This research paper discusses enhancing value investment strategies by incorporating expected profitability. For small cap value strategies, the paper proposes excluding stocks in each country with the lowest direct profitability, with the percentage excluded depending on the stock's price-to-book ratio. For large cap value strategies, the paper suggests selecting stocks based on both low price-to-book ratios and high direct profitability. It also proposes overweighting stocks that have higher profitability, lower market capitalization, and lower relative price. The goal is to structure portfolios to better capture the dimensions of expected returns related to company size, relative price, and expected profitability, while maintaining appropriate diversification and managing costs.

1. SECOND QUARTER 2013 | PART TWO
RESE ARCH UPDATE
Applying Direct
Profitability to Value Stocks
A value strategy systematically improves expected
returns by selecting only firms with low price-to-book
ratios, but a value strategy can further increase its
expected return by considering market capitalization
and direct profitability when selecting low relative
price securities.
This paper shows (1) how expected profitability
can enhance a value strategy that uses only relative
price and company size to select securities, and
(2) how security weighting schemas can be used
to integrate the three equity dimensions of expected
returns into a value strategy’s structure to increase
the reliability of expected outperformance
vs. conventional benchmarks.
Gerard O’Reilly, PhD
Head of Research
and Vice President
Dimensional Fund Advisors
Savina Rizova, PhD
Vice President
Dimensional Fund Advisors
Lukas Smart
Portfolio Manager
Dimensional Fund Advisors
Beginning on page 3
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2. What drives risk premiums?
The risk premium E(Rei) [of any asset] is driven by the covariance of returns with the
marginal value of wealth. Given that an asset must do well sometimes and badly at other
times, investors would rather it did well when they are otherwise desperate for a little bit of
extra wealth, and that it did badly when they do not particularly value extra wealth. Thus,
investors want assets whose payoffs have a positive covariance with hunger, and they will
avoid assets with a negative covariance. Investors will drive up the prices and drive down
the average returns of assets that covary positively with hunger, and vice versa, generating
the observed risk premia.
These predictions are surprising to newcomers for what they do not say. More volatile
assets do not necessarily generate a higher risk premium. The variance of the return Rei or
payoff xi is irrelevant per se and does not measure risk or generate a risk premium. Only
the covariance of the return with “hunger” matters.
—John H. Cochrane
“Financial Markets and the Real Economy,”
in Handbook of the Equity Risk Premium,
ed. Rajnish Mehra (Amsterdam: Elsevier, 2007), 237–325.

3. R E SE A R CH U PDATE
Using the direct profitability measure developed by
Dimensional Fund Advisors,1 this is the second in a series
of papers that explores the potential value added from
incorporating the expected profitability dimension into
investment strategies.2 In this paper, we examine how
profitability could be applied to small and large cap value
strategies in developed markets.
IMPROVING EXPECTED RETURNS:
VALUE STRATEGIES
Equity portfolio design can be broadly divided into two steps:
(1) finding the dimensions that determine expected returns
and (2) structuring portfolios to capture those dimensions.
A dimension of expected return identifies differences in
expected return. It should be sensible, persistent across time,
pervasive across markets, robust to alternative specifications,
and cost effective to capture in a well-diversified portfolio.
Good portfolio structure should (a) select and/or weight
stocks to continually and accurately target the dimensions
of expected returns, (b) integrate known dimensions of
expected returns to seek to increase the reliability of expected
outperformance vs. benchmarks, (c) maintain appropriate
diversification to control risk and allow for effective execution,
and (d) minimize unnecessary turnover.
Relative price is widely recognized as a dimension of expected
return. A lot of academic research shows that average returns
on stocks are inversely related to measures of relative price
such as price-to-book ratios. For example, from January 1927
to December 2012, US large cap value stocks outperformed
US large cap growth stocks by an average of 3.7% per year.
The t-statistic of the return difference was 2.1. In Table 1, we
present similar outcomes for US small caps and developed
market large and small caps.
Table 1
Value vs Growth, Annual Returns
Value Growth Difference
t-stat
United States Large
1927-2012
14.96
11.23
3.73
2.11
United States Small
1927-2012
19.13
13.25
5.87
3.37
Developed ex US Large
1981-2012
16.69
10.21
6.47
3.18
Developed ex US Small
1981-2012
17.14
12.81
4.33
1.90
Past performance is no guarantee of future results. Source: US large and
small value and growth indices are the Fama/French research indices.
Non-US developed value and growth indices are the Fama/French
international indices. Developed ex US small indices are Dimensional
indices (Dimensional International Small Cap Value Index and
Dimensional International Small Cap High Price-to-Book Index).
Motivated by this research, value strategies seek to
systematically improve expected returns by selecting firms
with low price-to-book ratios. But, within equities, there
are two other dimensions of expected returns in addition to
relative price—company size and expected profitability. A
value strategy could further pursue increased expected returns
by considering market capitalization and direct profitability
when selecting low relative price securities.3
Value (or any other equity investment) strategies can be
designed to focus on selection alone, or on both selection and
weighting. In this paper, we show how expected profitability
could enhance a value strategy that uses only relative price
and company size to select securities. We also show how
security weighting schemas could be used to integrate all
three dimensions of expected equity returns into a value
strategy’s structure to help increase expected outperformance
versus conventional benchmarks.
The paper is organized as follows. First, we describe general
diversification considerations that should be made when
selecting securities to include in a value strategy. Next, we
show how the security selection process could be used to
integrate direct profitability into developed market small cap
value strategies. We follow with developed market large cap
value strategies and show how they could be enhanced by
applying direct profitability to both security selection and
weighting. The different approach between small and large
caps used in this paper is primarily caused by differences in
trading costs between small and large cap stocks. The last
section of the paper presents results.
DIVERSIFICATION CONSIDERATIONS
IN SECURITY SELECTION
There are many aspects of diversification: security, sector, and
country. A value strategy should use the security selection
process to emphasize each aspect. Diversification helps
reduce uncertainty and control risk. It also affords portfolio
managers and traders flexibility that can be used for effective
implementation. For example, portfolio managers could use
this flexibility to balance competing premiums while they focus
on the dimensions of expected returns. Traders could trade
patiently to add value with respect to peers and benchmarks.
For a portfolio to be considered well diversified across
securities, it should include both a meaningful percentage of
aggregate market capitalization and an appropriate number of
firms. For example, value strategies should use price-to-book,
market capitalization, and direct profitability slices that are
designed to account for this goal. These well-designed slices
can be combined with individual security caps to help ensure
a value portfolio remains diversified across securities. Security
3

4. R E SE A R CH U PDATE
caps can be absolute or relative to a security’s market cap
weight in the total eligible market.
To achieve broad sector diversification while preserving the
benefits of sector rotation, a security selection process can
use dynamic sector caps that are relative to each sector’s
weight in the eligible market.4 After sorting eligible stocks
on their price-to-book ratios, we can compute the sector
weights of the stocks in the lowest price-to-book slice. For
sectors that are overweight by more than 10%, their priceto-book breakpoints can be reduced until the weight of
each overweight sector is its market weight plus 10%. This
approach would decrease the number of securities in the
overweight sectors so that only the very lowest price-to-book
securities in those sectors are included. Because it also reduces
the percentage of market cap included in the value strategy,
the price-to-book breakpoints of the underweight sectors
should be increased (making additional securities eligible)
until the same percentage of market cap as the original priceto-book slice is included. This last step helps preserve security
diversification while enforcing broad sector diversification.
Next, for each country, we exclude firms with the lowest direct
profitability. The fraction of market cap excluded is related to
the price-to-book ratio. For firms with very low price-to-book
ratios (relative to the small value universe in that country), a
smaller percentage of low profitability stocks are excluded.
For small value firms with higher relative price-to-book ratios
(those close to the upper price-to-book breakpoint), larger
percentages of low profitability firms are excluded.
Figure 1 illustrates the application of this approach. For firms
in the lowest 30% of the price-to-book rankings, those that are
also in lowest 10% of the market cap of all small value when
ranked by direct profitability are excluded. For firms in the
next 5% of the price-to-book ranking (between 30% and 35%),
those that are also in the lowest 50% of the market cap of all
small value when ranked on direct profitability are excluded.
Figure 1
Applying Profitability to
Developed Market Small Cap Value Stocks
Finally, for multi-country value strategies, the price-to-book,
market capitalization, and direct profitability slices should
target a similar percentage of aggregate market capitalization
in each country. Consequently, country weights will naturally
be similar to their weights in the total eligible market.
4
Size
LARGE
HIGH
Stocks
below
10%–12.5%
market cap
limit by
common
currency
Stocks with
lowest 35%
of P/B ratios
DIRECT PROFITABILITY AND SMALL CAP VALUE
Relative Price
LOW
HIGH
LOWEST
LOW
Expected Profitability
For the purposes of this paper, to integrate direct profitability
into a small value strategy, we begin by selecting securities
that represent the small cap value universe. We define small
cap stocks as those with the smallest market capitalization
in the eligible equity universe whose aggregate market
capitalization represents 10%–12.5% of the market.5 We then
define small cap value stocks as small cap stocks whose priceto-book ratios rank in the lowest 35% of aggregate market cap
of the eligible small cap universe. The price-to-book rankings
are done separately for each country. This approach seeks
to control for country-specific differences in accounting
standards. It also promotes country diversification, as the
country weights in the value strategy will be similar to their
weights in the total eligible universe.
Relative Price
SMALL
The security selection framework described above
acknowledges that the market provides a consensus
view of global equilibrium tradeoffs of risk and return. Upto-the minute news and changes in expectations are reflected
in current prices and security, sector, and country weights. By
construction, this security selection process for value strategies
uses this information to control risk and ensure diversification.
LOW
Conceptual example, provided for informational purposes only.

5. R E SE A R CH U PDATE
Why exclude firms in this way? A value strategy should
be structured to target the value premium accurately. The
expected value premium is generally largest for the deepest
value firms. By applying a graded profitability exclusion,
a small value strategy could preserve its deep value focus
while incorporating the information in direct profitability
about expected returns. This approach can be a very effective
way to integrate expected profitability and relative price.
Research results indicate this increases expected returns and
the reliability of expected outperformance of small value
strategies vs. conventional benchmarks.
As mentioned previously, any value strategy should include
a meaningful percentage of aggregate market capitalization
to ensure diversification. That implies the direct profitability
exclusion cannot be too extreme. The methodology described
above targets approximately 25%–30% of the market
capitalization of eligible small caps in each country.
A small value strategy must continually balance the tradeoffs
among competing premiums, diversification, and costs.
Because small cap stocks can be costly to trade, in this paper
we weight firms in proportion to their market capitalization.
Once a basket of stocks has been selected for a small value
strategy, this weighting schema generally produces the lowest
turnover. By minimizing unnecessary turnover (i.e., turnover
that does not increase expected return) and spreading it
over all the trading days of the year, those tradeoffs can be
effectively managed.
The result is a small value strategy that uses a thoughtful
security selection process to balance the dimensions of
expected equity returns and help ensure all aspects of
diversification are preserved. This approach helps increase
the consistency of expected outperformance vs. benchmarks
and provides flexibility to efficiently manage costs. Investors
are well-positioned to capture the premiums associated
with the market, company size, relative price, and expected
profitability dimensions in a real-world small value portfolio.
DIRECT PROFITABILITY AND LARGE CAP VALUE
Large cap stocks tend to be more liquid and less expensive
to trade than small cap stocks. As a result, we can use both
selection and weighting approaches to help improve the
expected returns of a large cap value strategy.
For the purposes of this paper, we first select securities that
represent the large cap value universe. We define large cap
stocks as those with the largest market capitalization in the
eligible equity universe whose total market capitalization
ranks above the bottom 10%–12.5% of the market.6 Within
each country, we define large cap value stocks as large caps
whose price-to-book ratios rank in the lowest 30% of the
eligible large cap universe.
Next, for each country, we exclude certain firms based on
their direct profitability. Sorting large cap value stocks on
direct profitability, we identify those with the lowest direct
profitability that represent 25% of the aggregate market
capitalization of large cap value. Of these, we exclude stocks
that have the highest price-to-book ratios and are in the
lowest direct profitability quartile. Similar to our approach
with small value, the profitability exclusion is based on
price-to-book and direct profitability. In this way, the
security selection process preserves a deep value focus while
incorporating information about expected profitability.
Within this selection of large cap value stocks, we then apply
a weighting schema that emphasizes securities with higher
profitability, lower market capitalization, and lower relative
price. In a well-designed weighting schema, a security’s target
weight can deviate from its market cap weight to improve
expected strategy returns, but deviations should be measured
and controlled to avoid excessive turnover. To achieve those
goals, we make a security’s target weight proportional to its
market capitalization, with the level of over- or underweight
relative to the market weight being a function of direct
profitability, market cap, and price-to-book. The strategy
overweights securities with higher profitability, lower market
capitalization, and lower relative price, and underweights
securities with lower profitability, higher market capitalization,
and higher relative price.
As an example, let’s look at the US large value index presented
in the next section (US Large Low Relative Price with
Profitability Index). As a result of the tilt toward companies
with lower market capitalization, the average ratio of a firm’s
tilted weight to its weight based on market capitalization alone
is approximately 0.8 for the largest firms, which represent
50% of the index, and approximately 1.2 for the remaining
smaller firms, as of June 2013. Similarly, as a result of the tilt
5

6. R E SE A R CH U PDATE
toward companies with higher profitability, the average ratio
of target weight to market weight is approximately 1.3 for the
most profitable firms, which represent 50% of the index, and
approximately 0.7 for remaining lower profitability firms.
Figure 2 summarizes the combination of the selection and
weighting approaches in the design of a developed market
large cap value strategy.
Figure 2
Applying Profitability to
Developed Market Large Cap Value Stocks
We also cap security weights in our large cap value strategies.
Security caps build additional diversification considerations
into the weighting schema. They limit any single security’s
representation. A small cap value strategy tends to hold many
more names than a large cap value strategy; consequently,
while security caps can be applied in small value strategies,
they are generally less important.
Relative Price
HIGH
Size
LARGE
LOW
SMALL
Stocks
above
10%–12.5%
market
cap limit
Stocks with lowest
30% of P/B ratios
Expected
Profitability
HIGH
MID
Size
MEGA
LOW
LOWEST
LOW
Relative Price
Conceptual example, provided for informational purposes only.
6
A large cap value strategy should also continually balance
the tradeoffs among competing premiums, diversification,
and costs. Large cap value stocks are less costly to trade;
therefore, we use a weighting schema that deviates from
market cap weights to emphasize company size and expected
profitability. This approach helps increase the expected return
and the consistency of outcomes. Because a firm’s target
weight remains strongly linked to its market capitalization,
unnecessary turnover is minimized and risk is controlled by
reflecting up-to-the minute news in target weights.
The result is a large value strategy that uses a thoughtful security
selection and weighting process to balance the dimensions
of expected equity returns and help ensure all aspects of
diversification are preserved. Investors are well-positioned to
capture the premiums associated with the market, company
size, relative price, and expected profitability dimensions in a
real-world large value portfolio.

7. R E SE A R CH U PDATE
EMPIRICAL RESEARCH
In this section, we explore the potential value added from
focusing on all three dimensions of expected equity returns
in value strategies. We begin with US small and large value.
Tables 2A and 2B report the performance of US value indices
constructed based on the methodology described above (US
Small Low Relative Price with Profitability Index and US
Large Low Relative Price with Profitability Index), as well as
the performance of market-cap weighted small and large cap
value indices that include all stocks with price-to-book ratios
in the bottom 25% of the eligible size universe (US Small
Low Relative Price Index and US Large Low Relative Price
Index). The low relative price indices in Tables 2A and 2B
are rebalanced annually. For comparison purposes, we also
report the historical performance of the Russell indices.7
Table 2A
US Small Cap Value Indices with and without Profitability, 1979-2012
US Small
Low Relative
Price Index
US Small Low
Relative Price with
Profitability Index
Russell 2000
Value Index
Russell
2000 Index
17.47
17.90
13.18
11.35
4.30
4.72
—
—
Annualized Average Return
18.35
18.48
14.05
12.84
Annualized Standard Deviation
20.63
19.41
17.67
19.93
t-Stat of Monthly Return Difference
(vs. Russell 2000 Value)
3.55
4.63
—
—
Annualized Tracking Error
(vs. Russell 2000)
8.73
8.30
5.96
Annualized Tracking Error
(vs. Russell 2000 Value)
7.06
5.59
—
1979-2012
Annualized Compound Return
Relative Premium
(vs. Russell 2000 Value)
—
Past performance is no guarantee of future results. Source: Compiled by Dimensional using CRSP and Compustat data. CRSP data provided by the Center for
Research in Security Prices. See appendix for additional information on the Dimensional indices.
Table 2B
US Large Cap Value Indices with and without Profitability, 1979-2012
US Large Low
Relative Price Index
US Large Low
Relative Price with
Profitability Index
Russell 1000
Value Index
Russell 1000
Index
13.49
14.13
11.97
11.46
1.53
2.16
—
—
Annualized Average Return
14.24
14.80
12.49
12.13
Annualized Standard Deviation
17.29
17.25
14.95
15.60
t-Stat of Monthly Return Difference
(vs. Russell 1000 Value)
2.27
2.94
—
—
Annualized Tracking Error
(vs. Russell 1000)
6.76
7.02
4.86
Annualized Tracking Error
(vs. Russell 1000 Value)
4.49
4.57
—
1979-2012
Annualized Compound Return
Relative Premium
(vs. Russell 1000 Value)
—
Past performance is no guarantee of future results. Source: Compiled by Dimensional using CRSP and Compustat data. CRSP data provided by the Center for
Research in Security Prices. See appendix for additional information on the Dimensional indices.
7

8. R E SE A R CH U PDATE
From 1979 to 2012, the Russell 2000 earned an annualized
compound return of 11.4% vs. 13.2% for the Russell 2000
Value, 17.5% for the US Small Low Relative Price Index,
and 17.9% for the US Small Low Relative Price with
Profitability Index. By incorporating direct profitability
in the security selection process, the US Small Low Relative
Price with Profitability Index outperformed the US Small
Low Relative Price Index by approximately 0.4% per year.
The standard deviation of the US Small Low Relative Price
with Profitability Index was more than 1% lower than the US
Small Low Relative Price Index.
Looking at annual returns, the US Small Low Relative Price
with Profitability Index outperformed the Russell 2000 Value
Index in 27 of the 34 years from 1979 to 2012, while the US
Small Low Relative Price Index outperformed the Russell 2000
Value Index in 23 of the 34 years. Further, the t-statistic of the
US Small Low Relative Price with Profitability Index’s monthly
premium vs. the Russell 2000 Value was 4.63, compared with
3.55 for the US Small Low Relative Price Index. This increase
in the reliability of outperformance vs. the Russell 2000 Value
is attributed to adding expected profitability to the security
selection process. The market, size, and value coefficients
from a Fama/French three-factor regression are similar for the
US Small Cap Value Indices with and without Profitability.8
The HML coefficient was approximately 0.7 for the US Small
Cap Value Indices with and without Profitability. Hence, both
indices provide a similar focus on the size and value premiums.
We find similar results for US large caps. From 1979 to 2012,
the Russell 1000 earned an annualized compound return of
11.5% vs. 12.0% for the Russell 1000 Value, 13.5% for the US
Large Low Relative Price Index, and 14.1% for the US Large
Low Relative Price with Profitability Index. By focusing on all
three dimensions of expected equity returns when selecting
and weighting stocks, the US Large Low Relative Price with
Profitability Index outperformed the US Large Low Relative
Price Index by more than 0.6% per year. The higher average
returns were achieved with a very similar standard deviation.
The inclusion of direct profitability and market cap in the
index design also results in more reliable outperformance
relative to the Russell 1000 Value Index. The t-statistic of
the monthly premium increases from 2.27 to 2.94 when we
move from the US Large Low Relative Price Index to the
US Large Low Relative Price with Profitability Index. The
Fama/French three factor coefficients are very similar for
the low relative price indices with and without profitability
(approximately 0.6 for both).
8
Overall, Table 2 suggests that by consistently focusing on all
three dimensions of expected equity returns, we could (1)
improve the expected performance of a small or large cap
value strategy, (2) increase the consistency of their expected
outperformance relative to benchmarks, and (3) maintain
broad diversification.
Tables 3A and 3B illustrate that broad diversification. We
present the characteristics of the low relative price indices
along with the Russell indices as of June 2013. The value
indices that use direct profitability in their construction are
well diversified across securities and sectors. The aggregate
index characteristics illustrate how the low relative price
indices with profitability balance market cap, price-to-book,
and direct profitability.

9. R E SE A R CH U PDATE
Table 3A
Characteristics for US Small Cap Value Indices with and without Profitability
Data in USD as of 6/30/2013
Weighted Average Market Cap
US Small Low
Relative Price Index
US Small Low
Relative Price Index
with Profitability Index
Russell 2000
Value
Russell
2000
1,121
1,181
1,385
1,603
Aggregate Price-to-Book
0.92
1.03
1.33
1.85
Weighted Average Direct Profitability
0.15
0.18
0.16
0.22
Number of Securities
672
691
1,392
1,934
Consumer Discretionary
10.6
11.3
13.1
14.8
Consumer Staples
3.0
3.8
2.8
3.8
Energy
14.1
12.1
6.1
5.7
Financials
27.0
27.1
24.8
14.6
Health Care
5.4
4.9
4.5
12.6
Industrials
14.2
17.3
12.3
14.9
Information Technology
15.9
14.7
12.1
16.6
Materials
7.8
7.4
5.1
4.8
REITs
0.0
0.0
12.8
8.3
Telecommunication Services
1.1
1.1
0.5
0.7
Utilities
0.8
0.3
5.9
3.2
100.0
100.0
100.0
100.0
Total
Source: Compiled by Dimensional using CRSP and Compustat data. CRSP data provided by the Center for Research in Security Prices. See appendix for
additional information on the Dimensional indices.
Table 3B
Characteristics for US Large Cap Value Indices with and without Profitability
Data in USD as of 6/30/2013
Weighted Average Market Cap
US Large Low
Relative Price Index
US Large Low
Relative Price with
Profitability Index
Russell 1000
Value
Russell
1000
76,543
66,341
97,398
95,057
Aggregate Price-to-Book
1.16
1.25
1.49
2.09
Weighted Average Direct Profitability
0.19
0.22
0.24
0.35
Number of Securities
206
226
696
989
Consumer Discretionary
10.5
10.6
8.6
13.0
5.8
5.0
7.1
9.8
Energy
20.7
20.6
15.3
9.9
Financials
25.7
24.3
24.7
14.2
9.3
10.7
11.8
12.4
Consumer Staples
Health Care
Industrials
11.7
11.5
9.0
10.9
Information Technology
6.2
6.8
7.0
17.2
Materials
3.9
5.0
3.3
3.6
REITs
0.0
0.0
4.0
3.1
Telecommunication Services
5.6
5.1
3.0
2.7
Utilities
Total
0.6
0.4
6.3
3.4
100.0
100.0
100.0
100.0
Source: Compiled by Dimensional using CRSP and Compustat data. CRSP data provided by the Center for Research in Security Prices. See appendix for
additional information on the Dimensional indices.
9

10. R E SE A R CH U PDATE
Next, we analyze non-US developed market value indices.
Can we draw similar conclusions? Tables 4A and 4B say we
can. We compare the performance of non-US developed
market value indices that include direct profitability in
their security selection and/or weighting schemas (NonUS Developed Small Low Relative Price with Profitability
Index and Non-US Developed Large Low Relative Price
with Profitability Index) to the performance of market-cap
weighted value indices that include all stocks whose priceto-book ratios rank in the bottom 25% of the eligible size
universe in each developed market outside the US (NonUS Developed Small Low Relative Price Index and Non-US
Developed Large Low Relative Price Index). For reference,
we also report the historical performance of the MSCI World
ex US Small and Small Value Indices and the MSCI World ex
US Standard and Standard Value Indices.
These tables present data over the longest available
common time periods for the indices (for example, the
MSCI World ex USA Small Cap Index begins in 1999).
Compared with the US, we observe the same general pattern
of higher returns and higher t-statistics of the monthly
return difference vs. benchmarks for the low relative price
indices with profitability vs. those without profitability.
Comparing the low relative price indices with and without
profitability, we observe similar or lower standard deviations
and similar market, size, and value coefficients using Fama/
French developed ex US factors. The HML coefficient was
approximately 0.7 for the non-US developed small low
relative price indices with and without profitability and
approximately 0.5 for the US large low relative price indices
with and without profitability.
Tables 4A and 4B suggest that, by focusing on company size,
relative price, and expected profitability when selecting and
weighting securities for developed market small and large
cap value strategies, we can improve their expected returns
and the reliability of their expected outperformance vs.
conventional benchmarks.
Table 4A
Non-US Developed Small Cap Value Indices with and without Profitability
Non-US Developed
Small Low Relative
Price Index
Non-US Developed Small
Low Relative Price with
Profitability Index
12.05
12.37
9.65
8.26
2.40
2.71
—
—
Annualized Average Return
13.48
13.66
11.04
9.90
Annualized Standard Deviation
20.17
19.66
18.74
19.45
2.32
2.84
—
—
6.01
5.72
3.71
—
3.93
3.46
—
—
1999-2012
Annualized Compound Return
Relative Premium
(vs. MSCI Value)
t-Stat of Monthly Return Difference
(vs. MSCI Value)
Annualized Tracking Error
(vs. MSCI)
Annualized Tracking Error
(vs. MSCI Value)
MSCI World ex USA MSCI World ex USA
Small Cap Value
Small Cap Index
Index (gross div.)
(gross div.)
Past performance is no guarantee of future results. Source: Compiled by Dimensional using Bloomberg data. See appendix for additional information on the
Dimensional indices. MSCI data copyright MSCI 2013, all rights reserved.
10

11. R E SE A R CH U PDATE
Table 4B
Non-US Developed Large Cap Value Indices with and without Profitability
Non-US Developed
Large Low Relative
Price Index
Non-US Developed Large
Low Relative Price with
Profitability Index
Annualized Compound Return
8.07
8.80
7.48
6.13
Relative Premium
(vs. MSCI Value)
0.60
1.32
—
—
July 1991 - Dec 2012
Annualized Average Return
Annualized Standard Deviation
t-Stat of Monthly Return Difference
(vs. MSCI Value)
Annualized Tracking Error
(vs. MSCI)
Annualized Tracking Error
(vs. MSCI Value)
MSCI World ex USA
Value Index MSCI World ex USA
(gross div.)
Index (gross div.)
9.83
10.37
8.76
7.40
20.10
19.47
17.38
16.82
1.05
1.73
—
—
6.76
6.28
3.40
—
4.70
4.32
—
—
Past performance is no guarantee of future results. Source: Compiled by Dimensional using Bloomberg data. See appendix for additional information on the
Dimensional indices. MSCI data copyright MSCI 2013, all rights reserved.
CONCLUSION
When designing investment solutions, it is important to
remember that prices are a reliable source of information,
and structure and implementation drive performance.
Our analysis illustrates how an investor might use direct
profitability to enhance expected returns when selecting
securities for small or large value strategies. Further, our
analysis shows how to integrate company size and expected
profitability when weighting securities in large value
strategies. These examples show how portfolio structure
can be used to accurately target the dimensions of higher
expected returns.
In this paper, our analysis also considers implementation. The
security selection process helps ensure broad diversification
across securities, sectors, and countries. To reduce expected
costs, we choose to market-cap weight the small cap value
strategies. For large cap value strategies, we deviate from
market weights to increase expected returns, but we use a
measured, controlled, low-turnover weighting schema that
incorporates current price. Low turnover combined with
broad diversification allow for disciplined yet flexible and
patient portfolio management and trading processes that
control implementation costs.
Such solutions would seek to add value for investors across all
aspects of the investment process.
11

12. A PPE N D I X
APPENDIX
US Large Low Relative Price Index: This index was created
by Dimensional in July 2013 and is compiled by Dimensional
from CRSP and Compustat. It focuses on large cap value
companies. Large cap companies are generally defined as the
top 90% of the eligible market. Large cap value companies
are defined as large cap companies whose relative price is in
the bottom 25% of the large cap market after the exclusion
of utilities, companies lacking financial data, and companies
with negative relative price. The eligible market is composed
of securities of US companies traded on the NYSE, AMEX,
and Nasdaq Global Market. Exclusions: Non-US companies,
REITs, UITs, and investment companies. The index is
rebalanced annually and backtested performance results
assume reinvestment of dividends and capital gains. Filters
were applied to data retroactively and with the benefit of
hindsight. Returns are not representative of actual portfolios
and do not reflect costs and fees associated with an actual
investment. Actual returns may be lower. It is not possible to
invest directly in an index, which is unmanaged.
US Large Low Relative Price with Profitability Index:
This index was created by Dimensional in July 2013 and
is compiled by Dimensional from CRSP and Compustat.
It focuses on large cap value companies and overweights
higher expected return securities (higher profitability,
lower relative price, and lower market cap). Large cap
companies are generally defined as the top 90% of the eligible
market. Large cap value companies are defined as large cap
companies whose relative price is in the bottom 30% of the
large cap market after the exclusion of utilities, companies
lacking financial data, and companies with negative relative
price. Profitability is measured as operating income before
depreciation and amortization minus interest expense scaled
by book. The eligible market is composed of securities of US
companies traded on the NYSE, AMEX, and Nasdaq Global
Market. Exclusions: Non-US companies, REITs, UITs, and
investment companies. The index is rebalanced annually
and backtested performance results assume reinvestment
of dividends and capital gains. Filters were applied to data
retroactively and with the benefit of hindsight. Returns are
not representative of actual portfolios and do not reflect costs
and fees associated with an actual investment. Actual returns
may be lower. It is not possible to invest directly in an index,
which is unmanaged.
US Small Low Relative Price Index: This index was created
by Dimensional in July 2013 and is compiled by Dimensional
from CRSP and Compustat. It focuses on small cap value
companies. Small cap companies are generally defined as the
bottom 10% of the eligible market. Small cap value companies
12
are defined as small cap companies whose relative price is in
the bottom 25% of the small cap market after the exclusion
of utilities, companies lacking financial data, and companies
with negative relative price. The eligible market is composed
of securities of US companies traded on the NYSE, AMEX,
and Nasdaq Global Market. Exclusions: Non-US companies,
REITs, UITs, and investment companies. The index is
rebalanced annually and backtested performance results
assume reinvestment of dividends and capital gains. Filters
were applied to data retroactively and with the benefit of
hindsight. Returns are not representative of actual portfolios
and do not reflect costs and fees associated with an actual
investment. Actual returns may be lower. It is not possible to
invest directly in an index, which is unmanaged.
US Small Low Relative Price with Profitability Index:
This index was created by Dimensional in July 2013 and
is compiled by Dimensional from CRSP and Compustat.
It focuses on small cap value companies and excludes
companies with low profitability. Small cap companies
are generally defined as the bottom 10% of the eligible
market. Small cap value companies are defined as small cap
companies whose relative price is in the bottom 35% of the
small cap market after the exclusion of utilities, companies
lacking financial data, and companies with negative relative
price. Profitability is measured as operating income before
depreciation and amortization minus interest expense scaled
by book. The eligible market is composed of securities of US
companies traded on the NYSE, AMEX, and Nasdaq Global
Market. Exclusions: Non-US companies, REITs, UITs, and
investment companies. The index is rebalanced annually
and backtested performance results assume reinvestment
of dividends and capital gains. Filters were applied to data
retroactively and with the benefit of hindsight. Returns are
not representative of actual portfolios and do not reflect costs
and fees associated with an actual investment. Actual returns
may be lower. It is not possible to invest directly in an index,
which is unmanaged.
Non-US Developed Large Low Relative Price Index:
This index was created by Dimensional in July 2013 and is
compiled by Dimensional from Bloomberg securities data. It
focuses on large cap value companies in non-US developed
markets. Large cap companies are generally defined as the
top 87.5% of the eligible market in each country. Value
breaks are formed by country on the bottom 25% of large
companies ranked on relative price after the exclusion of
utilities, companies lacking financial data, and companies
with negative relative price. Maximum index weight of
any one company is capped at 5%. Countries included are
Australia, Austria, Belgium, Canada, Denmark, Finland,

13. A PPE N D I X
France, Germany, Greece, Hong Kong, Ireland, Italy, Japan,
Netherlands, New Zealand, Norway, Portugal, Singapore,
Spain, Switzerland, Sweden, and United Kingdom. The
index excludes REITs. The index is rebalanced semiannually
and backtested performance results assume reinvestment
of dividends and capital gains. Filters were applied to data
retroactively and with the benefit of hindsight. Returns are
not representative of actual portfolios and do not reflect costs
and fees associated with an actual investment. Actual returns
may be lower. It is not possible to invest directly in an index,
which is unmanaged.
Non-US Developed Large Low Relative Price with
Profitability Index: This index was created by Dimensional
in July 2013 and is compiled by Dimensional from
Bloomberg securities data. It focuses on large cap value
companies in non-US developed markets and overweights
higher expected return securities (higher profitability, lower
relative price, and lower market cap). Large cap companies
are generally defined as the top 87.5% of the eligible market
in each country. Value breaks are formed by country on the
bottom 30% of large companies ranked on relative price after
the exclusion of utilities, companies lacking financial data,
and companies with negative relative price. Profitability
is measured as operating income before depreciation
and amortization minus interest expense scaled by book.
Maximum index weight of any one company is capped at 5%.
Countries included are Australia, Austria, Belgium, Canada,
Denmark, Finland, France, Germany, Greece, Hong Kong,
Ireland, Italy, Japan, Netherlands, New Zealand, Norway,
Portugal, Singapore, Spain, Switzerland, Sweden, and
United Kingdom. The index excludes REITs. The index is
rebalanced semiannually and backtested performance results
assume reinvestment of dividends and capital gains. Filters
were applied to data retroactively and with the benefit of
hindsight. Returns are not representative of actual portfolios
and do not reflect costs and fees associated with an actual
investment. Actual returns may be lower. It is not possible to
invest directly in an index, which is unmanaged.
Australia, Austria, Belgium, Canada, Denmark, Finland,
France, Germany, Greece, Hong Kong, Ireland, Italy, Japan,
Netherlands, New Zealand, Norway, Portugal, Singapore,
Spain, Switzerland, Sweden, and United Kingdom. The
index excludes REITs. The index is rebalanced semiannually
and backtested performance results assume reinvestment
of dividends and capital gains. Filters were applied to data
retroactively and with the benefit of hindsight. Returns are
not representative of actual portfolios and do not reflect costs
and fees associated with an actual investment. Actual returns
may be lower. It is not possible to invest directly in an index,
which is unmanaged.
Non-US Developed Small Low Relative Price with
Profitability Index: This index was created by Dimensional
in July 2013 and is compiled by Dimensional from Bloomberg
securities data. It focuses on small cap value companies
and excludes companies with low profitability. Small cap
companies are generally defined as the bottom 12.5% of the
eligible market in each country. Value breaks are formed
by country on the bottom 35% of small companies ranked
on relative price after the exclusion of utilities, companies
lacking financial data, and companies with negative relative
price. Profitability is measured as operating income before
depreciation and amortization minus interest expense scaled
by book. Maximum index weight of any one company is
capped at 5%. Countries included are Australia, Austria,
Belgium, Canada, Denmark, Finland, France, Germany,
Greece, Hong Kong, Ireland, Italy, Japan, Netherlands, New
Zealand, Norway, Portugal, Singapore, Spain, Switzerland,
Sweden, and United Kingdom. The index excludes REITs.
The index is rebalanced semiannually and backtested
performance results assume reinvestment of dividends and
capital gains. Filters were applied to data retroactively and
with the benefit of hindsight. Returns are not representative
of actual portfolios and do not reflect costs and fees
associated with an actual investment. Actual returns may be
lower. It is not possible to invest directly in an index, which
is unmanaged.
Non-US Developed Small Low Relative Price Index:
This index was created by Dimensional in July 2013 and is
compiled by Dimensional from Bloomberg securities data. It
focuses on small cap value companies in non-US developed
markets. Small cap companies are generally defined as the
bottom 12.5% of the eligible market in each country. Value
breaks are formed by country on the bottom 25% of small
companies ranked on relative price after the exclusion of
utilities, companies lacking financial data, and companies
with negative relative price. Maximum index weight of
any one company is capped at 5%. Countries included are
13

14. A PPE N D I X
REFERENCES
DISCLOSURES
1.
See Gerard O’Reilly and Savina Rizova, “Expected
Profitability: A New Dimension of Expected Returns,”
Dimensional Fund Advisors’ Quarterly Institutional Review
9, no. 1 (2013a): 4–7.
2. The first paper examined how the expected profitability
dimension could be applied to a universe of US large
cap stocks. See Gerard O’Reilly and Savina Rizova,
“Applying Direct Profitability to US Large Caps,”
Dimensional Fund Advisors’ Quarterly Institutional
Review 9, no. 1 (2013b): 8–11.
3. Direct profitability is defined as operating income before
amortization and depreciation minus interest expense
scaled by book equity. It is a reliable proxy for expected
profitability. For more information on direct profitability,
see O’Reilly and Rizova (2013a).
4. For more information on this issue, see Savina Rizova,
“Dimensional’s Approach to Sector Representation in Value
Strategies,” a Dimensional Fund Advisors white paper of
November 8, 2012, available at https://my.dimensional.
com/insight/papers_library/95021/.
5. In this paper, we exclude utilities and REITs from the eligible
universe, as they do not fully capture the equity premium
and have market-like expected returns. In the US, we target
stocks in the lowest 10% of aggregate market capitalization.
For developed countries outside the US, we target the
lowest 12.5%.
6. In this paper, we exclude utilities and REITs from the
eligible universe, as they do not fully capture the equity
premium and have market-like expected returns. In the US,
we target stocks above the bottom 10% of aggregate market
capitalization. For developed countries outside the US, we
target stocks above the bottom 12.5%.
7. Because the Russell Indexes start in 1979, our analysis
focuses on 1979–2012.
8. For more information on the Fama-French three-factor
model, see Eugene F. Fama and Kenneth R. French,
“Common risk factors in the returns on stocks and bonds,”
Journal of Financial Economics 33 (1993): 3-56.
Dimensional Fund Advisors LP is an investment advisor
registered with the Securities and Exchange Commission.
Past performance is no guarantee of future success. Indices are not available for
direct investment. There is no guarantee strategies will be successful.
14

16. BRO-QIR