Post on 12-Nov-2014
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• 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.
Value
Large
Small
Growth
Increased RiskExposure andExpected Return
TotalStockMarket
Decreased Risk Exposure and
Expected Return
Dimensions of Stock Returns around the World
Risk and Return Are Related
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. ©2012 by Dimensional Fund Advisors. All rights reserved.
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Precision in Portfolios
• Traditionally, “products” have been classified into rigid and sometimes arbitrary categories.
• Style boxes force crude strategic allocation.
• Using the three-factor model, the total portfolio is measured by factors that determine risk and expected return.
• Freedom from brittle definitions allows precisely tuned portfolios.
RR1250.2
Traditional Consulting Style Box
Large
Mid
SmallValue Blend Growth
Three-Factor Model Small
Growth Value
Large
3
Integrated Solutions Reduce Turnover
Annual: January 1989–December 2012.Russell components are Russell indices weighted according to Russell 3000 market value weights (buys and sells measured by the weight of each component).Estimated annual cost assumes transaction costs of 50 bps. Russell data copyright ©Russell Investment Group 1995-2013, all rights reserved.For illustrative purposes only.
• In effect, a component portfolio buys and sells from itself, generating needless costs and taxable events.
IC1450.7
R3000
3.4%
27.1%
33.5%
Russell 3000via ComponentsRussell 3000
Buys and Sells in Excess of Russell 3000
R2000
R1000
R2000G R2000V
R1000G R1000V
R200G R200V
R2000G R2000V
RMCG RMCV
4
Advancements in Research
Size
Small
Large
Relative Price
HighLow
Value Effect(1991)
Market
Single-Factor Model(1963) Size
Large
Small
Size Effect(1981)
Size
Large
Large
Small
Small High
Low
High
Low
Direct Profitability
Relative Price
HighLow
Expected Profitability (2012)
RR1255.1
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Annual Index Reconstitution EffectsConsistency of Asset Class Exposure
Month-end values from January 2004-December 2012. Russell data copyright © Russell Investment Group 1995-2013, all rights reserved. CRSP data provided by the Center for Research in Security Prices, University of Chicago. 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.
• Over time, securities within an index can migrate from one asset class to another (such as from small cap to large cap)
• An index’s characteristics may be significantly different 11 months after reconstitution due to security migration.
• An index that purports to represent a certain asset class may not offer thorough, consistent exposure to the underlying risk factors.
LI1770.5
Percentage of Assets in Bottom 10% of Market
Russell 2000 Index
CRSP 6-10Index
June 30 Averages(reconstitution month) 96.30 96.61
May 31 Averages(11 months after reconstitution) 88.42 97.24
Jan 2004 Jan 2005 Jan 2006 Jan 2007 Jan 2008 Jan 2009 Jan 2010 Jan 2011 Jan 2012 Jan 201380%
85%
90%
95%
100%
CRSP 6-10 IndexRussell 2000 Index
Per
cent
age
of A
sset
s in
Bot
tom
10%
of M
arke
t
Structure Determines Performance
• The vast majority 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
Structured Exposure to Factors explain 96% of return variation
Unexplained Variation is 4%
• Market• Size• Value/Growth
THE MODEL TELLS THE DIFFERENCE BETWEEN INVESTING AND SPECULATING
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Total Equity Risk
Company Risk
Industry Risk
Market Risk
Unsystematic
Systematic
Capital Asset Pricing ModelWilliam Sharpe: Nobel Prize in Economics, 1990
Beta measures volatility relative to the total market. A beta higher than the market’s beta of 1 implies more volatility, and a beta lower than the market’s implies less volatility.
Unsystematic
• Specific to firm or industry (lawsuit, fraud, etc.)
• Diversifiable
• No compensation
Systematic
• Marketwide, affects all firms (war, recession, inflation, etc.)
• Non-diversifiable
• Investor compensation
• Measured by beta
RR1210.2
Dimensions of Higher Expected Returns
1. Credit premium data (1973–2012) provided by Barclays Bank PLC.Indices are not available for direct investment. Their performance does not reflect the expenses associated with the management of an actual portfolio.Equity premiums provided by Fama/French. Maturity premium data provided by © Stocks, Bonds, Bills, and Inflation Yearbook©, Ibbotson Associates, Chicago (annually updated work by Roger G. Ibbotson and Rex A. Sinquefield).
Annual Average US Premiums: 1927–2012
1 2 3 4 5
8.05%
3.58%
4.80%
2.52%
0.85%
Market PremiumAll Equity Universe
minus T-Bills
Size Premium
Small Stocks minus
Large Stocks
BtM PremiumHigh BtM
minus Low BtM
Maturity PremiumLT Govt.
minus T-Bills
Credit1 PremiumInt. Corp.
minusLT Govt.
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VALUE MINUS GROWTHTop 30% – Bottom 30%
SMALL MINUS LARGEBottom 50% – Top 50%
Average Premium (%)
Standard Deviation (%)
Average Premium (%)
Standard Deviation (%)
Jan 1926–Dec 2012 4.77 16.60 4.53 16.08
Jan 1946–Dec 2012 4.56 13.83 3.04 13.67
Jan 1975–Dec 2012 3.55 14.53 3.35 12.83
Historical US Value and Small Cap Premiums
Data provided by Fama/French.
Annual
RR1221.5
The Risk Dimensions Delivered
Periods based on rolling annualized returns. 739 total 25-year periods. 799 total 20-year periods. 859 total 15-year periods. 919 total 10-year periods. 979 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.
July 1926–December 2012
RR1271.5
Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 99% of the time.
Value beat growth 96% of the time.
Value beat growth 86% of the time.
US Value vs. US GrowthOVERLAPPING PERIODS
In 5-Year Periods
In 10-Year Periods
In 15-Year Periods
In 20-Year Periods
In 25-Year PeriodsValue beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 95% of the time.
Value beat growth 91% of the time.
Value beat growth 80% of the time.
US Small vs. US Large
Small beat large 97% of the time.
Small beat large 88% of the time.
Small beat large 82% of the time.
Small beat large 75% of the time.
Small beat large 60% of the time.
The Risk Dimensions Delivered
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: 157 overlapping 25-year periods. 217 overlapping 20-year periods. 277 overlapping 15-year periods. 337 overlapping 10-year periods. 397 overlapping 5-year periods. International Small vs. International Large data: 217 overlapping 25-year periods. 277 overlapping 20-year periods. 337 overlapping 15-year periods. 397 overlapping 10-year periods. 457 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 2013, all rights reserved.
RR1271.5
International Small vs. International Large
Small beat large 100% of the time.
Small beat large 97% of the time.
Small beat large 83% of the time.
Small beat large 80% of the time.
Small beat large 79% of the time.
Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 98% of the time.
International Value vs. International GrowthOVERLAPPING PERIODS
In 5-Year Periods
In 10-Year Periods
In 15-Year Periods
In 20-Year Periods
In 25-Year Periods Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 100% of the time.
Value beat growth 96% of the time.
January 1975–December 2012 January 1970–December 2012
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Performance of the S&P 500 Index
Performance data for January 1970-August 2008 provided by CRSP; performance data for September 2008-December 2012 provided by Bloomberg. The S&P data are provided by Standard & Poor’s Index Services Group. US bonds and bills data © Stocks, Bonds, Bills, and Inflation Yearbook™, Ibbotson Associates, Chicago (annually updated work by Roger G. Ibbotson and Rex A. Sinquefield). 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.
Daily: January 1, 1970-December 31, 2012
LT1330.9
Total Period Missed 1 Best Day
Missed 5 Best Single Days
Missed 15 Best Single Days
Missed 25 Best Single Days
One-Month US T-Bills
Annualized Compound Return 9.94% 9.66% 8.84% 7.47% 6.33% 5.30%
$58,769
$52,702
$38,212
$22,191
$13,999
$9,195
Gro
wth
of $
1,00
0
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Perils of Market Timing
Returns are from market-close to market-close. Indices are not available for direct investment; their performance does not reflect the expenses associated with the management of an actual portfolio. The S&P data are provided by Standard & Poor’s Index Services Group. Dow Jones data provided by Dow Jones Indexes. Russell data copyright © Russell Investment Group 1995-2010 all rights reserved. Mutual fund universe statistical data and non-Dimensional money managers’ fund data provided by Morningstar, Inc. Nasdaq Composite Index data provided by The Nasdaq Stock Market, Inc. KBW Bank Index data provided by Keefe, Bruyette & Woods, Inc. (KBW). Past performance is not a guarantee of future results.
A Case Study of Q1 2009
LT1394.3
-12.4%
-24.7%
16.4%
-11.0%
-24.6%
18.1%
-14.9%
-31.0%
23.4%
-2.7%
-19.3%
20.5%
-35.8%
-55.3%
43.8%
Dow Jones Industrial Average
S&P 500 Index
Russell 2000 Index
Nasdaq Composite Index
KBW Bank Index
Negative Return Period1/1-3/9
Q1 2009 Returns1/1-3/31
Positive Return Period
3/10-3/31
• March 9 was the low closing date for four of the five featured indices year-to-date.
• The Dow Jones Industrial Average rose 5.8% on March 10, 2009.
• Looking at daily returns, it’s difficult to tell if a recovery is occurring.
Return excluding March 10, 2009
9.6%
6.3%
-0.6%
All US Stocks Excluding the Top 10% of Performers
Each Year
Excluding the Top 25%of Performers
Each Year
Compound Average Annual Returns: 1926-2012
Missing Opportunity
Results based on the CRSP 1-10 Index. CRSP data provided by the Center for Research in Security Prices, University of Chicago.
• Strong performance among a few stocks accounts for much of the market’s return each year.
• There is no evidence that managers can identify these stocks in advance—and attempting to pick them may result in missed opportunity.
• Investors should diversify broadly and stay fully invested to capture expected returns.
LT1395.5