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Low Volatility Investing from a Fundamental Perspective

Mark Ingham31 May 2012

1GMOMI_DiscMatls_CFAconf_5-12

Proprietary information – not for distribution. Copyright © 2012 by GMO LLC. All rights reserved.

OutlineIntroduction

Risk seems to be backwards

– behavioural factors are big drivers of this

– but not the only drivers...

Fundamental risk and quality characteristics also work backwards

On some dimensions low fundamental risk is more attractive than low trailing return risk:

– payoff structure

– liquidity

– valuation



Low Volatility – What a Backtest!

Source: GMO As of 5/15/12Note: High Beta = Top 25% of Beta by Market Cap in Top 1000 U.S. Equities and Low Beta = Bottom 25% of Beta by Market Cap in Top 1000 U.S. Equities.

0.5

1

2

4

8

16

32

64

128

1964 1969 1974 1979 1984 1989 1994 1999 2004 2009

Cum

ulat

ive

Ret

urn

High Beta

Low Beta



This Isn’t a New Phenomenon

Source: GMO As of 5/15/12Note: High Beta = Top 25% of Beta by Market Cap in Top 1000 U.S. Equities and Low Beta = Bottom 25% of Beta by Market Cap in Top 1000 U.S. Equities.

0.1250.25

0.51248

163264

128256512

102420484096

1927 1934 1941 1948 1955 1962 1969 1976 1983 1990 1997 2004 2011

High Beta

Low Beta

Cum

ulat

ive

Ret

urn



This Isn’t a U.S. Phenomenon

Source: GMO As of 7/31/11Note: Global High Beta = Top 25% of Beta by Market Cap in Top 2000 Global Equities and Global Low Beta = Bottom 25% of Beta by Market Cap in Top 2000Global Equities.

0.5

1

2

4

8

16

32

84 86 88 90 92 94 96 98 00 02 04 06 08 10

Global High Beta

Global Low Beta

Dec-

Cum

ulat

ive

Ret

urn



This Isn’t an Equity Phenomenon

Source: Frazzini and Pederson “Betting against Beta

Note: Results here are taken from Frazzini and Pederson “Betting against Beta.” To construct the BAB factor, all instruments are assigned to one of two portfolios: low beta and high beta. Instruments are weighted by the ranked betas and the portfolios are rebalanced every calendar month. Both portfolios are rescaled to have a beta of 1 at portfolio formation. The BAB factor is a zero-cost portfolio that is long the low-beta portfolio and shorts the high-beta portfolio.

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

U.S

. Sto

cks

Aust

ralia

Aust

ria Belg

ium

Can

ada

Switz

erla

ndG

erm

any

Den

mar

kSp

ain

Finl

and

Fran

ceU

nite

d K

ingd

omH

ong

Kong

Italy

Japa

nN

ethe

rland

sN

orw

ayN

ew Z

eala

ndSi

ngap

ore

Swed

enG

loba

l Sto

cks

(all)

Cre

dit I

ndic

esC

orpo

rate

Bon

dsC

redi

t Hed

ged

(CD

S)Tr

easu

ries

Equi

ty In

dice

sC

ount

ry B

onds

Fore

ign

Exc

hang

eC

omm

oditi

esAnnu

alis

ed S

harp

e Rat

io o

f BAB

Fac

tor



And Pretty Much the Same Phenomenon as MVP

Source: GMO As of 7/31/11Note: MVP = Minimum volatility portfolio, High Beta = Top 25% of Beta by Market Cap in Top 1000, Low Beta = Bottom 25% of Beta by Market Cap in Top 1000.

0.5

1

2

4

8

16

32

64

128

69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09

High Beta

Low Beta

Dec-

MVP

Cum

ulat

ive

Ret

urn



Behavioural or People are weak and stupid!Why Risk Is Backwards

Career Risk

– Benchmark huggers run the risk of picking high volatility, low return stocks in order to keep tracking error down.

Glamour Stocks

– High volatility tends to be associated with exciting growth stories. The chance of this growth not materialising is generally underappreciated.

Lottery Love

– Investors like positive skew, just as they overpay for lottery tickets.



Lottery LoveThe favourite long-shot bias

Source: Snowberg and Wolfers (2010)

BreakEven

-20

-40

-60

-80

Rat

e of

Ret

urn

per D

olla

r Bet

(%)

1/3 1/2 Evens 2/1 5/1 10/1 20/1 50/1 100/1 200/1Odds (Log Scale)

Sample: U.S. Horse Races, 1992-2001Raw Data: Aggregated into PercentilesAll RacesSubsample: Exotic Betting Data AvailableSubsample: Last Race of the Day



Behavioural or People are weak and stupid!Why Risk Is Backwards

Career Risk

– Benchmark huggers run the risk of picking high volatility, low return stocks in order to keep tracking error down.

Glamour Stocks

– High volatility tends to be associated with exciting growth stories. The chance of this growth not materialising is generally underappreciated.

Lottery Love

– Investors like positive skew, just as they overpay for lottery tickets.

Implicit leverage High beta can give additional exposure to investors who want

to go extra-long but can’t (or won’t) take on leverage



Not All Leverage Is Created EqualBeta is leverage, but beta’s leverage is “zero recourse”

Source: GMO

-200

-150

-100

-50

0

50

100

150

200

250

-100 -50 0 50 100

Theo

retic

al R

etur

n

Market Return

MarketLevered MarketBeta = 2



-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

-40%-30%-20%-10% 0% 10% 20% 30%

High

Bet

a Re

turn

Market Return

High Beta

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

-40%-30%-20%-10% 0% 10% 20% 30%

Low

Bet

a Re

turn

Market Return

Low Beta

Not All Leverage Is Created EqualIt’s not just about leverage, it’s about convexity

Beta ~ 2

Beta Converging to 1

Beta ~ 0.5

Note: Return = 20-Day Rolling Compound Return; Market = Top 1000 U.S. Equity Stocks by Market Capitalization; High Beta = Top 25%of Beta by Market Cap in Top 1000 U.S. Equities and Low Beta = Bottom 25% of Beta by Market Cap in Top 1000 U.S. Equities.



Not All Leverage Is Created EqualIn down markets, correlations go to 1

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Market Down5% or More

Market Between-5% and 5%

Market Up5% or More


Low Beta Portfolio

High Beta Portfolio

Realized Betas



Leverage Convexity / Concavity

High beta has a convex payoff.

– The bigger the market return, the higher the “beta.”

– Looks like a call option (or, at least, a stock plus a call).

Conversely, low beta has a concave payoff with a greater sensitivity to down markets than up

Convex payoffs are good, and good things are rarely free

Concave payoffs are bad, and you should be paid to take them



Mitigating Concavity

Can one maximise the behavioural aspects of low volatility investing whilst minimising concavity (or have your cake and eat it?)

YES!

– Reassess risk



Three routes to the permanent impairment of capital:

Real Risk Is Losing Your Money!

Fundamental risk

– “Real risk is measured not by the percent that a stock may decline in price in relation to the general market in a given period, but by the danger of a loss of quality and earnings power through economic change or deterioration in management.” — Ben Graham

Financing risk

– Leverage – “An investor who proposes to ignore near-term market fluctuations needs greater resources for safety and must not operate on so large a scale, if at all, with borrowed money.” — Maynard Keynes

Price risk

– Buying overvalued assets dooms you to low long run returns



Fundamental Risk…also seems backwards – high quality seems to pay!

2.4%

-2.8%

2.2%

-2.4%

1.8%

-1.7%

1.2%

-1.1%

0.7%

-1.6%

CombinedQuality* BetaLeverage Profitability

ProfitVolatility

MSCI EAFE

Low RiskStocks

High RiskStocks

LowHighLow

High Low

HighLowHigh Low High

EAFE

Source: GMO annualized data from 1/79 – 12/11

1.7%

-4.3%

2.9%

-5.5%

1.8%

-3.7%

2.1%

-4.7%

1.6%

-3.7%

Low RiskStocks

High RiskStocks

LowHighLow High Low

HighLowHigh Low High

Small Combined Quality* Small Beta

SmallLeverage

SmallProfitability

Small ProfitVolatility

U.S. Small Cap

Small Cap

* Leverage, profitability and profit volatility Note: GMO defines quality companies as those with high profitability, low profit volatility, and minimal use of leverage. Simulated relative returns of a hypothetical portfolio.

Source: GMO annualized data from 1/85 – 12/11



-6%

-4%

-2%

0%

2%

4%

6%

Rela

tive

Prof

itabi

lity

(RO

E)

Years

U.S. Quality U.S. Low Quality Realized U.S. Quality Realized U.S. Low Quality

After 30 years the high quality quartile is almost twice as profitable.

1975Highest Quality Quartile

IBM Eastman Kodak Co. Procter & Gamble Co. 3M Co.Wyeth Merck & Co., Inc. Johnson & Johnson Coca-Cola Co.Xerox Corp. Eli Lilly & Co. J.C. Penney Co., Inc. Warner-Lambert Co.Schering-Plough Corp. Hewlett-Packard Co. Federated Dept. Stores Bristol-Myers Squibb Co.Avon Products Inc. Emerson Electric Co. Pfizer Inc. PepsiCo, Inc.Kellogg Co. General Foods Corp. CBS Inc. Carnation Co.

Note: Profitability = Return On Equity Source: GMO, U.S. 1965-2010; Realized GMO 2004-31/10/11The securities identified above represent a selection of securities identified by the GMO quantitative model. These specific securities are selected for presentation by GMO based ontheir underlying characteristics and are not selected on the basis of their investment performance. These securities are not necessarily representative of the securities purchased, sold orrecommended for advisory clients, and it should not be assumed that the investment in the securities identified will be profitable.

Quality Characteristics PersistContrary to economic theory, quality exhibits a sustainable competitive advantage

1975Lowest Quality Quartile

0 3 6 9 12 15 18 21 24 30

United States Steel Corp. Atlantic Richfield Co. Standard Oil Co. Tenneco Inc.CitiCorp International Paper Co. American Electric Power Unicom Corp.Pharmacia Corp. Union Pacific Corp. Amax Inc. Bethlehem Steel Corp.Morgan (JP) & Co. Southern Co. Alcoa Inc. Aetna Inc.BCE Inc. Unocal Corp. Ford Motor Co. RCA Corp.ConocoPhillips BankAmerica Corp.



Source: GMO

Quality, the Market and Low Volatility during Historic Downturns

Market Quality Min vol Dates Name Duration (months)-71% N/A -68% Jan-29 toJan-32 Great Depression 36-48% N/A -45% Feb-37 to Mar-38 Echo of above 13-22% N/A -20% May-46 to Nov-46 Post-WWII 6-23% N/A -20% Dec-61 to Jun-62 Kennedy Break 6-29% -19% -30% Dec-68 to Jun-70 GGM meltdown* 18-44% -46% -37% Jan-73 to Sep-74 First Oil Shock 20-19% 11% 13% Nov-80 to Jul-82 Second Oil Shock 20-28% -27% -22% Sep-87 to Nov-87 Black Monday 2-15% -10% -13% May-90 to Oct-90 S & L crisis 5-16% -12% -11% Jun-98 to Aug-98 LTCM 2-46% -39% 7% Mar-00 to Sep-02 TMT meltdown 30-50% -37% -34% Oct-07 to Feb-09 Financial crisis 16

*Great Garbage Market



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-10%

0%

10%

20%

30%

40%

50%

-40%-30%-20%-10% 0% 10% 20% 30%

Low

Bet

a Re

turn

Market Return

Low Beta

Concavity / Convexity of Low Beta and QualityFlight to Quality NOT flight to Low Beta!


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-10%

0%

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20%

30%

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-40% -30% -20% -10% 0% 10% 20% 30%

Hig

h Q

ualit

y R

etur

n

Market Return

High Quality



Concavity / Convexity of Low Beta, Quality and MVP…and, on average, low beta




Mitigating Concavity

Can one maximise the behavioural aspects of low volatility investing whilst minimising concavity (or have your cake and eat it?)

YES!

– Reassess risk

– Extend investment horizon



Convexity Is a Shorter-Term PhenomenonConvexity over different return horizons

-1.0

-0.5

0.0

0.5

1.0

1.5

1 day 1 week 1 month 1 quarter 2 quarters 3 quarters 4 quarters

Con

vexi

ty

high betalow beta

Notes: High Beta = Top 25% of Beta by Market Cap in Top 1000 U.S. Equities and Low Beta = Bottom 25% of Beta by Market Cap in Top 1000 U.S. Equities. Convexity is the coefficient of the quadratic term from a quadratic fit of high beta and low beta returns against the market for different return horizons. Data is from 01-Jan-1966 to 30-Apr-2012



Deleveraging can drive correlations to 1


Fundamental risk


Financing risk


Price risk




$0

$10

$20

$30

$40

$50

$60

$70

1/04 5/04 9/04 1/05 5/05 9/05 1/06 5/06 9/06 1/07 5/07 9/07

Source: GMO As of 30/9/07

Tota

l Ass

ets

($ B

illio

ns) i

n H

igh

Ow

ners

hip

Gro

up

24x Growth

$61 Billion

$2.5 Billion

August 2007 – Correlations Going to 1USD value of coincident holdings of 8 prominent quants



Qua

nt L

ong/

Shor

t Per

form

ance

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

1/04 5/04 9/04 1/05 5/05 9/05 1/06 5/06 9/06 1/07 5/07

Source: GMO, LionShare As of 31/8/07

3 Years of Returns Were Wiped Out in 3 DaysQuant became the risk factor

The above illustrate a hypothetical strategy that GMO does not manage. Hypothetical returns are not predictive of future allocations. The results reflect returns an investor would have obtained had they investedin this hypothetical strategy during the time periods shown and do not represent actual returns. Hypothetical returns are calculated by the retroactive application of a model constructed on the basis of historicaldata and based on assumptions integral to the model which may or may not be testable. In the above, we aggregated reported holdings from eight quantitative managers identified by GMO to come up with a long/short portfolio.Changes in these assumptions may have a material impact on the hypothetical returns presented. Certain assumptions have been made for modeling purposes and are unlikely to be realized. No representations and warranties are made as to the reasonableness of the assumptions. Hypothetical returns are developed with the benefit of hindsight and have inherent limitations. Specifically, hypothetical returns do not reflect actual trading or the effect of material economic and market factors on the decision-making process. Because trades have not actually been executed, results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity, and may not reflect the impact that certain economic or market factors may have had on the decision-making process. Actual returns may differ significantly from the hypothetical returns.



Source: GMO As of 30/9/07

0

30

60

90

120

150

1 2 3 4 5 6 7 8 9 10

Num

ber o

f Nam

es in

H

igh

Ow

ners

hip

Gro

up

Days to Liquidate

2004August 2007

Ret

urn

on A

ug 7

th-9

th

Days to Liquidate

-12%-10%

-8%-6%-4%-2%0%2%

1 2 3 4 5 6 7 8 9 10

Illiquidity Was the Real RiskPerformance was determined by where the crowding took place

Estimated number of days to liquidate securities that were held by six or more of the eight prominent quantitative managers as determined by GMO while seeking to minimize market impacts.



Low Volatility Looking Forward

Source: GMO As of 30/4/12Note: Mega Quality represents Quality companies with the largest 100 companies by market cap.

0%

5%

10%

15%

20%

25%

30%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 >30

Low Volatility - $10 billion

Perc

enta

ge o

f Hol

ding

s

Days to Liquidate

0%

10%

20%

30%

40%

50%

60%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 >30

Mega Quality- $10 billion

Perc

enta

ge o

f Hol

ding

s

Days to Liquidate

Liquidity of Low Volatility and Quality



Three routes to the permanent impairment of capital:


Fundamental risk


Financing risk


Price risk




Note: Valuations = Price to Normalized EarningsSource: GMO As of 29/2/12

Low Volatility Looking ForwardValuation of trailing low volatility

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Valu

atio

n of

Low

Vol

atili

ty R

elat

ive

to th

e M

arke

t



-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

-10%

0%

10%

20%

30%

40%

50%

60%

65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11

Cumulative Return of M

EGA Cap Q

uality Stocks Relative to the Market

Valu

atio

n of

MEG

A Ca

p Q

ualit

y St

ocks

Rel

ativ

e to

the

Mar

ket

Dec-

ReturnValuation

Price Also MattersQuality MEGA cap stocks have won over the long term

Source: GMO As of 29/2/12* Stocks’ historical premium valuation since 1980.

Note: GMO defines quality companies as those with high profitability, low profit volatility, and minimal use of leverage. The historical valuation is determined by our proprietary intrinsic valuation measure. MEGA Cap Quality represents Quality companies within the largest 100 companies by market cap.

Stocks’ Historical Premium

Market AverageGMO LaunchesQuality Strategy

*



Conclusion

Low volatility investing has done well because of:

– Behavioural drivers

– Marketplace structure

– Concave payoffs

Considering fundamental risk can reduce concavity and is a good indicator of future fundamental risk

It can also reduce liquidity risk

Low trailing return volatility is expensive today and therefore at risk of disappointing

Appendix



-3

-2

-1

0

1

2

3

4

1 2 3 4 5

Implicit LeverageAverage bet on beta quintiles by U.S. mutual funds

Note: Data is taken from Karceski 2002 “Returns-Chasing Behaviour,Mutual Funds and Beta’s Death” and is based on U.S. domestic mutual fundholdings in Morningstar’s “Mutual Funds ondisc” reported from 1984-1996

Source: Karceksi 2002 “Returns-Chasing Behaviour, Mutual Funds and Beta’s death”

Bet

ver

sus

S&P

500



Not All Leverage Is Created EqualIt’s not just about leverage, it’s about convexity


Stra

tegy

Ret

urn

Market Return



Getting Convexity Is EasySystematically buying call options gives a nice convex result

Note: Market = S&P 500. No commissions, options priced at mid-point. Source: Ivy DB, GMO.

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

-30% -20% -10% 0% 10% 20% 30%

Ret

urn

Market Return

Buy 1 ATM Call with 1 Year Expiry



0.5

1.0

2.0

4.0

8.0

1996 1999 2002 2005 2008 2011

Cum

ulat

ive

Ret

urn

High Beta

Monetizing the Option Brings Back the ReturnBeta + Call option = Market

High Beta Covered Call

Market

Source: Ivy DB, GMO As of 9/1/11

Note: High Beta = Top 25% of Beta by Market Cap within Top 200 U.S. Equities; Low Beta Quartile = Bottom 25% of Beta by Market Cap within Top200 U.S. Equities; High Beta Covered Call = Top 25% of Beta by Market Cap with Top 200 U.S. Equities Paired with a Written 1 Month at the MoneyCall Option; Low Beta Covered Call = Bottom 25% of Beta by Market Cap with Top 200 U.S. Equities Paired with a Written 1 Month at the Money CallOption; Market = Top 200 U.S. Equities. All option trades assume crossing the spread and paying commission.

GMONorth America | Europe | Asia-Pacific

GMO NetherlandsGustav Mahlerplein 109 – 115, 26th floor

1082 MS Amsterdam Tel: +31 (0)20- 7085789

GMO Netherlands is a branch of GMO UK Limited. GMO UK Limited is registered with the AFM and the branch office is subject to, and regulated by, the AFM’s conduct of business rules.

Performance data quoted represents past performance and is not predictive of future performance. The foregoing does notconstitute an offer of any securities for sale. Returns are presented gross of management fees, net of transaction costs andinclude the reinvestment of dividends and other income. If these expenses were deducted performance would be lower. Forexample, if the strategy were to achieve a 10% annual rate of return each year for ten years and an annual advisory fee of0.75% were charged during that period, the resulting average annual net return (after the deduction of advisory fees) would be9.25%. A GIPS compliant presentation of composite performance has preceded this report in the past 12 months oraccompanies this presentation, or is also available at www.gmo.com. Actual fees are disclosed in the Prospectus for eachfund and are also available in each strategies compliant presentation.

Performance is shown compared to broad-based securities market indices. Broad-based indices are unmanaged and are notsubject to fees and expenses typically associated with managed accounts or investment funds. Investments cannot be madedirectly into an index.

low volatility investing from a fundamental perspective ingham... · low volatility investing from...

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