Goldman Sachs — —

Developed Markets ex-US Factor Tilt ETF NorthernTrust/FlexShares ARCX TLTD

Emerging Markets Factor Tilt ETF NorthernTrust/FlexShares ARCX TLTE

Long/Short Commodity Commodities Pool Nuveen Investments NYSE CTF

Wide Moat Focus ETF Van Eck Global/Market Vectors ARCX MOAT

Learn More About Morningstar® Indexes

Morningstar Indexes 2012/13 Yearbook Volume Eight

Contributing WritersDavid Blanchett, CFAElizabeth Collins, CFAMallory Horejs Brian Huckstep, CFA Thomas Idzorek, CFAPaul LarsonHal RatnerDavid Sekera Jeremy Stempien

Copy EditorsTori Brovet Tom CorbettAmy Eisenman

Corporate Marketing EditorsAnn Marie GrayCourey Gruszauskas

Senior Vice PresidentSanjay Arya, CFA

Director, Product DevelopmentMatthew Gries

Director, Business DevelopmentRobert Broadwell (Europe)Elaine Orr (Global)Marc Zieger (U.S.)

Marketing DirectorTara Giuliano

Marketing Assistant Jennifer Rehm

Art DirectorSiegfried Herrnreiter

©2012 Morningstar. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without prior written consent of Morningstar. All information provided is for informational purposes only, and no warranty is made as to its correctness, completeness, or accuracy. Morningstar shall not be responsible for any trading decisions resulting from, or related to, this information, data, analyses, or opinions and is not liable for damages arising therefrom. Every effort has been made to ensure that all information given is accurate, but Morningstar can accept no responsibility for errors or omissions.

Editorial and business communication may be addressed to: Morningstar Indexes, 22 West Washington Street, Chicago, IL 60602 For general information about Morningstar’s products and services, please contact Morningstar institutional sales at 11 888 736-0780 or visit http://global.morningstar.com.

Journalists please contact us at [email protected].

Investment Product CreationA consistent and stable methodology, objective rules, and a name that evokes trust and confidence among investors worldwide make the Morningstar® Indexes perfect vehicles for creating index-linked investment products, such as funds, exchange-traded funds, and derivatives.

Data Services and DistributionReal-Time Distribution: Morningstar offers real-time values for most Morningstar Indexes. Index values are distributed through leading data vendors and can also be found at: http://indexes.morningstar.com.

Available Historical Index Data InceptionMorningstar® Commodity Indexes 1979 Morningstar® US Market Index,SM 1991 Capitalization Indexes, and Sector IndexesMorningstar® Style and Dividend Indexes 1997Morningstar® Domestic Bond Indexes 1998Morningstar® Global Equity Indexes 1998Morningstar® Asset Allocation Indexes 1998Morningstar® Global Bond Indexes 2001Morningstar® Emerging Markets Bond Indexes 2001

Constituent Data Feeds: Constituent names, weights, prices, market caps, and free-float values are available daily or monthly. A separate file with details on all corporate actions affecting the index constituents is also available each business day.

Index Data Feeds: More than 50 unique data elements including index closing values, total returns, risk statistics, sector breakdowns, and index-level fundamental data are available electronically via FTP download or email.

Contact Information To discuss any of these opportunities or to order reprints of articles appearing in this publication, please visit: http://indexes.morningstar.com.

Morningstar® IndexesMorningstar offers indexes that cover all major asset classes as well as multi-asset class indexes.

US Market

Morningstar Core Bond Morningstar US Gov Bond Morningstar US Treasury Bond Morningstar US Agency Bond

Morningstar Corporate Bond Morningstar Mortgage Bond Morningstar Cash

Morningstar Long Term Core Bond Morningstar Long Term Corporate Bond Morningstar Long Term US Gov Bond

Morningstar Intermediate Core Bond Morningstar Intermediate Corporate Bond Morningstar Intermediate US Gov Bond

Morningstar Short Term Core Bond Morningstar Short Term Corporate Bond Morningstar Short Term US Gov Bond

Morningstar Cash

Canada Market

Morningstar Canada Liquid Bond

Global Government

Morningstar Global Gov Bond Morningstar Global ex-US Gov Bond Morningstar Australasian Gov Bond Morningstar Canadian Gov Bond Morningstar Eurozone Gov Bond Morningstar Japanese Gov Bond Morningstar Swiss Gov Bond Morningstar UK Gov Bond

Emerging Markets

Morningstar Emerging Markets Composite Bond Morningstar Emerging Markets Sovereign BondMorningstar Emerging Markets Corporate BondMorningstar Emerging Markets High-Yield BondMorningstar Emerging Markets Investment Grade Bond

European Market

Morningstar Eurobond CorpMorningstar European Bank CapitalMorningstar European Covered BondMorningstar UK Bank CapitalMorningstar UK Eurobond Corp

Inflation-Protected Securities

Morningstar Global TIPSMorningstar US TIPSMorningstar European Gov Inflation LinkedMorningstar UK Gov Inflation Linked

Fixed-Income Indexes

US Style

Morningstar US Market Morningstar US Value Morningstar US Core Morningstar US Growth

Morningstar US Large Cap Morningstar US Large Value Morningstar US Large Core Morningstar US Large Growth

Morningstar US Mid Cap Morningstar US Mid Value Morningstar US Mid Core Morningstar US Mid Growth

Morningstar US Small Cap Morningstar US Small Value Morningstar US Small Core Morningstar US Small Growth

US Sector

Morningstar US Basic Materials Morningstar US Consumer CyclicalMorningstar US Financial Services Morningstar US Real Estate Morningstar US Communication Services Morningstar US EnergyMorningstar US IndustrialsMorningstar US Technology Morningstar US Healthcare Morningstar US Consumer DefensiveMorningstar US Utilities

Factor-Based

Morningstar US Market Factor Tilt Morningstar Developed Markets Ex-US Factor TiltMorningstar Emerging Markets Factor Tilt

Morningstar Canada Momentum

Morningstar Canada Value

Dividend

Morningstar Dividend Composite Morningstar Dividend Leaders Morningstar US Dividend Target 50Morningstar Canada Dividend Target 30Morningstar Dividend Yield FocusMorningstar Dividend Yield Focus CAD-HedgedMorningstar MLP CompositeMorningstar MLP FocusMorningstar US REITMorningstar UK REITMorningstar Global REIT

Active Equity

Morningstar Wide Moat Focus Morningstar Wide Moat Focus Target Volatility 5Morningstar StockInvestor CoreMorningstar Ultimate Stock-PickersMorningstar Ultimate Stock-Pickers Target Volatility 7Morningstar Ultimate Stock-Pickers Target Volatility 10

Global Markets

Morningstar Global MarketsMorningstar Global Markets ex-USMorningstar Developed MarketsMorningstar Developed Markets ex-US Morningstar Emerging MarketsMorningstar National Bank Quebec

Commodity Equity

Morningstar Global Upstream Natural ResourcesMorningstar Agriculture Commodity ProducersMorningstar Energy Commodity ProducersMorningstar Metals & Mining Commodity ProducersMorningstar Gold Commodity Producers

Equity Indexes

Broad Commodity

Morningstar Long-Only Commodity Morningstar Long/Short Commodity Morningstar Long/Flat Commodity Morningstar Short/Flat Commodity Morningstar Short-Only Commodity

Commodity Sector

Morningstar Agriculture Commodity Morningstar Energy Commodity Morningstar Livestock Commodity Morningstar Metals Commodity

Single Commodity

Morningstar Soybean Oil Morningstar Corn Morningstar Brent Crude Morningstar WTI Crude Morningstar Cotton

Morningstar Gold Morningstar Copper Morningstar Heating Oil Morningstar Coffee Morningstar Live Cattle

Morningstar Gas-Oil Morningstar Lean Hogs Morningstar Natural Gas Morningstar RBOB Gas Morningstar Soybean Morningstar Cocoa

Morningstar Raw Sugar Morningstar Silver Morningstar Soybean Meal Morningstar Red Wheat

Managed Futures

Morningstar Commodity CurrencyMorningstar Diversified Commodity Exposure Morningstar Diversified Futures

Morningstar Global Long/Short CurrencyMorningstar Global Long/Short Equity

Hedge Fund

Morningstar Broad Hedge FundMorningstar Nexus Hedge Fund Replication

Alternative Investment Indexes

Lifetime Allocation

Morningstar Lifetime Aggressive IncomeMorningstar Lifetime Aggressive 2000Morningstar Lifetime Aggressive 2005Morningstar Lifetime Aggressive 2010Morningstar Lifetime Aggressive 2015Morningstar Lifetime Aggressive 2020Morningstar Lifetime Aggressive 2025Morningstar Lifetime Aggressive 2030Morningstar Lifetime Aggressive 2035Morningstar Lifetime Aggressive 2040Morningstar Lifetime Aggressive 2045Morningstar Lifetime Aggressive 2050Morningstar Lifetime Aggressive 2055

Morningstar Lifetime Conservative IncomeMorningstar Lifetime Conservative 2000Morningstar Lifetime Conservative 2005Morningstar Lifetime Conservative 2010Morningstar Lifetime Conservative 2015Morningstar Lifetime Conservative 2020Morningstar Lifetime Conservative 2025Morningstar Lifetime Conservative 2030Morningstar Lifetime Conservative 2035Morningstar Lifetime Conservative 2040Morningstar Lifetime Conservative 2045Morningstar Lifetime Conservative 2050Morningstar Lifetime Conservative 2055

Morningstar Lifetime Moderate IncomeMorningstar Lifetime Moderate 2000Morningstar Lifetime Moderate 2005Morningstar Lifetime Moderate 2010Morningstar Lifetime Moderate 2015Morningstar Lifetime Moderate 2020Morningstar Lifetime Moderate 2025Morningstar Lifetime Moderate 2030Morningstar Lifetime Moderate 2035Morningstar Lifetime Moderate 2040Morningstar Lifetime Moderate 2045Morningstar Lifetime Moderate 2050Morningstar Lifetime Moderate 2055

Target Risk

Morningstar ConservativeMorningstar Moderately ConservativeMorningstar ModerateMorningstar Moderately AggressiveMorningstar Aggressive

Multi-Asset High Income

Morningstar Multi-Asset High Income

Real Asset

Morningstar US Real Asset

Morningstar UK Real AssetMorningstar Global Real Asset

Asset Allocation Indexes

indexes.morningstar.com

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Morningstar® Indexes2012 13 Yearbook

Volume Eight22 West Washington StreetChicago Illinois 60602

100055-BRC-LO

Presorted StandardU.S. Postage P A I DMorningstar, Inc.

01 Harvesting the Morningstar Investment Research EcosystemSanjay Arya, CFA

02 The Morningstar Investment Research Ecosystem

03 Successful Products Grow from the Morningstar Ecosystem

04 What Makes a Moat?Paul Larson

09 Heading Upstream: A Route to Commodities that Bypasses the Futures MarketElizabeth Collins, CFA

13 Safety First—A Prudent Path to Corporate CreditDavid Sekera, CFA

16 Northern Trust Collaborates with Morningstar Indexes to Bring Distinctive FlexShare Products to Life

19 The Commodity-Currency ConnectionMallory Horejs

22 A New Income Frontier in Multi-Asset InvestingDavid Blanchett, CFA; Hal Ratner; Brian Huckstep, CFA

25 How to Benchmark Target-Date Funds: A Case StudyThomas Idzorek, CFA; Jeremy Stempien

31 Morningstar Indexes: New and Noteworthy

indexes.morningstarcorporate.morningstar.com/us/documents/brochures/indexes...25 how to benchmark...

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