The Power of Economic Science

Rebalanced annually. Barclays Capital data, formerly Lehman Brothers, provided by Barclays Bank PLC. The S&P data are provided by Standard & Poor’s Index Services Group. The Merrill Lynch Indices are used with permission; copyright 2011 Merrill Lynch, Pierce, Fenner & Smith Incorporated; all rights reserved. Dimensional Index data compiled by Dimensional. Emerging Markets Blended Index consists of 50% Fama/French Emerging Markets Index, 25% Fama/French Emerging Markets Small Cap Index, and 25% Fama/French Emerging Markets Value Index. Fama/French Emerging Markets, Fama/French Emerging Markets Value and Fama/French Emerging Markets Small Cap Index weightings allocated evenly between Dimensional International Small Cap Index and Fama/French International Value Index prior to January 1989 data inception. Dimensional International Small Cap Value Index weighting allocated to International Small Cap Index prior to July 1981 data inception. International Value weighting allocated evenly between International Small Cap and MSCI World ex USA Index prior to January 1975 data inception. Indexes are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio. Past performance is not a guarantee of future results. Not to be construed as investment advice. Returns of model portfolios are based on back-tested model allocation mixes designed with the benefit of hindsight and do not represent actual investment performance. See cover page for additional information.

S1920.7

AnnualizedCompound

Return

Annualized StandardDeviation

Model Portfolio 1 9.47% 11.16%





Barclays US Govt./Credit

Bond Index

S&P 500 Index

BofAMerrill Lynch

One-Year US Treasury

Note Index

US Small

Cap Index

US Large Value Index

Targeted Value Index

Intl. LargeIndex

Intl.SmallIndex

Intl. Large ValueIndex

Intl.Small ValueIndex

Emerging Markets Blended

Index

Model Portfolio 1 40% 60%

Model Portfolio 2 60% 40%

Model Portfolio 3 30% 40% 30%

Model Portfolio 4 15% 40% 15% 15% 15%

Model Portfolio 5 7.5% 40% 7.5% 7.5% 7.5% 6% 6% 6% 6% 6%

Merrill Lynch One-Year US Treasury Note Index

S&P 500 Index

US Small Cap Index

US Large Value Index

Targeted Value Index

International Large Index

International Small Index

International Large Value Index

International Small Value Index

Emerging Markets Blended Index

A Fully Diversified PortfolioQuarterly: 1973-2010Model Portfolio 5

In US dollars. Indices are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio. Past performance is not a guarantee of future results. US value and growth index data (ex utilities) provided by Fama/French. The S&P data are provided by Standard & Poor’s Index Services Group. CRSP data provided by the Center for Research in Security Prices, University of Chicago. International Value data provided by Fama/French from Bloomberg and MSCI securities data. International Small data compiled by Dimensional from Bloomberg, StyleResearch, London Business School, and Nomura Securities data. MSCI EAFE Index is net of foreign withholding taxes on dividends; copyright MSCI 2011, all rights reserved. Emerging markets index data simulated by Fama/French from countries in the IFC Investable Universe; simulations are free-float weighted both within each country and across all countries.Indexes are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio.Past performance is not a guarantee of future results. Values change frequently and past performance may not be repeated. There is always the risk that an investor may lose money. Small company risk: Securities of small firms are often less liquid than those of large companies. As a result, small company stocks may fluctuate relatively more in price. Emerging markets risk: Numerous emerging countries have experienced serious, and potentially continuing, economic and political problems. Stock markets in many emerging countries are relatively small, expensive, and risky. Foreigners are often limited in their ability to invest in, and withdraw assets from, these markets. Additional restrictions may be imposed under other conditions. Foreign securities and currencies risk: Foreign securities prices may decline or fluctuate because of: (a) economic or political actions of foreign governments, and/or (b) less regulated or liquid securities markets. Investors holding these securities are also exposed to foreign currency risk (the possibility that foreign currency will fluctuate in value against the US dollar).

Size and Value Effects Are Strong around the WorldAnnual Index Data

S1220.8

US Large Value

S&P 500

US Large

Growth

US Small Value

CRSP 6-10

US Small

GrowthIntl.

ValueIntl.

SmallMSCI EAFE

Intl. Growth

Emg. Markets

Value

Emg. Markets

Small

Emg. Markets “Market”

Emg. Markets Growth

US Large Capitalization Stocks

1927–2010

US Small Capitalization Stocks

1927–2010

Non-US Developed Markets Stocks

1975–2010

Emerging Markets Stocks

1989–2010

14.03 11.88 11.35 19.17 15.98 13.95 18.48 19.17 13.67 11.29 25.01 21.98 19.46 17.05

27.01 20.51 21.93 35.13 30.94 34.05 24.56 28.13 22.29 22.21 42.01 40.67 36.40 34.89

Average Return (%)Standard Deviation (%)

Annualized Compound Returns (%)

S1260.3

Structure Determines Performance

Source: Dimensional Fund Advisors study (2002) of 44 institutional equity pension plans with $452 billion total assets.Factor analysis run over various time periods, averaging nine years. Total assets based on total plan dollar amounts as of year end 2001.Average explanatory power (R2) is for the Fama/French equity benchmark universe.

• Over 96% of the variation in returns is due to risk factor exposure.

• After fees, traditional management typically reduces returns.

sensitivity to market[market return minus T-bills]

sensitivity to size[small stocksminus big stocks]

sensitivity to BtM[value stocksminus growth]

randomerrore(t)

++ + +=average expected return[minus T-bills]

average excess return

THE MODEL TELLS THE DIFFERENCE BETWEEN INVESTING AND SPECULATING

Priced Risk• Positive expected return.• Systematic.• Economic.• Long-term.• Investing.

Unpriced Risk• Noise.• Random.• Short-term.• Speculating.

96% Structured Exposure to Factors.

4% Unexplained Variation

• Market.• Size.• Value/Growth.

Five Factors Help Determine Expected ReturnAnnual Average Returns1927–2010

Equity factors provided by Fama/French. Fixed factors provided by Ibbotson Associates.Indices are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio.

8.04%

3.75%

4.90%

2.11%

0.30%

Market Factor

All Equity Universe

minus T-Bills

Size Factor

Small Stocks minus

Large Stocks

BtM Factor

High BtMminus

Low BtM

Maturity Factor

LT Govt.minus

T-Bills

Default Factor

LT Corp.minus

LT Govt.

S1270.2

Periods based on rolling annualized returns. 715 total 25-year periods. 775 total 20-year periods. 835 total 15-year periods. 895 total 10-year periods. 955 total 5-year periods.Performance based on Fama/French Research Factors. Securities of small companies are often less liquid than those of large companies. As a result, small company stocks may fluctuate relatively more in price. Mutual funds distributed by DFA Securities LLC.

The Risk Dimensions DeliveredJuly1926–December 2010

S1271.4

Value beat growth 100% of the time.





US Value vs. US GrowthOVERLAPPING PERIODS






Small beat large 96% of the time.





US Small vs. US Large






Based on rolling annualized returns. Rolling multi-year periods overlap and are not independent. This statistical dependence must be considered when assessing the reliability of long-horizon return differences. International Value vs. International Growth data: 133 overlapping 25-year periods. 193 overlapping 20-year periods. 253 overlapping 15-year periods. 313 overlapping 10-year periods. 373 overlapping 5-year periods. International Small vs. International Large data: 193 overlapping 25-year periods. 253 overlapping 20-year periods. 313 overlapping 15-year periods. 373 overlapping 10-year periods. 433 overlapping 5-year periods. International Value and Growth data provided by Fama/French from Bloomberg and MSCI securities data. International Small data compiled by Dimensional from Bloomberg, StyleResearch, London Business School, and Nomura Securities data. International Large is MSCI World ex USA Index gross of foreign withholding taxes on dividends; copyright MSCI 2011, all rights reserved.

The Risk Dimensions DeliveredS1271.4






International Small vs. International Large











International Value vs. International GrowthOVERLAPPING PERIODS






January 1975–December 2010 January 1970–December 2010

• Equity Market(complete value-weighted universe of stocks)Stocks tend to have higher expected returns than fixed income over time.

• Company Size(measured by market capitalization)Small company stocks tend to have higher expected returns than large company stocks over time.

• Company Price(measured by ratio of company book value to market equity)Lower-priced “value” stocks tend to have higher expected returns than higher-priced “growth” stocks over time.

Eugene F. Fama and Kenneth R. French, “The Cross-Section of Expected Stock Returns,” Journal of Finance 47, no. 2 (June 1992): 427-65.Eugene F. Fama and Kenneth R. French are consultants for Dimensional Fund Advisors. This page contains the opinions of Eugene F. Fama and Kenneth R. French but not necessarily of Dimensional Fund Advisors or DFA Securities LLC, and does not represent a recommendation of any particular security, strategy, or investment product. The opinions expressed are subject to change without notice. This material is distributed for educational purposes only and should not be considered investment advice or an offer of any security for sale. Dimensional Fund Advisors (“Dimensional”) is an investment advisor registered with the Securities and Exchange Commission. All materials presented are compiled from sources believed to be reliable and current, but accuracy cannot be guaranteed. This article is distributed for educational purposes, and it is not to be construed as an offer, solicitation, recommendation, or endorsement of any particular security, products or services described. ©2011 by Dimensional Fund Advisors. All rights reserved.

Value

Large

Small

Growth

Increased RiskExposure andExpected Return

TotalStockMarket

Decreased Risk Exposure and

Expected Return

Three Dimensions of Stock Returns around the World

S1274.3

Risk and Return Are Related

Day Month 3 Months Ending

6 Months Ending

12 Months Ending

10/13/08 10/74 10/82 6/75 6/83

10/19/87 10/87 11/08 2/09 2/09 Worst Periods and the Return If Missed

Best Periods and

the Return If Missed

Best/Worst Missed Period

Total Period

9.70% 9.58% 9.36% 9.06% 8.72%

11.52%11.45%10.94%10.64%10.57%9.99%

Ann

ualiz

ed C

ompo

und

Ret

urns

%

Time periods greater than one month are based on monthly rolling periods, and dates indicated are end of period.The S&P data are provided by Standard & Poor’s Index Services Group. Indexes are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio. Dimensional Fund Advisors is an investment advisor registered with the Securities and Exchange Commission. Information contained herein is compiled from sources believed to be reliable and current, but accuracy should be placed in the context of underlying assumptions. This publication is distributed for educational purposes and should not be considered investment advice or an offer of any security for sale. Past performance is not a guarantee of future results. Unauthorized copying, reproducing, duplicating, or transmitting of this material is prohibited. Date of first use: June 1, 2006.

S1330.7

Performance of the S&P 500 IndexDaily: January 1, 1970-December 31, 2010

• The best single day was October 13, 2008.

• The best one-month return, October 1974, happened immediately after the second-worst one-year period.

• The occurrence of strongly positive returns has been especially unpredictable. Investors attempting to wait out an apparent downturn ran a high risk of missing these best periods.

• Nine of the top 25 days occurred between September 2008 and February 2009, during which time the S&P dropped 41.8%

• Five of the Top 10 days occurred between October 2008 and November 2008, during which time, the S&P 500 dropped 22.8%.

S1400.1

5. Investment Considerations

I. Investment Considerations

II. Mutual Fund Expenses

III. Fees Matter

IV. The Limits of Fund Rating Services

V. Traditional Asset Allocation Generates Excess Turnover

Investment Considerations

• Reduce expenses.

• Diversify systematically.

• Minimize taxes and turnover.

• Think long-term.

• Apply discipline.

• Hold low-cost funds.

• Maintain asset allocation.

S1410.1

Mutual Fund Expenses

“After costs, the return on the average actively managed dollar will be less than the return on the average passively managed dollar for any time period.”

—William F. Sharpe, 1990 Nobel Laureate

William F. Sharpe, “The Arithmetic of Active Management,” Financial Analysts Journal 47, no. 1 (January/February 1991): 7-9.Mutual fund expense ratios as of April 9, 2010. Asset weighting based on net assets as of December 31, 2008. Data provided by Morningstar, Inc.Passive funds are those coded by Morningstar as Index Funds.

Average of All Funds

Weighted Average, Based on Fund Assets

Active Passive

Domestic Mutual Fund Expense Ratios





Active Passive



International Mutual Fund Expense Ratios

S1420.5

Fees MatterS1430.4

$4,983,951

$3,745,318

$2,806,794

1% Fee

2% Fee

3% Fee

$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

1 Year 3 Years 5 Years 10 Years 20 Years 30 YearsTime

Dol

lars

Assumed 6.5% Annualized Return over 30 Years

• Fees matter.

• Over long time periods, high management fees and related expenses can be a significant drag on wealth creation.

• Passive investments generally maintain lower fees than the average actively managed investment by minimizing trading costs and eliminating the costs of researching stocks.

For illustrative purposes only.

Fund A Fund B Fund C Fund D

Morningstar (Dec 2000)

Forbes (Dec 2000) C A A+ D

US News & World Report (Dec 2000) 34 50 10 93

Wall Street Journal (Jan 2001) E C A B

BusinessWeek (Jan 2001) A No Rating B+ C

Funds A, B, C, and D are actual funds. They are not identified because the purpose of this illustration is to emphasize that ratings, by themselves, do not provide enough information to make a sound investment decision.

Morningstar: Five stars is highest rating; one star is lowest rating.US News & World Report: 100 is highest rating; 1 is lowest rating.

The Limits of Fund Rating ServicesS1440.1

Innovations in FinanceS1610.2

1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974

The Birth of Index FundsJohn McQuown,Wells Fargo Bank, 1971;Rex Sinquefield,American National Bank, 1973

Banks develop the first passive S&P 500 Index funds.

Efficient Markets HypothesisEugene F. Fama,University of Chicago

Extensive research on stock price patterns.

Develops Efficient Markets Hypothesis, which asserts that prices reflect values and information accurately and quickly. It is difficult if not impossible to capture returns in excess of market returns without taking greater than market levels of risk.

Investors cannot identify superior stocks using fundamental information or price patterns.

Single-Factor Asset Pricing Risk/Return ModelWilliam SharpeNobel Prize in Economics, 1990

Capital Asset Pricing Model: Theoretical model defines risk as volatility relative to market.

A stock’s cost of capital (the investor’s expected return) is proportional to the stock’s risk relative to the entire stock universe.

Theoretical model for evaluating the risk and expected return of securities and portfolios.

The Role of StocksJames TobinNobel Prize in Economics, 1981

Separation Theorem:1. Form portfolio of risky assets.2. Temper risk by lending and borrowing.

Shifts focus from security selection to portfolio structure.

“Liquidity Preference as Behavior Toward Risk,” Review of Economic Studies, February 1958.

Conventional Wisdom circa 1950

“Once you attain competency, diversification is undesirable. One or two, or at most three or four, securities should be bought. Competent investors will never be satisfied beating the averages by a few small percentage points.”

Gerald M. Loeb, The Battle for Investment Survival, 1935

Analyze securities one by one. Focus on picking winners. Concentrate holdings to maximize returns.

Broad diversification is considered undesirable.

Diversification and Portfolio RiskHarry MarkowitzNobel Prize in Economics, 1990

Diversification reduces risk.

Assets evaluated not by individual characteristics but by their effect on a portfolio. An optimal portfolio can be constructed to maximize return for a given standard deviation.

Investments and Capital StructureMerton Miller and Franco ModiglianiNobel Prizes in Economics,1990 and 1985

Theorem relating corporate finance to returns.

A firm’s value is unrelated to its dividend policy.

Dividend policy is an unreliable guide for stock selection.

Behavior of Securities PricesPaul Samuelson, MITNobel Prize in Economics, 1970

Market prices are the best estimates of value.

Price changes follow random patterns. Future share prices are unpredictable.

“Proof That Properly Anticipated Prices Fluctuate Randomly,” Industrial Management Review, Spring 1965.

First Major Study of Manager PerformanceMichael Jensen, 1965A.G. Becker Corporation, 1968

First studies of mutual funds (Jensen) and of institutional plans (A.G. Becker Corp.) indicate active managers underperform indices.

Becker Corp. gives rise to consulting industry with creation of “Green Book” performance tables comparing results to benchmarks.

Options Pricing ModelFischer Black, University of Chicago;Myron Scholes, University of Chicago;Robert Merton, Harvard UniversityNobel Prize in Economics, 1997

The development of the Options Pricing Model allows new ways to segment, quantify, and manage risk.

The model spurs the development of a market for alternative investments.

S1610.2

1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Nobel Prize Recognizes Modern Finance

Economists who shaped the way we invest are recognized, emphasizing the role of science in finance.

William Sharpe for the Capital Asset Pricing Model.

Harry Markowitz for portfolio theory.

Merton Miller for work on the effect of firms’ capital structure and dividend policy on their prices.

Variable Maturity Strategy Implemented

Eugene F. Fama

With no prediction of interest rates, Eugene Fama develops a method of shifting maturities that identifies optimal positions on the fixed income yield curve.

“The Information in the Term Structure,” Journal of Financial Economics 13, no. 4 (December 1984): 509-28.

Multifactor Asset Pricing Model and Value Effect

Eugene Fama and Kenneth French,University of Chicago

Improves on the single-factor asset pricing model (CAPM).

Identifies market, size, and “value” factors in returns.

Develops the three-factor asset pricing model, an invaluable asset allocation and portfolio analysis tool.

“Common Risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics 33, no. 1 (February 1993): 3-56.

Database of Securities Prices since 1926

Roger Ibbotson andRex Sinquefield,Stocks, Bonds, Bills, and Inflation

An extensive returns database for multiple asset classes is first developed and will become one of the most widely used investment databases.

The first extensive, empirical basis for making asset allocation decisions changes the way investors build portfolios.

A Major Plan First Commits to Indexing

New York Telephone Companyinvests $40 million in an S&P 500Index fund.

The first major plan to index.

Helps launch the era of indexed investing.

“Fund spokesmen are quick to point out you can’t buy the market averages. It’s time the public could.”

Burton G. Malkiel, A Random Walk Down Wall Street, 1973 ed.

International Size Effect

Steven L. Heston, K. Geert Rouwenhorst, and Roberto E. Wessels

Find evidence of higher average returns to small companies in twelve international markets.

“The Structure of International Stock Returns and the Integration of Capital Markets,” Journal of Empirical Finance 2, no. 3 (September 1995): 173-97.

The Size Effect

Rolf Banz, University of Chicago

Analyzed NYSE stocks,1926-1975.

Finds that, in the long term, small companies have higher expected returns than large companies and behave differently.

Integrated Equity

Eugene F. Fama and Kenneth R. French

Increasing exposure to small and value companies relative to their market weights and integrating the portfolio across the full range of securities may reduce the turnover and transaction costs normally associated with forming an asset allocation from multiple components.

“Migration,” CRSP Working Paper No. 614, Center for Research in Security Prices, University of Chicago, February 2007.

Innovations in Finance

S1630.2

Value Added: Efficient Market Investing

Asset Class Management

•Grounded in the efficiency of capital markets.

•Captures specific dimensions of risk identified by academic research.

•Minimizes transaction costs and enhances returns through trading and engineering.

Active Management

•Attempts to beat the market through security selection and market timing.

•Undermines asset class exposure to keep up with the most “promising” securities.

•Generates higher fees, trading costs, and tax consequences due to increased turnover.

Index Management

•Accepts asset class returns.

• Allows commercial benchmarks to define strategy.

•Sacrifices transaction costs and turnover in favor of tracking.

• Markets work. Capital markets do a good job of fairly pricing all available information and investor expectations about publicly traded securities.

• Diversification is key. Comprehensive, global asset allocation can neutralize the risks specific to individual securities.

• Risk and return are related. The compensation for taking on increased levels of risk is the potential to earn greater returns.

• Portfolio structure explains performance. The asset classes that comprise a portfolio and the risk levels of those asset classes are responsible for most of the variability of portfolio returns.

S1810.3

Principles

Evaluating the Maturity Risk/Return Tradeoff Quarterly: 1964–2010

Source: One-Month US Treasury Bills, Five-Year US Treasury Notes, and Twenty-Year (Long-Term) US Government Bonds provided by Ibbotson Associates. Six-Month US Treasury Bills provided by CRSP (1964-1977) and B of A Merrill Lynch (1978-present). One-Year US Treasury Notes provided by CRSP (1964-May 1991) and B of A Merrill Lynch (June 1991-present). Ibbotson data © Stocks, Bonds, Bills, and Inflation Yearbook™, Ibbotson Associates, Chicago (annually updated work by Roger G. Ibbotson and Rex A. Sinquefield). CRSP data provided by the Center for Research in Security Prices, University of Chicago. The Merrill Lynch Indices are used with permission; copyright 2011 B of A Merrill Lynch, Pierce, Fenner & Smith Incorporated; all rights reserved.Indexes are not available for direct investment. Index performance does not reflect expenses associated with the management of an actual portfolio. Past performance is not a guarantee of future results. Values change frequently and past performance may not be repeated. There is always the risk that an investor may lose money. Fixed income securities are subject to interest rate risk because the prices of fixed income securities tend to move in the opposite direction of interest rates. In general, fixed income securities with longer maturities are more sensitive to these price changes and may experience greater fluctuation in returns.

S1840.7

• Not all investors define risk as standard deviation. Some investors may seek to hedge long-term liabilities using long-term bonds.

• Historically, longer-maturity instruments have higher standard deviations than shorter-maturity instruments.

0

2

4

6

8

10

12

Annualized Compound Returns

Annualized Standard Deviation

Maturity

One-Month US Treasury

Bills

Six-Month US Treasury

Bills

One-Year US Treasury

Notes

Five-Year US Treasury

Notes

Twenty-Year US Govt.

Bonds

Annualized Compound Return (%) 5.45 6.20 6.41 7.27 7.37

Annualized Standard Deviation (%) 1.42 1.77 2.34 6.21 11.29

S2000.5

Copyright MSCI 2011. Unpublished. All rights reserved. This information may only be used for your internal use, may not be reproduced or redisseminated in any form and may not be used to create any financial instruments or products or any indices. This information is provided on an “as is” basis and the user of this information assumes the entire risk of any use it may make or permit to be made of this information. Neither MSCI, any of its affiliates, nor any other person involved in or related to compiling, computing or creating this information makes any express or implied warranties or representations with respect to such information or the results to be obtained by the use thereof, and MSCI, its affiliates, and each such other person hereby expressly disclaims all warranties (including, without limitation, all warranties of originality, accuracy, completeness, timeliness, non-infringement, merchantability and fitness for a particular purpose) with respect to this information. Without limiting any of the foregoing, in no event shall MSCI, any of its affiliates or any other person involved in or related to compiling, computing, or creating this information have any liability for any direct, indirect, special, incidental, punitive, consequential, or any other damages (including, without limitation, lost profits) even if notified of, or if it might otherwise have anticipated, the possibility of such damages.

MSCI Disclosure

The Power of Economic Science

Economy & Finance

Transcript of The Power of Economic Science