S&P Low Volatility Indices · 2015/10/13 · 2 01 Introduction 02 Construction 03 Characteristics...

For Financial Professionals. Not for Public Distribution. PROPRIETARY. Permission to reprint or distribute any content from this presentation requires the written approval of S&P Dow Jones Indices.

S&P Low Volatility Indices EMERGING AND DEVELOPED MARKETS

October 2015


2

01 Introduction

02 Construction

03 Characteristics

04 Stylized Use Cases

Agenda


WHY LOW-VOLATILITY?

3

Extensive empirical evidence suggests that, contrary to financial theories, high-risk stocks have underperformed low-risk stocks on a risk-adjusted basis, across equity markets

The low-volatility anomaly may be the result of behavioural biases that lead investors to overpay for high-risk stocks

Source: Baker et al. 2011. “Benchmarks as Limits to Arbitrage”. Financial Analysts Journal. S&P Dow Jones Indices, Data from December 31, 1999 to December 31, 2012. Returns prior to March 19, 2012 are backtested Graphs and tables provided for illustrative purposes only. Past performance is not a guarantee of future results. This graph reflects historical performance. Please see Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back tested performance

Highest Beta

1.6%

Quintile 4

3.4%

Quintile 3

4.7%

Quintile 2

4.7%

Lowest Beta

5.7%

Sharpe Ratio Excess Return

Performance of Beta Sorted Quintile Portfolios (US Equities, 1968-2008)

0

1

2

3

4

5

6

0.0

0.1

0.2

0.3

0.4

0.5


S&P LOW VOLATILITY INDICES

4

Overview • Low-volatility indices are designed to target the low-volatility anomaly: stocks with lower volatility have tended to

outperform those with higher volatility on a risk-adjusted basis over medium- to long-term periods. • The S&P Low Volatility methodology is simple and non-optimized. A subset of the universe is chosen based on their

realized volatilities over a trailing time span and those stocks are weighted by the inverse of their volatilities, yielding a low-volatility portfolio.

• The low volatility anomaly is observed in almost all major markets and regions in the world. S&P Dow Jones has indices that track this effect in those markets (next slide)

• As of July 31, 2014, S&P Low Volatility indices had $5.3 billion in ETF assets tracking them

Source: S&P Dow Jones Indices. Data as of September 30, 2015. Charts are provided for illustrative purposes. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance. Past Performance is no guarantee of future results.

-1

0

1

2

3

4

5

6

7

8

S&P/TSX Composite Low Volatility

7.2%

S&P 500 Low Volatility

-0.4%

S&P BMI Emerging Markets Low Volatility

5.7%

S&P BMI International Low Volatility

2.6%

Annualized 5-Year Return Enhancement

0

10

20

30

40 38.2%

S&P 500 Low Volatility

28.8%


23.9%

S&P BMI International Low Volatility

28.2%

S&P/TSX Composite Low Volatility

Annualized 5-Year Risk Reduction


S&P LOW VOLATILITY INDICES

5

Low Volatility Index No. of Constituents Underlying Index Eligible Universe

Additional Liquidity Criteria

S&P 500 Low Volatility 100 S&P 500 None S&P BMI International Developed Low Volatility 200 S&P Developed Ex. US & South Korea

LargeMidCap USD 3 million

S&P BMI Emerging Markets Low Volatility 200 S&P Emerging Plus LargeMidCap USD 3 million

S&P EPAC Ex. Korea Low Volatility 200 S&P EPAC BMI Ex. Korea USD 3 million

S&P/TSX Composite Low Volatility 50 S&P/TSX Composite None

S&P Europe 350 Low Volatility 100 S&P Europe 350 None

S&P Nordic Low Volatility 30 S&P Nordic BMI USD 1.5 million

S&P Eurozone Low Volatility 80 S&P Eurozone BMI EUR 3 million

S&P Southern Europe Low Volatility 25 S&P Italy BMI, S&P Portugal BMI & S&P Spain BMI EUR 5 million

S&P Pan Asia Low Volatility 50 S&P Pan Asia Ex-New Zealand LargeMidCap USD 5 million

S&P Korea Low Volatility 50 S&P Korea BMI KRW 1 billion

S&P South Africa Low Volatility 40 S&P South Africa Composite ZAR 10 million

S&P MidCap 400 Low Volatility 80 S&P MidCap 400 None

S&P SmallCap 600 Low Volatility 120 S&P SmallCap 600 None

S&P Japan 500 Low Volatility 100 S&P Japan 500 JPY 300 million

Source: S&P Dow Jones Indices. Data as of September 30, 2015


6

01 Introduction

02 Construction

03 Characteristics


Agenda


FOCUS ON METHODOLOGY - HOW IS THE S&P BMI EMERGING MARKETS LOW VOLATILITY INDEX CREATED?

Additional Criteria for EM Low Volatility • Liquidity threshold for companies is $3

million • Only ADRs and GDRs are considered for

Indian and Russian companies • Mainland Chinese stocks are excluded

but Hong Kong listed shares are eligible • Only one most liquid share class is

considered eligible

The Index is rebalanced quarterly1

Step 1

•Measure the volatility of all stocks in the S&P Emerging Plus LargeMidCap Index (a Global BMI sub-index) which pass the liquidity and listing criteria (side panel)

•Volatility is defined as the standard deviation of price changes over the trailing 12 months (252 trading days) for each stock

Step 2

• Rank the stocks from lowest to highest by volatility

Step 3

• The 200 least volatile stocks from Step 2

are included in the Index • Stocks are weighted by the inverse of

their volatility thus assigning higher weights to lower volatile stocks

1In March, June, September, and December based on market data as of the last business day of February, May, August, and November respectively

Other low volatility indices are similarly constructed using the universe, liquidity criteria, and the number of stocks specified in the last slide


8

01 Introduction

02 Construction

03 Characteristics


Agenda


CHARACTERISTICS – WEALTH CURVES (15 YEARS)

9

Source: S&P Dow Jones Indices and/or its affiliates. Data as of September 30, 2015. Charts are provided for illustrative purposes. Past Performance is no guarantee of future results. These charts and graphs may reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

S&P BMI Emerging Markets Low Volatility S&P 500 Low Volatility

S&P BMI International Developed Low Volatility S&P EPAC Ex Korea Low Volatility


CHARACTERISTICS – WEALTH CURVES (15 YEARS)

10


S&P Eurozone Low Volatility (EUR) S&P Japan 500 Low Volatility (JPY)


CHARACTERISTICS: ANNUAL PERFORMANCE: S&P BMI EMERGING MARKETS LOW VOLATILITY

11

Annual Performance

2015 YTD

-15.4%

2014

-0.9% -3.7%

2013

-0.8%

0.3%

2012

18.1% 21.2%

2011

-18.1%

-5.4%

2010

20.2%

39.2%

2009

77.5%

46.4%

2008

-52.2%

-33.8%

2007

38.9% 33.6%

2006

33.4% 34.1%

2005

35.4%

21.3%

2004

23.7%

32.8%

2003

51.7% 48.7%

2002

-8.2%

2.4%

2001

1.3%

-2.2%

2000

-31.5%

-11.8% -15.1%

S&P Emerging Plus LargeMidCap




CHARACTERISTICS: ANNUAL PERFORMANCE: S&P BMI INTERNATIONAL DEVELOPED LOW VOLATILITY

12

Annual Performance

2015 YTD

-6.2% -6.8%

2014

-3.6%

2.3%

2013

21.4%

17.2%

2012

17.0% 14.7%

2011

-11.8%

-3.3%

2010

9.4%

14.1%

2009

35.0%

20.6%

2008

-43.0%

-29.8%

2007

13.8% 16.2%

2006

25.1%

33.5%

2005

15.4% 11.9%

2004

20.4%

32.7%

2003

39.5% 41.3%

2002

-15.8%

5.6%

2001

-21.5%

-7.9%

2000

-12.4%

10.6%

S&P Developed Ex US Ex Korea LargeMidCap

S&P BMI International Developed Low Volatility



LOW VOLATILITY STRATEGIES – 5 YEAR RISK RETURN PROFILE

13


0

6

12

18

24

-5 0 5 10

Annualized Risk

Annualized Return

BMI International Developed (Ex - US, SK) Low Volatility

BMI Developed (Ex - US, SK)

BMI Emerging Market Low Volatility

BMI Emerging Plus


CHARACTERISTICS – HIGHER SHARPE RATIOS AND BETTER DRAWDOWNS ACROSS TIME PERIODS AND REGIONS

14


Low Vol Benchmark Low Vol Benchmark Low Vol Benchmark Low Vol Benchmark

International 0.66 0.12 0.41 0.13 0.46 0.26 0.34 0.44Emerging Plus 0.65 0.27 0.47 0.17 0.03 (0.16) (0.42) (0.32)S&P 500 0.72 0.17 0.69 0.38 1.51 1.16 1.21 1.27S&P/TSX Composite (CAD) 1.00 0.19 0.68 0.27 1.96 0.46 1.62 0.69S&P Japan 500 (JPY) 0.33 0.00 0.40 0.05 1.15 0.76 1.87 1.60Eurozone (EUR) 0.52 0.50 0.17 1.24 0.56 1.58 1.11EPAC Ex Korea 0.65 0.11 0.36 0.13 0.44 0.29 0.45 0.52

Major Regions and Countries

Sharpe Ratios of the S&P Low Volatility Indices and the S&P BMI and Other Headline Indices by Region

Region Past 15 Years Past 10 Years Past 5 Years Past 3 Years

Low Vol Benchmark Low Vol Benchmark Low Vol Benchmark Low Vol Benchmark

International (42.20) (55.97) (42.20) (55.97) (12.28) (22.41) (12.28) (14.67)Emerging Plus (42.43) (60.26) (42.43) (60.26) (24.98) (25.34) (24.98) (24.46)S&P 500 (35.36) (50.95) (35.36) (50.95) (5.50) (16.26) (5.29) (8.36)S&P/TSX Composite (CAD) (39.48) (43.35) (39.48) (43.35) (5.12) (16.55) (5.12) (12.03)S&P Japan 500 (JPY) (37.12) (57.06) (37.12) (57.06) (11.10) (22.86) (10.60) (15.75)Eurozone (EUR) (46.55) (46.55) (56.48) (14.99) (24.74) (6.27) (12.22)EPAC Ex Korea (42.40) (56.04) (42.40) (56.04) (13.68) (22.37) (10.78) (13.36)

Major Regions and Countries

Maximum Drawdowns of the S&P Low Volatility Indices and the S&P BMI and Other Headline Indices by Region

Region Past 15 Years Past 10 Years Past 5 Years Past 3 Years


CHARACTERISTICS: S&P BMI EMERGING MARKETS LOW VOLATILITY

15


Low Vol LargeMidCap Low Vol LargeMidCap Low Vol LargeMidCap Low Vol LargeMidCapAnnual Return (%) 11.67 7.71 8.96 5.02 0.51 (2.70) (5.02) (4.29)Maximum Drawdown (%) (42.4) (60.3) (42.4) (60.3) (25.0) (25.3) (25.0) (24.5)Annual Volatility (%) 15.79 22.90 16.63 23.35 14.19 17.61 11.92 13.62Annual Skewness (0.26) (0.14) (0.26) (0.14) (0.13) (0.04) (0.13) (0.08)Monthly Alpha against the S&P Emerging Plus LargeMidCap (%)

0.49 0.41 0.20 (0.13)

T-Stats Of Alpha 3.90 2.70 1.19 (0.72)Beta to the S&P Emerging Plus LargeMidCap 0.64 0.67 0.76 0.83

Correlation with the S&P Emerging Plus LargeMidCap 0.93 0.94 0.95 0.95

Sharpe Ratio 0.65 0.27 0.47 0.17 0.03 (0.16) (0.42) (0.32)Sortino Ratio 0.94 0.40 0.67 0.24 0.05 (0.21) (0.53) (0.41)MAR Ratio 0.27 0.13 0.21 0.08 0.02 0.00 0.00 0.00Omega Ratio 1.78 1.39 1.56 1.29 1.08 0.95 0.76 0.83

Statistical Summary of the S&P BMI Emerging Market Low Vol and the S&P Emerging Plus LargeMidCap

Summary stats Past 15 Years Past 10 Years Past 5 Years Past 3 Years


CHARACTERISTICS – HIGHER SHARPE RATIOS AND BETTER DRAWDOWNS ACROSS TIME PERIODS AND REGIONS

16


Low Vol LargeMidCap Low Vol LargeMidCap Low Vol LargeMidCap Low Vol LargeMidCapAnnual Return (%) 9.85 3.51 6.66 3.51 5.44 3.95 3.79 5.17Maximum Drawdown (%) (42.2) (56.0) (42.2) (56.0) (12.3) (22.4) (12.3) (14.7)Annual Volatility (%) 12.69 17.35 13.42 18.33 11.64 14.90 11.15 11.64Annual Skewness (0.25) (0.18) (0.23) (0.20) (0.16) (0.11) (0.13) (0.02)Monthly Alpha against the S&P Developed Ex US SK LargeMidCap (%)

0.58 0.32 0.21 (0.03)

T-Stats Of Alpha 4.91 2.46 1.07 (0.11)Beta to the S&P Developed Ex US SK LargeMidCap 0.66 0.68 0.70 0.83

Correlation with the S&P Developed Ex US SK LargeMidCap

0.90 0.93 0.90 0.86

Sharpe Ratio 0.66 0.12 0.41 0.13 0.46 0.26 0.34 0.44Sortino Ratio 0.95 0.16 0.58 0.18 0.68 0.39 0.49 0.71MAR Ratio 0.23 0.06 0.16 0.06 0.44 0.18 0.31 0.35Omega Ratio 1.83 1.24 1.51 1.24 1.45 1.28 1.32 1.43

Statistical Summary of the S&P BMI International Developed Low Vol and the S&P Developed Ex US SK LargeMidCap

Summary stats Past 15 Years Past 10 Years Past 5 Years Past 3 Years


DYNAMICS – SECTOR HISTORY FOR S&P BMI EMERGING MARKETS LOW VOLATILITY

17

Source: S&P Dow Jones Indices and/or its affiliates. Charts are provided for illustrative purposes. Past Performance is no guarantee of future results. These charts and graphs may reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

Materials

Industrials

Consumer Staples

Financials

Jun

10

Dec

09

Jun

09

Dec

08

Jun

08

Dec

07

Jun

07

Dec

06

Jun

06

Dec

05

Jun

05

Dec

04

Information Technology

Dec

03

Jun

03

Dec

02

Jun

02

Dec

01

Jun

01

Jun

14

Dec

13

Dec

14

Jun

13

Dec

12

Jun

12

Dec

11

Dec

10

Jun

11

Health Care

Utilities

Energy

Consumer Discretionary

Telecommunication Services

Jun

04

Jun

00

Dec

00

Sector allocation has been dynamic throughout history and driven only by volatility signals Similar to the S&P 500 Low Volatility index, this index also moves out of Financials as the 2008 crisis is approaching and gets back in

when it subsides.

0

20

40

60

80

100


DYNAMICS – REGIONAL ALLOCATION FOR S&P BMI EMERGING MARKETS LOW VOLATILITY

18


For Emerging Markets, the country allocation is more dynamic - driven by volatility signals. The regions represented above include the following countries - Latin America (Chile, Brazil, Peru, Venezuela, Argentina, Colombia, and Mexico), East Asia (China, Korea, and Taiwan), South and South East Asia (India, Pakistan, Thailand, Philippines, and Indonesia), Africa (Morocco, Nigeria, and South Africa), Europe and Middle East (Poland, Czech Republic, Russia, Israel, Slovenia, Turkey, Hungary, Jordan, and Egypt). Some countries have changed classification from Emerging to Developed or Frontier over the time period.

Dec

00

Jun

01

Dec

01

Dec

02

South & South East Asia

Latin America

Europe and Middle East

East Asia

Africa

Jun

14

Jun

12

Jun

10

Jun

08

Jun

06

Jun

04

Jun

02

Jun

03

Dec

03

Dec

04

Jun

05

Dec

05

Dec

06

Jun

07

Dec

07

Dec

08

Jun

09

Dec

09

Dec

10

Jun

11

Dec

11

Dec

12

Jun

13

Dec

13

Dec

14

Jun

00

Recent expansion of East Asia exposure (taking away from South and South East Asia) is mainly the expansion of exposure to Taiwan at the expense of Malaysia

0%

20%

40%

60%

80%

100%


DYNAMICS – SECTOR HISTORY FOR S&P BMI INTERNATIONAL DEVELOPED LOW VOLATILITY

19


Dec

12

Jun

13

Dec

13

Jun

07

Dec

06

Jun

06

Dec

05

Jun

05

Dec

04

Jun

04

Dec

03

Jun

03

Dec

02

Jun

02

Dec

01

Jun

01


Materials

Energy

Health Care



Utilities

Industrials

Consumer Staples

Financials

Jun

12

Dec

11

Jun

11

Dec

10

Jun

10

Dec

09

Jun

09

Dec

08

Jun

08

Dec

07

Dec

00

Jun

14

Dec

14

Sector allocation has been dynamic throughout history and driven only by volatility signals Similar to the S&P 500 Low Volatility index, this index also moves out of Financials as the 2008 crisis is approaching and gets back in

when it subsides.

0

20

40

60

80

100


DYNAMICS – REGIONAL ALLOCATION FOR S&P BMI INTERNATIONAL DEVELOPED LOW VOLATILITY

20


For Developed Markets (similar to EM), the country allocation is more dynamic - driven by volatility signals. The regions represented above include the following countries - Eurozone (Germany, Netherlands, Belgium, France, Slovenia, Luxembourg, Greece, Portugal, Spain, Finland, Italy, and Ireland), Other Europe (Switzerland, Denmark, Austria, Sweden, Czech Republic, Norway, Israel, Hungary, Iceland), Asia Ex. Japan (Singapore, Hong Kong)

Jun

04

Jun

05

Dec

05

Jun

06

Jun

07

Dec

07

Jun

08

Jun

09

Dec

09

Jun

10

Jun

11

Dec

11

Jun

12

Jun

02

Dec

01

Dec

03

Jun

03

Australia/NZ

Japan

Asia Ex-Japan

Other Europe

Eurozone

UK

Canada

Dec

14

Dec

12

Dec

10

Dec

08

Dec

06

Dec

04

Dec

02

Dec

00

Jun

01

Jun

13

Dec

13

Jun

14

Note the spike of Japan exposure – post Tepco incident and prior to the rally in 2014

0%

20%

40%

60%

80%

100%


DYNAMICS – SECTOR HISTORY FOR S&P EPAC EX KOREA LOW VOLATILITY

21


Energy


Materials


Health Care

Utilities


Consumer Staples

Industrials

Financials

Dec

11

Sep

11

Jun

11

Mar

11

Dec

10

Sep

10

Jun

10

Mar

10

Dec

09

Sep

09

Jun

09

Mar

09

Dec

08

Sep

08

Jun

08

Mar

08

Dec

07

Sep

07

Jun

07

Mar

07

Dec

06

Sep

06

Jun

06

Mar

06

Dec

05

Sep

05

Jun

05

Mar

05

Dec

04

Mar

12

Jun

12

Sep

12

Dec

12

Mar

13

Jun

13

Sep

13

Dec

13

Mar

14

Jun

14

Sep

14

Dec

14

Mar

15

Jun

15

Technology 0

20

40

60

80

100


DYNAMICS – REGIONAL ALLOCATION FOR S&P EPAC EX KOREA LOW VOLATILITY

22


Sep

12

Dec

12

Mar

13

Jun

13

Sep

13

Dec

13

Mar

14

Jun

14

Sep

14

Dec

14

Mar

15

Jun

15

Other Europe

Eurozone

Isreal

Hong Kong

Japan

Australia/NZ

United Kingdom

Singapore

Dec

11

Sep

11

Jun

11

Mar

11

Dec

10

Sep

10

Jun

10

Mar

10

Dec

09

Sep

09

Jun

09

Mar

09

Dec

08

Sep

08

Jun

08

Mar

08

Dec

07

Sep

07

Jun

07

Mar

07

Dec

06

Sep

06

Jun

06

Mar

06

Dec

05

Sep

05

Jun

05

Mar

05

Dec

04

Mar

12

Jun

12 0%

20%

40%

60%

80%

100%


DYNAMICS – SECTOR HISTORY FOR S&P JAPAN 500 LOW VOLATILITY

23


Energy


Materials


Health Care

Utilities


Consumer Staples

Industrials

Financials

Dec

11

Sep

11

Jun

11

Mar

11

Dec

10

Sep

10

Jun

10

Mar

10

Dec

09

Sep

09

Jun

09

Mar

09

Dec

08

Sep

08

Jun

08

Mar

08

Dec

07

Sep

07

Jun

07

Mar

07

Dec

06

Sep

06

Jun

06

Mar

06

Dec

05

Sep

05

Jun

05

Mar

05

Dec

04

Mar

12

Jun

12

Sep

12

Dec

12

Mar

13

Jun

13

Sep

13

Dec

13

Mar

14

Jun

14

Sep

14

Dec

14

Mar

15

Jun

15

Technology 0

20

40

60

80

100


CHARACTERISTICS: HIGH TURNOVER BUT SIMILAR TO OTHER ALTERNATIVELY WEIGHTED STRATEGIES

24

2008

97.7%

2007

81.8%

2014

83.9%

2013

85.4%

2012

91.1%

2011

73.0%

2010

69.5%

2009

52.7%

Annual Turnover – S&P BMI Emerging Market Low Volatility

2014

62.7%

78.7%

2013 2012

73.9%

2011

77.4%

2010

63.7%

2009

62.3%

2008

93.4%

2007

83.5%

Annual Turnover – S&P BMI International Developed Low Volatility

Source: S&P Dow Jones Indices. Data as of December 30, 2014


CHARACTERISTICS: HIGH TURNOVER BUT SIMILAR TO OTHER ALTERNATIVELY WEIGHTED STRATEGIES (CONT.)

25

2012

55.7%

2011

73.1%

2010

41.1%

2009

46.4%

2008

71.8%

2007

60.8%

2006

46.7%

2005

93.6%

2013 2014

73.0%

48.0%

Annual Turnover – S&P EPAC Ex Korea Low Volatility

2012

51.5%

2011

48.6%

2010

39.7%

2009

39.8%

2008

57.3%

2007

72.9%

2006

53.9%

2005

73.1%

2014

57.2% 52.8%

2013

Annual Turnover – S&P Japan 500 Low Volatility

Source: S&P Dow Jones Indices. Data as of December 30, 2014


CHARACTERISTICS: DIVIDEND YIELD OF LOW VOLATILITY STRATEGIES ARE TYPICALLY HIGHER THAN THE BENCHMARK

26

International Developed (Global Developed Ex-US & Korea) Emerging Markets Plus

3.41%

2.56%

3.03%

3.89% Benchmark Low Volatility Index


Annual Trailing Yield as of September 30, 2015– Low Volatility Strategy Vs. Corresponding Benchmark

Companies exhibiting low volatility characteristics tend to be stable companies which payout higher dividend yield Observation is consistent across markets and cap-sizes (US) and over time (above is just a snapshot) Low Volatility Index in Emerging Market represented by S&P BMI Emerging Markets Low Volatility and in Global Developed Ex. US represented by S&P BMI International Developed Low Volatility Index. The Benchmark for Emerging is S&P Emerging Plus LargeMidCap Index and for Global Developed Ex. US is S&P Developed Ex. US & Korea LargeMidCap Index


CHARACTERISTICS: DIVIDEND YIELD OF LOW VOLATILITY STRATEGIES ARE TYPICALLY HIGHER THAN THE BENCHMARK (CONT.)

27

S&P Japan 500 EPAC Ex Korea

3.72%

3.13%

2.02% 1.89%

Benchmark Low Volatility Index


Annual Trailing Yield as of September 30, 2015– Low Volatility Strategy Vs. Corresponding Benchmark


CURRENCY HEDGING – OVERVIEW

28

Source: S&P Dow Jones Indices and/or its affiliates, Bloomberg. Data from September 31, 2005 to September 30, 2015. Charts are provided for illustrative purposes. Past Performance is no guarantee of future results. These charts and graphs may reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

S&P Eurozone Low Volatility S&P EPAC Ex Korea Low Volatility

S&P Japan 500 Low Volatility JPYUSD and EURUSD Spot Rates


CURRENCY HEDGING – RISK/RETURN PROFILE

29

Source: S&P Dow Jones Indices and/or its affiliates. Data from September 31, 2005 to September 30, 2015. Charts are provided for illustrative purposes. Past Performance is no guarantee of future results. These charts and graphs may reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

Risk-Return Profile

USD Hedged

Local Currency USD USD

Hedged EUR USD USD Hedged JPY USD

Annual Return (%)Past 1 Year 4.91 5.66 (5.21) 15.63 16.44 2.89 14.88 15.45 5.24Past 3 Years 14.35 14.87 5.23 16.06 16.10 10.74 24.86 25.43 8.44Past 5 Years 10.49 10.89 5.47 13.19 13.09 8.63 15.37 15.77 7.65Past 10 Years 6.88 6.68 6.12 7.80 7.32 6.49 7.39 6.38 5.77Annual Volatility (%)Past 3 Years 9.99 10.17 11.57 9.99 10.16 11.30 13.29 13.57 12.97Past 5 Years 9.26 9.43 12.43 10.43 10.48 15.18 13.45 13.64 12.72Past 10 Years 10.56 10.69 13.82 12.22 12.25 17.36 13.11 13.14 12.61Annual Return / Annual Volatility (x)Past 3 Years 1.44 1.46 0.45 1.61 1.59 0.95 1.87 1.87 0.65Past 5 Years 1.13 1.16 0.44 1.26 1.25 0.57 1.14 1.16 0.60Past 10 Years 0.65 0.63 0.44 0.64 0.60 0.37 0.56 0.49 0.46

S&P Eurozone Low VolS&P EPAC Ex Korea Low Vol S&P Japan 500 Low Vol


30

01 Introduction

02 Construction

03 Characteristics

04 Stylized Use Case

Agenda


RISK ADJUSTED RETURNS WITH VARIOUS COMBINATIONS OF LOW VOLATILITY AND THE CORRESPONDING BENCHMARK

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Source: S&P Dow Jones Indices and/or its affiliates. Data from September 31, 2005 to September 30, 2015. Charts are provided for illustrative purposes. Past Performance is no guarantee of future results. These charts and graphs may reflect hypothetical historical performance. Please see the Performance Disclosure at the end of this document for more information regarding the inherent limitations associated with back-tested performance.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

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

Ris

k A

djus

ted

Ret

urn

Allocation to Benchmark in Stylized Mix of Benchmark and Low Volatility Index

Developed Markets (Ex. US)

Emerging Markets

EPAC Ex Korea

Eurozone (EUR)

S&P Japan 500 (JPY)


KEY TAKEAWAYS

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Low Volatility anomaly has behavioural roots and is observed in most markets in the world (US, Europe, Canada, Emerging, Global, Developed, etc.)

Two main approaches to lowering volatility – simpler inverse volatility weighted method is efficient and adopted by S&P DJI and underlies the S&P BMI Emerging Markets Low Volatility Index and the S&P BMI International Developed Low Volatility Index

Risk Reduction is the key!

Historical out-performance in bear markets and under-performance in bull-markets and the higher magnitude of former has led to outperformance in the longer run. Downside protection, measured by drawdowns has been better compared to benchmark

Higher yields compared to benchmark historically

Investors, depending on their desired investment objective, can combine their core exposure to a market with the corresponding low volatility index, to either increase equity exposure, if they have fixed risk budget, or reduce the risk of the overall allocation.


RESOURCES

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White paper (Low Volatility) •http://www.spindices.com/documents/research/low-volatility-effect-comprehensive-look-201208.pdf

Practice Essential (Emerging Markets Low Volatility) •http://www.spindices.com/documents/education/practice-essentials-emerging-market-low-volatility.pdf

Factsheets (updated monthly), methodology and other resources: •http://www.spindices.com/indices/strategy/sp-bmi-emerging-markets-low-volatility-index

•http://www.spindices.com/indices/strategy/sp-500-low-volatility-index •http://www.spindices.com/indices/strategy/sp-bmi-international-developed-low-volatility-index

•http://us.spindices.com/indices/strategy/sp-japan-500-low-volatility-jpy-index

http://www.spindices.com/documents/education/practice-essentials-emerging-market-low-volatility.pdf

http://www.spindices.com/documents/education/practice-essentials-emerging-market-low-volatility.pdf

http://www.spindices.com/indices/strategy/sp-bmi-emerging-markets-low-volatility-index

http://www.spindices.com/indices/strategy/sp-bmi-emerging-markets-low-volatility-index

http://www.spindices.com/indices/strategy/sp-500-low-volatility-index

http://www.spindices.com/indices/strategy/sp-bmi-international-developed-low-volatility-index

http://www.spindices.com/indices/strategy/sp-bmi-international-developed-low-volatility-index

http://us.spindices.com/indices/strategy/sp-japan-500-low-volatility-jpy-index

http://us.spindices.com/indices/strategy/sp-japan-500-low-volatility-jpy-index


PERFORMANCE DISCLOSURE The S&P 500 Low Volatility Index was launched on April 4, 2011. The S&P BMI International Developed Low Volatility Index was launched on December 5, 2011. The S&P BMI Emerging Markets Low Volatility Index was launched on December 5, 2011. The S&P/TSX Composite Low Volatility Index was launched on April 10, 2012. The S&P Japan 500 Low Volatility Index was launched on June 8, 2015. All information presented prior to the index inception date is back-tested. The back-test calculations are based on the same methodology that was in effect when the index was officially launched. Complete index methodology details are available at www.spindices.com S&P Dow Jones Indices defines various dates to assist our clients in providing transparency on their products. The First Value Date is the first day for which there is a calculated value (either live or back-tested) for a given index. The Base Date is the date at which the Index is set at a fixed value for calculation purposes. The Launch Date designates the date upon which the values of an index are first considered live; index values provided for any date or time period prior to the index’s Launch Date are considered back-tested. S&P Dow Jones Indices defines the Launch Date as the date by which the values of an index are known to have been released to the public, for example via the company’s public Web site or its datafeed to external parties. For Dow Jones-branded indices introduced prior to May 31, 2013, the Launch Date (which prior to May 31, 2013, was termed “Date of Introduction”) is set at a date upon which no further changes were permitted to be made to the index methodology, but that may have been prior to the Index’s public release date. Past performance of the Index is not an indication of future results. Prospective application of the methodology used to construct the Index may not result in performance commensurate with the back-test returns shown. The back-test period does not necessarily correspond to the entire available history of the Index. Please refer to the methodology paper for the Index, available at www.spdji.com or www.spindices.com for more details about the index, including the manner in which it is rebalanced, the timing of such rebalancing, criteria for additions and deletions, as well as all index calculations. It is not possible to invest directly in an Index. Another limitation of back-tested hypothetical information is that generally the back-tested calculation is prepared with the benefit of hindsight. Back-tested data reflect the application of the index methodology and selection of index constituents in hindsight. No hypothetical record can completely account for the impact of financial risk in actual trading. For example, there are numerous factors related to the equities (or fixed income, or commodities) markets in general which cannot be, and have not been accounted for in the preparation of the index information set forth, all of which can affect actual performance. The Index returns shown do not represent the results of actual trading of investable assets/securities. S&P Dow Jones Indices LLC maintains the Index and calculates the Index levels and performance shown or discussed, but does not manage actual assets. Index returns do not reflect payment of any sales charges or fees an investor may pay to purchase the securities underlying the Index or investment funds that are intended to track the performance of the Index. The imposition of these fees and charges would cause actual and back-tested performance of the securities/fund to be lower than the Index performance shown. As a simple example, if an index returned 10% on a US $100,000 investment for a 12-month period (or US$ 10,000) and an actual asset-based fee of 1.5% was imposed at the end of the period on the investment plus accrued interest (or US$ 1,650), the net return would be 8.35% (or US$ 8,350) for the year. Over 3 years, 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 a cumulative net return of 27.2% (or US$ 27,200).

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