QS Investors Diversification Based Investing Whitepaper - FTSE

W H I T E P A P E R
FTSE DBI
(Diversification Based Investing)
By QS Investors, LLC
Diversification Based Investing or DBI, is an investment
strategy that seeks to take advantage of macro and
behavioural inefficiencies in global and international equity
markets by developing a diversified exposure to macro risk
factors. DBI focuses purely on portfolio construction rather
than stock selection and uses analysis of country and
industry correlations to create an active index that is highly
diversified across countries and industries. In this paper, we
explain the rationale for DBI, the details of the investment
process, and present detailed analysis of its performance
and characteristics to show why we believe it can deliver:
1. Higher absolute and risk-adjusted returns than market
capitalization weighted benchmarks over the long run
2. Higher returns in both falling and rising equity markets1 3. Low correlation of excess returns to market
capitalization indices2 and alternatively weighted equity
indices
1 Higher returns is defined as market return participation, i.e. when markets are rising the DBI index rises more than 100% and when the market is falling it falls less than 100% .
2 The excess return has no dependence on market direction, in other words there is no beta exposure in the excess return.
FTSE DBI Page 1

Introduction
Over ten years ago, QS Investors developed the
Diversification Based Investing (DBI) strategy to try to
take advantage of macro inefficiencies in equity
markets by developing a portfolio construction
process with a greater degree of diversified exposure
to macro risk factors. Through analysis of country and
industry correlations, DBI creates a portfolio that is
highly diversified across these factors and can create
higher absolute and risk-adjusted returns than market
capitalization indices with less downside risk.
DBI is based on three key beliefs:
1. Geography and industry are the primary drivers of
global equity risk
2. Market sentiment generates momentum effects in
indices, which leads to concentration risk that
builds and collapses
3. A diversified portfolio helps to avoid concentration
risk and reduces downside market participation
Recent academic and practitioner research lends
support to these beliefs by pointing out that a large
part of returns in international equity markets are
driven by macro effects: the business a company is in
(industry) and where the business is located
(geography).
Jung and Shiller have asserted that markets show
macro-inefficiency “in the sense that there are long
waves in the time series of aggregate indexes of
security prices below and above various definitions of
fundamental values.” 3
FTSE DBI Page 3
However, most active equity managers focus on stock
selection to beat their benchmarks despite the
argument from academic research that equity
markets show considerable micro efficiency, 4 that is
that individual security mispricings tend to be wiped
out fairly quickly.
This suggests broader investment opportunities may
exist to add value at the macro level through portfolio
construction rather than stock selection. DBI’s unique
portfolio construction process takes advantage of
these findings and has consistently added value,
delivering:
1. Higher absolute and risk-adjusted returns than
their respective indices
2. Outperformance in both up and down markets
3. Low correlation of excess return to both their
respective indices and stock selection based
alternative equity index approaches
For the 10 years ending December 31, 2010, the
FTSE DBI Indices have outperformed their respective
market capitalization benchmarks with a high level of
consistency as measured by the information ratio.
10 Year (%pa) 10 Year Information Ratio 5
FTSE DBI Developed Index 6.52 0.80
FTSE Developed Index 3.02
FTSE DBI Developed ex Japan Index 6.75 0.81
FTSE Developed ex Japan Index 3.23
FTSE DBI Developed ex US Index 8.43 1.36
FTSE Developed ex US Index 4.83
* Based on monthly annualized total returns
SOURCE: FTSE Group
3 Samuelson’s dictum and the stock market, Jung and Shiller (2005)
4 Irrational Exuberance, 2nd Ed. (2001), p. 243
5 Information Ratio as a measure of consistency of return measured by the annualized excess return divided by annualized standard deviation of that return

1 | Rationale and philosophy
DBI is based on three key beliefs:
1. Geography and industry are the primary drivers of global
equity risk
2. Market sentiment generates momentum effects in
capitalization-weighted indices, which leads to
concentration risk that builds and collapses
3. A diversified portfolio helps to avoid concentration risk
and reduces downside market participation
The rationale for the first two beliefs is given below. The third
is explained in section three, “Performance analysis”.
Figure 1: The importance of Country, Currency and Industry exposures
Explanatory Power of Gem Factors
Rolling 12-month average
100%
80%
60%
40%
20%
0%
Jan-1995
Jan-1996
FTSE DBI Page 4
Jan-1997
Jan-1998
Jan-1999
Jan-2000
Jan-2001
Belief 1 | Geography and industry drive global equity
risk and return
Geography (where a company is located or country and
currency) and Industry (what company a business is in) have
explained more than 90% of the factor risk in global equity
markets over the last 15 years. Other factors such as size,
value/growth, volatility and momentum, have explained less
than 10%. To illustrate this, Figure 1 shows the explanatory
power of BARRA’s Global Equity Market factors highlighting
that over a rolling 12-month basis that the Country, Currency
and Industry factors drive over 90% of the factor risk.
This is why DBI’s investment process focuses on geography
and industry as the key building blocks.
Jan-2002
Jan-2003
Jan-2004
Jan-2005
Jan-2006
Jan-2007
Jan-2008
Jan-2009
Source: BARRA, QS Investors analysis
Risk Indices
Industries
Currencies
Countries

Belief 2 | Market sentiment leads to concentration risk
that builds and collapses
Broad equity indices are often considered highly diversified
investments. And yet, market sentiment—or, put another
way, investors’ collective enthusiasms—can cause dangerous
concentrations in certain parts of capitalization weighted
indices.
Dec-1993
FTSE DBI Page 5
Dec-1995
Dec-1997
Dec-1999
Dec-2001
The FTSE World Index is one of many benchmarks to have
experienced concentrations that built up and then collapsed.
Two prime examples—from different decades—involved
Technology stocks and more recently, Financial stocks.
In the mid-to- late 1990s the weight of Technology stocks in
the FTSE Developed Index surged from just over 5% to almost
25% (Figure 2).
Figure 2: Index weight of Technology stocks in the FTSE Developed Index (December 1993 – August 2010)
% Weight Index
30%
25%
20%
15%
10%
5%
0%
Source: FTSE Group, QS Investors LLC analysis
Dec-2003
Dec-2005
Dec-2007
Dec-2009
Aug-2010

The increased weight reflected a strong enthusiasm for
Technology stocks. But it also generated momentum that
propelled the collective market capitalization of Technology
stocks even higher, as index tracking funds and active
managers bid up the stocks.
More recently, Financial stocks went through large increases
as earnings increased with the advent of financial firms
leveraging the real estate boom, new earnings sources
generated by new financial instruments, investors belief that
business cycles would be more moderate than in the past,
Dec-1993
In our view, these concentrations resulted from consistent and
repeated patterns of investor behavior. Over the long-term,
stock prices will oscillate around the company’s intrinsic value
but be closer to the average intrinsic value. But in the shortterm—and
for more extended periods during bubbles—
market cap-weighted indices often overweight overvalued
stocks as investors become too optimistic about their growth
potential, and underweight undervalued stocks for the
opposite reason. This phenomenon, which has been
documented in the academic literature over the last several
years, 6 is illustrated in Figure 5.
DBI’s investment process is designed to counteract the
concentration risk seen in market capitalization weighted
indices.
6 Financial Analysts Journal (Treynor, 2005), Journal of Investing (Hamza, et al, 2007)
FTSE DBI Page 6
Dec-1995
Dec-1997
Dec-1999
Dec-2001
and increased risk taking by these institutions. The increase
in earnings led investors to become very excited by the
earnings growth prospects of financial firms and the lower
potential volatility of earnings. This led them to bid up
financial stocks relative to the rest of the market causing the
weight of Financials in the index to increase from a low of
17% in 2000 to a peak of almost 28% of the index in 2006.
Over the next two years the concentration collapsed as
financial stocks fell to nearly half their weight to just over
16% of the index in early 2009 (see Figure 4).
Figure 4: Index weight of Financial stocks in the FTSE Developed Index (December 1993 – August 2010)
% Weight Index
30%
25%
20%
15%
Source: FTSE Group, QS Investors LLC analysis
Dec-2003
Dec-2005
Intrinsic value
Dec-2007
Figure 5: Distribution of Stock Price Versus True
“Intrinsic Value”
Undervalued Overvalued
Increasing
underweight
Source: FTSE Group, QS Investors LLC analysis
Increasing
overweight
Dec-2009
Aug-2010

Academic foundations
The conceptual basis for DBI is supported by a growing
body of research. Academics and theorists have recently
argued that although modern markets show considerable
micro efficiency7 —simply put, that individual security
mispricings tend to be wiped out fairly quickly—they are
less efficient at the macro level. Jung and Shiller have
asserted that markets show macro-inefficiency “in the sense
that there are long waves in the time series of aggregate
indices of security prices below and above various
definitions of fundamental values.” 8
Put another way, “because the aggregate averages out the
individual stories of the firms, and the reasons for changes
in the aggregate are more subtle and harder for the
investment public to understand—having to do with
national economic growth, stabilizing economic policy and
the like—factors such as stock market booms and busts
swamp out the effect of information about future dividends
in determining price and make the simple efficient markets
model a bad approximation for the aggregate stock
market.” 9
We believe that there are three primary drivers of this
inefficiency caused by the uncertainty of the impact of
these drivers: monetary policy, fiscal policy and regulatory
policy.
1. Monetary policy: The future levels of interest rates,
potential and implemented asset purchases, as well as
other actions by central banks are uncertain, as is their
impact over the near- and medium-term. Investors
struggle with these issues when evaluating the value of
different parts of the market and the impact on
economic growth as well as the effectiveness of policy
actions. Recent examples include expectations around
interest rate levels in 2010 and beyond and the use and
effectiveness of quantitative easing policies and tools.
7 Irrational Exuberance, 2nd Ed. (2001), p. 243
8 Samuelson’s dictum and the stock market, Jung and Shiller (2005)
9 Ibid
10 Confirmation bias: A ubiquitous phenomenon in many guises, Nickerson (1998)
FTSE DBI Page 7
2. Fiscal policy: Similarly to monetary policy, fiscal stimulus
or austerity is debated, enacted and modified over the
medium-term and subject to disagreement by policy
makers as well as investors. It takes years to assess the
impact of fiscal policy often with uneven and
contradictory economic data that is released on an
infrequent basis. Recent examples include the perceived
impact and market reaction to the size and length of
fiscal stimulus, its impact on sovereign debt levels, as
well as the impact of fiscal austerity on country growth
rates.
3. Regulatory policy: Legislative agendas and reaction to
market events can have a large impact on perceived and
actual country competitiveness as well as industry
profitability and business strategy. These changes are
often debated over a multi-year time frame and the
impact of legislation is uncertain. One needs look no
further then proposed and enacted reform surrounding
banks and other financial institutions in the US and
Europe as well as healthcare reform in the US for recent
examples.
This macro uncertainty opens the door for behavioral biases
and sentiment effects. One that has been well documented
is that people – and investors are no exception – are subject
to confirmation bias. That is, that they tend to hang on to
hypotheses in the face of conflicting data. 10 Even when
certain country and industry valuations are very high or low
compared to history, investors often hold on to their beliefs
in the face of contradictory data until it becomes patently
obvious that they have misjudged relative values. This
creates many investment opportunities which add value
through macro based portfolio construction rather than
stock selection.

2 | The DBI investment process
DBI takes into account the observed characteristics of
markets and indices described earlier, and uses them to
create a more diversified index. The strategy’s investment
process has four steps:
1 | Assign all stocks to risk units defined by the key drivers
of risk: country and industry
2 | Identify highly correlated risk units, and group them in a
single “cluster”
3 | Weight the clusters and the risk units in them equally.
The objective of equal weighting is to achieve a high
level of diversification
4 | Rebalance the index to capture changes in market
dynamics
These four steps are described in more detail.
FTSE DBI Page 8
Step 1 | Partition
Figure 6: All Risk Units and example of two within the FTSE DBI Developed Index
Australia
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Greece
Hong Kong
Ireland
Italy
Japan
Netherlands
Norway
Portugal
Singapore
Spain
Sweden
Switzerland
United Kingdom
United States
Basic
Materials
Consumer
Goods
Consumer
Services
Financial
Services
Risk Unit 1
The objective of this step is to group stocks with common
drivers of return. As the country that a company resides in
and the industry they compete in are the key drivers of risk
in a diversified portfolio, we use FTSE’s categorization of
stocks to partition each stock in to a single country/industry
“risk unit”, for example Netherlands Financial Services or
Japanese Utilities. Every stock in the relevant FTSE index,
e.g. FTSE Developed Markets, is assigned to one of these
risk units. Figure 6 shows all Risk Units and highlights these
two examples.
Health
Care Industrials
Oil &
Gas Technology
Telecommunications
Utilities
Risk Unit 2

Step 2 | Cluster
In this step, we cluster the risk units to identify diversification
potential. Once a year, we use statistical analysis based on
correlations over the last five years to identify risk units that
are highly correlated to each other. We group highly
correlated risk units in to clusters so as to maximize the
correlation of risk units within clusters and minimize the
correlations between clusters. Each cluster can be thought
of as a risk theme in the market. If investors have viewed
risk units as being highly correlated or driven by a common
risk factor, then the correlations will be high and these risk
units will be grouped into the same cluster. Two examples of
clusters in 2010 are illustrated in Figure 7: Cluster 1, global
financial services/cyclical stocks; and Cluster 2, Japanese noncyclical
stocks.
Figure 7: Example of two clusters in FTSE DBI Developed Index
Australia
Austria
Belgium
Canada
Denmark
Finland
France
Germany
Greece
Hong Kong
Ireland
Italy
Japan
Netherlands
Norway
Portugal
Singapore
Spain
Sweden
Switzerland
United Kingdom
United States
Source: QS Investors LLC
For illustrative purposes only
FTSE DBI Page 9
Basic
Materials
Consumer
Goods
Consumer
Services
Financial
Services
Cluster 1
Financials Svcs/
Cyclical
Some clusters are based primarily around sectors, while
others are determined more by geography. In the above
example, Financial Services are more globally integrated and
reside in cluster 1 while there are only Japanese risk units in
cluster two. In total DBI targets 10 clusters. At times there is
not enough difference between risk units to form 10 clusters
so that 9 clusters are the optimal number. For example, if
the 10th cluster only has one or two risk units in it, it means
that there is not enough difference between risk units in the
10th cluster and another cluster. If this occurs, we rerun the
process targeting 9 clusters and the index will only have 9
clusters for that year.
Health
Care Industrials
Oil &
Gas Technology
Telecommunications
Utilities
Cluster 2
Japan
Non Cyclical

Step 3 | Weight
The objective is to engineer a diversified exposure to the key
drivers of risk and return. By design each cluster has a low
correlation to other clusters, and from an intuitive standpoint
describes a risk theme in the market such as global
commodities, financial services/cyclical stocks or Japanese
non-cyclicals. Market capitalization indexes may have high
weights to a particular risk theme such as cyclical stocks, and
low weights to other risk themes such as Japanese noncyclicals.
In contrast, DBI seeks a more diversified exposure
to risk themes in the market by equal weighting all clusters.
In effect, DBI avoids forecasting which risk theme will do
better than others. This diversification approach forms the
Figure 8: Example of three “Clusters” within FTSE DBI Developed Index
Portfolio
Weight
As of September 30th, 2010.
Source: QS Investors LLC. For illustration purposes only
FTSE DBI Page 10
11% Cluster 1
0.36% Australia Industrials
0.36% Australia Financial Services
0.36% Austria Financial Services
0.36% Belgium Financial Services
0.36% Canada Industrials
0.36% Canada Financial Services
0.36% Switzerland Financial Services
0.36% Denmark Financial Services
0.36% Germany Consumer Goods
0.36% Germany Technology
0.36% Spain Financial Services
0.36% Finland Basic Materials
0.36% Finland Financial Services
0.36% Finland Technology
0.36% France Financial Services
0.36% France Technology
0.36% Great Britain Financial Services
0.36% Greece Financial Services
0.36% Ireland Industrials
0.36% Italy Consumer Goods
0.36% Italy Financial Services
0.36% Netherlands Industrials
0.36% Netherlands Financial Services
0.36% Sweden Consumer Goods
0.36% Sweden Financial Services
0.36% United States Basic Materials
0.36% United States Industrials
0.36% United States Consumer Goods
0.36% United States Consumer Services
0.36% United States Financial Services
0.36% United States Technology
Portfolio
Weight
heart of DBI’s portfolio construction process. As risk units
within a cluster are highly correlated, there is no reason to
overweight one compared to the other. Thus each risk unit
is equally weighted in each cluster. Figure 8 illustrates three
cluster examples as of September 30th, 2010. At this time,
the DBI process for the FTSE DBI Developed Index created 9
clusters so each cluster had a 11.1% weight (i.e. 100% ÷
9). Risk units in clusters that contain many risk units have
relatively smaller weights in the portfolio. By construction,
risk units in larger clusters will be highly correlated with more
of the other risk units; therefore, they are not good portfolio
diversifiers and should have a lower weight.
11% Cluster 2
2.78% Japan HealthCare
2.78% Japan Consumer Services
2.78% Japan Telecommunications
2.78% Japan Utilities
Portfolio
Weight
11% Cluster 3
0.85% Australia Oil and Gas
0.85% Australia Basic Materials
0.85% Canada Oil and Gas
0.85% Canada Basic Materials
0.85% France Oil and Gas
0.85% France Basic Materials
0.85% Great Britain Oil and Gas
0.85% Great Britain Basic Materials
0.85% Italy Oil and Gas
0.85% Japan Oil and Gas
0.85% Norway Oil and Gas
0.85% Norway Basic Materials
0.85% United States Oil and Gas

To further illustrate how good and bad diversifiers are
weighted in the portfolio, figure 9 shows how Netherlands
Financial Services (1 of 31 risk units in Cluster 1) and
Japanese Utilities (1 of 4 risk units in Cluster 2) are
correlated to all other risk units. Netherlands Financial
Services shows relatively high correlations to almost all other
risk units and is therefore not a good diversifier. Intuitively
this means that there are many risk units that have a
Correlation
100%
80%
60%
40%
20%
0%
-20%
-40%
Step 4 | Implementation
The objective of this step is to capture structural changes
between countries and industries, while controlling turnover
to keep transaction and market impact costs low. The
clustering process occurs annually when the largest part of
the relevant FTSE benchmark reconstitutes. For example, the
FTSE DBI Developed Index reclustering is completed in
December to coincide with the constituent review
FTSE DBI Page 11
Risk Units
common risk exposure (cyclical/financial services). As a
consequence, it is grouped in a Cluster with many risk units
and gets a small total portfolio weight (0.36%). In contrast,
Japanese Utilities is highly correlated to only a few other risk
units and is negatively correlated with over half of the other
risk units. Because of this, it is a good diversifier; it is
therefore grouped in a cluster with fewer risk units and is
allocated a higher weight (2.78%) as a consequence.
Figure 9: Overweighting good diversifiers; correlation pair example – two risk units to every other risk unit
Japan Utilities
(1 of 4 Risk Units in Cluster)
Netherlands Financial Services
(1 of 31 Risk Units in Cluster)
1
4
7
10
13
16
19
22
25
28
31
34
37
40
43
46
49
52
55
58
61
64
67
70
73
76
79
82
85
88
91
94
97
100
103
106
109
112
115
118
121
As of September 30th, 2010.
Source: QS Investors LLC. For illustration purposes only
High Correlation
Bad Diversifiers
Low Correlation
Good Diversifiers
(reconstitution) that occurs in that index for North America.
As constituent names will change in December, DBI changes
clusters / risk unit weights / stock specific weights to coincide
with that turnover. Immediately after that, market drift
occurs. To maintain diversification, the DBI Indexes are
rebalanced back to the original diversification weights once a
quarter. This process is illustrated below in Figure 10.
Figure 10: Implementation – Example of Clustering and Rebalancing timeline for FTSE DBI Developed Index
Cluster
Rebalance Rebalance Rebalance
Cluster
December March June September December

3 | Performance analysis
In this section, we detail how FTSE DBI Indices performed for
the 10-year period ending December 31, 2010.
Performance and performance patterns
The FTSE DBI indices have outperformed their respective
capitalization weighted indexes by an average of over 3%
per annum.
FTSE DBI Page 12
PERFORMANCE INFORMATION RATIO
12M (%) 3YR (%pa) 5YR (%pa) 10YR (%pa) 10YR IR
FTSE DBI Developed Index 10.97 -5.12 5.67 6.52 0.80
FTSE Developed Index 12.28 -4.13 3.29 3.02
FTSE DBI Developed ex Japan Index 8.28 -4.69 6.87 6.75 0.81
FTSE Developed ex Japan Index 11.98 -4.09 3.97 3.23
FTSE DBI Developed ex US Index 11.48 -1.07 8.46 8.43 1.36
FTSE Developed ex US Index 9.85 -5.53 4.08 4.83
As of December 31, 2010
*Based on monthly annualized total returns.
SOURCE: FTSE Group
Historical outperformance in both up and down markets
On average the FTSE DBI indices have outperformed their
respective market capitalization benchmarks whether the
market moved up or down. Figure 11 shows that each of the
indices captured more positive stock movements than its
benchmark, and declined less during the benchmark’s
negative movements. Because of this, DBI’s diversification
based approach has offered downside protection during
Figure 11: Up market / Down market capture
Up Market/Down Market Capture*
Market participation
FTSE DBI Developed
112.0%
Up Market
Capture
87.3%
Down Market
Capture
Source: Zephyr StyleAdvisor based on quarterly returns for the 10 year period ending December 31, 2010.
*Past performance is not a guarantee of future results. Performance is shown gross of fees and does not reflect investment advisory or other fees.
Had such fees been deducted, returns would have been lower.
falling markets. Falling markets are often driven by a
segment of the market, or risk theme that has risen to be a
large percentage of the index only to fall dramatically when
investors realize that the rise was not justified. Examples
would include Technology Stocks in the late 1990s and
cyclical stocks such as Financials and Industrials in
2005-2007 period.
FTSE DBI Developed Ex-US FTSE DBI Developed Ex-Japan
108.4%
Up Market
Capture
86.5%
Down Market
Capture
119.2%
Up Market
Capture
96.7%
Down Market
Capture

Low correlation of excess returns to the benchmark and alternatively weighted equity index strategies
Because DBI uses a differentiated top-down, diversification
based portfolio construction process, the strategy has shown
low correlation of excess returns to both its market
capitalization benchmarks and alternative weighted equity
index approaches that focus on stock selection. This makes
DBI a good portfolio diversifier as the excess return
complements market capitalization indices and stock
selection alternatively weighted index strategies. Figure 12
illustrates the correlation of the excess return of the FTSE DBI
Figure 12: Low correlation of excess returns to other indexes
1
0
-1
Visa IPO on
19/03/2008
Data as of December 31, 2010
Start dates: FTSE Developed Index-1/2001; FTSE RAFI Developed 1000 Index -4/2007; FTSE EDHEC Risk Efficient Developed Index - 1/2003
*Past performance is not a guarantee of future results. Performance is shown gross of fees and does not reflect investment advisory or other fees.
Had such fees been deducted, returns would have been lower. Source: FTSE Group, QS Investors analysis for longest available time frame.
FTSE DBI Page 13
0.04
FTSE Developed Index
Developed to the excess return of the FTSE RAFI Developed
1000 Index, the FTSE EDHEC Risk Efficient Developed Index
and to the FTSE Developed Index from inception through
December 31, 2010. As can be seen, the correlation of the
excess return generated by the DBI process has a low
correlation to the market capitalization index, the FTSE
EDHEC Risk Efficient Developed Index and a negative
correlation to the FTSE RAFI Developed 1000 Index.
-0.13
FTSE RAFI Developed 1000 Index
0.04
FTSE EDHEC Risk Efficient Developed Index

4 | Risk exposures
Active risk exposures
Over the last 10 calendar years, on average almost 90% of
the active risk exposures for the FTSE DBI Index series came
from country, industry and currency as illustrated in Figure 13
which illustrates the active risk exposure of the FTSE DBI
Developed Index compared to the FTSE Developed Index.
As DBI specifically focuses on developing alternative weights
Figure 13: FTSE DBI Developed Index active risk exposures over time
29/12/2000 31/12/2001 31/12/2002 31/12/2003 31/12/2004 30/12/2005 29/12/2006 31/12/2007 31/12/2008 31/12/2009
Specific % 12.1% 8.8% 8.0% 6.3% 4.2% 5.3% 8.6% 8.0% 11.3% 5.1%
Common % 87.9% 91.2% 92.0% 93.7% 95.8% 94.7% 91.4% 92.0% 88.7% 94.9%
Style % 19.0% 11.7% 18.0% 6.3% 3.6% 3.1% 2.3% 5.5% 14.3% 13.6%
Size % 3.7% 5.5% 4.8% 3.2% 2.2% 1.2% 1.3% 1.9% 0.4% 0.7%
Value % 0.5% 0.0% 0.4% 0.7% 0.1% 0.0% 0.2% 0.2% 0.9% 0.9%
Country % 25.1% 35.1% 39.3% 49.8% 45.6% 54.7% 56.8% 60.7% 62.1% 58.4%
Industry % 12.3% 7.2% 3.1% 3.4% 1.8% 3.4% 3.1% 1.5% 2.7% 3.1%
Currency % 19.6% 32.1% 17.1% 47.7% 44.4% 36.4% 37.0% 27.8% 24.8% 36.4%
Covar 11.9% 5.2% 14.6% -13.4% 0.4% -3.0% -7.7% -3.4% -15.2% -16.6%
SOURCE: Axioma, QS Investors LLC
5 | Summary
Summary
Diversification Based Investing (DBI) is an international or
global approach to gaining exposure to equity markets that
provides broad exposure and, over the long-term, seeks
higher returns and higher risk-adjusted returns than its
benchmark with less exposure to down markets.
The DBI investment process is designed to capture the
benefits of a higher level of diversification by taking into
account the primary drivers of global equity returns:
geography and industry. Diversification is maintained by
taking in to account changing correlations in the countries
and industries thereby reflecting changes in how investors
think of the world and what parts have higher or lower
interdependencies. By diversifying across risk themes or
“clusters” of risk in the market, the more diversified
exposure to the risk premium in these risk themes has on
average led to higher absolute and risk adjusted returns.
FTSE DBI Page 14
at the country and industry level, it is not surprising that this
is where the majority of active risk is generated. This is in
contrast to some other alternative weighting approaches
such as fundamental indexing that can generate significant
small cap and value biases.
Owing to its differentiated top down investment approach,
DBI has generated excess return that has been uncorrelated
to both their capitalization weighted benchmarks and some
alternative weighted equity index strategies such as
fundamental indexing. The DBI investment approach has
also led to positive excess return in both rising and falling
equity markets and has captured more than 100% of
returns in up markets and less than 100% of returns in
down markets. The primary drivers of DBI’s active risk
exposures are from active country, currency and industry
positions. The Developed Index strategy has exhibited no
persistent size or style bias relative to its benchmark and only
modest bias at any given time so is a good complement to
both market capitalization weighted indices and alternatively
weighted stock selection indices such as fundamental
weighted indices.

About QS Investors, LLC
QS Investors, LLC is an independent investment firm
providing asset management and advisory services to a
diverse array of institutional clients. The firm’s senior
management team previously worked together for over
10 years within Deutsche Asset Management’s
Quantitative Strategies Group. During that time, the
QS team pioneered approaches to integrating quantitative
and qualitative investment insights and dynamically
weighting key market drivers across a broad spectrum of
strategies including global tactical asset allocation, US and
Global equities.
FTSE DBI Page 15
Based in New York with more than 40 employees, QS
Investors is one of the largest majority woman owned asset
management firms.
www.qsinvestors.com
For more information on the FTSE DBI Index Series,
please visit www.ftse.com/Indices/
FTSE_Diversification_Based_Investing_Index_Series/index.jsp
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