EMU Managed Volatility

1. Part of State Street’s Vision Thought Leadership Series
SSgA CAPITALINSIGHTS EXCHANGE
EMU Managed Volatility
A ‘managed volatility’ approach seeks to provide competitive
returns and maintain low volatility, in each case compared to the
specified benchmark index, over the long term by constructing
a portfolio of stocks with low expected volatility relative to the
Index. We have tested the strategy in the EMU zone and find
that the Sharpe ratio and risk adjusted return are improved.
The Relationship Between Risk and Return
Markovitz’s theory of mean-variance optimisation1
and
Sharpe’s Capital Asset Pricing Model (CAPM)2
are two of
the most influential papers on investment theory to have
been published in the last century. Both papers model the
relationship between expected investment return and risk,
the key message being that there is no free lunch in the
investment world: the more risk you take on, the higher the
expected return.
According to Sharpe, in equilibrium, security prices adjust so
that expected return is an increasing linear function of risk
(with the risk of a security measured by its beta – exposure
to the market capitalisation-weighted portfolio). Yet Sharpe’s
finding has been challenged by empirical evidence: risk is not
perfectly correlated with returns and higher-risk (higher-beta)
stocks have actually not delivered higher average returns
over time.
1. Markowitz, H.M. (1952) Portfolio Selection.
2. Sharpe, W.F. (1964) Capital Asset Prices: A Theory of Market Equilibrium
Under Conditions of Risk.
Like Sharpe, Markovitz also believed that equity returns
increase with risk. As shown in Chart 1, Markovitz developed
a ‘mean-variance’ framework in which efficient portfolios
maximise expected return for any given level of risk (volatility).
A significant drawback of this model is that efficient portfolios
tend to be highly sensitive to input data i.e. the expected
return of each individual asset class and the covariance matrix
(which captures how assets are expected to move relative to
one another). As a result, minor changes in inputs can lead to
significant changes in the composition of the efficient portfolio.
Chart 1: Markovitz’s Efficient Frontier
Most efficient portfolios are highly sensitive to input data.
However, calculating expected returns is a difficult exercise
that can result in significant estimation errors. In contrast, risk
models tend to exhibit smaller and less frequent differences
between estimated and actual outcomes.
One portfolio on Markovitz’s efficient frontier – the ‘minimum
variance’ portfolio – does not require expected returns as an
input parameter. Instead it relies only on risk characteristics,
which are generally easier to forecast than expected returns.
This portfolio therefore uses the most reliable data in the
Markowitz framework.
Co-authored by: Selim Dekali Portfolio Manager, Index Equity
Frédéric P. Jamet Head of Investments, SSgA France
Return
Risk
Market Portfolio
Minimum-Variance Portfolio

2. SSSSSSggAA CACAPIPITATALL ININSISIGHGHTSSTS ||| EMU MANAGED VOLATILITY
Why Adopt a Managed Volatility Approach?
In the recent financial crisis, investors clearly demonstrated
their asymmetric risk tolerance to negative returns (i.e. higher
aversion to downside risk). In response to these heightened
concerns, strategies that seek to limit the downside risk in
investment portfolios, while still maintaining potential returns,
have become increasingly popular.
In the context of controlling risk independently from
returns, the managed volatility portfolio is an appealing
investment approach.
Managing volatility in eurozone portfolios is a particularly
interesting case given the absence of currency risk and thus
the need to quantify that risk in the investment process.
Simulating a Managed Volatility Strategy1
We conducted a simulation to compare the returns and
volatility of a managed volatility portfolio with those of the
market-cap-weighted MSCI EMU Index for the period
1999–2010. For the managed volatility portfolio we set
the following parameters:
25% Maximum absolute sector weight
10% Maximum absolute industry weight
2% Maximum holding on trade initiation
2.5% Maximum holding cap
20% Average daily volume constraint on trades
3% Country exposure deviation relative to the benchmark
As shown in Chart 2, the managed volatility portfolio (EMU
Managed Volatility) is shown to generate a higher Sharpe Ratio
for the period studied. The managed volatility portfolio recorded
volatility more than 28% lower than that of the index and
provided competitive risk adjusted return compared to the index.
Chart 2: Higher Returns and Lower Volatility from an Absolute
Approach to Managed Volatility Investing
The simulation time frame includes some particularly
interesting periods, as shown in Chart 3. During the technology
(‘dot.com’) bubble in 1999–2002, the managed volatility
strategy’s participation to both the upside and the downside
was significantly less relative to the MSCI EMU Index. As such,
risk, as measured by volatility, was reduced.
It is important to understand that while the return of a managed
volatility strategy has the potential to be materially greater than
the cap-weighted equity benchmark over certain periods,
particularly those periods consisting of multiple bear markets
such as those experienced during the first decade of the 21st
century, investors should not expect the return to be materially
greater than the cap-weighted benchmark over the long term.
2
28%
4%
24%
-18%
-33%
20%
13%
26%
23%
-45%
3%
31%
-34%
15%
7%
-7%
-17%
21%
32%
11%
30%
-1%
36%
10%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Percentage
EMU Managed Volume
MSCI EMU
Chart 3: Simulated Managed Volatility Portfolio – Performance Over Time
EMU Managed
Volatility
MSCI
EMU Index
Difference
1 Year Return 10.77% 2.77% 8.00%
3 Years Return -3.10% -9.70% 6.60%
5 Years Return 4.43% -0.21% 4.64%
12 Years Return
(Since Inception)
7.63% 1.96% 5.67%
Volatility 16.52% 23.19% -6.67%
Volatility
Reduction
– – -28.77%
Sharpe Ratio 0.27 -0.05 0.32
Source: Axioma, SSgA, Performance in Euro

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This material is for your private information.
The views expressed are the views of State Street Global Advisors only through the period
ended 1 July 2011 and are subject to change based on market and other conditions. The
information we provide does not constitute investment advice and it should not be relied on
as such. It should not be considered a solicitation to buy or an offer to sell a security. It does
not take into account any investor’s particular investment objectives, strategies, tax status or
investment horizon. We encourage you to consult your tax or financial advisor. All material
has been obtained from sources believed to be reliable, but its accuracy is not guaranteed.
There is no representation or warranty as to the current accuracy of, nor liability for, decisions
based on such information. This document contains certain statements that may be
deemed forward-looking statements. These statements are based on certain assumptions
and analyses made by SSgA in light of its experience and perception of historical trends,
current conditions, expected future developments and other factors it believes appropriate
in the circumstances. Past performance is no guarantee of future results.
MSCI Indices are trademarks of MSCI, Inc.
©2011 State Street Corporation EUMKT-1049 Exp. Date: 07/31/2012
Chart 4 shows that, as expected, the simulated portfolio
is biased towards stocks with a low beta (given their lower
volatility than high beta stocks). Over the simulation time frame,
the portfolio’s beta ranges between 0.5 and 0.8. As at the end
of December 2010, the portfolio was overweight in Health Care
and Consumer Staples (i.e. defensive stocks) and underweight
in Materials (i.e. cyclical stocks).
Conclusion
For investors in the eurozone equity markets, risk-reduction
strategies based on the concept of managed volatility hold a
number of attractions. Given their objective of limiting downside
risk, they may be particularly appealing as the growth portfolio
of a broader liability-driven investment solution.
Investors have shown considerable interest in strategies that
focus on risk reduction. The simulation of an EMU managed
volatility portfolio versus the MSCI EMU Index featured provide
interesting results for the period studied on a risk and risk-
adjusted return basis.
SSSSSSggAA CACAPIPITATALL ININSISIGHGHTSSTS ||| EMU MANAGED VOLATILITY
0% 10% 20% 30% 40% 50% 60%
1 (1.85)
2 (1.45)
3 (1.35)
4 (1.2)
5 (1.05)
6 (0.95)
7 (0.9)
8 (0.85)
9 (0.75)
10 (0.45)
BetaDecile
EMU Managed Volume MSCI EMU
Chart 4: Decile of Beta Exposure of Simulated EMU Managed
Volatility and MSCI EMU (as of December 2010)
Axioma European Fundamental Factor Risk Model
Source: Axioma, SSgA
DISCLAIMER
1
Europe Managed Volatility Performance:
Returns are simulated from January 4, 1999 to December 31, 2010 and assume 30bp transaction costs each way. Turnover was approximately 20% annually (one-way), with quarterly rebalancing.
The results shown do not represent the results of actual trading using client assets but were achieved by means of the retroactive application of a model that was designed with the benefit of
hindsight. The simulated performance was compiled after the end of the period depicted and does not represent the actual investment decisions of the advisor. These results do not reflect the effect
of material economic and market factors on decision making.
The simulated performance data is reported on a gross of fees basis, and gross of administrative costs. Additional fees, such as the advisory fee, would reduce the return. For example, if an
annualized gross return of 10% was achieved over a 5-year period and a management fee of 1% per year was charged and deducted annually, then the resulting return would be reduced from 61%
to 54%. The performance includes the reinvestment of dividends and other corporate earnings and is calculated in Euro.
The simulated performance is not necessarily indicative of future performance, which could differ substantially. The benchmark used is the MSCI Europe Index. The index returns are unmanaged
and do not reflect the deduction of any fees or expenses. The index returns reflect all items of income, gain and loss and the reinvestment of dividends and other income. All trademarks are property
of their respective owners.
The strategy described may be executed in a commingled fund managed by SSgA which is not insured by the FDIC or by another governmental agency; it is not an obligation of the FDIC nor is it
a deposit or obligation of or guaranteed by State Street Bank and Trust Company. All SSgA commingled funds pay State Street Bank and Trust Company for services as custodian, transfer agent,
and shareholder servicing agent and may pay affiliates of State Street Bank and Trust Company for investment advisory services.
Not all products will be available to all investors, please contact SSgA for further information regarding this strategy.
The performance information should not be shown without these accompanying notes.
Backtest Creation: The testing methodology used the Axioma European Fundamental Factor Risk Model, and Axioma optimization model to generate historical portfolios. The data used was only
that data which would have been available at the time when the historical portfolios were generated, not what is available now. These processes help to eliminate various forms of survivorship bias,
both in terms of a “smarter model” and in terms of making decisions based on information that was not available at the time.
Quarterly portfolios were created, and returns are the result of a buy and hold assumption on each of these portfolios. Transaction costs were assumed as stated above.
This Europe Managed Volatility process was backtested in May 2011.