Download The past five years have seen market behaviour dominated by

Benchmarking, Better Beta
and Beyond
Our survey of 51 institutional investors highlights a range
of issues with traditional benchmarks including large cap,
sector and regional biases. European institutions in
particular have started to explore alternative benchmarks
and smart beta strategies to overcome these limitations.
However, the first generation of such alternative
approaches have their own drawbacks. Persistent and
basic factor exposures explain the vast majority of
returns. Limited transparency, a lack of broad
understanding and modest liquidity are also cited as
concerns.
We explore two novel approaches to active equity
management that offer a way to address a number of
these issues.
This is for investment professionals only and
should not be relied upon by private investors
Contents
Benchmarking, Smart Beta and the evolution of active management
p3
The rise of alternative approaches
p6
Smart Beta
p7
Alternative Equity Benchmarks
p9
So what next?
p10
Conclusions
p13
Executive Summary
1
In a Fidelity Worldwide Investment sponsored research study about half of the institutions
interviewed have discussed or investigated the possibility of moving away from traditional
benchmarks, including 22% of the Asian institutions and 78% of institutions in Europe.
However, less than 8% of actively managed assets are currently run against alternative
benchmarks.
Investors cited a number of concerns about market capitalisation weighted indices
including their bias towards large caps, certain sectors and regions as some of the
practical issues with traditional indices. In addition, there are a number of conceptual and
empirical limitations often highlighted by academics, including: poor risk-adjusted returns
versus alternative benchmarks, a lack of consideration of correlations between stocks and
a tendency to overweight overpriced stocks and to carry a momentum bias.
In the last few years there has been significant focus on exploring the value that nontraditional approaches can add. Alternative approaches aim to overcome the issues with
traditional market cap-weighted indices and can be deployed as benchmarks or prepackaged low cost ‗smart beta‘.
A first generation of alternative benchmark approaches have their own drawbacks.
Persistent and basic factor exposures explain the vast majority of returns. A lack of
transparency, liquidity in some instances and general understanding of alternative
benchmarks are also cited as concerns by investors.
We explore two novel approaches to active equity management that could offer a way to
address a number of these issues: 1] the separation of a stock selection process from a
weighting methodology to reduce acute factor exposures; this is most appropriate for
systematic disciplines. 2] Unconstrained portfolio management where positions are sized
without reference to a benchmark and factor exposures are deliberate and fully owned.
Ultimately, all options will be judged on an opportunity cost basis versus market cap
indices and should deliver superior risk-adjusted returns in the medium to long term if they
are to be successful.
Author:
Hiten Savani
Investment Director
[email protected]
1
Greenwich Associates, on behalf of Fidelity Worldwide Investment, conducted interviews with 51 institutions,
28 in Asia and 23 in Europe, with over $1 trillion in total assets under management. Interviews focused on
understanding investors‘ current use of equity benchmarks, specific issues with the indices they are currently
using and expectations for change.
Benchmarking, Smart Beta and the evolution of active management
In an ideal world, long-run investment objectives determine strategic asset allocation and the
characteristics of the individual asset class strategies that form the portfolio building blocks. In such
a world expected risk and return - both for the total portfolio and each of the building blocks - are
managed in unison with the aim to deliver the long-run objective.
In the real world there are a number of issues that restrict assets being managed in such a perfectly
tailored fashion. Whilst strategic asset allocation is increasingly being driven by the specific
requirements of asset owners, aligning the characteristics of each asset class building block to the
overall investment objective is challenging. Often management of such sub-portfolios is outsourced
to specialists. This results in sharing the risk and return objective and benchmark of the building
block with other investors in the strategy. Whilst asset owners can often align risk and return,
benchmarks can present a more fundamentally challenging issue.
A survey of institutional investors
From May to June 2013, Greenwich Associates, on behalf of Fidelity Worldwide Investment,
conducted interviews with 51 institutions, 28 in Asia and 23 in Europe, with over $1trillion in total
assets under management. Interviews were conducted with sovereign wealth funds and other
government-affiliated investors, pension funds, insurance companies, endowments, and
foundations. Interview topics focused on understanding investors‘ current use of equity
benchmarks, specific issues with the indices they are currently using and expectations for change.
The results of the study show that institutional equity investors in Asia and Europe see significant
weaknesses in traditional, market capitalisation weighted benchmarks. In response, European
investors have begun to explore alternative benchmarks and other approaches to performance
measurement. Asian institutions, however, are primarily staying the course with standard indices—
for now.
Of course, traditional benchmarks like the FTSE 100 and the MSCI World Index remain the
standard for most institutional investors. Among the 23 European institutions participating in the
study, three-quarters of assets are managed against market-cap weighted benchmarks without any
customisation. In Asia that share is even larger: among the 28 Asian institutional investors in the
study, 87% of total assets are managed against traditional benchmarks, including 100% of Asian
pension fund assets.
About half of these institutions, however, are investigating the possibility of moving away
from traditional benchmarks, including 22% of the Asian institutions and an impressive 78% of
institutions in Europe. Two important drivers of this shift are:
Firstly, a growing number of investors in Europe are managing assets without a formal benchmark;
currently 13% of assets fall into this category. This practice has also been adopted by a smaller
number of investors in Asia, where 11% of assets are managed without a formal benchmark,
according to the study results. The European investors benchmark another 4% of assets against
cash or LIBOR, while the Asian investors use cash or LIBOR benchmarks for 2%.
Secondly, institutions are looking for ways to address what they see as shortcomings in the major
indices. Historically, investors have had several issues with the composition of these indices.
3
Exhibit 1: Issues cited with various traditional benchmarks (51 survey participants)
European
Investors
Asian
Investors
7
2
Global Equities
Domestic Equities
6
United States
5
Europe
5
Global Emerging
Markets
4
2
2
China
2
2
Taiwan, India, Japan
3
Cited mainly for
large cap stock
bias and sector
bias
1
Asian
European investors cite
mainly large cap stock
bias, Asian investors cite
developed market bias
European investors think
that the index is not
reflective of rapid changes
3
Question asked: In which of the areas where you currently have equity allocations do you face issues with the
type and quality of indices provided by major index providers? Which type of issues do you encounter in each of
these areas?
Source: FIL Limited, Greenwich Associates, 2013
For nearly all equity index types, from global to country-specific, many Asian and European
institutions in the study name large-cap bias as a major problem encountered with these indices.
Asian investors cite additional issues, such as developed-market bias in global equity indices, and
investors from both regions cite sector bias as a problem in some domestic equity and individual
country indices. One example: the sizable exposures to the financial service sector in both the
major Chinese and European indices. European institutions also say major indices are not reflective
of rapid changes in important developing markets like China.
The representative of a Danish pension fund explains why it makes adjustments to a standard
benchmark in global equities: ―We feel there is a better way of constructing passive benchmarks
and in terms of active, MSCI is not the ideal way to do it. This is more of a herding market
perspective where we are following what everyone else is buying.‖
In addition to being highly concentrated, in some instances, and biased towards large caps and
certain sectors, market capitalisation weighted indices have theoretical and empirical limitations that
are often highlighted by academics [Tabner 2007, Malevergne et al. 2009, Goltz and Le Sourd
2011]. The key issues raised are that cap-weighted indices:

Have provided poor risk-adjusted returns versus alternative benchmarks

Do not consider correlations between stocks

Overweight overpriced stocks

Carry a momentum bias
At least partially in response to these issues, the European institutions in the study have moved 8%
of total assets to be managed against alternative benchmarks such as equal-weighted indices,
fundamentally-weighted indices and other measures. Despite harbouring similar concerns over
standard indices, most Asian institutions still rely on them almost exclusively: only 1% of Asian
institutional assets are managed against alternative benchmarks. One reason for this phenomena is
that Asian institutions are largely still working through more fundamental issues, such as
diversifying their portfolios to reduce home-market bias (see box below) and large exposures to
domestic fixed income.
4
Exhibit 2: Share of actively managed equity assets run against various benchmarks
Asian Investors (28)
European Investors (23)
Cash/LIBOR etc.
4%
Cash/LIBOR etc.
2%
No f ormal
benchmark
11%
Alternative Equity
Benchmark
1%
Alternative Equity
Benchmark
8%
No f ormal
benchmark
13%
Traditional Market
Capitalization
Weighted
Benchmarks
75%
Traditional Market
Capitalization
Weighted
Benchmarks
87%
100%
Small group of
investors where
100% of assets
without formal
benchmark for
various reasons
such as LDI
approach
92%
74%
75%
Pension Funds
Insurance Companies
67%
Pension Funds
Others
Insurance
Companies
Question asked: Please give us an idea of the share of your equity assets actively managed against the
respective benchmarks.
Source: FIL Limited, Greenwich Associates, 2013
Among European institutions, 26% say they plan to shift assets toward management against
alternative benchmarks, as do 11% of the Asian institutions. Another 9% of European investors
and 4% of Asian investors expect to shift assets to cash or LIBOR benchmarks, or to forgo
benchmarks entirely as part of Liability Driven Investment or other approaches.
Exhibit 3: Share of investors expecting change in distribution of assets managed against different
benchmarks
Asian Investors (28)
European Investors (23)
Shif t towards
alternative equity
benchmarks
11%
Shift towards
alternative equity
benchmarks
26%
Other
4%
No
Change
86%
No
Change
65%
Other
9%
Question asked: Do you expect a change in the distribution of assets managed against different types of
benchmarks?
Source: FIL Limited, Greenwich Associates, 2013
5
Finding a Custom Fit for Global Equities
More than one-third of European institutions participating in the study currently use customized
global equity indices. In addition, while only two participating Asian investors say they currently use
alternative benchmarks for global equity investments, several anticipate adjusting global equity
benchmarks via customised indices in the future.
Exhibit 4: Investors Citing Type of Change Made / Anticipated in Customised Indices
13
5
―Exclude certain
countries‖
8
―Exclude EU
Equities‖
8
Asian
Investors
5
4
European
Investors
4
3
3
1
1
Adjust
Representation of
Regions
Exclude Certain
Sectors
3
Exclude Home
Country
Other
Question asked: Please describe what type of changes you make/ anticipate in customized indices for global
equities relative to traditional market cap-weighted indices.
Source: FIL Limited, Greenwich Associates, 2013
The bulk of changes institutions make or anticipate making via customised indices involve altering
the representation of countries or regions. Among the most common changes employed or
anticipated by the European institutions are the exclusion of European equities and home-country
stocks. Asian institutions looking to alter benchmarks have moved predominantly to exclude
equities from their domestic markets or other countries or sectors. A representative of a South
Korean insurance company explains: ―We already have the exposure to our home country in the
Korea equity index and fixed income; therefore, when we invest in the global market, it is fine to
exclude the home market.‖
The rise of alternative approaches
In the last few years there has been significant focus on exploring the value that non-traditional
approaches can add. Alternative approaches all aim to overcome the issues with traditional market
cap-weighted indices. Industry and academic work has been split into two areas:
1] Development of pre-packaged low cost smart beta products that aim to deliver better riskadjusted returns than cap-weighted indices in the medium to long term.
2] Development of alternative weighting schemes to benchmark active investment strategies.
Many of the new approaches that have raised interest can be deployed in either of these two ways.
This complicates the decision as to whether and how to use these new approaches.
6
Smart Beta
Smart beta products aim to deliver better risk-adjusted returns than their cap-weighted
counterparts. They do this by exploiting some of the biases in traditional benchmarks highlighted
2
above. In a paper published in early 2012 we explored some of the major types of smart beta
products, these include:

Risk based approaches such as minimum variance, equal risk contribution and maximum
diversification, which exploit an expected low volatility premium

Fundamentally weighted approaches, which weigh constituents on the basis of firm level
characteristics such as book value, revenue or dividends in an attempt to exploit an expected
value premium

Equally weighted approaches, which have an inherent tilt towards small caps and aim to
exploit any small cap premium
In recent years, given elevated levels of equity market volatility, risk based approaches have been
of particular interest. The charts below highlight the dramatic increase in academic investigation
and flows into minimum variance ETF products.
Exhibit 5: Minimum volatility strategies have been of significant interest in recent turbulent times
Academic references to ‘minimum variance portfolios’
200
Minimum Volatility ETF inflows
25
US$bn
180
160
20
140
120
15
100
80
10
60
40
5
20
0
0
2002
2004
2006
2008
2010
2012
Academic papers using term 'minimum variance portfolios'
2011
2012
Total
2013
Annualised
Source: ASR, 4th June 2013
The following questions explore these first generation smart beta products and the value they can
deliver:
Is smart beta active or passive? In the strictest sense only a market capitalisation weighted, or
‗market‘ index can be passive, i.e. held by all investors simultaneously. Allocating assets to smart
beta strategies is an active decision that provides exposure to one or more factor risk
premia. The fact that some smart beta products are exchange traded and low cost should not
distract from this important point.
The question itself demonstrates how we have been trained to think and categorise investments
into a rigid framework that can oversimplify matters. Moving away from such binary taxonomy and
gradually towards focusing on the individual needs of asset owners is a challenge, but one worth
taking on. For instance if an investor‘s long-run objective is to generate 4% above cash and there is
a 40% allocation to equities, why should the default be an overweight of large caps, growth and
2
Benchmarking and the road to unconstrained, Fidelity Worldwide Investment, Jan 2012
7
momentum using index trackers? Taking such exposure itself represents an ‗active‘ decision. For
those who do not have liquidity as a major issue, there is a host of alternative exposures to choose
from.
Do smart beta strategies solve all my problems with traditional benchmarks? Unfortunately
not. Whilst many smart beta products overcome some issues such as over concentration, large cap
bias and momentum exposure they cannot consistently deliver better risk-adjusted returns versus
market cap indices, and certainly not in all market conditions. Several studies (Kaplan 2008, Blitz &
Swinkels 2008, Amnec et al 2012) show that returns generated by major smart beta strategies can
almost entirely be explained by simple systematic factor exposures. This is demonstrated in Table 1
below.
Table 1: First generation smart beta performance can be explained largely by large factor tilts
Data shown are the T-stats of regressions of smart beta strategies on long/short equity factor indices, using
monthly returns back to 1994. Large and significant exposures are highlighted in green (positive tilt) and red
(negative tilt). The analysis is based on the largest 500 companies in the FTSE World Index.
R
2
Smart Beta Strategy
Cap
Weight
Market
Gearing
Risk
Size
Momentum
Quality
Growth
Value
Intercept
1.00
Equally weighted
187.7
2.16
-0.41
-5.20
-0.28
-2.76
1.24
3.56
2.8
1.00
Diversity Weighted
342.2
2.14
-0.36
-4.99
-0.30
-2.94
1.31
4.05
2.8
0.97
Fundamental Weighted
63.2
-1.94
3.34
-0.19
3.17
0.99
-3.03
10.70
0.8
0.79
Minimum Variance
24.2
2.14
-8.19
1.02
-0.58
-3.20
-1.27
-2.18
1.8
0.78
Max Diversification
21.7
2.53
-5.66
0.16
-0.42
-3.18
-0.81
-3.56
2.0
0.99
Risk parity
113.8
4.56
-6.91
-1.45
2.47
0.16
1.20
6.17
2.5
0.94
Min var (manual)
41.6
0.87
-12.26
3.62
1.46
1.26
0.55
4.31
0.3
Source: Nomura, 14 February 2013
Smart beta products have several limitations of their own, these can include: high turnover, limited
liquidity and high valuation multiples, as has been the case for low volatility strategies recently.
Can smart beta strategies be tailored? Whilst individual pre-packaged smart beta products do
not offer much flexibility, harnessing multiple risk factor premia by dynamically allocating to several
strategies is one way to reconcile investments with long term objectives. Table 2 below outlines
how some major smart beta strategies perform during various points in the economic cycle. An
investment process that forecasts such patterns and shifts allocations to various strategies through
the cycle should be able to deliver strong risk-adjusted returns.
Table 2: Average monthly relative performance of various equity smart beta strategies
Phase of
the
economic
cycle
Mkt Cap
Weighted
(Absolute
Performance)
Recovery
2.36%
0.15%
0.08%
0.12%
-1.53%
Expansion
1.78%
0.04%
0.02%
0.02%
Slowdown
-0.18%
0.06%
0.03%
Downturn
-1.18%
-0.04%
-0.02%
Equally Diversity Fundamental Minimum
Max
weighted Weighted
Weighted
Variance Diversification
Risk
parity
Min var (naïve
approach)
-1.48%
-0.04%
-1.01%
-0.98%
-0.73%
-0.15%
-0.62%
0.02%
0.49%
0.31%
0.36%
1.08%
0.12%
0.56%
0.28%
0.15%
0.66%
Economic phases defined by periods of expansion and contraction in the US economy as measured by the
National Bureau of Economic Research
Source: Nomura, 14 February 2013
A number of quantitative disciplines have well established processes for dynamically tilting factor
exposures within individual asset classes. Widening the process across asset classes would
8
deepen the opportunity set and potentially improve outcomes. There is now a growing focus and
investigation into multi asset smart beta processes.
This move away from thinking about allocation to traditional asset classes and regions towards
managing factor premia and exposures is a notion that asset owners are exploring closely. Results
of a detailed study by the Centre for Applied Research at State Street show that over 60% of
institutional investors interviewed globally plan on managing risk exposures across asset classes
rather than traditional asset allocation.
Alternative equity benchmarks
Many of the portfolio design processes that underlie smart beta strategies can be used to construct
benchmarks for active management.
Roll [1992] demonstrated analytically that alpha delivered through active management is
independent of benchmark construction. He showed that if skill and opportunity set are assumed to
be constant and active positions are sized using a consistent approach, relative performance and
risk are equal irrespective of the weighting methodology of the benchmark.
This result suggests that one should be entirely unbiased when it comes to selecting between
benchmarks with differing weighting processes. In reality there are several issues that will impact
results such as turnover and transaction costs. Where alternative benchmarks are adopted it is
critical to assess whether they overcome each of the limitations associated with traditional indices
highlighted above.
Exhibit 6: Investors citing possibility of moving away from traditional market capitalisation weighted
equity benchmarks
No
Yes
Number of Investors
3
10
13
1
6
5
5
3
Pension Funds Europe
Insurance Companies
Europe
Others Asia
2
Insurance Asia
1
Pension Funds Asia
Question asked: Has your organization discussed or investigated the possibility of moving away from traditional
market capitalization weighted equity benchmarks?
Source: FIL Limited, Greenwich Associates, 2013
Despite their interest in improving equity benchmarks, institutions participating in our study cited a
range of challenges they face in moving away from the major indices.
9
Exhibit 7: Investors citing biggest challenges in moving away from traditional market capitalization
weighted benchmarks (51 institutions surveyed)
Other Challenges cited by Investors
“We need to have clear evidence that alternative benchmarks work in a systematic way” (European Pension Fund)
“The main issue is liquidity with alternative benchmarks.” (Asian Insurance Company)
“The effectiveness of the alternative benchmark is important to us. The benchmark must have a good track record
and manager must be able to track this benchmark, not just passively but also actively.” (Asian Pension Fund)
24
21
19
Asian
Investors
18
13
10
9
8
10
European
Investors
7
6
11
11
10
10
6
4
Lack of
transparency/credibility
in how some alternative
benchmarks are
constructed
Other
Lack of broad
understanding of the
alternative equity
benchmarking
approaches
Difficulties in
communication
performance and risk
Cost of increased
portfolioturnover in
managing against
alternative benchmarks
1
Cost of
modifying/additional
infrastructure
Question asked: What do you believe are the biggest challenges in moving away from traditional market
capitalization weighted benchmarks?
Source: FIL Limited, Greenwich Associates, 2013
Overall, the challenge most commonly cited by institutions was a lack of transparency or credibility
in the construction of alternative benchmarks. This factor represents a particular problem for state
pension funds and other public institutions for which oversight, transparency and the need to
communicate performance and performance standards effectively to external constituencies remain
important concerns. Institutions also mention cost as a concern in moving away from traditional
benchmarks, both as a result of increased portfolio turnover and of modifying or upgrading
infrastructure. These factors represent serious hurdles to institutions looking to improve the
effectiveness of their benchmarks.
In addition to the practical limitations highlighted in our survey there are conceptual issues when
using alternative benchmarks for active management. Commercially available pre-packaged
alternative beta indices often do not allow one to unpack the influence of the stock selection
process from that of the weighting scheme applied. As we have seen in the discussion of smart
beta strategies above, it is the performance of the key risk premia, to which the benchmark is
exposed, that determines the vast majority of long-term returns. Smart beta strategies force
investors to be systematically exposed in this regard. The critical question is whether the factor
exposure delivered is superior to that of traditional benchmarks‘ exposures to large cap and
momentum.
So what next?
It is critical to focus on the impact of a move towards novel approaches on the likelihood of
achieving long-run investment objectives.
The key hurdles for novel approaches to overcome are the issues of concentration and other biases
of traditional indices, and the lack of transparency and simplistic static factor exposures embedded
in the first generation of smart beta strategies.
10
Two approaches that aim to do this:
1] Separation of stock selection and weighting methodology
Amenc et al [2012] have suggested a two step approach appropriate for systematic disciplines,
which splits out the process of stock selection from the weighting methodology applied. They find
that ―selecting stocks by firm fundamentals and using a diversification (weighting) scheme
maintains the outperformance of fundamentals-based stock selection and improves the relevant
diversification objective‖.
By narrowing the universe of stocks via a suitable selection process and then applying a weighting
methodology, the potency of factor tilts associated with the weighting scheme are dramatically
reduced. In fact, stock selection can be viewed as a tool with which to deliberately correct factor
exposures of various weighting schemes. When combining a stock picking process with alternative
weighting schemes in such a quantitative fashion, it is important to fully understand:

the biases and factor exposure in the stock selection process

the biases and factor exposure in the weighting methodology

how such exposures interact when these two elements are brought together
Choice of stock selection process and weighting scheme, in addition to being influenced by the
long-run investment objective, should be a reflection of an investor‘s confidence in their ability to
forecast returns and risk (including covariance).
Exhibit 8: Weighting methodology choice framework
High
Low
Unconstrained
investing
Focus on return views
Diversified or
concentrated stock
picks often vs.
market capitalisation
weighted index
Quantitative Max
Sharpe ratio
Focus on risk model / factor views
High
Minimum Variance
Risk Parity
Max Diversification
Low
Source: FIL Limited, adapted from Fraser-Jenkins et al
Performance measurement would likely be a challenging issue with such a two stage process. It
would ideally split out the assessment of the two elements and also look at the combined result.
Given the nature of the complexity here such an approach lends itself best to systematic or
quantitative disciplines.
2] Unconstrained investing
The misalignment of a company‘s market price and its intrinsic value determined by deep
fundamental analysis offers a substantial source of value. This value can be more effectively
accessed if stock weights within a portfolio are predominantly a reflection of a view on alpha and
risk and not influenced by the specific structure of a given benchmark.
11
An integrated unconstrained approach is particularly useful for countries and regional markets
where a handful of large stocks can have a large bearing on the market capitalisation index return.
Whilst these indices remain important yardsticks for performance over the medium to long term,
they do not influence the sizing of positions in unconstrained portfolios. Such investment
approaches focus less on relative risk and exposures and more on absolute measures.
In addition to allowing portfolio weights to be a function of alpha expectations, the detachment from
the benchmark allows risk factor exposures to be tilted dynamically through the cycle and managed
in a deliberate fashion. Such exposures can be viewed as an additional source of alpha as well as
tools with which to control total portfolio risk.
The left and right charts of Exhibit 9 show ‗before‘ and ‗after‘ snapshots of a portfolio‘s holdings by
weight. These charts draw on a real case study and reveal how the shape of the portfolio changed
when the management style became unconstrained. The unconstrained approach resulted in a
flatter profile of portfolio weights and slightly fewer stocks.
Exhibit 9: Change in the distribution of stock weights in a move to unconstrained management
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
1
1
0
0
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46
Source: FIL Limited
Whilst relative risk (or tracking error) versus a cap-weighted benchmark is likely to rise, absolute
risk is comparable and potentially lower with this style of investing.
Exhibit 10: Unconstrained portfolios can have high tracking error but low absolute volatility
% Absolute Risk (volatility)
30
Characteristics of unconstrained
approaches:
 Higher expected return over a cycle
 Higher tracking error
 Lower absolute risk (typically)
Typical Benchmark-aware
Portfolio
MSCI
20
 Higher expected Sharpe ratio
Indicative
Unconstrained Fund
10
Cash
0
0
5
10
15
20
% Tracking Error (risk relative to cap-weighted benchmark)
Source: FIL Limited, 2013
12
Table 3: Change in portfolio characteristics in a move to unconstrained management
Before
(2010)
After
(2013)
Active Money
38.5
85.1
Tracking Error
3.2
6.2
No. Of Stocks
51
47
Fund Volatility
23.0
16.5
Source: FIL Limited, 2013
Unconstrained portfolios ultimately ensure that risk factor exposures are not a result of decisions
made by index providers but are a function of deliberate investor choice.
Conclusions
No one size fits all: the needs and objectives of asset owners differ dramatically. There is
understandable frustration about the unwanted exposures that market cap benchmarks impose on
equity portfolios managed against them.
Given cap-weighted structures are highly liquid and have low turnover; a move away from them
should only be implemented once investors are fully convinced that the proposed solution will
sustainably overcome existing challenges. These include over concentration, systematic size,
momentum and growth biases.
The first round of smart beta strategies and alternative benchmarks have been heavily criticised for
their lack of transparency, which has made it difficult for investors to make a full appraisal of their
sources of value. Whilst such approaches have overcome some of the limitations of cap-weighted
indices they have tended to deliver alternative simple static exposures. Reconciling such factor tilts
with long-run investment objectives is a challenge. One way to do this would be to allocate assets
across several strategies in a dynamic fashion, which itself would be a complicated task.
The drawbacks of both cap-weighted benchmarks and the first generation of alternatives may be
overcome with an unconstrained investment approach or a systematic process that uses stock
selection deliberately to offset unwanted exposures associated with a portfolio weighting scheme.
Ultimately all novel options will be judged on an opportunity cost basis versus market cap indices
and must deliver superior risk-adjusted returns in the medium to long term if they are to be
successful.
13
Further reading and references
Amenc, N., F. Goltz, A. Lodh, and L. Martellini, Spring 2012, ―Diversifying the Diversifiers and
Tracking the Tracking Error: Outperforming Cap-Weighted Indices with Limited Risk of
Underperformance‖, The Journal of Portfolio Management, 38 (3), 72-88.
Amenc, N., F. Goltz, and A. Lodh, 2012, ―Choose Your Betas: Benchmarking Alternative Equity
Index Strategies‖, Journal of Portfolio Management, 39 (1), 88-111.
Amenc, N., F. Goltz, L. Martellini, and P. Retkowsky, 2011, ―Efficient Indexation: An Alternative to
Cap-Weighted Indices‖, Journal of Investment Management, 9 (4), 1-23.
Ang, A., R. J. Hodrick, Y. Xing, and X. Zhang. 2006, "The cross-section of volatility and expected
returns", Journal of Finance, 61 (1), 259-99.
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