Japan Quantitative Strategy Post-ROE-P/B Curve Steeppgening Strategy Nomura Securities Co., Ltd

Japan Quantitative Strategy Post-ROE-P/B curve steeppgening strategy Nomura Securities Co., Ltd.

Akihiro Murakami Chief Quantitative Strategist, Japan See Appendix A-1 for analyst certification, important disclosures Nomura Securities Co., Ltd. and the status of non-US analysts. +81 (0)3 6703 1746 akihiro. murakami@nomura. com Any authors named on this report are research analysts unless otherwise indicated. May, 2013 Summary

 Current investment environment in the Japanese equity market : ・ JittfdfdttiftJapanese equity quant fund performance and representative factors ・ Who are buying Japanese stocks?

 Our investment strategy : (()a) Maj or bu yers of Ja panese e quities are nonresident investors ・ Strategy utilizing non-resident investors’ stock selection skills

(b) Reliability of analyst forecasts improving ・ Earnings revisions focusing on the ROE-P/B curve

1 Who are buying Japanese stocks?

Trading by trust banks, insurance and nonresident investors

TOPIX End-2010/12 = 0% (bn Y)Yen) 40 1,750 35 1,500 30 1,250 25 Nonresidents (rhs) 1,000 20 750 15 10 500 5 250 0 0 -5 -250 -10 -500 -15 Trust banks & -750 -20 Insurance (rhs) TOPIX (lhs) -1,000 -25 -1,250 -30 Great East Japan European Resurgence of Changeof Government -35 -1,500 Earthquake Financial crisis European & -40 Financial crisis Abenomics-Driven Rally -1,750 -45 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013 Q1 Q2-2,000 12/6 12/9 13/3 11/3 11/6 11/9 12/3 (yyyy/m) 12/12 11/12 10/12 00 00 00 00 00 00 00 2 2 2 2 2 2 2 20 20 20

Note: Shows trust banks‘, insurance cos’ and nonresident investors' (bottom graph) trading value, taken from equity purchases by investor category data (right axis) and TOPIX return(left axis). Sample period is January 2011 through 10.May.2013 . Source: Nomura, from TSE's equity trading value by investor category data 2 As part of monetary easing, the BOJ also keeps buying Japanese ETFs

BOJ's ETF purchases and the TOPIX

TOPIX End -2010/12 = 0% (bn Yen ) 40 BOJ's ETF 40 35 purchases (rhs) 30 30 25 20 20 15 10 10 5 0 0 -5 -10 -10 -15 -20 TOPIX (lhs) -20 -25 -30 Great East Japan European Resurgence of Change of Government -30 Earthquake Financial crisis European & -35 Financial crisis Abenomics-Driven Rally -40 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013 Q1 Q2 -40 (yyyy/m) 010/12 011/12 012/12 2011/3 2011/6 2011/9 2012/3 2012/6 2012/9 2013/3 22 22 22

Note: Shows the actual amount of ETFs purchased by BOJ (right axis) and TOPIX return(left axis). Sample period is January 2011 through 10.May.2013 . Source: Nomura, based on BOJ and other data 3 Japanese equity quant funds started to recover since the change of government

Average performance of Japanese equity quant funds

End-2010/12 = 0% Cumulative return 10

-5

-10 Quant Fund Change of -15 Government 16th. Dec. 2012 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013 Q1 Q2 -20 Great East Japan European Resurgence of Earthquake Financial crisis crisis European Abenomics -DrivenRallyDriven Rally -25 Financial crisis

(yyyy/m) 2013/3 2012/3 2012/6 2012/9 2011/3 2011/6 2011/9 2012/12 2011/12 2010/12

Note: Shows daily average return (Jensen's alpha), on an indexed basis, on 23 funds (domestic publicly offered investment trusts and nonresident investor funds) that invest in Japanese equities using a quant-based approach. Sample includes long-only, individual stock long-short, and market-neutral (long on individual stocks, short on index futures, for example) funds. Sample period is January 2011 through 10.May.2013 . Source: Nomura 4 Mimic portfolio’s performance of quant funds

Average performance of Mimic portfolio and Quant funds

End-2010/12 = 0% Cumulative return 10 Mimic Quant Portfolio ( E/P + Revision + B/P + Reversal) 5

-5

-10 Quant Fund

-15

2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013 Q1 Q2 -20 Great East Japan European Resurgence of Earthquake Financial crisis crisis European Abenomics-Driven Rall y -25 Financial crisis

(yyyy/m) 2013/3 2012/3 2012/6 2012/9 2011/3 2011/6 2011/9 2012/12 2011/12 2010/12

Note: Shows daily return of mimic portfolio (the composite factor of E/P, B/P, Revision and reversal(past 3month return)) and daily average return (Jensen's alpha), on an indexed basis, on 23 funds (domestic publicly offered investment trusts and nonresident investor funds) that invest in Japanese equities using a quant-based approach. Sample includes long-only, individual stock long-short, and market-neutral (long on individual stocks, short on index futures, for example) funds. Sample period is January 2011 through 10.May.2013 . Source: Nomura 5 Value factors worked as the main driver for the Q4 quant recovery But…..

Daily performance of E/P and B/P

End-2010/12 = 0% Cumulative returnreturn 20

10 E/P

-5

-10 B/P -15 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013Q1 Q2 -20 Resurgence of Great East Japan European Abenomics -DrivenRallyDriven Rally EhEart hqua kke financial crisis European -25 financial crisis 012/12 010/12 011/12 2013/3 2011/3 2011/6 2011/9 2012/3 2012/6 2012/9

22 22 22 (yyyy/ m ))

Note: Universe of TOPIX500 stocks is divided into 5 quintiles, with an equal number of stocks in each quintile, by factor value. Portfolios are rebalanced at the beginning of each month. Cumulative spread return (#5 – #1) is calculated on a daily basis (end-Dec. 2010 = 0). We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. Sample period is 4 Jan. 2011 – 10.May.2013. Source: Nomura 6 B/P factors were driven by credit risk factor

Factor performance for B/P and 5-year CDS spreads

EdEnd-2010/12 =0% 0% Cumulative return 20

10 B/P

-10 CDS5Y

-20

2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013Q1 Q2 -30 Great East Japan European Resurgence of Abenomics-Driven Rally Earthquake financial crisis European financial crisis -40 010/12 011/12 012/12 2011/3 2011/6 2011/9 2012/3 2012/6 2012/9 2013/3 (yyyy/m) 22 22 22

Note: We divided the universe of TOPIX 500 stocks into five groups in terms of both B/P and 5-year CDS spreads at the beginning of each month. Figure shows cumulative monthly returns on a strategy of going long on the group of stocks with the highest factor values and short on the group of stocks with the lowest factor values, for each factor. We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. Sample period is January 2011 through 10.May.2013. Source: Nomura 7 Credit risk factor may no longer be a driver for B/P factors

CDS spreads for high-B/P and low-B/P stocks

((p)bp) CDS spreads for high‐B/P and low‐B/P stocks 400 High B/P 350

300

250

200 Low B/P 150

100 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013Q1 Q2 50 Great East Japan Resurgence of European Abenomics-Driven Rally Earthquake financial crisis European 0 financial crisis 010/12 011/12 012/12 2011/3 2011/6 2011/9 2012/3 2012/6 2012/9 2013/3 22 22 22

Note: Universe is TOPIX 500 stocks for which 5-year CDS spread data were available. We divided the universe into five groups on the basis of B/P factor values at the beginning of each month, and calculated the median 5-year CDS spread for the groups of stocks with the highest and lowest B/P, respectively. Sample period is January 2011 through 10.May.2013 . Source: Nomura 8 We expect profit-based factors to emerge as the next main driver

Daily performance of ROE, revision and recurring profit growth

End -2010/12 = 0% Cumulativereturn return 30

20 Revision

10 ROE

-10

-20 Recurring profit growth -30 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013Q1 Q2 Great East Japan European Resurgence of Abenomics-Driven Rally -40 Earthquake financial crisis European financial crisis crisis

-50 010/12 011/12 012/12 2011/3 2011/6 2011/9 2012/3 2012/6 2012/9 2013/3

22 22 22 (yyyy/m)

Note: Universe of TOPIX500 stocks is divided into 5 quintiles, with an equal number of stocks in each quintile, by factor value. Portfolios are rebalanced at the beginning of each month. Cumulative spread return (#5 – #1) is calculated on a daily basis (end-Dec. 2010 = 0). Sample period is 4 Jan. 2011 – 10 May.2013. We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. Source: Nomura 9 Nonresident investor purchases likely to work more positively for profit-based factors than value factors

Comparison of risk characteristics: Stocks overweighted by domestic pension funds vs. Stocks overweighted by nonresident investors

Size 0.20 Sensitivity to dollar B/P 0.10 0000.00 Historical volatility E/P (60 months) -0.10 -0.20 -0300.30 Historical beta Forecast dividend yield (60 months) -0.40

Debt ratio Sales growth

Past 1 year return ROE

Past 3-month return

Domestic pension funds #5-#1 Non-resident #5-#1 TOPIX Note: we calculated risk characteristics of each portfolio and plotted the historical average of each risk characteristic. We conducted a cross-sectional normalization of each set of data so that weighted average market cap was 0 and variance was 1 at the beginning of each month, adjusting standard deviation to ±3σ if it exceeded that level, and repeated this process three times. Sample period is June 1995 through March 2013. Source: Nomura 10 Idea 1: Learning from non-resident investors’ stock selection skills

Performance of stocks overweighted by domestic pension funds and nonresident investors

(End-1995/6 = 0%) Cumulative return 100 Active weight factor of Nonresident investors 80

60 Active weight factor of Domestic Pension 40

‐20 ROE factor

‐40 00612 00706 00712 00806 00812 00906 00912 01006 01012 01106 01112 01206 01212 99506 99512 99606 99612 99706 99712 99806 99812 99906 99912 00006 00012 00106 00112 00206 00212 00306 00312 00406 00412 00506 00512 00606 11 11 11 11 11 11 11 11 11 11 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22

Note: We divided the universe of TSE-1 stocks into five groups based on their active weightings in the portfolios of nonresident investors at the start of each month. Figure shows cumulative monthly returns on a strategy combining long positions on stocks in the highest group (overweighted stocks) with short positions on stocks in the lowest group (underweighted stocks). We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. Sample period is June 1995 through April 2013. Source: Nomura 11 Company valuation and profitability closely associated

 A simple residual income model gives the relationship between future ROE and P/B ratio. ∞ , , 1 1 1 The ROE-P/B curve: the cross sectional relationshipp( between ROE and valuation (P/B)

P/B (x) Relationship between ROE and P/B 7.0 Jan 2009 Apr 2013 606.0 Fitted curve (Jan 2009)

5.0 Fitted curve (Apr 2013)

4.0

3.0

2.0

1.0

0.0 -15. 0 -10. 0 -505.0 000.0 505.0 10. 0 15. 0 20. 0 25. 0 30. 0 35. 0 ROE (%) Note: We plotted each stock's expected ROE (next-FY forecast where available, otherwise current-FY forecast) on the x-axis and its P/B on the y-axis, in a two-dimensional scatter plot. Universes were TSE-1 stocks as at the beginning of April 2013 and the beginning of January 2009, respectively. To remove outliers, we excluded stocks in the top 1% and bottom 1% of the universe in terms of ROE from our analysis. 12 Source: Nomura The ROE-P/B curve fitted by converted model

Relationship between ROE and valuation (log P/B)

The convert ed mod el : , _, , ,

ln (P/B) Converted relationship between ROE and P/B (Apr 2013) 3.0 P/B (x) Relationship between ROE and P/B 7.0 2.0 6.0 Apr 2013 Fitted curve (Apr 2013) 5.0 101.0

4.0

0.0 3.0

y = 0.4556x + 0.078 2.0 -101.0

1.0

-2.0 0.0 -15.0 -10.0 -5.0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 ROE (()%) -3.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 (low) Standardized ROE (high)

Note: We plotted each stock‘s standardized expected ROE on the x-axis and its log P/B on the y-axis, in a two-dimensional scatter plot. Universe was TSE-1 stocks at the beginning of April 2013. We estimated the best fit line using model , _ , where ln(*) is the natural log of *, δ and β are the intercept and regression coefficient, respectively, at time t, and ε is the , , t t i,t residual. To estimate the regression coefficient,, we standardized ROE, the explanatory variable, so that the average was 0 and the standard deviation was 1, and rounded any values beyond ±3σ to ±3σ. To remove outliers, we excluded stocks in the top 1% and bottom 1% of the universe in terms or ROE from our analysis. Source: Nomura 13 The ROE-P/B curve has recently steepened rapidly

 The slope of the curve (β coefficient) has recovered to the level prior to Lehman collapse.

Time seri es β coeffic ien t for ROE-P/B curve

coefficient 0.7

0.6 The association between expected ROE and P/B is strong. 0.5 Steep

0.4

0.3

The association is weak. 0.2 Flat

0.1

0.0 198701 198801 198901 199001 199101 199201 199301 199401 199501 199601 199701 199801 199901 200001 200101 200201 200301 200401 200501 200601 200701 200801 200901 201001 201101 201201 201301 (yyyymm)

, Note: Universe was TSE-1 stocks. We carried out a cross-sectional regression analysis using expected ROE and P/B ratios at the beginning of each month, and the model _ , , , , where ln(*) is the natural log of *, δt and βt are the intercept and regression coefficient, respectively, at time t, and εi,t is the residual. Sample period was January 1987 through April 2013. To estimate the regression coefficient, we standardized ROE, the explanatory variable, so that the average was 0 and the standard deviation was 1, and rounded any values beyond ±3σ to ±3σ. To remove outliers, we excluded stocks in the top 1% and bottom 1% of the universe in terms or ROE from our analysis. We used a low-pass filter to determine phases of the coefficient. Source: Nomura 14 What does the steepening of the curve indicate?

 We hypothesize that the slope of the curve indicates the effectiveness of revision strategy.

ShSchemati c fhfor phases wh en slope ofROEf ROE-P/B curve i s hi gh ( st eep) and l ow (fl at)

ln (P/B) Converted relationship between ROE and P/B (schematic) (High) 303.0 (2) Steep A’

2.0 A (1) Flat 1.0 B’ B 000.0 Upward revisions -1.0

-2.0

(Low) -303.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 (Low) Standardized ROE (High)

Source: Nomura 15 Revision factors are certainly effective when the curve becomes steep

Effectiveness of revision factor when the curve is steep / flat

Return/risk Performance of revision factor by phase 0.80

0.60

0.40

0.20

0.00

-0.20

-0.40

-0.60

-0.80 Low Medium High (flat) Slopeof curve (steep)

Note: Universe was TSE-1 stocks. We investigated the effectiveness of the earnings forecast revision factor in high, medium, and low phases of regression coefficient βt , estimated using model , _, , . To calculate factor returns, we divided the universe into five groups based on the revision factor, then calculated statistical data for monthly returns on a strategy of , going long on the top group and short on the bottom group. We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. We divided the entire sample period into three groups based on coefficient value. We defined periods with coefficient values above the level that divides the top third from the middle third as high phases and periods with coefficient values below the level that divides the top third from the middle third as low phases. Source: Nomura 16 In steep phase, profit-based factors perform well

Difference in factor performance between “Steep” and “Flat” phases

Difference in factor performance between ”Steep” and ”Flat" phases

P/E

P/B

Dividend yield

ROE

Profit margin

Sales turnover ratio

High financial leverage

High revision

Hig h vo la tility

Large cap

High default probability

Historical 6-month return

Historical 3-month return

Herding

Equity finance

Earnings surprise (progress)

Earnings surprise (share price response)

Earnings surprise (company earnings estimate)

-1.50 -1.00 -0.50 0.00 0.50 1.00 1.50 2.00 High return in "Flat" phases High return in "Steep" phases , _, , Note: Universe was TSE-1 stocks. We investiggyg,,pgated the effectiveness of a key factors in high, medium, and low phases of regression coefficient βt ,,()( model (*) ( , ) . To calculate factor returns, we divided the universe into five groups in terms of each factor, and calculated statistical data for monthly returns on a strategy of going long on the top group and short on the bottom group for each factor (but long on the bottom group and short on the top group in the case of P/E and P/B). Figure shows difference between time series average/standard deviation (annualized) in high and low phases. We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. We divided the entire sample period into three groups based on coefficient value. We defined periods with coefficient values above the level that divides the top third from the middle third as high phases and periods with coefficient values below the level that divides the top third from the middle third as low phases. Source: Nomura 17 The curve for high-ROE stocks has tended to steepen more than others

Relationship between ROE and valuation (log P/B) β coefficient of ROE-P/B curve for different levels of varies with level of ROE expected ROE

 coefficient ln (P/B) Converted relationship between ROE and P/B (April 2013) 1.0 3.0 y = 0.8278x - 0.2294 High ROE 0.8 Medium ROE 2.0 LROELow ROE 0.6

1.0 Steep 0.4

0.0 0.2

0.0 -1.0 Flat -0.2 -2.0 y = 0.1847x - 0.1768 -0.4 m) 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 -3.0 mm -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 19910 19920 19930 19940 19950 19960 19970 19980 19990 20000 20010 20020 20030 20040 20050 20060 20070 20080 20090 20100 20110 20120 20130 19870 19880 19890 19900 (yyyy (low) Standardized ROE (high)

NtNote: We pl lttdotted each s tock' s st and ardi didzed expec tdROEted ROE on the x-axiditlP/Bis and its log P/B on the y-axis, in a two-dimensional scatter plot. Universe was TSE-1 stocks at the beginning of April 2013. We divided the universe into three groups in terms of expected ROE at the beginning of each month and estimated the best fit line for each , group using model _ , , , where ln(*) is the natural log of *, , δt and βt are the intercept and regression coefficient, respectively, at time t, and εi,t is Note: Universe was TSE-1 stocks. We divided the universe into three groups based on the residual. To estimate the regression coefficient, we standardized ROE, the expected ROE at the beginning of each month, and carried out a regression analysis , explanatory variable, so that the average was 0 and the standard deviation was 1, and for each group using model _ , , . , rounded any values beyond ±3σ to ±3σ. To remove outliers, we excluded stocks in the Shows time series data for regression coefficient βt . Sample period was January 1987 top 1% and bottom 1% of the universe in terms or ROE from our analysis. through April 2013. Source: Nomura Source: Nomura 18 Idea 2: revision factor is most effective for the high-ROE group

Revision factor performance by expected ROE

(End-Dec 1986 = 0%) Cumulative return 450 400 High ROE 350 Medium ROE 300 Low ROE 250 200 150 100 50 0 -50 198612 198712 198812 198912 199012 199112 199212 199312 199412 199512 199612 199712 199812 199912 200012 200112 200212 200312 200412 200512 200612 200712 200812 200912 201012 201112 201212 (yyyymm)

Note: Universe was TSE-1 stocks. Sample period was January 1987 through 12 April 2013. We divided the universe into three groups based on expected ROE at the beginning of each month, divided these three groups into a further five groups each based on our earnings forecast revision factor, and calculated monthly returns on a strategy of going long on the top group and short on the bottom group in terms of the earnings forecast revision factor, for each ROE group. Figure shows cumulative monthly returns. We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. Source: Nomura 19 Earnings revisions were larger (smaller) for the (low) high-ROE group

The absolute value of revisions factor by expected ROE

Revision factor by expected ROE (absolute value) (large) 8.0%

7.0%

6.0% lue)

ctor ctor 5.0% aa aa

4.0%

3.0% evision f evision bsolute v aa RR ( 2.0%

1.0% (small) 00%0.0% Low Medium High

Expected ROE

Note: Universe was TSE-1 stocks. Sample period was January 1987 through April 2013. We divided the universe into three groups based on expected ROE at the beginning of each month. Figure shows time series averages of the absolute value of the revision factor for each group. Source: Nomura 20 Passive funds have shown growing presence in the Japanese equity market

 AUM for passive Japanese equity ETFs has grown remarkably and became double in the last 3 years.  The BOJ is expected to keep buying Japanese stocks.

AUM growth for passive Japanese equity ETFs

(end-Jan.2005 = 1.0) AUM growth for passive Japanese equity ETFs 2.5

2.02 AUM growth – TOPIX return 2 1.82 AUM growth : 67, 044 mil USD

1.5

0.5

0 501 601 701 801 901 001 101 201 301 00 00 00 00 00 11 11 11 11 20 20 20 20 20 20 20 20 20 Note: Shows growth in AUM (assets under management) for passive ETFs (excluding leveraged and inverse ETFs) that track Japanese equities and are listed on major markets in the US and Asia, including Japan. The red line shows cumulative monthly growth in AUM from the beginning of 2005 (AUM at beginning of 2005 = 1). The blue line shows the cumulative spread between monthly AUM growth and monthly TOPIX return. Sample period is February 2005 through March 2013. Source: Nomura 21 Jan, Apr, Jul and Oct are periodical index rebalance season Anomalies might be seen around index events

 Typical trading pattern of TOPIX-tracking fund

Announcement Date Rebalance Date 5th business day Day before last business day in Jan / Apr / Jul /Oct in Jan / Apr / Jul /Oct

Trading by passive funds (a) Stocks about to see a relative increase in FFW → Buy

(()b) Stocks about to see a relative decrease in FFW → Sell  Trading in typical event-driven strategy

Announcement Date Rebalance Date 5th business day in October Day before last business day in Jan / Apr / Jul /Oct in Jan / Apr / Jul /Oct

Investments carried out in advance on basis of forecasts Reverse trades to lock in profits (a) Stocks expected to see a relative increase in FFW → Long

(b) Stocks expected to see a relative decrease in FFW → Short

22 Typical event-driven strategy

Announcement Date Rebalance Date 5th business day Day before last business day in Jan / Apr / Jul /Oct in Jan / Apr / Jul /Oct

Investments carried out in advance on basis of forecasts Reverse trades to lock in profits (a) Stocks expected to see a relative increase in FFW → Long

(b) Stocks expected to see a relative decrease in FFW → Short

Announcement date = 0% Cumulative return (vs TOPIX) Announcement date 3.0 Top 10% in terms of weighting change

202.0

1.0 (b)

000.0

Note: In this event, all constituent stocks, including stocks unchanged in FFW, see a change in their TOPIX weighting. We compare TOPIX weightings -1.0 (a) Bottom 10% in terms of weighting change based on post FFW and new FFW. Covering periodic reviews of FFW in every October from 2006 through 2011. Sample size for each groups is around 400 stocks. Average cumulative excess return relative to TOPIX -202.0 from 20 trading days before announcement/date to 20 days after announcement/rebalance date. We did not take transaction costs into account. Analysis is based on historical share prices and does not -3.0 guarantee future performance. -20 -15 -10 -5 0 5 10 15 20 Source: Nomura (days) 23 After the rebalances of passive funds, return reversal is expected

Announcement Date Rebalance Date 5th business day Day before last business day in Jan / Apr / Jul /Oct in Jan / Apr / Jul /Oct

Trading by passive funds (a) Stocks about to see a relative increase in FFW → Buy

(b) Stocks about to see a relative decrease in FFW → Sell

Rebalance date = 0% Cumulative return (vs TOPIX) Rebalance date 3.0

Bottom 10% in terms of weighting change 2.0 (b) 1.0

0.0

Note: In this event, all constituent stocks, including stocks unchanged in FFW, -1.0 see a change in their TOPIX weighting. We compare TOPIX weightings based on post FFW and new FFW. Covering periodic reviews of FFW in Top 10% in terms of weighting change every October from 2006 through 2011. Sample size for each groups is around 400 stocks. Average cumulative excess return relative to TOPIX -2.0 from 20 trading days before effective date to 20 days after (a) announcement/rebalance date. We did not take transaction costs into account. Analysis is based on historical share prices and does not -3.0 guarantee future performance. -20-15-10-50 5 101520 Source: Nomura (days) 24 Effect of FFW change on valuations

 B/P value spread of the stocks for which FFWs are increased and decreased is expanded more than 3%. Then, the spread is eliminated gradually.

Effect of FFW change on valuations Value spred of stocks with incresing/ decreasing FFWs 2.00% (a) Stocks for which FFWs are to be increased (Buy) → relatively overvalued 1.50%

1.00%

0.50%

0.00%

‐0.50%

Expanded value spread more than 3％ ‐1.00%

‐1.50% (b) Stocks for which FFWs are to be decreased (Sell) → relatively undervalued ‐2.00% Sep Oct Beginning of Nov Dec Jan Feb

Announcement Trading period by passive funds

Note: Taking TSE-1 stocks as our universe, we calculated the average P/B of stocks for which the FFW (free-float weight) was increased or decreased, respectively, in the periodic FFW review for the TOPIX carried out in October each year from 2006 through 2011. We then calculated the spread between these two averages, respectively, and the average P/B for the universe (the value spread). We rebased the data so that the value spread in the month preceding the announcement of the October FFW review each year = 0%. Source: Nomura 25 Idea 3: investment strategy based on change in FFW

 Start investment at the beginning of the next month when passive funds are rebalanced.  Short the stocks for which FFWs increased (overvalued), and long the stocks f()for which FFWs decreased (undervalued).

Strategy utilizing FFW change

Jan. 2002 = 0% Cumulative return 80

70 Composite: TOPIX + R/N + Passive Fund Buy/Sell 60

30 TOPIX FFW revision (()3M)

‐10 200201 200301 200401 200501 200601 200701 200801 200901 201001 201101 201201 201301

Note: We divided our universe of TSE-1 stocks into five groups on the basis of composite factor (TOPIX, R/N and Passive Fund Buy/Sell) at the beginning of each month. We then calculated the monthly return on a strategy combining long positions on the group of stocks with the lowest factor values (#1) and short positions on the group of stocks with the highest factor values (#5). Chart shows cumulative monthly return. We did not take transaction costs into account. Analysis is based on historical share prices and does not guarantee future performance. Sample period is January 2002 through April 2013. Source: Nomura 26 Conclusion

 We have seen more favorable investment environment in the Japanese equity market for profit-based factors to perform well.

 We propose the following three investment ideas (1) Strategy utilizing non-resident investors’ stock selection skills (()2) Revision strategy in the phase when the ROE-P/B curve becomes steep (3) Contrarian strategies based on passive fund trading

27 Appendix (1): definitions of factors

Definitions of factors

Factor Factor definition Market cap / earnings forecast 1P/E #1 (un derv al ued) - #5 (ov erv al ued) (f(next-FY forecast w here available; I/ ///SfB/E/S consensus forecast > Toyo Keizai f f)orecast)

2 P/B #1 (undervalued) - #5 (overvalued) Market cap / actual shareholders’ equity

3 Dividend yield #5 (high) - #1 (low ) Calculated from Nikkei estimated dividends

Earnings forecast / actual shareholders’ equity 4 ROE #5 (high) - #1 (low ) (next- FY forecast w here available; IFIS consensus forecast > Toyo Keizai forecast) Earnings forecast / sales forecast 5 Profit margin #5 (high) - #1 (low ) (next-FY forecast w here available; IFIS consensus forecast > Toyo Keizai forecast) Sales forecast / total assets 6 Sales turnover ratio #5 (high) - #1 (low ) (next-FY forecast w here available; IFIS consensus forecast > Toyo Keizai forecast) 7 High financial leverage #5 (high) - #1 (low ) Total assets / Net Equity

Recurring profit forecast / past 3-month average recurring profit forecast – 1 8 High revision #5 (high) - #1 (low ) (IFIS consensus forecast w here available, otherw ise Toyo Keizai forecast)

9 High volatility #5 (high) - #1 (low ) Standard deviation of daily share price return (past 60 days)

10 Large cap #5 (large cap) - #1 (small cap) Log market cap

11 High default probability #5 (high) - #1 (low ) Estimated using Merton options theory

12 Historical 6-month return #5 (high) - #1 (low )

13 Historical 3-month return #5 (high) - #1 (low )

Active fund ow nership as % of total shares out 14 Herding #5 (high) - #1 (low ) * Active funds defined as all the active (long-only) funds in the Japanese equities category, as categorized by The Investment Trusts Association, Japan

15 Equity finance #5 (high) - #1 (low ) Change in no. of shares out compared to 24 months previously

Calculated from cumulative recurring profits (from Q1 through most recent quarter) as % of consensus 16 Earnings surprise (progress) #5 (high) - #1 (low ) recurring profit forecast (FY1) 17 Earnings surprise (share price response) #5 (high) - #1 (low ) Cumulative return versus TOPIX from most recent results announcement date to tw o trading days after

Company estimate versus consensus recurring profit forecast (FYU1) (IFIS consensus forecast > Toyo 18 Earnings surprise (company earnings estimate) #5 (high) - #1 (low ) Keizai forecast)

Source: Nomura 28 Appendix (2) performance of Japanese fundamental-based active funds

Average performance of Japanese fundamental-based active funds

End -2010/12 = = 0% 0% Cumulative Cumulative return return 10

5 Fundamental Based ActiveActive Fund Fund

-5 Mimic ActiveActive Fund PortfolioPortfolio (E/P ++ Revision)Revision)

-10 2011 Q1 Q2 Q3 Q4 2012 Q1 Q2 Q3 Q4 2013 Q1 Q2 Great East Japan European Resurgence of Change of Government EthEarthqua kke financ ilial cr iiisis European & Abenomics-driven rally -15 financial crisis

(yyyy/m) 010/12 2011/3 2011/6 2011/9 011/12 2012/3 2012/6 2012/9 012/12 2013/3 22 22 22

Note: Shows average daily return (Jensen‘s alpha), on an indexed basis, for all long-only active domestic publicly offered investment trusts (based on Investment Trusts Association, Japan categories). Sample period is January 2011 through 10.May.2013 . Source: Nomura 29 Appendix (3): transition in shareholding at market value by investor category

Transition in shareholding at market value by investor category

(trillion yen) Shareholding at Market Value 700

600

500

400 Survey year 2011 ( as of Mar. 2012) 300 Business corporations, 67 200 IdiidlIndividuals, 63

Foreign corporations, 81 100 Financial Institutions, 90 0 00 00 55 00 55 00 55 00 55 201 197 197 198 198 199 199 200 200 (Survey year) Note: All domestic stock exchanges(Tokyo, Osaka, Nagoya, Fukuoka and Sapporo)in Japan. The market value of public pension funds is not included in that of Annuity Trusts. - Business corporations: All companies incorporated in Japan (ex “Financial institutions” and “Securities companies”). - Individuals and others: Individuals and non-incorporated groups with Japanese nationality, regardless of their place of residence. - Foreign corporations: Corporations that were established based on foreign laws; foreign and municipal governments, and entities that are not incorporated; and individuals whose nationalities are other than Japp,ganese, regardless of their place of residence. - Financial institutions > City, regional banks, etc.: Regular Japanese banks licensed under the Banking Act and the Long-Term Credit Bank Act (There have been no regular Japanese banks licensed under the Long- Term Credit Bank Act since the 2006 Shareownership Survey) > Trust banks: Trust banks that are members of the Trust Companies Association of Japan > Investment trusts: Trust assets of trustors that are stipulated in the Investment Trust Act (Act on Investment Trusts and Investment Corporations), and whose nominees (trustees) are banks that conduct trust business > Annuityypyp trusts: Employees’ pension funds that are sti pulated in the Em pyployees’ Pension Insurance Act ,pp, and corporate pensions stipulated in the Defined-Benefit Corporate Pension Act or the Defined Contribution Pension Act, whose nominees (trustees) are banks that conduct trust business. (excluding public pensions under management) > Life insurance companies: Life insurance companies that are stipulated in the Insurance Business Act > Non-life insurance companies: Non-life insurance companies that are stipulated in the Insurance Business Act > Other financial institutions: Financial institutions other than those stipulated above, including credit unions (shinkin banks), credit associations, agriculture-related financial institutions, mutual aid associations, and government-related financial institutions, etc. Source: Shareownership Survey (TSE), Nomura 30 Appendix (4): outline regarding periodic review of FFW

Outline of calculating FFW Definitions of free-float shares and non-free-float shares Outline Estimation of non-free-float shares

(1) Estimate the amount of non-free-float shares using publicly Shares held by the top 10 major shareholders, treasury stocks, available documents released by listed companies. shares held by the board of directors, and other shares TSE seems not available for trading in the market. (2) Calculate non-FFW. (Non-free-float shares / listed shares) TSE may t reat sh ares h eld b y th e t op 10 maj or sh areh old ers Obtain the FFW by removing the non-free-float factor from (3) as free-float shares in the following case. 1. (1 – Non-FFW) ※TSE multiply the FFW by 0.75x for stocks recognized as Condition Major shareholder having low liquidity and newly listed stocks As a general rule, shares considered as Securities finance Source: Nomura based on Tokyo Stock Exchange Index Guidebook published 9 February 2012 free-float. companies, securities Periodic Review depositories, Settlement Announcement Effective nominees for Term Date Date depository Receipts January – Fifth business day of Last business day of March October October Shares likely to be seemed as free-float. Trust banks, Cases where any of the following conditions master trusts, April – June Fifth business day of Last business day of are met and the TSE deems it appropriate to global January January consider such shares as free-float. custodians, - There are descriptions in the Securities July – Fifth business day of Last business day of insurance Report on the type of trust, the purpose of companies, September April April purchase of shares, etc. securities - It is clear that shares are held by several October - Fifth business day of Last business day of companies, etc. December July July beneficiaries and managed centrally - It is clear that shares are held for margin ※The TSE may review FFW in the cases (allocation of new shares to a third party, etc) where Transaction it seems that the existing FFW is expected to be significantly affected. Source: Nomura based on Tokyo Stock Exchange Index Guidebook published 9 February 2012 Source: Nomura based on Tokyo Stock Exchange Index Guidebook published 9 February 2012 31 Appendix A-1

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