Nomura Quant

Connecting Markets East & West

See Appendix A-1 for analyst certification, important disclosures and the status of non-US analysts.

Any authors named on this report are research

analysts unless otherwise indicated.

Equity Research

Quantitative Equity Strategy

October 2014

Quantitative Strategy

Inigo Fraser Jenkins – NIplc Alla Harmsworth – NIplc Paul Danis – NIplc Mark Diver – NIplc +44 20 7102 4658 +44 20 7102 2219 +44 20 7102 3406 +44 20 7102 2987 [email protected] [email protected] [email protected] [email protected]

Gerard Alix Guerrini – NIplc Rohit Thombre Robertas Stancikas – NIplc +44 20 7102 8153 +91 22 305 32561 +44 20 7102 3127 [email protected] [email protected] [email protected] Quantitative Solutions Industry Specialists

Ethan Brodie – NSI Bhavik Shah – NIplc Sarah McCarthy – NIplc Norman Pfeifer – NIplc +1 212 667 1076 +44 20 7103 9988 +44 20 7103 9988 +44 20 7103 9988 [email protected] [email protected] [email protected] [email protected]

Rupal Agarwal +91 22 6723 5436 [email protected]

Market outlook

Are earnings growing in Europe?

Global quant equity portfolio:

Tactical factor allocation: Buy growth over income as rates rise

Strategic quant trades

Long horizon concentrated strategies

Sector allocation and current trade ideas

Fund-management strategy

Is passive the new active?

Natural weighting

Cross-asset alternative beta/risk premia investing

EM country selection

Website, recommended strategy portfolio

Introduction

1

Market outlook

European EPS and market multiple

Source: Datastream, IBES, Nomura Strategy research 3

European EPS and the market multiple Multiple expansion following earnings troughs

Earnings troughMultiple

peak

Trailing earnings30/06/1976 11.5 30/04/1979 10.30 35 -1.20

31/01/1984 12.9 31/01/1984 12.90 0 0.00

Forward Earnings31/03/1993 14.7 31/01/1994 16.24 10 1.53

30/06/2003 12.6 27/02/2004 13.35 8 0.78

31/07/2009 12.6 30/09/2009 13.34 2 0.78

Median 8 0.78

Peak multiple attained

Multiple change (PE

points)Multiple at

earnings trough

Number of months from

earnings trough to multiple peak

50

100

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250

300

350

5

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11

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19

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23

Jan-88 Jan-91 Jan-94 Jan-97 Jan-00 Jan-03 Jan-06 Jan-09 Jan-12

RatioRatio

Market Multiple (LHS)

European EPS (RHS)

Multiple peakMultiple peak

Multiple peak

Earnings trough

Earnings trough

Earnings trough

Source: Nomura Strategy research, Shiller database 4

European and US Shiller P/E European 10-year inflation-adjusted earnings and current earnings

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Jan-1881 Jan-1905 Jan-1929 Jan-1953 Jan-1977 Jan-2001

Ratio

US Shiller PE

Europe Shiller PE

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100

105

110

115

Jan-80 Jan-85 Jan-90 Jan-95 Jan-00 Jan-05 Jan-10

Index

Current earnings

Consensus 2015

forecast

5

Figure shows the result of a regression of 12-month forward equity returns and 12-month forward returns of equities relative to bonds on start-of-period valuations and monetary policy. In the two left tables, the monetary policy is represented by a dummy variable that takes the value of 1 on the first hike of a cycle and zero otherwise, in the right panel we use the actual level of short-term rates. In the US, we use Fed funds target rate, in the euro area before the introduction of the EUR we use an avg of the French and German short-term rates. Regression is run from 1989 to 2013 for the dummy regressions and 1992 to 2013 for the short rate regressions. Source: Nomura Strategy research

Earnings versus monetary policy: Drivers of eurozone equities

Absolute equity returns Equities Relative to Bonds Absolute equity returns

Coefficients t Stat Coefficients t Stat Coefficients t Stat

Intercept 6.7 1.2 Intercept 7.2 2.9 Intercept 11.8 1.9

Fwd PE -0.1 -0.3 ERP -0.4 -0.9 Fwd PE -0.2 -0.5 12m fwd gth in trail eps 0.2 4.0

12m fwd gth in trail eps 0.2 3.9

12m fwd gth in trail eps 0.2 3.3

Fed Dummy 10.2 1.0 Fed Dummy 9.3 0.9 Fed rates 0.7 0.9

Europe dummy 0.4 0.1 Europe dummy 0.2 0.0 Europe rates -1.3 -2.1

Flow-based sentiment indicators

*Mutual fund net inflows are based on US net purchases of all equity mutual funds as well as net purchases of European, Japanese and Global Emerging markets funds. US and Global Emerging market flows are measured as the 12-week moving average of flows expressed as a percentage of US and GEM market capitalisation, while European and Japanese figures are measured in relation to reported assets under management. Return series is 12-week forward local currency return of Datastream World Index. ** Z-score is measured in standard deviation and is a rolling 2-year average. Japanese data prior to July 2005 is based on retail flows as a % a Japanese market cap. Source: AMG, EPFR, Datastream, FTSE, Nomura Strategy research

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5

Jan-87 Jan-92 Jan-97 Jan-02 Jan-07 Jan-12

Flows as % of Market Cap, 3MMA

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-2

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0

1

2

3

4

Feb-98 Feb-01 Feb-04 Feb-07 Feb-10 Feb-13

Feb 1998 – Aug 2014

Z-score

6

Global mutual fund activity indicator* Global net issuance and 12-month forward returns

Cross-border equity flows*

Strong flows indicative of bullish sentiment

Weak flows indicative of bearish sentiment

*Purchases of international equities by US, European & Japanese investors. Source: Nomura strategy research, US Treasury, ONS, ECB (from Jan 1998), Bank of France, Bank of Japan, Bundesbank, Sveriges Riksbank. The latest data point is estimated from weekly frequency data Source: EPFR, Nomura Strategy research

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-10

10

30

50 0.0

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1.0

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2.0

2.5


12 month forward returns (%)

12 month trailing net issuance (% mcap)

Global Net Issuance (LHS)

Global 12m Fwd Returns (RHS, inverted)

Source: SDC, Dealogic, Bloomberg, Datastream, Nomura Strategy research

Chart shows aggregate holdings of equity and total financial assets of Households and Insurance companies and pension funds domiciled in the US, eurozone, Japan and the UK. The equity aggregate includes holdings of mutual funds, but excludes unquoted equity and other equity where possible. Source: US Federal reserve, ECB, ONS, BOJ, Nomura Strategy research

Cumulative net flows into European equity mutual funds & ETFs Equity holdings and total financial assets

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-12

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13

USD trn USD trn

Total Financial Assets (LHS)

Equity (RHS)

Source: EPFR, Nomura Strategy research 7

-180

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-120

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-80

-60

-40

-20

0

Jun-07 Jun-08 Jun-09 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14

USD bn

Composite sentiment indicator

Our composite sentiment indicator combines five different sentiment signals: Mutual flows, Nasdaq speculative positioning, Investors Intelligence survey, Put-call ratios and Implied to realised volatility. Source: Nomura Strategy research

-2.0

-1.5

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13

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Jan-

14

Jul-1

4

1 Year Z-score

-0.6

Sentiment optimistic Future market weakness

Sentiment pessimistic Future market strength

8

CSI - combines five different sentiment signals: Mutual flows, Nasdaq speculative positioning, Investors Intelligence survey, Put-call ratios and Implied to realised volatility. Source: Nomura Quantitative Strategy research

Historical efficacy of the composite sentiment indicator

9

0

50

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400

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Index

Daily average pairwise correlation between 14 MSCI EM country indices with a 130-day rolling window. Countries considered - Egypt, South Africa, Turkey, Czech Republic, India, Indonesia, Chile, Poland, Hungary, Russia, Peru, Brazil, Thailand, South Korea. Source: Nomura Strategy research

EM country correlation (rolling 6-month window, daily)

10

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Aug-01 Aug-03 Aug-05 Aug-07 Aug-09 Aug-11 Aug-13

Correlation

6 month rolling correlation 3 month correlation

EM flows

Chart shows 12-month moving average of annualised monthly net purchases of GEM funds expressed as a percentage of global emerging market capitalisation. The Region Flows line is the sum of dedicated regional Asia ex Japan, LatAm and emerging EMEA flows on the same basis. Source: EPFR, FTSE, Nomura Strategy research

11

Difference between GEM flows and regional flows

Monthly net purchases of global emerging market funds (GEM)* and 12-month forward GEM returns relative to developed markets, 1996 - Aug 2014

*Purchases of Global Emerging Market Equity Funds as a percentage of market capitalisation, 12 Month Moving Average. Sources: EPFR, FTSE, Datastream, Nomura Strategy research

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

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1.0

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Flows as % of EM Market Cap, 12MMA Ann GEM Flows Region Flows

Correl: -0.71

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60 -1.5

-1.0

-0.5

0.0

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Flows as % of GEM Market Cap, 12MMA Ann

Net Purchases of Global Emerging Markets * (LHS)

Global Emerging Market Return relative to Developed (RHS, Inverted)

12 Source: Nomura Quantitative strategy

Reliability of GEM flow indicator

Fwd Relative Returns (EM-DM) ERP (%) ERP spread

1m 2m 3m 6m 9m 12m EM DM EM-DM

31/10/2000 -1.8% 0.3% 11.9% 9.2% 9.0% 9.3% 4.5 1.8 2.7

31/12/2001 6.6% 9.9% 11.6% 12.5% 14.6% 15.9% 2.8 1.6 1.2

31/03/2003 -0.8% 0.5% 4.6% 13.7% 15.5% 23.9% 9.7 6.1 3.7

30/04/2007 2.4% 6.9% 14.2% 25.3% 19.2% 25.4% 4.7 4.7 0.0

31/10/2008 -0.9% 2.8% 5.5% 23.6% 33.3% 38.1% 14.6 11.4 3.2

30/12/2011 5.7% 6.9% 1.8% -2.6% -2.3% 0.4% 9.7 9.9 -0.2

31/01/2014 -1.6% 1.8% 1.0%

Average 1.4% 4.2% 7.2% 13.6% 14.9% 18.8% 7.7 6.0 1.7

13 The equity risk premium is calculated as the difference between the market cap-weighted earnings yield and the real bond yield for both FTSE World and FTSE AW Emerging Markets. Source: Factset, IBES, Datastream, FTSE, Bloomberg, Nomura Quantitative strategy

Relative equity risk premium and relative forward returns

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Jul-00 Jul-02 Jul-04 Jul-06 Jul-08 Jul-10 Jul-12 Jul-14

% % yoy Forward Excess Returns (RHS) Relative ERP of EM relative to World (LHS)

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Correlation coefficient

Weekly average of absolute pairwise-correlations between returns of different asset classes over a 90-day rolling window. Asset classes considered - FTSE World Index (proxy for developed equities), FTSE EM Index (proxy for EM equities), dollar spot, gold spot, US govt. 10y bond, commodity index, credit spread indices (investment grade and high yield). Source: Nomura Quantitative strategy

14

Multi-asset correlation (90 day) Index volatility - Factor volatility (Global)

Chart shows 75 day rolling realised volatility of the FTSE World index less the average 75-day rolling volatility of Value, Growth, Momentum, Risk and Quality for a global universe. Note that the underlying factor indices are long-short $-neutral. Source: Nomura Quantitative strategy

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%

Are earnings growing in Europe?


European 12m forward EPS and European light commercial vehicle sales

European 12m forward EPS and Frankfurt airport freight volumes

European 12m forward EPS & European hotel occupancy rate European 12m forward EPS and global oil & gas rig count

Micro to macro earnings indicator

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Apr-97 Apr-00 Apr-03 Apr-06 Apr-09 Apr-12

European 12-month fwd EPS (LS)

Frankfurt airport air freight volumes (Advanced 4-months, RS) % y/y % y/y

-14 -12 -10 -8 -6 -4 -2 0 2 4 6 8

-50 -40 -30 -20 -10

0 10 20 30 40


European 12-month fwd EPS (LS) European hotel occupancy rate (Advanced 3-months, RS)

% y/y y/y chg (%)

-50 -40 -30 -20 -10 0 10 20 30 40 50

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0

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Global oil & gas rig count (RS)

% y/y % y/y

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Apr-00 Apr-03 Apr-06 Apr-09 Apr-12


European new light commercial vehicle sales (Advanced 2-months, RS)

% y/y % y/y

* Includes the European hotel occupancy rate, European light commercial vehicle sales, Frankfurt airport freight/mail volumes, global oil & gas rig count and global steel production. Source: Datastream, IBES, Fraport, STR Global, Nomura Strategy research

European 12m forward EPS and global steel production Regression statistics

R2: 79%

Variable (months advanced) Coefficient t-stat

European Hotel Occupancy (3m) 2.27 3.21

Frankfurt cargo volumes (4m) 2.16 3.37

World Steel Production (5m) 1.81 2.42

Global Oil/Gas rig count (0m) 2.98 3.03

Europe light commercial vehicle registrations (2m) 3.32 5.54

Constant 5.64 7.61 In the above table, we regress the y/y% change in European 12m fwd EPS on the Z-scores (expanding window from Jan. 2000) of the y/y% change in European hotel occupancy rate, Frankfurt airport cargo volumes, World Steel Production, Global Oil/Gas Rig count and European light commercial vehicle registrations advanced by 3, 4, 5, 0 and 2 months, respectively.

European 12m forward EPS and micro-macro indicator

17

Micro to macro earnings indicator

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Z score % y/y European 12-month fwd EPS (LS)

Micro-macro indicator*

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Global steel production (advanced 5-months, RS)

% y/y % y/y

Nomura medium-term macro model for European earnings

18

*Includes Spanish/German 10-year government bond yield spread, euro area M1 money supply, US corporate bond yield spread over Treasury, US unemployment initial claims, and global semiconductor sales. R2 = 75% Source: IBES, Datastream, Nomura Strategy research

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Jan-92 Jan-95 Jan-98 Jan-01 Jan-04 Jan-07 Jan-10 Jan-13

% y/y Europe 12m forward EPS level (LS) Medium-term model* (R2 = 75%)

19

European earnings and economic sentiment Gap between economic sentiment indicator and earnings

Source: Nomura Strategy research

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%

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125

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European consensus EPS revision balance* (LS)

EU economic sentiment indicator (RS)

% Index

Source: Nomura Strategy research 20

Change in lending standards and subsequent loan growth Strong European currencies are weighing on earnings

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Q1 2003 Q1 2005 Q1 2007 Q1 2009 Q1 2011 Q1 2013 Q1 2015

% % y-o-y Bank lending to non financial business (LS)

Net change in lending standards to firms last quarter (inverted, advanced 5-quarters, RS)

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y/y % % European 12m fwd EPS revision balance* (LS)

Market cap weighted European currency index* (RS)

European currencies strengthening

European currencies weakening

US ‘pent-up’ capex: key potential positive

Source: Bloomberg, Nomura Strategy research

Rising US capacity utilisation US private fixed investment in equipment and cost average age: non-residential equipment/software

21

6.5

6.7

6.9

7.1

7.3

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1991 1996 2001 2006 2011

US private fixed investment in equipment (LS)

Average age of non-resisdential equipment (advanced 1-yr, RS)

Years % y/y

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Index % Philly Fed survey of capex intentions (LHS)

US economic policy uncertainty (Inverted, RHS)

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Ratio Capital Goods Consumer Cyclicals Technology Utilities Telecoms

Capex/depreciation for European sectors Capex intentions and policy uncertainty

60

65

70

75

80

85

1997

19

98

1999

20

00

2001

20

02

2003

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04

2005

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2009

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2011

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2013

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14

US Capacity Utilisation Mfg- SA

Consensus implies a large gap between US and European margins: we think it might close

22

16%

17%

18%

19%

20%

21%

22%

Jan-

04

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Europe US FY2

FY3

FY1

FY2

FY3

FY1

Source: IBES, Nomura Strategy research

US profit margins at a turning point?

US profit margins typically fall on the back of labour market gains, with a lag

We are now past the point in the cycle when profit margins begin to fall

*Non-financial profits (w/ inventory and CC adjustment) as a share of non financial gross product Source: Datastream, Nomura Strategy research

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Mar-70 Mar-80 Mar-90 Mar-00 Mar-10

US non financial corporate profit margins

US unemployment rate (advanced 2.5-years)

?

% %

Date of profit margin peak

US unemployment

rate

Profit margin

peak level

Months from the peak in the

unemployment rate and the subsequent

peak in profit margins*

Decline in unemployment

rate experienced before profit

margins peaked*

Mar-73 4.9 12.9 20 1.2

Sep-77 6.8 13.4 29 2.2

Jun-84 7.2 11.8 19 3.6

Sep-97 4.9 13.3 64 2.9

Sep-06 4.5 14.5 40 1.8

Average 5.7 13.2 34.4 2.34

Median 4.9 13.3 29 2.2

Current 6.3 14.9 55 (so far) 3.7 (so far)

Factor allocation and global quant equity portfolio

Global factor views

Source: Bloomberg, Nomura Quantitative strategy 25

Long Growth (global) Risk (global) Large caps (Europe)

Neutral

Gearing Value (global) Momentum (global) Quality (global)

Short

Dividend yield

Chart shows the relative performance of Growth over income (both long-short) and 5y5y inflation. Source: Nomura Quantitative Strategy research

European growth vs income and 5y5y inflation

1.9

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Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14

% Ratio Growth/Income (LHS) 5y5y inflation (RHS)

26

Growth has been de-rated...


Valuation of Global Composite Growth Valuation of European Composite Growth

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6


Ratio Global Composite Growth - 12mth Fwd P/E Global Composite Growth - Price/Book

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Ratio

Europe Composite Growth - 12mth Fwd P/E

Europe Composite Growth - Price/Book

27

28

Earnings revisions for Global Composite Growth Style Long-term expected earnings growth for Global Composite Growth Style

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%


…and expectations for growth companies have been significantly cut

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Net earnings revisions %, (up -down) / total, 3MMA

US rates and factor performance

Shows one-yr fwd returns after the first hike in each cycle for our post-88 internal styles and the longer-term Ken French styles. Avg and Median refer to the average and median of the one-yr fwd returns after the first hike while the all period average refers to the average monthly returns of the respective series over the whole sample period regardless of monetary policy. Source: Nomura Quantitative Strategy research 29

Rate cycles and factor performance Growth relative to income and Fed funds rate

Income Growth Momentum Value Gearing Quality Risk

31/03/1972 22.3% 34.6%30/04/1976 9.1% 3.1%31/08/1977 -24.8% 15.2%31/10/1980 6.5% 10.4%30/03/1984 4.6% 22.5%31/12/1986 -1.8% 17.6%31/03/1988 -2.9% 20.6%28/02/1994 4.5% 9.6% -6.2% -0.2% -7.6% 8.6% 3.0%30/06/1999 -43.4% 48.5% 53.5% -46.0% -39.7% -7.5% 25.0%30/06/2004 4.5% -4.5% 4.4% 17.8% 8.9% -6.6% 0.2%

Avg -2.1% 17.9% 17.6% -9.5% -12.8% -1.8% 9.4%Median 4.5% 9.6% 16.4% -0.2% -7.6% -6.6% 3.0%All period average -2.6% 1.9% -0.9% 2.6% -1.0% 1.2% 4.9%

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Dec-72 Dec-78 Dec-84 Dec-90 Dec-96 Dec-02 Dec-08

% % US Federal Funds Target Rate (LHS)

Growth-Income 2 yr (RHS)

Shows two-year returns from growth-income and changes in the Fed rate. Source: Nomura Quantitative Strategy research

US rates and factor performance

Chart shows the relative performance of low-high yield stocks (ie, the INVERSE of an income strategy) and the Fed funds rate. Source: Nomura Quantitative Strategy research 30

Low-high yield and fed funds rate Performance of momentum and fed funds rate

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Dec-78 Dec-83 Dec-88 Dec-93 Dec-98 Dec-03 Dec-08 Dec-13

Fed Fund Rate, %

Index

Low-high yield (LHS)

US Federal Funds Target Rate (EP) (RHS)

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Dec-85 Dec-90 Dec-95 Dec-00 Dec-05 Dec-10

Fed Fund Rate, %

Index

High-low mtm (LHS)

US Federal Funds Target Rate (EP) (RHS)

Source: Nomura Quantitative Strategy research

US GDP cycles and factor performance

31 Note: Shows the return to factor portfolios in different market environments from 1926 to 2013. Factor returns are the annualised spread in returns between top and bottom quintile on each of the factors shown sourced from the Kenneth French data library available at http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/index.html. Periods of expansion and contraction are as defined by the NBER. Last recession ended in June 2009, so the analysis has only been run until that point in time. Source: Kenneth French Data Library, NBER, Nomura Quantitative Strategy research

StyleAverage

return all periods, %pa

Return, %pa t-stat Return,

%pa t-stat Return, %pa t-stat Return,

%pa t-stat Return, %pa t-stat

Price to Book (cheap/expensive) 11.40 7.98 1.14 7.90 1.10 20.68 4.50 12.19 2.75 11.38 2.59Momentum (high/low) 7.25 15.41 2.50 -8.30 -1.47 8.04 2.18 8.58 2.33 14.89 3.93Price to Cashflow (cheap/expensive) 8.36 15.72 3.65 4.47 1.08 12.08 5.19 9.75 4.37 4.20 1.94Dividend Yield (cheap/expensive) -0.14 10.76 2.41 -1.16 -0.28 4.81 1.84 -3.54 -1.41 -2.22 -0.88PE, trailing (cheap/expensive) 7.11 15.71 3.63 2.90 0.70 11.78 5.04 8.25 3.70 2.13 0.99Size (Large/Small) -12.45 10.46 1.24 -16.70 -2.20 -15.86 -3.43 -5.91 -1.22 -7.39 -1.54

Early recession Late recession Early expansion Mid expansion Late expansion

32

UK rate cycles and factor performance

Income Growth Value Gearing Quality Risk

30/06/1988 -2.99% -0.20%30/09/1994 -9.74% 6.63% -9.07% 2.31% 11.49% -1.86%31/10/1996 13.36% -8.72% 14.16% -4.04% 11.17% -3.81%30/09/1999 -17.35% 17.18% -19.71% -8.84% 2.67% 1.94%27/02/2004 15.93% -9.71% 25.24% 0.01% 4.40% -12.01%31/08/2006 -7.08% 1.86% -3.87% 3.40% -5.54% 3.03%

Avg -1.31% 1.17% 1.35% -1.43% 4.84% -2.54%Median -5.04% 0.83% -3.87% 0.01% 4.40% -1.86%All period average 3.40% 1.03% 1.92% -1.55% 5.48% 0.35%

Shows one-yr fwd returns after the first hike in each cycle for our post-88 internal styles and the longer-term Ken French styles. Avg and median refer to the average and median of the one-yr fwd returns after the first hike while the all period average refers to the average monthly returns of the respective series over the whole sample period regardless of monetary policy. Source: Nomura Quantitative Strategy research

33 Source: Nomura Quantitative Strategy research

Europe ex UK growth and income driven by valuation, ECB and Fed

Europe ex UK income Europe ex UK GrowthR2 0.27 R2 0.60

Intercept 11.83 2.70 Intercept 14.40 8.57PBK -18.13 -2.68 PBK -6.72 -9.7912m fwd gth in trail eps 0.03 0.74 12m fwd gth in trail eps 0.00 -0.14Fed rates -0.06 -0.13 Fed rates 1.05 5.55Europe rates 0.72 1.67 Europe rates -0.78 -4.47

Coefficients Coefficientst Stat t Stat

Income strategies unattractive

Source: Nomura Quantitative Strategy research 34

Valuation of global income strategy Analyst revisions for income strategy (global and Europe)

0.0

0.2

0.4

0.6

0.8

1.0

1.2


Ratio

Global Dividend Yield - 12mth Fwd P/E

Global Dividend Yield - Price/Book

-30

-25

-20

-15

-10

-5

0

5

10

15

20



Global Dividend Yield - Earning Rev. (3MMA)

Europe Dividend Yield - Earning Rev. (3MMA)

35 Note: The chart shows 12m trailing dividends as % of 12m forward EPS for the top quartile of dividend yield factor and for the current constituents of September 2014 back through time. Source: FTSE, Worldscope, Nomura Quant research

Dividend payout ratio for the highest yielding companies

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75


Ratio

Global high dividend quartile: median payout for last constituents

Global high dividend quartile: median payout

Source: Nomura Quantitative Strategy research 36

Risk valuations Correlation between Risk and Growth

0.0

0.5

1.0

1.5

2.0

2.5

3.0


Ratio Europe Composite Risk - Price/Book

US Composite Risk - Price/Book

Global Composite Risk - Price/Book

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

May-00 May-03 May-06 May-09 May-12

Correlation

Growth and Risk - Europe

Growth and Risk - Global

Figure shows rolling 90 day pairwise correlation coefficient between the styles. Source: Nomura Quantitative Strategy research

Risk still attractive

37 Rolling 90-day correlation between factor pairs. Source: Nomura Quantitative strategy

Correlation of Momentum with other factors

Momentum – global equity factor correlation (90 day)

-1.5

-1

-0.5

0

0.5

1

1.5

May-00 May-02 May-04 May-06 May-08 May-10 May-12 May-14

Correlation

Val-mom Mom-Risk Mom-Quality Mom-Size

Table shows the net exposure to sectors from taking long-short positions in top-quartile portfolios on the styles shown. Source: Nomura Quantitative strategy

Sector exposure of styles

38

Global Europe US UK JP A ex JP GEM Global Europe US UK JP A ex JP GEM Global Europe US UK JP A ex JP GEM

Basic Industries 8% 4% 6% -4% 10% 3% -8% 1% -3% 5% 2% 8% 10% 13% 2% -5% 5% -13% 6% -0% 1%

Capital Goods 2% 2% 5% -7% -6% 4% 8% -2% -4% -2% -4% 4% 6% 5% -4% -5% -8% -3% 2% -7% -11%

Consumer Cyclicals 13% 21% 26% 37% -2% -1% -2% 8% 14% 16% 7% -18% -3% -4% -11% -15% -4% -33% -10% -5% -15%

Consumer Staples -2% -9% -5% -16% 0% 0% -2% -11% -14% -7% -12% -8% 5% -3% 5% -1% 10% 11% 2% -4% -7%

Energy -4% -4% 1% 3% 0% -4% -10% 3% -0% 11% 10% -2% 2% 5% -2% 7% -6% -3% 4% 1% 9%

Financials -16% -11% -18% -14% 0% -11% -3% 9% 24% -4% 16% 10% -15% -7% 6% 7% 8% 21% 4% 18% 19%

Healthcare 4% 4% 6% 6% -6% 6% 8% -5% -12% -7% -3% -2% -1% -0% -12% -12% -14% 0% 8% -6% -7%

Media 7% 2% 8% 3% 3% -1% 2% -2% -3% 4% 1% -4% 0% 1% -1% 4% -6% 3% -2% 0% -3%

Technology 10% 11% -1% 3% 3% 8% 16% 10% 1% 3% 1% 6% 3% 4% -14% -9% -10% -3% -10% -2% -8%

Telecoms -3% -2% -2% 0% 0% -1% -10% -3% 1% -0% 0% -2% -5% -11% 12% 9% 4% 3% 4% 6% 16%

Utilities -20% -18% -27% -10% -3% -2% 0% -10% -5% -18% -16% 8% -1% -4% 18% 21% 21% 17% -8% 0% 4%

Composite growth Composite risk Dividend yield

Neutral Momentum

Source: Nomura Quantitative strategy 39

Global & Europe Composite Momentum - Price/Book Impact of GDP cycle on Momentum returns (US, 1926-2013)

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0


Ratio

Global Composite Momentum - Price/Book

Europe Composite Momentum - Price/Book

Return, %pa T-stat Average across periods

7.25% Early recession

15.40% 2.5 Late recession

-8.30% -1.47 Early expansion

8.00% 2.18 Mid expansion

8.60% 2.33 Late expansion

14.90% 3.93


Momentum composition is changing

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20% B

asic

Indu

strie

s

Cap

ital G

oods

Con

sum

er C

yclic

als

Con

sum

er S

tapl

es

Ene

rgy

Fina

ncia

ls

Hea

lthca

re

Med

ia

Tech

nolo

gy

Tele

com

s

Util

ities

January September

41 Relative price/book and PE of cheap/expensive stocks. Source: Nomura Quantitative strategy

Value is not offering good value…

0.1

0.2

0.3

0.4

0.5

0.6

0.7


Ratio

Global Composite Value - Price/Book Global Composite Value - 12mth Fwd P/E


… and analysts are worryingly bullish on value companies

-30

-25

-20

-15

-10

-5

0

5

10


Net earnings revisions %, (up -down) / total

Europe Composite Value - Earning Rev. (3MMA) Global Composite Value - Earning Rev. (3MMA)

Divergence of factor valuations by region

Figure shows Z scores of the current price/book of top relative to bottom quartile of stocks for each factor within each region Source: Nomura Strategy research 43

As on Aug 31, 2014 US Europe Japan Asia

Pacific Emerging Markets Australia

Value -0.35 -0.64 -0.78 -0.21 -0.48 -0.43

Growth -0.62 -1.32 -1.12 -0.71 -0.08 0.02

Risk 0.58 -0.80 -0.66 0.66 0.41 -0.44

Momentum -1.06 -1.31 0.99 -0.38 -0.38 -0.55

ROE 0.89 2.05 0.97 0.55 0.89 0.99

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5


Ratio Europe Size - Price/Book Global Size - Price/Book

44 Source: Nomura Strategy research

Price/book and P/E valuation of large/small cap stocks

Source: Bloomberg

Real time factor performance for all regions

45


Stable dividend strategy

•There is a ‘hunt for yield’, but simply buying passive equities is not an optimal way to do that and buying the highest yielding equities looks outright unattractive. •Instead we prefer to buy the next tranche of stocks down in terms of yield level, where the dividend is well covered and an analysis of historical dividend policy implies that dividends are likely to grow or be stable. •Purely systematic.

Aim

Methodology

The stocks are ranked on the following five criteria on an equal-weighted composite basis. •Trailing last reported Dividend Yield. •Dividend Growth (Compounded Annual Growth Rate over the past five years), but with a ‘knockout clause’ that the stock gets excluded if in any given year that growth is negative. •Last reported FCF dividend cover. •Standard deviation of the annual dividend growth rate over the past five years. •The five-year Z score of the Fwd P/E. We then create a combined rank and select the stocks that are in the top quartile based on this combination of criteria. The investment universe is the top 500 stocks from the FTSE World and the FTSE Japan for our Japanese version.


Absolute return performance Relative returns performance

Absolute return statistics Relative return statistics

Stable dividend portfolio – Global universe

Return, % pa Benchmark 1 yr 22.2 18.6

3 yr 18.0 15.2

5 yr 15.6 12.7

Whole Period 11.8 8.5

Return, % pa Annualised monthly

volatility Annualised monthly IR

1 yr 1.0 2.3 0.4

3 yr 1.6 3.8 0.4

5 yr 1.8 4.7 0.4

Whole Period 2.5 7.2 0.4

70

270

470

670

870

1070

1270


Stable Dividend

FTSE WORLD

70

90

110

130

150

170

190


Stable Dividend


Global multifactor model

• Our core purely systematic global stock-selection approach. • Has been published and hence live since July 2009, based on an initial European version first

published Sept 2008. • Objective is to find a combination of factors that works smoothly over the cycle, so one does not

need to dynamically allocate between factors. • A key differentiating aspect is that we include a non-linear combination of factors. The economic

interpretation of this is that it measures the level of agreement between factors. • So the model selects stocks that are attractive on factors that have worked within each sector

historically and gives extra score to those where the factors agree. • We choose to let the model use different factors within each sector to better capture different

accounting and business drivers within sectors. • Where possible, we guide the learning process to include at least one component from each of the

value, quality, momentum and growth factor groups.

Aim

Methodology

• We use a learning-based model that identifies which factors are most effective within each sector. This involves an expanding-window panel regression so there is no period that is just in-sample.

• Although the factor coefficients evolve in the learning period, they have been fixed since 2003, so this is a static multifactor model.

• Based on the 500 largest companies in the developed world, it selects the most attractive top/bottom quartiles; the long-only version just selects the top quartile of stocks within each sector.

• The model does not take any sector views.

One of the key innovations over previous work is that we introduce a non-linear ‘cross-term’ factor that models the interaction of factors

• The functional form of our multifactor model:

• Certain non-linear interaction functions can have the economic interpretation of measuring agreement.

• Extra complexity should only be added with good reason, but we can show an empirical benefit to such a term.

• To defend against a charge of data mining, we impose an a priori functional form that we believe is defendable.

• Non-linear interaction terms also have the benefit of lessening the impact of crowding if it brings together factors in ways that are not usually practiced.

Non-linear global multifactor model

)(... ,,,2,1:, tititititti MVMVr ⋅ℑ+++=+ γββαδ

49


We use a cubic interaction factor as our favoured approach Alternative is a discontinuous interaction screen

Increasing momentum

Cheaper

Increasing momentum

Cheaper

Interaction Score Interaction Score

50

Non-linear global multifactor model

Non-linear global multifactor model: weights of factors by sector


Basic Industries

Consumer Cyclicals

Capital Goods

Consumer Staples Energy Healthcare Media Tech Telecoms Utilities Financials

Value Price/book 5 EV/EBITDA 20 10 20 PE (forward) 35 PE (trailing) 20 FCF Yield 25 25 30 Div Yld (b'back adjusted) 10 20 20 25 10 20

Growth Internal Growth 25 20 25 35 10 15 Growth FY0-FY3 20 15 25 20 Long-Term Growth 30 35 Sales Growth (historical) 10

Quality Interest Cover 5 Debt/EBITDA -15 -15 Change in Shares -25 -20 -10 EBITDA Margin 25 ROE 20 10 25 ROCE 15 10 Accruals -5

Momentum 1m Price Momentum -15 -20 -15 -5 -20 9m Price Momentum 15 25 12m Price Momentum 20 Normalised 12m P Mtm 25 6m Earnings Momentum 20

Interaction (V+M) 3 15 10 10 15 25 20 20 10 15

51

Global multifactor model


Performance of Nomura global multifactor model Value added from non-linearity

100

150

200

250

300

350

400

450

500

550

600

650

700

750

Dec

-91

Dec

-93

Dec

-95

Dec

-97

Dec

-99

Dec

-01

Dec

-03

Dec

-05

Dec

-07

Dec

-09

Dec

-11

Dec

-13

Dec 91 = 100

Out of sample Live Period

Start of Drawdown

Length of Drawdown (Days)

% Fall

10/10/2005 368 -3.119/09/2007 135 -2.913/10/2008 546 -8.423/04/2010 173 -3.4

Return, % pa

Annualised monthly volatility

Annualised monthly IR

Whole Period 9.2 6.8 1.3 Dec 91 - Jun 04 13.0 8.3 1.6 Jun 04 - Present 4.7 4.1 1.1 July 09 - Present 5.2 4.3 1.2 Jan 10 - Present 4.8 4.3 1.1

100

105

110

115

120

125

Dec

-91

Dec

-93

Dec

-95

Dec

-97

Dec

-99

Dec

-01

Dec

-03

Dec

-05

Dec

-07

Dec

-09

Dec

-11

Dec

-13

Out of sample

Dec 91 = 100

Live Period Performance during live

period Return, %

pa

Annualised monthly volatility

Annualised monthly IR

Non-linear model 5.2 4.3 1.2

Linear model 4.4 4.1 1.1

Relative performance of non-linear and linear versions of our global multifactor model. Source: Nomura Strategy research


Absolute return performance (out of sample period) Relative returns performance (out of sample period)


Global multifactor (long-only version)

70.0

120.0

170.0

220.0

270.0

320.0

Jun-04 Jun-07 Jun-10 Jun-13

GMF Long only Sector Weighted

FTSE WORLD

90 95

100 105 110 115 120 125 130 135 140

Jun-04 Jun-07 Jun-10 Jun-13

GMF Long only Sector Weighted

Return, % pa Benchmark 1 yr 30.1 18.6

3 yr 19.4 15.2

5 yr 16.0 12.7

Out of sample Period 11.5 8.0


volatility Annualised monthly IR

1 yr 7.7 2.3 3.3

3 yr 3.3 3.4 1.0

5 yr 2.8 3.1 0.9 Out of sample

Period 3.2 3.2 1.0

The Nomura Global Equity Quant Recommended Portfolio

Note: As of end-August 2014. We established our Recommended Global Quant portfolio in August 2013 (see A portfolio of Quant Ideas August 27 2013). It uses a combination of strategic strategies that are long-term core quant holdings and tactical ones that are a function of the cycle. The strategic and tactical components receive equal weighting and among the strategic quant trades we use equal risk contribution weighting. This is an absolute return strategy, so the benchmark is cash or market neutral hedge fund strategies Source: Bloomberg, Nomura Quantitative strategy 54

Trade Bloomberg 1 month YTD 1 year 2 year 3 year 1 year R/R

Strategic trades

Global Multifactor Model na +1.4% +4.7% +12.9% +7.1% +5.7% 3.1

Equity Alternative Beta na +0.4% +0.3% +1.5% +2.0% +2.2% 0.7

Volatility Risk Premium NMEDSVP1 & NMEDSVP2 +1.4% +4.1% +7.8% +6.5% +8.8% 3.5

Natural Index na +1.8% +7.0% +21.8% +21.4% +16.9% 2.5

Stable Dividends NMRASDVD +2.7% +8.8% +22.2% +21.3% +18.0% 2.4

Tactical trades

Long Composite Risk NMGLRISK -0.9% -2.2% +0.3% +3.3% -2.1% 0.1

Long European cheap domestic NMRDOMS -2.5% +9.0% +9.4% +18.5% +1.1% 1.2

Short European Dividend Yield NMRADVDL/NMRADVDS +1.5% -9.7% -11.1% -3.6% -0.4% 1.9

Long Composite Growth +2.0% -4.5% -0.2% +4.6% +3.2% 0.0

Long European Size NMRASIZE +0.8% +2.8% +3.4% -2.3% +2.0% 0.8

Long EM quant country selector Model +0.8% +1.1% +1.7% +1.0% +0.1% 1.0

1 month YTD YTD R/R

Recommended Quant Portfolio +0.6% +1.4% 1.1

HFR Market Neutral Index +0.9% +2.3% 1.1

(As of end of Aug 2014)

Long horizon concentrated strategies: a global recommended quant stock portfolio

Figure shows return vs risk for several 3-year holding period and quarterly rebalancing P/E-based strategies. The portfolios are long only and built as the aggregate of 3 shifted portfolios with a one year interval and rebalanced every 3 years. The benchmark is the top-500 stocks in the FTSE World universe. The screening details: - The 3yr concentrated version is defined as the cheap top-20 stocks screened on their respective factor. - In the 3yr holding sector-neutral version the screening is on a sector neutral basis and the sector weights match sector weights’ benchmark at the rebalancing period. - The 3yr quartile version is defined as the cheap quartile stocks screened on their respective factor. - The quarterly rebalancing version is defined as the cheap quartile stocks screened on their respective factor with a 3-month holding period. The Value + Q or Value + M portfolios are screened using a composite ranking averaging value score with the quality or momentum score. Quality is defined on an equal weighted composite basis by EBITDA Margin, ROE, tax/pre-tax income, credit rating and change in number of shares. Earnings momentum is defined as the percentage change in average consensus of the 12-month forward earnings over the past two quarters. Source: Nomura Quantitative Strategy research

Return vs Risk for 3-year holding period P/E-based strategies

56

FWD PE FWD PE + Q

FWD PE + M FWD PE

FWD PE + Q

FWD PE + M

FWD PE

FWD PE + Q

FWD PE + M

FWD PE

FWD PE + Q

FWD PE + M

FTSE WORLD FTSE WORLD ex Fin

Top 500 Top 500 ex Fin

6

7

8

9

10

11

12

13

14 15 16 17 18 19 20 21

Return

Risk


Global Recommended Portfolio

•This is a blend of bottom-up systematic stock selection with top-down strategy views on regions and sectors. •The systematic stock selection uses our long-horizon quant stock selection model. •Note that the portfolio has always been a blend of quant and discretionary, but the long-horizon quant stock selection model has only been used since we published it in 2013.

•Portfolio has been run since 1997.

Aim

Note: Portfolio benchmark is FTSE All World Total Return index in USD terms Source: Datastream, Nomura Strategy research 58

Absolute return performance Relative returns performance


Global Recommended Portfolio

0

50

100

150

200

250

31/12/1999 31/12/2002 31/12/2005 31/12/2008 31/12/2011

Portfolio performance index

Benchmark performance index

80

85

90

95

100

105

110

115

120

125

31/12/1999 31/12/2002 31/12/2005 31/12/2008 31/12/2011

Portfolio relative performance Index

Return, % pa Benchmark, % pa

1yr 23.07 22.28

2yr 23.88 20.63

5yr 15.43 15.14

Since 2000 4.94 4.25

Rel Return, % pa Tracking Error IR

1yr 0.79 2.96 0.27

2yr 3.26 3.43 0.95

5yr 0.29 4.44 0.06

Since 2000 0.69 5.74 0.12

Global Quant Stock Portfolio

59

1 EPS Estimates are based on IBES Mean Consensus 2 Relative performance shown as total return performance less performance of FTSE All World total return index. 3 Analyst rating refers to Nomura research department rating. Past performance should not and cannot be viewed as an indicator of future performance. Complete record available upon request Source: Nomura Quantitative strategy

Price ($) Mkt Cap Calendarised EPS y/e Dec1 Price/ earnings Date Rel Perf. since Rel Perf. Over AnalystSector Stock Currency 27 Aug 14 US$m 2013a 2014e 2015e Dec 15 (x) Added Added2 week2 Rating6

North America Underweight

Capital Goods DEERE & CO USD 83.9 29358.8 9.1 8.1 6.8 12.3 6 Mar 14 -10 -3 Not RatedNORTHROP GRUMMAN CORP USD 127.6 27327.9 8.4 9.4 10.1 12.7 6 Mar 14 -3 -1 Not Rated

Consumer Cyclicals GAP INC USD 46.2 11818.2 2.7 2.9 3.3 13.9 31 Jul 14 13 6 NeutralEnergy CHEVRON CORP USD 128.6 245590.5 11.1 10.7 11.3 11.4 6 Mar 14 8 0 Not RatedFinancials AFLAC INC USD 61.4 26802.4 6.2 6.2 6.5 9.5 6 Mar 14 -11 0 Not Rated

ALLSTATE CORP USD 61.5 26703.5 5.7 5.0 5.7 10.7 6 Mar 14 6 0 Not RatedCANADIAN IMPERIAL BANK CAD 96.9 38712.3 8.1 8.2 8.7 11.2 6 Mar 14 9 1 Not RatedDISCOVER FINANCIAL SVCS INC USD 62.7 29539.3 5.0 5.3 5.6 11.1 6 Mar 14 1 0 Buy

Healthcare MERCK & CO USD 60.3 173885.6 3.5 3.5 3.6 16.8 6 Mar 14 0 0 Not RatedPFIZER INC USD 29.5 188232.5 2.2 2.2 2.2 13.2 6 Mar 14 -14 1 Not Rated

Media DIRECTV USD 86.2 43404.5 5.2 5.9 6.4 13.4 6 Mar 14 1 0 NeutralTechnology INTL BUSINESS MACHINES CORP USD 192.3 191787.1 16.3 17.9 19.8 9.7 6 Mar 14 -3 0 Not Rated

ORACLE CORP USD 41.6 144199.5 2.9 3.0 3.3 12.5 6 Mar 14 0 0 BuySEAGATE TECHNOLOGY PLC USD 61.2 19155.2 5.3 5.2 5.6 10.9 6 Mar 14 18 1 Not Rated

Europe Ex UK Neutral

Basic Industries BASF SE EUR 104.7 96614.8 7.6 8.3 7.5 13.9 6 Mar 14 -10 2 NeutralCapital Goods SIEMENS AG EUR 127.3 100884.0 7.7 9.5 7.2 17.6 6 Mar 14 -10 2 BuyConsumer Cyclicals A.P. MOLLER-MAERSK DKK 2559.7 17204.1 214.6 108.7 145.8 17.6 6 Mar 14 1 0 Buy

BAYER MOTOREN WERK EUR 119.2 38748.2 6.5 9.8 10.3 11.6 6 Mar 14 0 0 BuyVOLKSWAGEN AG EUR 229.8 6764.5 20.0 24.4 61.3 3.7 6 Mar 14 -13 0 Neutral

Energy STATOIL ASA NOK 28.6 27354.5 1.9 2.6 2.8 10.2 6 Mar 14 4 0 NeutralTOTAL EUR 65.7 133404.1 6.1 6.6 7.2 9.1 6 Mar 14 -3 1 Buy

Financials ALLIANZ SE EUR 172.2 78387.7 14.7 7.2 15.0 11.5 6 Mar 14 -4 1 BuyAXA EUR 24.9 47336.4 2.1 1.9 2.4 10.4 6 Mar 14 -7 3 BuyCREDIT AGRICOLE SA EUR 15.0 14993.3 1.2 2.1 1.6 9.4 6 Mar 14 -12 5 BuyMUENCHENER RUECKVE EUR 200.5 29848.9 17.2 5.2 23.7 8.4 6 Mar 14 -9 0 ReduceSWISS RE AG CHF 82.4 28185.5 2.5 7.1 11.1 7.4 6 Mar 14 -8 1 Buy

Telecoms ORANGE EUR 15.3 27619.6 2.6 2.1 1.7 9.1 6 Mar 14 7 3 Buy

United Kingdom Underweight

Energy ROYAL DUTCH SHELL GBP 42.1 103165.6 3.0 4.0 4.0 10.5 6 Mar 14 4 0 BuyFinancials STANDARD CHART PLC GBP 20.3 41109.8 1.9 2.0 2.2 9.1 6 Mar 14 -6 -1 BuyHealthcare ASTRAZENECA GBP 73.8 93106.6 6.7 7.3 6.4 11.5 6 Mar 14 5 3 Not Rated

GLAXOSMITHKLINE GBP 24.3 117953.9 2.2 1.9 1.8 13.2 6 Mar 14 -17 2 Not RatedMedia BRITISH SKY BROADC GBP 14.4 15146.2 0.5 0.8 0.9 15.9 6 Mar 14 -13 0 Neutral

Japan Overweight

Capital Goods ITOCHU CORP JPY 13.0 20135.9 1.0 1.6 1.7 7.5 6 Mar 14 -1 0 BuyMITSUBISHI CORP JPY 21.1 30307.5 2.7 2.7 2.2 9.4 6 Mar 14 6 -1 BuyMITSUI & CO JPY 16.5 28573.7 1.6 2.1 1.8 9.2 6 Mar 14 2 -1 Buy

Consumer Cyclicals FUJI HEAVY INDS JPY 28.8 18061.1 0.6 0.5 1.2 23.6 31 Jul 14 -2 1 BuyTelecoms NIPPON TEL&TEL CP JPY 66.4 24578.6 3.7 3.6 4.0 16.6 6 Mar 14 12 -2 Buy

Asia Ex Japan Underweight

Basic Industries BHP BILLITON LTD AUD 34.9 111862.1 2.2 3.6 2.7 12.9 6 Mar 14 -4 -3 Buy

Emerging Mkts Overweight

Basic Industries CHINA SHENHUA ENER HKD 2.9 9866.8 0.3 0.4 0.4 7.3 31 Jul 14 -5 -4 NeutralKUMBA IRON ORE LTD ZAR 31.0 1785.3 4.2 5.0 3.6 8.7 31 Jul 14 -10 -2 Not Rated

Capital Goods ITAUSA INV ITAU SA BRL 4.7 14893.3 0.3 0.4 0.4 13.2 6 Mar 14 37 5 Not RatedLG CORP KRW 71.4 6404.5 8.6 5.7 5.3 13.6 6 Mar 14 31 1 Buy

Consumer Cyclicals HYUNDAI MOTOR CO KRW 224.8 34471.9 19.8 27.8 31.1 7.2 6 Mar 14 -8 1 BuyKIA MOTORS CORP KRW 59.0 15246.9 6.5 8.3 9.4 6.3 6 Mar 14 6 -1 Neutral

Energy CAIRN INDIA INR 5.4 10034.8 0.5 0.7 1.0 5.6 6 Mar 14 -6 0 ReduceSK HOLDINGS CO LTD KRW 162.2 4185.5 N/A 39.7 25.5 6.4 6 Mar 14 -16 2 Not Rated

Financials BANK OF CHINA LTD HKD 0.5 39275.2 0.1 0.1 0.1 6.0 6 Mar 14 16 -2 BuyBANK OF COMMUNICAT HKD 0.7 26021.6 0.1 0.1 0.1 5.2 6 Mar 14 20 -1 NeutralBCO BRADESCO SA BRL 17.6 37191.9 1.0 1.2 1.2 14.5 6 Mar 14 40 5 Not RatedCHINA CONST BK HKD 0.8 181164.9 0.1 0.1 0.1 6.0 6 Mar 14 14 -2 NeutralCHINA MINSHENG BAN HKD 1.0 6727.8 0.1 0.1 0.2 5.3 6 Mar 14 17 -3 ReduceIND & COM BK CHINA HKD 0.7 58235.6 0.1 0.1 0.1 6.2 31 Jul 14 -5 -1 Buy

Healthcare TEVA PHARMA IND ILS 52.7 49906.0 4.5 5.0 5.4 9.8 6 Mar 14 -1 -1 Not RatedTechnology INTOUCH HOLDINGS P THB 2.2 3257.9 0.1 0.1 0.1 16.6 6 Mar 14 -6 -2 Buy

SAMSUNG ELECTRONIC KRW 1212.6 130106.2 104.2 87.7 151.8 8.0 6 Mar 14 -9 -3 BuyTelecoms AMERICA MOVIL SAB MXN 1.2 37083.9 0.1 0.1 0.1 13.1 6 Mar 14 20 1 Not Rated

TURK TELEKOMUNIKAS TRY 2.9 1525.2 0.3 0.3 0.3 8.3 6 Mar 14 4 1 Not Rated

Portfolio perf. (US$ terms, %)3 1 WK 1 MTH YTD 12 MTH 2013 2012 2011 2010 2009 4 2008 5 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997Nomura Strategy Recommend Portfolio 1.0 2.8 8.0 21.3 23.0 21.5 -14.9 14.6 55.9 -16.1 6.9 12.9 11.1 11.9 33.7 -23.8 -13.8 -2.8 40.8 35.7 20.1FTSE All World Index 0.9 1.7 7.8 21.2 23.3 17.4 -7.3 13.2 35.8 -18.9 12.8 18.8 8.9 13.7 31.0 -20.6 -17.5 -12.2 24.2 22.8 13.61 EPS Estimates are based on IBES Mean Consensus

3 Return history presented as price return in US$ Terms from before 2006. Returns from 2007 to present are on a Total Return basis.

2 Relative performance shown as total return performance less performance of FTSE All World total return index.

4 Starting 9th January 20095 Ending 12th September 2008

Sector allocation

Recommended sector weightings

1Combination of Cyclical Consumer Goods and Cyclical Services excluding Media Source: Nomura Strategy research

Europe Global

61

Benchmark Recommended

Weighting Recommendation

Energy 10 10 Neutral

Materials 6 5 Underweight

Industrials 10 14 Overweight

Consumer Discretionary 11 14 Overweight

Consumer Staples 9 0 Underweight

Healthcare 11 4 Underweight

Financials 22 30 Overweight

-Banks 11 19 Overweight

-Insurance 4 4 Neutral

-Other 7 7 Neutral

Information Technology 13 19 Overweight

Telecom Services 4 3 Underweight Utilities 3 0 Underweight

Benchmark Recommended

Weighting Recommendation

Basic Industries 10 10 Neutral

Capital Goods 8 12 Overweight

Consumer Cyclicals 1 10 15 Overweight

Consumer Staples 13 5 Underweight

Energy 10 9 Neutral

Financials 22 31 Overweight

of which: Banks 13 22 Overweight

Insurance 6 4 Underweight

Other 3 4 Overweight

Healthcare 12 8 Underweight

Media 2 2 Underweight

Technology 3 6 Overweight

Telecoms 4 2 Underweight Utilities 4 0 Underweight

Cyclical growth over stable growth

Figure shows the relative valuation of high expected growth to high stable growth companies. The dot at the end shows the same data for the subset of high expected growth companies from cyclical sectors which constitute our Cyclical Growth basket. Source: Nomura Quantitative Strateg 62

Valuation of Cyclical Growth/Stable Growth (P/E) Valuation of Cyclical Growth/Stable Growth (PBK)

0.6

0.8

1.0

1.2

1.4

1.6

1.8


Ratio

Cyclical growth/stable

growth

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2


Ratio

Cyclical growth/stable

growth

Figure shows the relative valuation of high expected growth to high stable growth companies. The dot at the end shows the same data for the subset of high expected growth companies from cyclical sectors which constitute our Cyclical Growth basket. Source: Nomura Quantitative Strategy

63 Source: Nomura Strategy research

Cyclical growth basket

Company Sector Company Sector

HOLCIM LTD. Basic Industries SOCIETE GENERALE S.A. CLASS A Financials

SOLVAY SA Basic Industries SCHRODERS PLC Financials

LAFARGE SA Basic Industries ASHTEAD GROUP PLC Financials

COMPAGNIE DE SAINT-GOBAIN SA Basic Industries PRUDENTIAL PLC Financials

HEIDELBERGCEMENT AG Basic Industries BANCO SANTANDER S.A. Financials

AKZO NOBEL N.V. Basic Industries BANCO POPULAR ESPANOL SA Financials

GLENCORE PLC Basic Industries BANCO BILBAO VIZCAYA ARGENTARIA, S.A. Financials

SKF AB CLASS B Capital Goods BANCO DE SABADELL SA Financials

AIRBUS GROUP NV Capital Goods CREDIT AGRICOLE SA Financials

VOLVO AB CLASS B Capital Goods COMMERZBANK AG Financials

SIEMENS AG Capital Goods BANKIA, S.A. Financials

HEXAGON AB CLASS B Capital Goods KBC GROUPE SA Financials

INTERNATIONAL CONSOLIDATED AIRLINES GROUP SA Consumer Cyclcials DANSKE BANK A/S Financials

EASYJET PLC Consumer Cyclcials CAIXABANK SA Financials

CRH PLC Consumer Cyclcials INTESA SANPAOLO S.P.A. Financials

VALEO SA Consumer Cyclcials JULIUS BAER GRUPPE AG Financials

PORSCHE AUTOMOBIL HOLDING SE PREF Consumer Cyclcials UBS AG Financials

RENAULT SA Consumer Cyclcials ILIAD SA Technology

VOLKSWAGEN AG Consumer Cyclcials ASML HOLDING NV Technology

WHITBREAD PLC Consumer Cyclcials UNITED INTERNET AG Technology

RYANAIR HOLDINGS PLC Consumer Cyclcials ARM HOLDINGS PLC Technology

ADECCO S.A. Consumer Cyclcials LM ERICSSON TELEFON AB CLASS B Technology

ACCOR SA Consumer Cyclcials INFINEON TECHNOLOGIES AG Technology

A.P. MOLLER - MARSK A/S CLASS B Consumer Cyclcials

RANDSTAD HOLDING NV Consumer Cyclcials

AEROPORTS DE PARIS SA Consumer Cyclcials

PANDORA A/S Consumer Cyclcials

Avoid income stocks: underweight Insurance and Utilities


Earnings revisions of European Insurance relative to the market Free cash flow dividend cover Utilities

Long-term expected EPS growth rate for Utilities and the market

2

4

6

8

10

12

14

16

18

Apr-88 Apr-94 Apr-00 Apr-06 Apr-12

Ratio

Utilities Market

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Jan-88 Jan-94 Jan-00 Jan-06 Jan-12

%

-20

-15

-10

-5

0

5

10

15

20

Mar-87 Mar-93 Mar-99 Mar-05 Mar-11


Buying Growth: Further increasing Tech overweight

65

P/E of European Tech relative to the market Earnings revisions of European Tech relative to the market

0.5

1.0

1.5

2.0

2.5

3.0

3.5


Ratio

-25

-20

-15

-10

-5

0

5

10

15

Mar-87 Mar-91 Mar-95 Mar-99 Mar-03 Mar-07 Mar-11



Margin recovery plays

Source: Datastream, Nomura Strategy research 66

12m trailing EBITDA margins: Cyclicals / defensives and EU economic sentiment indicator

US/UK capex intentions composite and Capital goods 12m fwd EBITDA margins

ECB bank lending survey and bank 12m forward net profit margins

75

80

85

90

95

100

105

110

115

120

0.65

0.70

0.75

0.80

0.85

0.90

May-91 May-98 May-05 May-12

Index Ratio 12m trailing EBITDA margins: Cyclicals / defensives (LS)

EU Economic sentiment indicator (Advanced, RS)

10.5

11.0

11.5

12.0

12.5

13.0

13.5

-3.5

-2.5

-1.5

-0.5

0.5

1.5

Jan-07 Jan-10 Jan-13

% Index US/UK capex intentions composite* (Advanced, LS)

Capital goods 12m forward EBITDA margins (RS)

*Includes Philly Fed capex intentions survey and BoE Agent scores survey of manufacturing sector investment intentions. Source: Datastream, Nomura Strategy research

10

12

14

16

18

20

22

24

26

28

-50

-40

-30

-20

-10

0

10

20

30

Q2 2004 Q2 2007 Q2 2010 Q2 2013

ECB bank lending survey: Net change in firms credit demand last quarter (Advanced, LS)

Bank 12m forward net profit margins (RS)

% %

Source: Datastream, Nomura Strategy research

Buy US capex exposure


US capex basket: median relative price/book and 12m fwd PE US capex-exposed companies (NMRAUSCX)

Company Industry

Arcelormittal Industrial Metals

BMW Autos & parts

Clariant Chemicals

CRH Construction

Daimler Autos & parts

Electrolux Household goods

Fiat Autos & parts

Heidelberg Cement Construction

Hochtief Construction

Philips Industrials

Rexel Electrical equipment

SAP Technology

Siemens Industrials

SSAB Industrial Metals 0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2


Ratio Ratio US CAPEX basket: Median relative PBK (LHS)

US Capex basket: Median relative 12m FWD PE (RHS)

Price/tangible book and return on tangible equity for banks


Europe Global

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0

5

10

15

20

25

30

Jan-

90

Jan-

92

Jan-

94

Jan-

96

Jan-

98

Jan-

00

Jan-

02

Jan-

04

Jan-

06

Jan-

08

Jan-

10

Jan-

12

Jan-

14

% Ratio

Return on tangible equity (LHS) Price/tangible book (RHS)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0

5

10

15

20

25

30

Jan-

90

Jan-

92

Jan-

94

Jan-

96

Jan-

98

Jan-

00

Jan-

02

Jan-

04

Jan-

06

Jan-

08

Jan-

10

Jan-

12

Jan-

14

% Ratio

Return on tangible equity (LHS)

Price/tangible book (RHS)

Fund management strategy and minimum variance

Fundamental managers underperforming

Source: Bloomberg, Nomura Strategy research

70

Recent relative performance of active fundamental managers has closely tracked momentum Exclusively bottom up vs top down macro funds

98.0

98.5

99.0

99.5

100.0

100.5

101.0

Jan-

14

Jan-

14

Mar

-14

Apr-

14

May

-14

May

-14

Jun-

14

Jul-1

4

Aug-

14

Index

88

90

92

94

96

98

100

102

104

106

92

93

94

95

96

97

98

99

100

101

102

Jul-1

3

Aug-

13

Sep-

13

Oct

-13

Nov

-13

Dec

-13

Jan-

14

Feb-

14

Mar

-14

Apr-

14

May

-14

Jun-

14

Jul-1

4

Aug-

14

Sep-

14

European Long-only fundamental funds (LHS)

Composite Momentum: World (RHS)

Source: Nomura Quantitative strategy

Performance of unconstrained vs constrained managers Concentrated fund performance and European cross-sectional stock correlation

Correlation is defined as 75 day rolling cross-sectional correlation between top 500 stocks in FTSE Europe index. Source: Nomura Quantitative strategy

71

99.2

99.4

99.6

99.8

100.0

100.2

100.4

100.6

100.8

101.0

Jan-

14

Feb-

14

Mar

-14

Apr-

14

May

-14

Jun-

14

Jul-1

4

Aug-

14

Sep-

14

Index

0.00

0.10

0.20

0.30

0.40

0.50

0.60

95

97

99

101

103

105

107

109

111

113

115

Jan-

05

Jan-

06

Jan-

07

Jan-

08

Jan-

09

Jan-

10

Jan-

11

Jan-

12

Jan-

13

Jan-

14

Correlation 3 Jan 05 = 100

Up to 50 vs Up to 100 stocks performance (LHS)

Europe cross sectional stock correl (RHS)

72 Source: Nomura Quantitative Strategy research

Asset share of fundamental managers with more than or fewer than 100 stocks

0.0

0.5

1.0

1.5

2.0

2.5

0

5

10

15

20

25


% %

Up to 100 >100

More ‘active’ approaches gaining asset share

Index of asset share of funds by tracking error range. Source: Bloomberg, Nomura Strategy research

AUM share by tracking error bucket Cumulative asset shares of high- relative to low-TE funds, and constrained relative to unconstrained funds


60

80

100

120

140

160

180


3 Jan 05 = 100

0-4

4 to 8

>8 (cap at 20)

60

70

80

90

100

110

120

130

140

0

20

40

60

80

100

120

140

160

180


Jan 05 = 100 Jan 05 = 100

High TE rel to low TE (LHS)

Unconstrained vs Constrained (RHS)

-1500

-1000

-500

0

500

1000

1500

Mar

-02

Mar

-03

Mar

-04

Mar

-05

Mar

-06

Mar

-07

Mar

-08

Mar

-09

Mar

-10

Mar

-11

Mar

-12

Mar

-13

Mar

-14

USDbn

Active Passive All funds

Source: EPFR, Nomura Quantitative strategy 74

Global equity mutual fund flows active passive Share of passively-managed equities

Source: EPFR, Nomura Quantitative strategy

14

16

18

20

22

24

26

28

30

32

Jan-

05

Jan-

06

Jan-

07

Jan-

08

Jan-

09

Jan-

10

Jan-

11

Jan-

12

Jan-

13

Jan-

14

%


Distribution of active Relationship of active share and tracking error

0

5

10

15

20

25

>95%

90-9

5%

80-9

0%

70-8

0%

60-7

0%

50-6

0%

40-5

0%

30-4

0%

20-3

0%

% of Total Sample

Quant

Fundamental

Enhanced Active Highly active

0

1

2

3

4

5

6

7

8

Highly Active Active Enhanced

%

Average Tracking Error (5yr)

Average Tracking Error (5yr) (Quant-only)

Active share

Highly active and active sample of non quant and quant funds, enhanced sample is purely quant funds. Source: Nomura Quantitative strategy research . 76

Highly active non quants and low active share quants outperforming Return and Risk for fund types

Highly active Active Enhanced

3yr 5yr

Return 3.01 0.10 1.58

Risk 7.51 5.18 5.11

R/R 0.40 0.02 0.31

95.00

100.00

105.00

110.00

115.00

120.00

125.00

130.00

135.00

140.00

145.00

Dec

-04

Jun-

05

Dec

-05

Jun-

06

Dec

-06

Jun-

07

Dec

-07

Jun-

08

Dec

-08

Jun-

09

Dec

-09

Jun-

10

Dec

-10

Jun-

11

Dec

-11

Jun-

12

Dec

-12

Jun-

13

Dec

-13

Jun-

14


Active share and fees

Source: Quantitative Strategy research 77

Expense ratio by active share category Active share and fee structure

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4


Ratio


Management fee 1.13 0.98 0.46

Expense ratio 1.27 1.18 0.66

Front load 1.41 2.84 2.18

Back load 0.10 0.20 0.34

Performance fee 7.83 7.86 0.00

We define highly active as funds with an active share>80%, active as between 50 and 80% and enhanced index as active shares<50%. Source: Nomura Quantitative strategy research

78

Note: Chart shows the asset share of quants as a proportion of total active equity AUM. Note that our sample of traditional quant funds is based on a survey that, although broad, is definitionally an under-representation of the true size of quants, so we have scaled this up to set quant at 10% of active AUM in July 2007. We then add the asset share of our alternative beta sample to this, which is not scaled as we think that we have captured the bulk of listed alternative beta assets. The Divine Comedy labels are, of course, just our own call. Source: Quantitative Strategy research

Quant market share

5.0

5.5

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

Dec

-06

Jun-

07

Dec

-07

Jun-

08

Dec

-08

Jun-

09

Dec

-09

Jun-

10

Dec

-10

Jun-

11

Dec

-11

Jun-

12

Dec

-12

Jun-

13

Dec

-13

% of AUM Inferno

Purgatorio Paradiso??

Chart shows the performance of quant funds that use a dynamic factor allocation strategy relative to those that use a static approach. Source: Nomura Strategy research

Performance of dynamic vs static quant funds Share of AUM for dynamic and static quant funds

79 Percentage AUM as a share of active equity funds Source: Nomura Strategy research

92

94

96

98

100

102

104

106

108

110

Jan-

06

Jul-0

6

Jan-

07

Jul-0

7

Jan-

08

Jul-0

8

Jan-

09

Jul-0

9

Jan-

10

Jul-1

0

Jan-

11

Jul-1

1

Jan-

12

Jul-1

2

Jan-

13

Jul-1

3

Jan-

14

Jul-1

4

2 Jan 06 = 100

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

Jan-

06

Jun-

06

Nov

-06

Apr-

07

Sep-

07

Feb-

08

Jul-0

8 D

ec-0

8 M

ay-0

9 O

ct-0

9 M

ar-1

0 Au

g-10

Ja

n-11

Ju

n-11

N

ov-1

1 Ap

r-12

Se

p-12

Fe

b-13

Ju

l-13

Dec

-13

May

-14

Static

Dynamic

Performance of funds with and without discretion

Performance of funds that employ different levels of discretion relative to pure quant funds with no discretion. Source: Nomura Strategy research

Performance of funds with and without discretion Asset share for funds with differing levels of discretion

80 Percentage AUM as a share of active equity funds. Source: Nomura Strategy research

80

85

90

95

100

105

110

115

120

Jan-

06

Jun-

06

Nov

-06

Apr-

07

Sep-

07

Feb-

08

Jul-0

8 D

ec-0

8 M

ay-0

9 O

ct-0

9 M

ar-1

0 Au

g-10

Ja

n-11

Ju

n-11

N

ov-1

1 Ap

r-12

Se

p-12

Fe

b-13

Ju

l-13

Dec

-13

Discretion on single stocks/Pure quant Broad discretion/Pure quant

Index

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

Jan-

06

Jun-

06

Nov

-06

Apr-

07

Sep-

07

Feb-

08

Jul-0

8 D

ec-0

8 M

ay-0

9 O

ct-0

9 M

ar-1

0 Au

g-10

Ja

n-11

Ju

n-11

N

ov-1

1 Ap

r-12

Se

p-12

Fe

b-13

Ju

l-13

Dec

-13

May

-14

Pure quant/systematic

Quant with discretionary views on single stocks

%

Source: Quantitative Strategy research 81

Relative performance of inductive and deductive quants Relative asset share of inductive and deductive quants

85

90

95

100

105

110

115


Index

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8


%

Induction deduction

Minimum variance flows and performance

Percentage AUM as a share of active equity funds. Source: Nomura Strategy research 82

Asset share of minimum variance Relative performance of minimum variance strategies

MSCI minimum variance is relative to MSCI World. For the relative minimum variance funds index the performance of funds is relative to their own fund’s benchmark as defined on Bloomberg. Source: Bloomberg, Nomura Quantitative strategy research

95

100

105

110

115

Dec-10 Dec-11 Dec-12 Dec-13

31 Dec 10 = 100 Minimum variance funds and ETFs (asset share)

Minimum variance funds (asset share)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

Dec-09 Dec-10 Dec-11 Dec-12 Dec-13

%

Minimum variance funds and ETFs (asset share)

Minimum variance funds (asset share)

Minimum variance: the volatility advantage and valuations

Volatility of the MSCI low volatility index less volatility of the MSCI World index, rolling 30-day periods. Source: Datastream, Bloomberg, Nomura Strategy research 83

Relative volatility of low volatility companies Relative price to book of the global minimum variance portfolio

-3.3

-2.8

-2.3

-1.8

-1.3

-0.8

-0.3

0.2

Feb-

06

Feb-

07

Feb-

08

Feb-

09

Feb-

10

Feb-

11

Feb-

12

Feb-

13

Feb-

14

%

Volatility of Min Var Sample of funds vs MSCI World

Volatility of MSCI Min Vol vs MSCI World

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Jan-

90

Jan-

92

Jan-

94

Jan-

96

Jan-

98

Jan-

00

Jan-

02

Jan-

04

Jan-

06

Jan-

08

Jan-

10

Jan-

12

Jan-

14

Ratio

Multi-asset still a bright spot

Source: Nomura Quantitative strategy research 84

AuM of multi-asset funds, USD million Multi-asset performance

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

1000000

Jan-

04

Jan-

05

Jan-

06

Jan-

07

Jan-

08

Jan-

09

Jan-

10

Jan-

11

Jan-

12

Jan-

13

Jan-

14

USD mn

80

100

120

140

160

180

200

Jan-

04

Jan-

05

Jan-

06

Jan-

07

Jan-

08

Jan-

09

Jan-

10

Jan-

11

Jan-

12

Jan-

13

Jan-

14

1 Jan 04 = 100

Performance and AuM of multi-asset funds by mandate type

Source: Nomura Quantitative strategy research 85

Performance by mandate type AuM by mandate type

80

85

90

95

100

105

110

Jan-

04

Jan-

05

Jan-

06

Jan-

07

Jan-

08

Jan-

09

Jan-

10

Jan-

11

Jan-

12

Jan-

13

Jan-

14

1 Jan 04 = 100 Defensive Balanced

Flexible Lifetime

0

50

100

150

200

250

300

350

Jan-

05

Jan-

06

Jan-

07

Jan-

08

Jan-

09

Jan-

10

Jan-

11

Jan-

12

Jan-

13

Jan-

14

Defensive/Cautious Balanced Flexible Lifetime

Index


Passive used to mean tracking the cap-weighted index. This definition is now changing to include alternative/smart beta and other factor strategies. We think that a few criteria are desired for such strategies though:

• generate smooth outperformance over time;

• have no discretionary input;

• not concentrated in terms of individual stock positions;

• implementable in large size; and

• do not require heavy transactions costs

We are seeing this in practice with:

•in Japan the GPIF buying a quality-biased index; and

•the UK government proposing that the 89 local authority pension schemes sell all their actively managed fund positions and go fully passive, but the latter can include non market cap weighting.

This is also extending into alternatives – eg the adoption of risk premia strategies by Scandinavian pension funds.

87


88

Types of alternative beta

Cross Asset Class Intra Asset Class

Static Nomura Cross Asset Model ‘Global Quantitative Monthly – May 2013

issues’, 9 May 2013 Natural Weighting

Dynamic Alternative Beta TAA Algorithmic Beta

‘When does “Quality” matter?’ Joseph J. Mezrich, 23 July 2013

Usually Long-short Usually Long-only


Alternative beta, ɔːlˈtɜːnətɪv / ˈbiːtə, noun

1. A financial market investment strategy previously thought of as being ‘active’, but now more freely available especially when pre-packaged, eg, in ETF or swap format.

2. A non-traditional benchmark (eg, as opposed to market cap weighting), specifically that outperforms traditional benchmarks by already incorporating characteristics that are generally agreed to add value in the long term.

Investor confidence and alternative beta preferences

89

Risk model confidence

1/σ [min var, risk parity, max diversification ]

Low High

High

Concentrated Max Sharpe ratio

1/N

Low

Ret

urn

mod

el c

onfid

ence


90

An alternative beta taxonomy

Max diversification

Risk parity

Risk Confidence

Min Var Cap weight index

Here one screens

Here one weights 1/N Diversity weighting

Ret

urn

conf

iden

ce


91

Natural weighting

1/ Variance

Volume

Free Cash Flow

& Earnings

ROE

Risk

Tradability

Value

Quality


Why natural indexation is different from the competition:

• It uses a range of variables to try to determine the natural weight of a stock in the index.

• The approach is anchored in mean-reversion which is a powerful long-term tool, and measures this with valuation, but this is offset with quality and risk measures. Meanwhile, the volume input ensures that the strategy is tradable in size and is geared towards large companies.

• The approach smoothly outperforms the cap weighted index, but without the extended periods of underperformance associated with approaches that are essentially mono-factor such as minimum variance and fundamental indexation.

• There is a clear rationale for why this focused approach should work.

92

Natural weighting

Performance of natural indexation and its peers


70

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100

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120

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140

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160

170

Jun-95 Jun-97 Jun-99 Jun-01 Jun-03 Jun-05 Jun-07 Jun-09 Jun-11 Jun-13

June 1995 = 100 Natural Index (1000 stocks) Minimum Variance (240 stocks)

Fundamental Index (1000 stocks)

94

Performance of components (1,000 stocks)


60

110

160

210

260

310

Jun-95 Jun-97 Jun-99 Jun-01 Jun-03 Jun-05 Jun-07 Jun-09 Jun-11 Jun-13

Jun 95 = 100

Index Risk Parity

Volume Value

FCF Earnings

ROE

95

Natural weighting

Performance statistics Natural Index (1000 stocks)

Minimum Variance

(240 stocks)

Fundamental Index (1000 stocks)

Absolute performance

Returns 10.5 8.2 10.0

Volatility 15.3 11.1 16.3

Return/Risk 0.7 0.7 0.6

Relative performance

Returns 2.6 -0.5 2.2

Volatility 2.5 9.2 4.6

Return/Risk 1.0 -0.1 0.5

Performance statistics for natural indexation and its peers


Cross-asset alternative beta/risk premia investing

Income

Value

Quality

Momentum

Carry

Value

Momentum

Carry

Value

Momentum

Cross-asset alternative beta

Equity Strategies Credit Strategies Rates Strategies

Weighting scheme: Equal Risk parity Minimum variance Max diversification Equal risk contribution IR-based


Performance of alternative beta portfolio combinations

Chart shows the performance of different portfolio combinations applied to cross-asset alternative betas. Strategies are rebalanced annually. Source: Nomura Quantitative strategy 98

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-92

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93

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-93

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-94

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95

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-95

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-96

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-12

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13

Dec

-13

Jun-

14

Dec 92 =100

Equally Weighted Performance Sharpe ratio Performance Risk Parity Performance ERC Performance MinVar Performance MaxDiv Performance

Performance statistics for alternative beta portfolio combinations

Sample run December 1992-April 2013. Source: Nomura Quantitative strategy 99

Stats Risk

Parity Minimum Variance ERC

Sharpe Ratio

Max Diversification

Equally weighted

Return 1.77% 1.66% 1.77% 1.40% 1.78% 2.62%

Vol 1.28% 1.33% 1.28% 1.43% 1.36% 1.87%

Return/risk 1.38 1.25 1.38 0.98 1.31 1.40

Max drawdown (%) -2.9% -2.5% -2.3% -2.5% -2.1% -3.3%

The benefits of a cross-asset approach to alternative beta portfolio construction

Figure shows return statistics for combinations of alternative betas within fixed income, within equities and across both asset classes. Bottom row shows the uplift in the return/risk ratio that results in moving from a single asset to multi-asset approach. R/R is return/risk ratio and MDD is max drawdown. Sample run December 1992-April 2013. Source: Nomura Quantitative strategy 100

Model \ Strategy Risk Parity

Minimum Variance ERC

Sharpe Ratio

Max Diversification

Equally weighted

Equity

return 4.35% 2.38% 3.36% 2.34% 2.88% 4.30% vol 4.21% 4.27% 3.96% 5.36% 4.10% 4.29% R/R 1.03 0.56 0.85 0.44 0.70 1.00 MDD (%) -12.64% -16.52% -15.48% -18.55% -12.80% -10.15%

Fixed Income

return 1.36% 1.49% 1.48% 1.30% 1.56% 1.43% vol 1.34% 1.37% 1.35% 1.41% 1.40% 1.36% R/R 1.02 1.09 1.10 0.92 1.12 1.05 MDD (%) -3.23% -2.98% -2.84% -3.48% -2.69% -2.90%

Cross asset

return 1.77% 1.66% 1.77% 1.40% 1.78% 2.62% vol 1.28% 1.33% 1.28% 1.43% 1.36% 1.87% R/R 1.38 1.25 1.38 0.98 1.31 1.40 MDD (%) -2.95% -2.47% -2.31% -2.46% -2.13% -3.31%

Uplift in return/risk

EQUITY 34% 124% 63% 124% 87% 39% FIC 36% 15% 26% 6% 17% 32%


Correlation of alternative beta strategies

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

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6

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-06

Jan-

07

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07

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7

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8

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9

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Apr-

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1

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-11

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-12

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-13

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4

Correlation coefficient

Average correlation (75days)


Equity alternative beta/risk premia

•a long-short risk premium strategy; •offered to those who want a more transparent approach instead of usual ‘alternatives’; and •we also have a version where this is combined with credit and rates strategies to form a cross-asset risk premium strategy.

Aim

Methodology

Our alternative beta strategy holds the following separate ‘betas’ with static weights:

• Income - Dividend yield + Net buy-back yield. • Value - Price to book. • Quality - Return on equity. • Momentum - Composite of Earnings and Price momentum.

The strategies are all applied to a global large-cap universe with a long-short construction. We then combine these with a risk-parity weighting to form the final strategy.


Performance

Return statistics

Equity alternative beta/risk premia


volatility Annualised monthly IR 1 yr 2.9 1.7 1.7

3 yr 2.9 3.0 1.0

5 yr 2.7 2.6 1.0

Whole Period 4.3 4.2 1.0

70 90

110 130 150 170 190 210 230 250 270

Dec-92 Dec-94 Dec-96 Dec-98 Dec-00 Dec-02 Dec-04 Dec-06 Dec-08 Dec-10 Dec-12

Risk Parity

Cross sectional & time series

104

Momentum Income or carry

Value or mean reversion

95 97 99 101 103 105 107 109 111 113 115

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Index Index Cross-sectional momentum (LHS) Time series momentum (RHS)

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Index Index

Cross-sectional dividend yield (LHS)

Time series carry (RHS)

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250


Index Index Cross-sectional price/book (LHS)

Time series mean-reversion (RHS)


105

Diversification benefit of time series and cross-sectional factors

Value/Mean-reversion Carry/Income Momentum

Cross-

Sectional Time Series Risk Parity

Combination Cross-


Combination Cross-


Combination

Return 1.6% 0.4% 2.2% 5.3% 0.4% 4.4% 1.9% 0.5% 3.8%

Vol 12.0% 1.8% 9.2% 15.8% 2.0% 11.8% 15.7% 1.4% 12.8%

R/R 0.14 0.23 0.24 0.34 0.22 0.37 0.12 0.38 0.30

The table shows the return/risk of the cross-sectional factors defined as the top-bottom quartile portfolio from the Top 500 stocks FTSE World and the times series factors defined at the index level. The Risk Parity portfolio is the risk weighted portfolio of the cross-sectional series with the volatility leveraged times series. The data are calculated using monthly returns from Dec-89. Source: Nomura Quantitative strategy

Characteristic Futures ETFs Stocks Swaps Certificates

Classification Exchange listed derivative contracts (un-funded)

Exchange Traded Fund UCITs compliant for European listings (funded)

Physical Holding of Stock Basket / (funded)

OTC Derivative (un-funded)

Notes (funded)

Fees Commission paid per contract. eg, 1 EUR per lot (minimal cost for index such as SX5E)

Management fee paid to ETF issuer Broker Commission

Broker Commission Borrow fee for shorts positions

Financing Spread over Libor Broker Commission

Management fee and/or Broker Commission

Liquidity Some contracts are very liquid on exchange, otherwise determined by cash market liquidity

Primary: Determined by underlying liquidity Secondary: On exchange trading with market makers

Depending on underlying Borrow cost for short positions



Counterparty Risk None. Client faces the exchange and only posts small initial margin to their clearer

•Physical ETFs: Counterparty risk owing to stock lending • Synthetic ETFs: The fund enters into a swap with credit institution (s) which are fully collateralized

None Client faces the swap counterparty and has risk to the relevant institution (which will be collateralized)

Client buys funded note from the counterparty with full counterparty risk in case of default

Customize to get exposure to theme

No Ask ETF provider to create ETF - due diligence process required

Yes Yes Yes

Ongoing management / operational effort

Requires cash management Rolling futures Daily margining

Custodian will take care of day-to-day management Accounting is relatively simple

Custodian will take care of day-to-day management

Requires cash management Collateral management needed on both sides

Custodian will take care of day-to-day management

Market Making On screen with anonymous counterparty during opening times of the exchange Off screen with counterparty

On screen with anonymous counterparty during opening times of the exchange Directly with market maker OTC

On Exchange Trading with initial counterparty, but can be economically closed out with third counterparty at any time

Trading only with initial counterparty

Leverage Yes In general no (only a small number of ETFs give leverage)

No Yes Yes

Shorting Yes L-S ETFs are possible , though short ing ETFs can be hard in individual cases of poor liquidity

Yes Yes Yes

Possible implementation channels for alternative beta


EM country selection

Signal 1 – Valuations performance of forward P/E selection strategy relative to the benchmark

Signal 2 – Earnings performance of earn rev strategy relative to the benchmark

Signal 3 – Sentiment performance of fund flows momentum strategy relative to the benchmark

Signal 4 – Growth performance of yield curve steepening strategy relative to the benchmark

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108

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107

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July 00 =100 July 00 =100

Excess Returns 0.5%

Tracking Error 0.9%

Info Ratio 0.5

% outperformance 55%

Excess Returns 0.4%

Tracking Error 0.9%

Info Ratio 0.5


Excess Returns 0.3%

Tracking Error 1.1%

Info Ratio 0.3


Excess Returns 0.4% Tracking Error 0.9% Info Ratio 0.4 % outperformance 44%


Signal 5 – Risk: Performance of CDS 12-month change Strategy Relative to the Benchmark

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107

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-08

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-09

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-10

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-11

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-12

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-14

July 00 =100

Excess Returns 0.4%

Tracking Error 1.0%

Info Ratio 0.4


108

Model recommendations for August 2014

The model recommendations for overweighting and underweighting the regions given above are based on a limit of 15% total deviation from the benchmark weight for the overweights and underweights. Source: Nomura Strategy research

% overweight/underweight recommendations relative to benchmark

Performance of EM country selection model relative to the benchmark

Chart shows the performance of the strategy derived by ranking countries as under/over weight based on variables that capture relative valuations, earnings, sentiment, growth and risk. We also impose a limit of 15% total deviation from the benchmark weight for the overweights and underweights. Source: FTSE, Datastream, EPFR, Worldscope, IBES, Factset, Bloomberg, Nomura strategy research 109

India 4.56% Taiwan 3.51% Turkey 2.96% China 1.75% Chile 1.16% Brazil 1.07% Czech Rep Neutral Hungary Neutral Indonesia Neutral Malaysia Neutral Philippines Neutral Thailand Neutral Mexico -1.05% Korea -1.36% Poland -1.73% Russia -2.29% South Africa -4.20% Israel -4.37% 100

105

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115

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125

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135

2000 2002 2004 2006 2008 2010 2012 2014

Excess Returns 2.0%

Tracking Error 2.1% Info Ratio 0.96


Custom product services, website, Bloomberg access to models, data and Recommended Portfolio

European Recommended Portfolio

111


Price (LC) Mkt Cap Calendarised EPS y/e Dec1Price/

earnings DateRel Perf.

sinceRel Perf.

Over Analyst Sector Stock Currency 4 Sep 14 US$m 2014e 2015e 2016e Dec 15 (x) Added Added week Rating2

Basic Industries BHP BILLITON GBP 19.05 65,975 2.4 2.7 2.8 7.1 28 Jan 14 -12 1 BuyCRH PLC EUR 18.58 17,812 0.8 1.1 1.4 16.6 31 Aug 12 3 1 Not RatedHEIDELBERGCEMENT EUR 58.36 10,641 3.9 4.9 6.0 11.8 26 Nov 13 -5 -1 Not RatedRIO TINTO GBP 32.42 66,315 5.3 5.7 6.2 5.7 28 Jan 14 -2 -1 BuySYNGENTA CHF 326.10 32,156 17.8 18.3 22.2 17.8 19 May 14 -8 -4 Buy

Capital Goods ABB SEK 163.50 53,615 1.3 1.5 1.7 107.0 6 Feb 13 -8 1 BuyPHILIPS EUR 23.65 28,008 1.3 1.3 1.8 17.5 5 Nov 12 -8 -1 BuySCHNEIDER ELECTRIC EUR 65.50 46,363 3.4 3.6 4.0 18.0 26 Nov 13 -2 -1 NeutralSIEMENS AG EUR 98.59 101,338 5.6 7.3 8.2 13.5 14 Oct 11 -9 1 BuySKF SEK 164.00 9,660 2.0 10.9 12.5 15.1 26 Nov 13 -18 -1 Neutral

Consumer Cyclicals A.P MOELLER-MAERSK DKK 14620.00 17,115 909.6 866.4 1072.1 16.9 19 May 14 8 0 BuyBMW EUR 91.54 38,585 8.1 8.3 8.5 11.1 27 Nov 12 12 0 BuyDEUTSCHE LUFTHANSA EUR 13.60 4,037 0.7 1.1 2.5 12.4 26 Nov 13 -21 -1 NeutralDEUTSCHE POST EUR 25.68 31,657 1.7 1.7 1.8 14.7 26 Nov 13 -11 0 BuyDSV DKK 174.70 5,215 8.9 8.9 11.4 19.7 26 Nov 13 -2 -2 BuyKERING EUR 165.40 15,812 9.8 9.7 10.7 17.1 16 Jun 14 1 1 BuyLVMH EUR 137.60 44,683 7.1 7.1 7.9 19.3 16 Jun 14 -7 2 BuyRANDSTAD HOLDING EUR 37.73 5,278 2.6 3.1 3.6 12.0 19 May 14 -9 1 Not Rated

Consumer Staples HENKEL EUR 81.95 18,441 3.7 4.1 4.7 20.0 2 Jul 14 -6 0 BuyWM MORRISON GBP 1.74 6,168 -0.1 0.1 0.2 13.5 2 Jul 14 -4 -9 BuyRECKITT BENCKISER GBP 53.65 56,753 2.6 2.7 2.9 19.7 2 Jul 14 6 1 BuyTESCO GBP 2.29 30,229 0.2 0.2 0.2 10.4 2 Jul 14 -20 -9 Neutral

Energy BG GROUP PLC GBP 12.33 68,809 0.6 1.1 1.2 10.8 27 Nov 12 -6 1 NeutralGALP ENERGIA EUR 13.66 6,691 0.4 0.5 0.6 27.5 27 Nov 12 -12 0 BuyTOTAL EUR 51.77 136,362 6.1 6.6 6.7 7.9 18 Jul 13 17 2 Buy

Financials - Banks BANCO SANTANDER EUR 7.89 120,347 0.5 0.6 0.7 13.3 18 Oct 13 10 2 NeutralBARCLAYS PLC GBP 2.31 62,034 0.2 0.3 0.3 8.5 4 Nov 11 0 1 BuyBNP PARIBAS EUR 54.30 68,761 5.0 5.5 6.3 10.0 16 Apr 10 -33 3 NeutralCREDIT SUISSE CHF 26.32 45,155 1.8 2.8 3.2 9.3 8 Apr 13 -12 0 BuyDANSKE BANK DKK 162.00 22,198 12.9 15.0 16.5 10.8 1 Apr 14 0 -1 BuyDEUTSCHE BANK EUR 27.00 48,288 2.3 3.3 4.1 8.2 1 May 13 -37 1 NeutralPKO BANK PLN 40.01 10,672 2.7 3.2 3.7 12.6 30 Aug 13 -9 2 Not RatedSOCIETE GENERALE EUR 41.00 37,949 3.9 4.8 5.4 8.6 5 Nov 12 37 4 BuyUNICREDITO ITALIANO EUR 6.40 36,950 0.3 0.5 0.7 12.6 16 Apr 10 -103 6 Buy

Financials - Insurance AVIVA PLC GBP 5.34 25,764 0.4 0.5 0.5 11.7 31 Jul 09 38 1 BuyAXA EUR 19.55 48,088 1.8 2.0 2.1 10.0 9 Jan 09 -33 2 BuyPRUDENTIAL PLC GBP 14.55 60,879 0.5 1.0 1.1 14.9 18 Jul 13 23 -1 Buy

Financials - Other BLACKROCK USD 331.73 41,504 19.2 21.5 24.7 15.5 18 Jul 13 4 0 Not RatedSCHRODERS PLC GBP 24.55 4,549 1.5 1.7 1.9 14.0 12 Dec 13 -5 0 Not Rated

Healthcare MERCK KGAA EUR 66.93 11,211 4.6 4.9 5.1 13.8 4 Sep 09 60 -1 Not RatedNOVARTIS CHF 87.10 218,015 5.3 5.8 6.2 14.9 26 Nov 13 16 4 Not RatedSANOFI EUR 85.75 127,261 5.2 5.7 6.3 14.9 26 Nov 13 2 2 Not Rated

Media PUBLICIS EUR 58.31 13,927 3.5 3.4 3.6 17.3 27 Nov 12 5 0 NeutralTechnology ALCATEL-LUCENT EUR 2.66 9,441 0.0 0.2 0.3 16.8 26 Nov 13 -24 0 Buy

INFINEON TECHNOLOGIES EUR 8.99 13,073 0.5 0.6 0.6 14.4 27 Nov 12 23 -1 Not RatedSAP AG EUR 59.99 69,525 3.4 3.7 4.1 16.2 23 Oct 09 24 -1 BuyARM HOLDINGS GBP 9.66 - - - - - 09-Sep-14 N/A N/A Not Rated

Telecoms BT GROUP GBP 3.90 50,354 0.2 0.3 0.3 14.9 13 Apr 12 55 -1 Buy

Portfolio perf. (Euro Return, %)3 1 WK 1 MTH YTD 12 MTH 2013 2012 2011 2010 2009 2008 4 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995Nomura Strategy Recommend Portfolio 2.9 6.2 4.0 25.4 29.3 26.2 -16.6 5.3 49.4 -20.7 -4.5 20.9 21.7 7.7 22.5 -34.0 -21.2 14.7 67.4 26.4 43.2 35.7 17.8FTSE-World Europe Index 2.3 5.6 9.4 23.5 20.0 18.8 -8.5 11.7 33.2 -20.4 3.6 17.2 23.0 9.4 12.6 -31.7 -17.3 -2.9 25.4 18.6 40.5 24.7 11.2

1 EPS estimates are based on Nomura estimates (for stocks under coverage), IBES (for stocks not currently under coverage)2 Analyst rating refers to Nomura research department rating3 Return history presented as price return in euro terms from before 2006. Returns from 2007 to present are on a total return basis.4 Ending 12 September 2008

Please turn to the back for an explanation of Nomura's rating system.Past performance is not a guarantee of future results.

We are adding ARM Holdings PLC (GBP 9.66, Not Rated) to our European recommended portfolio.

European Recommended Portfolio relative performance index

Performance of Nomura European strategy recommended portfolio relative to the FTSE World Europe index. Source: Nomura Strategy research 112

80

85

90

95

100

105

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115

Dec-06 Dec-07 Dec-08 Dec-09 Dec-10 Dec-11 Dec-12 Dec-13

Dec 06 = 100


StrategyInsight https://apps.nomuranow.com/EQS

113

114

1Ratios reflect Earnings Before Goodwill Amortisation 2Financials excluding Real Estate 3Asia ex Japan = Australia, Hong Kong, New Zealand & Singapore Source: Worldscope, FTSE, I/B/E/S, Nomura Strategy research

Global valuation and profitability

12 month Forward PE1

Current Values Post 1990 Average

US Eur ex UK UK Japan Asia ex Jp3 Emerging World US Eur ex UK UK Japan Asia ex Jp3 Emerging WorldEnergy 14.0 11.2 10.4 10.5 15.3 7.3 13.0 Energy 15.3 12.4 13.6 30.0 14.3 13.8 14.4Materials 16.6 15.3 11.7 13.4 13.2 12.3 14.8 Materials 15.1 12.5 11.6 9.0 12.9 10.7 14.5Industrials 15.9 14.8 14.9 13.4 15.7 13.8 15.2 Industrials 15.8 13.0 11.6 28.8 15.4 13.3 16.3Consumer Discretionary 17.3 13.0 15.1 12.2 15.6 11.9 14.9 Consumer Discretionary 17.5 14.7 14.3 48.0 17.5 11.5 17.4Consumer Staples 17.3 18.6 16.5 19.3 17.2 21.0 17.7 Consumer Staples 14.7 16.6 13.0 29.5 15.8 16.1 15.2Healthcare 16.4 17.5 17.1 25.1 20.8 15.9 16.9 Healthcare 17.5 17.5 16.7 23.5 20.6 14.4 17.8Financials2 13.7 11.3 11.3 12.9 13.9 8.8 12.7 Financials2 12.1 12.5 12.2 34.7 12.8 15.2 14.2Information Tech 14.8 18.2 26.9 17.1 17.3 12.1 14.5 Information Tech 20.2 21.1 20.5 29.9 16.7 16.3 20.8Telecom Services 13.4 15.6 20.2 15.0 16.3 14.8 15.1 Telecom Services 16.6 16.0 13.7 26.1 15.1 14.7 15.5Utilities 16.0 14.5 15.2 17.9 13.7 11.8 15.3 Utilities 13.2 13.9 10.2 27.2 13.6 13.2 13.8Market 15.4 14.2 13.3 14.2 14.5 10.9 14.6 Market 15.5 13.9 12.6 28.3 13.9 12.5 15.7

Enterprise Value / Sales


US Eur ex UK UK Japan Asia ex Jp3 Emerging World US Eur ex UK UK Japan Asia ex Jp3 Emerging WorldEnergy 1.6 0.8 0.7 0.3 1.9 0.8 1.2 Energy 1.3 1.0 1.1 0.5 2.5 1.1 1.1Materials 2.0 1.3 1.0 0.9 2.5 1.3 1.4 Materials 1.5 1.0 1.4 1.1 1.8 1.7 1.3Industrials 2.1 1.1 1.4 1.0 1.2 0.9 1.4 Industrials 1.8 0.8 0.9 0.8 1.5 1.2 1.1Consumer Discretionary 1.8 1.2 1.5 0.8 1.9 1.2 1.4 Consumer Discretionary 1.4 0.8 1.2 0.8 2.3 2.0 1.1Consumer Staples 1.4 1.5 1.9 0.9 0.8 1.5 1.4 Consumer Staples 1.7 1.1 1.3 0.7 0.9 1.6 1.3Healthcare 2.1 3.8 3.9 1.3 4.5 3.3 2.4 Healthcare 2.3 2.9 3.7 1.7 2.7 3.2 2.5Financials2,4 NA NA NA NA NA NA NA Financials2 NA NA NA NA NA NA NAInformation Tech 2.8 1.9 8.5 0.9 3.5 1.0 1.9 Information Tech 2.6 1.6 2.8 0.9 1.6 1.8 1.8Telecom Services 2.4 1.9 1.4 1.8 3.2 2.1 2.1 Telecom Services 2.9 2.4 2.7 1.7 4.1 4.6 2.4Utilities 2.9 1.0 1.6 1.4 3.2 2.0 1.7 Utilities 2.2 1.3 1.6 2.3 4.1 3.6 1.8Market ex Financials 2.0 1.4 1.3 0.9 1.7 1.2 1.6 Market ex Financials 1.8 1.1 1.3 0.9 1.9 1.8 1.3

Enterprise Value / EBITDA


US Eur ex UK UK Japan Asia ex Jp3 Emerging World US Eur ex UK UK Japan Asia ex Jp3 Emerging WorldEnergy 7.3 3.9 6.1 5.7 13.1 5.0 6.5 Energy 7.5 5.3 7.0 8.3 6.5 11.2 6.7Materials 9.8 9.3 7.1 7.2 7.3 8.2 8.6 Materials 8.4 6.1 6.9 9.7 7.6 10.2 7.7Industrials 11.9 9.2 8.7 8.7 10.0 10.8 10.4 Industrials 10.1 6.7 6.6 11.6 8.0 8.3 9.3Consumer Discretionary 10.8 8.0 10.4 7.1 11.8 7.9 9.2 Consumer Discretionary 9.2 6.2 8.6 8.4 13.8 10.5 8.3Consumer Staples 11.4 11.1 10.7 8.0 10.5 13.7 11.0 Consumer Staples 10.5 8.9 8.5 9.1 9.2 10.4 9.6Healthcare 12.7 13.6 10.3 10.6 18.3 14.4 12.7 Healthcare 12.5 10.8 11.3 9.3 13.3 12.5 11.8Financials2 NA NA NA NA NA NA NA Financials2 NA NA NA NA NA NA NAInformation Tech 10.4 11.7 11.8 7.2 17.8 5.8 8.9 Information Tech 12.1 10.6 14.2 8.1 11.5 10.3 10.7Telecom Services 6.5 5.7 4.8 5.9 8.9 6.2 6.1 Telecom Services 6.9 5.7 6.6 5.3 9.3 9.0 6.2Utilities 9.2 4.9 8.5 10.8 14.2 7.9 7.8 Utilities 7.4 6.0 6.3 11.0 11.5 9.3 7.4Market ex Financials 10.1 8.0 8.0 7.8 10.0 7.2 9.0 Market ex Financials 9.5 6.7 7.2 9.3 9.1 8.9 8.5

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1Ratios reflect Earnings Before Goodwill Amortisation 2Financials excluding Real Estate 3Asia ex Japan = Australia, Hong Kong, New Zealand & Singapore 4Return on Equity used for Financials. 5Price to Book Value used for Financials. 6ROE and RoCE calculated pre goodwill and pre exceptionals. Source: Worldscope, FTSE, I/B/E/S, Nomura Strategy research

Global valuation and profitability

1


US Eur ex UK UK Japan Asia ex Jp3 Emerging World US Eur ex UK UK Japan Asia ex Jp3 Emerging WorldEnergy 11.3 10.0 12.9 4.5 4.7 9.3 10.5 Energy 12.4 12.6 12.5 3.9 11.4 13.9 11.6Materials 9.2 7.0 7.0 3.9 9.3 4.5 6.8 Materials 9.0 8.8 10.8 4.2 11.3 9.0 7.9Industrials 8.4 9.3 15.6 5.3 6.9 4.3 7.6 Industrials 9.3 8.4 10.4 3.7 8.1 6.9 6.9Consumer Discretionary 11.7 7.9 14.4 5.8 11.4 10.6 9.3 Consumer Discretionary 8.1 7.8 11.2 4.4 8.4 8.4 7.0Consumer Staples 14.3 10.7 13.1 7.4 9.3 13.6 12.1 Consumer Staples 17.8 11.7 12.8 4.8 9.6 12.3 13.4Healthcare 14.7 15.1 21.5 8.4 16.8 12.3 14.7 Healthcare 17.7 13.2 28.2 7.7 11.3 12.9 16.2Financials2,4 10.6 7.6 7.2 10.3 11.0 14.9 9.8 Financials2,4 14.6 10.9 12.2 1.7 11.5 12.0 11.1Information Tech 19.4 8.8 13.9 6.1 10.4 13.0 15.5 Information Tech 14.2 11.4 12.8 4.1 13.1 10.8 10.1Telecom Services 7.5 9.6 19.4 7.2 15.9 12.4 11.2 Telecom Services 9.3 9.7 10.4 6.8 19.1 12.6 9.2Utilities 5.9 5.8 9.7 0.4 8.3 5.5 5.2 Utilities 7.5 7.8 8.3 3.3 14.9 5.6 6.7Market ex Financials 11.5 9.1 13.8 5.1 8.3 8.5 9.8 Market ex Financials 10.9 9.4 11.2 4.1 9.6 9.3 8.8

Enterprise Value / Capital Employed (P/BV Financials)


US Eur ex UK UK Japan Asia ex Jp3 Emerging World US Eur ex UK UK Japan Asia ex Jp3 Emerging WorldEnergy 1.7 1.1 1.2 0.7 1.3 0.8 1.5 Energy 2.1 1.6 1.9 0.9 1.5 1.8 1.8Materials 2.1 1.5 1.3 0.9 1.6 1.0 1.4 Materials 1.7 1.3 1.5 1.2 1.7 1.2 1.4Industrials 1.9 1.7 2.5 1.0 1.1 0.9 1.5 Industrials 1.7 1.3 1.4 1.1 1.1 1.1 1.4Consumer Discretionary 2.4 1.4 2.4 1.0 2.0 1.3 1.7 Consumer Discretionary 1.8 1.2 1.9 1.1 1.7 1.3 1.4Consumer Staples 2.9 2.1 2.6 1.4 1.7 2.3 2.4 Consumer Staples 3.4 2.1 1.9 1.3 1.6 2.0 2.4Healthcare 2.6 3.0 3.7 1.5 4.3 2.2 2.7 Healthcare 3.4 2.5 5.5 1.7 2.4 2.2 3.1Financials2,5 1.4 1.0 1.2 1.0 1.5 1.4 1.3 Financials2,5 2.0 1.7 1.7 2.0 1.5 2.1 1.8Information Tech 2.9 2.3 6.2 1.2 2.8 1.5 2.2 Information Tech 3.3 2.6 4.9 1.2 2.1 2.0 2.5Telecom Services 1.9 1.2 0.7 1.3 2.4 1.8 1.4 Telecom Services 1.8 1.4 1.4 1.4 3.2 2.3 1.5Utilities 1.3 0.9 1.7 0.9 1.5 1.0 1.1 Utilities 1.2 1.2 1.1 1.2 2.1 1.2 1.2Market ex Financials 2.2 1.6 1.6 1.1 1.4 1.2 1.7 Market ex Financials 2.1 1.5 1.6 1.2 1.5 1.4 1.6

Return on Capital Employed6 (ROE6 Financials)

Any Authors named on this report are Research Analysts unless otherwise indicated Analyst Certification We, Inigo Fraser-Jenkins and Alla Harmsworth, hereby certify (1) that the views expressed in this Research report accurately reflect our personal views about any or all of the subject securities or issuers referred to in this Research report, (2) no part of our compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this Research report and (3) no part of our compensation is tied to any specific investment banking transactions performed by Nomura Securities International, Inc., Nomura International plc or any other Nomura Group company. Important Disclosures Online availability of research and conflict-of-interest disclosures Nomura research is available on www.nomuranow.com/research, Bloomberg, Capital IQ, Factset, MarkitHub, Reuters and ThomsonOne. 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Explanation of Nomura's equity research rating system in Europe, Middle East and Africa, US and Latin America, and Japan and Asia ex-Japan from 21 October 2013 The rating system is a relative system, indicating expected performance against a specific benchmark identified for each individual stock, subject to limited management discretion. An analyst’s target price is an assessment of the current intrinsic fair value of the stock based on an appropriate valuation methodology determined by the analyst. Valuation methodologies include, but are not limited to, discounted cash flow analysis, expected return on equity and multiple analysis. Analysts may also indicate expected absolute upside/downside relative to the stated target price, defined as (target price - current price)/current price. STOCKS A rating of 'Buy', indicates that the analyst expects the stock to outperform the Benchmark over the next 12 months. A rating of 'Neutral', indicates that the analyst expects the stock to perform in line with the Benchmark over the next 12 months. A rating of 'Reduce', indicates that the analyst expects the stock to underperform the Benchmark over the next 12 months. A rating of 'Suspended', indicates that the rating, target price and estimates have been suspended temporarily to comply with applicable regulations and/or firm policies. Securities and/or companies that are labelled as 'Not rated' or shown as 'No rating' are not in regular research coverage. Investors should not expect continuing or additional information from Nomura relating to such securities and/or companies. Benchmarks are as follows: United States/Europe/Asia ex-Japan: please see valuation methodologies for explanations of relevant benchmarks for stocks, which can be accessed at: http://go.nomuranow.com/research/globalresearchportal/pages/disclosures/disclosures.aspx; Global Emerging Markets (ex-Asia): MSCI Emerging Markets ex-Asia, unless otherwise stated in the valuation methodology; Japan: Russell/Nomura Large Cap.

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Appendix A-1

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SECTORS A 'Bullish' stance, indicates that the analyst expects the sector to outperform the Benchmark during the next 12 months. A 'Neutral' stance, indicates that the analyst expects the sector to perform in line with the Benchmark during the next 12 months. A 'Bearish' stance, indicates that the analyst expects the sector to underperform the Benchmark during the next 12 months. Sectors that are labelled as 'Not rated' or shown as 'N/A' are not assigned ratings. Benchmarks are as follows: United States: S&P 500; Europe: Dow Jones STOXX 600; Global Emerging Markets (ex-Asia): MSCI Emerging Markets ex-Asia. Japan/Asia ex-Japan: Sector ratings are not assigned.

Explanation of Nomura's equity research rating system in Japan and Asia ex-Japan prior to 21 October 2013 STOCKS Stock recommendations are based on absolute valuation upside (downside), which is defined as (Target Price - Current Price) / Current Price, subject to limited management discretion. In most cases, the Target Price will equal the analyst's 12-month intrinsic valuation of the stock, based on an appropriate valuation methodology such as discounted cash flow, multiple analysis, etc. A 'Buy' recommendation indicates that potential upside is 15% or more. A 'Neutral' recommendation indicates that potential upside is less than 15% or downside is less than 5%. A 'Reduce' recommendation indicates that potential downside is 5% or more. A rating of 'Suspended' indicates that the rating and target price have been suspended temporarily to comply with applicable regulations and/or firm policies in certain circumstances including when Nomura is acting in an advisory capacity in a merger or strategic transaction involving the subject company. Securities and/or companies that are labelled as 'Not rated' or shown as 'No rating' are not in regular research coverage of the Nomura entity identified in the top banner. Investors should not expect continuing or additional information from Nomura relating to such securities and/or companies.

SECTORS A 'Bullish' rating means most stocks in the sector have (or the weighted average recommendation of the stocks under coverage is) a positive absolute recommendation. A 'Neutral' rating means most stocks in the sector have (or the weighted average recommendation of the stocks under coverage is) a neutral absolute recommendation. A 'Bearish' rating means most stocks in the sector have (or the weighted average recommendation of the stocks under coverage is) a negative absolute recommendation.

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