Moving Beyond Market Cap-Weighted Indices Trustee Forum London 12 May 2011 Michael Arone, CFA, Global Head of Product Engineering 1
The Expanding Passive Universe Why is Cap Weighting the Norm? Theory suggests cap-weights are optimal Investors, in aggregate, hold the market portfolio The market portfolio is straightforward to manage (and very cost effective) Any departure from cap weights viewed as active management Advanced Beta a positive development for investors A broader toolkit Designed to capture unique returns, diversify portfolios or express views Allows investors to express their investment views passively Retains benefits of indexing Potential challenges Turnover and transaction costs Credibility of investment thesis (reliance on empirical evidence) Where do strategies fit in the investment portfolio and/or investment process 2
Stages of Beta Innovation From Theory to Practice From Market Weighting to Hedge Fund Replication A Beta Timeline Traditional Indexing Equities and fixed income Cap-weighting Long positions (buy and hold) Beta Customisation Slicing the market portfolio Proliferation of capweighted benchmarks Beta Innovation Beyond equities and fixed income Moving away from cap-weighting Alternative payoffs 1st attempts at equity indexing early 1970s Vanguard introduces 1 st Index equity mutual fund (market weighted) 1975 1st retail bond index fund 1985 Fama/French 3 factor model introduced 1992 Fung and Hsieh research: common risk factors explain much of fixed income hedge fund returns 2001 Arnott, Hsu, Moore introduce fundamental beta alternative to market weight indexing 2005 600 + ETFs, AUM surpassed $500mn 2007 1960 1970 1980 1990 2000 2010 1960s William Sharpe develops CAPM and textbook definition of beta 1984 1st institutional bond index fund 1993 SSgA introduces the 1st ETF index fund (SPDR) 2004 Agarwal and Naik find common risk factors explain 50-70% of variability equity hedge fund returns 2010 Cerulli predicts ETF AUM to exceed $1 trillion 1989 Bill Sharpe creates returns-based style analysis 2002 100 + ETFs AUM around $100mn Source: SSgA 3
What is Advanced Beta? Advanced Beta can be broadly categorised as: Exposure to the desired risk of a market or market segment while minimising exposure to uncompensated/undesired market risk Advanced Beta strategies span asset classes, investment styles and the risk/return spectrum Capturing non-traditional asset class returns Extensions of equity and fixed income REITs, convertible bonds, LDI, TIPS, Frontier markets, ESG, etc.* Beyond equity and fixed income Volatility, commodities, currency, breakeven inflation Modifying asset class payoffs Seeking engineered return payoffs Leveraged and inverse ETFs, Buy-write strategies Beta optimisation Factor-based valuation, volatility, beta, size, momentum, quality Optimised strategies, Minimum variance, low beta, low valuation Emulation strategies hedge fund replication, holdings based cloning strategies Risk reduction strategies equal-weighted, capped indices, GDP-weighting, liquidity tiers * Real Estate Investment Trusts (REITs), Liability-driven Investing (LDI), Treasury Inflation Protected Securities (TIPS), Environmental and Social Governance (ESG) 4
Advanced Beta Maintains Passive Benefits Maintains all key benefits of traditional passive investing: Diversified, Risk-Managed Exposure Strict risk parameters in place for all of the major risk characteristics that drive portfolio returns and tracking error versus the benchmark Cost-Efficient Investing Competitive management fees, lower transaction costs Minimal Surprises Clearly defined exposures transparency of holdings Advanced Beta equity strategies are liquid Strategies seek exposure to tradeable securities 5
Global Equities: Departing from Cap Weights What Leads Investors to Alternative Equity Allocations? Cross-sectional empirical evidence Tests of equilibrium asset pricing models Beta not rewarded as theory suggests Other attributes explain the cross-section of returns Valuation, Volatility, Size, Momentum Returns not explained by realised volatility of returns Academic debate Risk factors or investor mistakes? Industry response Many different products, indexes or strategies Fundamental Indexing TM, Wealth weighting, Valuation-tilting, Min Vol, Low Beta, Equal-Weighted, Efficient Indexes, Active Betas, etc Various marketing claims Most are plays on cross-sectional evidence Valuation, beta/volatility, size or momentum (or combinations) 6
Global Equities: Departing from Cap Weights What Equity Attributes have the Highest Long-Term Reward? Low Valuation P/F (price/fundamental) Common fundamental metrics Earnings, cashflow, dividends, sales, book value, etc. Low Volatility (Low Beta) 60-month historical volatility or beta is typical Smaller Size Market capitalisation Positive Momentum 12-month price return 7
Departing from the Market s Allocation of Capital Evaluating the Cross-Sectional Empirical Evidence Create an intuitive way to evaluate cross-sectional equity evidence 20 subsets of the market portfolio sorted by each attribute (separately) Valuation, Volatility, Size and Momentum Methodology Each subset (sub-portfolio) represents 5% of market cap weight Constituents are cap-weighted within each sub-portfolio For example, valuation sub-portfolio #1 is the 5% of cap weight with the lowest valuation Sub-portfolios reconstituted annually (Momentum reconstituted quarterly) Results MSCI World Universe Q2 1990 to Q1 2010 Sub-portfolio annualised AUD return Sub-portfolio annualised AUD volatility 8
Global Equities: Departing from Cap Weights SSgA Sub-Portfolio Methodology 12% SSgA Sub-Portfolio Methodology Each Sub-Portfolio Represents 5% of Universe Cap Weight Stocks are Cap-weighted within Sub-Portfolios Sub-Portfolio Cap Weight 11% 10% 9% 8% 7% 6% 5% 4% Lowest ranked stocks by attribute Highest ranked stocks by attribute 3% 2% 1% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Sub-Portfolios (Ranked by Attribute: Val, Vol, Size, Mom, etc.) Source: SSgA/Factset 9
Global Equities: Departing from Cap Weights Valuation-Sorted Returns MSCI World Sub-Portfolio Annualised US$ Returns, Apr 1990 Dec 2009 14% 12% 10% 8% 10.3% 12.1% 9.7% 10.8% 10.2% 8.2% 9.5% 9.8% 8.2% 8.0% 8.5% 6% 4% 5.4% 4.2% 4.1% 3.0% 2.3% 2% 1.7% 0% -2% -4% -1.6% -1.0% -6% -8% Sub-Portfolios (low valuation to the left) -5.8% Source: Factset/SSgA 10
Minimum Variance Basic Investment Theory: The Efficient Frontier Positive Is this possible? Return Market Minimum Variance Portfolio (MVP) Negative Low Standard Deviation of Returns High Assumptions Market is mean-variance efficient MVP has low return and low risk Implications Managers develop strategies around the market MVP portfolios are to be avoided But what if the Minimum Variance Portfolio Performed Well? Source: SSgA. This information is stylised and is for illustrative purposes only. The results do not represent an actual portfolio, index or investment process. 11
Global Equities: Departing from Cap Weights Volatility-Sorted Returns MSCI World Sub-Portfolio Annualised US$ Returns, April 1990 December 2009 12% 11.0% 11.1% 10% 8% 6% 7.6% 7.0% 6.2% 5.4% 6.0% 6.6% 8.2% 8.6% 6.1% 6.2% 9.0% 6.0% 4.7% 4% 3.7% 2% 2.0% 2.5% 0% 0.2% 0.3% Sub-Portfolios (low volatility to the left) Source: Factset/SSgA 12
Global Equities: Departing from Cap Weights Size-Sorted Returns MSCI World Sub-Portfolio Annualised US$ Returns, April 1990 December 2009 12% 10% 9.5% 8% 8.7% 7.4% 8.3% 8.6% 8.3% 7.5% 7.7% 8.5% 7.9% 7.3% 6% 6.4% 5.7% 6.3% 5.1% 4.8% 5.1% 4.4% 4% 2.7% 2% 0% -2% Sub-Portfolios (small capitalisation to the left) -0.7% Source: Factset/SSgA 13
Global Equities: Departing from Cap Weights Momentum-Sorted Returns MSCI World Sub-Portfolio Annualised US$ Returns, April 1990 December 2009 12% 10% 9.5% 8.2% 8.3% 8% 7.2% 7.6% 6.9% 7.4% 7.7% 7.0% 6% 5.8% 4.9% 4.8% 4.9% 5.8% 5.3% 5.7% 6.2% 4% 3.3% 2.3% 2% 1.0% 0% Sub-Portfolios (high momentum to the right) Source: Factset/SSgA 14
Global Equities: Departing from Cap Weights Concluding Comments Policy-level departure from cap-weighting deserves serious consideration Meaningful historical incremental returns and reduction in volatility Empirical evidence points to valuation, volatility and size as key attributes Combining approaches yields diversification benefits Tilting and optimisation are intuitive techniques to depart from cap weights Retain benefits of indexing low cost, transparency, liquidity and diversification Not without challenges Lack of theoretical foundation Potential for meaningful interim performance differential Risk vis-à-vis peers 15
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