Finding Consistent Alpha

GLOBAL INVESTMENT RESEARCH

Seth J. Masters Chief Investment Officer—Style Blend Equities Drew W. Demakis Chief Investment Officer—Structured Equities

With future market returns unlikely to match the high levels

of the 1990s, generating incremental alpha has become crucial.

Our research shows that it’s possible to do so with relative

consistency by combining managers effectively.

www.institutional.alliancebernstein.com For several decades, US pension plans have looked to the stock market to achieve high returns on their assets, and over time, this has been a winning strategy: The return on equities has exceeded the return on long-term government bonds fairly consistently. However, the recent bear market—the worst since the Great Depression—has contributed significantly to a disconcerting shortfall in the funding of pension plan liabilities.

The market’s return is bound to revert to the norm over may not have seemed that important when the market was time, but the norm is nothing like the 16.4% returns that returning 16% a year, with the market returning 9%, that funds enjoyed in the 20 years that ended in 2000, when extra 1% becomes critical. equity returns were boosted by dramatic expansion of In this paper, we will discuss both why achieving alpha price-earnings multiples (Display 1). Without the benefit is possible and how it can be done with relative consistency. of multiple expansion, equities are likely to return about 9% a year on average, and bonds, just 5%. Therefore, a typical plan with 60% of its assets in stocks and 40% in WHY ALPHA IS POSSIBLE bonds would see returns of about 7.3% annually, less than Efficient market theory postulates that alpha shouldn’t the 8.7% average return assumption. This 1.4 percentage exist, and common sense suggests that since the market point gap spells trouble. sums to the index, for a large group of investors to beat There are several worthwhile strategies for bridging the the market, others must lag behind. Nonetheless, the gap. Since no single one is likely to do the job, median manager in Mercer Investment Consulting’s most plans should probably consider all of them: raise the universe of US large cap managers outperformed the equity allocation of the overall fund, globalize investment S&P 500 by 0.6% a year on average for the 10 years strategies, add hedge funds and private equity, and ending in December 2002; those in the top quartile increase the alpha on existing assets. outperformed by at least 1.9% (Display 2). How is this possible? Our answer is that alpha exists because not all Increasing alpha, of course, flies against one of the investors seek it, and many of those who do seek it face biggest trends in investing of the last 15 years: the shift to systematic obstacles. indexed equities. Our research, however, shows that increasing the alpha on existing assets offers great Many investors don’t seek alpha because they have potential: While picking up an additional 1% from alpha other goals for their equity investments. For example,

Display 1 Display 2 Plans Face a Looming Return Gap Managers Have Delivered Outperformance

Annualized Return Mercer Manager Universe* vs. S&P 500 16.4% (1993–2002) Information P/E 6.7 Expansion Gap Premium Tracking Error Ratio† 1.4% Top 1.9% 9.6% 0.3 8.9% 8.7% Quartile 7.3% Earnings Growth 6.2 6.0 4.9% Median 0.6% 7.5% 0.1 Yield 3.5 2.9 20 Years Forecast Forecast Forecast Average 1981–2000 Equities Bonds 60% Stocks/ Expected 40% Bonds* Plan Return Bottom (0.7)% 5.2% (0.1) Quartile As of March 31, 2003 *Stocks are represented by the S&P 500 and bonds by the Lehman Aggregate Bond Index. *Mercer universe of US managers with reported returns from 1993–2002 Source: Center for Research in Security Prices (CRSP), Federal Reserve Board, (351 managers eligible as of February 2003) Lehman, Standard & Poor’s Handbook and Bernstein estimates †Premium/tracking error Source: Mercer Investment Consulting and AllianceBernstein

Finding Consistent Alpha 1 many individuals and corporations own large stakes in Display 4 companies for strategic reasons or to control them; such Consequently, Market Inefficiencies Persist non-floating positions make up 16% of US market (%) capitalization (Display 3). Obviously, Bill Gates does not 50 Low P/E Stocks actively manage his stake in Microsoft to add value 40 Outperform relative to an index on a month-to-month or year-to-year 30 Average basis. Smaller holdings by individuals, who also tend not 20 to be effective alpha-seekers, comprise another 26% of 10 US market cap. Index funds account for another 9%; 0 by definition, they do not seek to add alpha. (10) (20) The two alpha-seeking groups, mutual funds and other 72 77 82 87 92 97 02 institutional investors, represent slightly less than 50% of (%) 50 Positive Momentum Stocks Outperform market capitalization. That means there is opportunity for 40 them to benefit in aggregate at the expense of the other 30 Average groups. Of course, not all alpha-seeking professionals 20 succeed in delivering alpha, and many face systematic 10 obstacles to doing so. 0 One systematic obstacle is the tendency of investors to (10) (20) chase performance, as shown in the recent tech bubble. 72 77 82 87 92 97 02 Growth stocks’ massive outperformance during the tech Through December 31, 2002 Annualized hedged returns of most attractive quintile of stocks relative to the bubble in 1998 and 1999 led to a total of $400 billion in equal-weighted universe of global large-cap developed markets net flows from value mutual funds to growth mutual Source: Bernstein analysis funds in 1999 and 2000, according to Morningstar. Awash with cash, managers of growth funds were forced to add to their established positions at ever-increasing prices, once the bubble burst, soaring fund redemptions forced creating alpha opportunities for other investors. Then, them to sell positions at ever-decreasing prices, which also created alpha opportunities. Display 3 Thus, timing decisions by the ultimate investors, rather Why Alpha Can Exist: Not All Investors Seek It than alpha-seeking activity by fund managers, drove many purchase and sale decisions at mutual funds. Such Composition of US Market Capitalization $13.2 Trillion market distortions allow alpha-generating inefficiencies Non-Floating to persist even when they are well understood and Holdings* “Alpha Seekers” exploited by active managers. 16% Active Institutional 31% Managers Two well-known examples of such market inefficiencies Individual (or anomalies) are often associated with the value and Holdings† 26% growth style disciplines, respectively. The cheapest 18% quintile of stocks, ranked by price-to-earnings, system- 9% atically outperformed the MSCI World (Display 4, top). So did the quintile of stocks with the highest price Index Funds Active Mutual Funds momentum (Display 4, bottom). Of course, a key step in As of December 31, 2001 choosing an active manager is believing in the anomaly *Includes company founders and their heirs and corporate stakes †Includes company employees and other direct investments by individuals that the manager is seeking to exploit and checking that the are not professionally managed Source: Federal Reserve, Salomon Smith Barney and AllianceBernstein manager’s process and portfolios are consistent with exploiting that anomaly.

2 ALLIANCEBERNSTEIN FINDING ALPHA THE RISK/RETURN TRADE-OFF But will active mangers be successful? As our legal The extremely long time required to have confidence in advisors insist we always say, past performance isn’t a high alpha managers, statistically speaking, arises because reliable indicator of future results. This is true for several only higher tracking error managers tend to deliver higher reasons. First, anomalies such as the long-term alpha. While the highest-alpha decile of US managers in outperformance of low P/E and high momentum stocks Mercer’s universe with high tracking error delivered don’t pay off consistently, so a manager that is disciplined annual premiums of at least 3% over the last 10 years, the in exploiting such anomalies will tend to have fairly high best performing managers with low tracking error tracking error. The median tracking error for managers in generated only a 1.3% premium (Display 6, top). the Mercer universe of US managers for the 10 years Furthermore, the incremental risk needed to generate ending 2002 was 7.5%, as Display 2 shows; such a greater alpha is large enough that the information ratio manager would typically underperform in nearly half of declines. Thus, high alpha managers tend to have lower all one-year periods. This variability in performance information ratios; managers with high information tends to decrease investors’ confidence. ratios, however, tend to have both lower tracking error Second, even unskillful managers can be lucky. It is and lower alpha (Display 6, bottom). That is, the only with the passage of time that you can tell whether the managers in whom you can have greater confidence good periods outweigh the bad ones and decrease the seldom offer high alpha; you can’t have such confidence influence of random outliers. Statistical tests allow us to in managers with high alpha. establish when you can have confidence that performance To understand why there is a declining marginal utility was due to skill. A manager’s information ratio—the pre- to added risk, let’s look at a simple example: One dollar mium divided by tracking error—is a useful measure for invested in a stock rises to $2 in the next year as the stock such tests, because by definition it relates return to risk. Unfortunately, the statistical evidence indicates that Display 6 many years of performance are needed to develop a High-Risk Managers Have Higher Premiums... reasonable degree of confidence that a manager’s alpha Premium for Top-Decile Manager was due to skill, not luck. For the median manager with in Mercer Universe* (vs. S&P 500; 1993–2002) an information ratio of 0.1, it would take 271 years to 3.0% obtain 95% confidence; for a first-quartile manager 2.2% with an information ratio of 0.3, it would take 31 years (Display 5). Both time periods are too long to be of much 1.3% practical use when judging real managers. Even the 11 years required to have 95% confidence in a manager with Tracking Error: <3% 3 to 6% >6% a 0.5 information ratio is long in the context of most investors’— and managers’—careers. …but Low-Risk Managers Usually Have Higher IRs Information Ratio Mercer Manager Universe* Display 5 (%) vs. S&P 500 0.5 Top (1993–2002) It Takes Many Years to Distinguish Skill from Luck Quartile 0.4 Information 0.3 Median 0.28% Ratio 95% Confidence of 1.0 a Positive Premium 0.2 0.1 0.06% 0.01% 0 Bottom 0.5 (0.1) Quartile 0.3 (0.2) Tracking Error: <3% 3 to 6% >6% 0.1 11 31 271 *Mercer US managers with a reported premium and with tracking error between Years 1% and 9% from 1993 to 2002 (245 managers eligible as of February 2003) Source: AllianceBernstein Source: Mercer Investment Consulting and AllianceBernstein

Finding Consistent Alpha 3 returns 100%, but drops back to $1 again the next year as However, the probability of outperforming the bench- the stock declines 50%. While the average return for the mark in any given 12-month period is greatest for portfolios two years is 25%, the compound growth per year is 0%. with 200–300 stocks (Display 10). Although alpha drops The 25% difference between the two is called “risk drag.” as the number of stocks increases from 50 to 250, risk drops It is the damage that volatility inflicts on long-term returns. Display 7 Risk drag is a function of the square of volatility: It Risk Drag Grows Geometrically grows geometrically as volatility rises. If you start with a volatility of roughly 10%, similar to the volatility of Approximate Risk Drag 18.0% bonds, the risk drag is about 0.5% (Display 7). If you double the volatility to 20%, about the volatility of most 12.5% equity indexes, the risk drag quadruples to 2%. If you 8.0% triple the volatility to 30%, about the volatility of a 4.5% 2.0% relatively stable single stock, the risk drag goes up by a 0.5% factor of nine, to 4.5%. If you raise the volatility six-fold 10 20 30 40 50 60 to 60%, which is typical of many small-cap and emerging- Volatility (%) markets stocks, the risk drag rises 36-fold, to 18%. Source: AllianceBernstein

Now, active portfolio management entails taking Display 8 risks with single stocks in portfolios, so risk drag Concentrated Portfolios Have Greater Risk... significantly affects how actively managed portfolios (%) Volatility deliver alpha and obtain information ratios. Highly (1970–2002) 40 concentrated portfolios are much more volatile than Volatility of Average Stock diversified portfolios. As you would expect, a Monte 35 Carlo simulation based on real US stock market returns 30 for the last 30-odd years shows that the more stocks 25 you add to a portfolio, the lower the portfolio’s volatility Volatility of Index 20 (Display 8, top). Perhaps surprisingly, however, the more you reduce the portfolio to just a handful of 15 10 stocks—the more concentration risk you take—the 1 2 3 5 10 20 50 100 200 500 lower your expected return (Display 8, bottom). This Number of Stocks is because risk drag slows compound growth. …and Risk Drag Slows Their Compound Growth Thus, even if a skillful manager chooses his very best (%) Compound Return idea for a one-stock portfolio, the alpha produced is likely 14 (1970–2002) Index Return to be negative, because the risk drag of owning only a 13 single stock overwhelms the manager’s skill at picking 12 Risk Drag Portfolio Return stocks. You need tremendous skill to overcome the risk 11 drag of a single-stock portfolio—or even the 20-stock 10 portfolios that have gained some popularity in recent years. 9 Thus, our Monte Carlo simulation shows that the sweet 8 spot for a portfolio aiming to produce high alpha from a 7 1 2 3 5 10 20 50 100 200 500 500-stock universe is 40 to 60 stocks (Display 9). When Number of Stocks you expand portfolios beyond that, you tend to see a Statistics for each portfolio of a target number of stocks are based on a Monte Carlo gradual decline in relative return, because your 200th simulation in which average statistics were calculated from 1,000 random samples. For each sample, yearly returns were generated based on a strategy of equally allocating “best idea” isn’t likely to produce the same return as your capital among the target number of randomly selected stocks in the S&P 500 at the beginning of each calendar year from 1970 to 2002 and holding the portfolio for a year. 50th best idea. And when you get to your 500th best idea Annual portfolio reconstitution incurred no transaction costs. (when drawing on a 500-stock index), you’ve given up on Source: Standard & Poor’s and AllianceBernstein active premiums altogether.

4 ALLIANCEBERNSTEIN even faster—so that information ratios and consistency Display 11 increase. This explains why managers with the highest Combing Portfolios with Uncorrelated Premiums premiums tend to be less consistent, and managers with Generates Consistent Alpha the greatest consistency tend to have lower premiums. (%) Probability of Outperforming 75 -0.3 Correlation Zero Correlation 70 Display 9 65 Highest Alpha Comes with Moderate Concentration 60 Monte Carlo Simulation 55 +0.5 Correlation of US Manager Performance* 50 Alpha Moderate Concentration 1 2 3 4 5 (%) Number of Managers 2 Assumes each manager has a 0.2 information ratio Source: AllianceBernstein 0

(2) SQUARING THE CIRCLE Excess Concentration (4) Fortunately, it’s possible to get high alpha with consistency for the plan as a whole, if not from any one manager, by (6) 1 5 20 50 100 200 300 400 500 combining high alpha managers with performance streams Number of Stocks that are negatively correlated to each other. Although combining many managers with 0.5 correlation is not very helpful, combining just two or three managers with Display 10 negative 0.3 correlation helps a lot (Display 11). Highest Win Rate Comes with Full Diversification A simple illustration helps to explain why. Let’s say Monte Carlo Simulation of you combine an aggressive growth manager with a US Manager Performance* Probability of deep value manager and both have 50-stock portfolios Winning (%) Fully Diversified benchmarked to the S&P 500 (Display 12). Each 80 50-stock portfolio has an average weight of 2% in each stock versus the 0.02% average for the S&P 500, 60 and average overweights that are nine times the size of its average underweights. Assuming no portfolio overlap, the 40 two portfolios together have 100 stocks, which lowers the ratio of overweights to underweights to four times. This 20 direct risk reduction is very significant. 1 5 10 20 50 100 200 300 400 500 Number of Stocks Display 12 Two Concentrated Portfolios Can Offset Risks *Performance for each portfolio of a target number of stocks is based on a Monte Carlo Ratio of simulation in which average statistics were calculated from 100 random samples. For Average Average Average Over- each sample, yearly returns were randomly generated for each of 500 stocks for 20 years. The returns were generated from a normal distribution with a mean, standard Security Over- Under- to Under- deviation, minimum and maximum return based on actual S&P 500 constituents for each Portfolio Weighting weight weight weights of the 20 years from 1983 to 2002. Next, yearly expected returns were randomly generated for each of 500 stocks for 20 years using the same distributions described 50 Value 2.0% +1.8% (0.2)% 9x above, such that the average cross-sectional rank correlation of returns and expected Stocks returns for each year was equal to 0.05.Yearly returns for a portfolio of a target number of stocks were generated by equally allocating capital among the target number of stocks 50 Growth 2.0 +1.8 (0.2) 9 with the highest expected returns at the beginning of each year and holding those stocks Stocks for a year (annual portfolio reconstitution incurred no transaction costs). The benchmark for comparison was a portfolio constructed using the same methodology 100 Stocks 1.0 0.8 (0.2) 4 with a portfolio size of 500. Source: Standard & Poor’s and AllianceBernstein Source: AllianceBernstein

Finding Consistent Alpha 5 Furthermore, the 50 value stocks are likely to be CONCLUSION precisely the kind of ideas that the growth manager underweights, and the 50 growth stocks are likely to be There is, after all, a practical way to have confidence that the kind of ideas that the value manager underweights. As you can harvest high alpha, without waiting for 271 a result, the two portfolios neatly offset each other’s risks. years. Find managers who have reasonably high alpha- In practice, when you combine two portfolios generating capacity and negatively correlated sources of with complementary styles, or two portfolios that for alpha, and rebalance between them on a disciplined basis. some other reason have complementary risk factors, Under these conditions, you can have much greater the correlation of their alphas is likely to be negative 0.3, confidence in the likely performance of the group than in or even less. any one manager alone. Of course, when you find such a pair, one of the Opponents of active management often argue that managers will tend to trail when the other is leading. it is hard to find skillful managers and that even if Needless to say, it can be very uncomfortable to stick you do, when you put several together, you simply end up with—and rebalance into—the laggard. For those who with a high-cost index fund. While we certainly agree cannot tolerate the discomfort, there is a simple solution: that skillful managers are hard to find, our research leads Get someone else to rebalance for you. Many plan us to a different conclusion: By combining managers sponsors decided after the emerging-markets crisis of the skillfully, you significantly enhance the chance of late 1990s that the best way to stick with emerging- harvesting alpha. markets equities was to invest in EAFE-plus mandates, which package emerging-markets equities with developed-market equities. Similarly, some plan sponsors today are seeking to avoid focusing on the inconsistent alpha of their active style managers by hiring a consultant or investment manager to rebalance between them.

6 ALLIANCEBERNSTEIN About the Authors Seth J. Masters Chief Investment Officer— Style Blend Equities Seth J. Masters is Chief Investment Officer for Style Blend and Core Equity Services at Alliance. He has been with Alliance and, prior to that, Sanford C. Bernstein since 1991. Mr. Masters is the Chairman of the firm’s US and Global Style Blend Investment Policy Groups, and a member of the Bernstein Global, International and Emerging Markets Value Investment Policy Groups. He joined Bernstein as a research analyst covering banks, insurance companies and other financial firms, then became CIO for Emerging Markets Value in 1994, and assumed his current position in 2002. Before joining Bernstein, he was a senior associate at Booz, Allen & Hamilton from 1986 to 1990 and taught Economics in China from 1983 to 1985. He earned a B.A. from Princeton University and an M.Phil. in Economics from Oxford University.

Drew W. Demakis Chief Investment Officer— Structured Equities

Drew W. Demakis is Chief Investment Officer for Structured Equities, the Chairman of the Risk Investment Policy Group and a member of the Core/Blend Services investment team. Previously, he served as the director of product development for Structured Equities. Mr. Demakis joined Bernstein in 1998 as a senior portfolio manager—international equities, and remains a member of the Global and International Value Investment Policy Groups. Before joining Bernstein, he was managing director and head of research at BARRA RogersCasey, an investment consulting firm, which he joined in 1988. Mr. Demakis earned a B.A. in Economics from the University of Chicago and an M.B.A. from Washington University.

Finding Consistent Alpha 7 A Global Leader Broad Array Of Services We are a global leader in institutional investment management AllianceBernstein’s products are designed to meet a broad and research. We bring together more than three decades of range of client requirements. In addition to our established Alliance Capital Management’s expertise in growth investing growth and value equity products, we offer style blend, and Sanford C. Bernstein’s excellence in value management. enhanced-index and passive services. Our wide array of equity We are a large and well-respected fixed-income manager, as services includes single-country portfolios for the US, UK, well. The unique breadth and depth of our skills allows us to Canada, Japan and Australia; international and global offer a broad array of products to clients around the world. strategies; and European and Asian regional portfolios. The capitalization focus ranges from large-cap to small, depending As of March 31, 2003, our firm managed US$386 billion in on the service. Strategies range from high-expected premium, assets, including US$212 billion for institutional clients around more concentrated services to benchmark-sensitive services. In the world. Our clients include private and public pension plans; the fixed-income arena, our products cover both taxable and foundations and endowments; insurance companies, and tax-exempt investments, ranging from investment-grade to governments in more than 30 countries. high-yield bonds in markets around the world. Here, too, we Research Strength offer an array of single-country, regional and global portfolios, We believe that research is the ultimate source of superior managed in various currencies. investment returns. Research is the touchstone of our investment process and a principal career path for our investment Flexibility in Client Mandates Our extensive product offerings—combined with the global professionals. As a result, our firm today boasts one of the scope of our research and portfolio management capabilities— largest global research commitments in the investment- gives us the flexibility to meet a wide range of client needs, management industry. Our research is also highly regarded. In regardless of home country, base currency or tax position. 2002, a major industry study* ranked Bernstein’s sell-side Many services can be customized to include or exclude institutional research analysts #1 in three crucial categories: countries and to meet clients’ benchmark sensitivity or asset- “quality of research,” “most trusted” and “best job of liability matching requirements. maintaining independence and objectivity.” With more than 200 analysts operating in 11 countries, we cover many thousands of Commitment to Client Service securities in every meaningful capital market in the world, for a We pride ourselves on the structure we have established to meet breadth and depth of coverage few firms can rival. our diverse clients’ needs. Alliance Capital Management L.P. is The research effort dedicated to our clients’ investment a US-registered investment adviser with affiliates licensed in portfolios is organized in three departments: separate groups various jurisdictions around the world; our client-service and dedicated to growth and value equities, reflecting the unique investment professionals work out of offices in 16 countries to focus and culture required for each style, and a fixed-income provide personalized, timely service and communications. We team. Each group employs its own methodology but shares also provide access to our investment professionals through information as needed to serve the interests of our portfolios. one-on-one meetings, conference calls, conferences and print and web-based publications. Disciplined Investment Process We believe our range of services, global research coverage and Regardless of asset class or assignment, our investment ability to serve clients in virtually all parts of the world make processes pay close attention to fundamentals and are highly AllianceBernstein the preeminent resource for institutional disciplined. Our growth, value and core equity, and our fixed- investors worldwide. income management teams adhere to clearly defined rules for security selection and portfolio construction to help clients get products with the characteristics and long-term performance patterns they seek.

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