Download Presentation GMO Low Volatility Fundamentals

GMO
North America | Europe | Asia-Pacific
Low Volatility Investing from a
Fundamental Perspective
Mark Ingham
31 May 2012
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Introduction
Outline

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
GMO
1
MI_DiscMatls_CFAconf_5-12
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Low Volatility – What a Backtest!
128
64
Cumulative Return
32
Low Beta
16
High Beta
8
4
2
1
0.5
1964
GMO
1969
1974
1979
1984
1989
1994
1999
2004
2009
Source: GMO As of 5/15/12
Note: 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.
MI_DiscMatls_CFAconf_5-12
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2
This Isn’t a New Phenomenon
4096
2048
1024
512
Low Beta
Cumulative Return
256
128
High Beta
64
32
16
8
4
2
1
0.5
0.25
0.125
1927
GMO
1934
1941
1948
1955
1962
1969
1976
1983
1990
1997
2004
2011
Source: GMO As of 5/15/12
Note: 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.
MI_DiscMatls_CFAconf_5-12
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3
This Isn’t a U.S. Phenomenon
32
16
Cumulative Return
Global Low Beta
8
4
Global High Beta
2
1
0.5
Dec- 84
GMO
86
88
90
92
94
96
98
00
02
04
06
08
10
Source: GMO As of 7/31/11
Note: 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 2000
Global Equities.
MI_DiscMatls_CFAconf_5-12
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4
This Isn’t an Equity Phenomenon
0.8
0.6
0.4
GMO
Commodities
Foreign Exchange
Country Bonds
Equity Indices
Treasuries
Corporate Bonds
Credit Indices
Global Stocks (all)
Sweden
Credit Hedged (CDS)
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.
Singapore
New Zealand
Norway
Netherlands
Japan
Italy
Hong Kong
United Kingdom
Finland
Spain
Denmark
Germany
Switzerland
Canada
Belgium
Austria
-0.2
Australia
0.0
France
0.2
U.S. Stocks
Annualised Sharpe Ratio of BAB Factor
1.0
Source: Frazzini and Pederson “Betting against Beta
MI_DiscMatls_CFAconf_5-12
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5
And Pretty Much the Same Phenomenon as MVP
128
MVP
64
Low Beta
Cumulative Return
32
16
8
High Beta
4
2
1
0.5
Dec- 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09
GMO
Source: GMO As of 7/31/11
Note: 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.
MI_DiscMatls_CFAconf_5-12
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6
Why Risk Is Backwards
Behavioural or People are weak and stupid!

Career Risk
–

Glamour Stocks
–

Benchmark huggers run the risk of picking high volatility, low return
stocks in order to keep tracking error down.
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.
GMO
7
MI_DiscMatls_CFAconf_5-12
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Lottery Love
The favourite long-shot bias
Rate of Return per Dollar Bet (%)
Break
Even
-20
-40
Sample: U.S. Horse Races, 1992-2001
-60
Raw Data: Aggregated into Percentiles
All Races
Subsample: Exotic Betting Data Available
Subsample: Last Race of the Day
-80
1/3 1/2
Evens
2/1
5/1
10/1
20/1
50/1
100/1
200/1
Odds (Log Scale)
GMO
Source: Snowberg and Wolfers (2010)
MI_DiscMatls_CFAconf_5-12
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8
Why Risk Is Backwards
Behavioural or People are weak and stupid!

Career Risk
–

Glamour Stocks
–

Benchmark huggers run the risk of picking high volatility, low return
stocks in order to keep tracking error down.
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
GMO
9
MI_DiscMatls_CFAconf_5-12
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Not All Leverage Is Created Equal
Beta is leverage, but beta’s leverage is “zero recourse”
250
200
Market
Levered Market
Beta = 2
Theoretical Return
150
100
50
0
-50
-100
-150
-200
-100
-50
0
50
100
Market Return
GMO
Source: GMO 10
MI_DiscMatls_CFAconf_5-12
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Not All Leverage Is Created Equal
It’s not just about leverage, it’s about convexity
Beta ~ 2
50%
40%
40%
30%
30%
20%
20%
Low Beta Return
High Beta Return
50%
High Beta
10%
0%
-10%
Low Beta
Beta ~ 0.5
10%
0%
-10%
-20%
-20%
-30%
-30%
-40%
-40%
-50%
-40%-30%-20%-10% 0% 10% 20% 30%
-50%
-40%-30%-20%-10% 0% 10% 20% 30%
Market Return
Market Return
Beta Converging to 1
GMO
MI_DiscMatls_CFAconf_5-12
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.
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11
Not All Leverage Is Created Equal
In down markets, correlations go to 1
Realized Betas
Low Beta Portfolio
High Beta Portfolio
Market Up
5% or More
Market Between
-5% and 5%
Market Down
5% or More
0.0
GMO
MI_DiscMatls_CFAconf_5-12
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
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.
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12
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
GMO
13
MI_DiscMatls_CFAconf_5-12
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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
GMO
14
MI_DiscMatls_CFAconf_5-12
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Real Risk Is Losing Your Money!
Three routes to the permanent impairment of capital:

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
GMO
15
MI_DiscMatls_CFAconf_5-12
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Fundamental Risk
…also seems backwards – high quality seems to pay!
U.S. Small Cap
Small
Leverage
Low Risk
Stocks
Low
1.6%
Small
Profitability
Small Profit
Volatility
High
2.1%
Low
1.8%
Small Combined
Quality*
High
2.9%
Small Beta
Low
1.7%
Small Cap
High Risk
Stocks
-3.7%
High
-3.7%
High
-4.7%
Low
-5.5%
Low
-4.3%
High
Source: GMO annualized data from 1/79 – 12/11
EAFE
Leverage
Low Risk
Stocks
Profitability
Low
1.8%
High
1.2%
Low
0.7%
Profit
Volatility
Combined
Quality*
High
2.2%
Beta
Low
2.4%
MSCI EAFE
High Risk
Stocks
GMO
-1.6%
High
-1.1%
Low
* 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.
-1.7%
High
-2.4%
Low
-2.8%
High
Source: GMO annualized data from 1/85 – 12/11
16
MI_DiscMatls_CFAconf_5-12
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Quality Characteristics Persist
Contrary to economic theory, quality exhibits a sustainable
competitive advantage
U.S. Quality
U.S. Low Quality
Realized U.S. Quality
Realized U.S. Low Quality
6%
Relative Profitability (ROE)
4%
2%
1975
Highest Quality Quartile
0%
1975
Lowest Quality Quartile
-2%
IBM
Wyeth
Xerox Corp.
Schering-Plough Corp.
Avon Products Inc.
Kellogg Co.
Eastman Kodak Co.
Merck & Co., Inc.
Eli Lilly & Co.
Hewlett-Packard Co.
Emerson Electric Co.
General Foods Corp.
Procter & Gamble Co.
Johnson & Johnson
J.C. Penney Co., Inc.
Federated Dept. Stores
Pfizer Inc.
CBS Inc.
3M Co.
Coca-Cola Co.
Warner-Lambert Co.
Bristol-Myers Squibb Co.
PepsiCo, Inc.
Carnation Co.
United States Steel Corp.
CitiCorp
Pharmacia Corp.
Morgan (JP) & Co.
BCE Inc.
ConocoPhillips
Atlantic Richfield Co.
International Paper Co.
Union Pacific Corp.
Southern Co.
Unocal Corp.
BankAmerica Corp.
Standard Oil Co.
American Electric Power
Amax Inc.
Alcoa Inc.
Ford Motor Co.
Tenneco Inc.
Unicom Corp.
Bethlehem Steel Corp.
Aetna Inc.
RCA Corp.
After 30
years the
high
quality
quartile is
almost
twice as
profitable.
-4%
-6%
0
3
6
9
12
Years
15
18
21
24
30
Note: Profitability = Return On Equity Source: GMO, U.S. 1965-2010; Realized GMO 2004-31/10/11
GMO
The securities identified above represent a selection of securities identified by the GMO quantitative model. These specific securities are selected for presentation by GMO based on
their underlying characteristics and are not selected on the basis of their investment performance. These securities are not necessarily representative of the securities purchased, sold or
recommended for advisory clients, and it should not be assumed that the investment in the securities identified will be profitable.
MI_DiscMatls_CFAconf_5-12
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17
Quality, the Market and Low Volatility
during Historic Downturns
Market
-71%
-48%
-22%
-23%
Quality
N/A
N/A
N/A
N/A
Min vol
-68%
-45%
-20%
-20%
Dates
Jan-29 toJan-32
Feb-37 to Mar-38
May-46 to Nov-46
Dec-61 to Jun-62
Name
Great Depression
Echo of above
Post-WWII
Kennedy Break
Duration (months)
36
13
6
6
-29%
-44%
-19%
-28%
-15%
-16%
-19%
-46%
11%
-27%
-10%
-12%
-30%
-37%
13%
-22%
-13%
-11%
Dec-68 to Jun-70
Jan-73 to Sep-74
Nov-80 to Jul-82
Sep-87 to Nov-87
May-90 to Oct-90
Jun-98 to Aug-98
GGM meltdown*
First Oil Shock
Second Oil Shock
Black Monday
S & L crisis
LTCM
18
20
20
2
5
2
-46%
-50%
-39%
-37%
7%
-34%
Mar-00 to Sep-02
Oct-07 to Feb-09
TMT meltdown
Financial crisis
30
16
GMO
*Great Garbage Market
Source: GMO 18
MI_DiscMatls_CFAconf_5-12
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Concavity / Convexity of Low Beta and
Quality
Flight to Quality NOT flight to Low Beta!
50%
40%
40%
30%
30%
20%
20%
High Quality Return
Low Beta Return
50%
High Quality
Low Beta
10%
0%
-10%
10%
0%
-10%
-20%
-20%
-30%
-30%
-40%
-40%
-50%
-40%-30%-20%-10% 0% 10% 20% 30%
-50%
-40% -30% -20% -10% 0% 10% 20% 30%
Market Return
GMO
Market Return
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.
MI_DiscMatls_CFAconf_5-12
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19
Concavity / Convexity of Low Beta, Quality
and MVP
…and, on average, low beta
GMO
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.
MI_DiscMatls_CFAconf_5-12
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20
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
GMO
21
MI_DiscMatls_CFAconf_5-12
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Convexity Is a Shorter-Term Phenomenon
Convexity over different return horizons
1.5
high beta
low beta
Convexity
1.0
0.5
0.0
-0.5
-1.0
1 day
GMO
MI_DiscMatls_CFAconf_5-12
1 week
1 month
1 quarter
2 quarters
3 quarters
4 quarters
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
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22
Real Risk Is Losing Your Money!
Deleveraging can drive correlations to 1

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 nearterm 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
GMO
23
MI_DiscMatls_CFAconf_5-12
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August 2007 – Correlations Going to 1
USD value of coincident holdings of 8 prominent quants
Total Assets ($ Billions) in High Ownership Group
$70
$61 Billion
$60
$50
$40
24x
Growth
$30
$20
$2.5 Billion
$10
$0
1/04
GMO
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 24
MI_DiscMatls_CFAconf_5-12
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3 Years of Returns Were Wiped
Out in 3 Days
Quant became the risk factor
12%
Quant Long/Short Performance
10%
8%
6%
4%
2%
0%
-2%
-4%
-6%
1/04
5/04
9/04
1/05
5/05
9/05
1/06
5/06
9/06
1/07
5/07
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 invested
in 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 historical
data 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.
GMO
Source: GMO, LionShare As of 31/8/07
MI_DiscMatls_CFAconf_5-12
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25
Illiquidity Was the Real Risk
Number of Names in
High Ownership Group
Performance was determined by where the crowding took place
150
120
2004
August 2007
90
60
30
0
1
2
3
4
5
6
7
8
9
10
7
8
9
10
Return on Aug 7th - 9th
Days to Liquidate
2%
0%
-2%
-4%
-6%
-8%
-10%
-12%
1
2
3
4
5
6
Days to Liquidate
GMO
MI_DiscMatls_CFAconf_5-12
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.
Source: GMO As of 30/9/07 26
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Low Volatility Looking Forward
Percentage of Holdings
Liquidity of Low Volatility and Quality
Low Volatility - $10 billion
30%
25%
20%
15%
10%
5%
0%
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
Percentage of Holdings
Days to Liquidate
Mega Quality- $10 billion
60%
50%
40%
30%
20%
10%
0%
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
Days to Liquidate
GMO
Note: Mega Quality represents Quality companies with the largest 100 companies by market cap.
Source: GMO As of 30/4/12 27
MI_DiscMatls_CFAconf_5-12
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Real Risk Is Losing Your Money!
Three routes to the permanent impairment of capital:

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
GMO
28
MI_DiscMatls_CFAconf_5-12
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Low Volatility Looking Forward
Valuation of trailing low volatility
Valuation of Low Volatility Relative to the Market
1.2
GMO
1.1
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Note: Valuations = Price to Normalized Earnings
Source: GMO
As of 29/2/12 29
MI_DiscMatls_CFAconf_5-12
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Price Also Matters
Quality MEGA cap stocks have won over the long term
40%
30%
50%
Valuation
Return
20%
40%
10%
30%
Stocks’
Historical
Premium
20%
0%
-10%
*
10%
-20%
0%
-30%
Market Average
GMO Launches
Quality Strategy
-10%
-40%
Dec- 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11
GMO
Cumulative Return of MEGA Cap Quality Stocks Relative to the Market
Valuation of MEGA Cap Quality Stocks Relative to the Market
60%
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. 30
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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
GMO
31
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Appendix
Implicit Leverage
Average bet on beta quintiles by U.S. mutual funds
4
Bet versus S&P 500
3
2
1
0
-1
-2
-3
1
GMO
2
Note: Data is taken from Karceski 2002 “Returns-Chasing Behaviour,
Mutual Funds and Beta’s Death” and is based on U.S. domestic mutual fund
holdings in Morningstar’s “Mutual Funds ondisc” reported from 1984-1996
3
4
5
Source: Karceksi 2002 “Returns-Chasing Behaviour, Mutual Funds and Beta’s death”
MI_DiscMatls_CFAconf_5-12
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33
Not All Leverage Is Created Equal
Strategy Return
It’s not just about leverage, it’s about convexity
Market Return
GMO
MI_DiscMatls_CFAconf_5-12
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.
Proprietary information – not for distribution. Copyright © 2012 by GMO LLC. All rights reserved.
34
Getting Convexity Is Easy
Systematically buying call options gives a nice convex
result
Buy 1 ATM Call with 1 Year Expiry
20%
15%
10%
Return
5%
0%
-5%
-10%
-15%
-20%
-30%
-20%
-10%
0%
10%
20%
30%
Market Return
GMO
Note: Market = S&P 500.
No commissions, options priced at mid-point.
Source: Ivy DB, GMO. 35
MI_DiscMatls_CFAconf_5-12
Proprietary information – not for distribution. Copyright © 2012 by GMO LLC. All rights reserved.
Monetizing the Option Brings
Back the Return
Beta + Call option = Market
8.0
Cumulative Return
4.0
High Beta
Market
2.0
High Beta
Covered Call
1.0
0.5
1996
GMO
MI_DiscMatls_CFAconf_5-12
1999
2002
2005
2008
2011
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 Top
200 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 Money
Call 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 Call
Source: Ivy DB, GMO As of 9/1/11
Option; Market = Top 200 U.S. Equities. All option trades assume crossing the spread and paying commission.
Proprietary information – not for distribution. Copyright © 2012 by GMO LLC. All rights reserved.
36
Performance data quoted represents past performance and is not predictive of future performance. The foregoing does not
constitute an offer of any securities for sale. Returns are presented gross of management fees, net of transaction costs and
include the reinvestment of dividends and other income. If these expenses were deducted performance would be lower. For
example, if the strategy were to achieve a 10% annual rate of return each year for ten years and an annual advisory fee of
0.75% were charged during that period, the resulting average annual net return (after the deduction of advisory fees) would be
9.25%. A GIPS compliant presentation of composite performance has preceded this report in the past 12 months or
accompanies this presentation, or is also available at www.gmo.com. Actual fees are disclosed in the Prospectus for each
fund 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 not
subject to fees and expenses typically associated with managed accounts or investment funds. Investments cannot be made
directly into an index.
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