Schwab Center For Financial Research Journal of Investment Research Strategic Beta Strategies: Do They Work Outside Our Borders? Anthony B. Davidow, CIMA Vice President, Alternative Beta and Asset Allocation Strategist, Schwab Center for Financial Research In this paper: We discuss the use of select strategic beta strategies in international and emerging markets. We address the following: How various strategies would have performed in international and emerging markets during the past 15 years Potential differences in sector weightings, market capitalization, and country allocations across the various strategies Issues that advisors should consider when evaluating the use of strategic beta strategies outside the U.S.
Strategic beta strategies, also known as smart beta or alternative beta, have grown in popularity over the last several years. Advisors increasingly have used these strategies as replacements for active management. 1 Much of the research on these strategies has focused on large-cap domestic allocations, and much of the appeal has been their outperformance relative to their market-cap index equivalents. 2 The question that I often hear is do these strategies work outside our borders? Do strategic beta strategies outperform their marketcap equivalents in international and emerging markets? In this paper, we ll share research on how a few of these strategies would have performed over the past 15 years. Specifically, we ll review the following: Do strategic beta strategies deliver a similar experience in international and emerging markets? Are there some factors that are more persistent than others? How do sector allocations, market capitalization, and country exposures vary by strategy? How have the strategies performed over time relative to market-cap benchmarks? Over the last couple of years, there has been a proliferation of strategic beta strategies coming to market. Based on data from Morningstar Research, there are currently 845 strategic beta exchange-traded products, with more than $875 billion in assets under management (AUM). 3 AUM has grown at a rate of more than 42% over the last two years, nearly twice the rate of the overall market. Part of the appeal has been the potential for delivering excess return relative to the traditional market-cap benchmarks (S&P 500, Russell 2000, FTSE 100, MSCI EAFE, etc.). Many of these strategies have delivered excess return by exploiting known factors in academic literature (e.g., Value, Size, Quality, Low Volatility, and Momentum, among others). Other strategies rely upon back-tested data that show strong hypothetical results. To test the results, we focused on strategies that are based on academic rigor and examined 15 years of data. We used historical index data to provide an apples-toapples comparison. Factor Investing With the proliferation of strategic beta strategies, investment research company Morningstar in 2014 introduced a new taxonomy to help advisors in distinguishing among the various types of strategies. It groups strategies by returnoriented, risk-oriented, and other. Returnoriented strategies, such as Value, Momentum, and Quality, are designed to deliver excess returns relative to market-cap indexes. Risk-oriented strategies, such as Low Volatility and Minimum Variance, are designed to have lower risk than the overall market. Other is a catch-all for strategies that are neither return- nor risk-oriented. The industry often uses strategic beta and factor investing interchangeably, but not all strategic beta strategies are based on factor research. The term factor describes characteristics of a group of securities that can explain return and risk. In recent years, there has been a plethora of new strategies coming to market claiming to have identified new factors. MSCI has conducted extensive research on factor investing and offered the following perspective: 4 While many factors have been shown to have statistical significance in explaining variations in risk and returns, not all of these factors offer risk premia relative to CAPM pricing. Risk premia factors are those which represent exposure to systematic sources of risk that have historically earned a long-term premium. We have so far identified six risk premia factors: Value, Low Size, Low Volatility, High Dividend Yield, Quality and Momentum. These factors have been empirically tested in years of academic research and there are solid explanations on why they have historically provided risk premia. Factor investing dates back to the 1960s, following the introduction of the Capital Asset Pricing Model (CAPM), which describes the relationship between systematic risk (i.e., volatility) and expected returns. Eugene Fama and Kenneth French built on CAPM, introducing in the 1 Schwab Investor Survey Results, 2017 2 Anthony Davidow, Strategic Beta Strategies: An Evaluation of Different Approaches, 2018 3 Morningstar Direct, December 31, 2017 4 Mehdi Alighanbari, Raman Aylur Subramanian & Padmakar Kulkarni, Factor Indexes in Perspective: Insights from 40 Years of Data, September 2014 2
Schwab Center For Financial Research Strategic Beta Strategies: Do They Work Outside Our Borders? 1990s their three-factor model, which added size and value factors to the market risk factors in the CAPM. Meanwhile, Barra (now part of MSCI) has been researching factors since the 1970s. The point is that there has been a lot of research on factor investing, going back decades. The reason we re so fascinated by it today is that exchangetraded funds (ETFs) can capture these factors in rules-based structures, so they re now easily accessible for advisors and investors. Investing Outside the U.S. There is a world of potential opportunities outside our borders. However, it is challenging to evaluate individual securities, geopolitical risks, and economic development per country. Picking individual companies and countries presents a number of issues. Most investors would be better served by owning a diversified basket of securities. This can be accomplished by owning separately managed accounts (SMAs), mutual funds or exchange-traded funds, each of which has unique pros and cons. Advisors can attempt to pick which countries and companies will flourish in one environment and which to avoid in another, or diversify their exposure across the world. For example, as you can see in Exhibit 1, Canada and Australia were the two top-performing countries in 2016 on a year-over-year basis, and the bottom two in 2017. Canada and Australia enjoy an abundance of natural resources. When the world is consuming these resources to build roads, bridges and skyscrapers, they benefit from increased demand. When demand tapers due to a global slowdown, their economies suffer due to their dependence on natural resources. Other global economies are affected by their own industries, resources, and trade. While we often think of international and emerging markets as homogenous groups, each country is affected by its own unique set of economic and geopolitical challenges. Exhibit 1 shows the change in market leadership from one period to the next. Note that the emerging markets represent many countries, including China, Russia, Brazil, and India, among others. By definition, these countries are less developed and consequentially carry additional risk. We believe that investors are probably better served in owning a diversified basket of international and emerging-market securities, Exhibit 1. Evaluating Select County and Regional Returns by Year Schwab Asset Class Quilt TM Source: Morningstar Direct and Schwab Center for Financial Research. This chart represents a hypothetical investment and is for illustrative purposes only. Data is from January 1, 2003 December 31, 2017. Geographical performance is represented by annual total returns of the following: MSCI AC World, MSCI USA, MSCI Japan, MSCI United Kingdom, MSCI Switzerland, MSCI Germany, MSCI France, MSCI Canada, MSCI Australia, MSCI Nordic Countries, MSCI Spain, MSCI EM (Emerging Markets). Indexes are unmanaged, do not incur fees or expenses, and cannot be invested in directly. Past performance is no guarantee of future results. 3
Exhibit 2. Strategic Beta Strategies in Emerging Markets: Sector Weightings Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Emerging Momentum Index; Quality FTSE Emerging Quality Index; Fundamental Russell RAFI Emerging Markets Large Company Index; Low Volatility FTSE Emerging Low Volatility Index; Market-Cap- FTSE Emerging Index. Sector allocations are subject to change without notice. Data for the Real Estate GICS sector is unavailable. and if there is strong conviction tactically overweighting the country or region. Advisors can hire a SMA manager who has demonstrated skill and proficiency in identifying strong companies and avoiding weak ones, or they can buy a number of broad-based index strategies. They can choose to own the market in the traditional market-capitalization fashion, or they can select from a variety of strategic beta strategies designed to provide a different experience. Emerging Markets Over the last several years, strategic beta strategies have been sought as a way of improving the market experience, either by delivering excess returns or lower risk than Exhibit 3. Strategic Beta Strategies: Size Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Emerging Momentum Index; Quality FTSE Emerging Quality Index; Fundamental Russell RAFI Emerging Markets Large Company Index; Low Volatility FTSE Emerging Low Volatility Index; Market-Cap- FTSE Emerging Index. Data is subject to change without notice. Market capitalization may vary without notice. Market-capitalization breakpoints, determined by Morningstar Direct: Mega cap, over $78.3 billion; Large cap, between $17.3 billion and $78.3 billion; Mid cap, between $3.6 billion and $17.3 billion; Small cap, between $1.1 billion and $3.6 billion, Micro cap between $0 and $1.1 billion. the overall market. Many of these strategies exploit known factors that have been shown to improve the market experience over time. Institutions have been using factor investing for decades. Now many of these strategies are available in ETFs, and have become core building blocks for advisors. Advisors can use these innovative strategies as either long-term strategic allocations or as tactical tools to take advantage of a particular market environment. While many of these strategies claim to outperform their market-cap equivalents, they do it in a very different fashion. We believe it s important to evaluate the underlying index construction methodologies. Fundamental is a value-tilting strategy that screens and weights securities based on fundamental measures such as sales, cash flow, and dividends plus buybacks. Conversely, Momentum is a growth-oriented strategy that weights securities based on how well they ve performed recently. To dig a little deeper, let us evaluate how a few strategic beta strategies have performed in emerging markets. First, let s compare the sector allocations of these strategies relative to the market-cap index. The market-cap index provides the largest weighting to the company with the greatest total market value of outstanding shares, while the strategic beta strategies weight securities based on their respective rules-based methodologies. As Exhibit 2 shows, there are big differences in the sector weightings across strategies as applied to emerging markets. The Low Volatility strategy overweights Financials stocks (30.6%), while the Quality strategy underweights Financials (5.9%). Also, based on energy company valuations, the 4
Exhibit 4. Strategic Beta Strategies in Emerging Markets: Country Weightings Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Emerging Momentum Index; Quality FTSE Emerging Quality Index; Fundamental Russell RAFI Emerging Markets Large Company Index; Low Volatility FTSE Emerging Low Volatility Index; Market-Cap- FTSE Emerging Index. Fundamental strategy dramatically overweights the Energy sector relative to the market-cap index (22.1% vs. 8.4%, respectively). If we look at market capitalization (Exhibit 3) we see some subtle differences across these strategies. Fundamental and Low Volatility have the highest allocation to mega-cap stocks (62.5% and 62.2%, respectively), and the lowest allocation to mid-caps (7.6% and 7.0%, respectively). This is a byproduct of the underlying company characteristics, not an intentional forward-looking bet. If we evaluate the underlying country allocations, we see some similarities among the top countries but the weightings are quite different (Exhibit 4). China is the largest country allocation across the selected strategies; however, the allocations range from 19.6% for Fundamental to 38.9% for Momentum. The difference in allocations can lead to dramatically different results. In fact, based on the different index construction methodologies, the different sector weightings, market capitalizations and country allocations, these strategies deliver widely varying returns on a year-over year basis (Exhibit 5). As the data in Exhibit 5 shows, there were changes in market leadership across these strategies. While each of these strategies outperformed the market-cap index in aggregate, they each experienced periods of underperformance, as well. Similar to performance in U.S. markets, Momentum strategies have done very well recently, but over the last 15 years, Fundamental has delivered the best results in emerging markets. Exhibit 5. Strategic Beta Strategies in Emerging Markets: Yearly Returns Schwab Asset Class Quilt TM Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Emerging Momentum Index; Quality FTSE Emerging Quality Index; Fundamental Russell RAFI Emerging Markets Large Company Index; Low Volatility FTSE Emerging Low Volatility Index; Market-Cap- FTSE Emerging Index. Performance information for the Low Volatility, Momentum, Quality and Fundamental indexes includes back-tested performance data. Back-tested performance data are hypothetical and done with the benefit of hindsight. Past performance of a back-tested model is not a guarantee that the model will produce similar results in the future. Past performance is no guarantee of future results. 5
Exhibit 6. Strategic Beta Strategies in International Markets: Sector Weightings Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Developed ex US Momentum Index; Quality FTSE Developed ex US Quality Index; Fundamental Russell RAFI Developed ex US Large Company Index; Low Volatility FTSE Developed ex US Low Volatility Index; Market-Cap- FTSE Developed ex US Index. Sector allocations are subject to change without notice. Data for the Real Estate GICS sector is unavailable. International Markets As shown above, the difference in weighting methodology led to dramatically different results across the various types of strategic beta strategies. Based on the index construction methodologies, we saw big differences between sector allocations, market capitalization and performance results. Let s next examine international strategic beta strategies. Similar to the analysis with emerging market strategies above, we wanted to evaluate some of the bets and biases exhibited by a select group of strategic beta strategies. If we compare the sector allocations (Exhibit 6), we can see some Exhibit 7. Strategic Beta Strategies in International Markets: Size Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Developed ex US Momentum Index; Quality FTSE Developed ex US Quality Index; Fundamental Russell RAFI Developed ex US Large Company Index; Low Volatility FTSE Developed ex US Low Volatility Index; Market-Cap- FTSE Developed ex US Index. Data is subject to change without notice. Market capitalization may vary without notice. Market-capitalization breakpoints, determined by Morningstar Direct: Mega cap, over $78.3 billion; Large cap, between $17.3 billion and $78.3 billion; Mid cap, between $3.6 billion and $17.3 billion; Small cap, between $1.1 billion and $3.6 billion, Micro cap between $0 and $1.1 billion. big differences from the market-cap benchmark. In particular, the Quality strategy has a 4.7% weighting to Financials, versus the marketcap benchmark with 22.4%. The Fundamental strategy has nearly a double weighting to Energy compared with the market-cap index (12.3% vs. 6.3%, respectively). The difference in the weightings is a byproduct of the screening and weighting methodology. From a market-capitalization perspective (Exhibit 7), Low Volatility has the highest allocation to mega-cap stocks and the lowest exposure to mid-cap. This makes intuitive sense, as a low-volatility strategy naturally would gravitate toward larger, more mature companies. Quality has the lowest exposure to mega-caps and the highest exposure to mid-caps. If we compare the respective country allocations (Exhibit 8), we see many of the same top country allocations among the strategies. However, we do see substantial differences in the percentage allocations. Low Volatility has a 12.9% allocation to Japan, while the other strategies have allocations in excess of 22%. Fundamental has the highest allocation to the UK (19.2%) and Quality has the lowest (9.0%). The top five countries represent over 68% of the Fundamental strategy and less than 60% of Low Volatility. With the large differences noted above, it shouldn t be surprising that these strategies deliver dramatically different results over time. To illustrate this point, we evaluate the yearly results from 2003 through 2017 (Exhibit 9). Each of these was both the best- and worst-performing strategy in a given year. Fundamental performed the best in 2003, 2013, and 2016 and the worst 6
Exhibit 8. Strategic Beta Strategies in International Markets: Country Weightings Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Developed ex US Momentum Index; Quality FTSE Developed ex US Quality Index; Fundamental Russell RAFI Developed ex US Large Company Index; Low Volatility FTSE Developed ex US Low Volatility Index; Market-Cap- FTSE Developed ex US Index Exhibit 9. Strategic Beta Strategies in International Markets: Yearly Returns Schwab Asset Class Quilt TM Source: Morningstar Direct and Schwab Center for Financial Research. Data is as of December 31, 2017. Strategies are representative of the following indexes: Momentum FTSE Developed ex US Momentum Index; Quality FTSE Developed ex US Quality Index; Fundamental Russell RAFI Developed ex US Large Company Index; Low Volatility FTSE Developed ex US Low Volatility Index; Market-Cap- FTSE Developed ex US Index. Performance information for the Low Volatility, Momentum, Quality and Fundamental indexes includes back-tested performance data. Back-tested performance are hypothetical and done with the benefit of hindsight. Past performance of a back-tested model is not a guarantee that the model will produce similar results in the future. Past performance is no guarantee of future results. in 2011 and 2015. Quality did best in 2007, 2008, and 2017 but was the worst in 2003, 2004, 2005, 2012, and 2013. Conclusion As we examine select strategic beta strategies across the international and emerging markets, we see a similar experience to that observed in domestic markets. There s a large degree of variability across the different types of strategies, leading to dramatically different results. In both the international and emerging markets, the selected strategies outperformed the respective market-cap benchmarks over the long run. The yearly results show a natural rotation of market leadership from one strategy to the next. Our research focused on strategies that rely upon academic rigor, and historical index results going back at least 15 years. We re not suggesting that all strategic beta strategies will deliver the same results. We would encourage advisors to follow the methodology used in this paper. Begin by understanding the underlying index construction methodology for the strategy under consideration. We then suggest evaluating some of the bets and biases by analyzing the sector allocation, market capitalization and country allocations. Lastly, we suggest evaluating performance relative to the market-cap equivalent index. This methodology can be used in evaluating all strategic beta strategies. 7
Anthony B. Davidow, CIMA Vice President, Alternative Beta and Asset Allocation Strategist, Schwab Center for Financial Research Anthony Davidow is responsible for providing Schwab s point of view on asset allocation and portfolio construction. He is also responsible for providing research and analysis on alternative beta strategies and how investors can incorporate them in their portfolios. Davidow is also a member of the firm s Asset Allocation Working Group and Alternative Investment Product Council. Before joining Schwab, Davidow was a managing director, portfolio strategist, and head of the ETF Knowledge Center for Guggenheim Investments. Before joining Guggenheim, Davidow was executive vice president and head of distribution for IndexIQ. Previously, he spent 15 years at Morgan Stanley, where he served as managing director and head of sales and training for the Consulting Services Group. While at Morgan Stanley, he was responsible for building and managing the Institutional Consulting Group and Graystone Wealth Management. Davidow has authored several white papers, and spoken at numerous industry conferences on a range of topics, including: Asset Allocation and Manager Selection, Alpha- Beta Separation, Democratizing Alternative Investments, An Evolutionary Approach to Portfolio Construction, and The Case for Global Asset Allocation, among others. In 2017, he was awarded the Stephen L. Kessler Writing Award by the Investment & Wealth InstituteTM (formerly IMCA), and in 2015, he received the Stephen L. Kessler Writing Award (Honorable Distinction). Davidow holds a B.B.A. degree in finance and investments from Bernard M. Baruch College, and has earned the Certified Investment Management Analyst (CIMA ) designation from the Investment Management Consultants Association (IMCA) and the Wharton School of the University of Pennsylvania. He served on the Board of Directors for IMCA from 2009 to 2015, and currently serves as the Chair, Investment & Wealth Monitor, Editorial Advisory Board. He holds FINRA Series 7, 24, and 63 registrations. 8
Glossary of Terms Alpha: A performance measure on a risk- adjusted basis. Alpha takes the volatility (risk) of a mutual fund, or other type of investment, and compares its risk-adjusted performance with a benchmark index. The excess return of the fund relative to the return of the benchmark index is a fund s alpha. Beta: A measure of the volatility, or systematic risk, of a security or a portfolio in comparison with the market as a whole. Beta is used in the capital asset pricing model (CAPM), which calculates the expected return of an asset based on its beta and expected market returns. Correlation: Correlation measures the relationship and movement of two or more securities, ranging between -1 and +1. Perfect positive correlation (a correlation of +1) implies that as one security moves, either up or down, the other security will move in lockstep in the same direction. Alternatively, perfect negative correlation means that if one security moves in either direction, the security that is perfectly negatively correlated will move in the opposite direction. If the correlation is 0, the movements of the securities are said to have no correlation; they are completely random. Equal Weight: Equal Weight is a type of weighting that gives the same weight, or importance, to each stock in a portfolio or index fund, and the smallest companies are given equal weight to the largest companies in an equal-weight index fund or portfolio. Fundamental index: A type of equity index in which components are chosen based on fundamental criteria as opposed to market capitalization. Fundamentally weighted indexes may be based on fundamental metrics such as sales, cash flow, and dividends. Proponents of these indexes claim that they are a more accurate aggregate measure of the market because market-capitalization figures tend to overweight companies that are richly valued while underweighting companies with low valuations. Fundamentally weighted indexes are sometimes referred to as strategic beta, alternative beta, or smart beta. Low Volatility: Low Volatility is a type of weighting methodology that weights stocks based on the level of volatility over a specific period, such as one year. Market-capitalization Weighting: Most of the broadly used market indexes today are cap-weighted indexes, such as the S&P 500, Russell, and MSCI indexes. In a cap-weighted index, large price moves in the largest components can have a dramatic effect on the value of the index. Some investors believe this overweighting toward the larger companies gives a distorted view of the market. Momentum: This strategy looks to capture gains by investing in hot stocks in the belief that they will continue to rise. There are mutual funds and ETFs that buy or overweight securities that have exhibited momentum over some predetermined time period (three, six, or 12 months). The basic idea is that once a trend is established, it is more likely to continue in that direction than to move against the trend. Quality: Quality is a type of weighting that weights stocks based on strong balance sheets (i.e., low debt), consistent earnings, and high levels of profit measures, such as return on equity. Sharpe ratio: A ratio developed by Nobel laureate William F. Sharpe to measure risk-adjusted performance. The Sharpe ratio measures the excess return (or risk premium) per unit of deviation (risk) in an investment. The Sharpe ratio characterizes how well the return of an asset compensates the investor for the risk taken. When comparing two assets versus a common benchmark, the one with a higher Sharpe ratio provides better return for the same risk (or, equivalently, the same return for lower risk). 9
Standard deviation: Standard deviation is a statistical measurement that sheds light on historical volatility. For example, a volatile portfolio will have a higher standard deviation than a less volatile portfolio. A large dispersion tells us how much the return on the fund is deviating from the expected normal returns. Strategic beta: Also known as alternative beta and smart beta. Strategic beta strategies attempt to deliver a better risk and return trade-off than conventional market-cap-weighted indexes by using alternative weighting schemes based on measures such as volatility. Strategic beta strategies include a range of alternative weighting methods: Fundamentally Weighted, Equal Weighting, Minimum Variance, and Low Volatility, among others. Index Definitions The FTSE 100, or Financial Times Stock Exchange 100 Index, is a share index of the 100 companies listed on the London Stock Exchange with the highest market capitalization. The FTSE Emerging Index is part of the FTSE Global Equity Index Series (GEIS). The index is a marketcapitalization weighted index representing the performance of large- and mid-cap companies in emerging markets. The FTSE Emerging Low Volatility Index is part of the FTSE Global Factor Index Series. The Low Volatility factor is designed to capture companies that exhibit low volatility, as they tend to perform better than companies with higher volatility. This index applies a consistent and transparent methodology to achieve controlled exposure to low volatility, while considering levels of diversification and capacity. The FTSE Emerging Momentum Index is part of the FTSE Global Factor Index Series. The Momentum factor is designed to capture companies with strong recent performance which tends to persist, either continuing to rise or fall. This index applies a consistent and transparent methodology to achieve controlled exposure to momentum, while considering levels of diversification and capacity. The FTSE Emerging Quality Index is part of the FTSE Global Factor Index Series. The Quality factor is designed to capture higher-quality companies, which tend to demonstrate higher performance than lower-quality companies. This index applies a consistent and transparent methodology to achieve controlled exposure to quality, while considering levels of diversification and capacity. The FTSE Developed ex US Index is part of the FTSE Global Equity Index Series (GEIS). The index is a market-capitalization weighted index representing the performance of large- and mid-cap companies in developed markets, excluding the United States. The FTSE Developed ex US Quality Index is part of the FTSE Global Factor Index Series. The Quality factor is designed to capture higher-quality companies, which tend to demonstrate higher performance than lower-quality companies. This index applies a consistent and transparent methodology to achieve controlled exposure to quality, while considering levels of diversification and capacity. The FTSE Developed ex US Momentum Index is part of the FTSE Global Factor Index Series. The Momentum factor is designed to capture companies with strong recent performance which tends to persist, either continuing to rise or fall. This index applies a consistent and transparent methodology to achieve controlled exposure to momentum, while considering levels of diversification and capacity. The FTSE Developed ex US Low Volatility Index is part of the FTSE Global Factor Index Series. The Low Volatility factor is designed to capture companies that exhibit low volatility, as they tend to perform better than companies with higher volatility. This index applies a consistent and transparent methodology to achieve controlled exposure to low volatility, while considering levels of diversification and capacity. 10
The MSCI AC World Index is a free float-adjusted market-capitalization-weighted index that is designed to measure the equity market performance of developed and emerging markets. The MSCI ACWI consists of 46 country indexes comprising 23 developed and 23 emerging market country indexes. The developed market country indexes included are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, the United Kingdom and the United States. The emerging market country indexes included are: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Peru, Philippines, Poland, Qatar, Russia, South Africa, Taiwan, Thailand, Turkey and United Arab Emirates. The MSCI Australia Index is designed to measure the performance of the large- and mid-cap segments of the Australia market. With 72 constituents, the index covers approximately 85% of the free float-adjusted market capitalization in Australia. The MSCI Canada Index is designed to measure the performance of the large- and mid-cap segments of the Canada market. With 94 constituents, the index covers approximately 85% of the free floatadjusted market capitalization in Canada. The MSCI EAFE (Europe, Australasia, Far East) Index is a free float-adjusted market capitalization index that is designed to measure developed market equity performance, excluding the U.S. and Canada. The MSCI EAFE Index consists of 21 developed market country indexes: Australia, Austria, Belgium, Denmark, Finland, France, Germany, Hong Kong, Ireland, Israel, Italy, Japan, the Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, and the United Kingdom. The MSCI EM (Emerging Markets) Index is a free float-adjusted market capitalization index that is designed to measure equity market performance of emerging markets. The MSCI Emerging Markets Index consists of the following 23 emerging market country indexes: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Peru, Philippines, Poland, Qatar, Russia, South Africa, Taiwan, Thailand, Turkey and United Arab Emirates. The MSCI France Index is designed to measure the performance of the large- and mid-cap segments of the French market. With 74 constituents, the index covers about 85% of the equity universe in France. The MSCI Germany Index is designed to measure the performance of the large- and mid-cap segments of the German market. With 55 constituents, the index covers about 85% of the equity universe in Germany. The MSCI Japan Index is designed to measure the performance of the large- and mid-cap segments of the Japanese market. With 318 constituents, the index covers approximately 85% of the free floatadjusted market capitalization in Japan. The MSCI Nordic Countries Index captures large- and mid-cap representation across Denmark, Finland, Norway and Sweden. With 66 constituents, the index covers approximately 85% of the free float-adjusted market capitalization in each country. The MSCI Spain Index is designed to measure the performance of the large- and mid-cap segments of the Spanish market. With 25 constituents, the index covers about 85% of the equity universe in Spain. The MSCI Switzerland Index is designed to measure the performance of the large- and mid-cap segments of the Swiss market. With 40 constituents, the index covers approximately 85% of the free float-adjusted market capitalization in Switzerland. 11
The MSCI United Kingdom Index is designed to measure the performance of the large- and mid-cap segments of the UK market. With 113 constituents, the index covers approximately 85% of the free float-adjusted market capitalization in the UK. The MSCI USA Index is designed to measure the performance of the large- and mid-cap segments of the U.S. market. With 633 constituents, the index covers approximately 85% of the free float-adjusted market capitalization in the U.S. The Russell 2000 Index: Russell indexes are market-capitalization weighted and are subsets of the Russell 3000 Index, which contains the largest 3,000 companies incorporated in the United States and represents approximately 98% of the investable U.S. equity market. The Russell 2000 Index is composed of the 2000 smallest companies in the Russell 3000 Index. The Russell RAFI Emerging Markets Large Company Index: The Russell RAFI Index Series is designed to capture the beta of a fundamental index strategy. Using publicly available data, the Russell RAFI Index Series methodology selects and weights securities using the average of three fundamental measures of company size including adjusted sales, retained operating cash flow and dividends plus buybacks. The S&P 500 Index is a market-capitalization weighted index that consists of 500 widely traded stocks chosen for market size, liquidity, and industry group representation Important Disclosures This material is for institutional investor use only. This material may not be forwarded or made available, in part or in whole, to any party that is not an institutional investor. The information here is for general informational purposes only and should not be considered an individualized recommendation or personalized investment advice. The type of investment strategies mentioned may not be suitable for everyone. Each investor needs to review a security transaction for his or her own particular situation. All expressions of opinion are subject to change without notice in reaction to shifting market conditions. Data here is obtained from what are considered reliable sources; however, its accuracy, completeness, or reliability cannot be guaranteed. Supporting documentation for any claims or statistical information is available upon request. Diversification strategies do not ensure a profit and do not protect against losses in declining markets. Investment returns will fluctuate and are subject to market volatility, so that an investor s shares, when redeemed or sold, may be worth more or less than their original cost The Schwab Fundamental Index ETFs are not in any way sponsored, endorsed, sold or promoted by Frank Russell Company (Russell), by the London Stock Exchange Group companies (LSEG), or by Research Affiliates LLC (RA) (collectively the Licensor Parties), and none of the Licensor Parties make any warranty or representation whatsoever, expressly or impliedly, either as to the results to be obtained from the use of the Russell RAFI Index Series (the Indexes) or otherwise. The Indexes are compiled and calculated by Russell in conjunction with RA. None of the Licensor Parties shall be liable (whether in negligence or otherwise) to any person for any error in the Indexes and none of the Licensor Parties shall be under any obligation to advise any person of any error therein. Russell is a trademark of Russell. The trade names Research Affiliates, Fundamental Index and RAFI are registered trademarks of RA. Charles Schwab Investment Management, Inc. has obtained full license from Russell to use the Indexes. For full disclaimer please see the funds statements of additional information. Charles Schwab & Co., Inc. is not affiliated with Russell Investments or Research Affiliates. The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc. 2018 Charles Schwab & Co., Inc. All rights reserved. Member SIPC SCFR (0618) 0618-85GG 12