Research

Natural Selection:
Tactics and Strategy with
Equity Sectors
Contributors
Joseph Nelesen, PhD
Head of Specialists
Index Investment Strategy
joseph.nelesen@spglobal.com
Tim Edwards, PhD
Managing Director
Index Investment Strategy
tim.edwards@spglobal.com

In recent years, the S&P 500® sectors have exhibited elevateddispersion, including their widest-ever spread between the best
and worst performers in 2022, highlighting an opportunity forstudying the impact of sector selection (see Exhibit 1).1 In a rapidly
evolving global investment landscape, S&P 500 sectors remain toolsin active and passive portfolio construction and worthy of
consideration.
In this paper, we will:–

Review sector characteristics, performance and influence on
stock returns;–

Evaluate the impact of skew on active selection of stocks, sectors
and industries;–

Present case studies on strategic and tactical portfolio
applications of sector indices.

106

94 98
84

78
65
40
31 30

38

37

2023

2022

2021

2020

2019

2018

25

2017

2016

2014

2013

2012

28

2015

41 38

37

2011

2010

29

2008

2005

53
40

2007

38 34

2006

30

2004

40

2003

2002

2001

2000

1999

34 33

1998

1997

43 40

1996

38

1995

30 32

53

2009

30-Year Average

1994

110
100
90
80
70
60
50
40
30
20
10
0

1993

Best-Worst Sector (%)

Exhibit 1: S&P 500 Sector Best-Worst Total Return Spread (Annual)

Source: S&P Dow Jones Indices LLC. Data as of Dec. 31, 2023. Past performance is no guarantee of future results. Chart is provided forillustrative purposes.

1

The GICS® was created in 1999 and has evolved over time. All data and analyses based on historical as-reported index levels, inclusive of
GICS changes and constituent reclassifications. See the GICS methodology for further details on GICS methodology and classifications.

Sign up to receive our latest research, education, and commentary aton.spdji.com/SignUp.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Contents
1. Introduction ..........................................................................................................................3
2. GICS®: A Global Taxonomy .................................................................................................4
3. Sector Performance Profiles ................................................................................................5
4. The Influence of Sectors on Stock Performance ..................................................................6
5. Stock Skew and Dispersion in Sectors ..............................................................................12
6. Modified Equal Weighting in Select Industries ...................................................................15
7. Sector Relations: Risk, Return & Correlations ...................................................................17
8. Conclusion .........................................................................................................................25
9. Appendices ........................................................................................................................26

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

1. Introduction“Look deep into nature, and then you will understand everything better.”
Albert Einstein
Imagine equity markets as a deep rainforest, grown dense through the centuries with new
ways of investing, constantly born out of soil made from those that came and went long before.
Teeming with life and ripe for exploration, this nested series of complex systems perpetuallylures intrepid investors seeking answers to the questions: What features drive the behavior ofa stock, and how can those help us make sense of the world? As colorful and novel species inthis evolving landscape attract the adventurer’s curiosity, so too should a curiously old andlarge tree with many branches found towering above the canopy. Like sectors, this tree not
only endures, but also remains intertwined with the ecosystem of stocks that surround it,
providing clues on how to thrive in constantly evolving conditions.
In this paper, we explore how the enduring power of sectors and industries helps to definemarkets and serve as the framework for myriad investing strategies. Just as the allure ofactive stock selection persists, so too does evidence that outperformance relative to indices is
elusive. Decades of data suggest that sectors and industries may sometimes be more
effective exposures than single stocks to diversify risk and express views on market andeconomic conditions around the world.
We will review past performance of sectors through the lens of 21st century market cycles,
identify consistent patterns that continue to make sectors useful and highlight the potential of
sectors to improve diversification and performance in global portfolios.
Sectors and industries concentrate securities with similar business models and risk factors,aligning company types around characteristics that largely transcend borders and make them
relevant for investors worldwide.2 The growing use of sectors and industries among diverse
investor types in a wide and growing array of liquid index-based strategies and holding periods
is reflected in asset levels for related exchange-traded funds (ETFs; see Exhibit 2). This paper
examines historical sector and industry index performance and tests strategic long-term useof one or more sectors to gain consistent exposure or correct an unintended bias, as well astactical use with the intent of adjusting allocations depending on market or economic
conditions. The outcomes reaffirm the enduring power of sectors and industries as building
blocks in modern equity allocations.

2

See Edwards, Tim, Craig Lazzara, Hamish Preston and Francesca Bruna Pipino; “Global Applications of S&P 500 Sectors” S&P Dow Jones
Indices, 2018.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 2: AUM in Sector or Industry-Linked ETFs and Futures
Global AUM (USD Billions)

450
400
350
300
250
200
150
100
50

Dec. 2002
Jun. 2003
Dec. 2003
Jun. 2004
Dec. 2004
Jun. 2005
Dec. 2005
Jun. 2006
Dec. 2006
Jun. 2007
Dec. 2007
Jun. 2008
Dec. 2008
Jun. 2009
Dec. 2009
Jun. 2010
Dec. 2010
Jun. 2011
Dec. 2011
Jun. 2012
Dec. 2012
Jun. 2013
Dec. 2013
Jun. 2014
Dec. 2014
Jun. 2015
Dec. 2015
Jun. 2016
Dec. 2016
Jun. 2017
Dec. 2017
Jun. 2018
Dec. 2018
Jun. 2019
Dec. 2019
Jun. 2020
Dec. 2020
Jun. 2021
Dec. 2021
Jun. 2022
Dec. 2022
Jun. 2023
Dec. 2023
Jun. 2024

0North America

EMEA

APAC

Futures (Open Interest)

Sources: S&P Dow Jones Indices LLC, Factset. Data as of June 28, 2024. Past performance is no guarantee of future results. Chart isprovided for illustrative purposes. For a full list of ETFs included in the calculation of Exhibit 2, please see Appendix D.

2. GICS®: A Global Taxonomy
Kingdom, phylum, class, order, family, genus, species; many of us remember learning thetaxonomic hierarchy that has been a foundation for categorizing over 1.2 million known
organisms together in nested groups with similar characteristics since the 18th century. We
may not commonly refer to the household dog as canis lupus familiaris, but intuitively we knowwhat behaviors our furry friend shares in common with other canines on the block. Similarly
with stocks, the comprehensive yet evolving Global Industry Classification Standard (GICS)
helps bring order to understanding the business models, economic sensitivities and othercharacteristics that certain subsets of stocks have in common among tens of thousands ofstocks worldwide.
With increasing specificity as categories branch off from the top level, GICS uses quantitativeand qualitative rules to place stocks into one of 163 sub-industries, then 74 industries, 25
industry groups and 11 sectors, as shown in Exhibit 3.3 For example, Harley Davidson
generated over 80% of its 2023 revenue from motorcycle & related products sales, placing it in
the GICS Motorcycle Manufacturers sub-industry, which itself is part of the Automobiles
industry, a subset of the Automobiles & Components industry group, which finally folds into the
top-level Consumer Discretionary sector.4

3

Source: S&P Dow Jones Indices LLC. GICS grouping totals as of March 2023 classification changes.

4

Source: Harley-Davidson 2023 Annual Report.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 3: GICS Hierarchy – 11 Sectors, 25 Industry Groups, 74 Industries and 163 SubIndustries

Source: S&P Dow Jones Indices LLC. GICS grouping totals as of March 2023 classification changes. Chart is provided for illustrative
purposes.

This way, the GICS structure aids an investor by making the first valuable assessment ofwhat kind of business a company is in and therefore how it can be compared to others andwhat types of global risk factors it is most sensitive to. These classifications have also allowed
for the creation of sector and industry indices to support investment products such as ETFs
rooted in universally understood categories.

3. Sector Performance Profiles
One of the enduringly elegant features of GICS is that it provides a universal nomenclature,essentially a shorthand for investors and researchers, to compare commonly understood andhistorically consistent groupings of stocks over time. If one person discusses performance of
the “Financials” sector with another, there is an immediate understanding of the types of stocks
being mentioned without the need to debate specific tickers. GICS facilitates such frameworks
by assigning stocks into mutually exclusive economic groupings, each of which performs andresponds to risk factors in ways that are internally aligned, while also externally being quite
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

different from one another. For example, Information Technology and Energy are among
sectors that both exhibit relatively high volatility yet are inversely correlated, outperforming atvery different periods in the market cycle (see Exhibit 4).
Exhibit 4: Rolling Three-Year Excess Returns of Selected S&P 500 Sectors
280%
230%
180%

Reutns

130%
80%
30%
-20%
-70%

EnergyDec. 2023

Dec. 2022

Dec. 2021

Dec. 2020

Dec. 2019

Dec. 2018

Dec. 2017

Dec. 2016

Dec. 2015

Dec. 2014

Dec. 2013

Dec. 2012

Dec. 2011

Dec. 2010

Dec. 2009

Dec. 2008

Dec. 2007

Dec. 2006

Dec. 2005

Dec. 2004

Dec. 2003

Dec. 2002

Dec. 2001

Dec. 2000

Dec. 1999-120%

Information Technology

Source: S&P Dow Jones Indices LLC. Data based on rolling three-year excess returns of selected S&P 500 sector indices relative to the S&P
500 from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Chart is provided for illustrative purposes.

4. The Influence of Sectors on Stock Performance
Sector perspectives can play a dual roIe in portfolio construction and analysis: as indices,
they represent passive exposures to distinct segments of the economy, yet they may
also be (and are often) employed in the service of active views. The aggregate interest
from both types of investor appears further to be growing—at least in the case of products
tracking S&P DJI’s indices (see Exhibit 2).
For a passive investor, the breadth of available sectors and industry indices provides ample
choices for building intentional and diversified portfolios. Conversely, active investors can use
sector and industry products (such as ETFs) as building blocks in strategic and tacticalapplications expressing investment views. The rationale for the active component ofsector investing is supported by two factors of interest, the first of which is well known,
the second less so: 1) the extent to which stocks behave similarly to their categorization, which

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

determines the importance of sector and industry bets to returns,5 and 2) the skewness ofstock returns within a given sector or industry, as compared to the skewness among all stocks,
or all sector returns—which determines the chances of selecting a “winning” pick.

Revisiting Stock-to-Sector Correlation
The overall fates of sectors and industries can explain much of their constituents’ performance.
For example, on average so far this century, sector membership has statisticallyaccounted for roughly half of the average S&P 500 constituent’s daily returns (seeExhibit 5).6

12-Montth Correlation Squared

Exhibit 5: S&P 500 Sectors Explain Much of Single Stock Performance
70.0%
60.0%

Average: 0.47

50.0%
40.0%
30.0%
20.0%

Average: 0.28

10.0%

Dec. 1999
Jul. 2000
Feb. 2001
Sep. 2001
Apr. 2002
Nov. 2002
Jun. 2003
Jan. 2004
Aug. 2004
Mar. 2005
Oct. 2005
May. 2006
Dec. 2006
Jul. 2007
Feb. 2008
Sep. 2008
Apr. 2009
Nov. 2009
Jun. 2010
Jan. 2011
Aug. 2011
Mar. 2012
Oct. 2012
May. 2013
Dec. 2013
Jul. 2014
Feb. 2015
Sep. 2015
Apr. 2016
Nov. 2016
Jun. 2017
Jan. 2018
Aug. 2018
Mar. 2019
Oct. 2019
May. 2020
Dec. 2020
Jul. 2021
Feb. 2022
Sep. 2022
Apr. 2023
Nov. 2023

0.0%

12-Month Correlation Squared to Sector

12-Month Correlation Squared to Market

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023. Rolling 12-month data based on correlation of stocks
to sectors and the S&P 500, calculated monthly.

A stock’s industry classification has proven to be even more important in its return, with acorrelation squared average of 0.52 over the same time period. Meanwhile, exposure to themarket (in this case, the S&P 1500®) had a correlation squared of 0.27 with single stock pricemovements. Exhibit 6 further shows that stock-to-segment correlations were particularly
elevated during periods of market stress, meaning that when the environment was mostchallenging for investors, sector trends were typically more important than theindividual circumstances of each stock.

5

See Edwards, Tim, Craig Lazzara, Hamish Preston and Francesca Bruna Pipino; “Global Applications of S&P 500 Sectors” S&P Dow Jones
Indices, 2018.

6

Source: S&P Dow Jones Indices LLC. Based on monthly correlation statistics sourced from S&P Dow Jones Indices, from December 1999
to June 2022. The square of the correlation statistic, or “coefficient of determination,” here provides the proportion of variation in one
variable that may be explained by variation in another. Stock correlation squared to sector was 0.47 and to market was 0.28.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 6: S&P 500 Performance and Average Correlation Squared of Stock to Sector

12-Month S&P 500 Performance

60.0%

40.0%

20.0%

0.0%

-20.0%-40.0%-60.0%
30.0%

35.0%

40.0%

45.0%

50.0%

55.0%

60.0%

65.0%

12-Month Average Correlation Squared of Stocks to Sector

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023. Rolling 12-month data based on correlation of stocks
to sectors and the S&P 500, calculated monthly. Past performance is no guarantee of future results.

Offering another perspective, Exhibit 7 provides a sector-by-sector summary of the degree towhich each constituent was correlated, on average, to its respective sector, highlighting thelevels each also achieved during selected periods of market crisis.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 7: Average Correlation Squared of Stock to Sector and Market
0.80
0.69

Average Correlation Squared

0.69
0.70
0.54

0.60

0.60

0.58
0.54
0.50
0.46

0.50

0.43

0.58
0.50

0.42

0.37
0.40
0.30
0.20
0.10
0.28

0.47

0.53

0.35

0.35

0.61

0.52

0.33

0.44

0.43

0.44

0.61

0.53

0.00

Average Correlation Squared

During Downturns

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023. Data based on average of monthly correlationsquared of stocks to sectors and the S&P 500. Downturn average since 1999 includes peak-to-trough performance during dot-com crash,
GFC, COVID-19 emergence and 2022 bear market. See Appendix for date details. Past performance is no guarantee of future results. Chart
is provided for illustrative purposes.

Skill in “stock picking” is purportedly magnified when equities are under pressure. But
as the previous exhibits show, the fortunes of sectors are more important in crises. Thissuggests a particularly important question: are sector-picking skills more valuable? Incontrast to the theoretical zero-sum game of stock versus benchmark performance, there isanother dimension when considering the trade-offs between stock picking and sector picking.
In the next section, we will see that the scales are not always evenly balanced; instead, theylook very different when weighing sectors instead of stocks.

Predator or Prey? The Role of Skew in Stock and Sector
Performance
In order to be successful, an active bet requires both the opportunity to outperform—that is,differentiated performance—and a decent chance of selecting an outperformer. The latter
leads to an important distinction between the prospects of selecting among sectors, industries
or stocks, because the probability that any one choice might result in outperformancediffers greatly.
The key to distinguishing between the two approaches (stock or sector) lies in a considerationof the skew of available returns. The impact of positively skewed returns on the challenge of
selecting outperforming stocks is relatively well known at the broad index level: absent skill or
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

luck (or both), the probability of finding an outperforming stock within a broad-market
benchmark is typically well below 50%, particularly when measured over longer-termhorizons.7 For example, as shown in Exhibit 8, in the period from December 1999 throughDecember 2023, 76% of stocks appearing within the S&P 500 underperformed theaverage stock. When so few stocks outperform, the chance of selecting a winner is naturally
diminished.
Exhibit 8: Distribution of S&P 500 Stock Returns
25%

Median: 55.4%

Frequency

20%

Average: 355.5% Index: 410.9%

15%

10%

5%

Over 1000%

950% to 1000%

900% to 950%

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

0%Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Chart
is provided for illustrative purposes.

Exhibit 8 provides an example of positive skew among broad benchmark constituent returns; it
is not immediately obvious whether a similar skew should be observed within each sector, or
across sectors themselves. In fact, sector returns displayed a negative skew. Morespecifically, Exhibit 9 shows that since December 1999, 8 out of 11 S&P 500 sectors haveoutperformed the S&P 500 itself.8 The fact that a majority of parts (sectors) haveoutperformed the whole (the benchmark) provides a clear indication that sector picking might
be less challenging than stock picking.

7“Fooled by Conviction” (2015), “The Agony & Ecstasy” (JP Morgan), the Bessembinder paper (“Do Stocks Outperform Treasury Bills”), andLazzara, Craig: “The Skew Is Not New” S&P Dow Jones Indices, 2020.

8

S&P 500 Real Estate index levels available since Oct. 9, 2001, and compared to the S&P 500 over the concurrent period.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 9: Cumulative Returns for S&P 500 Sectors
Cumulative Performance

700.0%
600.0%
500.0%

410.9%

433.5%

448.5%

474.1%

474.5%

475.3%

496.4%

541.1%

584.2%

636.4%

400.0%
300.0%

225.0%

200.0%
100.0%

75.7%

0.0%

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023, except for Real Estate from Oct. 9, 2001, through,Dec. 31, 2023. The S&P 500 total return for the concurrent period was 595.2%. Past performance is no guarantee of future results. Chart isprovided for illustrative purposes.

Of course, the positive skew observed among constituents in Exhibit 8 must come fromsomewhere, and Exhibit 10 illustrates that it arises from an even more strongly positive skew
within most sectors. In every sector, the majority of stocks included between December 1999
and December 2023 underperformed the average stock in their sector, and a majority of
constituents underperformed the average S&P 500 constituent. Overall, across all sectors, anaverage of 74% of stocks underperformed the average stock in their sector.
Exhibit 10: Average and Median Stock Returns by Sector
S&P 500 Sector

SectorTotal Return (%)

Stock Returns (%)

Percent of Stocks Underperforming

MedianAverage

Average Stock in
SectorAverage Stock in
S&P 500

Utilities

449

132

325

62.9

64.5

Consumer Staples

584

199

332

67.2

70.1

Financials

225

60

210

70.2

78.7

Real Estate*

496

48

150

71.4

83.3

Energy

475

36

189

72.3

78.5

Industrials

474

126

562

73.3

67.1

Health Care

636

99

429

76.1

72.6

S&P 500

411

55

356

76.4

76.4

Materials

474

45

263

78.6

84.3

Consumer Discretionary

541

24

403

80.5

79.3

Communication Services

76

17

116

81.4

88.4

Information Technology

433

24

445

83.0

88.9

Source: S&P Dow Jones Indices LLC, FactSet. Data from Dec. 31, 1999, to Dec. 31, 2023, with the exception of S&P 500 Real Estate from
Oct. 9, 2001, to Dec. 31, 2023, during which time the average S&P 500 stock return was 420.0%. Past performance is no guarantee of future
results. Table is provided for illustrative purposes.
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

In sectors such as Consumer Discretionary, Communication Services and Information
Technology, the landscape for stock pickers was especially dire: more than 80% of stocks
underperformed the average stock in their respective sectors.
Managers seeking to outperform the market are faced with the necessity of objectively
assessing their own ability to repeatedly identify and overweight stocks from a small pool ofwinners. The instinct to hold highly concentrated bets in a small number of stocks may be
counterproductive in light of consistent evidence that holding all stocks in a sector—orindustry—is statistically more likely to be a successful strategy, provided one can pick the rightsector and provided one is rewarded for doing so.

5. Stock Skew and Dispersion in Sectors
While measurement of skew helps illustrate the random probability of selecting anoutperforming stock from an index universe, an equally important measure of opportunity for
active success is dispersion. In essence, dispersion is a measure of the magnitude ofperformance differences among index constituents. Higher dispersion means a wider gap
between outperforming and underperforming constituents. As shown in Exhibit 11, constituent
dispersion varies over time and the potential impact of a manager’s stock-selection skill rises
when dispersion is high, as a larger gap between winners and losers means that active stock
selection makes a bigger difference in performance outcomes.
Exhibit 11: S&P 500 Dispersion Levels Vary Over Time
70.0%

S&P 500 Constituent Dispersion

60.0%
50.0%
40.0%
30.0%
20.0%
10.0%

12-Month Average Dispersion

1999-2023 Average

Dec. 2023

Dec. 2022

Dec. 2021

Dec. 2020

Dec. 2019

Dec. 2018

Dec. 2017

Dec. 2016

Dec. 2015

Dec. 2014

Dec. 2013

Dec. 2012

Dec. 2011

Dec. 2010

Dec. 2009

Dec. 2008

Dec. 2007

Dec. 2006

Dec. 2005

Dec. 2004

Dec. 2003

Dec. 2002

Dec. 2001

Dec. 2000

Dec. 1999

0.0%

Monthly Dispersion

Source: S&P Dow Jones Indices LLC. Monthly data from December 1999 to December 2023. Dispersion is the annualized index-weighted
standard deviation of the index constituents’ full-month total returns. Past performance is no guarantee of future results. Chart is provided forillustrative purposes.
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Natural Selection: Tactics and Strategy with Equity Sectors

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While higher dispersion may offer greater potential rewards to skillful stock pickers, it does notnecessarily increase the probability of success and, in fact, may equally indicate a greater
negative impact of poor stock selection.
Revisiting dispersion while now being mindful of skew, we find that the path to outperformance
may be more often a minefield. Higher dispersion is not necessarily associated with a greaternumber of stocks beating the index return. In fact, based on past evidence, the opposite istrue on average. In higher-dispersion sectors, a slightly greater proportion of stocks
underperformed the average stock return (see Exhibit 12). In other words, the times whenhigh dispersion makes prospects of selecting winning stocks particularly tempting are precisely
the times when such winners tend to be in short supply due to positive skew. In this context,
diversification via indices ensures exposure to an entire sector (including its highest-performing
stocks) as a means of navigating an uncertain passage while resisting the siren song of
pursuing alpha through concentrated bets that may lead to missed opportunities.9
Exhibit 12: Stock Dispersion and Proportion of Underperformers by Sector
Stocks Below Average Stock
Performance

85.0%

Information Technology
Communication Services

80.0%

Consumer Discretionary
Materials
Health Care

75.0%
EnergyIndustrials
Financials

70.0%
Consumer Staples
65.0%
Utilities
60.0%
15.0%

17.5%

20.0%

22.5%

25.0%

Average Dispersion
Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Chart
is provided for illustrative purposes.

Nested within each of the 11 GICS sectors, industry indices more narrowly categorize stocks
and also present many examples of positively skewed returns. Exhibit 13 shows the averageand median returns for S&P 1500 industries (limited to those that contained at least 30
constituents), as well as the proportion of stocks in each index that underperform the averagestock in their respective industry.

9

With apologies to Homer for the analogy, despite its aptness. The perils of concentrated portfolios are well covered. See for example
https://www.indexologyblog.com/2023/04/10/unwisely-concentrated/.

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Natural Selection: Tactics and Strategy with Equity Sectors

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Exhibit 13: Average and Median Stock Returns by Industry
Stock Returns (%)

Industry
Total Returns (%)

S&P 1500 Industry

Stocks Underperforming

MedianAverage

Average Stock in Industry (%)

Banks

283

75

129

52.9

Communications Equipment

-15

-17

67

54.0

Biotechnology

812

8

759

55.1

Chemicals

738

144

423

56.6

Software

764

33

534

57.1

Insurance

307

215

481

58.5

Electric Utilities

669

262

372

59.2

Food Products

713

154

318

59.4

Machinery

1397

428

835

63.1

Media

126

-6

60

63.2

Specialty Retail

688

98

659

64.2

Household Durables

807

106

610

68.5

Health Care Providers & Services

2164

186

663

73.8

Commercial Services & Supplies

626

56

422

74.3

Health Care Equipment & Supplies

951

86

578

79.7

Source: S&P Dow Jones Indices LLC. Includes 15 largest current S&P 1500 industries based on number of constituents over data period
from Dec. 31, 1999, to Dec. 30, 2023. Past performance is no guarantee of future results. Table is provided for illustrative purposes.

Just as sectors on average have outperformed their broader benchmark index, more than half(62%) of industries have outperformed their respective sectors (see Exhibit 14). It appears
that as an investor’s choice of exposures becomes more granular as they move from sectors
to single stocks, the frequency of outperformance may decrease considerably.
Exhibit 14: Sector, Industry and Stock Outperformance versus Benchmark Universe

73%

62%

22%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Performance
Sectors Outperforming the Market

Industries Outperforming their Sector

Stocks Outperforming Average S&P 1500 Composite Stock

Source: S&P Dow Jones Indices LLC. Data available from Dec. 31, 1999, to Dec. 31, 2023. Based on S&P 500 sectoral performance from
Dec. 1999 except Real Estate (counted as an underperforming sector). Single stock performances based on total return in U.S. dollars during
the period of index inclusion, as compared to the S&P 1500 Composite sample average. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

6. Modified Equal Weighting in Select Industries
When there is an expectation of a positively skewed environment where the outperformance ofa few big outliers drives up the market average, it becomes important to ensure participation.
Absent any information about which constituents will eventually beat the benchmark, there isno justification to weight one constituent higher than another. In such instances, an equalweighted approach may be appropriate to maximize exposure to eventual outperformers
without prior knowledge of which ones they’ll be.
The skew of stock returns within individual sectors or industries, when combined with thepotential concentration levels that can arise in simple market-capitalization-weighting schemes,
may lead some investors to periodically consider shifting to alternative weightings, such as
equal weighting at the level of industries.
S&P DJI’s most popular range of industry-level indices for U.S. equities, the S&P SelectIndustry Indices,10 use equal or capped weightings at the security level to reduce concentrationand thus mitigate the impact of positive skew.
The impact of these two weighting approaches over time are starkly visible throughcomparison of stock weightings in each index series. In Exhibit 15, for example, we show
weightings of the top 10 stocks in the market-cap-weighted S&P Retail Select Industry FloatAdjusted Market Cap (FMC) Index and their weights in the (closer to equal weight) S&P Retail
Select Industry Index.11
Exhibit 15: Top 10 Retail Industry Stock Weights in Select Industry and FMC Indices
Constituent Weight

60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
AMZN

COST

WMT

TJX

S&P Retail Select Industry Index

TGT

ORLY

ROST

AZO

KR

DG

S&P Retail Select Industry FMC Index

Source: S&P Dow Jones Indices LLC. Data as of Dec. 31, 2023. Past performance is no guarantee of future results. Chart is provided forillustrative purposes.

10

For details, refer to the index methodology.

11

Retail is selected in this illustration due to the presence of a constituent with more than 50% weight.

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Natural Selection: Tactics and Strategy with Equity Sectors

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Exhibit 16 illustrates the performance impact of different weightings across the same set ofstocks through rolling 12-month periods when equal weighting (represented by the S&P Retail
Select Industry Index) outperforms relative to market cap weighting (represented by the S&P
Retail Select Industry FMC Index).
Exhibit 16: S&P Retail Select Industry and FMC Indices’ Trailing 12-Month Returns

Trailing 12-Month Performance

250.0%
200.0%
150.0%
100.0%
50.0%
0.0%-50.0%

S&P Retail Select Industry Index

Dec. 2023

Dec. 2022

Dec. 2021

Dec. 2020

Dec. 2019

Dec. 2018

Dec. 2017

Dec. 2016

Dec. 2015

Dec. 2014

Dec. 2013

Dec. 2012

Dec. 2011

Dec. 2010

Dec. 2009

Dec. 2008

Dec. 2007

Dec. 2006

Dec. 2005

Dec. 2004

Dec. 2003

Dec. 2002

Dec. 2001

Dec. 2000-100.0%S&P Retail Select Industry FMC Index

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. The S&P Retail Select Industry Index was launched onJune 19, 2006. Past performance is no guarantee of future results. Chart is provided for illustrative purposes and reflects hypothetical
historical performance. All information for an index prior to its launch date is hypothetical back-tested, not actual performance, based on theindex methodology in effect on the launch date. Back-tested performance reflects application of an index methodology and selection of index
constituents with the benefit of hindsight and knowledge of factors that may have positively affected its performance, cannot account for all
financial risk that may affect results and may be considered to reflect survivor/look ahead bias. Actual returns may differ significantly from,and be lower than, back-tested returns. This back-tested data may have been created using a “Backward Data Assumption.” For more
information on “Backward Data Assumption” and back-testing in general, please see the Performance Disclosure at the end of this document.

Historically, concentration within an index tends to ebb and flow over time, rising in someperiods and mean-reverting in others. When concentration increases, market-cap-weighted
indices tend to outperform equal-weight indices, and the opposite is true when concentration
decreases. Ultimately, the availability of these two approaches allows an industry investor tochoose index exposures that suit their view of the relative opportunity set for larger and smaller
stocks.12
Data gathered in examining skew generally suggest that the majority of stocks often, but notalways, underperform their sector’s or industry’s average stock return, as well as the total
return of the index. When positive skew persists and performance is led by a small number ofthe largest stocks in an index, market-cap weighting stands out as a straightforward way toreflect index performance. Conversely, reversion of performance among large outperformers
12

In this, they may be aided by a perspective on how concentrated each industry is, relative to history. See Ganti, Anu, and Craig Lazzara;“Concentration within Sectors and Its Implications for Equal Weighting,” S&P Dow Jones Indices, 2022..

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

can eliminate positive skew and spread performance among a broader set of constituents,
favoring equal weighting. Research suggests that performance cycles of the two approaches
may be at least partially explained by factor cyclicality, with cap weighting covering the large
size and momentum factors, for example, while the weighting scheme and rebalancing effectinherent in equal weighting deliver a smaller-size bias and an anti-momentum tilt.13 This
makes the choice between cap weighting and equal weighting of stocks a powerful andmeaningful decision. Fortunately for investors, and as noted previously, equal-weighted
sector and industry indices and ETFs have become widely available alongside capitalizationweighted versions.

7. Sector Relations: Risk, Return & Correlations
For those tasked with outperforming the market, the fact (see Exhibit 9) that more than half ofsectors generated higher returns than the S&P 500 might engender newfound optimism,
particularly in comparison to the difficulty of selecting outperforming stocks. The differing
market sensitivities, risk levels and potentially complementary correlations among different
industries and sectors suggest that they might prove to be useful building blocks for portfolio
applications above and beyond concentrated sector picks.
The potential advantages to be gained by tactically re-weighting between sectors areillustrated in theory by the fact that their risk/return profiles can vary greatly. Exhibit 17 showstheir distinctive risk/return (volatility) levels over a period of 24 years, while Exhibit 18
compares volatility levels to degree of overall market participation, or beta.

13

See Edwards, Tim, Craig Lazzara, Hamish Preston and Oliver Pestalozzi; “Outperformance in Equal-Weight Indices,” S&P Dow Jones
Indices, 2018, p. 14.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 17: S&P 500 Sector Risk/Return
14.0%
Real Estate

12.0%

Annualized Performance

10.0%

Health Care

Industrials
Consumer Discretionary
Information Technology

Consumer Staples

8.0%

EnergyS&P 500

6.0%

Materials
Financials

Utilities
4.0%
Communication Services
2.0%

0.0%
0.0%

5.0%

10.0%

15.0%
20.0%
Annualized Volatility

25.0%

30.0%

35.0%

Source: S&P Dow Jones Indices LLC. Data based on annualized risk and return of S&P 500 sectors from Dec. 31, 1999, to Dec. 31, 2023,
with the exception of S&P 500 Real Estate from Oct. 9, 2001, to Dec. 31, 2023. Past performance is no guarantee of future results. Chart isprovided for illustrative purposes.

Exhibit 18: S&P 500 Sectors Ranked by Beta
1.60

35.0%
1.39

1.40

30.0%
1.21
1.06

1.07

1.11

20.0%

0.82
0.80

0.72
0.64

0.60

25.0%

0.97

1.00

Beta

1.06

15.0%

0.56

Annualized Volatility

1.20

10.0%

0.40
0.20

5.0%

0.00

0.0%

Beta (LH)

Annualized Volatility (RH)

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023, except for Real Estate from Oct. 9, 2001, throughDec. 31, 2023. Past performance is no guarantee of future results. Chart is provided for illustrative purposes.

Research18
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Natural Selection: Tactics and Strategy with Equity Sectors

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As Exhibit 18 shows, Consumer Staples and Utilities, for example, typically display lower
volatility than other sectors. Accordingly, the ability of these two sectors to offer calmer waters
can make them more attractive in times of market stress. Conversely, sectors such as
Information Technology and Financials tend to offer a greater participation in bull market gains,
but at the cost of a typically higher level of volatility than their sectoral peers.

Correlation Across Sectors
If some sectors are outperforming the market, then other sectors must be underperforming.
Consequently, the performance of the S&P 500 sectors is particularly distinguished in relative
terms. Exhibits 19 and 20 show that the relatively low correlations observed on average
between the excess returns of sectors and industries, respectively, based on a rolling threemonth comparison. As might be suggested by Exhibit 17, there are some natural pairs andopposites: Consumer Staples, Utilities and Health Care tend to swim together, while
Information Technology and Consumer Staples, conversely, tend to offer opposite relative
performance.

Communication
Services
Consumer
Discretionary
Consumer
Staples

-0.03

1.00

0.07

-0.24

1.00

Energy

-0.07

-0.26

0.01

1.00

Financials

-0.26

0.02

-0.09

0.10

1.00

Health Care

0.00

-0.29

0.59

-0.02

-0.10

1.00

Industrials

-0.24

0.03

-0.01

0.15

0.36

-0.11

1.00

Information
Technology

-0.01

0.10

-0.59

-0.34

-0.39

-0.54

-0.30

1.00

Materials

-0.22

0.08

-0.02

0.25

0.18

-0.11

0.42

-0.25

1.00

Real Estate

-0.13

0.16

0.08

-0.15

0.24

-0.04

0.12

-0.21

0.09

1.00

Utilities

0.09

-0.31

0.54

0.09

-0.14

0.40

-0.10

-0.42

-0.10

0.19

Utilities

Real Estate

Materials

Information
Technology

Industrials

Health Care

Financials

EnergyConsumer
Staples

Consumer
Discretionary

SectorCommunication
Services

Exhibit 19: S&P 500 Sector Excess Return Correlations

1.00

1.00

Source: S&P Dow Jones Indices LLC. Data based on correlation of one-month excess returns versus the S&P 500 from Dec. 31, 1999, toDec. 31, 2023. Past performance is no guarantee of future results. Table is provided for illustrative purposes.

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Natural Selection: Tactics and Strategy with Equity Sectors

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Aerospace &Defense1.00

Biotechnology-0.01 1.00

Technology
Hardware
Health Care
EquipmentInternet

Software & Services

Regional Banks

Insurance

Capital Markets

Banks

Transportation

Telecom

Semiconductors

RetailPharmaceuticals

Oil & Gas Equipment-0.04 0.40 1.00
0.19 0.52 0.00 1.00

Home Builders

0.12 -0.03 0.12 0.03 1.00

Health Care
Services

0.38 0.18 -0.17 0.53 0.19 1.00

Metals & Mining

0.30 -0.07 0.14 0.00 0.09 0.14 1.00

Oil & Gas
Exploration &Production
Oil & Gas
Equipment

Oil & Gas Exploration &Production

Metals & Mining

Health Care Services

Home Builders

Health Care Equipment

Technology Hardware

Biotechnology

SectorAerospace & Defense

Exhibit 20: S&P Select Industries Excess Return Correlations

0.18 -0.06 -0.01 0.01 0.03 0.10 0.49

1.00

0.26 0.04 0.19 0.00 0.03 0.06 0.53

0.82 1.00

Pharmaceuticals

0.07 0.44 -0.17 0.47 -0.09 0.38 -0.14

0.04 -0.05 1.00

Retail0.15 -0.02 0.24 0.04 0.47 0.17 0.16

0.10 0.16 -0.08 1.00

Semiconductors-0.11 0.41 0.74 0.01 0.11 -0.18 0.10

-0.03 0.12 -0.15 0.16 1.00

Telecom-0.10 0.30 0.61 0.04 -0.12 -0.11 0.11

-0.06 0.14 -0.08 0.15 0.59 1.00

Transportation

0.37 -0.07 0.10 -0.05 0.37 0.14 0.25

0.02 0.05 -0.06 0.33 0.03 -0.10 1.00

Banks

0.18 0.11 0.11 0.01 0.32 0.07 0.01

0.13 0.18 0.06 0.19 0.03 -0.04 0.42 1.00

Capital Markets

0.18 0.18 0.37 0.06 0.33 0.14 0.22

0.12 0.18 0.01 0.27 0.26 0.25 0.35 0.51 1.00

Insurance

0.25 -0.13 -0.10 -0.12 0.15 0.11 -0.02

0.01 0.12 0.00 0.00 -0.26 -0.12 0.20 0.44 0.31 1.00

Regional Banks

0.19 0.16 0.11 0.06 0.32 0.13 -0.01

0.13 0.17 0.09 0.23 0.02 -0.06 0.45 0.95 0.46 0.42 1.00

Software &Services

0.20 0.38 0.62 0.32 0.15 0.24 0.10

0.02 0.08 0.09 0.25 0.46 0.42 0.15 0.03 0.31 -0.10 0.06 1.00

Internet

0.14 0.34 0.50 0.30 0.18 0.24 0.16

0.12 0.15 0.11 0.41 0.41 0.36 0.16 0.04 0.25 -0.14 0.06 0.78 1.00

Source: S&P Dow Jones Indices LLC. Data based on correlation of one-month excess returns versus the S&P 1500 from Dec. 31, 1999, toDec. 31, 2023. The index launch date for indices in this table range from Jan. 27, 2006, to Feb. 1, 2016. Past performance is no guarantee of
future results. Chart is provided for illustrative purposes. All information for an index prior to its launch date is hypothetical back-tested, notactual performance, based on the index methodology in effect on the launch date. Back-tested performance reflects application of an index
methodology and selection of index constituents with the benefit of hindsight and knowledge of factors that may have positively affected its
performance, cannot account for all financial risk that may affect results and may be considered to reflect survivor/look ahead bias. Actual
returns may differ significantly from, and be lower than, back-tested returns. This back-tested data may have been created using a “Backward
Data Assumption.” For more information on “Backward Data Assumption” and back-testing in general, please see the Performance Disclosure
at the end of this document.

The differentiated and lowly correlated excess returns of sectors and industries present
investors with an opportunity set for seeking outperformance, and there are myriad
approaches to sector tilting or rotation. Nonetheless, some common ground can be found in
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

the basic observation that certain sectors have tended to fare better or worse depending onwhether the market is rising or falling. Knowing which sectors have historically outperformed ineach phase, an investor may seek to forecast where their economy is headed and change
their sector allocations accordingly.
For example, simple binary defensive/cyclical categorization can also be effective. Bucketing
sectors into one of these two groups based on ranking their risk attributes and their excess
returns during rising or falling markets (see Exhibit 21) can allow for rational tilts based onowning sectors that offer relatively better performance in each environment.
Exhibit 21: Sector Excess Performance in 3-Month Up and Down Periods
8.0%
6.0%

6.17%

5.46%
4.33%

3.50%

4.0%

0.70%

0.55%

0.0%
-0.14%-0.23%

0.63%

0.79%

0.42%

0.02%

-1.39%-0.42%-1.70%-2.0%-1.18%-0.25%-1.87%-2.07%

Consumer Staples

0.77%

Utilities

1.90%

2.0%

Communication Services

Performance

2.76%-2.95%-4.0%-6.0%-6.57%

Health Care

EnergyReal Estate

Materials

Industrials

Financials

Consumer Discretionary

Information Technology

S&P 500 Average Total Return for Up/Down
Periods-8.0%

Defensive

Cyclical

3-Month Up-Market Excess

3-Month Down-Market Excess

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023, except for Real Estate from Oct. 9, 2001, throughDec. 31, 2023. Excess return for S&P 500 sectors versus the S&P 500 over rolling periods of 63 trading days (three months). Past
performance is no guarantee of future results. Chart is provided for illustrative purposes.

In the following section, we explore performance of sectors and blends of sectors throughmajor market expansions and contractions since the turn of the 21st century, illustrating the

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

power of sector-based approaches to navigating broader market cycles. We will look closer
during seven sequential periods (see Exhibit 22) of differing market environments.14
Exhibit 22: Major Market Periods since December 1999
Market Period

Beginning & End Dates

S&P 500 Total Return (%)

The Dot-Com Crash of 2000

Sept. 1, 2000–Oct. 9, 2002

-47.4

Post-Crash Recovery

Oct. 9, 2002–Oct. 9, 2007

120.7

Global Financial Crisis (GFC)

Oct. 9, 2007–March 9, 2009

-55.3

Post-GFC Bull Market

March 9, 2009–Feb. 19, 2020

528.9

COVID-19 Crash

Feb. 19, 2020–March 23, 2020

-33.8

COVID-19 Recovery

March 23, 2020–Jan. 12, 2022

117.3

2022 Bear Market

Jan. 12, 2022–Oct. 12, 2022

-23.4

2022-2023 Recovery

Oct. 12, 2022–Dec. 31, 2023

36.1

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Tableis provided for illustrative purposes.

We begin with the following five groupings of typically defensive and cyclical sectors.15
The Defensive Blend combines five lower beta sectors, namely Consumer Staples, HealthCare, Energy, Utilities and Communication Services, with the goal of harnessing their generally
lower risk while diversifying away some single-sector risks.
The Defensive Blend of Equal Weight comprises the same five defensive sectors above, buteach sector itself uses a methodology that equal weights the underlying constituents.
The Cyclical Blend comprises five sectors on the higher end of the beta spectrum, namely
Consumer Discretionary, Industrials, Information Technology, Materials and Financials, whichhave tended to outperform in rising markets.
The Cyclical Blend of Equal Weight is comprised of the same five cyclical sectors above, buteach sector itself uses a methodology that equal weights the underlying constituents.
Finally, we include a simple Equal Weighted Blend of all individually cap-weighted S&P 500
sectors (10 until the addition of Real Estate in 2001).

14

Beginning and end dates are chosen based on peak and trough index values for the S&P 500 from Dec. 31, 1999, through June 30, 2022.

15

For purposes of analysis, Real Estate is excluded not only because its performance generally lies between other sectors are clearly moredefensive or cyclical, but also because the S&P 500 Real Estate sector was a relatively recent carve-out from Financials (in 2018) and does
not have the same length of index history as its peers.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

None of the sector blends described in Exhibit 23 are optimized for a specific investment
outcome, thus they are not prescriptive. Instead, the blends are intentionally simple and naïve
to any individual investor’s objectives.
Exhibit 23: Simple Sector Blend Construction
Sector Portfolio
Defensive Blend
Defensive Blend of Equal Weight
Cyclical Blend

Cyclical Blend of EW
Equal Weighted Blend

Description
Equal-weighted combination of five cap-weighted defensive sectors (Utilities, Energy,
Consumer Staples, Health Care and Communication Services) rebalanced monthly.
Equal-weighted combination of five equal-weighted defensive sectors (Utilities, Energy,
Consumer Staples, Health Care and Communication Services), rebalanced monthly.
Equal-weighted combination of five cap-weighted cyclical sectors (Information
Technology, Financials, Materials, Consumer Discretionary and Industrials), rebalanced
monthly.
Equal-weighted combination of five equal-weighted cyclical sectors (Information
Technology, Financials, Materials, Consumer Discretionary and Industrials), rebalanced
monthly.
Equal-weighted blend of cap-weighted S&P 500 sectors, rebalanced monthly*.

Source: S&P Dow Jones Indices LLC. *Equal weighted 10-sectors prior to October 2001 with beginning of Real Estate Sector index levels.
Equal weighted 11-sectors including Real Estate for all periods after. Table is provided for illustrative purposes.

Full-Period Summary
While Exhibits 8 and 9 illustrated the cumulative performance of sectors throughout 21st
century crises and recoveries, Exhibits 24-25 show how illustrative blends have led to different
outcomes through simple yet intuitive combinations that harness sector cyclicality.
Exhibit 24: Cumulative Sector Blends Performance
1000.0%

Dot-Com Crash

2022 Bear Market

GFC

COVID-19

Cumulative Performance

800.0%
600.0%
400.0%
200.0%
0.0%

Dec. 2023

Dec. 2022

Dec. 2021

Dec. 2020

Dec. 2019

Dec. 2018

Dec. 2017

Dec. 2016

Dec. 2015

Dec. 2014

Dec. 2013

Dec. 2012

Dec. 2011

Dec. 2010

Dec. 2009

Dec. 2008

Dec. 2007

Dec. 2006

Dec. 2005

Dec. 2004

Dec. 2003

Dec. 2002

Dec. 2001

Dec. 2000

Dec. 1999-200.0%

S&P 500

Market Crises

Defensive Blend

Cyclical Blend

Defensive Blend of Equal Weight

Cyclical Blend of Equal Weight

Equal Weight Blend
Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, through Dec. 31, 2023. The S&P 500 Equal Weight Sector Indices werelaunched on June 20, 2006. All data prior to index launch date are back-tested hypothetical data. Past performance is no guarantee of future
results. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure
linked at the end of this paper for more information regarding back-tested performance.
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 25: Periodic and Cumulative Performance of Sectors and Blends
S&P 500
Category
Sector
Total
Return.

S&P 500-47.40120.70-55.30528.90-33.80117.30-23.4036.10

410.9019.60

Energy23.30

157.109.90-451.30-22.10

74.70

55.00

-27.40475.3028.60

Utilities-9.80

106.8012.40-151.70-1.80-52.8013.80-28.60448.5020.10

Materials

37.10

73.80

-2.80

-188.30

-2.30

25.70

0.60

-7.70

474.5024.40

Financials

16.30

-2.40

-26.40124.40

-9.10

26.60

-2.40

-8.50

225.0029.70-32.90

31.50

3.00

423.40

2.60

26.10

-7.20

32.20

433.50

27.50

13.80

-32.70-1.50

355.30

2.10

7.50

-7.00

-5.20

541.10

22.70

61.40

-64.0026.60-173.80

9.80-49.4013.10-24.30584.2015.20

Health Care

27.60

-67.9017.30-40.805.90-29.0013.80-21.80636.4018.10

Industrials

7.20

27.80

-8.40

51.50

-7.90

7.10

4.20

1.50

474.1021.80-17.80

38.20

7.60

-264.205.20-22.00-15.20

18.20

75.70

22.90

-

80.60

-17.80205.80-3.90-13.50-5.60-12.60496.4030.10

S&P 500-47.40120.70-55.30528.90-33.80117.30-23.4036.10

410.9019.60

Defensive Blend

12.90

23.50

15.20

-225.40-0.90-16.5014.60-17.00489.7016.70

Cyclical Blend

3.90

20.30

-8.50

137.70

-2.90

19.90

-2.30

2.70

482.80

22.40

16.50

87.20

11.70

-157.10

-3.60

-6.00

15.20

-20.90793.60

17.90

14.50

69.80

-9.50

209.30

-7.10

39.50

-0.20

-3.50

801.20

23.40

9.60

29.00

0.20

-39.00

-2.10

0.00

4.80

-7.70

520.2019.10

Information
Technology
Consumer
Discretionary
Consumer
Staples

SectorExcessReturnCommunication
Services
Real Estate*
Total
Return.

Blend
ExcessReturnJan. 2000Post2022
2022Jan. 2000Dot Com Dot Com
Global
GFC COVID-19
Dec. 2023
Crash
Bear
2023
Dec. 2023
Crash Recovery Financial Recovery
2020
Cum.
Recovery Market Recovery
Ann. Vol.*(%)(%) Crisis (%)(%) Crash (%)
Return*
(%)
(%)
(%)
(%)
(%)

Defensive Blend
Equal Weighted
Cyclical Blend
Equal Weighted
Equal Weighted
Blend

Source: S&P Dow Jones Indices LLC. Cumulative data from Dec. 31, 1999, to Dec. 31, 2023, except Real Estate from Oct. 9, 2001, to Dec.
31, 2023. Periodic data from Sept. 1, 2000, to Dec. 31, 2023. The S&P 500 Equal Weight Sectors indices were launched on June 20, 2006.
All data prior to index launch date are back-tested hypothetical data. Past performance is no guarantee of future results. Table is provided forillustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure linked at the end of this paper
for more information regarding back-tested performance.

Some key observations stand out when we look at the cumulative results for sectors andhypothetical blends. Over the entire sequence of crises and recoveries from 2000 through2023:–

During each of the eight crisis and recovery periods, an average of 6 out of 11 sectors
outperformed.

–

Of the 11 sectors, 8 outperformed the S&P 500 on a cumulative basis.

–

All five of the sector blends outperformed on a cumulative basis.

–

Sector blends produced less volatile performance than their individual components,
underscoring the historical diversification benefits of combining sectors in a portfolio.

–

Across the eight periods examined from September 2000 through December 2023, theaverage defensive sector has outperformed in falling periods 75% of the time, and theaverage cyclical sector has outperformed in rising markets 70% of the time.

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Natural Selection: Tactics and Strategy with Equity Sectors

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8. Conclusion
Sectors and industries have endured and indeed grown as popular tools for investors due tofeatures including their precision of targeted exposure, low correlation to one another andutility to express active views on market and economic conditions.
Sector taxonomy (GICS) has allowed for the creation of new indices and, in turn, investment
products and sector- or industry-based investment strategies. For global investors, S&P 500
Sectors remain powerful and efficient tools to strategically adjust for home biases, maketactical tilts and harness the diversification qualities that have allowed simple sector blends tooutperform the majority of single stocks and the broader index itself.
The changes in sector leadership through time are not random, but instead evidence clear
patterns of alignment with different market regimes. Harnessing these patterns andrelationships has been a foundation of sector investing for decades and creates a frameworkwith enduring utility.
Like species through time, thousands of stocks may come and go, adapting and thriving or
petering out in extinction. Single securities may follow unpredictable paths, but sectors andindustries endure because they bring order, enable better decisions and improveunderstanding of the equity ecosystem for investors around the world.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

9. Appendices
Appendix A – Dispersion and Skew Illustration
To unravel how higher dispersion portfolios can actually present less opportunity for stock
pickers, we offer the following simple illustration in Exhibit 26.
Consider two hypothetical 10-stock portfolios, Portfolio 1 and Portfolio 2, with weights andstock-level total returns below:
Exhibit 26: Dispersion in Two Illustrative Portfolios
Portfolio 1

Portfolio 2

25.0%

40.0%

20.0%
30.0%

15.0%

20.0%

3.6%

Dispersion

Dispersion

10.0%
5.0%
0.0%
-5.0%

0.2%

-10.0%

3.6%

10.0%
0.0%
-1.3%

-10.0%-15.0%-20.0%-20.0%-25.0%-30.0%
A

B

C

D

E

F

G

H

I

Total Return

WeightPortfolio Total Return

Average Stock

L

A

B

C

D

E

F

G

H

I

Total Return

WeightPortfolio Total Return

Average StockL

Both portfolios are hypothetical.
Source: S&P Dow Jones Indices LLC. Charts are provided for illustrative purposes.

Both portfolios have the same total return, 3.6%. However, they differ in that Stock A has ahigher return in Portfolio 2 while Stocks B, C, D and E are negative instead of positive.
As results indicate in Exhibit 27, Portfolio 2 has higher dispersion (16%) than Portfolio 1 (10%).
Would it be wise to argue that higher dispersion makes Portfolio 2 the preferred hunting
ground for stock pickers? Positively skewed returns suggest otherwise. In Portfolio 1, 50% of
the stocks outperform the average stock return of 0.20%, but Portfolio 2’s -1.4% average
return is surpassed by only 10% of the stocks. Outside of a manager possessing the skill topick the one winner from Portfolio 2, others should wade carefully into higher-dispersion waters
lest they fall prey to what lurks beneath.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 27: Illustrative Portfolio ComparisonsPortfolio 1

Portfolio 2

Stock
Total Return (%)

Weight (%).

Total Return (%).

Weight (%)

A

20.0

20.0

35.0

20.0

B

8.0

10.0

-8.0

10.0

C

3.0

10.0

-3.0

10.0

D

3.0

10.0

-2.0

10.0

E

2.0

10.0

-1.0

10.0

F

-1.0

10.0

-1.0

10.0

G

-2.0

10.0

-2.0

10.0

H

-3.0

10.0

-3.0

10.0

I

-8.0

5.0

-8.0

5.0

J

-20.0

5.0

-20.0

5.0

Total Return

3.6

3.6

Average Stock

0.2

-1.3

Dispersion

10.0

16.3

% Stocks > Average

50.0

10.0

All portfolios are hypothetical.
Source: S&P Dow Jones Indices LLC. Table is provided for illustrative purposes.

Research27
For use with institutions only, not for use with retail investors.

Research

For use with institutions only, not for use with retail investors.

Materials

25%
474%

20%

15%

Over 1000%

Over 1000%

15%950% to 1000%20%950% to 1000%

25%

900% to 950%

576% 636%

900% to 950%

Health Care

Over 1000%

950% to 1000%

900% to 950%

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

76%116%850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%

Communication Services

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%103%

550% to 600%

500% to 550%

263%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

45%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

30%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

% of Constituents

17%

50% to 100%30%

0% to 50%

-50% to 0%-100% to -50%

% of Constituents
30%

0% to 50%

-50% to 0%-100% to -50%

% of ConstituentsNatural Selection: Tactics and Strategy with Equity Sectors
July 2024

Appendix B: Skew among S&P 500 Sector Constituents

Exhibit 28: Performance Skew by Sector
Frequency

25%
Median Stock20%
Average Stock15%
Index Total Return

10%

5%

0%

Cumulative Return Range
Frequency

Median Stock

Average Stock

Index Total Return

10%

5%

0%

Cumulative Return Range

Frequency

Median Stock

Average Stock

Index Total Return

10%

5%

0%

Cumulative Return Range

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Charts
are provided for illustrative purposes.

28

Research

For use with institutions only, not for use with retail investors.
225%

20%
Average Stock15%
Index Total Return

Over 1000%

Over 1000%

Median Stock950% to 1000%

900% to 950%449%

950% to 1000%

900% to 950%

Frequency

Over 1000%

Financials

850% to 900%

Utilities

950% to 1000%

25%

900% to 950%

562%

850% to 900%

Industrials

850% to 900%

25%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

15%800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

20%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

474%

550% to 600%

500% to 550%

450% to 500%

126%450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

325%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

% of Constituents

132%

300% to 350%

210%

250% to 300%

20%

200% to 250%

60%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

% of Constituents
30%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

% of ConstituentsNatural Selection: Tactics and Strategy with Equity Sectors
July 2024

Exhibit 28: Performance Skew by Sector (cont.)

25%

Average Stock

Index Total Return

10%

5%

0%

Cumulative Return Range
Frequency

Median Stock

10%

5%

0%

Cumulative Return Range

Frequency

Median Stock

15%
Average Stock10%
Index Total Return

5%

0%

Cumulative Return Range

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Charts
are provided for illustrative purposes.

29Research

For use with institutions only, not for use with retail investors.
541%

20%

Over 1000%25%950% to 1000%

Consumer Discretionary
Over 1000%

950% to 1000%

900% to 950%

584%

900% to 950%

Consumer Staples

Over 1000%

950% to 1000%

900% to 950%

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

475%

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

Energy850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

332%

550% to 600%

403%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

% of Constituents

189%

450% to 500%

24%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

199%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

% of Constituents

36%

150% to 200%

100% to 150%

50% to 100%30%

0% to 50%

-50% to 0%-100% to -50%

% of ConstituentsNatural Selection: Tactics and Strategy with Equity Sectors
July 2024

Exhibit 28: Performance Skew by Sector (cont.)
25%
Frequency

20%
Median Stock

15%
Average Stock10%
Index Total Return

5%

0%

Cumulative Return Range

25%
Frequency

20%
Median Stock

15%
Average Stock10%
Index Total Return

5%

0%

Cumulative Return Range

Frequency

Median Stock

Average Stock15%
Index Total Return

10%

5%

0%

Cumulative Return Range

Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Charts
are provided for illustrative purposes.

30

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 28: Performance Skew by Sector (cont.)% of Constituents

Information Technology

Frequency

35%

Median Stock

30%

24%

445%

25%

433%

Average Stock
Index Total Return

20%
15%
10%
5%

Over 1000%

950% to 1000%

900% to 950%

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

0%(% of Constituents

Cumulative Return Range

Real Estate
30%

48%

150%

Frequency

496%

Median Stock25%

Average Stock20%

Index Total Return

15%
10%
5%

Over 1000%

950% to 1000%

900% to 950%

850% to 900%

800% to 850%

750% to 800%

700% to 750%

650% to 700%

600% to 650%

550% to 600%

500% to 550%

450% to 500%

400% to 450%

350% to 400%

300% to 350%

250% to 300%

200% to 250%

150% to 200%

100% to 150%

50% to 100%0% to 50%

-50% to 0%-100% to -50%

0%Cumulative Return Range
Source: S&P Dow Jones Indices LLC. Data from Dec. 31, 1999, to Dec. 31, 2023. Past performance is no guarantee of future results. Charts
are provided for illustrative purposes.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Appendix C: Crisis and Recovery Case Studies
With daily index levels for individual sectors as well as the sector blends, we can take a deeper
dive into the performance of each through four major crises and three periods of recovery insequence since December 1999.

Walk Through the Wild: Two Decades of Crisis and Recovery
Dot-Com Crash of 2000
After peaking on Sept. 1, 2000, the S&P 500 began a 47% decline over the subsequent 25
months, mostly due to the Information Technology sector’s precipitous 80% drop over thesame period combined with its position as the largest sector weight in the benchmark.
Exhibit 29 details how 9 out of 10 sectors declined over this period, with only Consumer
Staples remaining in positive territory with a 14% return. However, on a relative (excess
return) basis, 7 out of 10 sectors outperformed the S&P 500. Among the five sector blends, alloutperformed the S&P 500 as well, with the Defensive Blend of Equal Weight leading at 24%
excess performance.
Exhibit 29: Sectors and Blends During the Dot-Com Crash
14%

20%
0%
-10%

Performance

-20%

-20%

-24%
-31%

-40%

-34%

-60%

-31%

-35%

-40%

-33%

-44%

-38%

-57%
-65%

-80%
-80%

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Cyclical Blend

Defensive Blend of Equal Weight

S&P 500

Defensive Blend

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

Utilities

Energy-100%

Source: S&P Dow Jones Indices LLC. Data from Sept. 1, 2000, through Oct. 9, 2002. Real Estate data excluded due to analysis datepreceding availability of index levels. The S&P 500 Equal Weight Sectors indices were launched on June 20, 2006. All data prior to index
launch date are back-tested hypothetical data. Past performance is no guarantee of future results. Chart is provided for illustrative purposes
and reflects hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information
regarding back-tested performance.
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Post-Crash Recovery
After the S&P 500 reached its low point on Oct. 9, 2002, the market shifted into five years ofrecovery, generating 121% return over the whole period. Six out of 10 S&P 500 sectors
outperformed the S&P 500, and Real Estate became the seventh as its index history began in
2001.16 Interestingly, Energy and Utilities were the best-performing sectors, outperforming the
S&P 500 by 157% and 107%, respectively, and underscoring the potential for typicallydefensive or cyclical sectors to thrive in opposite parts of the cycle under the right conditions(see Exhibit 30). All five blends of sectors also fared well in the recovery and generated
excess return, with the Defensive Blend of Equal Weight outpacing the S&P 500 by 87%.
Exhibit 30: Sectors and Blends during the Post-Crash Recovery
278%

250%

227%

152%

148%

190%

159%

150%

144%

141%

Cyclical Blend

Perofrmance

208%

201%

195%

200%

Defensive Blend

300%

150%

118%
88%

100%

57%

53%

50%

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Defensive Blend of Equal Weight

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

Utilities

Energy0%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from Oct. 9, 2002, through Oct. 9, 2007. The S&P 500 Equal Weight Sectors indices werelaunched on June 20, 2006. All data prior to index launch date are back-tested hypothetical data. Past performance is no guarantee of future
results. Chart is provided for illustrative purposes and reflects hypothetical historical performance. Please see the Performance Disclosure at
the end of this document for more information regarding back-tested performance.

Global Financial Crisis
Although some warning signs emerged in mid-2007, it wasn’t until October of that year that the
S&P 500 peaked and began its descent during the Global Financial Crisis (GFC). While the
S&P 500 declined 55% during the nearly two-year downturn, the Financials sector fell by an
16

Although Real Estate became the 11th GICS sector in 2018, we begin including it in this analysis beginning with its earliest available index
level data in October 2001.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

additional 26% as banks and other institutions of all sizes suffered catastrophic losses. During
the GFC, all five defensive sectors outperformed the broader market while Information
Technology was the only outperformer among five cyclical sectors (see Exhibit 31). Across thefive sector blends, both the Cyclical Blend and the Cyclical Blend of Equal Weightunderperformed due to their large allocations to the Financials sector.
Exhibit 31: Sectors and Blends during the GFC
0%
-10%

-30%

-29%

-40%

-38%
-45%

-40%

-43%

-44%

-48%
-52%

-60%

-55%

-57%

-58%

-64%

-70%

-64%

-65%

-73%

-80%

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Defensive Blend of Equal Weight

Cyclical Blend

Communication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Materials

Utilities

Energy-90%

Financials-82%

Defensive Blend-50%

Real Estate

Perofrmance-20%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from Oct. 9, 2007, through March 9, 2009. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

Post-GFC Bull Market
Although the S&P 500 recovered after March 2009, generating a 529% return over the next 11
years, lingering effects of the GFC and a concurrent recession weighed heavily on some
sectors more than others. In particular, Energy trailed the S&P 500 by more than 450% asplummeting oil and gas prices combined with a contraction in credit to squeeze energy
company revenues. All four of the other traditionally defensive sectors also trailed the S&P
500. Among cyclical sectors, however, Materials was the only laggard while Information
Technology led other outperforming sectors with a 124% excess return (see Exhibit 32).
Much of Information Technology’s outperformance came in the latter five years of the recovery,leading to outperformance for the Cyclical Blend and Cyclical Blend of Equal Weight, while theother three trailed the S&P 500 due to their relative underweight of large-cap Information
Technology companies.
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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 32: Sectors and Blends in the Post-GFC Recovery
1000%
900%
800%

Performance

700%
600%
500%
400%
300%
200%
100%

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Defensive Blend of Equal Weight

Cyclical Blend

Defensive Blend

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

Utilities

Energy0%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from March 9, 2009, through Feb. 19, 2020. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

2020 COVID-19 Crash
After nearly 11 years of market expansion, the emergence of a global pandemic led to one of
the most severe crashes in nearly a century. From a high on Feb. 19, 2020, the S&P 500
plummeted 34% over just 23 trading days. No sector was spared and correlation across themarket spiked as investors headed for the exits. Energy fared the worst, falling an additional
22% as it became clear that a halt to normal activities would severely alter demand for fuel andenergy. Conversely, Information Technology slightly outperformed as virtual connections
became even more vital in daily life along with Consumer Staples and Health Care (see Exhibit33). All five sector blends trailed the market by margins ranging from 1% to 7%.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 33: Sectors and Blends during the 2020 COVID-19 Crash
0%-10%

Performance

-20%
-30%
-40%
-50%

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Defensive Blend of Equal Weight

Cyclical Blend

Defensive Blend

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

Utilities

Energy-60%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from Feb. 19, 2020, through March 23, 2020. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

COVID-19 Recovery Rally
Although a timeline for getting back to “normal” was not yet clear, the market bottom on March
23, 2020, became a launch pad for a two-phased recovery. Initially, Information Technology
continued to lead out of the bottom as a result of stay-at-home lifestyles combined withinvestors’ hunger for companies generating earnings growth. For the same reasons, Energy
lagged as transportation and manufacturing demand slowed down significantly. However,announcements of successful virus prevention and treatments in late 2020 sparked a“reopening” rally based on hopes of a return to normal life. Energy stocks quickly shot upwardand it soon became the best-performing sector since the March 2020 nadir, outperforming the
S&P 500 by 77% through Jan. 12, 2022 (see Exhibit 34).
The Cyclical Blend of Equal Weight was the best-performing sector combination during therecovery, beating the S&P 500 by 40%, while the Cyclical Blend also outperformed. Defensive
Blend trailed the market and the Equal Weight Blend was flat.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 34: Sectors and Blends during the COVID-19 Recovery
250%

Performance

200%

150%

100%

50%

Equal Weighted Blend

Cyclical Blend of Equal
Wweight

Defensive Blend of Equal
WeightCyclical Blend

Defensive Blend

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

Utilities

Energy0%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from March 23, 2020, through Jan. 12, 2022. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

2022 Bear Market
The period analyzed and displayed in Exhibit 35 was the bear market beginning in January
2022. From a peak on Jan. 12, 2022, to a trough on Oct. 12, 2022, the S&P 500 dropped
23%. Although it previously led the market on the way up, Information Technology was thesecond-biggest decliner as the largest sector in the S&P 500 fell 31%. Energy was the only 1
out of 11 S&P 500 sectors to generate positive performance during this period, up 32% and
55% ahead of the S&P 500. The Defensive Blend and Defensive Blend of Equal Weight each
outperformed by 15%, and the Equal Weight Blend surpassed the S&P 500 by 5%.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 35: Sectors and Blends during the 2022 Bear Market
40%
30%
20%

Performance

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

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Defensive Blend of Equal Weight

Cyclical Blend

Defensive Blend

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

Utilities

Energy-50%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from Jan. 12, 2022, through Oct. 12, 2022. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

2022-2023 Recovery
The period analyzed and displayed in Exhibit 36 illustrates the market recovery beginning on
Oct. 12, 2022, as the S&P 500 climbed more than 50% through December 2023. Information
Technology and Communication Services were the leading sectors, reversing theirunderperformance during the previous downturn. In fact, the disproportionate dominance of
these two sectors combined with their heavy weights in the S&P 500 meant that most othersectors and blends lagged, with Industrials the only other sector and the Cyclical Blend theonly blend outperforming, by 1.5% and 2.7%, respectively.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 36: Sectors and Blends during the 2022-2023 Recovery
80%
68%

70%
60%

54%

28%

30%

33%

31%

28%

28%
24%
19%

20%
12%

9%

7%

Utilities

10%

39%

38%

40%

EnergyPerformance

50%

15%

14%

Equal Weighted Blend

Cyclical Blend of Equal Wweight

Defensive Blend of Equal Weight

Cyclical Blend

Defensive Blend

Real EstateCommunication Services

Industries

Health Care

Consumer Staples

Consumer Discretionary

Information Technology

Financials

Materials

0%

S&P 500
Source: S&P Dow Jones Indices LLC. Data from Oct. 12, 2022, through Dec. 31, 2023. Past performance is no guarantee of future results.
Chart is provided for illustrative purposes.

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Appendix D: Sector, Industry and Thematics
Futures and ETFs
Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2
Name

Index

Amundi PEA S&P US Consumer Staples ESG
S&P 500 Plus Sustainability Enhanced Consumer Staples Index (USD)
UCITS ETF
NTR
Amundi S&P Global Industrials ESG UCITS ETF S&P Developed Ex-Korea LargeMidCap Sustainability Enhanced Industrials-DR- EUR
Index - Benchmark TR Net
Amundi S&P Global Information Technology ESG S&P Developed Ex-Korea LargeMidCap Sustainability Enhanced
UCITS ETF -DR- EUR
Information Technology Index - EUR - Benchmark TR Net
Amundi S&P Global Materials ESG UCITS ETF S&P Developed Ex-Korea LargeMidCap Sustainability Enhanced Industrials
EUR
Index - Benchmark TR Net
BetaPro S&P/TSX Capped Energy -2x Daily Bear
S&P/TSX Capped / Energy
ETF
BetaPro S&P/TSX Capped Energy 2x Daily Bull
S&P/TSX Capped / Energy
ETF
BetaPro S&P/TSX Capped Financials -2x Daily
S&P/TSX Capped / Financial
Bear ETF
BetaPro S&P/TSX Capped Financials 2x Daily
S&P/TSX Capped / Financial
Bull ETFBMO Junior Gold Index ETF

Dow Jones North America Select Junior Gold Index - CAD

Capital Dow Jones U.S. Real Estate Index ETF

DJ Global United States (All) / Real Estate -SS

Comm. Services Select Sector SPDR Fund

S&P Communication Services Select Sector Index

Cons. Discretionary Select Sector SPDR Fund

Consumer Discretionary Select Sector

Cons. Staples Select Sector SPDR Fund

Consumer Staples Select Sector

Credit Suisse S&P MLP Index ETN

S&P MLP

Direxion Daily Aerospace & Defense Bull 3X
SharesDJ US Select / Aerospace & Defense

Direxion Daily Cons. Discretionary Bull 3x Shares Consumer Discretionary Select Sector
Direxion Daily Energy Bear 2X Shares

Energy Select Sector

Direxion Daily Energy Bull 2x Shares

Energy Select Sector

Direxion Daily Financial Bear 3X Shares

Financial Select Sector

Direxion Daily Financial Bull 3x Shares

Financial Select Sector

Direxion Daily Healthcare Bull 3x Shares

Health Care Select Sector

Direxion Daily Industrials Bull 3X Shares

S&P Industrial Select Sector

Direxion Daily Metal Miners Bull 2X Shares

S&P TMI

Direxion Daily Pharmaceutical & Medical Bull 3X
S&P Pharmaceuticals Select Industry
SharesDirexion Daily Real Estate Bear 3X Shares

S&P Real Estate Select Sector

Direxion Daily Real Estate Bull 3x Shares

S&P Real Estate Select Sector

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

40
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

Direxion Daily Regional Banks Bull 3X Shares

S&P Regional Banks Select Industry

Direxion Daily S&P Biotech Bear 3X Shares

S&P Biotechnology Select Industry

Direxion Daily S&P Biotech Bull 3X Shares

S&P Biotechnology Select Industry

Direxion Daily S&P Oil & Gas Exp. & Prod. Bear
S&P Oil & Gas Exploration & Production Select Industry
2X Shares
Direxion Daily S&P Oil & Gas Exp. & Prod. Bull
S&P Oil & Gas Exploration & Production Select Industry
2X Shares
Direxion Daily Software Bull 2X Shares

S&P North American Expanded Technology Software Index

Direxion Daily Technology Bear 3X SharesTechnology Select Sector

Direxion Daily Technology Bull 3x SharesTechnology Select Sector

Direxion Daily Transportation Bull 3X Shares

S&P Transportation Select Industry FMC Capped Index - Benchmark TR
Net

Direxion Daily Utilities Bull 3X Shares

Utilities Select Sector

Energy Select Sector SPDR Fund

Energy Select Sector

Financial Select Sector SPDR Fund

Financial Select Sector

First Trust S&P REIT Index FundS&P United States REIT

Fullgoal S and P Oil and Gas Exploration and
Production Select Industry ETF QDIIS&P Oil & Gas Exploration & Production Select Industry Total Return Index

Global X S&P Biotech ETF

S&P Biotechnology Select Industry

Health Care Select Sector SPDR Fund

Health Care Select Sector

Horizons S&P/TSX Capped Energy Index ETF

S&P/TSX Capped / Energy

Horizons S&P/TSX Capped Financials Index ETF S&P/TSX Capped / Financial
HSBC S&P INDIA TECH UCITS ETF

S&P India Tech Index (EUR) NTR

Industrial Select Sector SPDR Fund

S&P Industrial Select Sector

Invesco Dow Jones US Insurance UCITS ETF

Dow Jones U.S. Select Insurance Index NTR

Invesco Communications S&P US Select Sector
S&P Select Sector Capped 20% Communication Services Index
UCITS ETF
Invesco Consumer Discretionary S&P US SelectS&P Select Sector Capped 20% Consumer Discretionary Index
Sector UCITS ETF
Invesco Consumer Staples S&P US SelectS&P Select Sector Capped 20% Consumer Staples Index
Sector UCITS ETF Accum USD
Invesco Energy S&P US Select Sector UCITS
S&P Select Sector Capped 20% Energy Index
ETF
Invesco Financials S&P US Select Sector UCITS
S&P Select Sector Capped 20% Financial Services Index- TR Net
ETF
Invesco Health Care S&P US Select Sector
S&P Select Sector Capped 20% Health Care Index
UCITS ETF
Invesco Industrials S&P US Select Sector UCITS
S&P Select Sector Capped 20% Industrials Net Total Return Index - USD
ETF
Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

41
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

Invesco Materials S&P US Select Sector UCITS
ETF
Invesco Real Estate S&P US Select Sector
UCITS ETF
Invesco S&P 500 Equal Weight Communication
Services ETF
Invesco S&P 500 Equal Weight Consumer
Discretionary ETF
Invesco S&P 500 Equal Weight Consumer
Staples ETF

S&P Select Sector Capped 20% Materials Index
S&P Select Sector Capped 20% Real Estate Index
S&P 500 Equal Weight Communication Services Plus Index
S&P 500 Equal Weighted / Consumer Discretionary -SEC
S&P 500 Equal Weighted / Consumer Staples -SEC

Invesco S&P 500 Equal Weight Energy ETF

S&P 500 Equal Weight Energy Plus Index

Invesco S&P 500 Equal Weight Financials ETF

S&P 500 Equal Weighted / Financials -SEC

Invesco S&P 500 Equal Weight Health Care ETF S&P 500 Equal Weighted / Health Care -SEC
Invesco S&P 500 Equal Weight Industrials ETF

S&P 500 Equal Weighted / Industrials -SEC

Invesco S&P 500 Equal Weight Materials ETF

S&P 500 Equal Weighted / Materials -SEC

Invesco S&P 500 Equal Weight Real Estate ETF S&P 500 Equal Weighted / Real Estate - SEC
Invesco S&P 500 Equal Weight Technology ETF S&P 500 Equal Weighted / Information Technology -SEC
Invesco S&P 500 Equal Weight Utilities ETF

S&P 500 Equal Weighted / Utilities Plus

Invesco S&P SmallCap Cons. Discretionary ETF S&P Small Cap 600 / Consumer Discretionary -SEC
Invesco S&P SmallCap Consumer Staples ETF

S&P Small Cap 600 Capped Consumer Staples

Invesco S&P SmallCap Energy ETF

S&P Small Cap 600 / Energy -SEC

Invesco S&P SmallCap Financials ETF

S&P SmallCap 600 Capped Financials & Real Estate Index

Invesco S&P SmallCap Health Care ETF

S&P Small Cap 600 / Health Care -SEC

Invesco S&P SmallCap Industrials ETF

S&P Small Cap 600 / Industrials -SEC

Invesco S&P SmallCap Information Tech. ETF

S&P Small Cap 600 / Information Technology -SEC

Invesco S&P SmallCap Materials ETF

S&P Small Cap 600 / Materials -SEC

Invesco S&P SmallCap Utilities &Communication Services ETF

S&P SmallCap 600 Capped Utilities & Telecommunication Services

Invesco S&P/TSX REIT Income Index ETF

S&P/TSX Capped REIT Income Index - CAD

Invesco Tech. S&P US Select Sector UCITS ETF S&P Select Sector Capped 20% Technology Index
Invesco Utilities S&P US Select Sector UCITS
ETF

S&P Select Sector Capped 20% Utilities Index

Invesco S&P World Energy ESG UCITS ETF

S&P World ESG Enhanced Energy Index (USD) NTR

Invesco S&P World Financials ESG UCITS ETF S&P World ESG Enhanced Financials Index (USD) NTR
Invesco S&P World Health Care ESG UCITS
ETF

S&P World ESG Enhanced Health Care Index (USD) NTR

Invesco S&P World Info. Tech. ESG UCITS ETF S&P World ESG Enhanced Info. Tech. Index (USD) NTR
Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

42
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2(cont.)
ETF

Index

iPath S&P MLP ETN

S&P MLP

iShares Cohen & Steers REIT ETF

S&P Cohen & Steers US Realty Majors Portfolio

iShares Essential Metals Producers UCITS ETF S&P Global Essential Metals Producers Index (USD) NTR
iShares Expanded Tech-Software Sector ETF

S&P North American Expanded Technology Software Index

iShares Global Comm Services ETF

S&P Global 1200 Comm. Services 4.5/22.5/45 Capped

iShares Global Consumer Discretionary ETF

S&P Global 1200 Consumer Discretionary (Sector) Capped Index (USD)

iShares Global Consumer Staples ETF

S&P Global 1200 Consumer Staples (Sector) Capped Index

iShares Global Consumer Staples ETF Cert.

S&P Global 1200 / Consumer Staples -SEC

iShares Global Energy ETF

S&P Global 1200 / Energy -SEC

iShares Global Financials ETF

S&P Global 1200 / Financials -SEC

iShares Global Healthcare ETF

S&P Global 1200 / Health Care -SEC

iShares Global Healthcare ETF CDI

S&P Global 1200 Healthcare Sector Index - AUD

iShares Global Industrials ETF

S&P Global 1200 / Industrials -SEC

iShares Global Materials ETF

S&P Global 1200 / Materials -SEC

iShares Global Tech ETF

S&P Global 1200 / Information Technology -SEC

iShares Global Utilities ETF

S&P Global 1200 Utilities (Sector) Capped Index

iShares Gold Producers UCITS ETF USD

S&P Commodity Producers Gold Index - USD

iShares International Dev. Property ETF

S&P Developed x United States Property

iShares Listed Private Equity UCITS ETF

S&P Listed Private Equity Index

iShares Listed Private Equity UCITS ETF USD

S&P Listed Private Equity Index

iShares North American Tech-Multimedia
S&P North American Technology Sector Multimedia Networking
Networking ETF
iShares Oil & Gas Exploration & Production
S&P Commodity Producers Oil & Gas Exploration & Production Index UCITS ETF USD
USD
iShares S&P 500 Communication Sector UCITS
S&P 500 Capped 35/20 Communication Services Sector Index
ETF
iShares S&P 500 Consumer Discretionary Sector
S&P 500 Consumer Discretionary Index - USD
UCITS ETF
iShares S&P 500 Consumer Staples Sector
S&P 500 Capped 35/20 Consumer Staples Index - USD
UCITS ETF
iShares S&P 500 Energy Sector UCITS ETF

S&P 500 Energy Index - USD

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

43
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

iShares S&P 500 Financials Sector UCITS ETF

S&P 500 CAPPED 35/20 FINANCIALS NTR

iShares S&P 500 Health Care Sector UCITS ETF S&P 500 CAPPED 35/20 HEALTH CARE NTR
iShares S&P 500 Health Care Sector UCITS ETF S&P 500 CAPPED 35/20 HEALTH CARE NTR
iShares S&P 500 Industrials Sector UCITS ETF

S&P 500 Capped 35/20 Industrials Sector Index

iShares S&P 500 Information Technology Sector
S&P 500 CAPPED 35/20 INFORMATION TECHNOLOGY NTR
UCITS ETF
iShares S&P 500 Materials Sector UCITS ETF

S&P 500 Capped 35/20 Materials Sector Index - USD

iShares S&P 500 Utilities Sector UCITS ETF

S&P 500 Capped 35/20 Utilities Sector Index - USD

iShares S&P Global Consumer Discretionary
S&P Global 1200 Consumer Discretionary Hedged to CAD Index - CAD
Index ETF (CAD-Hedged)
iShares S&P Global Healthcare Index FundS&P Global 1200 Health Care Hedged to CAD Index - CAD(CAD-Hedged)
iShares S&P Global Industrials Index ETF (CADS&P Global 1200 Industrials Hedged to CAD Index - CAD
Hedged)iShares S&P U.S. Banks UCITS ETF USD

S&P 900 Banks (Industry) 7/4 Capped Index

iShares S&P US Banks UCITS ETF

S&P 900 Banks (Industry) 7/4 Capped Index

iShares S&P US Financials Index ETF

Financial Select Sector Index (CAD) TR

iShares S&P/TSX Capped Consumer Staples
Index Fund

S&P/TSX Capped Consumer Staples Index - CAD

iShares S&P/TSX Capped Energy Index ETF

S&P/TSX Capped / Energy

iShares S&P/TSX Capped Financials Index ETF S&P/TSX Capped / Financial
iShares S&P/TSX Capped Information
Technology Index ETF

S&P/TSX Capped Information Technology Index - CAD

iShares S&P/TSX Capped Materials Index ETF

S&P/TSX Capped Materials Index - CAD

iShares S&P/TSX Capped REIT Index ETF

S&P/TSX Capped REIT Index - CAD

iShares S&P/TSX Capped Utilities Index Fund

S&P/TSX Capped Utilities Index - CAD

iShares S&P/TSX Energy Transition Materials
Index ETF
iShares S&P/TSX Global Base Metals Index
Fund

S&P/TSX Energy Transition Materials Index (CAD) TR
S&P/TSX Global Base Metals Index - CAD

iShares S&P/TSX Global Gold Index ETF

S&P/TSX Global GoldiShares U.S. Aerospace & Defense ETF

DJ US Select / Aerospace & Defense

iShares U.S. Broker-Dealers & Securities
Exchanges ETF

DJ US Select / Investment Services

iShares U.S. Healthcare Providers ETF

DJ US Select / Health Care Providers

iShares U.S. Insurance ETF

DJ US Select / Insurance

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

44
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

iShares U.S. Medical Devices ETF

DJ US Select / Medical Equipment

iShares U.S. Oil & Gas Exploration & Production
DJ US Select / Oil & Gas Exploration & Production
ETF
iShares U.S. Oil Equipment & Services ETF

DJ US Select / Oil Equipment & Services

iShares U.S. Pharmaceuticals ETF

DJ US Select / PharmaceuticaliShares U.S. Real Estate ETF

Dow Jones U.S. Real Estate Capped Index

iShares U.S. Regional Banks ETF

DJ US Select / Regional BanksiShares US Financial Services ETF

Dow Jones U.S. Financial Services Index

iShares US Medical Devices UCITS ETF USD

Dow Jones U.S. Select Medical Equipment Capped 35/20 Index

iShares US Transportation ETF

S&P Transportation Select Industry FMC Capped Index - Benchmark TR
Gross

KB KBSTAR Global 4th Industry Revolution IT
S&P Global 1200 / Information Technology -SEC
ETF(SYNTH H)KB KBSTAR SYNTH-US Oil&Gas E&P Company
S&P Oil & Gas Exploration & Production Select Industry
ETF(H)KIM KINDEX SYNTH-Dow Jones US Real Estate
Dow Jones U.S. Real Estate Index
ETF
Kiwoom HEROES Global REITs IGIS Active ETF
S&P Global REIT Index
Units
Leverage Shares 3x Long Financials ETP
Financial Select Sector
Securities
Leverage Shares 3x Long Oil & Gas ETP
Energy Select Sector
Securities
Leverage Shares -3x Short Oil & Gas ETP
Energy Select Sector
Securities
Listed Index Fund Australian REIT (S&P/ASX200
S&P/ASX 200 A-REIT Index - AUD
A-REIT)
Materials Select Sector SPDR Fund

Materials Select Sector

MTF Sal 4D S&P Semiconductors Select Industry S&P Semiconductors Select Industry Index Net TR
NH-Amundi HANARO Global Luxury S&P ETF(Synth)S&P Global Luxury Index

Nuveen Short-Term REIT ETF

Dow Jones U.S. Select Short-Term REIT Index

ProShares S&P Kensho Smart Factories ETF

S&P Kensho Smart Factories Index

ProShares S&P Technology Dividend Aristocrats
S&P Technology Dividend Aristocrats
ETF
ProShares Short Financials

DJ Global United States (All) / Financials -IND

ProShares Short Real Estate

DJ Global United States (All) / Real Estate -SS

ProShares Ultra Basic Materials

DJ Global United States (All) / Basic Materials -IND

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

45
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

ProShares Ultra Consumer Goods

DJ Global United States (All) / Consumer Goods -IND

ProShares Ultra Consumer Services

DJ Global United States (All) / Consumer Services -IND

ProShares Ultra Financials

DJ Global United States (All) / Financials -IND

ProShares Ultra Health Care

DJ Global United States (All) / Health Care -IND

ProShares Ultra Industrials

Dow Jones U.S. Industrials Index

ProShares Ultra Oil & Gas

DJ Global United States (All) / Oil & Gas -IND

ProShares Ultra Real Estate

DJ Global United States (All) / Real Estate -SS

ProShares Ultra Semiconductors

DJ Global United States (All) / Semiconductors -SUB

ProShares Ultra Technology

Dow Jones U.S. Technology Index

ProShares Ultra Utilities

DJ Global United States (All) / Utilities -IND

ProShares UltraShort Basic Materials

DJ Global United States (All) / Basic Materials -IND

ProShares UltraShort Consumer Goods

DJ Global United States (All) / Consumer Goods -IND

ProShares UltraShort Consumer Services

DJ Global United States (All) / Consumer Services -IND

ProShares UltraShort Financials

DJ Global United States (All) / Financials -IND

ProShares UltraShort Health Care

DJ Global United States (All) / Health Care -IND

ProShares UltraShort Industrials

DJ Global United States (All) / Industrials -IND

ProShares UltraShort Oil & Gas

DJ Global United States (All) / Oil & Gas -IND

ProShares UltraShort Real Estate

DJ Global United States (All) / Real Estate -SS

Proshares Ultrashort Semiconductors

DJ Global United States (All) / Semiconductors -SUB

ProShares UltraShort Technology

DJ Global United States (All) / Technology -IND

ProShares UltraShort Utilities

DJ Global United States (All) / Utilities -IND

Real Estate Select Sector SPDR FundS&P Real Estate Select Sector

Roundhill S&P Global Luxury Etf

S&P Global Luxury Net Total Return Index

SAMSUNG KODEX DJI US REITs ETF(H) Units Dow Jones U.S. Real Estate Index
Samsung KODEX SYNTH-US Biotech ETF

S&P Biotechnology Select Industry

Samsung KODEX SYNTH-US Energy ETF

Energy Select Sector

Samsung KODEX SYNTH-US Industrial ETF

S&P Industrial Select Sector

SAMSUNG KODEX WTI Crude Oil Futures
Inverse ETF(H)S&P GSCI Crude Oil

Schwab U.S. REIT ETF

Dow Jones Equity All REIT Capped

Shin Kong S&P Electric Vehicles ETF

S&P Kensho Capped Electric Vehicles Index (USD) TR

Smartshares Australian Financials ETF

S&P/ASX 200 Financials Ex-A-REIT - AUD

Smartshares Australian Property ETF

S&P/ASX 200 A-REIT Equal Weight Index - AUD

Smartshares NZ Property ETF

S&P/NZX Real Estate Select Index - NZD

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research46
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

SP Funds S&P Global REIT Sharia ETF

S&P Global All Equity REIT Shariah Capped Index

SP Funds S&P Global Technology ETF

S&P Global 1200 Shariah Information Technology (Sector) Capped (USD)

SPDR Dow Jones Global Real Estate ETF

DJ Global Select Real Estate Securities Index (RESI)SPDR Dow Jones Global Real Estate ETF
Exchange Traded Fund Units
SPDR Dow Jones Global Real Estate UCITSETFSPDR Dow Jones Global Real Estate UCITSETF Accum Unhedged USD

DJ Global Select Real Estate Securities Index (RESI)DJ Global Select Real Estate Securities Index (RESI)DJ Global Select Real Estate Securities Index (RESI)SPDR Dow Jones International Real Estate ETF DJ Global x US Select Real Estate Securities Index (RESI)SPDR Dow Jones REIT ETF

Dow Jones US Select REIT

SPDR S&P Aerospace & Defense ETF

S&P Aerospace & Defense Select Industry

SPDR S&P ASX 200 Financials EX A-REIT Fund S&P/ASX 200 Financials Ex-A-REIT - AUD
SPDR S&P Bank ETF

S&P Banks Select Industry

SPDR S&P BIOTECH ETF

S&P Biotechnology Select Industry

SPDR S&P Capital Markets ETF

S&P Capital Markets Select Industry

SPDR S&P Health Care Equipment ETF

S&P Healthcare Equipment Select Industry

SPDR S&P Health Care Services ETF

S&P Health Care Services Select Industry

SPDR S&P Insurance ETF

S&P Insurance Select Industry

SPDR S&P Metals & Mining ETF

S&P Metals and Mining Select Industry

SPDR S&P Oil & Gas Equip. & Services ETF

S&P Oil & Gas Equipment Select Industry Index

SPDR S&P Oil & Gas Exp. & Prod. ETF

S&P Oil & Gas Exploration & Production Select Industry

SPDR S&P Pharmaceuticals ETF

S&P Pharmaceuticals Select Industry

SPDR S&P Regional Banking ETF

S&P Regional Banks Select Industry

SPDR S&P Semiconductor ETF

S&P Semiconductors Select Industry

SPDR S&P Software & Services ETF

S&P Software & Services Select Industry

SPDR S&P Transportation ETF

S&P Transportation Select Industry

SPDR S&P US Communication Services SelectSector UCITS ETF
SPDR S&P US Consumer Discretionary SelectSector UCITS ETF
SPDR S&P US Consumer Staples Select Sector
UCITS ETF

S&P Communication Services Select Sector Daily Capped 25/20 Index
S&P Consumer Discretionary Select Sector Index
S&P Consumer Staples Select Sector Daily Capped 25/20 Index Benchmark TR Net

SPDR S&P US Energy Select Sector UCITS ETF S&P Energy Select Sector Daily Capped 25/20 Index
SPDR S&P US Financials Select Sector UCITS
ETF

S&P Financials Select Sector Daily Capped 25/20 Index

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research

47
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Exhibit 37: Sector, Industry and Thematics-Listed ETFs Included in Exhibit 2 (cont.)
ETF

Index

SPDR S&P US Health Care Select Sector UCITS
S&P Health Care Select Sector Daily Capped 25/20 Index
ETF
SPDR S&P US Industrials Select Sector UCITS
S&P 500 Index - EUR
ETF
SPDR S&P US Materials Select Sector UCITS
S&P Materials Select Sector Daily Capped 25/20 Index
ETF
SPDR S&P US Technology Select Sector UCITS
S&P TECHNOLOGY SELECT SECTOR DAILY CAPPED 25/20 NTR
ETF
SPDR S&P US Utilities Select Sector UCITS ETF S&P Utilities Select Sector Daily Capped 25/20 Index - USD
SPDR S&P/ASX 200 Listed Property Fund

S&P/ASX 200 A-REIT Index - AUD

Technology Select Sector SPDR Fund

Technology Select Sector

Utilities Select Sector SPDR Fund

Utilities Select Sector

Vanguard Australian Property Securities Index
ETF

S&P ASX 300 / A-REIT -SEC

Vanguard Global ex-U.S. Real Estate ETF

S&P Global x United States Property

WOORI US SP AerospaceDefense ETF Units

S&P Aerospace & Defense Select Industry

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Exhibit 38: Index Futures
Name

Exchange

S&P E-mini Financial Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Energy Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Utilities Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Consumer Staples Select Sector Futures

Chicago Mercantile Exchange

E-mini S&P Real Estate Select Sector Stock Index Futures

Chicago Mercantile Exchange

S&P E-mini Health Care Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Materials Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Technology Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Industrial Select Sector Futures

Chicago Mercantile Exchange

E-mini Communication Services Select Sector Futures

Chicago Mercantile Exchange

S&P E-mini Consumer Discretionary Select Sector Future

Chicago Mercantile Exchange

E-mini S&P Regional Banks Select Industry Futures

Chicago Mercantile Exchange

E-mini S&P Biotechnology Select Industry Futures

Chicago Mercantile Exchange

E-mini S&P Oil & Gas Exploration & Production Select Industry Futures

Chicago Mercantile Exchange

E-mini S&P Insurance Select Industry Futures

Chicago Mercantile Exchange

E-mini S&P Retail Select Industry Futures

Chicago Mercantile Exchange

Source: S&P Dow Jones Indices LLC. Data as of March 28, 2024. Table is provided for illustrative purposes.

Research48
For use with institutions only, not for use with retail investors.

Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

Performance Disclosure/Back-Tested Data
The S&P 500 Equal Weight Sector Indices were launched June 20, 2006. The S&P Biotechnology Select Industry Index, S&P Home Builders
Select Industry Index, S&P Semiconductors Select Industry Index were launched on January 27, 2006. The S&P Aerospace & Defense SelectIndustry Index, S&P Technology Hardware Select Industry Index, S&P Health Care Equipment Select Industry Index, S&P Health Care
Services Select Industry Index, S&P Metals & Mining Select Industry Index, S&P Oil & Gas Exploration & Production Select Industry Index,
S&P Oil & Gas Equipment Select Industry Index, S&P Pharmaceuticals Select Industry Index, S&P Retail Select Industry Index, S&P Telecom
Select Industry Index, and S&P Transportation Select Industry Index were launched on June 19, 2006. The S&P Banks Select Industry Index,
S&P Capital Markets Select Industry Index, S&P Insurance Select Industry Index, and S&P Regional Banks Select Industry Index werelaunched on September 9, 2011. The S&P Software & Services Select Industry Index was launched on September 19, 2011. The S&P
Internet Select Industry Index was launched on February 1, 2016. All information presented prior to an index’s Launch Date is hypothetical(back-tested), not actual performance. The back-test calculations are based on the same methodology that was in effect on the index Launch
Date. However, when creating back-tested history for periods of market anomalies or other periods that do not reflect the general current
market environment, index methodology rules may be relaxed to capture a large enough universe of securities to simulate the target market
the index is designed to measure or strategy the index is designed to capture. For example, market capitalization and liquidity thresholds may
be reduced. Complete index methodology details are available at www.spglobal.com/spdji. Past performance of the Index is not an indicationof future results. Back-tested performance reflects application of an index methodology and selection of index constituents with the benefit ofhindsight and knowledge of factors that may have positively affected its performance, cannot account for all financial risk that may affectresults and may be considered to reflect survivor/look ahead bias. Actual returns may differ significantly from, and be lower than, back-tested
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accrued interest (or US $1,650), the net return would be 8.35% (or US $8,350) for the year. Over a three-year period, an annual 1.5% fee
taken at year end with an assumed 10% return per year would result in a cumulative gross return of 33.10%, a total fee of US $5,375, and acumulative net return of 27.2% (or US $27,200).

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Natural Selection: Tactics and Strategy with Equity Sectors

July 2024

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