the economics of wireless data part 4: japan country view

www.morganmarkets.com

Asia Pacific Equity Research21 January 2013

The Economics of Wireless Data Part 4: Japan Country ViewDetailed Supply/Demand forecasts + Conclusions...

Asian Telecommunications

James R. Sullivan, CFA AC

(65) 6882-2374

[email protected]

J.P. Morgan Securities Singapore Private Limited

Hitoshi Hosoya AC

(81-3) 6736-8631

[email protected]

JPMorgan Securities Japan Co., Ltd.

Michelle Wei, CFA

(852) 2800-8562

[email protected]

J.P. Morgan Securities (Asia Pacific) Limited

Jesper J Koll

(81-3) 6736-8600

[email protected]

JPMorgan Securities Japan Co., Ltd.

See page 16 for analyst certification and important disclosures, including non-US analyst disclosures.J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in making their investment decision.

Welcome to Part Four of our Economics of Wireless Data series. Parts 1-3 explored the impact of spectrum, population density, infrastructure, and technology choice on the new dynamics of data as a business model. Part Four consists of a series of country focused reports that updates and expands our wireless data supply / demand analysis. This edition focuses on Japan, the previous reports looked at Indonesia, Taiwan, China and Korea. Data capacity excel models are available for each market analyzed, please contact us for details.

Japan, The Premier Asian Data Market. Japan presents very good elasticity (1.7x for DCM and SB, higher for KDDI), still high data prices (above USD30/GB, the highest in Asia, so still room for pricing cuts), and one of the best affordability outlooks (measured as ARPU / monthly income). Network utilization levels for KDDI and Softbank remain low, indicating the potential for significant revenue upside at minimum incremental expense. We see Softbank as the best investment into this theme, given their relatively low utilization rates (12% on 4G vs. DCM at 32% and KDDI at 5%), the lowest data unit pricing in Japan (USD29/GB vs. DCM at USD37/GB and KDDI at USD39/GB) and positive elasticity (1.7x, in line with DCM).

DM vs. EM? Japan’s positive data price elasticity of 1.7x compares well with Taiwan at 1.2x, vs. Emerging Asia at significantly below 1x. Korea appears to be an outlier with sub 1x elasticity, as Japan buttresses the DM vs. EM case. Emerging Market customers, who spend 2-3x more of their income (% basis) on wireless services already, lack the ability to spend an absolutely higher amount. We continue to suggest an investment strategy focused on Developed Market Integrated carriers over Emerging Market Wireless only carriers (please see our recent Telco/Internet strategy presentation slides here).

How much time will people spend using data? Aggressive network investments paired with still expensive data pricing and good elasticity make us bullish on monetizable data take up in Japan. The key limitation here will not be affordability nor network capacity, in our view, but the amount of time consumers will spend online. Voice usage levels maxed at 8.3 hours per month in almost every market in the world, which implies around 3.5GB/month (assuming 400MB per hour of streaming video and 200Meg for 1K MOU).

Japan Wireless Data Supply Estimation

Source: J.P. Morgan estimates, Company data.

3G 4G 3G 4G 3G 4GTotal BTS 113,615 18,386 49,714 29,355 108,341 15,364

Total spectrum (MHz) 100 50 30 60 60 40

Average data capacity per BTS (Mbytes/month) 4,492,800 2,632,500 1,347,840 3,159,000 2,695,680 2,106,000

Total data capacity (Mbytes/month) 510,449,472,000 48,401,145,000 67,006,517,760 92,732,445,000 292,052,666,880 32,356,584,000

Subscriber base (mn) 55 6

Data capacity per subscriber (Mbytes/Month) 9,351 7,809 1,906 55,640 9,798 21,374

Average data usage per subscriber (Mbytes/Month) 632 2,532 720 2,532 895 2,532

Current capacity utilization 7% 32% 38% 5% 9% 12%

KDDI Softbank

37 31

NTT DoCoMo

USD monthly Income (RHS) vs. % spend on wireless services (LHS)

Source: J.P. Morgan estimates, Company data

3/4G Network Utilization Rates


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https://mm.jpmorgan.com/PubServlet?action=open&doc=GPS-1024424-0.pdf





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James R. Sullivan, CFA(65) [email protected]

Economics of Wireless Data Reports

The Economics of Wireless Data Part One: The Importance of Population Density and Spectrum 4th May 2011

The Economics of Wireless Data India Edition: Data Services, the opportunity near and far 1st June 2011

The Economics of Wireless Data Industry Dialogues: A Discussion with CSL’s CMO 6th July 2011

The Economics of Wireless Data Industry Dialogues: The Rise of the Incumbents –A discussion with KTC 26th November 2011

The Economics of Wireless Data Part Two: Valuing Air 7th December 2011

The J.P. Morgan Global Telco Call: Economics of Wireless Data 16th January 2012

The Economics of Wireless Data Part Three: What LTE means for Asia 26th March 2012

The Economics of Wireless Data Part Four: Indonesia Country View 23rdNovember 2012

The Economics of Wireless Data Part Four: Taiwan Country View 3 December 2012

The Economics of Wireless Data Part Four: China Country View 7 December 2012

The Economics of Wireless Data Part Four: Korea Country View 8 January 2013

Table of ContentsEconomics of Wireless Data Reports .....................................2

Japan in Context: Key Charts..................................................3

Supply Forecasting: Quick Review.........................................5

Supply vs. Demand vs. Pricing: Japan.................................10

Company Capacity Estimate Details.....................................13

Appendix I: Tables and Figures Index .................................15
















3



Japan in Context: Key Charts

Data affordability

Figure 1: USD monthly Income (RHS) vs. % spend on wireless services (LHS)


Figure 2: Strong negative correlation between USD Monthly Income (x-axis) and % spent on wireless services (y-axis)


Figure 3: USD per GB, Select Markets


Figure 4: Data Pricing (RHS) relative to Income (LHS)


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y = -3E-06x + 0.0196R² = 0.6248

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4



Data Usage levels

Figure 5: 3/4G Network Utilization Rates


Figure 6: 3/4G Elasticity estimates


Figure 7: Monthly data levels per user (GB/Month)


Figure 8: Strong relationship between usage levels (x-axis GB/Month) and affordability (y-axis )


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Supply Forecasting: Quick Review

Our Global Telecom research team has been doing work on data capacity estimation for several years, beginning in 2008 (The Power of Mobile Broadband, 2nd May 2008) and extending through our Economics of Wireless Data and J.P. Morgan Global Telco Call pieces of the past two years (please see links to relevant reports on Page 2 of this report).

The major conclusion of much of this work is that, finally, we Telco analysts can become "real" industry analysts for the first time. By that, we mean that we can run "normal" supply and demand analysis in order to take a view on the direction of pricing trends. This was next to impossible in a voice environment, given the scale-ability and fixed cost nature of voice networks. There is an explicit quality vs. quantity trade off available when running voice networks that makes capacity estimation something of a wild good chase. Data networks, as we've been saying for years now, work differently. Their lack of scale-ability (please see our The Economics of Wireless Data Part One: The Importance of Population Density and Spectrum for a detailed discussion of scale and data networks) implies a more variable cost nature, but also implies that for the first time in a very long time, we can estimate data capacity on a point estimate basis.

Data Estimation Equations

Data capacity estimation is actually a quite simple function…well, it can be. We initially began with a far more complex equation that included topography, population density, building density and the like, but found that for a rough estimate of overall network capacity, we did not learn much from these incremental data points. In the interests of simplicity (and the legacy of Ockham's razor: “among competing hypotheses, the one that makes the fewest assumptions should be selected”, or if you want to go way back, Numquam ponenda est pluralitas sine necessitate), we arrived at the following equation:

Figure 9: Wireless Data Capacity Supply Equation

Capacity = Constant x (Sectors x Carriers x Cell Rate x

Utilization) / Busy Hour

Source: J.P. Morgan.

Constant: simple numerical conversion factors to adjust Mbits to Mbytes and to adjust the per second calculation to a per month value.

Sectors: describes the number of sectors per base station. Sectors describe splitting a single base station into multiple directional base station sectors to reuse capacity. We take Sectors = 3 for all cases as this is the standard configuration for basestations. In a limited number of cases, further sectorisation might be undertaken, but we assume this will not be the usual case.

Carriers: describes the number of deployed 5Mhz carriers at each location. We assume the full 5Mhz is always available, however guard band requirements may reduce the incremental capacity available for the 2nd or 3rd carrier.





6



Cell Rate: describes whether the base station implements basic UMTS, HSPA, upgraded additional channels or an upgraded HSPA network in 700/900Mhz frequency range where indoor propagation characteristics are improved. CellRate should not be confused with peak data rate per user – instead it reflects the peak data rate the cell is capable of sustaining to all users in its coverage area.

Utilization: captures the maximum network utilization achieved in the busiest hour of the day. The network never operates at maximum capacity, despite some base stations operating near to 100% capacity, because traffic is unevenly distributed in time and place and individual base station upgrades add large incremental capacity. We expect base station capacity upgrades to occur when peak utilization surpasses 85%. We model utilization on a regional basis as per Table 1 which results in a network wide Utilization = 65%.

Table 1: Regional Distribution of network utilization

% sites 25% 30% 30% 15%Cell utilisation 85% 70% 55% 40%System utilisation 65%


Busy Hour Share: is a key sensitivity in the model, describing the percentage of daily traffic that occurs in the busiest hour of the day. We use operator data and set BusyHourShare = 15%. Note that BusyHourShare is lower than seen in mobile voice cases due to operator guidance that data usage is less ‘peaky’ than voice usage.

Below is a screen shot of our simplified Excel model used to calculate the capacity estimates in this report, please contact us for a copy.

Table 2: Wireless Data Supply Forecasting Equation for HSPA BTS –Details


a Sectors (max 3) 3

b Carrier size (MHz) 5

c Total Spectrum (MHz) 5

c/b = e I mplied Carriers 1

Cell Rate (b/s/Hz)

EDGE 0.33

WCDMA 1.00

HSPA 1.28

LTE 1.50

Current Technology HSPA

f Implied Cell Rate 1.28

g Busy Hour 15%

h Network Utilization 65%

i Constant 13,500

i * ((a * e * h)/g) Capacity per Base Station (Mbyte / Month) 224,640

7



Table 3: Wireless Data Supply Forecasting Equation for LTE BTS –Details


Spectrum Holdings

The following table shows the current spectrum holdings of the Japanese wireless carriers. We assume that NTT DoCoMo, KDDI and Softbank are using 50MHz, 60MHz and 40MHz of 4G spectrums respectively.

Figure 10: Japan Wireless Spectrum Banks

Source: Company Data and JP Morgan estimates.

a Sectors (max 3) 3

b Carrier size (MHz) 5

c Total Spectrum (MHz) 5

c/b = e Implied Carriers 1

Cell Rate (b/s/Hz)

EDGE 0.33

WCDMA 1.00

HSPA 1.28

LTE 1.50

Current Technology LTE

f Implied Cell Rate 1.50

g Busy Hour 15%

h Network Utilization 65%

i Constant 13,500

i * ((a * e * h)/g) Capacity per Base Station (Mbyte / Month) 263,250

Operator Technology Frequency Bandwidth

NTT DoCoMo 3G 800MHz 30MHz

LTE 800MHz 10MHz

LTE 1.5GHz 30MHz

3G 1.7GHz 40MHz

LTE 2.0GHz 10MHz

3G 2.0GHz 30MHz

KDDI 3G 800MHz 10MHz

LTE 800MHz 20MHz

LTE 1.5GHz 20MHz

3G 2.0GHz 20MHz

LTE 2.0GHz 20MHz

WiMAX 2.5GHz 30MHz

Softbank 3G 900MHz 10MHz

3G 1.5GHz 20MHz

3G 2.0GHz 30MHz

LTE 2.0GHz 10MHz

AXGP(TDLTE) 2.5GHz 30MHz

8



Spectrum vs. BTS

Figure 11: Japan Wireless Carrier Base Station Infrastructure


Figure 12: 4G subscribers per 4G BTS driven by Spectrum Bank


Figure 13: 4G subscribers per 4G BTS per Mhz


Figure 14: 4G Spectrum vs. Average Data Capacity per 4G BTS


Figure 15: 4G BTS Count / Total 4G Data Capacity Estimate


113,615

49,714

108,341

18,386

29,355

15,364

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NTT DoCoMo KDDI Softbank

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2,106,000

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LHS: Average data capacity per 4G BTS (Mbytes/month) RHS: 4G spectrum (MHz)

18,386

29,355

15,364

48,401,145,000

92,732,445,000

32,356,584,000

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9



The calculations above drive the conclusions below, namely that current data capacity per 4G subscriber ranges from 54G for KDDI to 8G for NTT DoCoMo.

Table 4: Japan Wireless Data Supply Estimates per Operator: Detail


3G 4G 3G 4G 3G 4GTotal BTS 113,615 18,386 49,714 29,355 108,341 15,364

Total spectrum (MHz) 100 50 30 60 60 40

Average data capacity per BTS (Mbytes/month) 4,492,800 2,632,500 1,347,840 3,159,000 2,695,680 2,106,000

Total data capacity (Mbytes/month) 510,449,472,000 48,401,145,000 67,006,517,760 92,732,445,000 292,052,666,880 32,356,584,000

Subscriber base (mn) 55 6

Data capacity per subscriber (Mbytes/Month) 9,351 7,809 1,906 55,640 9,798 21,374

Average data usage per subscriber (Mbytes/Month) 632 2,532 720 2,532 895 2,532

Current capacity utilization 7% 32% 38% 5% 9% 12%

KDDI Softbank

37 31

NTT DoCoMo

10



Supply vs. Demand vs. Pricing: Japan

Unit Pricing and Usage elasticity

Table 5: Average data usage per month per user as of Sept-12– Detail


Table 6: Japan Wireless Data Elasticity calculations

Source: J.P. Morgan estimates.

Figure 16: Japan wireless data elasticity – Time Series -4G

Source: J.P. Morgan estimates.

Average data usage per sub per month (MB) 3G 4G

DoCoMo

smartphone 1,946 Company data 2,532 Company data

feature 195 Assume smartphone users' data usage is ten times that of feature phone users

Average 632 Assume 25% of DoCoMo's 3G users use smartphones 2,532

KDDI

smartphone 1,946 Assume same as DoCoMo. 2,532 Assume same as DoCoMo.


Average 720 Assume 30% of KDDI's 3G users use smartphones 2,532

Softbank

smartphone 1,946 Assume same as DoCoMo. 2,532 Assume same as DoCoMo.


Average 895 Assume 40% of Softbank's 3G users use smartphones 2,532


Average data unit price (USD/GB) 37 39 29

change (Mar-12 vs. Sep-12) -33% -5% -26%

Current data usage per sub (GB/month) 0.81 0.78 0.95

change (Mar-12 vs. Sep-12) 55% 74% 44%

Elasticity 1.7 14.5 1.7

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Softbank:Elasticity =1.7

KDDI:Elasticity =14.5

DoCoMo:Elasticity =1.7

11



Capacity Utilization: Intersection of spectrum / pricing / infrastructure

The above analysis combined leads to our conclusion that data network capacity utilization (4G) in Japan ranges from 32% (DoCoMo) to 5% (KDDI).

Figure 17: 4G capacity Utilization estimates for Japanese Wireless Carriers

Source: J.P. Morgan estimates. Note: Average per sub data usages for KDDI and Softbank are J.P. Morgan estimates.

Why do we care about capacity utilization?

One of the exciting things about finally finding the ability to run traditional supply / demand analysis on this sector is the ability to take a structural view as to pricing trends. In general, markets with significant excess network capacity are ripe for unit price declines, for the same reason that this maxim is true in other industries. Supply and Demand meet at a clearing price on a longer term basis, this is as true for telecom operators is it is in steel, oil, or iPhones.

7,809

55,640

21,374

2,532 2,532 2,532

32%

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12



Figure 18: Japan Telecom Mobile EBITDA margin trends


Figure 19: Japan Mobile Sector absolute CAPEX trends


Figure 20: Mobile capex as % of mobile service revenue trends


20%

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2008 2009 2010 2011 2012 2013E


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13



Company Capacity Estimate Details

Table 7: NTT DoCoMo Detailed Analysis of Wireless Data Supply vs. Demand


Table 8: KDDI Detailed Analysis of Wireless Data Supply vs. Demand


NTT DoCoMo 3G 4G

Data used (Tbyte / Month) 32,918 14,967

Subscribers (Mn) 55 6

Data revenue per user per month (Yen)


Data usage per month per subscriber (MBs)

Spectrum (MHz)

Total 100 50

800 30 10

1500 30

1700 40

2000 30 10

BTS

BTS 113,615 18,386

HSPA as % of 3G 100%

Subscribers per BTS 480 337

Subscribers per MHz per BTS 5 7

Capacity per BTS

HSPA 4,492,800

FD-LTE 2,632,500

Total Capacity 510,449,472,000 48,401,145,000

Capacity per sub per month 9,351 7,809

Current capacity utilization 7% 32%

2,675

37

826

KDDI 3G 4G

Data used (Tbyte / Month) 24,132 4,024

Subscribers (Mn)




Spectrum (MHz)

Total 30 60

800 10 20

1500 20

2000 20 20

BTS

BTS 49,714 29,355




Capacity per BTS

HSPA 1,347,840

FD-LTE 3,159,000

Total Capacity 67,006,517,760 92,732,445,000



37

802

2,719

38.5

14



Table 9: Softbank Detailed Analysis of Wireless Data Supply vs. Demand


Softbank

Data used (Tbyte / Month) - assuming per subs usage same as NTT DoCoMo 25,442 3,655

Subscribers (Mn) 30 2

Subscribers (Mn)




Spectrum (MHz)

Total 60 40

900 10

1500 20

2000 30 40

BTS

BTS 108,341 15,364




Capacity per BTS

HSPA 2,695,680

FD-LTE/TD-LTE 2,106,000

Total Capacity 292,052,666,880 32,356,584,000



29.1

974

2,497

31

15



Appendix I: Tables and Figures Index

TablesTable 1: Regional Distribution of network utilization...............................................6

Table 2: Wireless Data Supply Forecasting Equation for HSPA BTS –Details..........6

Table 3: Wireless Data Supply Forecasting Equation for LTE BTS –Details.............7

Table 4: Japan Wireless Data Supply Estimates per Operator: Detail........................9

Table 5: Average data usage per month per user as of Sept-12– Detail ...................10

Table 6: Japan Wireless Data Elasticity calculations ..............................................10

Table 7: NTT DoCoMo Detailed Analysis of Wireless Data Supply vs. Demand....13

Table 8: KDDI Detailed Analysis of Wireless Data Supply vs. Demand.................13

Table 9: Softbank Detailed Analysis of Wireless Data Supply vs. Demand.............14

FiguresJapan Wireless Data Supply Estimation ...................................................................1

Figure 1: USD monthly Income (RHS) vs. % spend on wireless services (LHS) .......3

Figure 2: Strong negative correlation between USD Monthly Income (x-axis) and % spent on wireless services (y-axis) ...........................................................................3

Figure 3: USD per GB, Select Markets ....................................................................3

Figure 4: Data Pricing (RHS) relative to Income (LHS) ...........................................3

Figure 5: 3/4G Network Utilization Rates ................................................................4

Figure 6: 3/4G Elasticity estimates ..........................................................................4

Figure 7: Monthly data levels per user (GB/Month) .................................................4

Figure 8: Strong relationship between usage levels (x-axis GB/Month) and affordability (y-axis ) ..............................................................................................4

Figure 9: Wireless Data Capacity Supply Equation ..................................................5

Figure 10: Japan Wireless Spectrum Banks..............................................................7

Figure 11: Japan Wireless Carrier Base Station Infrastructure ..................................8

Figure 12: 4G subscribers per 4G BTS driven by Spectrum Bank.............................8

Figure 13: 4G subscribers per 4G BTS per Mhz.......................................................8

Source: J.P. Morgan estimates, Company data. ........................................................8

Figure 14: 4G Spectrum vs. Average Data Capacity per 4G BTS..............................8

Figure 15: 4G BTS Count / Total 4G Data Capacity Estimate...................................8

Figure 16: Japan wireless data elasticity – Time Series -4G....................................10

Figure 17: 4G capacity Utilization estimates for Japanese Wireless Carriers...........11

Figure 18: Japan Telecom Mobile EBITDA margin trends .....................................12

Figure 19: Japan Mobile Sector absolute CAPEX trends ........................................12

Figure 20: Mobile capex as % of mobile service revenue trends .............................12

16



Companies Recommended in This Report (all prices in this report as of market close on 21 January 2013)KDDI (9433) (9433.T/¥6,200/Not Rated), NTT DOCOMO (9437) (9437.T/¥132,100/Neutral), SOFTBANK (9984) (9984.T/¥2,968/Overweight)

Analyst Certification: The research analyst(s) denoted by an “AC” on the cover of this report certifies (or, where multiple research analysts are primarily responsible for this report, the research analyst denoted by an “AC” on the cover or within the document individually certifies, with respect to each security or issuer that the research analyst covers in this research) that: (1) all of the views expressed in this report accurately reflect his or her personal views about any and all of the subject securities or issuers; and (2) no part of any of the research analyst's compensation was, is, or will be directly or indirectly related to the specific recommendations or views expressed by the research analyst(s) in this report.

Important Disclosures

Lead or Co-manager: J.P. Morgan acted as lead or co-manager in a public offering of equity and/or debt securities for NTT DOCOMO (9437) within the past 12 months.

Beneficial Ownership (1% or more): J.P. Morgan beneficially owns 1% or more of a class of common equity securities of KDDI (9433), NTT DOCOMO (9437).

Client: J.P. Morgan currently has, or had within the past 12 months, the following company(ies) as clients: SOFTBANK (9984), KDDI (9433), NTT DOCOMO (9437).

Client/Investment Banking: J.P. Morgan currently has, or had within the past 12 months, the following company(ies) as investment banking clients: KDDI (9433), NTT DOCOMO (9437).

Client/Non-Investment Banking, Securities-Related: J.P. Morgan currently has, or had within the past 12 months, the following company(ies) as clients, and the services provided were non-investment-banking, securities-related: SOFTBANK (9984), KDDI (9433), NTT DOCOMO (9437).

Client/Non-Securities-Related: J.P. Morgan currently has, or had within the past 12 months, the following company(ies) as clients, and the services provided were non-securities-related: SOFTBANK (9984), KDDI (9433).

Investment Banking (past 12 months): J.P. Morgan received in the past 12 months compensation for investment banking KDDI (9433), NTT DOCOMO (9437).

Investment Banking (next 3 months): J.P. Morgan expects to receive, or intends to seek, compensation for investment banking services in the next three months from KDDI (9433), NTT DOCOMO (9437).

Non-Investment Banking Compensation: J.P. Morgan has received compensation in the past 12 months for products or services other than investment banking from SOFTBANK (9984), KDDI (9433), NTT DOCOMO (9437).

J.P. Morgan is acting as financial advisor to KDDI Corporation in connection with its tender offer for shares of Jupiter Telecommunications Co., Ltd. with a company jointly held with Sumitomo Corporation as announced on October 24, 2012. The transaction is subject to necessary approvals by the regulatory authorities. This research report and the information herein is not intended to provide voting advice, serve as an endorsement of the proposed transaction or result in procurement, withholding or revocation of a proxy or any other action by a security holder.

Company-Specific Disclosures: Important disclosures, including price charts, are available for compendium reports and all J.P. Morgan–covered companies by visiting https://mm.jpmorgan.com/disclosures/company, calling 1-800-477-0406, or e-mailing [email protected] with your request. J.P. Morgan’s Strategy, Technical, and Quantitative Research teams may screen companies not covered by J.P. Morgan. For important disclosures for these companies, please call 1-800-477-0406 or e-mail [email protected].

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17



Date Rating Share Price (Y)

Price Target (Y)

14-Oct-08 N 1147 1860

22-Jul-09 UW 1848 1910

22-Dec-09 UW 2130 2030

12-Apr-10 UW 2295 2380

14-Jul-10 UW 2493 2520

14-Jan-11 UW 2834 2720

04-Feb-11 UW 2874 2910

10-Jan-12 OW 2285 3000

02-Jul-12 OW 2958 3500

21-Nov-12 OW 2863 3800


Price Target (Y)

22-Dec-09 OW 4770 9490

12-Apr-10 OW 4845 9410

26-Apr-10 OW 4595 8050

14-Jan-11 OW 4845 8140

10-Jan-12 N 5010 5000

10-Oct-12 N 5750 6000

26-Oct-12 NR 6370 --

0

909

1,818

2,727

3,636

4,545

5,454

Price(Y)

Aug08

May09

Feb10

Nov10

Aug11

May12

Feb13

SOFTBANK (9984) (9984.T, 9984 JT) Price Chart

UW Y2,520 UW Y2,910

N Y1,860 UW Y1,910UW Y2,030UW Y2,380 UW Y2,720 OW Y3,000OW Y3,500OW Y3,800

Source: Bloomberg and J.P. Morgan; price data adjusted for stock splits and dividends.

Initiated coverage Oct 14, 2008.

0

1,137

2,274

3,411

4,548

5,685

6,822

7,959

9,096

10,233

Price(Y)

Sep09

Dec09

Mar10

Jun10

Sep10

Dec10

Mar11

Jun11

Sep11

Dec11

Mar12

Jun12

Sep12

Dec12

KDDI (9433) (9433.T, 9433 JT) Price Chart

OW Y8,050 NR

OW Y9,490OW Y9,410 OW Y8,140 N Y5,000 N Y6,000


Initiated coverage Dec 22, 2009.

18




Price Target (Y)

30-Apr-09 N 137000 165000

22-Jul-09 N 137400 175000

14-Jan-11 N 145000 180000

10-Jan-12 OW 142500 160000

05-Nov-12 N 116600 125000

The chart(s) show J.P. Morgan's continuing coverage of the stocks; the current analysts may or may not have covered it over the entire period. J.P. Morgan ratings or designations: OW = Overweight, N= Neutral, UW = Underweight, NR = Not Rated

Explanation of Equity Research Ratings, Designations and Analyst(s) Coverage Universe: J.P. Morgan uses the following rating system: Overweight [Over the next six to twelve months, we expect this stock will outperform the average total return of the stocks in the analyst’s (or the analyst’s team’s) coverage universe.] Neutral [Over the next six to twelve months, we expect this stock will perform in line with the average total return of the stocks in the analyst’s (or the analyst’s team’s) coverage universe.] Underweight [Over the next six to twelve months, we expect this stock will underperform the average total return of the stocks in the analyst’s (or the analyst’s team’s) coverage universe.] Not Rated (NR): J.P. Morgan has removed the rating and, if applicable, the price target, for this stock because of either a lack of a sufficient fundamental basis or for legal, regulatory or policy reasons. The previous rating and, if applicable, the price target, no longer should be relied upon. An NR designation is not a recommendation or a rating. In our Asia (ex-Australia) and U.K. small- and mid-cap equity research, each stock’s expected total return is compared to the expected total return of a benchmark country market index, not to those analysts’ coverage universe. If it does not appear in the Important Disclosures section of this report, the certifying analyst’s coverage universe can be found on J.P. Morgan’s research website, www.jpmorganmarkets.com.

Coverage Universe: Sullivan, James: 21Vianet Group Inc. (VNET), AXIATA Group Berhad (AXIA.KL), Advanced Info Services (ADVA.BK), Astro Malaysia Holdings Bhd (ASTR.KL), Digi (DSOM.KL), Globe Telecom (GLO.PS), M1 (MONE.SI), Manchester United Plc (MANU), Maxis Berhad (MXSC.KL), PT Indosat Tbk (ISAT.JK), PT Telekomunikasi Indonesia Tbk (TLKM.JK), PT XL Axiata Tbk (EXCL.JK), Philippine Long Distance Telephone Company (TEL.PS), Singapore Telecom (STEL.SI), StarHub (STAR.SI), Telekom Malaysia (TLMM.KL), Total Access Communication (DTAC.BK)

Hosoya, Hitoshi: All Nippon Airways (9202) (9202.T), Central Japan Railway (9022) (9022.T), East Japan Railway (9020) (9020.T), Japan Airlines (9201) (9201.T), KDDI (9433) (9433.T), Kawasaki Kisen (9107) (9107.T), Mitsui O.S.K. Lines (9104) (9104.T), NTT DOCOMO (9437) (9437.T), Nippon Telegraph and Telephone (9432) (9432.T), Nippon Yusen (9101) (9101.T), Odakyu Electric Railway(9007) (9007.T), SOFTBANK (9984) (9984.T), Tobu Railway (9001) (9001.T), Tokyu (9005) (9005.T), West Japan Railway (9021) (9021.T)

0

31,144

62,288

93,432

124,576

155,720

186,864

218,008

249,152

280,296

Price(Y)

Aug08

May09

Feb10

Nov10

Aug11

May12

Feb13

NTT DOCOMO (9437) (9437.T, 9437 JT) Price Chart

N Y175,000

N Y165,000 N Y180,000 OW Y160,000 N Y125,000


Initiated coverage Apr 30, 2009.

19



J.P. Morgan Equity Research Ratings Distribution, as of January 1, 2013

Overweight(buy)

Neutral(hold)

Underweight(sell)

J.P. Morgan Global Equity Research Coverage 44% 44% 12%IB clients* 53% 46% 34%

JPMS Equity Research Coverage 42% 49% 9%IB clients* 71% 62% 51%

*Percentage of investment banking clients in each rating category.For purposes only of FINRA/NYSE ratings distribution rules, our Overweight rating falls into a buy rating category; our Neutral rating falls into a hold rating category; and our Underweight rating falls into a sell rating category. Please note that stocks with an NR designation are not included in the table above.

Equity Valuation and Risks: For valuation methodology and risks associated with covered companies or price targets for covered companies, please see the most recent company-specific research report at http://www.jpmorganmarkets.com, contact the primary analyst or your J.P. Morgan representative, or email [email protected].

Equity Analysts' Compensation: The equity research analysts responsible for the preparation of this report receive compensation based upon various factors, including the quality and accuracy of research, client feedback, competitive factors, and overall firm revenues.

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"Other Disclosures" last revised January 1, 2013.

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