Diversification Based Investing (DBI)

Diversification Based Investing (DBI) by 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 3. Low correlation of excess returns to indices and other investment managers

Executive Summary Over 10 years ago, developed an investment approach aimed at taking advantage of macro inefficiencies 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 Diversification 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 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 ember 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 ember 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 ember 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:, MSCI *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 Form ADV 2A. 1 Jung and Shiller (2005) 2 Irrational Exuberance, 2nd Ed. (2001), p. 243 Diversification Based Investing (DBI) 2

Introduction Many active equity managers focus on stock selection to beat their benchmarks. has developed a very different active management approach aimed at creating a high level of diversification across geography and sectors, rather than identifying individual 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 characteristics, 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 concentration 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, Currency 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 ember 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. FIGURE 1: Drivers of Global Equity Market Returns Importance of Country, Currency and Industry Rolling 12 Month Average (ember 1999 March 2012) 60% 50% Weight in Index 40% 30% 20% 10% 0% 99 00 01 02 03 04 05 06 07 08 09 10 11 Mar 12 Source: Factor returns are regressed cross-sectionally on country, currency and industry. 3 Hopkins and Miller (2001) Country, sector, and company factors in global equity portfolios, The Research Foundation of AIMR and Blackwell Series in Finance Diversification Based Investing (DBI) 3

Belief 2 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 FIGURE 2: Market Sentiment Led to Concentration in Japan Equities Index Weight of Japan in MSCI World Index ember 31, 1985 November 30, 2007 40% July 1989 30% Weight in Index 20% 10% 0% Jan 1985 Jan 1987 Jan 1989 Jan 1991 Jan 1993 Jan 1995 Jan 1997 Jan 1999 Jan 2001 Jan 2003 Jan 2005 Jan 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 ember 31, 1991 November 30, 2001 30% Capitalization Weight February 2000 Weight in Index 20% 10% 0% 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Nov 2001 Source: MSCI World Index 4 MSCI Diversification Based Investing (DBI) 4

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 overvalued 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 performing 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 capitalizationweighted indices. FIGURE 4: Concentration Risk Can Detract from Diversified Benefits Index Weight of Financials and Health Care June 30, 1999 May 15, 2009 30% Financials Health Care 25% 20% 15% 10% 5% 6/30/1999 12/31/1999 6/30/2000 12/29/2000 6/29/2001 12/31/2001 6/28/2002 12/31/2002 6/30/2003 12/31/2003 6/30/2004 12/31/2004 6/30/2005 12/30/2005 6/30/2006 12/29/2006 6/29/2007 12/31/2007 6/30/2008 12/31/2008 Weight 5/15/2009 Source: MSCI World Index 5 Ibid 6 Financial Analysts Journal (Treynor, 2005), Journal of Investing (Hamza, et al, 2007) Diversification Based Investing (DBI) 5

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 misdirected. 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 hypothesized 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 Telecom) 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. FIGURE 5: Investors Become Overly Optimistic & Pessimistic Valuation January 1986 January 2011 Basic Materials Price/Book vs Average Price/Book Average 4 Hong Kong Price/Book vs Average Price/Book Average 4 3 3 2 2 1 1 0 1986 1991 1996 2001 2006 2011 0 1986 1991 1996 2001 2006 2011 Health Care Price/Book vs Average Price/Book Average 8 Sweden Price/Book vs Average Price/Book Average 8 6 6 4 4 2 2 0 1986 1991 1996 2001 2006 2011 0 1986 1991 1996 2001 2006 2011 Source: Datastream, analysis 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 Diversification Based Investing (DBI) 6

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 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 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 geographically 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. FIGURE 6: Step 1 Partition the Universe into Region/Sector Units Example of Two Risk Units within DBI World Portfolio Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Information Technology Materials Telecom Services Utilities Americas Unit 1 Asia EMU Unit 2 Non-EMU Source: For illustrative purposes only FIGURE 7: Step 2 Group Highly Correlated Region/Sector Units into Clusters Example of Two Clusters within DBI World Portfolio Cluster 1 Cluster 2 Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Information Technology Materials Telecom Services Utilities Americas Asia EMU Non-EMU Source: For illustrative purposes only Diversification Based Investing (DBI) 7

Step 3 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 weighting of 1.11% (i.e., 16.67% 15). By construction, risk units in more crowded clusters will be highly correlated 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 ember 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 100% DBI World Strategy MSCI World Index 75% 50% 25% 0% Americas & European Cyclicals Global Commodities Non-Cyclicals: Americas & North EMU Asian Cyclicals Americas & Asia High Dividend Non-Cyclicals: Europe As of June 2012 Source:, MSCI For illustrative purposes only Diversification Based Investing (DBI) 8

FIGURE 9 Example of All Clusters within DBI World Portfolio (as of June 2012) 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 Source: as of June 2012 For illustrative purposes only Diversification Based Investing (DBI) 9

Step 4 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 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 Rebalance Rebalance Rebalance Cluster June September ember March June FIGURE 11: DBI Dynamically Reacts to Correlation Changes Energy Sector Weight in DBI World and MSCI World 20% 18% 16% DBI World reasing correlations to Utilities lead to increasing overweight MSCI World 14% 12% 10% 8% 6% 12/29/2006 3/30/2007 6/29/2007 9/28/2007 12/31/2007 3/31/2008 6/30/2008 9/30/2008 12/31/2008 Weights Increasing correlations to Materials sector leads to underweight Data based on portfolio holdings as of ember 31, 2008 Source:, 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. Diversification Based Investing (DBI) 10

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 illustrates 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 companies 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 commodities 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. Telecommunications, 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 combined 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. Diversification Based Investing (DBI) 11

FIGURE 12 DBI Portfolio in June 2011 and June 2012 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 2.78% Asia Industrials 2.78% Asia Consumer Discretionary 2.78% Asia Financials 2.78% Asia Information Technology 2.78% European and Asian Materials European Non-Cyclicals: 16.67%% 2.78% Americas Consumer Staples excludes Retailing 2.78% EMU Consumer Staples 2.78% EMU Health Care 2.78% EMU Telecommunications 2.78% Non-EMU Consumer Staples 2.78% European Utilities Global Health Care and Non-Cyclicals: 16.67% 4.17% Americas Health Care 4.17% Americas Pharmaceuticals 4.17% Non-EMU Health Care 4.17% Asia Consumer Staples, Telcom Services, Health Care, Utilities 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 IT and Telecom: 16.67% 5.56% Americas Information Technology 5.56% Americas Information Technology Services 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 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: 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 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 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. Diversification Based Investing (DBI) 12

3 Performance analysis In this section, we detail DBI s backtested and live perfromance (through ember 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. 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). During the live period, from inception in August 2001 to ember 2012, DBI World returned 5.52%, FIGURE 13 DBI World Live Performance August 1, 2001 (inception) to ember 31, 2012 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 Form ADV 2A. FIGURE 14 Hypothetical DBI World Performance March 1985 to July 2001 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% Source:, MSCI 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 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. Diversification Based Investing (DBI) 13

Understanding performance patterns DBI World has shown consistent patterns of performance. These are explored below. Low correlation with many other active strategies Because DBI uses a differentiated portfolio construction process, the strategy has shown low correlation 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 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* Market Participation 99% 90% Correlation 0.5 0.0-0.5-1.0 A B C D E F Managers Time period: Ten years as of ember 2012 Source: Consultant Manager Universe, Zephyr StyleAdvisor G H I J Up Market Capture Down Market Capture As of ember 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 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. Diversification Based Investing (DBI) 14

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. FIGURE 17 DBI World Composite Five-Year Rolling Excess Return August 2001 to ember 2012 4 3 2 Percent 1 0-1 Jun 06 06 Jun 07 07 Jun 08 08 Jun 09 09 Jun 10 10 Jun 11 11 Jun 12 12 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. FIGURE 18 Hypothetical DBI Cumulative Returns versus Its Benchmark from March 1985 to July 2001 14 12 10 8 6 4 2 0 MSCI World Benchmark (Net Index USD) Hypothetical DBI 3/31/1985 3/31/1986 3/31/1987 3/31/1988 3/31/1989 3/31/1990 3/31/1991 3/31/1992 3/31/1993 3/31/1994 3/31/1995 3/31/1996 3/31/1997 3/31/1998 3/31/1999 3/31/2000 3/31/2001 Source:, MSCI 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. Diversification Based Investing (DBI) 15

Avoiding concentrations DBI s ability to avoid some of the concentrations found in market capitalization-weighted indices was highlighted 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- 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). FIGURE 19: Concentration Risk Can Build and Collapse Capitalization Weight of Technology, Media, and Telecommunication (TMT) Stocks ember 31, 1991 November 30, 2001 30% Capitalization Weight Hypothetical DBI Weight February 2000 Weights 20% 10% 0% 1991 1992 1993 1994 1995 Source:, MSCI 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. 1996 1997 1998 1999 2000 Nov 2001 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. FIGURE 20: Active Risk is Driven by Industry, Country and Currency omposition of Active Risk June 2012 120% 100% 80% 60% 40% 20% 0% 2006 2007 2008 2009 2010 2011 2012 MACRO RISK Industry Country Currency Risk Indices 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. Diversification Based Investing (DBI) 16

Region and sector exposures As of ember 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 industries, 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 ember 2012 FIGURE 22 Sector Weights for ember 2012 DBI World MSCI World Index DBI World MSCI World Index North America AsiaPac Health Care Telecommunication Services Consumer Staples Utilities Energy Financials EMU Non-EMU 0% 10% 20% 30% 40% 50% 60% Consumer Discretionary Information Technology Industrials Materials 0% 5% 10% 15% 20% 25% 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. Diversification Based Investing (DBI) 17

Style and size exposures Our analysis confirms that DBI has had no persistent size or style bias since inception. DBI s average Priceto-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 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Price/Book DBI World Price/Book MSCI World Index (Net) 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 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 Data based on portfolio holdings as of ember 31, 2012 Source:, MSCI 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. FIGURE 24 Market Capitalization Since Inception 90 80 70 60 50 40 30 20 10 0 Market Cap DBI World Market Cap MSCI World Index (Net) 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 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 Data based on portfolio holdings as of ember 31, 2012 Source:, MSCI 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. 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 portfolioweighted 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. Diversification Based Investing (DBI) 18

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%. FIGURE 25 DBI EAFE Performance February 2001 to ember 2012 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% Source:, MSCI *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 Form ADV 2A. Diversification Based Investing (DBI) 19

FIGURE 27 DBI ACWI Hypothetical Performance June 2000 to ember 2010 Performance DBI ACWI continues to expand the platform. In January of 2011, 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. Annualized Return FIGURE 26 DBI ACWI Performance Performance Since Inception DBI ACWI Composite (gross of fees) 4.28% MSCI ACWI Index Net USD 3.73% Value added 0.55% As of ember 31, 2012 Inception date: January 2011; time period used by, LLC to report performance of GIPS-compliant composites. Past performance is not necessarily 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. Please see the appendix for additional composite information. 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. 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. FIGURE 28 DBI Emerging Markets Hypothetical Performance June 2000 to ember 2012 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 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. Diversification Based Investing (DBI) 20

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 ember 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 returns 12 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 declined 11 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 strategies 12 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. Diversification Based Investing (DBI) 21