Nomura Securities Co Ltd, TokyoJapan Equity Quants Research

Nomura Securities Co., Ltd.

Quant strategy after the earthquake in Japanearthquake in Japan

Hiromichi Tamura Head of Equity Quantitative Research, Japan

June 2011

Nomura Securities Co., Ltd, TokyoTel: +81-3-6703-1680E-mail: hiromichi.tamura@nomura.com June 2011

Please read the important disclosures and analyst certifications on pages 26–29. gl

@

SummarySummarySummarySummary1. In the year or so before March 2011, Japanese quant funds were generally doing well

in terms of performance. However, after the earthquake on March 11, this does not t b thseem to be the case.

2. One reason why quant fund performance had improved is that earnings sentiment recovered and the forecast E/P factor outperformed. However, we now need to be

f l b th diti h h d ft th th kcareful because these conditions have changed after the earthquake.

3. We think sentiment will be changing for some time. Therefore it is important to understand how factors behave in each sentiment phase. Here we introduce a

ti t b d f t t tsentiment-based factor strategy.

4. Moreover, we think it is possible to take advantage of the current difficulty in projecting earnings. We consider a method of estimating future revisions for stocks for hich the consens s earnings forecast has been left nchangedfor which the consensus earnings forecast has been left unchanged.

5. We also focus on the minimum variance portfolio, which is becoming popular within the pension community in Japan. This approach has actually underperformed since the earthquake In contrast the minimum downside risk portfolio which wethe earthquake. In contrast, the minimum downside risk portfolio, which we developed in 2010, has outperformed.

1

Japanese quant funds were coming back butJapanese quant funds were coming back butJapanese quant funds were coming back, but…Japanese quant funds were coming back, but…

We selected 23 Japanese mutual funds 80

100end-Jan 2001 =0% Quant fund： Cumulative return

E/P boom period E/Pslump period

E/P rehabilitation period

(Post-earthquake) p

that appear to use quantitative approaches, and calculated the average rate of return of these funds to emulate the performance of a typical quant fund

20

40

60 Quant fund average

the performance of a typical quant fund.

Japanese quant funds’ performance had been improving before March 2011, which is closely related to the

-20

0

2001

0120

0104

2001

0720

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0120

0204

2002

0720

0210

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0304

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0504

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0720

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0720

0610

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0704

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0904

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0720

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1004

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0720

1010

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1104

200

end-Jan 2001 =0% Earnings-based factor ： Cumulative return

E/P boom period E/P E/P rehabilitation which is closely related to the outperformance of the forecast E/P and revision factors.

However after the earthquake50

100

150

E/P

E/P boom periodslump period period

(Post-earthquake)

However, after the earthquake, the basic conditions for “Quant strategies” may be changing for the worse.-50

0

50

101

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107

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001

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104

Analyst-Revision

2

Note: Average performance of 23 publicly offered investment trusts that we regard as quant funds . For E/P and revision factors, figure shows the cumulative monthly factor return calculated. Sample period is from 1 Feb 2001 to May 2011.

Source: Nomura

2001

2001

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2011

What has changed?What has changed?What has changed?What has changed? Forecast dispersion has started to increase recently, which is not good for the

credibility of earnings forecasts.

Also, the basic conditions for earnings forecasts are getting worse. It is difficult to estimate the final impact of the earthquake on earnings. Some companies have chosen not to announce earnings guidance for the current

(%)E/P boom period E/P slump E/P rehabilitation

p g gfiscal year.

Ratio of companies not providing earnings guidance Dispersion of analyst earnings estimates (median value)

3.0%

15

20

25

30

08/11 collapse of Lehman Brothers

E/P boom period E/P slump period

E/P rehabilitation period (Post-

earthquake)

3.0%

18.1%

0

5

10

212

306

312

406

412

506

512

606

612

706

712

806

812

906

912

006

012

C ti t C ti t

2002

2003

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2010

3Note: Universe is TSE1-listed stocks covered by Nomura whose FY ends in March.Source: Nomura

Note: Exhibit shows range (median value) of analyst earnings estimates. Range of analyst earnings estimates is the standard deviation of IFIS or I/B/E/S (in that order of priority) recurring profit estimates for the following fiscal year, divided by the absolute value of the average of the earnings estimates, multiplied by 100. Universe is TOPIX 500.

Source: Nomura

Company estimateFY2011/03

(as of end of May 2010)

Company estimateFY2012/03

(as of end of May 2011)

SentimentSentiment based quant strategybased quant strategySentimentSentiment--based quant strategybased quant strategy

Although the fundamentals for quant investment in Japan have been Although the fundamentals for quant investment in Japan have been recovering, we need to be very careful about the current situation, which is likely to remain uncertain. We will likely receive either “good news” or “bad news” in the future related to: We will likely receive either good news or bad news in the future related to: Supply chain problems Nuclear plant accident (and Tokyo Electric Power problem) Electric power shortagesElectric power shortages Decline in consumer confidence Aftershocks

Sentiment-based quant strategy is recommended Sentiment-based quant strategy is recommended. Performance of quant factors is affected by investor sentiment and/or risk

tolerance. We should switch factors in light of investor sentiment or attitude toward risk We should switch factors in light of investor sentiment or attitude toward risk

tolerance.

4

Sentiment toward earnings estimatesSentiment toward earnings estimatesSentiment toward earnings estimatesSentiment toward earnings estimates

There is little doubt that investor Nomura Revision Index and Liquidity-based Information Quality (IQ)

sentiment toward analyst earnings estimates is important. Nomura Revision Index-20

0

20

40 Upward

ura r

evisio

nInd

ex

− Upward: good sentiment− Downward: bad sentiment

Liquidity-based Information Quality (IQ)-80

-60

-40

9950

1

9960

1

9970

1

9980

1

9990

1

0000

1

0010

1

0020

1

0030

1

0040

1

0050

1

0060

1

0070

1

0080

1

0090

1

0100

1

0110

1-3.0

2 5

Downward

High

Nomu

− Positive: less information asymmetry between investors and issuers

− Negative: information asymmetry reduces the credibility of earnings estimates

19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20-2.5

-2.0

-1.5

-1.0

-0 5 IQ (l

iquidi

ty)moving average y g

Our assumption: When sentiment is good, investors

focus on earnings-forecast-based

0.5

0.0

0.5

1.0

1.5

Marke

t g g

Low

factors.

Note: Market liquidity as shown in exhibit is the average (equal weighted basis) of the values of the liquidity indicator for each individual stock in the universe each month. For the liquidity of individual stocks, we calculated the log of the ILLIQ indicator (the monthly average of the absolute daily return on each stock divided by its trading value on the same day), on the basis of the definition set out in Amihud (2002). The higher the value of this indicator, the lower the liquidity. We regard it as a high IQ phase if the current value is lower than the 24-month historical average. Universe is TOPIX.

Source: Nomura 5

1995

01

1996

01

1997

01

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01

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01

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01

2001

01

2002

01

2003

01

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01

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01

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2007

01

2008

01

2009

01

2010

01

2011

01

Risk appetite / toleranceRisk appetite / toleranceRisk appetite / toleranceRisk appetite / tolerance

Especially after the financial crises, Change of Nikkei Volatility Index and level of ti l t di i

p y ,factor performances have been largely affected by investor risk appetite. Change of Nikkei Volatility Index

cross-sectional return dispersion

2

4

6

of V

I d

reve

rse)

g y− Decrease: investors are risk-taking− Increase: investors are risk-averse

Level of cross-sectional return 8

-6

-4

-2

0

Chan

ge o

(nor

mali

zed

and

dispersion− High level: investor will take risk afterwards− Low level: investor will not take risk

O ti

-8

1995

01

1996

01

1997

01

1998

01

1999

01

2000

01

2001

01

2002

01

2003

01

2004

01

2005

01

2006

01

2007

01

2008

01

2009

01

2010

01

2011

011 2 3 4

disp

ersio

n m

alize

d)

Our assumption: When investors are risk tolerant,

contrarian-type strategies work.-3 -2 -1 0

9501

9601

9701

9801

9901

0001

0101

0201

0301

0401

0501

0601

0701

0801

0901

1001

1101

Retu

rn d

(nor

m

Note: The return dispersion is cross-sectional standard deviation of monthly returns of TOPIX stocks. The change of Nikkei Volatility Index is calculated as the difference between monthly figure and three-month moving average of the index value. The Nikkei Volatility Index is a model-free type implied volatility index (similar to VIX).

Source: Nomura6

199

199

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201

“Earnings sentiment” and “risk appetite” indices“Earnings sentiment” and “risk appetite” indicesEarnings sentiment and risk appetite indicesEarnings sentiment and risk appetite indices

"Earnings sentiment" and "risk appetite" Indices

0 00.5 1.0 1.5 2.0

Good

ntim

ent

By combining two indicators, we constructed "earnings sentiment" and "risk appetite" indices.

3 0-2.5 -2.0 -1.5 -1.0 -0.5 0.0

Bad

Earn

ings

sen

Earnings sentiment− Nomura Revision Index + Information

Quality-3.0

1995

01

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01

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01

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01

1999

01

2000

01

2001

01

2002

01

2003

01

2004

01

2005

01

2006

01

2007

01

2008

01

2009

01

2010

01

2011

01

01 2 3 4

Risk taking

appe

tite

Risk appetite− (-1) x change of Nikkei Volatility Index +

return dispersion

-4 -3 -2 -1 0

9501

9601

9701

9801

9901

0001

0101

0201

0301

0401

0501

0601

0701

0801

0901

1001

1101

Risk averse

Risk

a

Note: The earnings sentiment measure is calculated as the average of normalized Nomura revision index and the liquidity-based IQ. The lQ is the deviation from the 24-month historical average. The risk appetite measure is calculated as the average of normalized change of Nikkei Volatility Index x(-1) and the return dispersion.

Source: Nomura7

199

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201

Factor behavior in each phaseFactor behavior in each phase (1)(1)Factor behavior in each phaseFactor behavior in each phase (1)(1) Factors perform differently in each phase.

Factor effectiveness by "earnings sentiment" phase and "risk appetite" phase

Earnings sentiment: positive Earnings sentiment: negative Risk taking Risk averse

94 months 42 months 66 months 70 months

Returnannualized

%

Standarddev iation

(ann.)

Return/Standarddev iation(% ann.)

RankReturn

annualized%

Standarddev iation

(ann.)

Return/Standarddev iation(% ann.)

RankReturn

annualized%

Standarddev iation

(ann.)

Return/Standarddev iation(% ann.)

RankReturn

annualized%

Standarddev iation

(ann.)

Return/Standarddev iation(% ann.)

Rank

Specific return - 11.35 6.58 1.72 3 15.46 10.00 1.55 4 16.74 9.02 1.86 3 8.73 6.26 1.40 2

Time normalized E/P + 14.25 6.43 2.22 1 0.41 7.18 0.06 14 14.93 7.79 1.92 2 5.31 5.67 0.94 8E/P + 14.75 6.83 2.16 2 2.93 9.50 0.31 11 16.00 9.07 1.76 4 6.48 6.34 1.02 7B/P + 15.39 10.08 1.53 4 25.53 9.71 2.63 1 23.22 11.98 1.94 1 14.09 7.60 1.85 1Volume momentum + 5.44 5.34 1.02 9 9.09 5.68 1.60 3 8.36 5.38 1.56 7 4.88 5.51 0.89 9Nomura RP Revision + 7 37 5 55 1 33 6 1 08 9 66 0 11 15 2 58 8 54 0 30 15 6 81 5 48 1 24 4Nomura RP Revision + 7.37 5.55 1.33 6 -1.08 9.66 -0.11 15 2.58 8.54 0.30 15 6.81 5.48 1.24 4Normalized accruals - 5.93 4.43 1.34 5 5.05 6.21 0.81 8 4.93 5.17 0.95 11 6.34 4.91 1.29 3Gap in TOPIX downsideβ- upsideβ + 8.09 6.97 1.16 7 12.08 6.83 1.77 2 12.67 8.11 1.56 6 6.16 5.49 1.12 5Quarterly surprise + 4.48 3.94 1.14 8 -0.92 7.07 -0.13 16 0.74 5.90 0.12 16 4.76 4.27 1.12 6Hedge fund　beta + 0.48 6.69 0.07 15 7.55 10.01 0.75 9 3.94 9.11 0.43 14 1.46 6.57 0.22 11Consensus rating-aligned - -2.62 7.10 -0.37 17 -6.06 10.90 -0.56 19 -6.80 9.64 -0.71 18 -0.75 7.06 -0.11 19Consensus rating-contrarian + 2.62 7.10 0.37 14 6.06 10.90 0.56 10 6.80 9.64 0.71 12 0.75 7.06 0.11 14Merton's default probability (#5-#1) + 8.64 11.48 0.75 11 3.89 16.55 0.24 13 14.71 14.97 0.98 10 0.06 11.01 0.01 15Merton's default probability (#1-#5) - -8.64 11.48 -0.75 19 -3.89 16.55 -0.24 17 -14.71 14.97 -0.98 19 -0.06 11.01 -0.01 18ROE + -3.55 8.41 -0.42 18 -14.93 8.58 -1.74 20 -6.60 10.38 -0.64 17 -7.50 6.50 -1.15 20Estimate Dispersion (#5-#1) + 6.11 6.51 0.94 10 2.51 8.81 0.28 12 10.28 7.19 1.43 8 0.02 7.11 0.00 16Estimate Dispersion (#1-#5) - -6.11 6.51 -0.94 20 -2.51 8.81 -0.28 18 -10.28 7.19 -1.43 20 -0.02 7.11 0.00 17ln(Market cap) - 6.78 10.46 0.65 12 14.29 10.19 1.40 5 17.32 10.76 1.61 5 1.34 9.57 0.14 12Skewness - 0.19 5.57 0.03 16 6.05 7.42 0.82 7 3.49 7.66 0.46 13 0.58 4.47 0.13 13MAX+MIN - 2.60 5.86 0.44 13 9.42 7.80 1.21 6 7.87 7.97 0.99 9 1.72 4.76 0.36 10

Note: The factor returns are calculated for each earnings sentiment and risk appetite measure. Each phase is determined by the sign of the measure. Symbols to right of each factor indicate direction of factor return, showing #5 - #1 if positive and #1 - #5 if negative.

Source: Nomura 8

Factor behavior in each phaseFactor behavior in each phase (2)(2)Factor behavior in each phaseFactor behavior in each phase (2)(2) Changes in IR are observed on both the x-axis (earnings sentiment) and

y-axis (risk appetite) for each factor.Factor behavior in each phase

Estimate Dispersion (#5-#1)

ln(Market cap)1.5 Phase 1: Risk takingPhase 2: Non-earnings factor

Risk taking

Specific return

Time normalized E/P

E/PVolume momentum

Gap in TOPIX downsideβ- upsideβ

Consensus rating-contrarian

Merton's default probability (#5-#1)

ROE

Skewness

MAX+MIN0.5

1.0

tite

g

B/P

Normalized accruals

downsideβ upsideβHedge fund beta

Consensus rating-aligned

Skewness

-0.5

0.0

Risk

appe

t

Nomura RP RevisionQuarterly surprise

aligned

Merton's default probability (#1-#5)

Estimate Dispersion (#1-#5)-1.5

-1.0

Phase 3: Risk avoidingPhase 4: Under-reaction to estimate

Risk averse

Source: Nomura

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

Earnings sentimentPhase 3: Risk avoiding

Bad Good

9

SentimentSentiment phasephase based factor strategy (1)based factor strategy (1)SentimentSentiment--phasephase--based factor strategy (1)based factor strategy (1)

ConceptConceptWe should switch factors in light of the situation in earnings sentiment and risk appetite.Basic strategy

B/P (20%), E/P (40%), estimate revision (40%)

First quadrant (risk taking, good earnings sentiment) Take risks on undervalued stocks in terms of earnings estimate

B/P (10%), E/P (30%), time-series normalized E/P (30%), revision (20%), dispersion (+; 10%)

Second quadrant (risk taking bad earnings sentiment)Second quadrant (risk taking, bad earnings sentiment) Focus on the non-earnings measure

B/P (40%), E/P (10%), revision (10%), downside beta (30%), logMKV (small; 10%)

Third quadrant (risk averse, bad earning sentiment) Risk averse strategy

B/P (50%), E/P (10%), revision (10%), dispersion (-; 10%), default prob. (small; 20%)

Fourth quadrant (risk averse, good earning sentiment) Utilize the under reaction to earnings news

10

Utilize the under-reaction to earnings newsB/P (15%), E/P (40%), revision (25%), quarterly surprise (20%)

SentimentSentiment phasephase based factor strategy (2)based factor strategy (2)SentimentSentiment--phasephase--based factor strategy (2)based factor strategy (2)

Performances of the basic and switching strategies

140

160

180(%)

switching strategy

it hi t t h 1 h 2 h 3 h 4

80

100

120

140

basic strategy

switching strategy phase 1 phase 2 phase 3 phase 4Average return (annualized % ) 13.67 20.39 17.54 11.70 7.67Standard deviation (annualized) 4.86 5.01 6.16 5.48 3.02Average return / Standard deviation (annualized % ) 2.81 4.07 2.85 2.13 2.54sample (months) 136 38 28 14 56

0

20

40

60basic stratey phase 1 phase 2 phase 3 phase 4

Average return (annualized % ) 10.05 17.57 4.62 8.30 8.10Standard deviation (annualized) 4.73 5.34 5.54 4.23 3.38Average return / Standard deviation (annualized % ) 2.13 3.29 0.83 1.96 2.39sample (months) 136 38 28 14 56

0

1999

12

2000

06

2000

12

2001

06

2001

12

2002

06

2002

12

2003

06

2003

12

2004

06

2004

12

2005

06

2005

12

2006

06

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12

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06

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12

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06

2008

12

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06

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12

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06

2010

12

Note: The switching strategy changes the factor mix in light of the value of the earnings sentiment and the risk appetite measure at the beginning of each month. The precise factor mix for each phase is described on page 10. This simulation is based on purely factor return, not the return of the portfolio. No costs are considered. Portfolio is rebalanced every month.

Source: Nomura11

Strategy taking advantage of uncertain earnings forecastStrategy taking advantage of uncertain earnings forecastStrategy taking advantage of uncertain earnings forecastStrategy taking advantage of uncertain earnings forecast

Some companies have chosen not to announce earnings guidance for the Some companies have chosen not to announce earnings guidance for the current fiscal year.

It is difficult to estimate the final impact on earnings.

Analysts also have difficulty in projecting earnings.

Therefore, it is possible that the number of the earnings revision signals will decline.dec e

We introduce a model of estimating the revision factor for stocks for which the consensus earnings forecast did not change during the preceding month. We break down each company’s sales into sales in each business segmentWe break down each company s sales into sales in each business segment, and estimate the revision factor for each segment. Then we add up all these segment revision factors, in line with the proportion of the company’s total sales accounted for by each segment.

12

sales accounted for by each segment.

Forecast revision signal by sales breakdown (1)Forecast revision signal by sales breakdown (1)Forecast revision signal by sales breakdown (1)Forecast revision signal by sales breakdown (1) The consensus forecast is now at the stage of “wait and see”. The percentage of stocks for which the consensus earnings forecast was

h d h i h l i th th k (l ft h t)unchanged has risen sharply since the earthquake. (left chart) The divergence of analyst forecasts has increased even more since the earthquake.

(right chart)Ratio of stocks with unchanged earnings forecasts Dispersion of consensus earnings forecasts at o o stoc s t u c a ged ea gs o ecasts

(12-month moving average)spe s o o co se sus ea gs o ecasts

(12-month moving average)

40%

45%Ratio of unchanged (FY1)

8%

9%

10%

30%

35%Ratio of unchanged (FY2)

3%

4%

5%

6%

7%

FY2

20%

25%

2003

12

2004

12

2005

12

2006

12

2007

12

2008

12

2009

12

2010

12

0%

1%

2%

2003

12

2004

12

2005

12

2006

12

2007

12

2008

12

2009

12

2010

12

FY2

Note: Universe is TSE-1 stocks for which I/B/E/S forecasts are available; sample period is December 2003 through 26 April 2011. We count the number of stocks for which, at the beginning of each month, the consensus earnings forecast had not been revised during the preceding month, and then calculate this as a proportion of the total number of stocks in the universe.

Source: Nomura

Note: Universe is TSE-1 stocks for which I/B/E/S forecasts are available; sample period is December 2003 through 26 April 2011. For each stock, we calculated the divergence of I/B/E/S recurring profit forecasts at the beginning of each month, on the basis of the gap between the most bullish analyst forecast and the most bearish analyst forecast.

Source: Nomura13

Forecast revision signal by sales breakdown (2)Forecast revision signal by sales breakdown (2)Forecast revision signal by sales breakdown (2)Forecast revision signal by sales breakdown (2) If the earnings forecast is unchanged, estimate the revision by adding up all segment

revision factors, in line with the proportion of the company’s total sales accounted for by each segment based on the method set out in Lou and Cohen (2011)by each segment, based on the method set out in Lou and Cohen (2011).

Step 2: Calculate segment revision factors Step 3: Calculate aggregate revision factorTarget: Unchanged consensus earnings

Step 1: Estimate business portfolio

average revision for specialist system support companies

companies Seg_Rev1

17%

6%

Business portfolio of company A

System support Services

w1

w2Pharmaceuticals_ 1 = 11

1=1

= _4=1

average revision for specialist pharmaceutical companies

Seg_Rev223%

17%

w3Fine chemicalsprocessed resins _ 2 = 12

2=1

Aggregate revision factor,weighted in line with each segment’s salesweighting

average revision for specialist fine chemical companies

Seg_Rev3

i i f i li t

54%

w4

Synthetic fibres _ 3 = 133

=1

average revision for specialist synthetic fiber companies

Seg_Rev4

Source: Nomura 14_ 4 = 14

4=1

Forecast revision signal by sales breakdown (3)Forecast revision signal by sales breakdown (3)Forecast revision signal by sales breakdown (3)Forecast revision signal by sales breakdown (3)

Conditions of simulationUniverse Stocks in TSE-1 with no change to consensus earnings forecast over preceding monthSample period 01/6 - 11/4/26Method Grouping simulation

Universe is divided into five groups on the basis of the historical one-month aggregate revision factor (AggREV) for the past month for each stock at the beginning of the month, and measure the monthly performance of each group.p g g , y p g p

Weighting EqualRebalancing MonthlyBenchmark Universe (equal weighted)factor Historical one-month aggregaterevision factor (AggREV)

#5

#4

Large

#3

#2

aggregated revision

#1Small

Source: Nomura15

Forecast revision signal by sales breakdown (4)Forecast revision signal by sales breakdown (4)Forecast revision signal by sales breakdown (4)Forecast revision signal by sales breakdown (4) Backtesting confirms the predictive power of the aggregate revision factor with respect

to future returns on stocks for which the consensus earnings forecast has not changed.

80

100End of Jun. 2001 = 0%

Cumulative return (#5-#1)

40

50End of Jun.2001 = 0%

#5

Cumulative excess return for each group

20

40

60

0

10

20

30

#4

#3

-20

0

20

106

206

306

406

506

606

706

806

906

006

-40

-30

-20

-10

0106

0206

0306

0406

0506

0606

0706

0806

0906

1006

#3

#2#1

200

200

200

200 4

200

200

200

200 8

2009

2010

200

200

200

200

200

200

200

200

200

201

period average std dev ave/std

From July 2001 to April 2011 6.75 6.36 3.33 *** 1.06

t stat#1 #2 #3 #4 #5

average -2.37 -1.74 -0.96 0.74 4.33std dev 3.92 3.58 3.39 3.50 3.80t stat -1.91 *** -1.53 -0.89 0.67 3.59 ***

16

Note: Universe is stocks in TSE-1 for which, at each point in time, there was no change to the consensus forecast over the preceding month. Sample period is June 2001 through 26 April 2011. At the beginning of each month, we divide the universe into five groups on the basis of the level of the aggregate revision factor for each stock, and then construct five equally weighted portfolios, one for each group. Figure shows statistical data for cumulative return (top) and monthly return (bottom) if each portfolio is held for one month. t-values are for the null hypothesis in which the average monthly return is zero. *** indicates significance of 1%, ** indicates significance of 5%, and * indicates significance of 10%.

Source: Nomura

From January 2008 to April 2011 6.60 6.11 3.39 *** 1.081.91 1.53 0.89 0.67 3.59

ave/std -0.61 -0.49 -0.28 0.21 1.14

Minimum variance portfolioMinimum variance portfolio How has the existing risk management approach worked after the quake? Minimum variance portfolio has been popular and had shown better performance

f l

Minimum variance portfolioMinimum variance portfolio

for a couple years. According to Clarke et al (2006), market portfolio (M) is inefficient and minimum

variance portfolio (GMV) can gain a higher return with lower risk.Concept of minimum variance portfolio

25 0

30.0

35.0

40.0 Mean variance - Frontier

p p

nual

ized

%)

5 0

10.0

15.0

20.0

25.0

Minimum variance(GMV)

× Market portfolio(M)

Eepe

cted

retu

rn (a

n.%

)

An investor can realize higher excess return per unit risk simply by selecting the portfolio with the lowest volatility and without having to forecast future return.

Exp

ecte

d re

turn

(ann

However, the risk characteristics of stocks that used to have low risk are changing.

0.0

5.0

60.0 65.0 70.0 75.0 80.0 85.0 90.0

Variance(an. ％)Source: Nomura

g gHas managing risk via the minimum variance approach worked after the quake?

“Minimum downside risk portfolios” are introduced as a risk management method that can be effective in this period after the earthquake. 17

Performance of minimum variance portfolios after the earthquakePerformance of minimum variance portfolios after the earthquakePerformance of minimum variance portfolios after the earthquakePerformance of minimum variance portfolios after the earthquake Minimum variance portfolios have slightly underperformed TOPIX since the quake. Minimum variance portfolios tend to overweight defensive sectors.

-15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0 25.0

Sector weight (compared with TSE1 market weight)

%Overweight20.0

end-Dec 2010=0% Cumulative return (absolute return)

Performance of minimum variance portfolios Sector weight of minimum variance portfolios Electric power and gas sector used to be a defensive sector.

ELECTRIC POWER & GASFOODS

LAND TRANSPORTATIONPHARMACEUTICAL

RETAIL TRADESERVICES

TEXTILES & APPARELSPULP & PAPER

OIL & COAL PRODUCTSAIR TRANSPORTATION5.0

10.0

15.0

Immediatelyafter the quake

FISHERY,AGRICULTURE & FORESTRYMETAL PRODUCTS

CHEMICALSWAREHOUSING & HARBOR TRANSPORTATION …

MININGCONSTRUCTION

PRECISION INSTRUMENTSOTHER PRODUCTS

RUBBER PRODUCTSMARINE TRANSPORTATION-10.0

-5.0

0.0 TOPIX

OTHER FINANCING BUSINESSGLASS & CERAMICS PRODUCTS

NONFERROUS METALSINSURANCE

REAL ESTATEWHOLESALE TRADE

IRON & STEELMACHINERY

SECURITIES & COMMODITY FUTURESBANKS

-20.0

-15.0

0-D

ec-1

0

1-Ja

n-11

8-Ja

n-11

5-Ja

n-11

1-Fe

b-11

8-Fe

b-11

6-Fe

b-11

3-Fe

b-11

-Mar

-11

-Mar

-11

-Mar

-11

-Mar

-11

-Mar

-11

7-A

pr-1

1

4-A

pr-1

1

1-A

pr-1

1

8-A

pr-1

1

-May

-11

-May

-11

-May

-11

→→→ Post - Earthquake →→→

Minimum Variance

INFORMATION & COMMUNICATIONTRANSPORTATION EQUIPMENT

ELECTRIC APPLIANCES

Underweight

30 11 18 25 01 08 16 23 02 09 16 24 31 0 7 14 21 28 11-

18-

25-

18

Note: Universe is stocks in TOPIX 500 and period of analysis is January 2011–May 2011. Shows cumulative performance of TOPIX and minimum variance portfolios constructed at start of each month and held for one month. Shading indicates March 11th, when the quake occurred, 12th, and 13th.

Source: Nomura

Note: Taking January 1995–May 2010 as our period of analysis, we calculated sector weights (deviation from TSE-1 market cap weight) of minimum variance portfolios constructed at the beginning of each month and plotted the average time series of each. Sectors based on TSE 33-sector classification.

Source: Nomura

Minimum downside risk portfoliosMinimum downside risk portfolios Measuring downside risk Assuming only negative change as risk, minimize the risk exceeding a certain loss

(VaR)

Minimum downside risk portfoliosMinimum downside risk portfolios

(VaR).

VaR (value at risk): the maximum possible loss that a portfolio can suffer given a confidence interval of β(%).

varianceDistribution of portfolio’s return

CVaR (conditional value at risk): expresses the loss expected if a portfolio’s return is less than VaR (the maximum possible loss).

Freq

uenc

y

Probability βRange of possible losses

occurring with probability 1 – βVaR = -αβ

CVaRβ(conditional expected return)

Return (%) 19Source: Nomura

Minimum downside risk portfoliosMinimum downside risk portfolios Mean-CVaR frontier The mean-CVaR frontier is convex in the same way as the mean-variance frontier.

The portfolio on the far left hand edge of the frontier is the “minimum CVaR

Minimum downside risk portfoliosMinimum downside risk portfolios

E t d t ( li d %)

Mean-CVaR frontier

The portfolio on the far left-hand edge of the frontier is the minimum CVaR portfolio”.

70

80

90

Expected return (annualized, %)

Mean-CVaR frontier

30

40

50

60

Minimum CVaRx

0

10

20

0.0 0.5 1.0 1.5 2.0CV R (d il %)CVaR (daily, %)

20

Note: Taking the stocks in the TOPIX 500 as the universe, we assumed the expected return on individual stocks is the average daily return for the previous 12 months and estimated the distribution of the return of individual stocks using the daily return for the previous 100 days. The frontier was drawn by linear interpolation, calculating the portfolio's mean return and CVaR.

Source: Nomura

The difference from minimum variance portfoliosThe difference from minimum variance portfolios When comparing the ex-post betas in downward market phases and upward market

phases,

The difference from minimum variance portfoliosThe difference from minimum variance portfolios

minimum variance portfolios reduce downside risk but underperform in bull marketsminimum downside risk portfolios reduce downside risk and follow the trend in bull markets

Ex-post beta of minimum variance portfolios Ex-post beta of minimum CVaR portfolios

40

60

Return on minimum CVaR portfolio (%)

40

60Return on minimum variance portfolio (%)

y = 0.90x

0

20

40

Mitigates downsiderisk in bear market

Matches performance in bull markety = 0.45x

0

20

40

Mitigates downsiderisk in bear market

Underperforms

y = 0.57x

-60

-40

-20

45º line

y = 0.30x

-60

-40

-20

45º line

in bull market

Note: We measured daily returns for previous 60 days of minimum variance and minimum CVaR and of TOPIX (overlapping 60-day rolling windows) and then measured how sensitive each portfolio's return was to that of TOPIX.

Source: Nomura 21

-60 -10 40Market return (%) (TSE-1 market cap weight)

-60 -40 -20 0 20 40 60Market return (%) (TSE-1 market cap weight)

Performance of minimum variance portfolios after the earthquakePerformance of minimum variance portfolios after the earthquake Both strategies outperformed immediately after the quake and successfully protected

portfolios. Mi i d id i k tf li f ll d th k t ft th k b t

Performance of minimum variance portfolios after the earthquakePerformance of minimum variance portfolios after the earthquake

Minimum downside risk portfolio before and after the quake Sector weight of Minimum downside risk portfolios

Minimum downside risk portfolios followed the market recovery after the quake, but minimum variance portfolios underperformed the market.

Minimum downside risk portfolios have lower sectoral risk.

-30.0 -20.0 -10.0 0.0 10.0 20.0 30.0

ELECTRIC POWER & GASFOODS

LAND TRANSPORTATIONPHARMACEUTICAL

RETAIL TRADESERVICES

TEXTILES & APPARELSPULP & PAPER

Sector weight (compared with TSE1 market weight)%Overweight

6.0

8.0

10.0

end-Dec 2010=0% Cumulative return ( vs market portfolio:TOPIX)

Minimum CVaR

Immediatelyafter the quake

PULP & PAPEROIL & COAL PRODUCTSAIR TRANSPORTATION

FISHERY,AGRICULTURE & FORESTRYMETAL PRODUCTS

CHEMICALSWAREHOUSING & HARBOR TRANSPORTATION …

MININGCONSTRUCTION

PRECISION INSTRUMENTSOTHER PRODUCTS

RUBBER PRODUCTS

Minimum variance portfolio

Minimum CVaR portfolio

4 0

-2.0

0.0

2.0

4.0 Minimum CVaR

MARINE TRANSPORTATIONOTHER FINANCING BUSINESS

GLASS & CERAMICS PRODUCTSNONFERROUS METALS

INSURANCEREAL ESTATE

WHOLESALE TRADEIRON & STEEL

MACHINERYSECURITIES & COMMODITY FUTURES

BANKS

-10.0

-8.0

-6.0

-4.0

c-10

n-11

n-11

n-11

b-11

b-11

b-11

b-11

ar-1

1

ar-1

1

r-11

r-11

r-11

pr-1

1

pr-1

1

pr-1

1

pr-1

1

y-11

y-11

y-11

Minimum Variance

→→→ Post - Earthquake →→→

INFORMATION & COMMUNICATIONTRANSPORTATION EQUIPMENT

ELECTRIC APPLIANCES

Underweight

22

Note: (1) Universe is stocks in TOPIX 500 and period of analysis is Jan 2011–May 2011. Shows cumulative performance with respect to excess return versus TOPIX of minimum CVaR portfolios and minimum variance portfolios constructed at start of each month and held for one month. (2) We used the low pass filter method with regard to measuring upturns and downturns. Shading indicates March 11th, when the quake occurred, 12th, and 13th.

Source: Nomura

Note: Taking January 1995–May 2010 as our period of analysis, we calculated sector weights (deviation from TSE-1 market cap weight) of minimum variance and minimum CVaR portfolios constructed at the beginning of each month and plotted the average time series of each. Sectors based on TSE 33-sector classification.

Source: Nomura

30-D

e

11-J

a

18-J

a

25-J

a

1-Fe

8-Fe

16-F

e

23-F

e

2-M

a

9-M

a

16-M

a

24-M

a

31-M

a

7-A

p

14-A

p

21-A

p

28-A

p

11-M

a

18-M

a

25-M

a

Minimum downside risk portfoliosMinimum downside risk portfolios Comparison of long-term performances

When dividing the market into downward phases and upward phases, the

Minimum downside risk portfoliosMinimum downside risk portfolios

When dividing the market into downward phases and upward phases, the minimum downside risk portfolio appears to be more effective in bull markets.

Performance of minimum variance portfolios(compared with TOPIX)

Performance of minimum CVaR portfolios(compared with TOPIX)

80

100end-Dec 2010=0% Cumulative return (vs TOPIX)

80

100end-Dec 2010=0% Cumulative return (vs TOPIX)

20

40

60

80Minimum Variance(excess return versus TOPIX )

20

40

60

80Minimum CVaR(excess return versus TOPIX )

-40

-20

0

1994

12

1995

12

1996

12

1997

12

1998

12

1999

12

2000

12

2001

12

2002

12

2003

12

2004

12

2005

12

2006

12

2007

12

2008

12

2009

12

2010

12

Shading indicates bear markets; no shading indicates bull markets

-40

-20

0

1994

12

1995

12

1996

12

1997

12

1998

12

1999

12

2000

12

2001

12

2002

12

2003

12

2004

12

2005

12

2006

12

2007

12

2008

12

2009

12

2010

12

Shading indicates bear markets; no shading indicates bull markets

23

Note: (1) Universe is stocks in TOPIX 500 and period of analysis is January 1995–May 2011. Shows cumulative performance with respect to excess return versus TOPIX of minimum variance portfolios constructed at start of each month and held for one month. (2) We used the low pass filter method with regard to measuring upturns and downturns. Shading indicates bear markets; no shading indicates bull markets.

Source: Nomura

Note: (1) Universe is stocks in TOPIX 500 and period of analysis is January 1995–May 2011. Shows cumulative performance with respect to excess return versus TOPIX of minimum CVaR portfolios constructed at start of each month and held for one month. (2) We used the low pass filter method with regard to measuring upturns and downturns. Shading indicates bear markets; no shading indicates bull markets.

Source: Nomura

1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2

ConclusionConclusionConclusionConclusion

1. In the year or so before March 2011, Japanese quant funds were generally doing well in terms of performance However after the earthquake on March 11 this does notin terms of performance. However, after the earthquake on March 11, this does not seem to be the case. We now need to be careful because conditions have changed after the earthquake.

2 We think sentiment will be changing for some time Therefore it is important to2. We think sentiment will be changing for some time. Therefore it is important to understand how factors behave in each sentiment phase. Here we have introduced a sentiment-based factor strategy.

3 M thi k it i ibl t t k d t f th t diffi lt i3. Moreover, we think it is possible to take advantage of the current difficulty in projecting earnings. We considered a method of estimating future revisions for stocks for which the consensus earnings forecast has been left unchanged.

f4. Also, we examined the minimum variance portfolio. This approach has underperformed since the earthquake. In contrast, the minimum downside risk portfolio, which we developed in 2010, has outperformed. In terms of “minimizing risk”, the minimum downside risk portfolio might be the better choice.risk , the minimum downside risk portfolio might be the better choice.

24

ReferencesReferencesReferencesReferences

Information quality Yoko Ishige and Hiromichi Tamura 2010 An enhanced revision-based strategy that takes information Yoko Ishige and Hiromichi Tamura, 2010. An enhanced revision based strategy that takes information

quality into account, Nomura Global Quantitative Research report, 6 May 2010.

Return dispersion and Nikkei Volatility Index Tomonori Uchiyama and Hiromichi Tamura, 2011. Relationship between lower return volatility and value y y

stocks, Nomura Global Quantitative Research report, 24 February 2011.

Academic paper Lou, Dong and Cohen, Lauren, Complicated Firms (October 11, 2010). AFA 2011 Denver Meetings Paper.

A il bl t SSRN htt // / b t t 1570869Available at SSRN: http://ssrn.com/abstract=1570869

Forecast revision signal by sales breakdown Akihiro Murakami and Hiromichi Tamura, 2011. Projecting revisions for stocks with unchanged consensus

forecasts Nomura Global Quantitative Research report 12 May 2011forecasts, Nomura Global Quantitative Research report, 12 May 2011.

Minimum downside risk portfolios Akihiro Murakami and Hiromichi Tamura, 2010. Minimum variance portfolios versus minimum downside

risk portfolios, Nomura Global Quantitative Research report, 2 July 2010.risk portfolios, Nomura Global Quantitative Research report, 2 July 2010.

25

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fl i d i fl i i h d l i k I ddi i ibl b d d i d i f i i l h i k f l i f hrate fluctuations and price fluctuations in the underlying stock. In addition, convertible bonds denominated in foreign currencies also carry the risk of losses owing to factors such as foreign exchange rate fluctuations.

When bonds are purchased via public offerings, secondary distributions, or other OTC transactions with Nomura Securities, only the purchase price shall be paid, with no sales commission charged. Bonds carry the risk of losses, as prices fluctuate in line with changes in market interest rates. In addition, foreign currency-denominated bonds also carry the risk of losses owing to factors such as foreign exchange rate fluctuations.

When Japanese government bonds (JGBs) for individual investors are purchased via public offerings, only the purchase price shall be paid, with no sales commission charged. When JGB f i di id l i t ld b f t it t l l t d i th f ll i f l ill b bt t d f th l f th b d l d i t t f 10JGBs for individual investors are sold before maturity, an amount calculated via the following formula will be subtracted from the par value of the bond plus accrued interest: for 10-year variable rate bonds, an amount equal to the two preceding coupon payments (before tax) x 0.8; for 5-year fixed rate bonds, an amount equal to the four preceding coupon payments (before tax) x 0.8.

Purchases of investment trusts (and sales of some investment trusts) are subject to a fee of up to 5.25% (tax included) of the transaction amount. Also, a direct cost that may be incurred when selling investment trusts is a fee of up to 2.0% of the unit price at the time of redemption. Indirect costs that may be incurred during the course of holding investment trusts include, for domestic investment trusts, a trust fee of up to 5.25% (tax included, annualized basis) of the net assets in trust, as well as fees based on investment performance. Other indirect costs may also be incurred. For foreign investment trusts, indirect fees may be incurred during the course of holding such as investment company compensation.y g , y g g p y p

Investment trusts invest mainly in securities such as Japanese and foreign equities and bonds, whose prices fluctuate. Investment trust unit prices fluctuate owing to price fluctuations in the underlying assets and to foreign exchange rate fluctuations. As such, investment trusts carry the risk of losses. Fees and risks vary by investment trust. Maximum applicable fees are subject to change; please thoroughly read the written materials provided, such as prospectuses or documents delivered before making a contract.

An annual account maintenance fee of up to ¥1,575 (tax included) is charged for any account held with Nomura Securities containing equities or investment securities. An additional annual account maintenance fee of up to ¥3,150 (tax included) is charged for any account containing foreign securities. No account fee will be charged for other marketable securities or monies deposited. Transfers of equities to another securities company via the Japan Securities Depository Center are subject to a transfer fee of up to ¥10,500 (tax included) per issue p q p y p p y j p , ( ) ptransferred depending on volume.

Nomura Securities Co., Ltd.Financial instruments firm registered with the Kanto Local Finance Bureau (registration No. 142)Member associations: Japan Securities Dealers Association; Japan Securities Investment Advisers Association; and The Financial Futures Association of Japan.

Additional information available upon requestNIPlc and other Nomura Group entities manage conflicts identified through the following: their Chinese Wall, confidentiality and independence policies, maintenance of a Restricted List

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p g g g , y p p ,and a Watch List, personal account dealing rules, policies and procedures for managing conflicts of interest arising from the allocation and pricing of securities and impartial investment research and disclosure to clients via client documentation.

Disclosure information is available at the Nomura Disclosure web page:http://www.nomura.com/research/pages/disclosures/disclosures.aspx

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