focus: volatility - msci

FOCUS: VOLATILITY

Factor Investing

msci.com

2 | MSCI.COM

FACTOR INVESTING

FACTOR FOCUS: VOLATILITY

Tactical investors have used MSCI Minimum Volatility Indexes to

reduce risk during market downturns, while retaining exposure

to equity. Strategic investors have recognized (1) the benefits

of minimum volatility strategies in asset allocation and (2) that

minimum volatility strategies have tended to outperform high

volatility strategies on a risk-adjusted basis in the long run.

There are several behavioral explanations for the minimum

volatility premium, which was identified in the early 1970s by

economist Fischer Black and elaborated on by others since then

(see sources below). One theory posits that investors underpay

for low volatility stocks, viewing them as less rewarding,

and overpay for high volatility stocks that are seen as long-

shot opportunities for higher returns. A secondary academic

explanation holds that investors can be overconfident in their

ability to forecast the future, and that their opinions differ more

for high volatility stocks, which have less certain outcomes,

leading to higher volatility and lower returns.

In terms of methodology, the main approaches to implementing a

minimum volatility strategy fall into two groups: (1) simple rank

and selection and (2) optimization-based solutions.

A simple approach ranks the universe of stocks by their expected

volatility, selects a subset of the constituents from the universe

and then applies a weighting method. These approaches generally

ignore the correlation between stock returns, which can have a

significant impact on the overall volatility strategy.

While a simple rank and selection method reflects the volatility

DEFINING VOLATILITY

WHY INSTITUTIONAL INVESTORS HAVE USED MINIMUM VOLATILITY STRATEGIES

A minimum volatility strategy involves buying stocks based on

the estimate of their volatility and correlations with other stocks.

Minimum volatility is categorized as a “defensive” factor, meaning

it has tended to benefit during periods of economic contraction (see

“Performance and Implementation”). This type of strategy is more

concerned with volatility management than with maximizing gains.

Paradoxically, the strategy has produced a premium over the market

for long periods, contravening the principle that investors should not

be rewarded with higher risk-adjusted returns for taking less than

market risk.

The key objective of a minimum volatility strategy is to capture

regional and global exposure to stocks with potentially less risk.

Historically, the MSCI Minimum Volatility Indexes, for example, have

realized lower volatility and lower drawdowns (peak-to-trough

declines) relative to their parent index during significant market

downturns.

IN THE REALM OF INVESTING, A FACTOR IS ANY CHARACTERISTIC THAT HELPS EXPLAIN THE LONG-TERM RISK AND RETURN PERFORMANCE OF AN ASSET. MSCI FACTOR INDEXES ARE DESIGNED TO CAPTURE THE RETURN OF FACTORS WHICH HAVE HISTORICALLY DEMONSTRATED EXCESS MARKET RETURNS OVER THE LONG RUN.

MSCI Factor Indexes are rules-based, transparent indexes targeting stocks with favorable factor

characteristics – as backed by robust academic findings and empirical results – and are designed for

simple implementation, replicability, and use for both traditional passive and active mandates.

MSCI.COM | 3

FACTOR FOCUS: MINIMUM VOLATILITY

of individual stocks, optimization-based approaches account for

both volatility and correlation effects, i.e., the magnitude and

the degree to which stocks move in tandem. However, a naive

unconstrained minimum volatility strategy has its own set of

challenges, such as biases toward certain sectors and countries,

unwanted factor exposures and potentially high turnover

at rebalancing. Well-designed optimizations with carefully

constructed constraints, however, may be able to neutralize these

shortcomings.

The MSCI Minimum Volatility Indexes are calculated by using an

optimization designed to produce an index with the least overall

volatility with a given set of sector, country, and factor constraints

in addition to ensuring index replicability and investability.

For illustration purposes, the chart below compares the sector

exposure of a constrained minimum volatility index to that of an

unconstrained index. Without these constraints, we see large

biases toward consumer staples and utilities.

THE EXPOSURES OF CONSTRAINED VS. UNCONSTRAINED

MINIMUM VOLATILITY STRATEGIES

To see how a constrained minimum volatility index performed,

we can look at the MSCI World Minimum Volatility Index (WMVI)

backtested over the 26-year period to May 2014 (chart below),

which includes four bear markets (defined here as a decline of

20% or more in the parent MSCI World Index that lasts for at least

two months).

The WMVI posted significantly lower drawdowns and lower

realized volatility than its parent index during these downturns.

This index also outperformed a negative market 88% of the time,

by an average of 8.8 percentage points based on rolling one-year

periods. In cases where the index underperformed the market, the

average shortfall was only 1.24 percentage points.

In years when market return exceeded 10%, the WMVI

underperformed, as one would expect, and the gap widened with

increasing market returns. However, for more moderate positive-

return periods (defined as 10% or less), the WMVI outperformed

the market 67% of the time.

As shown below, the WMVI returned about 80% during its first

eight years, through April 2016, while the market gained about

40%. The index’s volatility over this period (calculated using

monthly returns) was 12.5%, compared with 17.6% for the parent

index, a roughly 30% reduction.

The universe of stocks is the MSCI World Index as of Nov. 25, 2014, constrained only to prohibit short positions (bets that prices will fall) and to keep sector exposures within 5 percentage points of the parent-index weighting.

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Bear Markets MSCI World MinVol/MSCI World (lhs) MSCI World (rhs)

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7.70%9.16%

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12.50%11.56%

14.64% 15.21%

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2.09%3.39%

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Decile 1 Decile 2 Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 10

Annualized Return CAPM adj. Premium

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8.37% 8.49%

7.60% 7.75%7.04%

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ROE Quality EV D/E

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92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14HIGH SIZE LOW SIZE

THE MSCI WORLD MINIMUM VOLATILITY INDEX HAS HISTORICALLY

PROVED LESS VOLATILE THAN ITS PARENT INDEX

THE MSCI WORLD MINIMUM VOLATILITY INDEX OUTPERFORMED ITS

PARENT IN THE EIGHT YEARS AFTER ITS LAUNCH

MSCI World Minimum Volatility (USD) was launched on April 14, 2008.

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7.70%9.16%

10.14%11.62%

12.50%11.56%

14.64% 15.21%

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ROE Quality EV D/E

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4 | MSCI.COM

FACTOR INVESTING0

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WORLD

WORLD EQUAL WEIGHTED

WORLD MINIMUM VOLATILITY (USD)

WORLD RISK WEIGHTED

WORLD HIGH DIVIDEND YIELD

WORLD MOMENTUM

WORLD QUALITY

WORLD VALUE WEIGHTED

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

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Over time, individual factors have delivered outperformance relative to the market (see chart below).

From a longer-term perspective, the chart below shows that the MSCI Minimum Volatility Index (represented by the MSCI Top 300

Volatility Tilt prior to 1988 and by the MSCI Minimum Volatility Index afterwards) generated an annualized return of approximately

11% during a 40-year period. In contrast to the other key factors MSCI has identified, the MSCI Minimum Volatility Index has realized

significantly lower risk relative to the parent index.

Although factor strategies have exhibited long-term outperformance, in the short-term factor performance has been cyclical and has

generated periods of underperformance.

PERFORMANCE & IMPLEMENTATION

15%

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11% 12% 13% 14% 15% 16% 17%

Annualized Risk

Annu

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Volatility

Yield

Quality

Momentum

Value

Size

MSCI World

MSCI WORLD FACTOR INDEXES

LONG-TERM PERFORMANCE: JANUARY 1976 TO DECEMBER 2016

World MomentumWorld Equal Weighted (Size)

World Minimum VolatilityWorld QualityWorld High Dividend Yield

World Value WeightedWORLD

MSCI.COM | 5


HOW THE SIX FACTORS HAVE PERFORMED RELATIVE TO EACH OTHER: VOLATILITY

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

45.6% 1.5% -4.5% -9.6% 56.7% 28.6% 28.4% 31.0% 19.9% -29.2% 42.0% 18.2% 8.0% 16.7% 32.7% 12.1% 5.8% 10.3%

40.1% 1.2% -8.0% -9.8% 50.4% 24.1% 17.2% 28.9% 16.8% -33.5% 41.9% 16.5% 4.8% 16.5% 30.3% 9.0% 4.5% 9.4%

25.3% 0.3% -10.0% -13.6% 33.8% 21.3% 15.2% 22.1% 10.3% -39.9% 33.8% 12.8% 4.8% 15.0% 27.7% 7.0% 4.2% 8.9%

20.5% -2.1% -11.5% -14.4% 30.5% 20.8% 10.0% 21.2% 9.6% -40.3% 33.5% 12.3% 4.4% 14.8% 27.4% 5.5% -0.3% 8.2%

18.4% -10.2% -12.1% -15.1% 26.0% 20.0% 8.5% 20.7% 7.3% -41.9% 30.8% 11.4% -5.0% 13.7% 26.5% 4.6% -1.0% 8.2%

8.6% -12.9% -16.5% -16.5% 25.9% 15.2% 8.3% 19.1% 6.4% -42.4% 17.2% 9.1% -9.3% 13.3% 22.9% 3.4% -2.4% 5.1%

8.4% -18.9% -20.5% -19.5% 22.0% 12.7% 6.0% 16.8% 6.1% -42.6% 14.8% 7.2% -11.0% 8.9% 19.4% 3.3% -2.7% 4.7%

ValueYield Momentum WorldSizeVolatility Quality

The analysis and observations in this report are limited solely to the period of the relevant historical data, backtest or simulation. Past performance — whether actual,

back tested or simulated — is no indication or guarantee of future performance. None of the information or analysis herein is intended to constitute investment advice or a

recommendation to make (or refrain from making) any kind of investment decision or asset allocation and should not be relied on as such.

The time periods covered in the charts in this paper were dictated by the data available when we conducted the simulations which produced them.

There are frequently material differences between backtested or simulated performance results and actual results subsequently achieved by any investment strategy

6 | MSCI.COM

FACTOR INVESTING

Data from November 28, 1975 to September 30, 2016.

Sharp decline Moderate decline Moderate uptick Sharp uptick

Volatility Yield Quality Momentum Value Size

Qua

rter

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elat

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Ret

urn

(Ave

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)

2%

1%

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0%

Defensive Factors Pro-cyclical FactorsPersistence

MACRO EFFECTS ON FACTOR PERFORMANCE

Sharp decline Moderate decline Moderate uptick Sharp uptick

The Composite Leading Indicator used here, designed

to provide early-warning signals on business-cycle

turning points, is an aggregate time series displaying

a reasonably consistent leading relationship with the

reference series for the macroeconomic cycle

75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15

102.5

100.00

97.5

95.0

In general, factor performance has been cyclical in nature.

Individual factors have been shown to outperform during different

macroeconomic environments. As the charts on this page illustrate,

the minimum volatility factor falls into the “defensive” category,

meaning that this type of strategy historically outperformed during

declining market conditions over the study period.

While categorized as “defensive” when looking at the cyclicality of

factor performance, minimum volatility indexes have been considered

as a core holding due to their long-term risk/return profile, as

demonstrated in Long-term Performance chart on p4.

MSCI.COM | 7


CONCLUSION

Minimum volatility is one of the few factors that have performed well in turbulent markets,

serving as a means of capital preservation. Moreover, over long periods of time, this defensive

strategy has produced a premium over the market, contravening one of the most basic

theories in finance — that one should not be rewarded with greater returns for taking less than

market risk.

While naïve minimum volatility indexes may have unintended exposures to other factors,

optimization based minimum volatility strategies have been calibrated to achieve targeted

levels of country, sector and style exposure without significantly increasing volatility risk itself.

The MSCI USA Minimum Volatility Indexes aim to reflect the performance characteristics of a

minimum volatility strategy by optimizing towards the lowest absolute risk within a given set

of constraints to minimize unintended risks and exposures.

Alighanbari, M., R.A. Subramanian and P. Kulkarni. (2014). “Factor

Indexes in Perspective: Insights from 40 Years of Data.” MSCI

Research Insight.

Ang, A., R. Hodrick, Y. Xing and X. Zhang. (2006). “The Cross-

Section of Volatility and Expected Returns.” Journal of Finance,

Vol. 61, No. 1, pp. 259-299.

Baker, N.L. and R.A. Haugen. (2012). “Low Risk Stocks Outperform

Within All Observable Markets of the World.” Available at http://

ssrn.com/abstract=2055431.

Black, F. (1972). “Capital Market Equilibrium with Restricted

Borrowing.” Journal of Business, Vol. 45, No.3, pp. 444-455.

Blitz, D. and P. Van Vliet. (2007). “The Volatility Effect: Lower Risk

Without Lower Return.” Journal of Portfolio Management, Vol. 34,

No. 1, pp. 102-113.

Clarke, R., H. De Silva and S. Thorley. (2006). “Minimum-Variance

Portfolios in the U.S. Equity Market.” Journal of Portfolio

Management, Vol. 33, pp. 10-24.

Jagannathan, R. and T. Ma. (2003). “Risk Reduction in Large

Portfolios: Why Imposing the Wrong Constraints Helps.” Journal

of Finance, Vol. 58, No. 4, pp. 1651-1684.

Nielsen, F. and R.A. Subramanian. (2008). “Far From the Madding

Crowd – Volatility-Efficient Indexes.” MSCI Barra Research Insight.

Sefton, J., D. Jessop, G. De Rossi, C. Jones and H. Zhang. (2011).

“Low-Risk Investing.” UBS Research.

Vangelisti, M. (1992). “Minimum-Variance Strategies: Do They

Work?” Barra Newsletter.

REFERENCES

VOLATILITY

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