Diversification Based Investing (DBI)

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Diversification Based Investing (DBI)

by QS Investors Research Group

Diversification Based Investing, or DBI, is an investment strategy that seeks

to take advantage of macro and behavioral inefficiencies in global and

international equity markets by developing a diversified exposure to macro

risk factors. DBI focuses purely on top-down portfolio construction rather

than bottom-up stock selection and uses analysis of correlations to create a

portfolio that is highly diversified across countries and sectors. In this paper,

we explain the rationale for DBI, the details of the investment process, and

present detailed analysis of its performance and characteristics to show why

we believe it can deliver:

1. Higher absolute and risk-adjusted returns than cap-weighted indices

2. Lower downside risk

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Over 10 years ago, QS Investors developed an investment approach aimed at taking advantage of macro inef-ficiencies in equity markets by developing a portfolio construction process with a greater degree of diversified exposure to macro risk factors. Through analysis of country and sector correlations, this strategy, called Diversifi-cation Based Investing (DBI), constructs a portfolio that is highly diversified across these factors.

It is based on three key beliefs:

l_{Geography and sector are key drivers of global equity risk and return}

l _{Market sentiment generates momentum effects in indices, which leads to concentration risk} that builds and collapses

l A more diversified portfolio can help mitigate concentration risk and downside risk

Executive Summary

Recent academic and practitioner research lends support to these beliefs by pointing out that a large part of returns in global equity markets are driven by macro effects: the business a company is in (sector) and where the business is located (geography). Jung and Shiller have asserted that markets show macro-inefficiency “in the sense that there are long waves in the time series of aggregate indices of security prices below and above various definitions of

fundamental values.”1

However, most active equity managers focus on stock selection to beat their benchmarks despite the argument from academic research that equity markets

show considerable micro efficiency.2_{Individual security}

mispricings tend to be wiped out fairly quickly.

This provides broader investment opportunities to add value at the macro level through portfolio construction rather than stock selection. DBI’s top-down portfolio construction process takes advantage of these findings and has consistently added value, delivering:

l Higher risk-adjusted returns than the MSCI World

and MSCI EAFE indices*

l _{Outperformance in both up and down markets*}

l _{Low correlation of excess return to both indices and}

stock selection managers*

From inception through December 31, 2012, the DBI World and DBI EAFE strategies have outperformed their benchmarks with a similar level of volatility, as outlined below. In 2011, a DBI ACWI strategy was launched which has also outperformed the benchmark over the past two years (FIGURE 26).

DBI World performance

August 1, 2001 (inception) to December 31, 2012 Annualized Return Excess Return Annualized Volatility Active Risk Information Ratio

DBI World Composite (Gross) 5.52% 1.57% 15.95% 2.55% 0.62

DBI World Composite (Net) 5.36% 1.40% — — —

MSCI World Index Net USD 3.96% — 16.64% — —

DBI EAFE performance

February 1, 2002 (inception) to December 31, 2012 Annualized Return Excess Return Annualized Volatility Active Risk Information Ratio

DBI EAFE Composite (Gross) 8.25% 1.92% 18.12% 2.95% 0.65

DBI EAFE Composite (Net) 7.88% 1.55% — — —

MSCI EAFE Index USD 6.33% — 18.43% — —

Source: QS Investors, MSCI

*Past performance is not an indication of future results. The historical returns achieved by the account are not a prediction of future perfor-mance and there can be no assurance that these or comparable returns will be achieved or that the account’s perforperfor-mance objective will be achieved. Please see the accompanying composite description for additional composite information. Fees are described in detail in QS Investors Form ADV 2A.

1_{Jung and Shiller (2005)}

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FIGURE 1: Drivers of Global Equity Market Returns

Importance of Country, Currency and Industry Rolling 12 Month Average (December 1999–March 2012)

Source: QS Investors

Factor returns are regressed cross-sectionally on country, currency and industry. 0% 10% 20% 30% 40% 50% 60%

Dec 99 Dec 00 Dec 01 Dec 02 Dec 03 Dec 04 Dec 05 Dec 06 Dec 07 Dec 08 Dec 09 Dec 10 Dec 11 Mar 12

Weight in Index

Introduction

Many active equity managers focus on stock selection to beat their benchmarks. QS Investors has developed a very different active management approach— aimed at creating a high level of diversification across geography and sectors, rather than identifying indi-vidual mispriced securities. We believe this approach can outperform consistently.

The strategy, called Diversification Based Investing (DBI), uses analysis of correlations to create a portfolio that is highly diversified across countries and sectors. In this paper, we explain the rationale for DBI, present detailed analysis of its performance and characteris-tics, and show why we believe it can deliver:

l_{Better risk-adjusted returns than its benchmark}

l_{Lower downside risk}

l Low correlation of excess returns to other managers

The paper is structured as follows:

1 | Rationale and Philosophy of DBI

2 | DBI Investment Process

3 | Performance Analysis

4 | Risk and Exposures inherent in the strategies

5 | The next step in diversification

1 | Rationale and philosophy

DBI is based on three key beliefs:

l_{Geography and sector are key drivers of global equity}

risk and return

l_{Market sentiment generates momentum effects in}

indices, which leads to concentration risk that builds and collapses

l_{A diversified portfolio can help mitigate}

concentra-tion risk and downside risk

The rationales for the first two beliefs are given below. The third is explained in section three, “Performance analysis.”

Belief 1

|

Macro factors (Geography,

Cur-rency and Sector) drive global equity risk

and return

In 2001, Hopkins and Miller found that geography (where a company does business) and sector (the type of business that a company is engaged in) explained 40% of the MSCI World Index returns

during the time period 12/92-12/00.3_{The remaining}

60% included stock specific information and the randomness in the stock return data. Given that equity returns exhibit a great deal of randomness, they concluded that country and industry factors were the key drivers of return. We extended this analysis and found similar results; from December 1999 through June 2011 we found that country, currency, and industry explain 41% of returns for the MSCI World Index. Their importance is even more significant over the recent past, explaining 47% of returns over the last three years.

This is quite apparent in FIGURE 1. Despite this, most active equity strategies focus primarily on identifying mispricings of individual companies. In contrast, DBI’s investment process focuses on geography and sector.

3_{Hopkins and Miller (2001) “Country, sector, and company factors in global equity portfolios,” The Research Foundation of AIMR} and Blackwell Series in Finance

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FIGURE 2: Market Sentiment Led to Concentration in Japan Equities

Index Weight of Japan in MSCI World Index

December 31, 1985–November 30, 2007

Source: MSCI World Index

FIGURE 3: Market Sentiment Led to Concentration in TMT Equities

Index Weight of Technology, Media and Telecommunications (TMT) Stocks in the MSCI World Index

December 31, 1991–November 30, 2001

Source: MSCI World Index

Belief 2

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Market sentiment leads to

concentration risk

Broad equity indices are often considered highly diversified investments. And yet, market sentiment— or, put another way, investors’ collective enthusiasm —can cause dangerous concentrations in certain index constituents.

The MSCI World Index is one of many benchmarks to have experienced concentrations that build up and then collapse. Two prime examples—from different decades—involved Japanese equities and Technology, Media and Telecom (TMT) stocks.

In the 1980s, an equity and real estate market bubble in Japan drove domestic equity prices up much faster than stock prices in the rest of the world. At the peak of the bubble in July 1989, Japanese stocks accounted for 35% of the MSCI World Index by weight, up three and a half times from only 10% four years earlier (FIGURE 2). The concentration was even higher in the MSCI EAFE index, with Japan representing over 65% of the benchmark. As investors came to realize they had been overly optimistic on Japan’s prospects, the country’s stocks started to fall in value. They continued to do so over the next 10 years—a period that was to

become known as Japan’s “lost decade.”4

4_MSCI 0% 10% 20% 30% 40% Jan 2007 Jan 2005 Jan 2003 Jan 2001 Jan 1999 Jan 1997 Jan 1995 Jan 1993 Jan 1991 Jan 1989 Jan 1987 Jan 1985 Weight in Index July 1989 0% 10% 20% 30% Nov 2001 Dec 2000 Dec 1999 Dec 1998 Dec 1997 Dec 1996 Dec 1995 Dec 1994 Dec 1993 Dec 1992 Dec 1991 Weight in Index Capitalization Weight February 2000

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A similar example occured in the late 1990s. The weight of TMT stocks in the MSCI World Index surged from just over 10% to almost 25% (FIGURE 3). The increased weight reflected a strong enthusiasm for TMT stocks. But it also generated momentum that propelled the collective market capitalization of TMT stocks even higher, as index tracking funds and active managers

bid up the stocks.5

In our view, these concentrations resulted from consistent and repeated patterns of investor behavior. Over the long-term, investors tend to agree on the intrinsic value of a stock. But in the short-term—and for more extended periods during bubbles—market cap-weighted benchmarks often overweight overval-ued stocks as investors become too optimistic about their growth potential, and underweight undervalued

stocks for the opposite reason. This phenomenon has been widely documented in academic literature over the

last several years.6

More recent examples include the excessive optimism surrounding financial stocks from 2005 to 2007 and relative pessimism for healthcare stocks. Financial stocks increased in weight in the MSCI World Index to more than 25% by 2007, by which time the weighting of healthcare stocks had declined to less than 10% (FIGURE 4). In 2008, Financials was the worst perform-ing sector in the index, while the healthcare sector outperformed all others.

DBI’s investment process is designed to counteract the concentration risk seen in market capitalization-weighted indices.

5_Ibid

6_{Financial Analysts Journal (Treynor, 2005), Journal of Investing (Hamza, et al, 2007)}

5/15/2009 12/31/2008 6/30/2008 12/31/2007 6/29/2007 12/29/2006 6/30/2006 12/30/2005 6/30/2005 12/31/2004 6/30/2004 12/31/2003 6/30/2003 12/31/2002 6/28/2002 12/31/2001 6/29/2001 12/29/2000 6/30/2000 12/31/1999 6/30/1999 5% 10% 15% 20% 25% 30% Weight

Financials Health Care

FIGURE 4: Concentration Risk Can Detract from Diversified Benefits

Index Weight of Financials and Health Care

June 30, 1999–May 15, 2009

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Academic foundations

Academics, theorists and practitioners have argued for decades over whether active stock selection can consistently add value. However, when it comes to global and international equity management, we believe that perhaps their focus has been misdirect-ed. A growing body of academic literature and empirical data point to greater inefficiency – and therefore better investment opportunities – when looking across macro markets. Nobel prize winner Paul Samuelson theorized that “Modern markets show considerable micro efficiency…I had hypoth-esized considerable macro inefficiency, in the sense of long waves in the time series of aggregate indices of security prices below and above various definitions of

fundamental values.” 7_{In other words, when two}

companies with similar products and clients have a large divergence in valuation, stock pickers step in and arbitrage away any micro inefficiency. In 2006, Jung and Shiller concluded, “the aggregate averages

out the individual stories of the firms and the reasons for changes in the aggregate are more subtle and harder for the investing public to understand, having to do with national economic growth, stabilizing monetary policy and the like…factors such as stock market booms and busts swamp out the effect of information about future dividends in determining

price…”8_{Consistent with this theory, countries and}

sectors have shown consistent and persistent patterns of bubbles and busts; people become overly optimistic and overshoot on the upside and become overly pessimistic and undershoot on the downside. As mentioned above, examples of bubbles include Japan in the 1980’s, TMT (Technology, Media, and Tele-com) in the 1990’s and Financial Stocks in the 2000’s. Rather than diminishing, this pattern has become

broader, more persistent and increasing in frequency.9

The charts below provide additional illustrations of greater than average valuation swings at both the country and sector level over the last 25 years.

7_{Jung and Shiller (2006) “Samuelson’s dictum and the stock market” Cowles Foundation, Yale University} 8_Ibid

9_{Norman and Thiagarajan (2009) “Asset bubbles and market crisis” Journal of Investing, vol 18, no. 4}

FIGURE 5: Investors Become Overly Optimistic & Pessimistic

Valuation

January 1986–January 2011 1986 1991 1996 2001 2006 2011 Price/Book Average 0 1 2 3 4 1986 1991 1996 2001 2006 2011 Price/Book Average 0 1 2 3 4 1986 1991 1996 2001 2006 2011 Price/Book Average 0 2 4 6 8 1986 1991 1996 2001 2006 2011 Price/Book Average 0 2 4 6 8

Health Care Price/Book vs Average Sweden Price/Book vs Average

Basic Materials Price/Book vs Average Hong Kong Price/Book vs Average

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2 | The DBI investment process

DBI takes into account the observed characteristics of markets and indices described earlier, and uses them to create a more diversified portfolio. The strategy’s investment process has five steps:

1 | Partition: Classify all stocks by the key drivers of risk/ return: geography and sector

2 | Cluster: Identify highly correlated geographies and sectors, and group them together in “clusters”

3 | Weight: Equal weight the clusters. The objective of equal weighting is to achieve a high level of diversification

4 | Implement Efficiently: Convert the model portfolio weights into the live portfolio via an “optimization” process

5 | Rebalance: Capture changes in market dynamics quarterly

These five steps are described in more detail.

Step 1

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Partition

The objective of this step is to group together stocks with common drivers of risk and return. We use the MSCI index company’s classifications of stocks by region and sector as a starting point. We then divide the stock universe—for example, the MSCI World Index—into “region/sector risk units,” which are determined by both geography and sector, and based

on the index providers classification of each. Typical region/sector risk units include Americas Energy (Unit 1) and EMU Healthcare (Unit 2), shown in FIGURE 6.

Step 2

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Cluster

In this step, we cluster the region/sector risk units together into what, we believe, are the key drivers of risk and return. We use statistical analysis and research based on correlations over the last five years to identify region/sector risk units that are highly correlated with each other. Highly correlated region/sector risk units are grouped into the same clusters. The resulting portfolio exhibits high correlations within clusters and low correlations between clusters. Examples of clusters are shown in FIGURE 7.

Some clusters are based primarily around sectors, while others are driven more by geography. In FIGURE 7, the region/sector units in the Global Commodities Cluster have a common exposure to oil and gas prices; the stocks of companies in this sector have been subject to global forces, irrespective of where the company is based. The European NonCyclical Cluster is geographi-cally driven; its stocks have a common exposure to Europe. Although these region/sector units encompass a variety of industry sectors, many of the companies represented focus primarily on Europe, which is why they show a high degree of correlation.

Consumer Discretionary

Consumer

Staples Energy Financials Health Care Industrials

Information Technology Materials Telecom Services Utilities Americas Unit 1 Asia EMU Unit 2 Non-EMU

FIGURE 6: Step 1—Partition the Universe into Region/Sector Units

Example of Two “Risk Units” within DBI World Portfolio

Source: QS Investors For illustrative purposes only

Consumer Discretionary

Consumer

Staples Energy Financials Health Care Industrials

Information Technology Materials Telecom Services Utilities Americas Asia EMU Non-EMU

FIGURE 7: Step 2—Group Highly Correlated Region/Sector Units into Clusters

Example of Two “Clusters” within DBI World Portfolio

■ Cluster 1 ■ Cluster 2

Source: QS Investors For illustrative purposes only

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Step 3

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Weight

This step forms the heart of our portfolio construction process. The objective is to engineer a diversified exposure to the key drivers of risk and return by equally weighting all clusters and the risk units within each cluster.

Below, FIGURE 8 shows a portfolio comprising six clusters, each with a weighting of one-sixth (16.67%) of the total portfolio. Next, we equal weight the region/sector units within each cluster. This means that the weight of an individual unit in the portfolio is inversely proportional to the total number of risk units in its cluster. In other words:

l_{Region/sector risk units in clusters that contain many}

units have relatively smaller weights in the portfolio: see the Americas and European Cyclicals Cluster in the table on the following page, which contains 15 region/sector risk units, each with a portfolio weight-ing of 1.11% (i.e., 16.67% ÷ 15). By construction, risk units in more crowded clusters will be highly corre-lated with more of the other risk units; therefore, they are not good portfolio diversifiers and should have a lower weight.

l_{Region/sector risk units in clusters that contain fewer}

units have relatively larger weights in the portfolio: see the Asian Cyclicals region/sector, which contains four risk units, each with a weight of 4.17% (i.e., 16.67% ÷ 4). Region/sector risk units in less crowded clusters are highly correlated to fewer other units. Even though clusters are determined by our analysis of correlations, there is generally a clear theme within each. For example, the clusters as of December 2012 are:

l_{Global Commodities}

l_{Asian Cyclicals}

l European Non-Cyclicals: Europe

l Americas and Non-EMU Non-Cyclicals

l_{Americas and European Cyclicals}

l_{Americas and Asia High Dividend}

To further illustrate how good and bad diversifiers are weighted in the portfolio, FIGURE 8 shows how DBI equal weights across themes. For example, due to the large weight to North America in the cap weighted index, Americas and European Cyclicals comprise almost half of the index. In contrast, DBI gives the macro theme one-sixth of the portfolio, or 16.67%.

FIGURE 8: DBI World is More Diversified Across Macro Themes

Market Cap weighting stocks leads to concentrated risks

As of June 2012

Source: QS Investors, MSCI For illustrative purposes only

0% 25% 50% 75% 100%

DBI World Strategy MSCI World Index

Non-Cyclicals: Europe Americas & Asia High Dividend Asian Cyclicals

Non-Cyclicals: Americas & North EMU Global Commodities

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Portfolio Weight Global Commodities: 16.67% 3.33% Americas Energy 3.33% Americas Materials 3.33% EMU Energy

3.33% Asian and non-EMU Energy

3.33% European and Asian Materials

Asian Cyclicals: 16.67%

4.17% Asia Industrials

4.17% Asia Consumer Discretionary

4.17% Asia Financials

4.17% Asia Information Technology

European Non-Cyclicals: Europe: 16.67%

3.33% EMU Consumer Staples

3.33% EMU Health Care

3.33% EMU Telecommunications

3.33% Non-EMU Telecommunications

3.33% European Utilities

Americas and Non-EMU Non-Cyclicals: 16.67%

3.33% Americas Consumer Staples excludes Retailing

3.33% Americas Health Care

3.33% Americas Pharmaceuticals

3.33% Non-EMU Consumer Staples

3.33% Non-EMU Health Care

Portfolio Weight

Americas and European Cyclicals: 16.67%

1.11% Americas Industrials

1.11% Americas Consumer Discretionary

1.11% Americas Media

1.11% Americas Food and Staples Retailing

1.11% Americas Financials

1.11% Americas Diversified Financials

1.11% Americas Information Technology

1.11% Americas Information Technology Services

1.11% EMU Industrials

1.11% EMU Consumer Discretionary

1.11% EMU Financials

1.11% Non-EMU Industrials

1.11% Non-EMU Consumer Discretionary

1.11% Non-EMU Financials

1.11% European Information Technology

Americas and Asia High Dividend: 16.67%

5.56% Americas Telecommunications

5.56% Americas Utilities

5.56% Asia Consumer Staples, Telecom Services,

Healthcare, Utilities

FIGURE 9

Example of All “Clusters” within DBI World Portfolio (as of June 2012)

Source: QS Investors as of June 2012 For illustrative purposes only

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Step 4

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Implement Efficiently

In this step, we convert the model portfolio weights into the live portfolio via an optimization process. The primary purpose is to produce a favorable trade-off between implementation costs and a faithful representation of the model portfolio.

The end result is a portfolio whose exposures, risk characteristics and realized performance closely match the model, but with slightly lower turnover and fewer holdings. For example, the DBI World Model portfolio may hold around 1600 names, whereas the live portfolio tends to hold roughly 900. Our efficient implementation process provides a number of benefits including:

l_{The ability to control for liquidity and market impact}

l Lower turnover (reduced trading costs)

l Fewer holdings/trades (operational efficiency, lower

custody fees)

l_{Efficient integration of client-specific restrictions (e.g.}

SRI or ESG)

Step 5

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Rebalance

The objective of this step is to capture structural changes between geography and sectors, while minimizing turnover to keep transaction and market impact costs low.

We perform the clustering process annually in June and rebalance back to equally weighted clusters quarterly (FIGURE 10).

FIGURE 10

Cluster June Cluster June Rebalance September Rebalance December Rebalance March 12/31/2008 9/30/2008 6/30/2008 3/31/2008 12/31/2007 9/28/2007 6/29/2007 3/30/2007 12/29/2006 6% 8% 10% 12% 14% 16% 18% 20% Weights

DBI World MSCI World

Increasing correlations to Materials sector leads to underweight Decreasing

correlations to Utilities lead to increasing overweight

FIGURE 11: DBI Dynamically Reacts to Correlation Changes

Energy Sector Weight in DBI World and MSCI World

Data based on portfolio holdings as of December 31, 2008 Source: QS Investors, MSCI

The statistics discussed in this presentation are based on the unreconciled holdings of a representative portfolio which is included in the composite; your account may differ due to specific client guidelines and restrictions.

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Dynamic portfolio construction

Changes in cluster composition are based on changes in correlation between risk units. When correlations between risk units change, weightings will increase or decrease a sector or region. One example that illus-trates this process is our changing exposure to the Energy sector, as illustrated in FIGURE 11. In 2007 we were slightly overweight Energy stocks versus the benchmark as Energy stocks had a relatively low correlation to other sectors. Prior to this time period, Utilities stocks had been highly correlated to Energy stocks and thus they were combined in one cluster. But the correlation declined over time; indeed, Energy stocks began to show low correlation with all other risk units as oil prices and the earnings of Energy compa-nies increased. So at the June 2007 clustering, they formed a cluster comprised exclusively of Energy stocks. Since there were a smaller number of units within the cluster, each risk unit had a larger weight. As a result, we were overweight Energy stocks versus the benchmark in 2007.

By the June 2008 clustering, Materials stocks were showing higher correlation with Energy stocks, as investors began to think that the prices of all com-modities were rising together. Therefore Materials and Energy were combined into a cluster. The addition of Materials reduced the weight of Energy stocks in the portfolio, and we moved to an underweight position in Energy versus the benchmark.

This enabled DBI to capture the relative outperformance of Energy stocks driven by the boom in oil prices, and avoid the Energy sector’s relative underperformance when oil prices declined. FIGURE 11 shows the weight of Energy stocks in DBI and its benchmark. Returns from Energy stocks peaked in June 2008 and then declined, just as DBI moved to an underweight Energy position.

The increasing correlation between Energy and Materials stocks leading up to the June 2008 clustering reflected a broader trend of rising correlations between sectors.

Cluster theme

On the following page, FIGURE 12 shows how clusters changed from 2011 to 2012.

Many of the dominant themes from 2011 were similarly represented in the June 2012 clustering, such as cyclicals and non-cyclicals.

Financials and Industrials continue to exhibit high correlations to other units and therefore continue to have one of the largest underweights. Telecommunica-tions, Utilities and Health Care have the largest overweights as they continue to be less correlated to other region/sector units.

Last year, we saw a predominantly Global Health Care clustered-theme. In 2012 Health Care combined with Consumer Staples to form an Americas and Non-EMU Non-Cyclicals cluster.

The weight to the Energy sector in 2012 moved from an overweight to a small underweight. This is due to the pure Energy cluster combining with Materials, forming the current Global Commodities Cluster. The current commodities cluster indicates a stronger relationship between Energy and Materials, which is a recurring theme. In June 2007, we saw a pure Energy cluster. The following year in 2008, prior to the energy bubble crash (July 2008), Energy and Materials com-bined together, indicating Energy was not as good a diversifier. We saw a shift in themes as the active weight to Asia Cyclicals increased. For the last two years, we saw Asia Cyclicals and Materials cluster together. This year, Materials combines with Energy instead of Asia leading to a pure Asia Cyclical cluster.

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Portfolio

Weight

June 2011

Global Energy: 16.67%

5.56% Americas Energy

5.56% EMU Energy

5.56% Asian and Non-EMU Energy

Asian Cyclicals and Materials: 16.67%

2.78% Americas Materials

European Non-Cyclicals: 16.67%%

Global Health Care and Non-Cyclicals: 16.67%

4.17% Asia Consumer Staples, Telcom Services,

Health Care, Utilities

Americas IT and Telecom: 16.67%

5.56% Americas Telecommunications Portfolio Weight

June 2012

Global Commodities: 16.67% 3.33% Americas Energy 3.33% Americas Materials 3.33% EMU Energy

3.33% Asian and non-EMU Energy

Asian Cyclicals: 16.67%

European Non-Cyclicals: 16.67%

3.33% Non-EMU Telecommunications

Americas and Non-EMU Non-Cyclicals: 16.67%

Americas and Asia High Dividend: 16.67%

5.56% Americas Telecommunications

5.56% Americas Utilities

5.56% Asia Consumer Staples, Telecom Services,

Healthcare, Utilities

FIGURE 12

DBI Portfolio in June 2011 and June 2012

For illustrative purposes only. The weightings are based on a representative portfolio, which is included in the composite. A client’s account may differ due to specific guidelines and restrictions.

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3 | Performance analysis

In this section, we detail DBI’s backtested and live perfromance (through December 31, 2012). The analysis presented is for the DBI World strategy—other DBI strategies are introduced in the final part of this paper. The strategy has delivered higher absolute and risk-adjusted returns than its benchmark in both analysis periods.

During the live period, from inception in August 2001 to December 2012, DBI World returned 5.52%,

outperforming the MSCI World Index by 157 basis points (gross of fees) on an annualized basis, with an annualized volatility of 15.95% (FIGURE 13) and an information ratio of 0.62.

In the backtesting period from March 1985 to July 2001, DBI delivered an annualized excess return of 175 basis points for an active risk level (tracking error) of 4.1% (FIGURE 14).

Annualized

Return Annualized Volatility Beta Active Risk Excess Return Information Ratio

DBI World Composite (Gross) 5.52% 15.95% 93% 2.55% 1.57% 0.62

DBI World Composite (Net) 5.36% — — — 1.40% —

MSCI World Index (Net) 3.96% 16.64% — — — —

Past performance is not an indication of future results. The historical returns achieved by the account are not a prediction of future performance and there can be no assurance that these or comparable returns will be achieved or that the account’s performance objective will be achieved. Please see the accompanying composite description for additional composite information. Fees are described in detail in QS Investors Form ADV 2A.

FIGURE 13

DBI World Live Performance — August 1, 2001 (inception) to December 31, 2012

Annualized

Return Annualized Volatility Beta Active Risk Excess Return Information Ratio

Hypothetical DBI World 14.85% 14.82% 96% 4.09% 1.75% 0.43

MSCI World Index (Gross) 13.10% 14.89% 100% — — —

The DBI hypothetical backtest employs the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process which slices the MSCI World equity universe into regional and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. Transaction costs are assumed to be 20bp each way. Old industry definitions are used until May 2000 and the new GICs classifications are used thereafter. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. There are numerous other factors related to the markets in general or to the imple-mentation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results. Please see hypothetical disclosures for additional information on hypothetical information.

FIGURE 14

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Understanding performance patterns

DBI World has shown consistent patterns of perfor-mance. These are explored below.

Low correlation with many other active strategies

Because DBI uses a differentiated portfolio construc-tion process, the strategy has shown low correlaconstruc-tion of excess returns to most active managers that focus on stock selection. FIGURE 15 illustrates the correlation of DBI’s excess returns to those of strategies run by the 10 largest global managers in a leading investment consultancy’s database. The correlation is disbursed between 0.51 and -0.04, supporting our view that DBI World can be a strong portfolio diversifier for investors.

FIGURE 15

DBI World Correlation of Excess Return to Ten

Largest Global Equity Managers

-1.0 -0.5 0.0 0.5 1.0 J I H G F E D C B A Managers Corr ela tion

Time period: Ten years as of December 2012

Source: Consultant Manager Universe, Zephyr StyleAdvisor

Outperformance in up and down markets

On average DBI has outperformed whether the market moved up or down. FIGURE 16 shows that DBI World captured more positive stock movements than its benchmark, and avoided some of the benchmark’s negative movements. DBI has outperformed by more in down markets than up markets, and so offers potential for downside protection.

FIGURE 16

DBI World Composite Supplemental Live

Performance*

Down Market Capture Up Market Capture Mark et P ar ticipa tion 99% 90% As of December 31, 2012 Since inception: August 2001 Source: Zephyr StyleAdvisor Based on quarterly returns.

*Please see the DBI World Composite for full disclosures. Time period used by QS Investors to report performance of GIPS-compliant composites.

Past performance is not indicative of future results. This information is supplemental to the composite description. Please see the accompanying composite description for additional composite information.

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Consistency

DBI World has exhibited consistency of excess returns. As illustrated by the two charts below, FIGURE 17 shows five-year Rolling Excess Return since inception, while FIGURE 18 displays cumulative returns of the DBI World backtest and of the benchmark.

-1 0 1 2 3 4

Jun 06 Dec 06 Jun 07 Dec 07 Jun 08 Dec 08 Jun 09 Dec 09 Jun 10 Dec 10 Jun 11 Dec 11 Jun 12 Dec 12

Percent 0 2 4 6 8 10 12 14 3/31/2001 3/31/2000 3/31/1999 3/31/1998 3/31/1997 3/31/1996 3/31/1995 3/31/1994 3/31/1993 3/31/1992 3/31/1991 3/31/1990 3/31/1989 3/31/1988 3/31/1987 3/31/1986 3/31/1985

MSCI World Benchmark (Net Index USD) Hypothetical DBI

FIGURE 17

DBI World Composite Five-Year Rolling Excess Return — August 2001 to December 2012

Past performance is not indicative of future results. Performance is shown gross of fees and does not reflect investment advisory fees. Had such fees been deducted, returns would have been lower. This information is supplemental to the composite description. Please see the accompanying composite description for additional composite information.

The DBI hypothetical backtest employs the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process which slices the MSCI World equity universe into regional and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results. Please see hypothetical disclosures for additional information on hypothetical information.

FIGURE 18

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Avoiding concentrations

DBI’s ability to avoid some of the concentrations found in market capitalization-weighted indices was high-lighted during the TMT bubble. DBI’s weight in these sectors increased as they started to have a lower correlation to the broad market while outperforming many parts of the market. However, our equal

weight-4 | Risk and exposures

This section outlines the strategy’s risk exposures. DBI has no persistent active style or size biases relative to its benchmark.

As we showed earlier (FIGURE 13), DBI’s total volatility was approximately 69 basis points lower than that of the MSCI World Index from inception to 12/31/2012, and similar to that of the benchmark in the backtesting period (FIGURE 14). FIGURE 20 gives a decomposition of DBI’s active risk, based on an Axioma analysis of holdings as of June 2012. The largest contributors to risk are country, industry, and currency—an expected outcome given the focus of our investment process.

ing of clusters limited the exposure that we had in these sectors which provided diversification. Thus our weight increased less dramatically during the bubble, and fell only modestly when the bubble burst. This illustrates the diversification and the benefit of the DBI strategy when compared to the MSCI World Index (FIGURE 19). 0% 10% 20% 30% Nov 2001 Dec 2000 Dec 1999 Dec 1998 Dec 1997 Dec 1996 Dec 1995 Dec 1994 Dec 1993 Dec 1992 Dec 1991 Weights Capitalization Weight February 2000 Hypothetical DBI Weight

FIGURE 19: Concentration Risk Can Build and Collapse

Capitalization Weight of Technology, Media, and Telecommunication (TMT) Stocks

December 31, 1991—November 30, 2001

The DBI hypothetical backtest employs the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process which slices the MSCI World equity universe into regional and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. Please see hypothetical disclosures for additional information on hypothetical information.

FIGURE 20: Active Risk is Driven by

Industry, Country and Currency

Decomposition of Active Risk — June 2012

Source: Axioma

The weightings are based on a representative portfolio, which is included in the composite. A client’s account may differ due to specific guidelines and restrictions.

Periods ending June

Risk Indices include: Global Market, Value, Leverage, Growth, Size, ST Momentum, MT Momentum, Volatility, Liquidity and FX Sensitivity. 0% 20% 40% 60% 80% 100% 120% 2006 2007 2008 2009 2010 2011 2012 Industry Country Currency Risk Indices

MACRO RISK

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Region and sector exposures

As of December 2012, DBI’s largest regional position was an underweight of North America relative to the benchmark (FIGURE 21). The US is a large integrated market, comprising over 50% of the MSCI World Index, and is subject to powerful common risk factors. Because of this, US risk units tend to fall into common clusters—recall that clusters with more risk units result in smaller portfolio weights for each unit within that cluster, and vice versa. Moreover, US companies

make up a large portion of globally integrated indus-tries, such as Industrials and Financials, which also tend to fall into large clusters.

By sector, the largest underweight was to Financials (FIGURE 22). Financials is the largest global sector— almost 20% of the index—and its stocks correlate strongly both with one another and with other cyclical sectors. For this reason, Financial stocks tend to be grouped in clusters with a large number of risk units.

FIGURE 21

Region Weights for December 2012

FIGURE 22

Sector Weights for December 2012

0% 10% 20% 30% 40% 50% 60% Non-EMU EMU AsiaPac North America

DBI World MSCI World Index

0% 5% 10% 15% 20% 25% Materials Industrials Information Technology Consumer Discretionary Financials Energy Utilities Consumer Staples Telecommunication Services Health Care

DBI World MSCI World Index

The statistics discussed are based on the unreconciled holdings of a representative portfolio which is included in the composite; your account may differ due to specific client guidelines and restrictions.

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Style and size exposures

Our analysis confirms that DBI has had no persistent size or style bias since inception. DBI’s average Price- to-Book (P/B) ratio was slightly lower than the index in the first four years after inception and in 2008 but slightly above benchmark from 2004 to 2007 (FIGURE 23).10

FIGURE 24 presents the corresponding analysis for size. DBI World had a slight bias toward small-cap stocks from 2002 to 2004, and in 2006 and 2008, but a slight large-cap bias in the other three years.

FIGURE 23

Price/Book Since Inception

FIGURE 24

Market Capitalization Since Inception

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001

Price/Book DBI World Price/Book MSCI World Index (Net)

0 10 20 30 40 50 60 70 80 90 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001

Market Cap DBI World Market Cap MSCI World Index (Net)

10_{The average P/B ratio for a portfolio is computed as a “harmonic mean.” This is the total price of the portfolio divided by the total} book value, i.e., it is simply the P/B ratio of the portfolio. For the average capitalization of stocks in a portfolio, we use a portfolio-weighted average rather than the usual arithmetic average. This measure of average capitalization has the important property that it is insensitive to the presence of many small positions, as long as their total portfolio weight is small.

2.61 1.93 2.32 2.43 2.74 2.71 2.98 1.46 1.78 1.91 1.60 1.66 2.82 2.18 2.50 2.47 2.68 2.64 2.75 1.49 1.85 1.83 1.61 1.77

67.27 55.17 64.64 68.77 69.78 74.35 84.47 51.43 65.63 69.62 60.47 57.70 57.57 61.70 70.84 71.88 68.38 76.96 81.12 58.58 65.43 66.30 65.48 72.00

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FIGURE 25

DBI EAFE Performance — February 2001 to December 2012

5 | The next steps

in diversification

DBI EAFE

Our extensive research into the DBI concept resulted in the development of DBI EAFE(European, Australasia and Far East). DBI EAFE has the same objective and philosophy as DBI World, but uses more granular risk units based on country and sector (rather than region and sector). A typical country/sector unit for DBI EAFE might be France Information Technology. The cluster and weighting procedures are identical to those used in DBI World.

Using country rather than region leads to:

l More clusters

l Higher volatility between clusters

l_{Lower correlation between clusters}

l_{A higher expected absolute and risk-adjusted return}

Since January 2006, DBI EAFE has followed this portfolio construction methodology. Since inception in February 2002, DBI EAFE has generated an annualized return of 8.25% versus 6.33% for the MSCI EAFE Index, with an annualized volatility of 18.12%.

DBI EAFE performance

February 1, 2002 (inception) to September 30, 2011 Annualized Return Excess Return Annualized Volatility Active Risk Information Ratio

DBI EAFE Composite (Gross) 8.25% 1.92% 18.12% 2.95% 0.65

DBI EAFE Composite (Net) 7.88% 1.55% — — —

MSCI EAFE Index USD 6.33% — 18.43% — —

*Past performance is not an indication of future results. The historical returns achieved by the account are not a prediction of future performance and there can be no assurance that these or comparable returns will be achieved or that the account’s performance objective will be achieved. Please see the accompanying composite description for additional composite information. Fees are described in detail in QS Investors Form ADV 2A.

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Performance Annualized Return Annualized Volatility Beta Active Risk Excess Return Information Ratio

Hypothetical DBI ACWI 6.01% 17.38% 99% 2.84% 3.40% 1.20

MSCI All Country World Index 2.62% 17.40% N/A N/A N/A N/A

Assumption – 50 bps of transaction costs per year

The DBI ACWI back-test employs the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process which slices the MSCI All Country World Index universe into region and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. Hypothetical performance is not an indicator of future actual results and do not represent returns that any investor actually attained. No representation is being made that any portfolio will, or is likely to replicate the information shown. A client’s account may differ due to specific guidelines and restrictions. Past performance is no guarantee of future results. Both back-test and benchmark returns are considered gross of withholding tax. Please see the Appendix for important information on hypothetical performance.

FIGURE 27

DBI ACWI Hypothetical Performance — June 2000 to December 2010

Performance Annualized Return Annualized Volatility Beta Active Risk Excess Return Information Ratio

Hypothetical DBI Emerging Markets 13.71% 22.64% 91% 4.91% 3.47% 0.71

MSCI Emerging Markets 10.24% 24.33% N/A N/A N/A N/A

Assumption – 50 bps of transaction costs per year

The DBI EM back-test employs the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process which slices the MSCI Emerging Markets Free universe into country and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. Each country weight is constrained within +/- 5% of the index weight. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. Hypothetical performance is not an indicator of future actual results and do not represent returns that any investor actually attained. No representation is being made that any portfolio will, or is likely to replicate the information shown. A client’s account may differ due to specific guidelines and restrictions. Past perfor-mance is no guarantee of future results. Both back-test and benchmark returns are considered gross of withholding tax. Please see the Appendix for important information on hypothetical performance.

FIGURE 28

DBI Emerging Markets Hypothetical Performance — June 2000 to December 2012

Performance Since Inception

DBI ACWI Composite (gross of fees) 4.28%

MSCI ACWI Index Net USD 3.73%

Value added 0.55%

As of December 31, 2012

Inception date: January 2011; time period used by QS Inves-tors, LLC to report performance of GIPS-compliant composites. Past performance is not necessarily indicative of future re-sults. Performance is shown gross of fees and does not reflect investment advisory fees.

Had such fees been deducted, returns would have been lower. Please see the appendix for additional composite information.

FIGURE 26

DBI ACWI Performance

DBI ACWI

QS Investors continues to expand the platform. In January of 2011, QS Investors launched DBI ACWI, a region/sector strategy benchmarked to the MSCI All Country World Index. The DBI methodology has proven effective within the broader ACWI Universe resulting in 0.55% excess return since inception.

DBI Emerging Markets

The DBI approach has also been applied to Emerging Markets through a country/sector approach. The backtest (FIGURE 28) exhibits results consistent with

the historical return patterns observed in our other DBI strategies. The hypothetical DBI Emerging Markets strategy outperformed the benchmark by 3.47% over the backtesting period.

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Summary

Diversification Based Investing (DBI) is an equity strategy that provides broad exposure and seeks higher risk-adjusted returns than its benchmark with less downside risk.

The DBI investment process is designed to capture the benefits of a higher level of diversification by taking into account the primary drivers of equity returns: geography and sector. Diversification is maintained by rebalancing the portfolio.

The primary drivers of DBI’s active risk exposures are from country and sector differences. The strategy has exhibited no persistent size or style bias relative to the MSCI World Index since inception (up to December 2012), and only modest bias at any given time.

Key benefits of the DBI strategies include:11

l_{Higher risk-adjusted returns: DBI targets a higher}

level of diversification than its benchmark, which

has produced higher risk-adjusted returns12

l_{Outperformance in both up and down markets with}

less downside risk: DBI has offered downside protection relative to its benchmark when equity

markets have declined11

l Low correlation of excess returns to other enhanced/

active managers: DBI’s differentiated methodology results in a low correlation of excess returns to many

traditional enhanced and active strategies12

11_{The strategy could underperform if a very narrow segment of the market has a very dramatic increase.} 12_{No assurance can be given that this will continue in the future.}

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Bibliography

Arnott, Robert D., Jason C. Hsu, and Philip Moore. “Fundamental Indexation.” Financial Analysts Journal 61(2), pp. 83-99. March/April 2005.

Bernstein, William J., and David Wilkinson. “Diversifica-tion, rebalancing, and the geometric mean frontier.” November 1997. Available at http://www.effisols.com/ basics/rebal.pdf.

Bird, Ron, Xue-Zhong He, Satish Thosar and Paul Woolley. “The case for market inefficiency: Investment style and market pricing.” Journal of Asset Management 5(6). April 2005.

Booth, David, and Eugene Fama. “Diversification return and asset contributions.” Financial Analysts Journal 48(3) pp. 26-32. May/June 1992.

Harvey, Campbell R. and Claude B. Erb. “The Tactical and Strategic Value of Commodity Futures.” Manuscript. February 2005. Available from the NBER website at http://www.nber.org/papers/w11222.pdf.

Rubinstein, Mark. Continuously rebalanced investment strategies. Journal of Portfolio Management. Fall 1991. Treynor, Jack. Why Market-Valuation-Indifferent Indexing Works. Financial Analysts Journal 61(5) pp. 65-69.September/October 2005.

Winston, Kenneth. The “efficient index” and prediction of portfolio variance. Journal of Portfolio Management. Spring 1993.

Author biographies

James Norman, President

l Responsible for assisting the CEO with all business, strategic and investment decisions. He is also panel member

of the Investment Oversight Committee.

l Formerly head of Deutsche Asset Management’s Quantitative Strategies Qualitative Alpha research. At Deutsche

Asset Management, he also served as Global Head of Product Management, Senior Portfolio Specialist for Active US Equity and Asset Allocation, and as a senior management consultant from 1995 to 2010. Prior to joining Deutsche Asset Management, he spent five years as a senior casualty underwriter for CIGNA International

l_{Education: AB from Vassar College; MBA from New York University}

Keri McLaughlin, Relationship Management

l Responsibilities include client service and reporting

l Formerly at Deutsche Asset Management from 2002 – 2010. She served as product specialist for the quantitative

strategies group from 2005 – 2010. Prior to joining the QS group, she worked as a Client Service Associate. Prior to joining Deutsche Asset Management, she had eight years of experience at Citigroup Asset Management, most recently as manager of the RFP team, and at State Street Bank, as senior fund accountant

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Hypothetical Disclosures

The DBI World, DBI World Plus and DBI ACWI backtests employ the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process.

The DBI World backtest slices the MSCI World equity universe into regional and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. The DBI World Plus backtest slices the MSCI World equity universe into country and sector units. These units are grouped into new clusters which have low correlations to each other and equally weighted. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. Transaction costs are assumed to be 20bp each way. Old industry definitions are used until May 2000 and the new GICs classifications are used thereafter.

The DBI ACWI backtest slices the MSCI All Country World Index universe into region and sector units. These units are grouped into new clusters which have low correlations to each other and are equally weighted. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis. Returns are net of 50 bps transaction costs.

The DBI EM (constrained) back-test employs the same investment process as the live DBI strategy. The investment process is a purely quantitative portfolio construction process which slices the MSCI Emerging Markets Free universe into country and sec-tor units. These units are grouped into new clusters which have low correlations to each other. Active country underweights/ overweights are constrained to be no more than 5%. The clusters are reconstituted annually and the portfolio is rebalanced back to the model on a quarterly basis

Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differ-ences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. For example, the ability to withstand losses or adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully ac-counted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results. Total returns for the ‘Model Portfolio’ presented herein do not reflect actual investor returns. The returns are calculated daily and are time weighted. They do not reflect the deduction of investment management fees or other expenses. If such fees and expenses were deducted, the results would be lower.

Transaction costs are assumed to vary depending on country and traded assets, but do not necessarily reflect the cost an actual account might experience. Past performance is not indicative of future results. The value of investments can go down as well as up. Exchange rate fluctuations may alter the value of your investment. The tax treatment of investments may change and you may get back less than you have contributed.

This material is intended for informational purposes only and it is not intended that it be relied on to make any investment decision. It does not constitute investment advice or a recommendation or an offer or solicitation and is not the basis for any contract to pur-chase or sell any security or other instrument, or for QS Investors, LLC and its affiliates to enter into or arrange any type of transaction as a consequence of any information contained herein. Neither QS Investors, LLC nor any of its affiliates, gives any warranty as to the accuracy, reliability or completeness of information which is contained in this document. Except insofar as liability under any statute cannot be excluded, no member of the QS Investors, LLC , the Issuer or any officer, employee or associate of them accepts any liability (whether arising in contract, in tort or negligence or otherwise) for any error or omission in this document or for any resulting loss or damage whether direct, indirect, consequential or otherwise suffered by the recipient of this document or any other person. The views expressed in this document constitute QS Investors’ judgment at the time of issue and are subject to change. This document is only for professional investors. This document was prepared without regard to the specific objectives, financial situation or needs of any particular person who may receive it. The value of shares/units and their derived income may fall as well as rise. Past performance or any prediction or forecast is not indicative of future results. No further distribution is allowed without prior written consent of the Issuer.

The forecasts provided are based upon our opinion of the market as at this date and are subject to change, dependent on future changes in the market. Any prediction, projection or forecast on the economy, stock market, bond market or the economic trends of the markets is not necessarily indicative of the future or likely performance.

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Important Information

This material was prepared without regard to the specific objectives, financial situation or needs of any particular person who may receive it. It is intended for informational purposes only and it is not intended that it be relied on to make any investment decision. It does not constitute investment advice or a recommendation or an offer or solicitation and is not the basis for any contract to purchase or sell any security or other instrument, or for QS Investors, LLC and its affiliates to enter into or arrange any type of transaction as a consequence of any information contained herein. Neither QS Investors, LLC nor any of its affiliates, gives any warranty as to the accuracy, reliability or completeness of information which is contained in this document. Except insofar as liability under any statute cannot be excluded, no member of the QS Investors, LLC, the Issuer or any officer, employee or associate of them accepts any liability (whether arising in contract, in tort or negligence or otherwise) for any error or omission in this document or for any resulting loss or damage whether direct, indirect, consequential or otherwise suffered by the recipient of this document or any other person.

The views expressed in this document constitute QS Investors, LLC’s or its affiliates’ judgment at the time of issue and are subject to change. The value of shares/units and their derived income may fall as well as rise. Past performance or any predic-tion or forecast is not indicative of future results. This document is only for professional investors. No further distribupredic-tion is allowed without prior written consent of the Issuer.

Any forecasts provided herein are based upon our opinion of the market as at this date and are subject to change, dependent on future changes in the market. Any prediction, projection or forecast on the economy, stock market, bond market or the eco-nomic trends of the markets is not necessarily indicative of the future or likely performance. Investments are subject to risks, including possible loss of principal amount invested.

For Investors in Australia:

This information is only available to persons who are professional, sophisticated, or wholesale investors under the Corporations Act. An investment with QS Investors, LLC is not a deposit with or any other type of liability of QS Investors, LLC or its affiliates. The capital value and performance of an investment with QS Investors, LLC is not guaranteed by QS Investors, LLC or its affiliates. Investments are subject to investment risk, including possible delays in repayment and loss of income and principal invested. QS Investors, LLC does not hold an Australian financial services license. QS Investors, LLC is exempt from the requirement to hold an Australian Financial Services License for the financial services it provides to you. QS Investors , LLC is regulated by the Securi-ties and Exchange Commission under the laws of the United States of America and those laws differ from Australian laws.

For investors in New Zealand:

No prospectus (as defined in the Securities Act 1978 of New Zealand) or other disclosure document in relation to the Fund or the Interests has been or will be lodged with the Registrar of Companies of New Zealand or the Securities Commission of New Zealand. The Interests have not been offered or sold (and will not be offered or sold), directly or indirectly, and no offering materials or advertisement in relation to any offer of the Interests has been distributed (nor will be distributed), directly or indirectly, in New Zealand other than:

(i) to persons whose principal business is the investment of money or who, in the course of and for the purposes of their busi-ness, habitually invest money;

(ii) to persons who in all the circumstances can properly be regarded as having been selected otherwise than as members of the public; or

(iii) to persons who are each required to pay a minimum subscription price of at least N.Z.$500,000 for Interests before the allotment of those Interests (disregarding any amounts payable, or paid out of money lent by the Fund, the General Partner or the Manager or any associated person of the Fund, the General Partner or the Manager); or

(iv) in other circumstances where there is no contravention of the Securities Act 1978 of New Zealand (or any statutory modifi-cation or re-enactment of, or statutory substitution for, the Securities Act 1978 of New Zealand).

For investors in the United Kingdom:

This document is a “non-retail communication” within the meaning of the FSA’s Rules and is directed only at persons satisfying the FSA’s client categorization criteria for an eligible counterparty or a professional client. This document is not intended for and should not be relied upon by a retail client.

When making an investment decision, potential investors should rely solely on the final documentation relating to the invest-ment or service and not the information contained herein. The investinvest-ments or services invest-mentioned herein may not be ap-propriate for all investors and before entering into any transaction you should take steps to ensure that you fully understand the transaction and have made an independent assessment of the appropriateness of the transaction in the light of your own objectives and circumstances, including the possible risks and benefits of entering into such transaction. You should also consider seeking advice from your own advisers in making this assessment. If you decide to enter into a transaction with us you do so in reliance on your own judgment.

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Diversification Based Investing (DBI) World Composite: Composite Description

Schedule of Investment Performance for the Period: December 31, 2012

Benchmark: MSCI The World Total Return Net Index

Notes:

a) Inception and/or termination period of performance may not comprise a full year; see reporting period dates above. b) Period August 1, 2001 to May 31, 2002 the MSCI Provisional World Net Dividends was used MSCI World Total Return Net Index was used after May 31, 2002. Due to differences in sources for benchmark performance, there may be slight variances between benchmark returns noted above and those from other published sources.

c) Asset-weighted standard deviation; calculated for gross returns for composites with five or more portfolios active over the full year.

d) 3-year annualized ex-post standard deviation. See Accompanying Notes below

1. Basis of Presentation

QS Investors, LLC (“QS Investors”) is a registered investment adviser with the SEC, providing investment and advisory services to a diverse array of institutional clients. QS Investors, based in New York City, is a 100% employee owned firm launched in August, 2010. The firm was created on August 1, 2010 via a management buy-out of the Quantitative Strategies Group within Deutsche Asset Management and therefore Firm assets prior to 2010 are not applicable.

QS Investors claims compliance with the Global Investment Performance Standards (GIPS®) and has prepared and presented this report in compliance with the GIPS standards. QS Investors has not been independently verified. This presentation of in-vestment performance sets forth the time-weighted gross and net rates of return for the Diversification Based Investing (DBI) World Composite (the “Composite”) for the period shown. Past performance is no guarantee of future results and may differ in future time periods. Additional information regarding the Firm’s policies and procedures for valuing portfolios, preparing compliant presentations, and calculating and reporting performance results is available upon request.

2. Composite Description and Valuation Procedures

The Composite includes all fee-paying portfolios invested in developed global equity securities which use region and sector as the building blocks to portfolio construction. The Composite strategy is designed to create an optimal portfolio that maximizes long-term wealth and produces better risk-adjusted returns than the index.

Eligible new portfolios are added to the Composite at the start of the first performance measurement period following the date that the portfolio is fully invested as defined by the Composite strategy. Securities listed on any national exchange are valued at their last trade price. Securities that are not listed are valued at the most recent publicly quoted bid price. Securities transactions are recorded on a trade date basis. If applicable, dividend income is recorded as of the ex-dividend date. Returns reflect investment of dividends and other earnings. Policy for valuing portfolios, calculating performance, and preparing com-pliant presentations are available upon request. The Composite was created August 1, 2010.

Derivatives are used to equitize cash where permitted. Period Ending (a) Composite Gross of Fees Returns (%) Composite Net of Fees Returns

(%) Benchmark (b) Number of Accounts

Composite Assets

(US$m) Firm Assets (US$m) Dispersion (c)Composite

2012 12.98 12.71 15.83 4 895 10,516 N/A 2011 -1.42 -1.65 -5.54 4 777 14,797 N/A 2010 8.94 8.72 11.76 4 758 17,282 N/A 2009 30.53 30.31 29.99 5 727 — N/A 2008 -37.82 -37.90 -40.71 2 418 — N/A 2007 13.30 13.16 9.04 2 664 — N/A 2006 20.17 20.02 20.07 3 625 — N/A 2005 10.25 10.11 9.49 3 499 — N/A 2004 16.36 16.21 14.72 2 334 — N/A 2003 33.77 33.59 33.11 1 204 — N/A 2002 -15.86 -15.97 -20.09 1 157 — N/A Standard Deviation (d) 3-Year 2012 15.68 15.68 16.74 3-Year 2011 19.04 19.04 20.15