credit suisse peers

DISCLOSURE APPENDIX AT THE BACK OF THIS REPORT CONTAINS IMPORTANT DISCLOSURES, ANALYST CERTIFICATIONS, LEGAL ENTITY DISCLOSURE AND THE STATUS OF NON-US ANALYSTS. US Disclosure: Credit

Suisse 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.

14 November 2016 Global

Equity Research Investment Strategy

Credit Suisse PEERs The Credit Suisse Connections Series leverages our

exceptional breadth of macro and micro research to deliver

incisive cross-sector and cross-border thematic insights for

our clients.

Research Analysts

Richard Kersley

44 20 7888 0313

[email protected]

Eugene Klerk

44 20 7883 4678

[email protected]

Marcelo Preto

44 207 888 0873

[email protected]

Brandon Vair

44 20 7888 6381

[email protected]

Stephanie MacAulay

44 20 7883 3958

[email protected]

THEME

A chain reaction: Supply chain strategies

Mapping the supply chain of companies to better understand their risk exposure and look for lateral investment opportunities is a potentially rich seam for research. We have revisited and extended our own prior analysis to examine whether information inefficiencies implicitly exist across the supply chain linking companies in a way that offers opportunities for investors to extract excess return. Academic research has pointed to such persistent return potential. Has the market become more efficient? Our analysis suggests a customer-supplier price signal continues to offer alpha-generating potential.

■ Credit Suisse's proprietary global relationship database (PEERs) provides a unique and high-quality tool with which to conduct supply chain analysis and with the advantage of drawing from a live dataset. We have extended the reach and depth of our database over the past several years to cover 3,400 companies and 110,000 of their business relationships. PEERs has been built bottom-up by our analysts, enhancing the quality of the output.

■ While stressing important caveats, we find modelling a simple long/short trading strategy based around global supplier reactions to earnings events in their respective customers, generated excess returns of 6-7% annualised, and approaching 10% for small cap stocks. These results are based on analysing 48,000 earnings events since 2010.

■ What's more important is knowing where to look for the most rewarding signals. Our dataset disaggregates the data by sector. We find the technology, capital goods and consumer sectors have driven double-digit supplier returns. Perhaps owing to the openness of the economies and international nature of the companies, we find Europe as fertile ground for supply chain investing.

■ We also analyse which customer stocks have typically provided the most reliable signals to their suppliers' stock prices following earnings-related share-price moves. A subset of global names appears below. The linked suppliers clearly stretch beyond their regions. In turn, we have examined which stocks have proved to be the clearest and most consistent 'supply chain' trades stemming from such signals.

Figure 1: "The Watch List": companies with consistent supplier signals

Note: Signals reflect earnings surprises, which we define here as share-price moves of over +/-5% over the five days surrounding an earnings release date. The 'Avg hit rate' refers to % of profitable trades. Based on data from January 2010 to December 2015.

Source: Company data, Credit Suisse research, Credit Suisse PEERs

Name Country Industry# of

signals

Avg. hit

rateName Country Industry

# of

signals

Avg. hit

rate

TJX USA Specialty Retail 5 76% Nike 'B' USA Textiles & Lux. 9 60%

Sekisui House Japan Cons Dur & App. 5 70% Occidental Ptl. USA Int. Oil & Gas 8 60%

Volkswagen Germany Automobiles 8 69% Alibaba Group China Internet Retail 8 60%

Astra Intl Indonesia Automobiles 7 67% Apache USA Oil & Gas E & P 7 60%

Norsk Hydro Norway Metals & Mining 8 66% Hitachi Japan Tech HW & Equip. 7 59%

Baker Hughes USA O&G Equip. & Svs. 11 66% Boeing USA Aero & Def 6 57%

Newfield Exp USA Energy 18 61% Micron Tech. USA Semiconductors 18 57%

BT Group UK Telecoms 7 60% Rolls-Royce UK Aero & Defense 4 56%

American Airlines USA Airlines 20 60% Samsung Electron. S.Korea Tech HW & Equip. 4 55%

Tata Motors India Automobiles 11 60% Kia Motors S.Korea Automobiles 12 55%

14 November 2016

Credit Suisse PEERs 2

Table of contents

Key charts 3

I Executive summary 4

II Mapping the supply chain 7

The PEERs Map ....................................................................................................... 7

III A shock to the system 9

Alpha in the supply chain .......................................................................................... 9

Sector signals – what really matters ....................................................................... 15

Welcome to the real world ...................................................................................... 21

It's all about stocks .................................................................................................. 23

Limitations of the analysis ....................................................................................... 28

Conclusions ............................................................................................................. 29

Appendix 1: Earnings surprise methodology 30

Scope and universe ................................................................................................ 30

Earnings surprise .................................................................................................... 30

Quintile formation .................................................................................................... 31

Trading strategy ...................................................................................................... 32

Results of significance test ..................................................................................... 33

Appendix 2: Sector back-tests 34

Top and bottom quintiles excess returns by sector ................................................ 35

Appendix 3: Stock screens 37

Appendix 4: Further reading 39

Appendix 5: How to find Credit Suisse PEERS 41

The team wishes to acknowledge the immense contributions made to this report by Akanksha Kharbanda

and Mahadevan Subramanian, employees of CRISIL Global Research and Analytics, a business division

of CRISIL Limited, a third-party provider of research services to Credit Suisse.

14 November 2016


Key charts Figure 2: The Apple supply chain: cumulative

performance post Apple's Jan 2015 earnings (%)

Figure 3: Apple supplier relative performance post

27/1/15 results surprise (subsequent 40 days)

Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse PEERS, Credit Suisse research

Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse PEERS, Credit Suisse research

Figure 4: A long/short strategy focused on global

PEERs suppliers indicates excess returns…

Figure 5: …while small cap further leverages the

strategy

Note: Based on data from January 2010 to December 2015. Source: Credit Suisse PEERS, Credit Suisse research

Note: Based on data from January 2010 to December 2015. Source: Credit Suisse PEERS, Credit Suisse research

Figure 6: Some sector signals have been stronger Figure 7: What stocks have given the best signals?

Past performance should not be taken as an indication or guarantee of future performance. Note: Based on data from January 2010 to December 2015. Source: Credit Suisse PEERS, Credit Suisse research

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% against the industry group benchmark over the five days surrounding an earnings release date. The 'Avg hit rate' refers to % of profitable trades. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse PEERS, Credit Suisse research

+5.6%

+6.5%

-2%

0%

2%

4%

6%

8%

10%

12%

T-2 T T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Relative returns for suppliers Apple relative returns

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-0.28%

+0.58%

-0.4%

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-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Bottom Quintile Top Quintile

8.5%

6.2%

4.6%

3.1%

4.7%

9.2%8.8%

12.4%

4.4%

6.0%

4.9%

15.3%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

2010 2011 2012 2013 2014 2015

All Stocks Small Cap

Sector Stability

Ann. Excess

Returns

Relation-

ships

Earnings

events

All sectors Good 6.06% 8,442 15,372

Consumer Staples Good 16.64% 774 882

Financials Good 5.45% 407 885

Health Care Good 5.50% 494 736

Industrials Good 6.28% 1100 2500

Information Technology Good 5.91% 1358 2417

Telecom. Services Good 18.87% 352 421

Energy Moderate 7.53% 932 1036

Materials Moderate 4.95% 514 1377

Consumer Discretionary Poor 0.71% 2,127 3,628

Utilities Poor -7.08% 332 475

Name Country Industry# of

signals

Avg. hit

rate

TJX USA Specialty Retail 5 76%

Sekisui House Japan Cons Dur & App. 5 70%

Volkswagen Germany Automobiles 8 69%

Astra Intl Indonesia Automobiles 7 67%

Norsk Hydro Norway Metals & Mining 8 66%

Baker Hughes USA O&G Equip. & Svs. 11 66%

Newfield Exp USA Energy 18 61%

BT Group UK Telecoms 7 60%

American Airlines USA Airlines 20 60%

Tata Motors India Automobiles 11 60%

Nike 'B' USA Textiles & Lux. 9 60%

Occidental Ptl. USA Int. Oil & Gas 8 60%

Alibaba Group China Internet Retail 8 60%

Apache USA Oil & Gas E & P 7 60%

Hitachi Japan Tech HW & Equip. 7 59%

Boeing USA Aero & Def 6 57%

Micron Tech. USA Semiconductors 18 57%

Rolls-Royce UK Aero & Defense 4 56%

Samsung Electron. S.Korea Tech HW & Equip. 4 55%

Kia Motors S.Korea Automobiles 12 55%

14 November 2016


I Executive summary Using the unique resource provided by Credit Suisse's supply chain tool PEERs, the aim

of this report is to consider the network of relationships surrounding companies and

sectors and the relevance these connections have for investors. Industry- and firm-specific

effects are, of course, key for understanding corporate performance, but to what extent do

lateral connections have a material impact and carry risk across the entire value chain?

While there are a wide range of different topics that relate to such a theme, we examine

just one here – how sensitive are stocks to surprises within their supply chains? We

highlight the following:

■ Having substantially increased the scope and depth of our supply chain database

through 2016, we revisit and update the analysis we first conducted in 2010 published in

Global Equity Themes: Exploiting Earnings Surprises (25 October 2010). Do

inefficiencies in the flow of information across the supply chain exist, providing

opportunities for systematic alpha generation?

■ Ad hoc evidence of stock moves amongst the constituents of the likes of Apple's supply

chain around Apple events provides general support for the merits of such a thesis.

However, to test this view, we have analyzed the impact across the supply chain of out-

size share-price movements or 'surprises' of 48,000 global earnings events from 2010-

2015. This significantly extends our initial work.

■ Our analysis indicates a potential annualised excess return of 6-7% from what is, in our

view, a conservative long/short strategy of buying/selling suppliers to a given company

when the company reports a positive or negative 'earnings surprise'. For the purposes of

our analysis, the term 'earnings surprise' refers to a material share-price move in the

stock on the days surrounding the event rather than the size of the beat/miss itself.

■ Restricting our focus to smaller-cap names, our data indicate annualised returns would

have increased closer to 10% (if at higher liquidity cost). Our approach is somewhat

simplistic and not without its caveats, which we discuss in detail. However, we also

conduct no sophisticated optimisation by using other factors to try and enhance returns.

Our results meet tests for statistical significance.

■ If results of this nature confirm plenty of academic and more sophisticated work in this

field (see Appendix 4 for more), our analysis brings three aspects of differentiation. First,

the back-testing and our results are based around a global rather than US dataset.

Second, having data built bottom-up by our analysts provides enhanced quality to the

data used. Third, it can be applied "live" given the nature of PEERs.

■ As much as the headline results, what is of particular value is identifying where the

signals within the market are strongest. We examine this at a sector level and find areas

where sectors merit the most attention and those where they are less relevant. We find

signals within technology (semis), industrials (capital goods/aerospace) and consumer

(consumer durables/retail) as key consistent areas for focus.

■ We take back-tests (which cynics will say always work) as close as possible to the real

world and identify which stocks have provided the strongest signals. US companies are

prominent owing to their global reach, but their links extend into regions well beyond the

US. A summary is detailed in Figure 8. We also detail the stocks that consistently have

proven sensitive to signals from their PEERs customers (Figure 9).

■ Given this quantitative approach may not appeal to all, we would flag prior supply chain

analysis by Credit Suisse, notably from Michael Mauboussin and Dan Callahan in their

report, Measuring the Moat, 1 November 2016, leveraging the concept of industry

mapping to assess competitive positioning upon which PEERs is essentially based. We

have also considered the topic of systemic shocks to the supply chain, such as the

dislocation following the tsunami and Fukushima disaster in Japan: Global Equity

Themes: Japanese Supply Chain Disruptions, 17 March 2011 (See Appendix 4 for

more.)

https://plus.credit-suisse.com/r/yalzXs

https://plus.credit-suisse.com/r/V6fkr51AF-WElY95

https://plus.credit-suisse.com/r/yalz9w


14 November 2016


Figure 8: "The Watch List": companies with consistent supplier signals (vs MSCI industry benchmark)

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% against the industry group benchmark over the five business days surrounding an earnings release date. Stocks in bold are under Credit Suisse coverage. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Company data, Credit Suisse research, Credit Suisse PEERs

Name Country GICS Level 2 Ind Grp # of signals,

T+2 / T-2

Average % of suppliers

whose T+40 / T+2

returns are in line with

customer surprise

High relevance suppliers

TJX USA Retailing 5 76% Federal Realty, Kimco Realty

Petrochina 'H' China Energy 4 72% Anton Oil, Green Dragon Gas, Jereh Group, SPT Energy

Sekisui House Japan Cons Dur & Apparel 5 70% LIXIL Group, Sekisui

Volkswagen Germany Auto & Components 8 69% BorgWarner, Constellium, Hella Hueck, Schaeffler

Astra International Indonesia Auto & Components 7 67% Surya Semesta

Valeo France Auto & Components 12 66% Nexans, Sandvik

Norsk Hydro Norway Materials 8 66% Seadrill

Baker Hughes USA Energy 11 66% Hunting, SBO

Luxottica Italy Cons Dur & Apparel 4 65% Macerich

Kansai Electric Pwr. Japan Utilities 8 64% Woodside

Anadarko Petroleum USA Energy 4 63% Forum Energy Tec, RPC, TETRA

Toyota Tsusho Japan Capital Goods 8 63% Infineon Technol, Toyota

Repsol Ypf Spain Energy 4 63% Seadrill

Enbridge Canada Energy 5 62% Cdn Natural Rsc

Priceline Group USA Retailing 19 62% Choice Htl Intl, Hilton Wrldwide, La Quinta

Bank Of America USA Banks 8 61%Boston Ppty, CBRE Group, Federal Realty, Proofpoint,

Textron

Phillips 66 USA Energy 4 61% Phillps 66 Ptns, Spectra Energy

Newfield Exploration USA Energy 18 61%

BT Group UK Telecoms 7 60% Computacenter

American Airlines USA Transportation 20 60%

Nike 'B' USA Cons Dur & Apparel 9 60% FT, Indorama Venture, Shenzhou Intl, Yue Yuen Ind

Alibaba Group China Software & Svs 8 60% Baozun

Occidental Ptl. USA Energy 8 60%

Apache USA Energy 7 60% Forum Energy Tec, Oil States Intl, Rowan

Expedia USA Retailing 14 59%Choice Htl Intl, Derwent London, Hilton Wrldwide, Hyatt

Hotels, La Quinta, Marriott Intnl, Starwood Hotels

Tata Motors India Auto & Components 11 60% Apollo Tyres, Bharat Forge

Royal Dutch Shell Netherlands Energy 4 59% KBR, Weir Group

Hitachi Japan Tech HW & Equip. 7 59% Allison Trn Hldg, Disco, Hitachi Metals, Proofpoint

Tripadvisor USA Retailing 14 58%Expedia, Hilton Wrldwide, Hyatt Hotels, La Quinta, Marriott

Intnl, Priceline Group, Starwood Hotels

Jd.Com China Retailing 5 58% GLP

Encana Canada Energy 8 58% TransCanada

Best Buy USA Retailing 16 58% LG Elec

Peugeot France Auto & Components 8 57%

Nissan Motor Japan Auto & Components 7 57%

Calsonic Kansei, Ichikoh Ind, JFE Holdings, Kobe Steel,

Mitsui Min & Sml, NGK Insulators, Nippon Sheet G,

NIPPON STEEL, NTN, Sumitomo EI, Takata, Topre,

Unipres

General Motors USA Auto & Components 5 57%

AK Steel, Alfa, HASCO, Interpublic, Isuzu, Johnson Ctrl, LG

Chem, Mando Corp, Next Auto, NGK Insulators, Rockwell

Auto, Takata, Teijin, Victrex, Worthington Ind

Nvidia USA Semis 15 57% CHROMA, SPIL, TSMC

Nippon Stl.& Sumit.Mtl. Japan Materials 7 57% Rio Tinto, Vale SA

Altice A Netherlands Media 7 57% Comcast

Boeing USA Capital Goods 6 57%

Alcoa, Constellium, Fuji Heavy, GE, Honeywell Intl, IHI,

Kaiser Aluminum, Kawasaki Heavy, Kennametal, MHI,

Orbital ATK, Precision Cast, Rolls-Royce Hldg, Safran,

Teijin, Toray Industries, Victrex, Zodiac Aero

Micron Technology USA Semis 18 57%Advantest, Applied, ChipMOS, HMI, Inotera, Lam

Research, Siltronic

Wesfarmers Australia Food & Staples Rtl 4 57% Breville, BWP Trust, DuluxGroup, Tassal Group

Sony Japan Cons Dur & Apparel 11 56% Disco, Merck, Samsung Elec

Cigna USA H/C Equip & Svs 9 56%Laboratory Corp, LifePoint Health, QuestDiagnostics,

Tenet Healthcare

Netflix USA Retailing 21 56% CBS Corp

Denso Japan Auto & Components 5 56% Disco, Toyota

Marriott Intl.'A' USA Consumer Services 4 56%

Kroger USA Food & Staples Rtl 6 56% Equity One, Regency Center

Interpublic Group USA Media 13 56%CBS Corp, Comcast, Discovery Commns, Time Warner,

Twenty-First Fox, Viacom, Walt Disney

Western Digital USA Tech HW & Equip. 10 56% Nidec, STMicroelectron, Teradyne

Halliburton USA Energy 9 56%Forum Energy Tec, Hi-Crush Partner, Hunting, SBO, U.S.

Silica

Akzo Nobel Netherlands Materials 9 56% Elementis

Amerisourcebergen USA H/C Equip & Svs 4 56% Allergan

Rolls-Royce Holdings UK Capital Goods 4 56% Alcoa, Bodycote, IHI, Kawasaki Heavy, Meggitt

Pembina Pipeline Canada Energy 8 55%

Samsung Electronics South Korea Tech HW & Equip. 4 55%

3M, AAC Tech, Advantest, Applied, ARM, ASML, AUO,

Disco, DNF, Goertek, Hirose Electric, Imagntn Tech, KAL,

KLA-Tencor, Lam Research, Lens Tech, ROEC, Rudolph

Tech, Seoul Semi, Shin-Etsu Chem, Siltronic, SK

Materials, Soul Brain, STMicro, Sumco, Tokyo Electron,

TSMT, Wacker Chemie, Wacom, Wonik Materials

14 November 2016


Figure 9: "Supply Chain Trades": Screen of suppliers that have consistently responded to customer

surprise signals

Note: Signals reflect a customer's earnings surprises, which we define here as share-price moves of over 5% against the industry group benchmark over the five business days surrounding an earnings release date. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Company data, Credit Suisse research, Credit Suisse PEERs

Customer Country Ind Group Supplier Country Ind Group # signals

% times supplier inline

with customer signal

over T+40 / T+2

Best Buy USA Retailing Activision USA Software 16 75%

Nokia Finland Communications Equip. Emerson Electric USA Electrical Equip. 14 79%

eBay USA Internet SW & Svs Equinix USA Equity REITs 13 77%

Interpublic Grp USA Advertising CBS Corp USA Broadcasting 13 77%

Cinemark Hldgs USA Movies & Entertainment Time Warner USA Movies & Entertainment 10 80%

Humana USA Managed Health Care Walgreens Boots USA Drug Retail 10 80%

Cigna USA Managed Health Care Universal Health USA Health Care Facilities 9 78%

DISH Network USA Cable & Satellite Comcast USA Cable & Satellite 9 78%

DISH Network USA Cable & Satellite Walt Disney USA Movies & Entertainment 9 78%

Express USA Health Care Services CVS Health USA Drug Retail 9 78%

Bank of America USA Diversified Banks MGIC Investment USA Thrifts & Mortgage Fin. 8 88%

Volkswagen Germany Automobiles BorgWarner USA Auto Parts & Equip. 8 75%

Norsk Hydro Norway Metals & Mining Baker Hughes USA Energy Equip. & Svs. 8 75%

Bank of America USA Diversified Banks MasterCard USA IT Services 8 75%

Occidental USA Integrated Oil & Gas Helmerich USA Oil & Gas Drilling 8 75%

American Airline USA Airlines Zodiac Aero France Aerospace & Defense 20 75%

Amazon.com USA Internet Retail Logitech Inter Switzerland Tech HW & Equip. 17 76%

Valeo France Auto Components Nexans France Electrical Equip. 12 75%

Tata Motors India Automobiles Koninklijke DSM Netherlands Chemicals 11 82%

Technip France Energy Equip. & Svs. Outokumpu Finland Steel 9 78%

Volkswagen Germany Automobiles RTL Group Luxembourg Broadcasting 8 75%

Renault France Automobiles Publicis Groupe France Advertising 8 75%

Renault France Automobiles ITV UK Broadcasting 8 75%

Norsk Hydro Norway Metals & Mining Transocn Switzerland Oil & Gas Drilling 8 75%

BT Group UK Telecoms Siemens Germany Capital Goods 7 86%

BT Group UK Telecoms Ericsson Sweden Communications Equip. 7 86%

Apache USA Oil & Gas E & P Rowan UK Oil & Gas Drilling 7 86%

Ford Motor USA Automobiles Johnson Matthey UK Chemicals 7 86%

Ford Motor USA Automobiles ArcelorMitta Luxembourg Steel 7 86%

Hess USA Oil & Gas E & P Subsea UK Energy Equip. & Svs. 7 86%

Sharp Japan Household Durables Disco Japan Semis 11 82%

Yamaha Motor Japan Automobiles NTN Japan Machinery 11 82%

Alfresa Holdings Japan H/C Providers & Svs Ono Pharm Japan Pharmaceuticals 9 78%

Alfresa Holdings Japan H/C Providers & Svs Sawai Pharm Japan Pharmaceuticals 9 78%

Alfresa Holdings Japan H/C Providers & Svs Mitsub Tanabe Japan Pharmaceuticals 9 78%

Toshiba Japan Capital Goods Nissha Printing Japan Comml. & Prof. Svs. 9 78%

Hino Motors Japan Capital Goods Sumitomo Rub Ind Japan Auto Components 8 88%

Hyundai Motor South Korea Automobiles Takata Japan Auto Components 8 88%

Toyota Tsusho Japan Capital Goods Tokai Rika Japan Auto Components 8 75%

Toyota Tsusho Japan Capital Goods Toyota Inds Japan Auto Components 8 75%

Toyota Tsusho Japan Capital Goods Toyota Boshoku Japan Auto Components 8 75%

Hino Motors Japan Capital Goods Denso Japan Auto Components 8 75%

Hino Motors Japan Capital Goods Toyoda Gosei Japan Auto Components 8 75%

Hino Motors Japan Capital Goods Nippon Yusen Japan Transportation 8 75%

Hino Motors Japan Capital Goods Bridgestone Japan Auto Components 8 75%

Nissan Japan Automobiles Aisan Industry Japan Auto Components 7 86%

Skyworks Solutns USA Semis JCET China Semis 21 71%

HP USA Tech HW & Equip. Realtek Semicon Taiwan Semis 13 77%

Royal Bank Scot UK Banks Iress Australia IT Services 12 75%

TEP Hldg Japan Electric Utilities Santos Ltd Australia Oil & Gas E & P 12 75%

Sharp Japan Household Durables AUO Taiwan Electronic Comp. 11 73%

Sharp Japan Household Durables Innolux Taiwan Electronic Comp. 11 73%

Sony Japan Household Durables MediaTek Taiwan Semis 11 73%

Sony Japan Household Durables EIH Taiwan Electronic Comp. 11 73%

Western Digital USA Tech HW & Equip. SK Hynix South Korea Semis 10 70%

Nike USA Apparel & Luxury Shenzhou Intl China Apparel & Luxury 9 78%

Skyworth Digit Hong Kong Household Durables Innolux Taiwan Electronic Comp. 8 75%

Matahari Putra Indonesia Food & Staples Rtl HM Sampoerna Indonesia Tobacco 8 75%

Kansai Elec Japan Electric Utilities Origin Energy Australia Integrated Oil & Gas 8 75%

Bank of America USA Banks Iress Australia IT Services 8 75%

Astra Intl Indonesia Automobiles Surya Semesta Indonesia Construction & Engin. 7 86%

USA

Europe

Japan

Asia Pac ex Japan

14 November 2016


II Mapping the supply chain

The PEERs Map

Credit Suisse PEERs maps out the relationships between companies and competitors,

customers, suppliers, joint ventures and partnerships for over 3,400 listed firms globally

and hence makes the concept of an industry map stock-specific and, importantly, dynamic,

as explained below. This mapping of over 110,000 relationships is built by Credit Suisse

analysts. Analysts classify the materiality of these relationships (high, moderate and low),

but only focus on relationships that are genuinely relevant to an investor.

Our dataset allows us to examine the supply chain of any given company in a dynamic

fashion, given we have approximately 10 years of time series data for the relationships

concerned. We recognise there are other sources of supply chain data available from the

likes of FactSet and Bloomberg. However, in our view, having such data built by the

analysts who cover and speak to the companies concerned provides added quality relative

to other data available in terms of insights and longevity, particularly in emerging markets.

Figure 10: PEERs map example – Marathon Oil Corp

Source: Credit Suisse PEERs

The oil industry is an apt worked example given its inherent end market connectivity.

Figure 10 focuses on the oil E&P company, Marathon, as an example. The PEERs map in

Figure 10 details customers and suppliers but also Marathon's key competitors,

partnerships, joint ventures and equity investments. The chart displays only relationships

of high and moderate relevance from Marathon's perspective. It should be stressed that

these are companies that our analyst views as important for Marathon, even if the reverse

is not the case. Within PEERs, we can follow the network further to track the relationships

built by our analysts from any of the companies in Marathon's network out into their own

ecosystem. For instance, Figure 11 shows Marathon's relationship to Baker Hughes. The

linkage goes on.

14 N

ovem

ber 2

01

6

Cre

dit S

uis

se

PE

ER

s

8

Figure 11: PEERs map example – Marathon Oil Corp


14 November 2016


III A shock to the system

Alpha in the supply chain

Testing for signals and related alpha generation in the supply chain is not a new topic for

us or for financial research more widely. A considerable body of work exists in this space

and is detailed in Appendix 4 of this report. Notably, a leading study by Professors of

Finance Lauren Cohen and Andrea Frazzini ("Economic Links and Predictable Returns",

Journal of Finance, 2008) examined how shocks to one firm rippled through to other firms

via supply or demand links, revealing a compelling price momentum trading strategy

based on the lagged response to signals from customers through to the performance of

their suppliers. This points to implicit inefficiencies in the flow of information across the

supply chain.

Our contribution to this analysis in our initial report, Global Equity Themes: Exploiting

Earnings Surprises (25 October 2010) focused on the response across the supply chain to

an event and specifically to an earnings surprise. The added value of this work was the

ability to leverage a global rather than just a US dataset (which a large proportion of the

academic data have been based on) to look for signals across countries and identify the

industries within them that provided the most meaningful sources of excess return.

While the approach was different from the Cohen/Frazzini paper, the results of information

inefficiencies pointing to persistent excess return were apparent. However, what also

stood out in our analysis was the differing importance of signals from one sector versus

another. We revisit this analysis here to see if the message has held true since our 2010

report. Has the market become more efficient in its discount mechanism and eroded this

excess return? We have also extended the analysis to consider the implications for small

cap stocks, where the results are striking. We have also sought to drill down to identify

which stocks have typically offered the best signaling quality.

Supply chain investing strategy

The simple question we posed in our original report was whether excess return could be

generated by buying and selling the suppliers into a given customer on a surprise on

earnings around its results. Our testing universe for the overall exercise in this report

comprises over 8,400 unique customer-supplier relationships with "high" and "medium"

relevance as determined by our analysts, measured from the perspective of the supplier.

The analysis covers over 2,500 unique customers and nearly 2,000 unique suppliers and

tested earnings events from January 2010 to December 2015. We have examined 48,000

earnings events, 15,000 of which qualified as an earnings surprise.

However, to simplify things, we first run through a worked example, focusing on a stock

that is well known for its supply chain sensitivities, Apple. Figure 12 shows the supply

chain for Apple as per our PEERs framework, similar to that displayed for Marathon in

Figure 10 , showing high and moderate relationships for Apple. The direction of this

relationship is important to stress, as the number of suppliers that are important for Apple

is far smaller than the companies who see Apple as key customer. In PEERs, the reverse

network of relationships reveals 30 suppliers for whom Apple is of high importance versus

the 14 that are of moderate and high relevance for Apple.

https://plus.credit-suisse.com/r/xrrOwN

https://plus.credit-suisse.com/r/xrrOwN

14 November 2016


Figure 12: PEERs map example – Apple Inc


In Figure 13 we have examined the price movements around the publication of Apple's

fiscal first quarter results on January 27th 2015 and the impact that the significant move in

Apple's stock price had on its suppliers in the weeks following. Apple's Q1 results were

indeed strong, reflecting a 30% increase in revenue and guidance for strong sustained

growth in the coming quarter. The results were accompanied by a series of product

launches, notably the Apple Watch, underpinning guidance. As shown in Figure 13 , the

stock price reaction was sharp. In the five days that straddled the results announcement,

the stock outperformed the global technology sector by 4.9%, reaching a relative peak of

10.6% 19 days on from the results before settling somewhat back but still recording 6.5%

outperformance over a 40-day period.

Figure 13 also shows the performance of Apple's suppliers post the strong results based

on an unweighted group of suppliers for whom Apple is of 'high relevance' in PEERs (i.e.

the reverse relationship to that referenced above). After a slow start, they began to

outperform and ultimately ended in relatively similar performance territory as Apple over

the same 40-day period. Figure 14 shows the performance of the specific suppliers

concerned. As one might expect, they are diverse in terms of both sector and geography.

We have shown their performance versus their own region and find that 21 out of 30

suppliers outperformed their regional benchmark during the period – a 'hit rate' of 70%.

The implication from this example would be one of information inefficiencies at work in the

transmission of the positive signal from Apple's surprise (which we have defined here and

14 November 2016


do elsewhere in the report via its share-price move) to other parts of the supply chain

witnessed in the lagged but ultimately positive reaction of its suppliers' stock prices. The

varied geographic and sector mix of its suppliers could be contributory factors. Of course,

before reaching any definitive conclusion, the key question is whether this is an isolated

(and convenient) example. What do the results across our whole dataset reveal? Does this

hypothesis stand up to scrutiny?

Figure 13: Cumulative excess returns of Apple vs MSCI Global Tech and its

suppliers vs respective regional benchmarks post the 27/1/15 earnings surprise

Source: Credit Suisse research, Thomson Reuters

Figure 14: Apple's suppliers' individual relative share price performance (vs

regional benchmarks) post Apple's 27/1/15 earnings surprise

Note: In this report, we define earnings surprises as share-price moves of over 5% against the industry group benchmark over the five days surrounding an earnings release date. Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse research, Thomson Reuters

+5.6%+6.5%

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

T-2 T+0 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Relative returns for suppliers Apple relative returns

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

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14 November 2016


Scaling the analysis

We set out our back-testing methodology in more detail in Appendix 2, but we summarise

the basic principles and results below. To conduct our analysis, we would stress that we

do not define a given earnings surprise as an estimate of a recorded earnings outturn

versus a prevailing consensus expectation, but rather the reaction of the stock price itself

– i.e. an 'earnings reaction model'. The thought process here is that the surprise may be

driven by the future 'guidance' offered with the results. Moreover, we consider the price

movement around the earnings announcement rather than only on the day itself. We may

have seen a stock move ahead of the results due to a read-across elsewhere or guidance

making a stated consensus estimate less reflective of a surprise.

Hence our earnings surprise is calculated as the price performance of the stock relative to

its MSCI sector benchmark during a five-day period. The five-day period is defined as T-2

to T+2, where T is the earnings release date. We have established a threshold of

materiality to define a surprise as excess returns of over +/-5% generated relative to its

sector benchmark in collecting surprises or events. While there is no inherent mystery in

this 5% threshold, we found a 5% relative move against the sector met a materiality test

when judged relative to typical volatility through time.

We start our analysis by clustering a customer's earnings surprises across our global

universe each semester into five equal quintiles. (Note that hereafter we refer to 'customer'

as the company standing at the centre of the PEERs map.) The top quintile represents a

strong positive earnings surprise whilst the bottom quintile represents strong negative

earnings surprise measured during the five days around the earnings announcement. For

each company in each quintile, we then calculate the relative performance of all

suppliers related to the customer globally against its regional benchmark during the

40-day period following the earnings surprise (i.e. T+2 to T+40).

Where a customer has multiple suppliers (which is often the case), the simple average of

all its suppliers' returns is calculated. We have taken only the suppliers where our analysts

view the relationship with the customer as being of high or moderate relevance. We

record the overall performance of a quintile as the average of the excess returns of

suppliers attributed to each customer in a quintile over the testing period.

Below we summarise the output from modelling a long/short strategy of buying/selling

suppliers to a given customer when the customer reports a positive or negative 'earnings

surprise'.

Long/short strategy

Figure 15 contrasts the supplier returns with their respective regional market benchmarks

in the top quintile versus the bottom quintile over the 40-day period from T+2. Figure 16

reflects the accumulated return of a 'long top quintile suppliers vs short bottom quintile

suppliers' strategy. The accumulated annualised return would have been an excess return

of 6.1% over the period. While still material (and still enough to compensate for likely

transaction costs), this positive result was slightly lower than the overall results we saw in

our initial report, where the average excess return was 7.8%. We look into the breakdown

of the results below. It should be stressed that we have not taken into account any

transaction costs in the back-testing.

14 November 2016


Figure 15: Excess returns of suppliers relative to

the market – all companies

Figure 16: Top minus bottom quintile excess

returns relative to the market – all companies

Global, all sectors Global, all sectors

Note: Based on data from January 2010 to December 2015. Source: Credit Suisse research, Thomson Reuters


If these overall results suggest a less than perfect flow of information across the global

network of relationships, we find this effect is magnified for small cap suppliers (which we

define here as stocks with market caps under US$3bn). Figures 17 and 18 replicate the

charts above for small caps. The outperformance over the 40-day period increases from

0.86% to 1.27% or from 6.1% to 9.0% on an annualised basis. Intuitively, this makes

sense to us. If there are going to be inefficiencies in information flow, it would not be

unreasonable to believe that less researched companies should reflect the greater impact.


the market – small cap


returns relative to the market – small cap

Global, all sectors, small cap Global, all sectors, small cap



-0.28%

+0.58%

-0.4%

-0.3%

-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40


-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

0.8%

0.9%

1.0%

T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

-0.38%

+0.89%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Bottom Quintile Top Quintile-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

14 November 2016


Stability of returns

A reasonable question is whether our overall average results are distorted in any sense by

an individual and out-size year. There has admittedly been some variability. Figure 19

examines the global returns year by year by combining each year's half-year returns to

provide annual data. Since 2010, the data confirm positive returns from the long/short

strategy in each year, with 2015 coming out as the best year, with annual average excess

returns of 9.2%. Clearly, we do not yet have 2016 returns.

Figure 19: Annualized supplier net excess returns Figure 20: Annualized supplier net excess returns

5% customer earnings surprise cut-off 10% customer earnings surprise cut-off



As we highlighted earlier, there was no mystery in our choice of 5% to define our surprise

threshold. Hence, we have also examined the potential returns of this strategy by focusing

on bigger surprises by raising our threshold for materiality to a 10% relative move in the

share price to define a surprise rather than 5%. The results did indicate higher annualized

returns of 7.1% (vs. 6.1% using a 5% cutoff) across the 2010-2015 period. However, we

found the year by year results were less consistent as we show in Figure 19. This may be

for sample size reasons rather than the squeezing out of inherently lower-volatility sectors

from our exercise and limiting the diversity. We highlight this issue amongst the range of

limitations of the exercise we have pursued.

8.5%

6.2%

4.6%

3.1%

4.7%

9.2%8.8%

12.4%

4.4%

6.0%4.9%

15.3%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

2010 2011 2012 2013 2014 2015


1.2% 0.8%

14.5%

-0.4%

2.3%

15.2%

4.6% 5.5%

18.2%

2.4%3.4%

30.4%

-5%

0%

5%

10%

15%

20%

25%

30%

35%

2010 2011 2012 2013 2014 2015


14 November 2016


Sector signals – what really matters

The structure and depth of our dataset allows us to drill down to analyse the signals by

sector and region. A message from our previous research was that the impact measured

by the excess return of a surprise in some sectors mattered more than in others,

suggesting the genuine economic relevance of the recorded supply chain differed across

the market. We test this again below.

In the bar chart in Figure 21 we rank the potential excess return generated by signals

from each sector concerned over the 40-day testing period (i.e. what would be the impact

of buying/selling suppliers stemming from a surprise in a given sector?). At first sight, the

signals from telecoms, consumer staples and energy appear stronger with the information

content in utilities, consumer discretionary and healthcare relatively weaker.


the market – all stocks


returns relative to the market – small cap

All stocks Small cap

Note: Based on data from January 2010 to December 2015. Source: Credit Suisse research Note: Based on data from January 2010 to December 2015. Source: Credit Suisse research

There are three important points to stress here to put this analysis in context. First, we are

just looking at MSCI Level 1 sectors. As we touch on later, the signaling of certain sub-

sectors within the top level can differ considerably. Moreover, as we show later, the

signalling of specific stocks as well as sectors display can also show different signaling

qualities. Second, the sample sizes differ by sector in terms of the number of events and

related potential trades, with the sizes at the smallest in Telecommunication Services (421

trades). Third, the returns we have measured over the 40-day period can reflect varying

degrees of stability. The figures above conceal much when examined with this in mind.

In the charts that follow, we focus on the third of these caveats – charting the stability of

these returns over the period by comparing the path of the supplier positions in the top and

bottom quintiles. For example, in the case of the industrials sector (Figure 23 and Figure

24 ), the net returns as per Figure 24 may not be the strongest, but the relative trends in

the top and bottom quintiles are stable and clearly differentiated. We find the excess return

builds quite consistently through time. In contrast, in the materials sector (Figure 25 and

Figure 26 ) we see a far more erratic pattern, even if our 40-day net results are a small

positive. Figures 27 and Figure 28 shows the pattern for utilities, which was consistently

poor throughout the period of analysis.

-10%

-5%

0%

5%

10%

15%

20%

25%

30%

Tel

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15%

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25%

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Util

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14 November 2016



the market


returns relative to the market



the market





the market




-0.52%

+0.38%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Industrials

Bottom Quintile Top Quintile0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Industrials

-1.41%

-0.71%

-1.8%

-1.6%

-1.4%

-1.2%

-1.0%

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Materials


-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

0.8%

T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Materials

-0.62%

-1.68%

-2.5%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Utilities


-1.4%

-1.2%

-1.0%

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

14 November 2016


Sector 'heat maps'

In Appendix 2 we provide similar charts for all the MSCI Level 1 sectors showing the

relative stability of the top versus bottom quintiles. In Figure 29 we summarise these

findings with a simple colour-coded heat map. In each box of the table, we first indicate the

number of unique customer-supplier relationships in our PEERs database. The second

number indicates the qualifying amount of customers' earnings events that were recorded

in either the top or bottom quintile, matching our threshold criteria of a 5% relative return

over the five days surrounding the earnings release date. The third number is the average

excess return of the trades relative to their regional benchmark.

We group the results into three categories in keeping with the sector charts above to

reflect the stability of returns: good, moderate and poor.

■ Good (green): The top quintile (i.e., suppliers to customers with very strong earnings

results) consistently outperformed the bottom quintile (i.e., suppliers to customers with

very poor earnings results) for a considerable part of the 40-day period. This is in

keeping with our example of the industrials sector.

■ Moderate (yellow): The top quintile outperformed the bottom for the majority of the 40-

day period but to a lesser extent, and could underperform the bottom quintile for a

portion of the testing period. There still appear to be opportunities for a long/short

strategy to work. The materials group example above falls into this category.

■ Poor (red): The top quintile significantly underperforms the bottom quintile for a

significant portion of the 40-day period and offers no potential positive returns. Utilities

is the clear case in point.

Figure 29: Supplier excess returns, 2010-2015 – all companies

Note: In this report, we define earnings surprises as share-price moves of over 5% over the five days surrounding an earnings release date. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse research, Thomson Reuters

The 'heat map' supports the 6.1% annualised excess return for the sectors overall and the

green colour coding indicates stability, as we showed in the headline results earlier. Within

the stable column, returns were highest in telecoms, with returns as high as 18.9% while

financials at 5.5% were at the bottom end of the scale. These lag the returns in materials

and energy though they display only "moderate" stability. (We can show the same results

for small cap trades.)

Sector Stability

Ann. excess

returns Relationships Earnings events

All sectors Good 6.06% 8,442 15,372

By sector

Consumer Staples Good 16.64% 774 882

Financials Good 5.45% 407 885

Health Care Good 5.50% 494 736

Industrials Good 6.28% 1100 2500

Information Technology Good 5.91% 1358 2417

Telecom. Services Good 18.87% 352 421

Energy Moderate 7.53% 932 1036

Materials Moderate 4.95% 514 1377

Consumer Discretionary Poor 0.71% 2,127 3,628

Utilities Poor -7.08% 332 475

14 November 2016


It is important to note the number of events varies considerably, reflecting the point made

earlier about differing sample sizes. For example, contrast the rich number of events and

unique relationships in technology and industrials with the recorded events for telecoms.

As discussed in Appendix 2, we would also note that in industrials, the data indicate a

long/short strategy would have generated an excess return on both sides of the trade

rather than just the net spread within the results.

Connecting the dots

We would stress that the potential returns generated stem from the signals that emerge

from buying or selling suppliers for which companies in these sectors are customers. They

are essentially outbound signals. The trades that emerge from a given event/surprise

can be within the same industry group or sub-sector or from a far more lateral connection

outside of the sector. The charts below illustrate the network of suppliers that the

industrials and technology sectors reflect and, by implication, the sectors from which

potential trades may come. The industrials sector reflects a markedly wider range of inter-

relationships and sector signals in contrast to technology and financials. They are also

better spread across the market cap scale.

Figure 30: Suppliers breakdown


Technology Hardware

26%

Semiconductors26%Software &

Services11%

Capital Goods9%

Materials8%

Real Estate5%

Other16%

Information Technology

Capital Goods32%

Materials15%

Transportation10%

Technology Hardware

6%

Automobiles & Components

6%

Semiconductors6%

Software & Services

6%

Real Estate5%

Energy3%

Business Services3%

Other9%

Industrials

Technology Hardware

18%

Software & Services

18%

Media13%Telecom

13%

Capital Goods8%

Real Estate8%

Banks7%

Business Services4%

Consumer Durables & Apparel

3%

Other8%

Telecom

Software & Services

26%

Real Estate17%

Diversified Financials

10%

Capital Goods6%

Business Services6%

Banks5%

Insurance5%

Media4%

Transportation3%

Materials3%

Telecom3%

Health Care Equipment &

Services3%

Other10%

Financials

14 November 2016


Digging deeper

We can, of course, dig below the MSCI Level 1 returns into the sub-groups at Level 2.

However, given the limitations in the history of our dataset, the sample size in certain

areas does begin to shrink and would begin to question the statistical significance of the

results for some groups. However, below we focus on the three sectors with the largest

event lists: technology, industrials and consumer discretionary. The first two of these fell

into the 'green' category while the third was 'red'. Figure 31 to Figure 33 display the

excess returns for the Level 2 sectors within these categories.

■ In technology, all sub-sectors indicate positive returns from the signals given out by the

sub-groups, but the sub-sector that stands out is the supply chain surrounding the

semiconductor space, with excess returns of 15.3%.

■ In industrials, while the returns stemming from commercial services stand out, the

sample events and relationships are pretty low. We would prefer to focus on the

excess returns across capital goods, where the sample size is large. We have also

looked at testing events with a 10% cutoff for capital goods in Figure 32 , which still

leaves a large sample for testing. The returns rise from 5.8% to 18.2%.

■ In the consumer discretionary space, the pattern is far more mixed, reflecting a far less

homogenous group of sectors and varying sample sizes. The sub-sector of more

obvious note would be retailing, where we found returns to be stable if not spectacular

and based on a large base of relationships and events. Given the supply chain we

naturally associate with the automotive industry, we had expected signals from autos to

have yielded better results than actually proved to be the case. We do though find

specific exceptions to this rule stock-wise as we show in our stock-specific analysis

where a number of the prominent OEMs do emerge.

Figure 31: Annualized excess returns – Information Technology

Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse research, Credit Suisse PEERs, Thomson Reuters

10.5%

7.3%

1.4%

15.3%

6.7%

3.1%

0% 2% 4% 6% 8% 10% 12% 14% 16% 18%

Semiconductors &Semiconductor Equipment

(727, 611)*

Software & Services(501, 331)*

Technology Hardware& Equipment(1258, 955)*

All Stocks

Small Cap

*(X,Y): Represents # of qualifying trades for All suppliers and Small Cap Suppliers respectively

14 November 2016


Figure 32: Annualized excess returns – Industrials


Figure 33: Annualized excess returns – Consumer Discretionary


The outbound signals from tech, industrials and consumer sectors

The charts below illustrate the network of suppliers for the capital goods, semiconductors

and retailing sectors and the sectors from which potential trades may come. The diversity

of relationships in capital goods and retailing is more sizeable than for the semiconductor

supply chain where the supply chain remains more closely knit with the technology space.

49.6%

18.7%

7.5%

11.7%

45.6%

18.2%

5.8%

4.0%

0% 10% 20% 30% 40% 50% 60%

Commercial Services& Supplies(145, 96)*

Capital Goods10% cut-off

earnings surprise(413, 313)*

Capital Goods5% cut-off

earnings surprise(1531, 1062)*

Transportation(745,492)*

All Stocks

Small Cap


15.3%

21.2%

7.3%

6.5%

8.4%

10.3%

6.9%

4.2%

2.0%

-0.5%

-5% 0% 5% 10% 15% 20% 25%

Media(266,224)*

ConsumerDurables & Apparel

(766,531)*

Retailing(1751, 1246)*

Automobiles& Components

(716,583)*

Consumer Services(489,369)*

All Stocks

Small Cap


14 November 2016


Figure 34: Suppliers breakdown


Welcome to the real world

As satisfying as some of the above results may be – and in reality few analysts are likely

to present back-tests that don't work – the strategy above could not be applied in the real

world for one simple reason: it would not be possible to determine what quintile any single

earnings release was falling into as it was released and hence execute the trading

strategy. That said, we still view this as a proof of concept.

To address the limitation of the 'quintile' approach, we show below a very simple back-

testing exercise that is more applicable in the real world, based around the principles set

out above. Focusing on events of both a 5% and 10% relative move of a stock versus its

sector around an earnings announcement, we have simply modelled buying or selling high

and moderate relevance suppliers into a given customer depending on the direction of the

move. We have retained the same 40-day holding period and assumed execution at T+2.

We have focused on all global suppliers and calculated the simple average performance of

these suppliers against their respective local benchmarks. We have conducted this from

2011-2015. Our data indicate the net result from the long/short strategy using 10% as a

signal was a net 6.3% gain compared to 5.7% using a cutoff of 5% as a signal and holding

the respective supplier positions for 40 days. Indeed, these are surprisingly similar to the

returns indicated in the quintile approach above.

Our model indicated a success rate over 50% throughout the period, generating an excess

return on each side of the potential long/short trade. Although 52% may seem like a

modest success rate, we would note that we have not optimised the signal thresholds for

sectors or applied any other factor filters. We view this as a 'sanity check' for the quintile

approach above.

Figure 35: Annualised returns for a 5% and 10% relative stock price move

Global Cut-off Total

Number of Trades

Successful Trades

% Successful

Avg Annualised

return

T+40

Long Trades 5% 7,483 3,886 52% 3.7%

Short Trades

7,437 3,847 52% 2.1%

All

14,920 7,733 52% 5.7%

Long Trades 10% 2,441 1,284 53% 3.5%

Short Trades

2,260 1,181 52% 2.8%

All

4,701 2,465 52% 6.3%

Note: T+40 days holding period. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse PEERs, Credit Suisse research

Semiconductors56%

Technology Hardware

15%

Materials13%

Capital Goods7%

Software & Services

3%

Other6%

Semicondusctors

Consumer Durables & Apparel

23%

Real Estate13%

Software & Services

8%

Food, Beverage & Tobacco

7%Capital Goods

7%

Technology Hardware

7%

Household & Personal Products

5%

Transportation5%

Materials4%

Retailing4%


3%

Consumer Services3%

Business Services3%

Media3%

Other5%

Retailing

Capital Goods35%

Materials18%

Technology Hardware

7%

Semiconductors7%


7%

Real Estate5%

Software & Services

5%

Transportation4%

Other12%

Capital Goods

14 November 2016


Figure 36 provides further colour and application of the overall results. First, we seek to

consider the application of the strategy for investors who might be constrained regionally

in portfolio terms. Hence, we show the potential returns that would be achieved from

trading in the stocks purely within their own region but on the basis of the signals from

global customers. Returns are positive in all regions, but strongest in Europe and weaker

in APAC. We haven't broken out Japan here and would note that we find a large number

of Japanese stocks amongst our list of those companies who do provide strong supply

chain signals.

Second, if the message of the quintile approach above was that supply chain signals

seemingly have different power in one sector versus another, we have sought to test that

here as well by focusing on five of the sectors that seemed to offer the stronger and more

profitable signals—capital goods, semiconductors, tech hardware, retailing and consumer

durables. While we do not get confirmation across the board, the sector results appear

generally supportive.

Figure 36: Regional average annualised long/short net returns

Supplier Region

Customer Earnings Overall Americas Europe Asia Pacific

Sector Cut-off T+40 T+40 T+40 T+40

Overall 5% 5.7% 5.7% 7.0% 3.2%

10% 6.3% 5.8% 11.2% 3.0%

Capital 5% 5.1% 13.3% -0.4% -1.7%

Goods 10% 19.3% 33.6% 6.3% 10.9%

Tech 5% 16.3% -1.6% 47.5% 11.4%

Semiconductors 10% 11.0% -7.7% 55.1% -0.8%

Tech 5% 2.9% 5.8% 8.3% -4.1%

Hardware 10% -1.4% 0.5% 8.3% -5.2%

Retail 5% 6.9% 10.3% 5.5% 6.8%

10% 6.7% 15.7% 20.6% 4.2%

Consumer 5% 4.4% 0.3% 2.7% 11.6%

Durables 10% -1.0% -2.5% 8.4% -3.2%

Note: T+40 days holding period. Shaded cells highlight best performing scenario across each customer-supplier region pair. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Credit Suisse PEERs, Credit Suisse research

14 November 2016


It's all about stocks

What to watch out for?

When it comes to the real world, we think a powerful application of this analysis is

ultimately about stocks and identifying the ones to focus on most. We are used to hearing

the term 'bellwether stock' to describe a company that provides a broader, if qualitative,

relevance for the economy or market more broadly. We can leverage our framework here

with that thought process in mind, but with a less subjective judgement. Which specific

stocks have given the strongest signals to their suppliers in terms of their subsequent

stock market performance? (Remember, we are measuring the performance of companies

for which the customer is relevant rather than the reverse).

We have looked at this in a series of different ways in the tables below, though using the

same signal measurement as per above, by defining a surprise in keeping with the +/- 2-

day relative move and the subsequent 40-day measurement period used throughout this

report. We look at stocks with a minimum of four suppliers in PEERs, displaying at least

four surprises over the testing period and with a potential returns 'hit rate' over 55%. We

use an $8bn market cap cutoff. The typical average performance of the of suppliers across

the multiple signal events is shown. (Note that the sample will penalise some stocks

outside the US that do not report quarterly, hence making it more difficult for them to

qualify for inclusion.)

Figures 37 and 38 differ in that the former measures the surprise In terms of a move in the

stock judged relative to MSCI World, while the latter measures the moves relative to the

respective global MSCI Level 2 industry group, in keeping with the heat maps earlier.

While there are multiple suppliers for each stock, in the final column of the table we have

highlighted those that see the relationship of HIGH relevance by way of illustration of the

nature of the relationships. However, we include HIGH and MODERATE in the overall hit

rate and performance statistics just as we have throughout the analysis in this report.

There can be on average a negative performance statistic for the supplier basket in a

particular trade(s), but the 'hit rate' should still be above 55%. We have used bolded text to

indicate the stocks that Credit Suisse has under coverage.

We have a preference for the second approach in that we think it reflects a genuine

surprise versus the companies' industry group and to that extent arguably a stronger and

differentiating signal in its information content. However, in reality, there is a considerable

overlap between the tables, with many stocks appearing in both. US stocks dominate the

customer column (as one would expect), though the supplier column reflects a wide global

spread. The sector spread of the companies concerned reflects a broad consistency with

much of the sector analysis throughout the report. The number of oil companies is perhaps

an exception.

As an aside, we would flag in Appendix 3 a screen we have run focusing simply on where

a customer signal proved, with the benefit of hindsight, to be particularly robust in that the

customer performance remained positive over the subsequent 40-trading day period. This

was to proxy what might be seen as a higher "quality" surprise on earnings as viewed by

investors/analysts at the time. In reality, the impact on our results was marginal in terms of

improvement. It would arguably suggest that we should just listen to the market and the

signal rather than seek to over-rationalise the price moves.

14 November 2016


Figure 37: Customers delivering a consistently high "hit rate" in trading signals in suppliers (using the

move relative to the MSCI ACWI MARKET BENCHMARK to define the signal)

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% over the five days surrounding an earnings release date. Based on data from January 2010 to December 2015. Bolded stocks are under CS coverage. Past performance should not be taken as an indication or guarantee of future performance. Source: Company data, Credit Suisse research, Credit Suisse PEERs, Thomson Reuters


T+2 / T-2

Average % of

suppliers whose T+40

/ T+2 returns are in

line with customer

surprise


TJX United States Retailing 6 76% Federal Realty, Kimco Realty



Endesa Spain Utilities 5 70% ACS ES

E I Du Pont De Nemours United States Materials 4 70% Iluka





Priceline Group United States Retailing 18 66% Choice Htl Intl, Hilton Wrldwide, La Quinta

Royal Dutch Shell A Netherlands Energy 5 65% KBR, Weir Group

Baker Hughes United States Energy 12 65% Hunting, SBO

Halliburton United States Energy 8 65%Forum Energy Tec, Hi-Crush Partner, Hunting, SBO, U.S.

Silica


Wesfarmers Australia Food & Staples Rtl 5 64% Breville, BWP Trust, DuluxGroup, Tassal Group Ltd




Caterpillar United States Capital Goods 6 62%

Nike 'B' United States Cons Dur & Apparel 10 62% FT, Indorama Venture, Shenzhou Intl, Yue Yuen Ind

Anadarko Petroleum United States Energy 7 62% Forum Energy Tec, RPC, TETRA

Bank Of America United States Banks 10 62%Boston Ppty, CBRE Group, Federal Realty, Proofpoint,

Textron

IAG United Kingdom Transportation 10 60% Gategroup Holdg

American Airlines Group United States Transportation 20 60%


Boeing United States Capital Goods 7 59%





Tripadvisor 'A' United States Retailing 14 58%Expedia, Hilton Wrldwide, Hyatt Hotels, La Quinta, Marriott


Jd.Com 'A' Adr 1:2 China Retailing 5 58% GLP

Encana (Nys) Canada Energy 8 58% TransCanada

Devon Energy United States Energy 12 58% Forum Energy Tec, Patterson-UTI, TETRA

Apache United States Energy 9 58% Forum Energy Tec, Oil States Intl, Rowan

Gap United States Retailing 6 58%Federal Realty, General Grow, Macerich, Shaftesbury,

Simon Prop Grp, Taubman Centers

Newfield Exploration United States Energy 16 58%


Best Buy United States Retailing 16 58% LG Elec

Nvidia United States Semis 17 58% CHROMA, SPIL, TSMC

Oil & Natural Gas India Energy 5 58% Transocean


Occidental Ptl. United States Energy 7 57%

BMW Germany Auto & Components 4 57%Autoneum Hold, Constellium, Georg Fis, Hella Hueck,

Samsung SDI

Micron Technology United States Semis 19 57%Advantest, Applied, ChipMOS, HMI, Inotera, Lam

Research, Siltronic

Expedia United States Retailing 16 57%Choice Htl Intl, Derwent London, Hilton Wrldwide, Hyatt



Cigna United States H/C Equip & Svs 9 56%Laboratory Corp, LifePoint Health, QuestDiagnostics,

Tenet Healthcare

Netflix United States Retailing 21 56% CBS Corp


Aisin Seiki Japan Auto & Components 9 56% Exedy, Jtekt, Toyota

Cvs Health United States Food & Staples Rtl 5 56% Cardinal Health, McKesson

Marriott Intl.'A' United States Consumer Services 4 56%

Emerson Electric United States Capital Goods 4 56% Infineon Technol, YRC Worldwide

Goldman Sachs Gp. United States Diversified Financials 4 56%





Unipres


Rolls-Royce Holdings United Kingdom Capital Goods 4 56% Alcoa, Bodycote, IHI, Kawasaki Heavy, Meggitt

Dow Chemical United States Materials 8 55% Air Liquide, Range Resource, Union Pacific, Vopak

Mahindra & Mahindra India Auto & Components 10 55% Apollo Tyres

14 November 2016


Figure 38: Customers delivering a consistently high "hit rate" in trading signals in suppliers (using the

move relative to the MSCI ACWI INDUSTRY GROUP benchmark to define the signal)

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% over the five days surrounding an earnings release date. Based on data from January 2010 to December 2015. Bolded stocks are under CS coverage. Past performance should not be taken as an indication or guarantee of future performance. Source: Company data, Credit Suisse research, Credit Suisse PEERs, Thomson Reuters


T+2 / T-2


whose T+40 / T+2

returns are in line with

customer surprise


TJX USA Retailing 5 76% Federal Realty, Kimco Realty

Petrochina 'H' China Energy 4 72% Anton Oil, Green Dragon Gas, Jereh Group, SPT Energy






Baker Hughes USA Energy 11 66% Hunting, SBO



Anadarko Petroleum USA Energy 4 63% Forum Energy Tec, RPC, TETRA



Enbridge Canada Energy 5 62% Cdn Natural Rsc

Priceline Group USA Retailing 19 62% Choice Htl Intl, Hilton Wrldwide, La Quinta

Bank Of America USA Banks 8 61%Boston Ppty, CBRE Group, Federal Realty, Proofpoint,

Textron

Phillips 66 USA Energy 4 61% Phillps 66 Ptns, Spectra Energy

Newfield Exploration USA Energy 18 61%

BT Group UK Telecoms 7 60% Computacenter

American Airlines USA Transportation 20 60%

Nike 'B' USA Cons Dur & Apparel 9 60% FT, Indorama Venture, Shenzhou Intl, Yue Yuen Ind


Occidental Ptl. USA Energy 8 60%

Apache USA Energy 7 60% Forum Energy Tec, Oil States Intl, Rowan

Expedia USA Retailing 14 59%Choice Htl Intl, Derwent London, Hilton Wrldwide, Hyatt



Royal Dutch Shell Netherlands Energy 4 59% KBR, Weir Group


Tripadvisor USA Retailing 14 58%Expedia, Hilton Wrldwide, Hyatt Hotels, La Quinta, Marriott


Jd.Com China Retailing 5 58% GLP

Encana Canada Energy 8 58% TransCanada

Best Buy USA Retailing 16 58% LG Elec






Unipres

General Motors USA Auto & Components 5 57%

AK Steel, Alfa, HASCO, Interpublic, Isuzu, Johnson Ctrl, LG

Chem, Mando Corp, Next Auto, NGK Insulators, Rockwell

Auto, Takata, Teijin, Victrex, Worthington Ind

Nvidia USA Semis 15 57% CHROMA, SPIL, TSMC



Boeing USA Capital Goods 6 57%





Micron Technology USA Semis 18 57%Advantest, Applied, ChipMOS, HMI, Inotera, Lam

Research, Siltronic

Wesfarmers Australia Food & Staples Rtl 4 57% Breville, BWP Trust, DuluxGroup, Tassal Group


Cigna USA H/C Equip & Svs 9 56%Laboratory Corp, LifePoint Health, QuestDiagnostics,

Tenet Healthcare

Netflix USA Retailing 21 56% CBS Corp

Denso Japan Auto & Components 5 56% Disco, Toyota

Marriott Intl.'A' USA Consumer Services 4 56%

Kroger USA Food & Staples Rtl 6 56% Equity One, Regency Center

Interpublic Group USA Media 13 56%CBS Corp, Comcast, Discovery Commns, Time Warner,

Twenty-First Fox, Viacom, Walt Disney

Western Digital USA Tech HW & Equip. 10 56% Nidec, STMicroelectron, Teradyne

Halliburton USA Energy 9 56%Forum Energy Tec, Hi-Crush Partner, Hunting, SBO, U.S.

Silica

Akzo Nobel Netherlands Materials 9 56% Elementis

Amerisourcebergen USA H/C Equip & Svs 4 56% Allergan

Rolls-Royce Holdings UK Capital Goods 4 56% Alcoa, Bodycote, IHI, Kawasaki Heavy, Meggitt

Pembina Pipeline Canada Energy 8 55%

Samsung Electronics South Korea Tech HW & Equip. 4 55%

3M, AAC Tech, Advantest, Applied, ARM, ASML, AUO,

Disco, DNF, Goertek, Hirose Electric, HMI, Imagntn Tech,

KAL, KLA-Tencor, Lam Research, Lens Tech, ROEC,

Rudolph Tech, Seoul Semi, Shin-Etsu Chem, Siltronic, SK

Materials, Soul Brain, STMicro, Sumco, Tokyo Electron,

TSMT, Wacker Chemie, Wacom, Wonik Materials

14 November 2016


The 'Supply Chain Trades'

As well as screening for stocks that provide the strongest signals for others, we can also

highlight the reverse. What specific stocks have consistently proved most sensitive to a

surprise in a given customer's results? Figures 39 to 42 break down the data by region.

While this is just a small sample of the more extreme examples, a striking feature is how

the groupings in the US and Japan are mainly intra-regional whereas in NJA and Europe

they are far more cross-border.

Figure 39: US suppliers (in bold) that have consistently responded to customer surprise signals

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% against the industry group benchmark over the five days surrounding an earnings release date. The 'Avg hit rate' refers to % of profitable trades. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Company data, Credit Suisse research, Credit Suisse PEERs, Thomson Reuters

Figure 40: European suppliers (in bold) that have consistently responded to customer surprise signals



# instances

supplier inline

with signal



over T+40 / T+2

Best Buy United States Retailing Activision United States Software 16 12 75%

Nokia Finland Communications Equip. Emerson Electric United States Electrical Equip. 14 11 79%

eBay United States Internet SW & Svs Equinix United States Equity REITs 13 10 77%

Interpublic Grp United States Advertising CBS Corp United States Broadcasting 13 10 77%

Cinemark Hldgs United States Movies & Entertainment Time Warner United States Movies & Entertainment 10 8 80%

Humana United States Managed Health Care Walgreens Boots United States Drug Retail 10 8 80%

Cigna United States Managed Health Care Universal Health United States Health Care Facilities 9 7 78%

DISH Network United States Cable & Satellite Comcast United States Cable & Satellite 9 7 78%

DISH Network United States Cable & Satellite Walt Disney United States Movies & Entertainment 9 7 78%

Express United States Health Care Services CVS Health United States Drug Retail 9 7 78%

Bank of America United States Diversified Banks MGIC Investment United States Thrifts & Mortgage Fin. 8 7 88%

Volkswagen Germany Automobiles BorgWarner United States Auto Parts & Equip. 8 6 75%

Norsk Hydro Norway Metals & Mining Baker Hughes United States Energy Equip. & Svs. 8 6 75%

Bank of America United States Diversified Banks MasterCard United States IT Services 8 6 75%

Occidental United States Integrated Oil & Gas Helmerich United States Oil & Gas Drilling 8 6 75%

Occidental United States Integrated Oil & Gas Patterson-UTI United States Oil & Gas Drilling 8 6 75%

Ford Motor United States Automobiles Celanese US DE United States Chemicals 7 6 86%

Ford Motor United States Automobiles Kennametal United States Machinery 7 6 86%

Hess United States Oil & Gas E & P Oil States Intl United States Energy Equip. & Svs. 7 6 86%

Petrobras Brazil Integrated Oil & Gas Seacor Holdings United States Energy Equip. & Svs. 7 6 86%

Toyota Japan Automobiles KCS US United States Road & Rail 6 5 83%

LG Elec South Korea Household Durables Prologis MD United States Equity REITs 6 5 83%

Boeing United States Aerospace & Defense GE United States Capital Goods 6 5 83%

Boeing United States Aerospace & Defense Kennametal United States Machinery 6 5 83%

Boeing United States Aerospace & Defense Orbital ATK United States Aerospace & Defense 6 5 83%


# instances

supplier inline

with signal



over T+40 / T+2

American Airline United States Airlines Zodiac Aero France Aerospace & Defense 20 15 75%

Amazon.com United States Internet Retail Logitech Inter Switzerland Tech HW & Equip. 17 13 76%

Valeo France Auto Components Nexans France Electrical Equip. 12 9 75%

Tata Motors India Automobiles Koninklijke DSM Netherlands Chemicals 11 9 82%

Technip France Energy Equip. & Svs. Outokumpu Finland Steel 9 7 78%

Volkswagen Germany Automobiles RTL Group Luxembourg Broadcasting 8 6 75%

Renault France Automobiles Publicis Groupe France Advertising 8 6 75%

Renault France Automobiles ITV United Kingdom Broadcasting 8 6 75%

Norsk Hydro Norway Metals & Mining Transocn Switzerland Oil & Gas Drilling 8 6 75%

BT Group United Kingdom Telecoms Siemens Germany Capital Goods 7 6 86%

BT Group United Kingdom Telecoms Ericsson Sweden Communications Equip. 7 6 86%

Apache United States Oil & Gas E & P Rowan United Kingdom Oil & Gas Drilling 7 6 86%

Ford Motor United States Automobiles Johnson Matthey United Kingdom Chemicals 7 6 86%

Ford Motor United States Automobiles ArcelorMitta Luxembourg Steel 7 6 86%

Hess United States Oil & Gas E & P Subsea United Kingdom Energy Equip. & Svs. 7 6 86%

McKesson United States Health Care Distr. Mylan NL United Kingdom Pharmaceuticals 7 6 86%

Petrobras Brazil Integrated Oil & Gas Noble Corp United Kingdom Oil & Gas Drilling 7 6 86%

Orange France Telecoms Wirecard Germany IT Services 6 5 83%

Carphone Ware. United Kingdom Retailing Intu Prop United Kingdom Retail REITs 6 5 83%

Toyota Japan Automobiles Publicis Groupe France Advertising 6 5 83%

Toyota Japan Automobiles Dassault System France Software 6 5 83%

Boeing United States Aerospace & Defense Safran France Aerospace & Defense 6 5 83%

Boeing United States Aerospace & Defense Zodiac Aero France Aerospace & Defense 6 5 83%

Boeing United States Aerospace & Defense Dassault System France Software 6 5 83%

Boeing United States Aerospace & Defense Rolls-Royce Hldg United Kingdom Aerospace & Defense 6 5 83%

Boeing United States Aerospace & Defense SKF Sweden Machinery 6 5 83%

Microsoft United States Software Seagate Tech Republic of Ireland Tech HW & Equip. 6 5 83%

14 November 2016


Figure 41: Asia Pacific (ex Japan) suppliers (in bold) that have consistently responded to customer surprise

signals


Figure 42: Japanese suppliers (in bold) that have consistently responded to customer surprise signals



# instances

supplier inline

with signal



over T+40 / T+2

Skyworks Solutns United States Semis JCET China Semis 21 15 71%

HP United States Tech HW & Equip. Realtek Semicon Taiwan Semis 13 10 77%

Royal Bank Scot United Kingdom Banks Iress Australia IT Services 12 9 75%

TEP Hldg Japan Electric Utilities Santos Ltd Australia Oil & Gas E & P 12 9 75%

Sharp Japan Household Durables AUO Taiwan Electronic Comp. 11 8 73%

Sharp Japan Household Durables Innolux Taiwan Electronic Comp. 11 8 73%

Sony Japan Household Durables MediaTek Taiwan Semis 11 8 73%

Sony Japan Household Durables EIH Taiwan Electronic Comp. 11 8 73%

Western Digital United States Tech HW & Equip. SK Hynix South Korea Semis 10 7 70%

Nike United States Apparel & Luxury Shenzhou Intl China Apparel & Luxury 9 7 78%

Skyworth Digit Hong Kong Household Durables Innolux Taiwan Electronic Comp. 8 6 75%

Matahari Putra Indonesia Food & Staples Rtl HM Sampoerna Indonesia Tobacco 8 6 75%

Kansai Elec Japan Electric Utilities Origin Energy Australia Integrated Oil & Gas 8 6 75%

Bank of America United States Banks Iress Australia IT Services 8 6 75%

Astra Intl Indonesia Automobiles Surya Semesta Indonesia Construction & Engin. 7 6 86%

Nissan Japan Automobiles Somboon Adv Tech Thailand Auto Components 7 6 86%

Astra Intl Indonesia Auto & Components Media Citra Indonesia Broadcasting 7 5 71%

Astra Intl Indonesia Auto & Components Bekasi Fajar Indonesia Real Estate 7 5 71%

NIPPON STEEL Japan Steel Rio Tinto Australia Metals & Mining 7 5 71%

Hitachi Japan Tech HW & Equip. SK Hynix South Korea Semis 7 5 71%

Honda Japan Automobiles Thai Stanley Thailand Auto Components 7 5 71%

Honda Japan Automobiles Somboon Adv Tech Thailand Auto Components 7 5 71%

LG Display South Korea Tech HW & Equip. Coretronic Taiwan Electronic Equip. 7 5 71%

LG Display South Korea Tech HW & Equip. ROEC Taiwan Semis 7 5 71%

Ford Motor United States Automobiles HASCO China Auto Components 7 5 71%

Puma DE Germany Apparel & Luxury Yue Yuen Ind Hong Kong Footwear 6 5 83%

LG Elec South Korea Household Durables Skyworth Digit Hong Kong Consumer Electronics 6 5 83%

LG Elec South Korea Household Durables MediaTek Taiwan Semis 6 5 83%

Nordstrom United States Retailing Li & Fung Hong Kong Apparel & Accessories 6 5 83%

Apple United States Tech HW & Equip. Samsung SDI South Korea Electronic Comp. 5 5 100%

Apple United States Tech HW & Equip. LG Chem South Korea Chemicals 5 5 100%

GM United States Automobiles LG Chem South Korea Chemicals 5 5 100%

Kawasaki Kisen Japan Transportation HPH Trust Singapore Marine Ports & Services 5 4 80%

Citigroup United States Banks Iress Australia IT Services 5 4 80%

GM United States Automobiles Hyundai Mobis South Korea Auto Components 5 4 80%


# instances

supplier inline

with signal



over T+40 / T+2

Sharp Japan Household Durables Disco Japan Semis 11 9 82%

Yamaha Motor Japan Automobiles NTN Japan Machinery 11 9 82%

Alfresa Holdings Japan H/C Providers & Svs Ono Pharm Japan Pharmaceuticals 9 7 78%

Alfresa Holdings Japan H/C Providers & Svs Sawai Pharm Japan Pharmaceuticals 9 7 78%

Alfresa Holdings Japan H/C Providers & Svs Mitsub Tanabe Japan Pharmaceuticals 9 7 78%

Toshiba Japan Capital Goods Nissha Printing Japan Comml. & Prof. Svs. 9 7 78%

Hino Motors Japan Capital Goods Sumitomo Rub Ind Japan Auto Components 8 7 88%

Hyundai Motor South Korea Automobiles Takata Japan Auto Components 8 7 88%

Toyota Tsusho Japan Capital Goods Tokai Rika Japan Auto Components 8 6 75%

Toyota Tsusho Japan Capital Goods Toyota Inds Japan Auto Components 8 6 75%

Toyota Tsusho Japan Capital Goods Toyota Boshoku Japan Auto Components 8 6 75%

Hino Motors Japan Capital Goods Denso Japan Auto Components 8 6 75%

Hino Motors Japan Capital Goods Toyoda Gosei Japan Auto Components 8 6 75%

Hino Motors Japan Capital Goods Nippon Yusen Japan Transportation 8 6 75%

Hino Motors Japan Capital Goods Bridgestone Japan Auto Components 8 6 75%

Nissan Japan Automobiles Aisan Industry Japan Auto Components 7 6 86%

Nissan Japan Automobiles Tokai Rika Japan Auto Components 7 6 86%

Nissan Japan Automobiles Toyota Japan Auto Components 7 6 86%

Nissan Japan Automobiles Toyoda Gosei Japan Auto Components 7 6 86%

Nissan Japan Automobiles NGK Insulators Japan Capital Goods 7 6 86%

Nissan Japan Automobiles NEC Japan Tech HW & Equip. 7 6 86%

Nissan Japan Automobiles Mitsui Chemicals Japan Chemicals 7 6 86%

Hitachi Japan Tech HW & Equip. Nippon Yusen Japan Transportation 7 6 86%

LG Display South Korea Tech HW & Equip. Mitsubishi Elec Japan Electrical Equipment 7 6 86%

Toyota Japan Automobiles NGK Spark Plug Japan Auto Components 6 6 100%

Toyota Japan Automobiles Bridgestone Japan Auto Components 6 6 100%

Toyota Japan Automobiles Sumitomo Rub Ind Japan Auto Components 6 5 83%

LG Elec South Korea Household Durables Hirose Electric Japan Electronic Components 6 5 83%

14 November 2016


Limitations of the analysis

We more than recognise that this analysis is somewhat simplistic, not least owing to its

'costless' approach. However, beyond that, we would highlight a series of other limitations

in its methodology and application.

■ The first and arguably most important consideration here is a risk of survivorship bias.

For our quintile analysis, we have only used a snapshot of the relationship database as

of 2015H2 to conduct the back-tests, rather than using in-time testing that would

rebalance with new relationships over the period, which would be the ideal approach. A

feed from our database would permit this, but we chose our current approach given

that our dataset now has considerably more depth than several years ago. We would

also note that experience from previous work suggests supply chain relationships do

not change significantly year by year and hence should mitigate the risks of adopting

this approach. (Note we have used September 2016 data for our stock analysis.)

■ We have made no attempt to optimise holding periods or overlay other factors to

minimise periods of drawdown as a more sophisticated trading approach would do.

However, one aim of the analysis has been to reflect a degree of conservatism in the

approach. Selecting events on the basis of a five-day window for analysis is intended

to remove a degree of 'noise' from the system. Measuring performance from T+2 also

removes the rather unrealistic possibility of being able to trade at the moment a set of

results are released.

■ Our 40-day holding period is intended to moderate potentially too aggressive an

approach in terms of turnover (even if still short term for the taste of many investors).

That said, it was notable that the excess return accumulated over the whole period

rather than in the first few days. Indeed, there is evidence amongst the academic work

detailed in Appendix 4 that the excess return persists for longer than we are measuring

here, reflecting the notion of "earnings announcement drift".

■ It should be noted that we have not used regional sector benchmarks to calculate

relative supplier returns. It could be argued that this would be more appropriate. The

approach we have taken is largely an exercise of pragmatism. The suppliers applicable

for a given customer can come from a multitude of regions and sectors within them. To

avoid performance calculations across a myriad of differing sector benchmarks, we

have taken the simple approach of using the regional MSCI index for the geography in

which the company is domiciled.

■ With regards to optimisation, there is also work to do on determining what constitutes a

genuine 'surprise'. Although tested for materiality, our 5% stock-price threshold is far

from scientific – not just in an overall sense but also in a sector-specific sense. A 5%

move in a high-volatility steel stock is less significant than a 5% move in a low-volatility

consumer staples stock. A flat threshold raises the risk of introducing an unintended

sector bias into the sample.

■ We have considered only one element of supply chain signalling. While the signal from

customer to supplier carries plenty of potential significance, the timing of news flow in

the markets can be such that a signal from a supplier can pre-empt news from a

customer (i.e. the reverse of our analysis). We have seen plenty of examples of this

surrounding Apple and its Asian supply chain, with early news flow emanating from

Apple's component manufacturers. We have also not analysed in this report the simple

read-across from one peer group competitor to another, though our PEERs database

would make this quite straightforward. We did indeed look at this in our previous

research and found that systematic trading approaches based around this element of

the network appeared to work best in the more consolidated industries (see Global

Equity Themes: Exploiting Earnings Surprises, 25 October 2010).



14 November 2016


Conclusions

■ While it makes intuitive sense to buy stocks that supply companies that are themselves

faring well and vice versa, we find that the stock market still does not appear to

discount signals to this effect as quickly as it could.

■ While this was the essential takeaway from the original study by Cohen and Frazzini,

the fact that we are still seeing such persistent alpha (high single-digits on our relatively

unsophisticated approach) despite improved technology and speed in the flow of

information in capital markets is striking to us.

■ We believe market inefficiencies in the flow of information across regions and across

sectors remain and present alpha generation opportunities, with small cap stocks

offering a leveraged play (if at higher liquidity cost).

■ Our analysis indicates sectors that may warrant the most attention under this strategy,

with excess returns heading into the double digits based on our back-tests. They are

typically in the industrial, technology and consumer supply chains. As much as sectors,

there are stocks that appear to generate stronger signals than others which may fine-

tune this approach further.

■ Finding a way to take advantage of such inadequacies in the transmission mechanism

has typically been the stumbling block. We think Credit Suisse's PEERs tool, given that

it is based on the unique insights of our analysts, provides scope to do so.

■ Given this quantitative approach may not appeal to all, we would flag prior supply chain

analysis by Credit Suisse, notably from Michael Mauboussin and Dan Callahan in their

report, Measuring the Moat, 22 July 2013 and 1 November 2016, leveraging the

concept of industry mapping to assess competitive positioning upon which PEERs is

essentially based.

■ We have also considered the topic of systemic shocks to the supply chain, such as the

dislocation following the tsunami and Fukushima disaster in Japan: Global Equity

Themes: Japanese Supply Chain Disruptions, 17 March 2011 (see Appendix 4 for

more).

https://plus.credit-suisse.com/r/xrrOm4



14 November 2016


Appendix 1: Earnings surprise methodology

Scope and universe

The PEERs database contains qualitative data on companies under coverage and

identifies key relationships for each company in the form of competitors, customers,

suppliers, joint ventures and equity investments. These relationships are classified into

relevance levels—high, medium and low—depending upon the strength and significance

of the relationship.

For our analysis, we focus only on High and Medium ‘Customer-Supplier’ relationships

from the PEERs database. This comprises more than 8,400 relationships between 2,500

unique customers and 2,000 unique suppliers.

The analysis was done for all GICS level-1 and selected GICS level-2 sectors, at both

global and three regional levels: the Americas, Europe and Asia Pacific (including Japan

and Australia). The back-testing was done for the period ranging from January 2010 to

December 2015. It is worth noting that the designated region and sector is that of the

customer, and the results from the analysis may refer to suppliers that belong to different

sectors or regions.

Earnings surprise

In order first to try to identify when a company has surprised positively or negatively, we

consider the market’s reaction to the company’s earnings announcement. We use this

approach rather than focusing on the conventional definition of Earnings Surprise as

‘Actual over consensus EPS’ due to the lack of quality earnings data for our universe and

the mathematical difficulty in dealing with negative and near-zero EPS numbers, as well as

to eliminate the 'noise' caused by one-off items that could steer investor sentiment

irrespective of the announced EPS numbers.

Furthermore, we observe the customer’s price performance over a five-day period in order

to reduce the impact of volatility in the stock around its announcement date. Our earnings

surprise metric utilises the company’s five business day returns (from T-2 to T+2) around

the earnings announcement day (T), relative to its regional sector benchmark index.

For example, an analysis of Rolls-Royce, which announced its FY2015 results on 12

February 2016, is calculated based on its returns relative to the MSCI All Country World

Industrials Sector Index from 10 February 2016 to 16 February 2016. Within these five

days, Rolls-Royce stock rose by 17.1% relative to the market after reporting an EPS of

58.7p versus consensus at 51.1p despite an 11% drop compared with 2014 reported

figures. Within our analysis, this would be considered a positive surprise.

14 November 2016


Quintile formation

For each semester over the period tested, we divide the customers into five equal groups

(quintiles) based on the ‘strength’ of their quarterly earnings surprise values, as

determined by their price movement in the five-day period discussed above. Hence, the

top quintile represents customers that report significant positive earnings surprises, while

the bottom quintile represents customers that report significant negative earnings

surprises. In quarters where the earnings surprises are mostly unidirectional, i.e., the

majority of them are either on the positive or negative side, we have found that even the

more modest earnings surprises may enter the top or bottom quintile. Therefore, we ignore

any earnings surprises in the top quintile that have a value of less than 5% and, similarly,

we ignore earnings surprises in the bottom quintile that have a value of greater than -5%.

Figure 43: Calculation of quintile returns

Source: Credit Suisse research

In Figure 43 , Customer A is associated with Suppliers 1, 2 and 3. An average of returns of

Suppliers 1, 2, 3 is attributed to Customer A. Also, since Supplier 2 supplies to both

Customer A and Customer E its returns will be attributed to both. It is to be noted that if

Customer A and Customer E were in two different quintiles, Supplier 2’s returns would

contribute to both quintiles.

Customer A

+26%Customer B

+1%

Customer C

+17%Customer D

-6%

Customer I

-5%

Customer G

+4%

Customer H

+1%

Customer F

-7%Customer K

-11%Customer J

+13%

Customer L

+3%

Customer M

+12%

Customer N

-27%Customer O

+2%

Customer E

+19%Customer P

+0%

Customer R

+10%

Customer T

+8%Customer…

+xx%

Customer Q

-9%

Customer S

-14%

Customer Earnings Surprise

Quintile 1

(top)

Quintile 2 Quintile 3 Quintile 4 Quintile 5

(bottom)

±5% cut-off

Customer A

+26%

Top Quintile Bottom Quintile

Supplier 1

+7%Supplier 2

+13%

Supplier 3

-2%

Customer E

+19%

Supplier 4

+6%

Supplier 2

-1%

Supplier 5

+2%

Supplier 6

+10%

Customer…

+xx%

Supplier…

+xx%

Customer M

-27%

Supplier …

-xx%Supplier 11

-5%

Supplier 12

-3%

Customer S

-14%

Supplier 13

-1%

Supplier 14

-9%

Supplier 15

-8%

Supplier 16

+5%

Customer…

-xx%

Supplier…

-xx%

Consolidated Quintile Returns

Top Quintile

Consolidated Quintile Returns

Bottom Quintile

Average of supplier returns Average of supplier returns

14 November 2016


Trading strategy

We then conduct a dummy trading approach of a long/short strategy based on adopting a

long position in the top quintile and a short position in the bottom quintile. This is adopted

for the 40-day window. It is not based on any optimisation, and no trading costs have been

considered in calculating the returns.

To assess the output from the analysis and appraise the merits of any potential trading

strategy, we summarised the results into three categories — good, moderate and poor.

(1) Good: The top quintile (i.e., suppliers to customers with very strong earnings results)

consistently outperforms the bottom quintile (i.e., suppliers to customers with very poor

earnings results) for a considerable part of the 40-day period.

Figure 44: Example of 'good' results


(2) Moderate: The top quintile outperforms the bottom for the majority of the 40-day period

but to a lesser extent, and could actually underperform the bottom quintile for a portion of

the testing period. There still appear to be opportunities for a long/short strategy to work.

Figure 45: Example of 'moderate' results


-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40Bottom Quintile Top Quintile

-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40


14 November 2016


(3) Poor: The top quintile significantly underperforms the bottom quintile for a significant

portion of the 40-day period and offers no potential positive returns.

Figure 46: Example of 'poor' results


Results of significance test

We have conducted one tailed Z-test to validate the results from our back-testing exercise.

The aim of this hypothesis test is to prove that alpha is generated by investing in suppliers

based on signals received from customers. We have taken the T+40 day excess returns

generated for suppliers in each year and undertaken the Z-test.

■ Null Hypothesis-Ho: No average excess returns generated at the end of the 40-day

period i.e.µ=0

■ Alternative Hypothesis-H1: Positive average excess returns are generated at the end

of the 40-day period i.e. µ>0

■ Testing the sample at 95% confidence level; i.e. α =0.05

■ If p-value < α, then Null Hypothesis is rejected

■ Result: As p-value <α for each year and across all years, null hypothesis is rejected

and Alternative Hypothesis is accepted. This implies that positive excess returns are

generated at the end of the 40-day period.

Figure 47: One tail Z-test on the back-testing results implies positive excess

returns are generated at the end of the 40-day period


-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40


Year Number of Trades P-Value

2010 2,431 0.0003

2011 2,636 0.0004

2012 2,547 0.0023

2013 2,480 0.0138

2014 2,696 0.0050

2015 2,582 Less than .0001

2010-2015 15,372 Less than .0001

Result: As p-value <α for each year and across all years, null hypothesis is rejected and

Alternative Hypothesis is accepted. This implies that positive excess returns are generated at

the end of 40 day period

14 November 2016


Appendix 2: Sector back-tests Top and bottom quintiles excess returns by region

Figure 48: Global – Overall Figure 49: Global – Small Cap

Note: Based on data from January 2010 to December 2015. Source: Thomson Reuters, Credit Suisse PEERs, Credit Suisse research


Figure 50: Americas – Overall Figure 51: Americas – Small Cap



Figure 52: Europe – Overall Figure 53: Europe – Small Cap

Note: Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Source: Thomson Reuters, Credit Suisse PEERs, Credit Suisse research


-0.28%

+0.58%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Global Overall


-0.38%

+0.89%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Global Small Cap


-0.55%

+0.18%

-0.6%

-0.5%

-0.4%

-0.3%

-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Americas Overall


-0.71%

+0.49%

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Americas Small Cap


-0.10%

+0.33%

-0.4%

-0.3%

-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Europe Overall


-0.25%

+0.58%

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Europe Small Cap


14 November 2016


Appendix 2: Sector back-tests (cont'd) Top and bottom quintiles excess returns by region (cont'd)

Figure 54: APAC – Overall Figure 55: APAC – Small Cap

Note: Based on data from 1/2010 to 12/2015. Source: Thomson Reuters, CS PEERs and research

Note: Based on data from 1/2010 to 12/2015. Source: Thomson Reuters, CS PEERs and research

Top and bottom quintiles excess returns by sector

Figure 56: Consumer Discretionary Figure 57: Consumer Staples



Figure 58: Energy Figure 59: Financials



+0.15%

+1.22%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Asia Pacific Overall


+0.04%

+1.35%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Asia Pacific Small Cap


+0.39%

+0.49%

-0.2%

-0.1%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Consumer Discretionary


+0.68%

+2.96%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Consumer Staples


-1.65%

-0.59%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Energy


+1.21%

+1.99%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Financials


14 November 2016


Appendix 2: Sector back-tests (cont'd) Top and bottom quintiles excess returns by sector (cont'd)

Figure 60: Health Care Figure 61: Industrials



Figure 62: Information Technology Figure 63: Materials



Figure 64: Telecommunication Services Figure 65: Utilities



+0.67%

+1.46%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Health Care


-0.52%

+0.38%

-0.6%

-0.4%

-0.2%

0.0%

0.2%

0.4%

0.6%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Industrials


+0.03%

+0.87%

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Information Technology


-1.41%

-0.71%

-1.8%

-1.6%

-1.4%

-1.2%

-1.0%

-0.8%

-0.6%

-0.4%

-0.2%

0.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Materials


-0.24%

+2.32%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Telecommunication Services


-0.62%

-1.68%

-2.5%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

T+2 T+5 T+10 T+15 T+20 T+25 T+30 T+35 T+40

Utilities


14 November 2016


Appendix 3: Stock screens

Figure 66: Stocks that generated a signal (i.e. earnings surprise) during the initial 5-day window and

sustained it over 40 trading days, using MSCI ACWI benchmark

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% over the five days surrounding an earnings release date. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Bolded stocks are under CS coverage. Source: Thomson Reuters, Credit Suisse PEERs, Credit Suisse research

Name Country GICS Level 2 Ind Grp

# of signals based on

T+2 / T-2 & T+40 /

T+2

Average T+40 / T+2

returns of suppliers rel. to

MSCI regional

benchmarks, annualised


whose T+40 / T+2 returns

are in line with customer

surprise


Volkswagen Germany Auto & Components 6 60% 92% BorgWarner, Constellium, Hella Hueck, Schaeffler

Halliburton United States Energy 5 115% 88% Forum Energy Tec, Hi-Crush Partner, Hunting, SBO, U.S. Silica

Apache United States Energy 4 54% 81% Forum Energy Tec, Oil States Intl, Rowan

Devon Energy United States Energy 5 35% 77% Forum Energy Tec, Patterson-UTI, TETRA

Nike 'B' United States Cons Dur & Apparel 6 67% 77% FT, Indorama Venture, Shenzhou Intl, Yue Yuen Ind

Skyworks Solutions United States Semis 10 126% 75% AWSC, Visual Photonics, Win

Baker Hughes United States Energy 7 37% 75% Hunting, SBO

Occidental Ptl. United States Energy 4 77% 75%

D R Horton United States Cons Dur & Apparel 4 46% 75%

Newfield Exploration United States Energy 9 64% 74%

Valeo France Auto & Components 6 69% 74% Nexans, Sandvik

Priceline Group United States Retailing 9 23% 73% Choice Htl Intl, Hilton Wrldwide, La Quinta

IAG United Kingdom Transportation 7 33% 73% Gategroup Holdg

Akzo Nobel Netherlands Materials 7 21% 71% Elementis

E I Du Pont De Nemours United States Materials 4 19% 70% Iluka

Anadarko Petroleum United States Energy 4 51% 70% Forum Energy Tec, RPC, TETRA

Micron Technology United States Semis 9 53% 69%Advantest, Applied, ChipMOS, HMI, Inotera, Lam Research,

Siltronic

Marathon Oil United States Energy 5 39% 68% Kirby, TETRA, Willbros Group

Kia Motors South Korea Auto & Components 7 47% 68%Hankook Tire, Hanon Systems, Hyundai Mobis, Hyundai Wia,

Mando Corp

Charter Comms.Cl.A United States Media 7 22% 67%CBS Corp, Comcast, Discovery Commns, Time Warner, Twenty-

First Fox, Viacom, Walt Disney

Alcatel-Lucent France Tech HW & Equip. 9 20% 67% Disco

Repsol Ypf Spain Energy 4 160% 67% Seadrill

Hess United States Energy 4 27% 66%

Maruti Suzuki India India Auto & Components 4 29% 65% Apollo Tyres, Bosch

Boeing United States Capital Goods 4 20% 65%

Alcoa, Constellium, Fuji Heavy, GE, Honeywell Intl, IHI, Kaiser

Aluminum, Kawasaki Heavy, Kennametal, MHI, Orbital ATK,

Precision Cast, Rolls-Royce Hldg, Safran, Teijin, Toray Industries,

Victrex, Zodiac Aero

Toyota Motor Japan Auto & Components 5 19% 64%

Aichi Steel, Aisan Industry, Aisin Seiki, Denso, Disco, Hino Motors,

Hitachi Metals, Ichikoh Ind, JFE Holdings, Jtekt, Kobe Steel, Koito

Mfg, Mitsui Min & Sml, NGK Insulators, Nippon Sheet G, NIPPON

STEEL, NTN, Somboon Adv Tech, Sumitomo EI, Thai Stanley,

Tokai Rika, Toyoda Gosei, Toyota Boshoku, Toyota Inds,

TsubakimotoChain

Kroger United States Food & Staples Rtl 5 28% 64% Equity One, Regency Center

Nvidia United States Semis 11 24% 64% CHROMA, SPIL, TSMC

Carmax United States Retailing 8 32% 63%

Macy'S United States Retailing 5 23% 63% Coach, General Grow, PVH, Ralph Lauren, Westfield

Target United States Retailing 4 23% 62%Amplify Snack, Columbia Sptswr, Logitech Inter, VF, Werner

Entprise

Caterpillar United States Capital Goods 4 10% 61%

Sony Japan Cons Dur & Apparel 8 26% 61% Disco, Merck, Samsung Elec

Royal Bank Of Sctl.Gp. United Kingdom Banks 9 8% 60%

Seagate Tech. Republic of Ireland Tech HW & Equip. 11 11% 60% Nidec, Shimizu

Interpublic Group United States Media 5 3% 60%CBS Corp, Comcast, Discovery Commns, Time Warner, Twenty-

First Fox, Viacom, Walt Disney

Bt Group United Kingdom Telecoms 5 4% 60% Computacenter

Fuji Heavy Inds. Japan Auto & Components 8 14% 59% Ichikoh Ind, Kobe Steel, NIPPON STEEL, Toyoda Gosei, Toyota

Tata Motors India Auto & Components 11 4% 59% Apollo Tyres, Bharat Forge

Dow Chemical United States Materials 4 6% 59% Air Liquide, Range Resource, Union Pacific, Vopak

Foot Locker United States Retailing 5 6% 58% adidas, General Grow, Macerich, Nike, Simon Prop Grp

Mitsui Japan Capital Goods 4 -3% 58% Chiyoda Corp, Hyundai E&C, JGC

Petrobras Brazil Energy 4 12% 58%

Baker Hughes, Halliburton, Noble Corp, SapuraKencana,

Schlumberger, Seacor Holdings, Sulzer, TETRA, Tidewater,

Transocn, WEG

Mazda Motor Japan Auto & Components 8 15% 58%DaikyoNishikawa, Kobe Steel, Nippon Sheet G, NIPPON STEEL,

PCS Mach Gp Hldg

Bmw Germany Auto & Components 4 17% 57%Autoneum Hold, Constellium, Georg Fis, Hella Hueck, Samsung

SDI

Renault France Auto & Components 6 -2% 56% LG Chem, Nissan, NTN, Takata, Textron

Nissan Motor Japan Auto & Components 6 1% 56%

Calsonic Kansei, Ichikoh Ind, JFE Holdings, Kobe Steel, Mitsui Min

& Sml, NGK Insulators, Nippon Sheet G, NIPPON STEEL, NTN,

Sumitomo EI, Takata, Topre, Unipres

Bank Of America United States Banks 6 32% 56% Boston Ppty, CBRE Group, Federal Realty, Proofpoint, Textron

Netflix United States Retailing 13 5% 55% CBS Corp

Chubu Elec.Power Japan Utilities 4 19% 55% Indo Tambangraya

14 November 2016


Figure 67: Stocks that generated a signal (i.e. earnings surprise) during the initial 5-day window and

sustained it over 40 trading days, using MSCI ACWI Industry Group benchmark

Note: Signals reflect earnings surprises, which we define here as share-price moves of over 5% over the five days surrounding an earnings release date. Based on data from January 2010 to December 2015. Past performance should not be taken as an indication or guarantee of future performance. Bolded stocks are under CS coverage. Source: Thomson Reuters, Credit Suisse PEERs, Credit Suisse research

Name Country GICS Level 2 Ind Grp

# of signals

based on T+2 /

T-2

# of signals based on

T+2 / T-2 & T+40 /

T+2

Average T+40 / T+2

returns of suppliers rel. to

MSCI regional

benchmarks, annualised


whose T+40 / T+2 returns

are in line with customer

surprise


Volkswagen Pref. Germany Auto & Components 8 4 77.0% 88% BorgWarner, Constellium, Hella Hueck, Schaeffler

Newfield Exploration United States Energy 18 10 61.6% 77%

Valeo France Auto & Components 12 6 51.6% 76% Nexans, Sandvik

D R Horton United States Cons Dur & Apparel 15 4 46.1% 75%

Akzo Nobel Netherlands Materials 9 6 13.3% 72% Elementis

Occidental Ptl. United States Energy 8 5 54.3% 72%

Skyworks Solutions United States Semis 21 13 92.0% 69% AWSC, Visual Photonics, Win

Carmax United States Retailing 17 4 17.5% 69%

Maruti Suzuki India India Auto & Components 11 5 29.4% 68% Apollo Tyres, Bosch

Baker Hughes United States Energy 11 5 12.0% 67% Hunting, SBO

Micron Technology United States Semis 18 9 38.6% 66% Advantest, Applied, ChipMOS, HMI, Inotera, Lam Research, Siltronic

Hess United States Energy 7 4 26.7% 66%

Toyota Tsusho Japan Capital Goods 8 4 27.6% 66% Infineon Technol, Toyota

Kia Motors South Korea Auto & Components 12 8 44.3% 65%Hankook Tire, Hanon Systems, Hyundai Mobis, Hyundai Wia, Mando

Corp

Royal Bank Of Sctl.Gp. United Kingdom Banks 12 7 16.7% 65%

Renault France Auto & Components 8 5 9.6% 64% LG Chem, Nissan, NTN, Takata, Textron

Bt Group United Kingdom Telecoms 7 6 13.1% 63% Computacenter

Peugeot France Auto & Components 8 4 24.0% 63%

Repsol Ypf Spain Energy 4 4 96.7% 63% Seadrill

Priceline Group United States Retailing 19 9 8.0% 62% Choice Htl Intl, Hilton Wrldwide, La Quinta

Sony Japan Cons Dur & Apparel 11 5 34.9% 61% Disco, Merck, Samsung Elec

IAG United Kingdom Transportation 7 4 20.2% 60% Gategroup Holdg

Seagate Tech. Republic of Ireland Tech HW & Equip. 15 9 7.7% 60% Nidec, Shimizu

Alcatel-Lucent France Tech HW & Equip. 19 12 12.7% 58% Disco

Interpublic Group United States Media 13 6 4.4% 58%CBS Corp, Comcast, Discovery Commns, Time Warner, Twenty-First

Fox, Viacom, Walt Disney

Tata Motors India Auto & Components 11 10 -0.5% 58% Apollo Tyres, Bharat Forge

Petrobras Brazil Energy 7 4 15.2% 58%

Baker Hughes, Halliburton, Noble Corp, SapuraKencana,

Schlumberger, Seacor Holdings, Sulzer, TETRA, Tidewater, Transocn,

WEG

Cigna United States H/C Equip & Svs 9 4 1.1% 57% Laboratory Corp, LifePoint Health, QuestDiagnostics, Tenet Healthcare

Foot Locker United States Retailing 11 4 4.3% 56% adidas, General Grow, Macerich, Nike, Simon Prop Grp

Whirlpool United States Cons Dur & Apparel 17 9 15.6% 56%

Nissan Motor Japan Auto & Components 7 5 5.2% 55%

Calsonic Kansei, Ichikoh Ind, JFE Holdings, Kobe Steel, Mitsui Min &

Sml, NGK Insulators, Nippon Sheet G, NIPPON STEEL, NTN,

Sumitomo EI, Takata, Topre, Unipres

Netflix United States Retailing 21 13 5.2% 55% CBS Corp

Isuzu Motors Japan Auto & Components 13 8 6.0% 55% PCS Mach Gp Hldg, Toyoda Gosei

Mazda Motor Japan Auto & Components 9 6 14.4% 55%DaikyoNishikawa, Kobe Steel, Nippon Sheet G, NIPPON STEEL, PCS

Mach Gp Hldg

14 November 2016


Appendix 4: Further reading Credit Suisse Research

Global Equity Themes: Exploiting Earnings Surprises (25 October 2010)

Global Equity Themes: Japanese Supply Chain Disruptions (17 March 2011)

Supply chain disruptions: Impact of Floods in Thailand (11 November 2011)

Global Equity Themes: Exploiting Earnings Surprises in Healthcare (14 December 2011)

Other publications

Agarwal, A., Prabhudev K., Alok K., and Alvin L. "A Study of Search Attention and Stock

Returns Cross Predictability." (Twenty-first Americas Conference on Information Systems,

Puerto Rico, 2015)

Alldredge, D. M., "The Performance of Institutional Investor Trades Across the Supply

Chain. " (PhD diss., University of Tennessee, 2015)

Barber, B. M., Odean, T., “All that Glitters: The Effect of Attention and News on the Buying

Behavior of Individual and Institutional Investors” (Review of Financial Studies 21-2, 2006,

pg.785-818)

Cohen, L. and Frazzini, A., “Economic Links and Predictable Returns” (Journal of Finance,

2008, vol. 63, issue 4, pages 1977-2011)

Daniel, K., Titman, S., “Market Reactions to Tangible and Intangible Information” The

Journal of Finance 61, 2006, pg.1605-1643)

DellaVigna, S., Pollet, J., “Investor Inattention, Firm Reaction, and Friday Earnings

Announcements” (NBER Working Paper 11683, 2005)

Di (Andrew) Wu, "Shock Spillover and Financial Response in Supply Chain Networks:

Evidence from Firm-Level Data" (Research Papers, University of Pennsylvania’s Wharton

School, 2016)

Ferment, F.P., "Analysis of recent changes in supply chain link predictability" (Erasmus

School of Economics, Bachelor Thesis, 2013)

Funkea, C., Gebkena, T., Johanning, L., and Michela, G., “Is It Really There? Predictability

of Supplier Returns After Large Customer Price Changes” (Source for Alpha AG and Otto

Beisheim School of Management, 2007)

Hirshleifer, D., Teoh, S.H., “Limited Investor Attention and Stock Market Misreactions to

Accounting Information” (unpublished working paper, 2006, Ohio State University)

Hirshleifer, D., and Teoh, S., “Limited Attention, Information Disclosure, and Financial

Reporting” (Journal of Accounting and Economics 36, 2006, pg.337-386)

Hirshleifer, D., Teoh, S. “Limited Investor Attention and Earnings-related Under- and

Overreactions” (unpublished working paper, 2006, Ohio State University)

Kewei, H., “Industry Information Diffusion and the Lead-Lag Effect in Stock Returns”

(Review of Financial Studies 20, 2006, pg.1113-1138)

Lamont, O. and Frazzini, A., “The Earnings Announcement Premium and Trading Volume”

(University of Chicago and Yale University, Working paper w13090, 2006)

Menzly, L., and Ozbas, O., “Market Segmentation and Cross-Predictability of Returns”

(The Journal of Finance 65, 2007)

Menzly, L., Ozbas, O., “Cross-industry Momentum” (unpublished manuscript, 2006,

University of Southern California)



https://plus.credit-suisse.com/r/yal0nw

https://plus.credit-suisse.com/r/yal0ic

14 November 2016


Meyricke, R., "Theoretical and empirical evidence of the influence of economic linkages on

stock returns" (PhD diss., University of Cambridge, 2012)

Moers, F., "Supply chain links and predictability of returns" (Erasmus School of

Economics, Bachelor Thesis, 2013)

Shahrur, H.K., Becker, Y.L., Rosenfeld, D “Return Predictability Along the Supply Chain:

The International Evidence” (Working Paper Series, 2009, Bentley University)

Timmermans, R., "Supply chain links predictability of returns" (Erasmus School of

Economics, Bachelor Thesis, 2013)

14 November 2016


Appendix 5: How to find Credit Suisse PEERS

Figure 68: Credit Suisse PEERs online tool


The PEERS database is a proprietary system maintained by research analysts that records the relationships the analysts

consider to be of significance to the stocks they cover. Started back in 2005 it has around 110,000 active relationships

recorded for the approximately 3,400 global stocks covered by Credit Suisse Research and over 10 years of journaled

history PEERS can be accessed online via our research portal CS Plus by searching for "PEERS" or by going to directly

to https://rave.credit-suisse.com/research/peers – please note online access to PEERS is only available for entitled users

and can be requested by emailing [email protected].

https://rave.credit-suisse.com/research/peers

14 November 2016


Companies Mentioned (Price as of 10-Nov-2016) 3M (MMM.N, $174.28) AAC Tech Hldg (A2XN.F, €8.476) ACS (ACS.MC, €28.845) AEON (8267.T, ¥1,476) AGL Energy (AGL.AX, A$19.66) AK Steel Holding Corp. (AKS.N, $7.3) ALFA (ALFAA.MX, MXN24.64) ANTA Sports (2020.F, €2.644) AP Moller Maersk (MAERSKb.CO, Dkr9210.0) APA Group (APA.AX, A$7.73) ARC Resources Ltd. (ARX.TO, C$22.71) ARM Holdings (ARM.L, 1700.0p) ASM Pacific Tech. (0522.HK, HK$75.8) ASML Holding N.V. (ASML.AS, €93.09) ASX (ASX.AX, A$46.95) AU Optronics (2409.TW, NT$11.8) AUO (AUOy.BEÂ12, €3.71) AUO (AUOy.BEÂ12, €3.71) AVEVA (AVV.L, 1700.0p) AVI Limited (AVIJ.J, R91.44) Abbott Laboratories (ABT.N, $40.61) Abercrombie & Fitch Co. (ANF.N, $15.69) Accenture Plc (ACN.N, $120.33) Acer Group (2353.TW, NT$13.5) Activision Blizzard, Inc (ATVI.OQ, $38.7) AdvancePierre Foods Holdings Inc. (APFH.N, $25.56) Advanced Micro Devices, Inc. (AMD.OQ, $6.3) Advanced Semicon. Engr. (2311.TW, NT$36.0) Advanced Wireless Semiconductor Company (8086.TWO, NT$43.65) Advantage Oil (AAV.N, $6.7) Advantest (6857.T, ¥1,485) Aena (AENA.MC, €124.45) AerCap Holdings (AER.N, $41.82) Aeroports de Paris (ADP.PA, €89.99) Aetna Inc. (AET.N, $119.9) Aggreko (AGGK.L, 831.5p) Agrium (AGU.TO, C$131.94) Agrium Inc. (AGU.N, $97.85) Aichi Steel (5482.NG, ¥5,130) Aimia (GAPFF.PK, $10.96) Air Berlin (AB1.DE, €0.59) Air China (0753.F, €0.587) Air France-KLM (AIRF.PA, €5.36) Air Lease (AL.N, $33.18) Air Liquide (AIRP.PA, €95.27) Air Products & Chemicals (APD.N, $139.98) Airbus Group (AIR.MC, €55.2) Airtac (1590.TW, NT$250.0) Aisan Industry (7283.NG, ¥250.0) Aisin Seiki (7259.NG, ¥4,610) Akamai Technologies Inc. (AKAM.OQ, $66.22) Aker Solutions (AKSOL.OL, Nkr36.27) AkzoNobel (AKZO.AS, €59.39) Alarm.com Holdings Inc. (ALRM.OQ, $30.17) Alcatel-Lucent (ALUA.PA, €3.5) Alfa Laval (ALFA.ST, Skr132.4) Alfresa Holdings (2784.T, ¥1,779) Alibaba (BABA.K, $94.34) Allerg (AGN.N^C15, $240.22) Allerg (AGN.N^C15, $240.22) Alliance Data (ALLD.DEÊ11, €40.35) Alliance Data (ALLD.DEÊ11, €40.35) Allison Transmission (ALSN.N, $30.4) Ally Financial Inc. (ALLY.N, $18.12) Almarai Co (2280.SE, SAR60.59) Alphabet (GOOGL.OQ, $780.29) Alps Electric (6770.T, ¥2,510) Alstom (ALSO.PA, €26.0) AltaGas (ALA.TO, C$32.09) Altice (ATCA.AS, €16.25) AmBev (ABEV3.SA, R$18.05) Amadeus (AMA.MC, €40.29) Amazon com Inc. (AMZN.OQ, $742.38) Amec Foster Wheeler (AMFW.L, 450.7p) American Airlines Group Inc. (AAL.OQ, $42.3) American Electric Power (AEP.N, $59.74) American International Group Inc. (AIG.N, $63.21) AmerisourceBergen (ABC.N, $79.59) Amkor Technology Inc. (AMKR.OQ, $11.16) Amorepacific Corp (090430.KS, W380,000) Amplify Snack Brands Inc (BETR.N, $14.34) Anadarko Petroleum Corp. (APC.N, $61.87) Analog Devices Inc. (ADI.OQ, $64.25) Anheuser-Busch InBev (ABI.BR, €98.59) Anritsu (6754.T, ¥548) Anton Oil (3337.F, €0.115) Aon plc (AON.N, $112.74) Apache Corp. (APA.N, $58.32) Apollo Tyres (APLO.NS, Rs195.55) Apple Inc (AAPL.OQ, $107.79) Applied Materials Inc. (AMAT.OQ, $28.18) ArcelorMittal (MT.N, $7.1) Archer Daniels Midland Inc. (ADM.N, $45.18) Archrock Partners, LP (APLP.OQ, $15.48)

Arconic (ARNC.K, $18.45) Arrow Electronics, Inc. (ARW.N, $62.79) Arvind (ARVN.NS, Rs388.45) Asahi Glass (5201.T, ¥715) Asahi Kasei (3407.T, ¥978) Assa Abloy (ASSAb.ST, Skr174.5) Associated British Foods (ABF.L, 2543.0p) Astellas Pharma (4503.T, ¥1,554) Astra International (ASII.JK, Rp8,300) AstraZeneca (AZN.ST, Skr509.5) Asustek (2357.TW, NT$273.5) Atlas Copco (ATCOa.ST, Skr280.7) Atos (ATOS.PA, €93.46) Atresmedia (A3M.MC, €9.49) Atwood Oceanics, Inc. (ATW.N, $7.47) Aurizon (AZJ.AX, A$4.95) Aurobindo Pharm (ARBN.NS, Rs792.2) AusNet Services (SPAU.SI, S$1.59) Autoneum (AUTON.S, SFr252.0) Avis Budget Group, Inc. (CAR.OQ, $37.9) Avnet Inc. (AVT.N, $43.52) Axalta Coating Systems (AXTA.N, $26.06) BAE Systems (BAES.L, 612.0p) BBA Aviation (BBA.L, 251.1p) BEC World Public Company Limited (BEC.BK, Bt20.3) BMW (BMWG.DE, €76.78) BOE Technology Group Co. Ltd (000725.SZ, Rmb2.77) BP (BP.F, €5.2) BP (BP.N, $33.94) BT Group (BT.L, 347.85p) BWP Trust (BWP.AX, A$2.91) BYD (1211.F, €5.758) BYD Electronic (0285.F, €0.838) Baker Hughes Inc. (BHI.N, $59.37) Ball Corporation (BLL.N, $75.89) Bank of America (8648.T, ¥1,885) Bankers Petrol (BNKq.L, 125.5p) Baozun Inc. (BZUN.OQ, $14.39) Barnes & Noble, Inc. (BKS.N, $10.95) Baxter International Inc. (BAX.N, $47.84) Baytex Energy (BTE.N, $3.9) Baytex Energy Corp. (BTE.TO, C$5.26) Bazaarvoice Inc. (BV.OQ, $4.75) Beach Energy (BPT.AX, A$0.79) Beiersdorf (BEIG.DE, €77.27) Beijing Airport (0694.F, €0.931) Beijing Shiji Information Technology Co., Ltd (002153.SZ, Rmb25.5) Bellatrix Explo (BXE.N, $0.7773) Berry Plastics Group (BERY.N, $44.35) Best Buy (BBY.N, $39.98) Bharat Forge (BFRG.NS, Rs880.85) Birchcliff Energy (BIR.TO, C$8.41) BlackBerry (BBRY.OQ, $7.17) Blackmores Ltd (BKL.AX, A$116.85) Boardwalk Pipeline Partners, LP (BWP.N, $16.61) Bodycote Plc (BOY.L, 593.5p) Boeing (BOEB.L, $70.96) Bonavista Energy Corporation (BNP.TO, C$4.29) BorgWarner, Inc. (BWA.N, $35.2) Bosch (BOSH.NS, Rs20866.35) Boston Properties, Inc. (BXP.N, $122.31) Boston Scientific Corp (BSX.N, $21.88) Box, Inc. (BOX.N, $14.77) Brambles (BXB.AX, A$11.67) Brandywine Realty Trust (BDN.N, $14.21) Breville Group (BRG.AX, A$8.83) Bridgestone (5108.NG, ¥3,663) Brilliance China Automotive Holdings Limited (1114.HK, HK$9.91) Bristol Myers Squibb Co. (BMY.N, $56.66) British Land (BLND.L, 581.0p) Brooks Automation Inc. (BRKS.OQ, $14.18) Builders FirstSource (BLDR.OQ, $10.1) Bumi Armada Bhd (BUAB.KL, RM0.68) Bunge Limited (BG.N, $67.36) Bunzl (BNZL.L, 2081.0p) Burberry Group (BRBY.L, 1441.0p) Bureau Veritas (BVI.PA, €17.14) CBRE Group (CBG.N, $27.69) CBS Corp (CBSa.N, $57.73) CF Industries Holding Inc. (CF.N, $27.13) CJ Cheiljedang (097950.KS, W373,500) CNOOC (0883.BE, €1.154) CNOOC (0883.HK, HK$9.79) CONSOL Energy Inc. (CNX.N, $17.63) COSL (2883.F, €0.827) CP (CP.TO, C$197.0) CVS Health (CVS.N, $77.28) Cadence Design System (CDNS.OQ, $24.84) Calsonic Kansei (7248.T, ¥1,294) Campbell Soup Company (CPB.N, $53.31) Canadian Natural Resources Limited (CNQ.TO, C$41.73) Cap & Counties (CCOJ.J, R48.8)

Capita (CPI.L, 562.5p) CarMax Inc. (KMX.N, $52.73) Cardinal Health (CAH.N, $71.72) Carlsberg (CARLb.CO, Dkr592.5) Carrefour (CARR.PA, €22.48) Carrizo Oil & Gas Inc. (CRZO.OQ, $36.82) Casetek Holdings Limited (5264.TW, NT$81.7) Caterpillar Inc. (CAT.N, $93.45) Celanese Corporation (CE.N, $76.29) Cellnex Telecom (CLNX.MC, €13.03) Centrica (CNA.L, 205.0p) Charles River Laboratories International Inc. (CRL.N, $75.37) Charter Communications Inc. (CHTR.OQ, $270.87) Charter Hall Group (CHC.AX, A$4.45) Charter Hall Retail REIT (CQR.AX, A$4.14) Check Point Software Technologies Ltd. (CHKP.OQ, $85.15) Cheniere Energy Partners, LP (CQP.A, $27.95) Chesapeake Energy Corp. (CHK.N, $5.7) Chevron Corp. (CVX.N, $107.79) Chicago Bridge & Iron (CBI.N, $31.05) China Eastern (CIAH.BE, €0.404) China Mobile Limited (0941.HK, HK$87.1) China Power International (2380.HK, HK$2.78) China Telecom (0728.F, €0.461) China Unicom HK (0762.BE, €1.048) ChipMOS Technologies Inc. (8150.TW, NT$23.5) Chipbond (6147.TWO, NT$45.1) Chiyoda Corp (6366.T, ¥888) Choice Hotels (CHH.N, $49.5) Chr Hansen Hldg (CHRH.F, €49.442) Chroma (2360.TW, NT$78.0) Chubu Elec (9502.NG, ¥1,545) Chubu Electric Power (9502.T, ¥1,542) Chugai Pharmaceutical (4519.T, ¥3,355) Cigna Corporation (CI.N, $134.77) Cinemark Holdings, Inc (CNK.N, $40.01) Cisco Systems Inc. (CSCO.OQ, $31.0) Citigroup (8710.T, ¥4,660) Citrix Systems Inc. (CTXS.OQ, $86.72) Cliffs Natural Resources Inc. (CLF.N, $7.4) Coach Inc (COH.N, $36.72) Coca-Cola Amatil (CCL.AX, A$9.59) Coca-Cola Euro (CCE.MC, €33.0) Cognizant Technology Solutions Corp. (CTSH.OQ, $53.81) Columbia (COLM.OQ, $58.75) Comcast Corporation Inc. (CMCSA.OQ, $65.1) Commercial Metals Co. (CMC.N, $20.35) Community Health Systems, Inc. (CYH.N, $4.95) Companhia Siderurgica Nacional (CSNA3.SA, R$11.25) Computacenter (CCC.L, 718.0p) Conagra Brands (CAG.N, $34.3) Concho Resources, Inc. (CXO.N, $131.25) ConocoPhillips (COP.N, $44.78) Constellium (CSTM.N, $5.9) Continental (CONG.DE, €160.1) Continental Building Products (CBPX.N, $20.45) Continental Resources, Inc (CLR.N, $47.29) Coolpad Group Limited (2369.HK, HK$1.06) Coretronic Corp (5371.TWO, NT$31.15) Corporate Office Properties Trust (OFC.N, $27.28) Corus Entmt (CJREF.PK, $17.49) Costamare Inc. (CMRE.N, $6.51) Costco Wholesale Corporation (COST.OQ, $146.7) Cott (BCB.TO, C$18.57) Crescent Point (CPG.N, $10.91) Crew Energy Inc (CR.TO, C$6.76) Crown Holdings Inc. (CCK.N, $52.69) Cummins Inc. (CMI.N, $137.81) DISCO (6146.T, ¥12,940) DISH Network Corporation (DISH.OQ, $56.38) DKSH Holdings (DKSH.S, SFr67.6) DNB (DNB.OL, Nkr122.4) DNF (092070.KQ, W14,400) DR Horton (DHI.N, $27.52) DUET Group (DUE.AX, A$2.3) Daewoo E&C (047040.KS, W6,590) Daido Steel (5471.NG, ¥400) Daiichi Sankyo (4568.T, ¥2,368) DaikyoNishikawa (4246.T, ¥1,228) Daimler (DAIGn.DE, €63.69) Dairy Crest (DCG.L, 603.0p) Danaher Corporation (DHR.N, $80.24) Danone (DANO.PA, €58.0) Danske Bank (DANSKE.CO, Dkr204.0) Dassault Aviation (AVMD.PA, €1033.95) Dassault Systemes (DAST.PA, €69.91) Datang Power (0991.DE^B16, €0.264) Datang Power (0991.DE^B16, €0.264) Dean Foods Company (DF.N, $18.85) Deckers Brands (DECK.N, $57.35) Deere & Co. (DE.N, $90.7)

14 November 2016


Delek US Holdings, Inc. (DK.N, $17.07) Delta Air Lines, Inc. (DAL.N, $45.95) Denka (4061.T, ¥467) Denso (6902.NG, ¥4,568) Denso (6902.T, ¥4,525) Derwent London (DLN.L, 2435.0p) Deutsche Lufthansa (LHAG.DE, €12.46) Deutsche Post DHL (DPWGn.DE, €28.62) Devon Energy Corp (DVN.N, $43.14) Diageo (DGE.BE, €23.21) Dialog Semiconductor (DLGS.DE, €35.88) Diamond Offshore Drilling, Inc (DO.N, $16.54) Diamondback Energy, Inc. (FANG.OQ, $97.37) Dick's Sporting Goods (DKS.N, $59.3) Digital China Holdings Limited (0861.HK, HK$6.43) Digital Telecom Infrastructure Fund (DIFu.BK, Bt14.8) Dillard's Inc. (DDS.N, $70.47) Discovery Communications (DISCA.OQ, $26.03) Dixons Carphone Plc (DC.L, 321.9p) Dominion Resources (D.N, $71.13) Dongfang Elec (1072.F, €0.698) Dongfang Electric Corporation Limited (600875.SS, Rmb9.85) Dongfeng Group (0489.F, €0.94) Dongjiang Env (0895.BE, €1.535) Doosan Heavy Industries & Construction (034020.KS, W26,550) Dover Corporation (DOV.N, $71.61) Dow (4850.T, ¥5,630) Dow Chemical Company (DOW.N, $54.15) Dr Pepper Snapple Group (DPS.N, $83.24) DuPont de Nemours and Co. (DD.N, $70.95) Duke Energy (DUK.N, $75.16) Dulux Group (DLX.AX, A$6.14) Dynagas LNG Partners LP (DLNG.N, $13.77) E Ink Holdings Inc (8069.TWO, NT$25.95) ENAV SpA (ENAV.MI, €3.16) ENI (ENI.MI, €12.75) EOG Resources (EOG.N, $92.63) Eastman Chemical (EMN.N, $75.74) EasyJet (EZJ.L, 1038.0p) Eaton Corporation (ETN.N, $68.7) Eclat Textile Co., Ltd. (1476.TW, NT$323.5) Edwards LifeSciences Corp. (EW.N, $92.85) Egis Technology Inc. (6462.TWO, NT$238.0) Eisai (4523.T, ¥6,714) Elan Microelectronics Corp (2458.TW, NT$33.3) Electricite de France (EDF.PA, €9.908) Electrolux (ELUXb.ST, Skr213.7) Electronic Arts, Inc (EA.OQ, $76.79) Elementis (ELM.L, 254.4p) Embraer (ERJ.N, $22.0) Emerson (EMR.N, $55.75) EnLink Midstream Partners (ENLK.N, $16.77) Enable Midstream Partners (ENBL.N, $16.27) Enbridge Energy Partners, LP (EEP.N, $23.48) Enbridge Inc. (ENB.TO, C$56.64) Enbridge Income Fund Holdings (ENF.TO, C$33.55) Encana (ECA.TO, C$14.32) Endesa (ELE.MC, €18.04) Endo Health Solutions (ENDP.OQ, $17.48) Endologix (ELGX.OQ, $9.88) Enel (ENEI.MI, €3.65) Energy Absolute (EAm.BK, Bt29.75) Energy Recovery Inc. (ERII.OQ, $10.49) Enerplus (ERF.N, $6.67) Ensco Plc. (ESV.N, $8.17) Entergy Corp (ETR.N, $67.87) Epistar Corporation (2448.TW, NT$21.1) Equiniti (EQN.L, 196.25p) Equinix (EQIX.OQ, $330.8) Equity One (EQY.N, $27.15) Ericsson (ERICb.ST, Skr46.29) Esterline Technologies (ESL.N, $78.95) Eutelsat Communications (ETL.PA, €18.26) Evergreen Marine (2603.TW, NT$11.55) Everlight Electronics Co Ltd (2393.TW, NT$45.95) Everyday Health, Inc. (EVDY.N, $10.5) Evolva (EVE.S, SFr0.41) Evonik (EVKn.DE, €25.91) ExOne (XONE.OQ, $10.86) Exedy (7278.T, ¥2,917) Exide Ind (EXID.NS, Rs193.6) Exova (EXO.L, 195.5p) Expedia (EXPE.OQ, $123.63) Expeditors International of Washington (EXPD.OQ, $50.57) Experian (EXPN.L, 1444.0p) Express Scripts (ESRX.OQ, $75.39) ExxonMobil Corporation (XOM.N, $87.05) FIH Mobile (FW3.F, €0.28) FMC Technologies, Inc. (FTI.N, $34.48) Far EasTone Telecom (4904.TW, NT$73.9) FedEx Corporation (FDX.N, $183.57)

Federal Realty Investment Trust (FRT.N, $136.98) Feng Tay Enterprises Co., Ltd. (9910.TW, NT$125.0) Fiat Chrysler Automobile (FCHA.MI, €6.755) Fibra Prologis (FIBRAPL14.MX, MXN30.46) Fibra Uno Administracion S A (FUNO11.MX, MXN31.17) Fidelity National Information Services Inc (FIS.N, $77.05) Fincantieri (FCT.MI, €0.4184) First Data Corporation (FDC.N, $14.14) First Solar (FSLR.OQ, $31.95) Flowserve Corp. (FLS.N, $45.94) Flughafen Zuerich AG (FHZN.S, SFr171.6) Fluor (FLR.N, $50.4) Foot Locker, Inc. (FL.N, $71.63) Ford Motor Company (F.N, $11.94) Ford Otosan (FROTO.IS, TL30.48) Formosa Plastics (1301.TW, NT$86.4) Fortune Brands (FBHS.N, $55.74) Forum Energy Technologies, Inc. (FET.N, $18.7) Frank's International (FI.N, $11.01) Fresenius (FREG.DE, €68.3) Fuji Heavy Industries (7270.T, ¥3,805) Fujikura (5803.T, ¥620) Fujitsu (6702.NG, ¥597) Fuyao Glass Industry Group Co., Ltd. (600660.SS, Rmb17.8) G.U.D. Holdings (GUD.AX, A$9.7) GE (GECG.L, €19.0) GEA Group (G1AG.DE, €33.45) GasLog Partners LP (GLOP.N, $20.15) Gategroup Holding (GATE.S, SFr51.45) Gemalto (GTO.AS, €47.41) General Dynamics Corporation (GD.N, $166.51) General Electric (GE.N, $30.41) General Growth Properties (GGP.N, $25.25) adidas (ADSGn.DE, €131.7) dorma+kaba (DOKA.S, SFr720.0) eBay Inc. (EBAY.OQ, $28.16) GKN (GKN.L, 305.8p) GOME (0493.F, €0.105) GPT Group (GPT.AX, A$4.52) GS Yuasa Corp (6674.T, ¥441) GSK (GSK.F, €18.293) General Mills (GIS.N, $61.07) General Motors Company. (GM.N, $32.73) Genesee & Wyoming, Inc. (GWR.N, $75.02) Genesis Energy, LP (GEL.N, $33.63) Georg Fischer (FIN.S, SFr856.0) Gerresheimer AG (GXIG.DE, €67.03) Gibson Energy Inc. (GEI.TO, C$16.2) Gildan Activewear Inc. (GIL.N, $25.24) Global Logistic Properties (GLPL.SI, S$2.08) Global Power Synergy (GPSC.BK, Bt35.75) Globaltrans (GLTRq.L, $4.9) GoerTek Inc. (002241.SZ, Rmb30.35) Goldman Sachs Group, Inc. (GS.N, $200.87) Goldwind (2208.F, €1.329) Goodman Group (GMG.AX, A$6.56) Gree Electric Appliances Inc of Zhuhai (000651.SZ, Rmb22.4) Green Dragon Gas (GDG.L, 192.375p) Green REIT PLC (GN1.I, €1.25) Grupo Aeroportuario del Centro Norte (OMAB.MX, MXN102.14) Grupo Aeroportuario del Pacifico (GAPB.MX, MXN168.61) Grupo Aeroportuario del Sureste (ASURB.MX, MXN293.53) Gudang Garam (GGRM.JK, Rp67,950) GulfMark Offshore (GLF.N, $1.3) Gulfport Energy (GPOR.OQ, $23.42) Guodian Technology & Environment Group Corporation (1296.HK, HK$0.59) HAECO (0044.HK, HK$53.1) HCA Holdings, Inc. (HCA.N, $72.06) HDPI (1071.F, €0.358) HIAG Immobilien (HIAG.S, SFr103.5) HNPIT (0902.F, €0.55) Haier Electronics Group Co., Ltd. (1169.HK, HK$13.32) Halliburton (HAL.N, $48.81) Halma (HLMA.L, 1027.0p) Hammerson (HMSO.L, 542.5p) Han's Laser Technology Co., Ltd (002008.SZ, Rmb23.65) HanOn Systems (018880.KS, W10,300) Hanesbrands Inc. (HBI.N, $24.43) Hanjaya Mandala Sampoerna (HMSP.JK, Rp4,000) Hankook Tire (161390.KS, W55,300) Harbin Power (HP6H.F, €0.43) Hays (HAYS.L, 139.8p) Heineken (HEIN.AS, €71.21) Helix Energy Solutions (HLX.N, $9.32) Hella (HLE.DE, €33.22) Helmerich & Payne, Inc. (HP.N, $63.69)

Henkel KGaA (HNKG_p.DE, €109.85) Hess Corporation (HES.N, $49.64) Hewlett Packard (HPQ.N, $15.49) Hi-Crush Partners, LP (HCLP.N, $16.45) Hilong (1623.HK, HK$2.01) Hilton Worldwide Holdings (HLT.N, $23.46) Himax (H6Qy.BE, €6.792) Hino Motors (7205.NG, ¥1,092) Hirose Electric (6806.T, ¥13,470) Hitachi (6501.NG, ¥556) Hitachi Chemical (4217.T, ¥2,447) Hitachi Construction Machinery (6305.T, ¥2,263) Hitachi Kokusai Electric (6756.T, ¥2,187) Hitachi Metals (5486.T, ¥1,360) Hiwin (2049.TW, NT$131.5) Home Depot (HD.N, $129.03) Hon Hai Precision (2317.TW, NT$81.5) Honda Motor (7267.T, ¥2,980) Honeywell International Inc. (HON.N, $113.19) Honeywell Intl (HONH.L, $61.468120559999996) Hornbeck Offshore (HOS.N, $4.63) Hortonworks, Inc. (HDP.OQ, $8.94) Hua Hong Semiconductor Limited (1347.HK, HK$9.25) Huayu Automotive Systems Co., Ltd (600741.SS, Rmb16.16) Hudson's Bay Company (HBC.TO, C$16.56) Hugo Boss (BOSSn.F, €59.3) Humana Inc. (HUM.N, $192.88) Hunting Plc (HTG.L, 492.8p) Huon Aquaculture Group Limited (HUO.AX, A$3.54) Hutchison Port Holdings Trust (HPHT.SI, $0.435) Hyatt Hotels (H.N, $52.6) Hypermarcas S.A. (HYPE3.SA, R$24.92) Hyundai E&C (000720.KS, W43,700) Hyundai Heavy Industries (009540.KS, W146,000) Hyundai Marine & Fire (001450.KS, W36,750) Hyundai Mobis (012330.KS, W248,000) Hyundai Motor Company (005380.KS, W129,000) Hyundai Wia (011210.KS, W71,000) IAG (ICAG.MC, €4.997) IBM (IBMI.L, $211.53) ICON PLC (ICLR.OQ, $82.24) IENOVA (IENOVA.MX, MXN77.83) IHI (7013.NG, ¥296) IMAX Corp (IMAX.N, $32.4) IMI (IMI.L, 977.0p) INPEX Corp (1605.T, ¥975) INWIT (INWT.MI, €4.07) IRESS (IRE.AX, A$11.26) ITV (ITV.L, 168.1p) Ibiden (4062.NG, ¥1,366) Ichikoh Industries (7244.T, ¥328) Iluka Resources (ILU.AX, A$6.2) Imagination Technologies (IMG.L, 217.75p) Indofood Agri Resources Ltd (IFAR.SI, S$0.48) Indofood CBP (ICBP.JK, Rp9,425) Indofood Sukses Makmur (INDF.JK, Rp8,300) Indorama Ventures PCL (IVL.BK, Bt32.25) Indra (IDR.MC, €10.6) Infineon Technologies AG (IFXGn.DE, €15.41) Ingredion Inc (INGR.N, $119.71) Inmarsat PLC (ISA.L, 723.0p) Innolux Corporation (3481.TW, NT$11.05) Inotera Memories, Inc. (3474.TW, NT$29.65) Insurance Australia Group (IAG.AX, A$5.43) Intel Corp. (INTC.OQ, $34.5) Intercontinental Hotels (IHG.L, 3110.0p) International Paper Co. (IP.N, $45.81) Interpublic Group (IPG.N, $21.87) Intertek (ITRK.L, 3162.0p) Intu Prop (ITUJ.J, R46.18) Iochpe-Maxion (MYPK3.SA, R$14.0) Isuzu Motors (7202.T, ¥1,270) Itron (ITRI.OQ, $59.35) J Sainsbury (SBRY.L, 230.5p) JB Hunt Transport Services (JBHT.OQ, $88.07) JC Penney (JCP.N, $8.81) JCDecaux (JCDX.PA, €24.78) JD.com, Inc. (JD.OQ, $24.39) JFE Holdings (5411.NG, ¥1,685) JGC Corp (1963.T, ¥1,842) JPMorgan (JPMJ.L, $41.59) JSR (4185.T, ¥1,537) Jacobs Engineering (JEC.N, $55.89) James Hardie Industries plc (JHX.AX, A$18.9) Japan Aviation Electronics Industry (6807.T, ¥1,466) Jazz Pharmaceuticals (JAZZ.OQ, $114.31) JetBlue Airways Corporation (JBLU.OQ, $19.2) Jiangsu Changjiang Electronics Technology Co., Ltd (600584.SS, Rmb19.7) Johnson & Johnson (JNJ.N, $119.54) Johnson Controls (JCI.N^I16, $47.591604000000004)

14 November 2016


Johnson Electric Holdings Limited (0179.HK, HK$19.12) Johnson Matthey (JMT2.BE, €37.405) Jtekt (6473.NG, ¥1,465) KBR Inc. (KBR.N, $15.62) KDDI (9433.T, ¥2,930) KLA-Tencor Corp. (KLAC.OQ, $74.51) KMG Chemicals (KMG.N, $29.68) Kaiser Aluminum Corp. (KALU.OQ, $78.86) Kalbe Farma (KLBF.JK, Rp1,670) Kansai Electric Power (9503.T, ¥1,040) Kansas City Southern (KSU.N, $81.11) Kawasaki Heavy (7012.NG, ¥300) Kawasaki Kisen (9107.NG, ¥300) Keihin (7251.T, ¥1,665) Kellogg Company (K.N, $72.65) Kelt Exploration Ltd (KEL.TO, C$5.71) Kennametal Inc. (KMT.N, $33.72) Kering (PRTP.PA, €194.0) Keyence (6861.T, ¥76,470) Keyera Corp. (KEY.TO, C$38.53) Kia Motors (000270.KS, W38,100) Kilroy Realty Corp. (KRC.N, $68.45) Kimberly-Clark Corporation (KMB.N, $112.15) Kimco Realty (KIM.N, $25.66) Kinder Morgan, Inc. (KMI.N, $21.53) Kirby Corporation (KEX.N, $64.75) Klépierre (LOIM.PA, €34.97) Knight Transportation (KNX.N, $33.1) Kobe Steel (5406.NG, ¥870) Kohl's Corporation (KSS.N, $50.97) Koito Manufacturing (7276.T, ¥5,430) Koninklijke DSM NV (DSMN.AS, €56.5) Korea Gas Corp (036460.KS, W45,250) Korean Air (003490.KS, W30,700) Kroger Co. (KR.N, $32.87) Krung Thai Bank (KTB.BK, Bt17.2) Kudelski (KUD.S, SFr16.65) Kumho Tire (073240.KS, W10,050) Kuraray (3405.T, ¥1,568) Kyocera (6971.T, ¥5,089) Kyowa Hakko Kirin (4151.T, ¥1,586) L Brands, Inc. (LB.N, $68.13) L'Oreal (OREP.PA, €158.95) LG Chem Ltd. (051910.KS, W241,000) LG Display Co Ltd. (034220.KS, W27,200) LG Electronics Inc (066570.KS, W46,700) LG Household & Healthcare (051900.KS, W888,000) LIXIL Group (5938.NG, ¥2,310) LLOYDS BANKING GROUP (LLOY.L, 59.63p) La Quinta Holdings Inc. (LQ.N, $10.92) LabCorp of America (LH.N, $126.21) Lam Research Corp. (LRCX.OQ, $95.97) Land Securities (LAND.L, 975.5p) Lantheus Medical Imaging, Inc. (LNTH.OQ, $9.45) Lanxess (LXSG.DE, €58.81) Legrand SA (LEGD.PA, €53.88) Lennar (LEN.N, $41.84) Lenovo Group (0992.DE, €0.574) Lens Technology Co., Ltd (300433.SZ, Rmb27.53) Lextar (3698.TW, NT$12.5) Li & Fung Ltd (0494.HK, HK$3.61) Li Ning (2331.F, €0.649) LifePoint Health, Inc. (LPNT.OQ, $53.75) Lightstream Resources Ltd (LTS.TO^J16, C$0.12) Linde (LING.DE, €152.5) Lite-On Technology (2301.TW, NT$45.05) Lockheed Martin Corporation (LMT.N, $257.27) Logitech Inter (LOGI.OQ, $24.18) London Sumatra (LSIP.JK, Rp1,465) Lowe's (LOW.N, $69.46) Lundbeck (LUN.CO, Dkr255.5) Luxfer (LXFR.N, $9.65) Luxottica Group (LUX.MI, €48.16) Luxshare Precision Industry Co., Ltd (002475.SZ, Rmb21.4) LyondellBasell Industries (LYB.N, $83.35) MGIC Investment Corporation (MTG.N, $8.88) MHI (7011.NG, ¥422) MMA Offshore Limited (MRM.AX, A$0.285) MTU Aero Engines (MTXGn.DE, €94.7) MacDonald, Dettwiler and Associates Ltd. (MDA.TO, C$72.47) Macerich Company (MAC.N, $69.36) Macy's Inc. (M.N, $40.53) Maersk (MAERSKa.CO, Dkr8765.0) Mahindra (MAHM.NS, Rs1321.3) Mahindra CIE (MAHN.NS, Rs193.0) Makalot Industrial Co., Ltd. (1477.TW, NT$111.5) Makita (6586.NG, ¥111.5) Mando Corp (204320.KS, W239,500) Marathon Oil Corp (MRO.N, $15.14) Marfrig Global Foods (MRFG3.SA, R$5.26) Marks & Spencer (MKS.L, 316.8p) Marriott International (MAR.OQ, $73.42) Marsh McLennan (MHMM.L, $73.42)

Maruti Suzuki In (MRTI.NS, Rs5328.5) Marvell Technology Group Ltd. (MRVL.OQ, $12.49) Masco (MAS.N, $31.45) MasterCard Inc. (MA.N, $104.5) Matahari Putra Prima (MPPA.JK, Rp1,735) Mazda Motor (7261.T, ¥1,563) McDermott International (MDR.N, $5.31) McDonald's Corp (MCD.N, $114.51) McKesson (MCK.N, $147.49) Media Nusantara Citra (MNCN.JK, Rp1,985) MediaTek Inc. (2454.TW, NT$222.0) Mediaset (MS.MI, €2.34) Medidata Solutions Inc. (MDSO.OQ, $52.99) Medipal Holdings (7459.T, ¥1,528) Medtronic (MDT.N, $82.72) Meggitt (MGGT.L, 459.1p) Merck KGaA (MRCG.DE, €95.51) Merlin Properties (MRL.MC, €9.23) Merry Electronics Co. Ltd (2439.TW, NT$120.0) Metso (METSO.HE, €26.47) Mexichem (MEXCHEM.MX, MXN42.06) Michael Kors (KORS.N, $51.76) Micron Technology Inc. (MU.OQ, $16.99) Microsoft Corporation (MSFT.OQ, $58.7) Midea Group Co Ltd (000333.SZ, Rmb27.57) Mills Estruturas e Servicos de Engenharia S.A. (MILS3.SA, R$4.08) Minth Group (0425.F, €2.998) Mirvac Group (MGR.AX, A$2.02) Mitsubishi (8058.NG, ¥2,375) Mitsubishi Chemical (4188.T, ¥671) Mitsubishi Elec (MELM.L, ¥968) Mitsubishi Est (8802.NG, ¥1,966) Mitsubishi Gas Chemical (4182.T, ¥1,685) Mitsubishi Heavy Industries (7011.T, ¥454) Mitsubishi Motors (7211.T, ¥525) Mitsubishi Tanabe Pharma (4508.T, ¥2,081) Mitsui Chemicals (4183.T, ¥484) Mitsui Co (8031.NG, ¥1,430) Mitsui Mining & Smelting (5706.T, ¥228) Mitsui Osk (9104.NG, ¥232) Mohawk Industries (MHK.N, $202.38) Molina Healthcare, Inc. (MOH.N, $50.38) Moneysupermarket.com (MONY.L, 280.6p) Monsanto Company (MON.N, $97.93) Monster Beverage Corp (MNST.OQ, $42.33) Mosaic Co. (MOS.N, $28.23) Multi Packaging Solutions (MPSX.N, $12.51) Murata Manufacturing (6981.T, ¥13,230) Murphy Oil Corp. (MUR.N, $28.71) Musashi Seimitsu (7220.NG, ¥28.71) Mylan NL (MYL.TA, agora14960.0) NEC (6701.T, ¥288) NGK Insulators (5333.NG, ¥1,820) NGK Spark Plug (5334.NG, ¥2,167) NIPPON STEEL (5401.NG, ¥2,072) NRW Holdings Limited (NWH.AX, A$0.54) NSG Group (5202.T, ¥773) NSK (6471.T, ¥1,133) NTN (6472.T, ¥364) NVIDIA Corporation (NVDA.OQ, $67.77) NVR Inc. (NVR.N, $1511.86) NXP Semiconductors N.V. (NXPI.OQ, $96.59) Nabors Industries, Ltd. (NBR.N, $12.66) Nabtesco Corp (6268.T, ¥2,924) Nan Ya Plastics (1303.TW, NT$66.0) Nanya Technology (2408.TW, NT$40.2) National Grid (NG.L, 943.9p) National Oilwell (NOV.D, €29.93) Netflix, Inc. (NFLX.OQ, $115.42) Newfield Exploration (NFX.N, $38.84) Newpark Resources, Inc. (NR.N, $6.7) Nexans (NEXS.PA, €49.76) Nexen Tire (002350.KS, W13,650) Next (NXT.L, 4891.0p) NextDC (NXT.AX, A$3.56) NextEra Energy Inc. (NEE.N, $115.06) Nexteer Automotive Group Limited (1316.HK, HK$9.66) Nidec (6594.T, ¥10,185) Nielsen Holdings (NLSN.N, $44.87) Nien Made Enterprise Co., Ltd. (8464.TW, NT$365.0) Nifco (7988.T, ¥6,040) Nike Inc. (NKE.N, $50.39) Nippon Electric Glass (5214.T, ¥560) Nippon Kayaku (4272.T, ¥1,224) Nippon Shokubai (4114.T, ¥6,920) Nippon Yusen (9101.NG, ¥182) Nissan Motor (7201.T, ¥983) Nissha Printing (7915.T, ¥2,543) Noble Corp (NLC.MU, €4.365) Noble Energy (NBL.N, $37.32) Nokia (NOKIA.HE, €4.09) Nordea Bank (NDA1V.HE, €9.7) Nordic American Offshore (NAO.N, $2.75)

Nordstrom (JWN.N, $56.03) Norfolk Southern (NSC.N, $100.5) Norsk Hydro (NHYN.L, 385.75p) Northrop Grumman Corporation (NOC.N, $245.17) Novatek Microelectronics Corp Ltd (3034.TW, NT$108.0) Novo Nordisk A/S (NOVOb.CO, Dkr230.9) NuStar Energy, LP (NS.N, $45.98) NuVista Energy (NVA.TO, C$6.82) Nucor Corporation (NUE.N, $59.14) OC Oerlikon Corp AG (OERL.S, SFr9.01) ONGC (ONGC.NS, Rs276.0) Occidental Petroleum (OXY.N, $65.72) Ocean Rig UDW Inc (ORIG.OQ, $1.09) Oil Search (OSH.AX, A$6.6) Oil States International (OIS.N, $31.4) Okuma (6103.NG, ¥31.4) Omnicom Group Inc. (OMC.N, $80.37) Ono Pharmaceutical (4528.T, ¥2,606) Orange (ORAN.PA, €13.68) Orbital ATK Inc. (OA.N, $80.63) Orica (ORI.AX, A$17.75) Origin Energy (ORG.AX, A$5.42) Osaka Gas (9532.T, ¥433) Osaka Gas Co (9532.NG, ¥420) Otsuka Holdings (4578.T, ¥4,706) Outokumpu (OUT1V.HE, €7.24) Owens & Minor (OMI.N, $32.29) Owens Illinois (OI.N, $18.93) P.C.S. Machine Group Holding (PCSGH.BK, Bt4.56) PCCW (0008.HK, HK$4.53) PDC Energy (PDCE.OQ, $65.05) PG&E Corp. (PCG.N, $58.5) PPG Industries, Inc (PPG.N, $96.87) PSA Peugeot Citroen (PEUP.PA, €13.68) Pacific Txtils (1382.F, €1.065) Painted Pony (PDPYF.PK, $5.6464) Palo Alto Networks (PANW.N, $151.91) Panasonic (6752.NG, ¥956) Parade Technologies (4966.TWO, NT$345.0) Paramount Resources Ltd (POU.TO, C$14.53) Parker Hannifin Corporation (PH.N, $136.97) Patterson-UTI Energy, Inc. (PTEN.OQ, $22.39) PayPal Holdings, Inc. (PYPL.OQ, $40.45) Peabody Energy Corporation (BTU.N, $2.07) Pembina Pipeline Corporation (PPL.TO, C$39.03) Pengrowth Energy Corp. (PGF.TO, C$1.76) Penn West (PWE.N, $1.55) Pentair Plc (PNR.N, $60.24) PepsiCo, Inc. (PEP.N, $103.25) Perrigo Company (PRGO.TA, agora33820.0) Perusahaan Gas Negara (PGAS.JK, Rp2,510) PetroChina (0857.DE, €0.633) PetroChina (0857.HK, HK$5.27) PetroVietnam Technical Services Corporation (PVS.HN, D18000.0) Petrobras (PBR.N, $10.34) Petrofac (PFC.L, 766.5p) Peyto Exploration & Development Corp. (PEY.TO, C$33.85) Pfizer (PFE.ST, Skr303.5) Philips (PHG.AS, €27.14) Phillips 66 (PSX.N, $83.09) Phillips 66 Partners, LP (PSXP.N, $44.44) Phillips-Van Heusen (PVH.N, $112.3) Pioneer Foods (PFGJ.J, R160.56) Pioneer Natural Resources (PXD.N, $179.43) Plains GP Holdings, LP (PAGP.N, $12.14) Ply Gem Holdings, Inc. (PGEM.N, $14.45) Power Xinchen (1148.HK, HK$1.33) Powertech Technology (6239.TW, NT$87.4) Praxair Inc. (PX.N, $120.23) Premier Foods (PFD.L, 43.75p) Prologis, Inc. (PLD.N, $47.01) Proofpoint (PFPT.OQ, $79.01) Prysmian (PRY.MI, €23.16) 21st Century Fox Inc. (FOXA.OQ, $27.16) PSP Swiss Property AG (PSPN.S, SFr86.65) PT Bekasi Fajar Industrial Estate Tbk (BEST.JK, Rp302) PT Indo Tambangraya Megah (ITMG.JK, Rp17,000) PT Indosat Tbk (ISAT.JK, Rp6,450) PT Kawasan Industri Jababeka Tbk (KIJA.JK, Rp296) PT Kino Indonesia (KINO.JK, Rp3,350) PT Sarana Menara Nusantara (TOWR.JK, Rp3,800) PT Surya Semesta Internusa Tbk (SSIA.JK, Rp570) PTT Exploration & Production (PTTEP.BK, Bt81.5) PTT Global Chemical (PTTGC.BK, Bt59.0) PTT Public Company Limited (PTT.BK, Bt341.0) Publicis Groupe SA (PUBP.PA, €59.68) Pulte (PHM.N, $18.69)

14 November 2016


Puma DE (PUMG.DE, €223.9) QUALCOMM Inc. (QCOM.OQ, $66.31) Qualys (QLYS.OQ, $35.3) Quanta Services (PWR.N, $31.36) Quest Diagnostics (DGX.N, $81.51) ROHM (6963.T, ¥6,090) ROYAL BANK OF SCOTLAND (RBS.L, 202.7p) RPC, Inc. (RES.N, $17.23) RPM International (RPM.N, $51.34) RTL Group (AUDKt.BR, €68.3) RWE (RWEG.DE, €12.68) Radian Group, Inc. (RDN.N, $14.25) Radiant Opto-Electronics (6176.TW, NT$57.5) Raging River Exploration (RRX.TO, C$10.3) Ralph Lauren (RL.N, $106.26) Randstad (RAND.AS, €48.39) Range Resources (RRC.N, $32.45) Raytheon Company (RTN.N, $147.71) Realtek Semiconductor (2379.TW, NT$105.0) Refresco Group (RFRG.AS, €13.58) Regal Entertainment Group (RGC.N, $22.12) Regency Centers (REG.N, $68.16) Reliance Steel & Aluminum Co. (RS.N, $78.03) Renault (RENA.PA, €72.7) Repsol (REP.MC, €12.49) Republic Services, Inc. (RSG.N, $52.9) Rexel (RXL.PA, €13.84) Rexnord Corporation (RXN.N, $20.07) Rio Tinto (RIO.AX, A$58.13) Rio Tinto (RIO.L, 3147.5p) Rite Aid (RAD.N, $7.04) Robert Walters (RWA.L, 335.0p) Roche (ROG.S, SFr237.2) Rockwell Automation (ROK.N, $130.75) Rolls-Royce (RR.L, 770.5p) Ros Agro (AGRODR.MM, Rbl812.0) Rotork (ROR.L, 210.0p) Rowan Companies (RDC.N, $14.47) Rudolph Technologies (RTEC.N, $18.2) SAF Holland (SFQN.DE, €13.12) SAP (SAPG.DE, €77.38) SATS Ltd (SATS.SI, S$4.74) SCA Property Group (SCP.AX, A$2.12) SCREEN (7735.T, ¥7,070) SEACOR Holdings (CKH.N, $52.56) SEB (SEBa.ST, Skr92.8) SES SA (SESFg.LU, €20.33) SFS Group (SFSN.S, SFr75.55) SIASUN Robot & Automation Co., Ltd (300024.SZ, Rmb23.61) SK Holdings (034730.KS, W230,500) SK Hynix Inc. (000660.KS, W41,000) SK Innovation (096770.KS, W161,500) SK Materials (036490.KQ, W165,000) SKF (SKFb.ST, Skr158.9) SL Green Realty Corp. (SLG.N, $101.77) SLM Solutions Group AG (AM3D.DE, €30.97) SM Investments Corp (SM.PS, P669.5) SMC (6273.T, ¥31,590) SMIC (0981.F, €0.14) SOHU.COM INC. (SOHU.OQ, $34.7) SOMPO Holdings (8630.T, ¥3,403) SPT Energy (1251.HK, HK$0.7) SSAB (SSABAH.HE, €3.204) STMicroelectron (STM.N, $9.06) STMicroelectron (STM.MI, €8.31) SUMCO (3436.T, ¥1,141) Sabmiller (SABJ.J, R792.0) Safran (SAF.PA, €63.81) Saipem (SPMI.MI, €0.4) Salim Ivomas Pratama (SIMP.JK, Rp498) Salvatore Ferragamo Spa (SFER.MI, €21.9) Samsung Elec (005935.KS, W1,294,000) Samsung Electro-Mechanics (009150.KS, W47,950) Samsung Electronics (005930.KS, W1,649,000) Samsung Fire & Marine (000810.KS, W294,000) Samsung Heavy Industries (010140.KS, W9,160) Samsung SDI (006400.KS, W93,700) Samsung SDS (018260.KS, W148,500) Sanan Optoelectronics Co. Ltd (600703.SS, Rmb12.2) Sandvik (SAND.ST, Skr108.9) Sanofi (SASY.PA, €76.98) Santen Pharmaceutical (4536.T, ¥1,487) Santos Ltd (STO.AX, A$3.58) Sanyo Chemical (4471.T, ¥4,645) SapuraKencana Petroleum Bhd (SKPE.KL, RM1.5) Saras (SRS.MI, €1.57) Sawai Pharmaceutical (4555.T, ¥6,400) Scentre Group (SCG.AX, A$4.17) Schaeffler (SHA_p.DE, €11.95) Schlumberger (SCL.L, $80.005) Schlumberger (SLB.N, $79.88) Schneider Electric (SCHN.PA, €64.05) Schoeller Bleckmann Oilfield Equipment (SBOE.VI, €68.87)

Scorpio Tankers Inc. (STNG.N, $4.09) Seadrill (SDRLNOK.ST, Nkr18.73) Seagate Tech (STX.OQ, $36.17) Sealed Air Corp. (SEE.N, $46.94) Sears Holdings Corp. (SHLD.OQ, $12.24) Sekisui Chemical (4204.T, ¥1,677) Sekisui House (1928.NG, ¥1,730) Seoul Semiconductor Co Ltd (046890.KQ, W13,650) ServiceNow (NOW.N, $82.14) Seven Generations Energy Ltd. (VII.TO, C$29.56) Shaftesbury (SHB.L, 913.0p) Shanghai Electric Group Company Limited (2727.HK, HK$3.55) Shanghai International Airport Co (600009.SS, Rmb26.43) Sharp (6753.T, ¥174) Shell (RDSa.AS, €23.5) Shell (RDSa.N, $51.15) Shenzhen O-film Tech Co., Ltd (002456.SZ, Rmb39.59) Shenzhou Intl (2313.BE, €5.805) Sherwin-Williams Company (SHW.N, $265.01) Shimizu (1803.NG, ¥935) Shin-Etsu Chem (4063.NG, ¥7,650) Shinko Electric Industries (6967.T, ¥668) Shinsegae Inc (004170.KS, W191,500) Shionogi (4507.T, ¥5,429) Shire Pharmaceuticals (SHP.L, 5083.0p) Showa Denko (4004.T, ¥1,527) Siam Commercial Bank (SCB.BK, Bt146.0) Siemens (SIEGn.DE, €109.3) Siliconware Precision (2325.TW, NT$46.9) Siltronic (WAFGn.DE, €33.9) Silver Spring Networks (SSNI.N, $13.89) Singapore Airlines Limited (SIAL.SI, S$9.97) Sinopec (0386.HK, HK$5.52) Sinopec Corp (0386.F, €0.639) Sinopec Engineering (2386.HK, HK$6.79) Sinopec Kantons (0934.HK, HK$3.54) Sinopec SSC (1033.BE, €0.165) Skyworks Solutns (SWKS.O, $75.91) Skyworth Digital (0751.HK, HK$5.2) Snam (SRG.MI, €3.56) Software AG (SOWG.DE, €32.46) Solvay (SOLB.BR, €101.8) Somboon Advance Technology (SAT.BK, Bt13.5) Sony (6758.T, ¥3,207) Sony Financial (8729.T, ¥1,457) Soulbrain (036830.KQ, W64,500) Southwest Airlines Co. (LUV.N, $43.64) Spar Group Ltd (SPPJ.J, R179.91) Spark Infrastructure Group (SKI.AX, A$2.1) Spectra Energy (SE.N, $41.03) Speedcast International (SDA.AX, A$3.31) Stanley Black & Decker, Inc. (SWK.N, $125.07) Stanley Electric (6923.T, ¥2,955) Staples (SPLS.OQ, $8.58) Starwood Hotels & Resorts Worldwide (HOT.N, $77.05) Statoil (STL.OL, Nkr139.7) Steel Dynamics, Inc. (STLD.OQ, $32.35) Stockland Group (SGP.AX, A$4.21) Stride Property (SPG.NZ, NZ$1.83) Stryker Corporation (SYK.N, $114.03) Subsea 7 S.A. (SUBC.OL, Nkr92.85) Sulzer (SUN.S, SFr96.2) Sumber Alfaria (AMRT.JK, Rp520) Sumitomo Chemical (4005.T, ¥476) Sumitomo Corp (8053.NG, ¥1,238) Sumitomo Dainippon Pharma (4506.T, ¥1,795) Sumitomo EI (5802.NG, ¥1,420) Sumitomo Heavy Industries (6302.T, ¥615) Sumitomo Metal Mining (5713.T, ¥1,480) Sumitomo Rubber Industries (5110.T, ¥1,752) Summit Midstream Partners, LP (SMLP.N, $22.3) Suncor Energy (SU.TO, C$40.09) Suning Commerce Group Co., Ltd. (002024.SZ, Rmb11.23) Sunny Optical (2382.F, €4.612) Superior Energy Services, Inc. (SPN.N, $15.3) Surya Citra Media (SCMA.JK, Rp2,490) Suzuken (9987.NG, ¥3,810) Suzuki Motor (7269.T, ¥4,018) Svenska Handelsbanken (SHBa.ST, Skr126.1) Swedbank (SWEDa.ST, Skr213.3) Sydney Airport (SYD.AX, A$6.04) Synchronoss Technologies, Inc. (SNCR.OQ, $47.01) Synchrony Financial (SYF.N, $31.61) Synopsys Inc. (SNPS.OQ, $58.63) TCL Communication Technology Holdings Limited (2618.HK, HK$7.47) TF1 (TFFP.PA, €8.99) TOTO (5332.NG, ¥4,160) TPK Holdings (3673.TW, NT$50.8) TPV Technology (0903.HK, HK$1.49)

TXC Corp. (3042.TW, NT$41.7) Tableau Software, Inc. (DATA.N, $47.32) Taisho Pharmaceutical Holdings (4581.T, ¥9,620) Taiwan Semiconductor Manufacturing (2330.TW, NT$185.5) Taiwan Surface Mounting Technology (6278.TW, NT$25.6) Takata Corp (7312.T, ¥390) Takeda Pharma (4502.NG, ¥4,340) Tallgrass Energy GP, LP (TEGP.N, $23.76) Tallgrass Energy Partners, L.P. (TEP.N, $45.47) Targa Resources Corp. (TRGP.N, $48.04) Target Corporation (TGT.N, $70.54) Tassal Group Limited (TGR.AX, A$3.74) Tata Motors (TAMO.NS, Rs533.7) Tate & Lyle (TATE.L, 684.0p) Taubman Centers, Inc. (TCO.N, $71.26) Tech Mahindra (TEML.NS, Rs442.25) Technip (TECF.PA, €64.08) Techtronic Industries (0669.HK, HK$28.5) Tecnicas Reunidas (TRE.MC, €33.75) Teekay Corporation (TK.N, $6.51) Teijin (3401.T, ¥1,984) Tekfen Holding (TKFEN.IS, TL7.14) Telecom Italia (TLIT.MI, €0.73) Telefonica (TDET.L, €8.57) Telia Company (TELIA1.HE, €3.478) Temenos Group (TEMN.S, SFr63.85) Tenaris (TENR.MI, €14.27) Tenet Healthcare Corporation (THC.N, $14.51) Teradyne Inc. (TER.N, $23.4) Terna (TRN.MI, €3.99) Tesco (TSCO.L, 199.5p) Tesoro Corp. (TSO.N, $84.61) Tetra Technologies, Inc. (TTI.N, $5.18) Teva Pharmaceutical Industries Ltd. (TEVA.N, $40.06) Texas Instruments Inc. (TXN.OQ, $69.14) Textron (TXT.N, $44.08) Texwinca Holdings (0321.HK, HK$5.43) Thai Oil (TOP.BK, Bt75.0) Thai Stanley Electric (STANLY.BK, Bt173.5) Thales (TCFP.PA, €91.63) The Coca-Cola Company (KO.N, $40.94) The Gap, Inc. (GPS.N, $28.58) The Kraft Heinz Company (KHC.OQ, $81.42) The Priceline Group Inc (PCLN.OQ, $1554.32) The TJX Companies, Inc. (TJX.N, $75.39) The Walt Disney Company (DIS.N, $94.96) Thyssen Krupp AG (TKAG.DE, €21.34) Tidewater (TDW.N, $1.75) Tiger Brands Ltd (TBSJ.J, R378.0) Time Warner Inc. (TWX.N, $86.33) Tofas (TOASO.IS, TL22.18) Toho Holdings (8129.T, ¥1,965) Tokai Carbon (5301.T, ¥358) Tokai Rika (6995.NG, ¥2,102) Tokuyama (4043.T, ¥446) Tokyo Electric Power (9501.T, ¥407) Tokyo Electron (8035.T, ¥9,787) Tokyo Gas (Unlisted) Tongda Group Holdings Ltd (0698.HK, HK$2.19) Topoint Technology Co Ltd (8021.TW, NT$19.4) Topre (5975.T, ¥2,448) Toray Industries (3402.T, ¥894) Toshiba (6502.NG, ¥380) Tosoh (4042.T, ¥726) Total System Services, Inc. (TSS.N, $49.83) Tourmaline Oil Corp (TOU.TO, C$34.59) Tower Bersama (TBIG.JK, Rp5,750) Toyoda Gosei (7282.NG, ¥2,190) Toyota (7203.NG, ¥5,830) Toyota Boshoku (3116.NG, ¥2,322) Toyota Inds (6201.NG, ¥4,820) Toyota Tsusho (8015.NG, ¥2,210) TransAlta Corporation (TA.TO, C$5.46) TransCanada Corp. (TRP.TO, C$60.2) Transocn (RIGN.S, SFr10.28) Trilogy Energy Corp (TET.TO, C$6.15) TripAdvisor, Inc. (TRIP.OQ, $51.83) True Corp PCL (TRUE.BK, Bt7.6) Truly International (0732.HK, HK$3.25) Tsubakimoto Chain (6371.T, ¥828) Tsumura & Co (4540.T, ¥3,205) Tupras (TUPRS.IS, TL64.55) Tyson Foods (TSN.N, $66.24) U.S. Silica (SLCA.N, $46.45) UCB (UCB.BR, €63.89) USG Corporation (USG.N, $26.8) USISH (601231.SS, Rmb11.76) Ube Industries (4208.T, ¥216) Umicore (UMI.BR, €54.94) Under Armour, Inc. (UA.N, $31.57) Unibail-Rodamco (UNBP.AS, €206.05) Unilever (UNc.AS, €36.59) Unilever Indonesia (UNVR.JK, Rp43,700) Union Pacific (UNP.N, $97.49)

14 November 2016


Unipres (5949.T, ¥1,871) United Microelectronics (2303.TW, NT$11.6) United Parcel Service Inc. (UPS.N, $113.31) United States Steel Corp. (X.N, $24.66) United Technologies Corp (UTX.N, $108.41) UnitedHealth Group Incorporated (UNH.N, $146.13) Universal Health Services, Inc. (UHS.N, $121.0) VAT (VACN.S, SFr79.7) VF Corporation (VFC.N, $56.33) VINCI (SGEF.PA, €61.23) VMware Inc. (VMW.N, $76.82) Vale SA (VALED3.PA, €7.37) Valeant Pharm In (VRX.TO, C$22.7) Valeo (VLOF.PA, €49.075) Valero Energy Corporation (VLO.N, $62.96) Valero Energy Partners, LP (VLP.N, $39.95) Vallourec (VLLP.PA, €4.75) Valspar (VAL.N, $102.48) Vanguard International Semiconductor (5347.TWO, NT$60.2) Vantiv Inc (VNTV.K, $57.4) Venture Corporation (VENM.SI, S$9.71) VeriSign Inc. (VRSN.OQ, $81.05) Verizon (VZC.L, $54.05) Vermilion Energy (VET.N, $39.53) Vesta, S.AB. De C.V (VESTA.MX, MXN24.97) Vestas (VWS.CO, Dkr426.1) Viacom Inc. (VIAB.OQ, $38.01) Victrex (VCTX.L, 1730.0p) Visa Inc. (V.N, $81.87) Visual Photonics Epitaxy Co., Ltd (2455.TW, NT$42.95) Vocus Communications (VOC.AX, A$5.6)

Vodafone Group (VOD.L, 207.9p) Voestalpine (VOES.VI, €35.41) Volkswagen (VOWG_p.DE, €114.75) Volkswagen (VOWG.DE, €126.9) Volvo (VOLVa.ST, Skr98.05) Vopak (VOPA.AS, €42.65) WCI Communities (WCIC.N, $23.0) WEG (WEGE3.SA, R$16.5) WPG Holdings Ltd (3702.TW, NT$38.25) WPP (WPP.L, 1653.0p) Wabco India Ltd. (WABC.BO, Rs5368.0) Wacker Chemie (WCHG.DE, €80.71) Wacom (6727.T, ¥265) Wal-Mart Stores, Inc. (WMT.N, $71.39) Walgreens Boots Alliance (WBA.OQ, $80.87) Wangsu Science & Technology Co. Ltd (300017.SZ, Rmb59.66) Wanhua Chemical (600309.SS, Rmb20.86) Waste Connections (WCN.N, $75.87) Waste Management, Inc. (WM.N, $66.54) Weatherford (0WE.BE, €4.172) Weatherford International, Inc. (WFT.N, $5.07) Weichai Power (2338.F, €1.581) WellCare Health Plans, Inc. (WCG.N, $119.83) Wells Fargo & Company (WFC.N, $51.63) Werner Enterprises, Inc. (WERN.OQ, $25.9) Wesfarmers (WES.AX, A$41.17) Western Digital Corp. (WDC.OQ, $56.84) Western Gas Equity Partners, L.P. (WGP.N, $42.87) Western Gas Partners, LP (WES.N, $56.37) Western Refining Inc. (WNR.N, $27.98) Western Refining Logistics, LP (WNRL.N, $21.05) Westfield Corporation (WFD.AX, A$8.49)

Westlake Chem (WLK.N, $54.25) Whirlpool (WHR.N, $165.0) Whitecap Resources (WCP.TO, C$10.92) Willbros Group Inc. (WG.N, $2.07) Williams Companies, Inc (WMB.N, $30.64) Winbond (2344.TW, NT$9.84) Wirecard (WDIG.DE, €41.69) Wisconsin Energy Corporation (WEC.N, $55.45) Wm Morrison (MRW.L, 211.0p) Wolverine World (WWW.N, $22.7) Wonik Materials (104830.KQ, W70,100) Wood Group (WG.L, 785.0p) Woodside Petroleum (WPL.AX, A$28.72) Woolworths (WOW.AX, A$23.19) World Fuel Svc (INT.N, $41.91) Worldline (WLN.PA, €24.76) Worldpay (WPG.L, 275.2p) WorleyParsons (WOR.AX, A$8.68) Worthington Industries, Inc. (WOR.N, $52.26) XL Axiata Tbk (EXCL.JK, Rp2,580) YRC Worldwide, Inc. (YRCW.OQ, $10.67) Yamaha Motor (7272.T, ¥2,428) Yamato Kogyo (5444.T, ¥3,205) Yantai Jereh (002353.SZ, Rmb17.98) Yaskawa Electric Corp (6506.T, ¥1,716) Yitai Coal (YT8.F, €0.829) Yokogawa Electric Corp (6841.T, ¥1,572) Ypsomed (YPSN.S, SFr180.6) Yue Yuen Industrial Holdings Ltd (0551.HK, HK$29.0) ZTE (0763.F, €1.303) Zeon (4205.T, ¥953) Zimmer Biomet Holdings (ZBH.N, $100.68) Zodiac Aerospace (ZODC.PA, €22.02)

14 November 2016


Disclosure Appendix

Analyst Certification The analysts identified in this report each certify, with respect to the companies or securities that the individual analyzes, that (1) the views expressed in this report accurately reflect his or her personal views about all of the subject companies and securities and (2) no part of his or her compensation was, is or will be directly or indirectly related to the specific recommendations or views expressed in this report. The analyst(s) responsible for preparing this research report received Compensation that is based upon various factors including Credit Suisse's total revenues, a portion of which are generated by Credit Suisse's investment banking activities

As of December 10, 2012 Analysts’ stock rating are defined as follows: Outperform (O) : The stock’s total return is expected to outperform the relevant benchmark* over the next 12 months. Neutral (N) : The stock’s total return is expected to be in line with the relevant benchmark* over the next 12 months. Underperform (U) : The stock’s total return is expected to underperform the relevant benchmark* over the next 12 months. *Relevant benchmark by region: As of 10th December 2012, Japanese ratings are based on a stock’s total return relative to the analyst's coverage uni verse which consists of all companies covered by the analyst within the relevant sector, with Outperforms representing the most att ractive, Neutrals the less attractive, and Underperforms the least attractive investment opportunities. As of 2nd October 2012, U.S. and Canadian as well as European ra tings are based on a stock’s total return relative to the analyst's coverage universe which consists of all companies covered by the analyst within the relevant sector, with Outperforms representing the most attractive, Neutrals the less attractive, and Underperforms the least attractive investment opportunities. For Latin Ame rican and non-Japan Asia stocks, ratings are based on a stock’s total return relative to the average total return of the relevant country or regional benchmark; prior to 2nd October 2012 U.S. and Canadian ratings were based on (1) a stock’s absolute total return potential to its current share price and (2) the relative attractiveness of a stock’s total return potential within an analyst’s coverage universe. For Australian and New Zealand stocks, the expected total return (ETR) calculation includes 1 2-month rolling dividend yield. An Outperform rating is assigned where an ETR is greater than or equal to 7.5%; Underperform where an ETR less than or equal to 5%. A Neutral may be assigned where the ETR is between -5% and 15%. The overlapping rating range allows analysts to assign a rating that puts ETR in the context of associated risks. Prior to 18 May 2015, ETR ranges for Outperform and Underperform ratings did not overlap with Neutral thresholds between 15% and 7.5%, wh ich was in operation from 7 July 2011. Restricted (R) : In certain circumstances, Credit Suisse policy and/or applicable law and regulations preclude certain types of communications, including an investment recommendation, during the course of Credit Suisse's engagement in an investment banking transaction and in certain other circumstances. Not Rated (NR) : Credit Suisse Equity Research does not have an investment rating or view on the stock or any other securities related to the company at this time. Not Covered (NC) : Credit Suisse Equity Research does not provide ongoing coverage of the company or offer an investment rating or investment view on the equity security of the company or related products.

Volatility Indicator [V] : A stock is defined as volatile if the stock price has moved up or down by 20% or more in a month in at least 8 of the past 24 months or the analyst expects significant volatility going forward.

Analysts’ sector weightings are distinct from analysts’ stock ratings and are based on the analyst’s expectations for the fundamentals and/or valuation of the sector* relative to the group’s historic fundamentals and/or valuation: Overweight : The analyst’s expectation for the sector’s fundamentals and/or valuation is favorable over the next 12 months. Market Weight : The analyst’s expectation for the sector’s fundamentals and/or valuation is neutral over the next 12 months. Underweight : The analyst’s expectation for the sector’s fundamentals and/or valuation is cautious over the next 12 months. *An analyst’s coverage sector consists of all companies covered by the analyst within the relevant sector. An analyst may cover multiple sectors.

Credit Suisse's distribution of stock ratings (and banking clients) is:

Global Ratings Distribution

Rating Versus universe (%) Of which banking clients (%) Outperform/Buy* 44% (63% banking clients) Neutral/Hold* 39% (60% banking clients) Underperform/Sell* 15% (56% banking clients) Restricted 3% *For purposes of the NYSE and NASD ratings distribution disclosure requirements, our stock ratings of Outperform, Neutral, and Underperform most closely correspond to Buy, Hold, and Sell, respectively; however, the meanings are not the same, as our stock ratings are determined on a relative basis. (Please refer to definitions above.) An investor's decision to buy or sell a security should be based on investment objectives, current holdings, and other individual factors.

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14 November 2016


The subject company (ASSAb.ST, DAST.PA, CSNA3.SA, DVN.N, CXO.N, FLR.N, AENA.MC, ABI.BR, DKS.N, ENF.TO, A3M.MC, DOW.N, BERY.N, DOV.N, ENEI.MI, ENBL.N, DHR.N, ASML.AS, CYH.N, ADP.PA, ADI.OQ, 097950.KS, CPI.L, BBRY.OQ, EXPE.OQ, ENI.MI, 047040.KS, FI.N, CMCSA.OQ, CSCO.OQ, ABEV3.SA, EMR.N, AGU.N, CCC.L, CARLb.CO, FHZN.S, CR.TO, FTI.N, FANG.OQ, ATCOa.ST, ALRM.OQ, CMC.N, DF.N, AIG.N, BXB.AX, AAL.OQ, CTSH.OQ, ELM.L, BV.OQ, BBY.N, DO.N, DAL.N, DISCA.OQ, ALFAA.MX, DUK.N, CVX.N, BAES.L, ALLY.N, AON.N, AL.N, AGGK.L, BOY.L, G1AG.DE, DANSKE.CO, BUAB.KL, DLX.AX, DNB.OL, ERJ.N, 2357.TW, APA.N, ETL.PA, AMKR.OQ, APC.N, DIFu.BK, ALSN.N, FIS.N, CAH.N, CARR.PA, CSTM.N, GLOP.N, CCL.AX, 2311.TW, GOOGL.OQ, EOG.N, CLF.N, EA.OQ, FREG.DE, ATOS.PA, ACN.N, AMZN.OQ, CAT.N, CBI.N, CRZO.OQ, AKZO.AS, BLL.N, 8150.TW, AIRF.PA, CDNS.OQ, GTO.AS, FSLR.OQ, BETR.N, DC.L, 0883.HK, FUNO11.MX, ATCA.AS, BRBY.L, CHTR.OQ, AXTA.N, KMX.N, MMM.N, DLNG.N, COP.N, APFH.N, BG.N, BVI.PA, FDC.N, BEC.BK, AMAT.OQ, CAR.OQ, AER.N, CNX.N, CHK.N, ESL.N, AAPL.OQ, F.N, ABF.L, ABC.N, ASII.JK, CRL.N, DOKA.S, AET.N, AEP.N, 8267.T, ETN.N, 8069.TWO, ENLK.N, DD.N, ELE.MC, ETR.N, BT.L, FET.N, 4519.T, BMY.N, DPS.N, DPWGn.DE, COH.N, BZUN.OQ, CI.N, ATW.N, CQP.A, DE.N, 5264.TW, EZJ.L, MT.N, CNA.L, CNK.N, CLNX.MC, CMRE.N, AZJ.AX, ENB.TO, ALFA.ST, GE.N, EEP.N, XOM.N, D.N, GD.N, BEIG.DE, EXO.L, CF.N, ALSO.PA, BHI.N, ENAV.MI, EVDY.N, 2353.TW, 1114.HK, EQN.L, AMD.OQ, ATVI.OQ, DANO.PA, 0861.HK, DISH.OQ, DUE.AX, EBAY.OQ, 1590.TW, GATE.S, 2448.TW, ESRX.OQ, FIBRAPL14.MX, LHAG.DE, AKSOL.OL, AKS.N, ERII.OQ, BWP.N, BNP.TO, AVMD.PA, CPB.N, LMT.N, 000333.SZ, 001450.KS, 1169.HK, LEGD.PA, 5486.T, HAL.N, MA.N, NFLX.OQ, LSIP.JK, GLF.N, NXT.AX, 3658.TWO, HPQ.N, MPSX.N, NVA.TO, INDF.JK, MCK.N, GPOR.OQ, HCLP.N, MGGT.L, LNTH.OQ, K.N, NXPI.OQ, 012330.KS, MRL.MC, METSO.HE, HTG.L, KEL.TO, MDSO.OQ, ITRK.L, OMAB.MX, GLPL.SI, OSH.AX, 000720.KS, PRY.MI, HBI.N, OMI.N, GXIG.DE, PSX.N, PFD.L, PPL.TO, HLMA.L, 6305.T, MOH.N, LOIM.PA, MONY.L, MNST.OQ, HON.N, JD.OQ, 7267.T, MON.N, PSXP.N, 6674.T, HUM.N, HD.N, LUN.CO, PEP.N, 3481.TW, OERL.S, JEC.N, IFAR.SI, OXY.N, 8464.TW, KBR.N, IENOVA.MX, PBR.N, PFC.L, IMAX.N, LUX.MI, ORG.AX, HEIN.AS, HIAG.S, KMI.N, NFX.N, GEI.TO, LLOY.L, POU.TO, ORI.AX, MOS.N, 4114.T, MRCG.DE, KSS.N, PNR.N, PXD.N, MRFG3.SA, HCA.N, PX.N, KEX.N, NEE.N, MTG.N, NVDA.OQ, MPPA.JK, NS.N, NOKIA.HE, DSMN.AS, INTC.OQ, NG.L, ICBP.JK, IVL.BK, GAPB.MX, 066570.KS, ISA.L, 4217.T, KLAC.OQ, ITRI.OQ, 6701.T, PDCE.OQ, LXSG.DE, MGR.AX, FIN.S, OUT1V.HE, 0857.HK, MRVL.OQ, OA.N, 051900.KS, NBL.N, HLX.N, MEXCHEM.MX, 2317.TW, GS.N, KALU.OQ, NOC.N, KUD.S, 005380.KS, HUO.AX, NUE.N, M.N, KEY.TO, LPNT.OQ, 6756.T, MKS.L, LH.N, OMC.N, ORAN.PA, PPG.N, NDA1V.HE, INGR.N, HMSO.L, HMSP.JK, IFXGn.DE, MCD.N, NSC.N, BTU.N, JBLU.OQ, ILU.AX, NLSN.N, MRO.N, MS.MI, ITV.L, MU.OQ, GPSC.BK, MNCN.JK, IMI.L, GM.N, 000270.KS, NR.N, 018880.KS, PVH.N, OREP.PA, NBR.N, KSU.N, ORIG.OQ, ASURB.MX, PGAS.JK, NOVOb.CO, GIS.N, IDR.MC, MDA.TO, 3034.TW, PHG.AS, OIS.N, 2408.TW, PYPL.OQ, 4151.T, PRTP.PA, 034220.KS, SU.TO, WLN.PA, SPN.N, EXCL.JK, PUBP.PA, WFD.AX, RTN.N, ITMG.JK, SNCR.OQ, 002024.SZ, RIO.AX, WCN.N, SBOE.VI, TGT.N, RGC.N, DGX.N, WPG.L, SKI.AX, PTT.BK, 2455.TW, WERN.OQ, 004170.KS, TRN.MI, RS.N, 6753.T, DIS.N, SGEF.PA, SCMA.JK, 2303.TW, SMLP.N, 005930.KS, ISAT.JK, SUBC.OL, VLO.N, RTEC.N, 018260.KS, ZODC.PA, VOC.AX, SCP.AX, 034730.KS, UHS.N, WNRL.N, SOHU.OQ, TRUE.BK, WES.N, SDA.AX, TECF.PA, UNc.AS, SCB.BK, TEGP.N, PCLN.OQ, TENR.MI, 0551.HK, TSS.N, TUPRS.IS, VOD.L, UNBP.AS, PTTGC.BK, STLD.OQ, 2330.TW, KINO.JK, RFRG.AS, WES.AX, 4506.T, SFSN.S, VOES.VI, WPP.L, SHBa.ST, WMB.N, SSNI.N, 0386.HK, SRS.MI, TJX.N, 009150.KS, 3673.TW, WOW.AX, SWEDa.ST, RSG.N, RRX.TO, WCHG.DE, UMI.BR, WAFGn.DE, TRIP.OQ, WFC.N, UNH.N, VIAB.OQ, UTX.N, SOLB.BR, UCB.BR, RDC.N, 2386.HK, SEE.N, WNR.N, TA.TO, TWX.N, TCFP.PA, TOP.BK, WGP.N, RXN.N, REP.MC, STL.OL, 036490.KQ, SAND.ST, 2727.HK, UNP.N, WDIG.DE, SASY.PA, TDW.N, KHC.OQ, SCHN.PA, SEBa.ST, TRGP.N, SATS.SI, TATE.L, RRC.N, WDC.OQ, YPSN.S, SAF.PA, SIEGn.DE, TOWR.JK, 006400.KS, SPMI.MI, TFFP.PA, KO.N, RBS.L, SLCA.N, TEVA.N, WOR.N, PWR.N, 6758.T, WG.N, ROG.S, TEP.N, SUN.S, WG.L, 2325.TW, UNVR.JK, SCG.AX, QCOM.OQ, SYF.N, TSO.N, VLP.N, TSN.N, TTI.N, TLIT.MI, FOXA.OQ, SHP.L, SLB.N, STNG.N, WPL.AX, RR.L, KIJA.JK, TOU.TO, SIAL.SI, TRE.MC, RIO.L, 046890.KQ, VFC.N, SKFb.ST, X.N, SOWG.DE, WCG.N, SPLS.OQ, VII.TO, 000660.KS, PSPN.S, THC.N, TEMN.S, WBA.OQ, 000810.KS, WM.N, WMT.N, 4005.T, VACN.S, SKPE.KL, INT.N, 8729.T, CKH.N, PTTEP.BK, 4555.T, TRP.TO) currently is, or was during the 12-month period preceding the date of distribution of this report, a client of Credit Suisse. Credit Suisse provided investment banking services to the subject company (DVN.N, CXO.N, AENA.MC, ABI.BR, ENF.TO, BERY.N, DOV.N, ENEI.MI, ENBL.N, DHR.N, ASML.AS, CYH.N, ADI.OQ, BBRY.OQ, EXPE.OQ, ENI.MI, CMCSA.OQ, CSCO.OQ, ABEV3.SA, FANG.OQ, AIG.N, AAL.OQ, CTSH.OQ, BBY.N, DO.N, DAL.N, DISCA.OQ, DUK.N, ALLY.N, AON.N, AL.N, DANSKE.CO, DNB.OL, APC.N, DIFu.BK, ALSN.N, FIS.N, CARR.PA, 2311.TW, GOOGL.OQ, CLF.N, ACN.N, CRZO.OQ, BLL.N, 8150.TW, CDNS.OQ, BETR.N, 0883.HK, FUNO11.MX, ATCA.AS, CHTR.OQ, AXTA.N, MMM.N, DLNG.N, COP.N, APFH.N, BG.N, BVI.PA, FDC.N, AMAT.OQ, CAR.OQ, AER.N, CNX.N, CHK.N, AAPL.OQ, F.N, ABF.L, AET.N, AEP.N, ETN.N, ENLK.N, DD.N, ELE.MC, 4519.T, BMY.N, DPS.N, BZUN.OQ, ATW.N, CQP.A, DE.N, MT.N, AZJ.AX, ENB.TO, GE.N, EEP.N, XOM.N, D.N, GD.N, BEIG.DE, EXO.L, ENAV.MI, 1114.HK, EQN.L, AMD.OQ, ATVI.OQ, 0861.HK, EBAY.OQ, GATE.S, ESRX.OQ, AKS.N, CPB.N, LMT.N, 001450.KS, HAL.N, LSIP.JK, 3658.TWO, HPQ.N, MPSX.N, NVA.TO, INDF.JK, GPOR.OQ, HCLP.N, LNTH.OQ, K.N, NXPI.OQ, 012330.KS, MRL.MC, KEL.TO, OMAB.MX, PSX.N, PFD.L, PPL.TO, MONY.L, MON.N, PSXP.N, HD.N, 3481.TW, IFAR.SI, OXY.N, 8464.TW, IENOVA.MX, ORG.AX, HEIN.AS, HIAG.S, KMI.N, NFX.N, LLOY.L, MOS.N, PXD.N, HCA.N, PX.N, NEE.N, MPPA.JK, DSMN.AS, INTC.OQ, NG.L, ICBP.JK, GAPB.MX, 066570.KS, ISA.L, PDCE.OQ, FIN.S, MRVL.OQ, 051900.KS, 2317.TW, GS.N, NOC.N, KUD.S, 005380.KS, M.N, KEY.TO, PPG.N, NDA1V.HE, HMSP.JK, MCD.N, MS.MI, ITV.L, MU.OQ, GM.N, 000270.KS, KSU.N, ORIG.OQ, ASURB.MX, PGAS.JK, GIS.N, PYPL.OQ, 034220.KS, SPN.N, EXCL.JK, WFD.AX, RTN.N, ITMG.JK, SNCR.OQ, RIO.AX, WCN.N, RGC.N, WPG.L, TRN.MI, DIS.N, SMLP.N, 005930.KS, VLO.N, VOC.AX, 034730.KS, SOHU.OQ, TRUE.BK, WES.N, SDA.AX, UNc.AS, TENR.MI, TSS.N, UNBP.AS, KINO.JK, RFRG.AS, SHBa.ST, WMB.N, 009150.KS, SWEDa.ST, WCHG.DE, WAFGn.DE, TRIP.OQ, WFC.N, UNH.N, UTX.N, SOLB.BR, TWX.N, WGP.N, RXN.N, STL.OL, 036490.KQ, 2727.HK, UNP.N, KHC.OQ, SEBa.ST, TRGP.N, SATS.SI, TATE.L, RRC.N, WDC.OQ, SAF.PA, TOWR.JK, 006400.KS, SPMI.MI, KO.N, RBS.L, TEVA.N, WOR.N, ROG.S, TEP.N, SUN.S, 2325.TW, UNVR.JK, QCOM.OQ, SYF.N, TSO.N, VLP.N, TLIT.MI, FOXA.OQ, SHP.L, SLB.N, WPL.AX, RR.L, TOU.TO, SIAL.SI, RIO.L, VFC.N, X.N, VII.TO, PSPN.S, 000810.KS, WMT.N, VACN.S, TRP.TO) within the past 12 months. Credit Suisse provided non-investment banking services to the subject company (DANSKE.CO, CARR.PA, FDC.N, ABC.N, AET.N, DPS.N, GE.N, XOM.N, EQN.L, ESRX.OQ, LMT.N, HPQ.N, HON.N, HUM.N, ORG.AX, NFX.N, LLOY.L, HCA.N, INTC.OQ, GS.N, PPG.N, NSC.N, GM.N, SCP.AX, UNBP.AS, SHBa.ST, SWEDa.ST, RSG.N, WFC.N, UNH.N, SEBa.ST, SIEGn.DE, KO.N, RBS.L, TEVA.N, X.N, WM.N, CKH.N) within the past 12 months. Credit Suisse has managed or co-managed a public offering of securities for the subject company (DVN.N, CXO.N, ABI.BR, BERY.N, CYH.N, ADI.OQ, CMCSA.OQ, CSCO.OQ, ABEV3.SA, FANG.OQ, AAL.OQ, DO.N, DISCA.OQ, DUK.N, AL.N, DANSKE.CO, DNB.OL, APC.N, GOOGL.OQ, CLF.N, BETR.N, FUNO11.MX, ATCA.AS, CHTR.OQ, MMM.N, COP.N, APFH.N, BVI.PA, FDC.N, AER.N, F.N, AET.N, AEP.N, DPS.N, CQP.A, DE.N, ENB.TO, GE.N, XOM.N, D.N, EXO.L, ENAV.MI, EQN.L, AMD.OQ, EBAY.OQ, ESRX.OQ, AKS.N, MPSX.N, NVA.TO, GPOR.OQ, HCLP.N,

14 November 2016


LNTH.OQ, MRL.MC, PSX.N, PPL.TO, MONY.L, PSXP.N, HD.N, 8464.TW, IENOVA.MX, HIAG.S, NFX.N, PXD.N, HCA.N, PX.N, NEE.N, GAPB.MX, ISA.L, PDCE.OQ, FIN.S, GS.N, KUD.S, M.N, KEY.TO, NDA1V.HE, HMSP.JK, MCD.N, MU.OQ, GM.N, ASURB.MX, GIS.N, ITMG.JK, DIS.N, VLO.N, VOC.AX, WES.N, SDA.AX, KINO.JK, RFRG.AS, SHBa.ST, SWEDa.ST, WFC.N, UNH.N, SOLB.BR, TWX.N, WGP.N, RXN.N, 2727.HK, UNP.N, KHC.OQ, SEBa.ST, TRGP.N, SATS.SI, WDC.OQ, KO.N, RBS.L, TEVA.N, TEP.N, SUN.S, VLP.N, TLIT.MI, SHP.L, WPL.AX, SIAL.SI, VFC.N, X.N, VII.TO, VACN.S, TRP.TO) within the past 12 months. Credit Suisse has received investment banking related compensation from the subject company (DVN.N, CXO.N, AENA.MC, ABI.BR, ENF.TO, BERY.N, DOV.N, ENEI.MI, ENBL.N, DHR.N, ASML.AS, CYH.N, ADI.OQ, BBRY.OQ, EXPE.OQ, ENI.MI, CMCSA.OQ, CSCO.OQ, ABEV3.SA, FANG.OQ, AIG.N, AAL.OQ, CTSH.OQ, BBY.N, DO.N, DAL.N, DISCA.OQ, DUK.N, ALLY.N, AON.N, AL.N, DANSKE.CO, DNB.OL, APC.N, DIFu.BK, ALSN.N, FIS.N, CARR.PA, 2311.TW, GOOGL.OQ, CLF.N, ACN.N, CRZO.OQ, BLL.N, 8150.TW, CDNS.OQ, BETR.N, 0883.HK, FUNO11.MX, ATCA.AS, CHTR.OQ, AXTA.N, MMM.N, DLNG.N, COP.N, APFH.N, BG.N, BVI.PA, FDC.N, AMAT.OQ, CAR.OQ, AER.N, CNX.N, CHK.N, AAPL.OQ, F.N, ABF.L, AET.N, AEP.N, ETN.N, ENLK.N, DD.N, ELE.MC, 4519.T, BMY.N, DPS.N, BZUN.OQ, ATW.N, CQP.A, DE.N, MT.N, AZJ.AX, ENB.TO, GE.N, EEP.N, XOM.N, D.N, GD.N, BEIG.DE, EXO.L, ENAV.MI, 1114.HK, EQN.L, AMD.OQ, ATVI.OQ, 0861.HK, EBAY.OQ, GATE.S, ESRX.OQ, AKS.N, CPB.N, LMT.N, 001450.KS, HAL.N, LSIP.JK, 3658.TWO, HPQ.N, MPSX.N, NVA.TO, INDF.JK, GPOR.OQ, HCLP.N, LNTH.OQ, K.N, NXPI.OQ, 012330.KS, MRL.MC, KEL.TO, OMAB.MX, PSX.N, PFD.L, PPL.TO, MONY.L, MON.N, PSXP.N, HD.N, 3481.TW, IFAR.SI, OXY.N, 8464.TW, IENOVA.MX, ORG.AX, HEIN.AS, HIAG.S, KMI.N, NFX.N, LLOY.L, MOS.N, PXD.N, HCA.N, PX.N, NEE.N, MPPA.JK, DSMN.AS, INTC.OQ, NG.L, ICBP.JK, GAPB.MX, 066570.KS, ISA.L, PDCE.OQ, FIN.S, MRVL.OQ, 051900.KS, 2317.TW, GS.N, NOC.N, KUD.S, 005380.KS, M.N, KEY.TO, PPG.N, NDA1V.HE, HMSP.JK, MCD.N, MS.MI, ITV.L, MU.OQ, GM.N, 000270.KS, KSU.N, ORIG.OQ, ASURB.MX, PGAS.JK, GIS.N, PYPL.OQ, 034220.KS, SPN.N, EXCL.JK, WFD.AX, RTN.N, ITMG.JK, SNCR.OQ, RIO.AX, WCN.N, RGC.N, WPG.L, TRN.MI, DIS.N, SMLP.N, 005930.KS, VLO.N, VOC.AX, 034730.KS, SOHU.OQ, TRUE.BK, WES.N, SDA.AX, UNc.AS, TENR.MI, TSS.N, UNBP.AS, KINO.JK, RFRG.AS, SHBa.ST, WMB.N, 009150.KS, SWEDa.ST, WCHG.DE, WAFGn.DE, TRIP.OQ, WFC.N, UNH.N, UTX.N, SOLB.BR, TWX.N, WGP.N, RXN.N, STL.OL, 036490.KQ, 2727.HK, UNP.N, KHC.OQ, SEBa.ST, TRGP.N, SATS.SI, TATE.L, RRC.N, WDC.OQ, SAF.PA, TOWR.JK, 006400.KS, SPMI.MI, KO.N, RBS.L, TEVA.N, WOR.N, ROG.S, TEP.N, SUN.S, 2325.TW, UNVR.JK, QCOM.OQ, SYF.N, TSO.N, VLP.N, TLIT.MI, FOXA.OQ, SHP.L, SLB.N, WPL.AX, RR.L, TOU.TO, SIAL.SI, RIO.L, VFC.N, X.N, VII.TO, PSPN.S, 000810.KS, WMT.N, VACN.S, TRP.TO) within the past 12 months. Credit Suisse expects to receive or intends to seek investment banking related compensation from the subject company (ASSAb.ST, 6462.TWO, DAST.PA, CSNA3.SA, DVN.N, CXO.N, FLR.N, AENA.MC, ABI.BR, DKS.N, ENF.TO, A3M.MC, DOW.N, BERY.N, DOV.N, ENEI.MI, ENBL.N, DHR.N, ASML.AS, DLGS.DE, CYH.N, ADP.PA, ADI.OQ, 097950.KS, CPI.L, 4061.T, BBRY.OQ, EXPE.OQ, ENI.MI, 047040.KS, FI.N, CMCSA.OQ, CSCO.OQ, ABEV3.SA, EMR.N, AGU.N, CCC.L, CARLb.CO, FHZN.S, CR.TO, FTI.N, FANG.OQ, ATCOa.ST, ALRM.OQ, CMC.N, DF.N, AIG.N, BXB.AX, AAL.OQ, CCK.N, CTSH.OQ, 3407.T, ELM.L, BV.OQ, BBY.N, DO.N, DAL.N, DISCA.OQ, ALFAA.MX, DUK.N, CVS.N, CVX.N, BAES.L, ALLY.N, CQR.AX, AON.N, 1301.TW, AL.N, AGGK.L, APLP.OQ, CHC.AX, BOY.L, G1AG.DE, COLM.OQ, DANSKE.CO, BUAB.KL, DLX.AX, DNB.OL, ERJ.N, 2357.TW, APA.N, ETL.PA, AMKR.OQ, APC.N, DIFu.BK, ALSN.N, FIS.N, CAH.N, CARR.PA, GLOP.N, CAG.N, CCL.AX, 2311.TW, GOOGL.OQ, EOG.N, CLF.N, FL.N, EA.OQ, FREG.DE, ATOS.PA, ACN.N, AMZN.OQ, CAT.N, CBI.N, CRZO.OQ, AKZO.AS, APD.N, BLL.N, 8150.TW, AIRF.PA, CDNS.OQ, GTO.AS, 2409.TW, FSLR.OQ, BETR.N, DC.L, 0883.HK, FUNO11.MX, ATCA.AS, BRBY.L, CHTR.OQ, AXTA.N, KMX.N, MMM.N, DLNG.N, COP.N, BIR.TO, APFH.N, BG.N, BVI.PA, FDC.N, BEC.BK, BWA.N, AMAT.OQ, 0522.HK, CAR.OQ, 5803.T, 4523.T, ANF.N, AER.N, CNX.N, CHK.N, ESL.N, CMI.N, AAPL.OQ, BPT.AX, 4503.T, F.N, ABF.L, ABC.N, ASII.JK, DCG.L, DOKA.S, COST.OQ, AET.N, AEP.N, 8267.T, ETN.N, ADM.N, 8069.TWO, ENLK.N, DD.N, ELE.MC, ETR.N, BT.L, AIRP.PA, FET.N, 4519.T, BMY.N, 2458.TW, DPS.N, DPWGn.DE, COH.N, BZUN.OQ, CI.N, ATW.N, CQP.A, DE.N, CLR.N, 5264.TW, EZJ.L, MT.N, CNA.L, CNK.N, 600875.SS, CLNX.MC, AGL.AX, CMRE.N, AZJ.AX, ENB.TO, ALFA.ST, GE.N, EEP.N, XOM.N, D.N, GD.N, BEIG.DE, EXO.L, CF.N, ALSO.PA, BHI.N, ENAV.MI, EVDY.N, 2353.TW, 1114.HK, EQN.L, AMD.OQ, ATVI.OQ, DANO.PA, 0861.HK, DISH.OQ, DUE.AX, EBAY.OQ, 1590.TW, GATE.S, 2448.TW, 7248.T, ESRX.OQ, FIBRAPL14.MX, LHAG.DE, AKSOL.OL, AKS.N, BWP.AX, ERII.OQ, BWP.N, EAm.BK, 4568.T, BNP.TO, AVMD.PA, BRKS.OQ, CNQ.TO, CPB.N, LMT.N, 000333.SZ, 001450.KS, 1169.HK, 4188.T, KR.N, NEXS.PA, LEGD.PA, 5486.T, HAL.N, MA.N, NFLX.OQ, LB.N, LSIP.JK, GLF.N, NXT.AX, 3658.TWO, KMT.N, HPQ.N, MPSX.N, NVA.TO, INDF.JK, MCK.N, 1303.TW, GPOR.OQ, 2454.TW, HCLP.N, KLBF.JK, MGGT.L, PGF.TO, 6239.TW, 7201.T, HYPE3.SA, 2301.TW, LNTH.OQ, K.N, NXPI.OQ, 012330.KS, 6594.T, PEY.TO, MRL.MC, 161390.KS, KTB.BK, METSO.HE, HTG.L, KEL.TO, 7261.T, MDSO.OQ, MDR.N, ITRK.L, OMAB.MX, OSH.AX, 000720.KS, PRY.MI, HBI.N, 7988.T, GXIG.DE, PSX.N, PFD.L, PPL.TO, HLMA.L, 6305.T, LOIM.PA, MONY.L, GWR.N, MNST.OQ, HON.N, 002350.KS, JD.OQ, 7267.T, 4183.T, MON.N, PSXP.N, OI.N, HUM.N, HD.N, LUN.CO, 7011.T, PEP.N, 3481.TW, LTS.TO^J16, OERL.S, JEC.N, IFAR.SI, OXY.N, 002008.SZ, 8464.TW, 4528.T, KBR.N, IENOVA.MX, PBR.N, PFC.L, IP.N, IMAX.N, 4185.T, LUX.MI, ORG.AX, HEIN.AS, MYPK3.SA, PCG.N, HIAG.S, KMI.N, NFX.N, GEI.TO, 4578.T, LLOY.L, POU.TO, HOS.N, ORI.AX, MOS.N, HBC.TO, 4114.T, MRCG.DE, IPG.N, 3405.T, KSS.N, PNR.N, PXD.N, MRFG3.SA, HCA.N, IAG.AX, KNX.N, 6268.T, PX.N, JWN.N, KEX.N, NEE.N, 0008.HK, PTEN.OQ, MTG.N, NVDA.OQ, JCP.N, MPPA.JK, NS.N, NOKIA.HE, PH.N, 6471.T, DSMN.AS, INTC.OQ, NG.L, ICBP.JK, IVL.BK, GAPB.MX, 066570.KS, 4508.T, ISA.L, 4217.T, KLAC.OQ, GMG.AX, ITRI.OQ, 6701.T, PDCE.OQ, LXSG.DE, MGR.AX, FIN.S, 7211.T, OUT1V.HE, 073240.KS, 0857.HK, LOW.N, MRVL.OQ, 6807.T, OA.N, 051900.KS, NBL.N, HLX.N, MEXCHEM.MX, 2317.TW, MUR.N, 5706.T, GS.N, 6472.T, SBRY.L, KALU.OQ, NOC.N, KUD.S, 005380.KS, HUO.AX, NUE.N, M.N, KEY.TO, LPNT.OQ, 6756.T, MKS.L, LH.N, OMC.N, ORAN.PA, PPG.N, NDA1V.HE, GPT.AX, INGR.N, HMSO.L, HMSP.JK, IFXGn.DE, MCD.N, BTU.N, JBLU.OQ, ILU.AX, NLSN.N, MRO.N, MS.MI, ITV.L, 6971.T, LRCX.OQ, JNJ.N, MU.OQ, GPSC.BK, MNCN.JK, IMI.L, GM.N, 000270.KS, NR.N, 1605.T, GEL.N, 018880.KS, PVH.N, OREP.PA, NBR.N, KSU.N, ORIG.OQ, ASURB.MX, PGAS.JK, NOVOb.CO, HP.N, GIS.N, IDR.MC, MDA.TO, GGRM.JK, 3034.TW, PHG.AS, OIS.N, JBHT.OQ, 2408.TW, PYPL.OQ, 4151.T, 4966.TWO, PRTP.PA, 034220.KS, SU.TO, WLN.PA, SPN.N, EXCL.JK, PUBP.PA, 600703.SS, WFD.AX, RTN.N, ITMG.JK, SNCR.OQ, 002024.SZ, RIO.AX, WCN.N, SBOE.VI, TGT.N, TSCO.L, RGC.N, DGX.N, WPG.L, SKI.AX, PTT.BK, 4540.T, 2455.TW, WERN.OQ, 004170.KS, SHW.N, 5713.T, TRN.MI, RS.N, 6753.T, 6302.T, DIS.N, SGP.AX, SGEF.PA, SCMA.JK, 2303.TW, SMLP.N, 005930.KS, ISAT.JK, VLO.N, RTEC.N, LUV.N, 018260.KS, ZODC.PA, VOC.AX, SCP.AX, 034730.KS, 3402.T, UHS.N, WNRL.N, SOHU.OQ, TRUE.BK, WES.N, SDA.AX, TECF.PA, UNc.AS, 002353.SZ, SCB.BK, TEGP.N, PCLN.OQ, TENR.MI, 0551.HK, TSS.N, TUPRS.IS, VAL.N, 0934.HK, VOD.L, UNBP.AS, PTTGC.BK, STLD.OQ, BEST.JK, 2330.TW, KINO.JK, UPS.N, RFRG.AS, WES.AX, 4506.T, RL.N, SFSN.S, 4507.T, VOES.VI, WPP.L, WFT.N, SHBa.ST, WMB.N, SSNI.N, VCTX.L, TXN.OQ, 0386.HK, SRS.MI, TJX.N, TET.TO, 009150.KS, 3673.TW, 1251.HK, UA.N, WOW.AX, SWEDa.ST, RSG.N, RRX.TO, RAND.AS, WCHG.DE, UMI.BR, WAFGn.DE, GPS.N, 3401.T, TRIP.OQ, WFC.N, UNH.N, VIAB.OQ, UTX.N, SOLB.BR, UCB.BR, RES.N, 6963.T, RDC.N, 0732.HK, 2386.HK, SEE.N, WNR.N, TA.TO, TWX.N, TCFP.PA, 4042.T, TOP.BK, WGP.N, RXN.N, REP.MC, STL.OL, 036490.KQ, SAND.ST, WWW.N, VLLP.PA, 2727.HK, UNP.N, WDIG.DE, SASY.PA, TDW.N, KHC.OQ, SCHN.PA, SEBa.ST,

14 November 2016


TRGP.N, SATS.SI, 0669.HK, TATE.L, RRC.N, WDC.OQ, TBIG.JK, YPSN.S, SAF.PA, SIEGn.DE, TOWR.JK, 006400.KS, SPMI.MI, TFFP.PA, V.N, KO.N, RBS.L, 4581.T, TEVA.N, WOR.N, ROK.N, PWR.N, 6758.T, WG.N, ROG.S, TEP.N, SUN.S, WG.L, 2325.TW, UNVR.JK, 4204.T, SCG.AX, QCOM.OQ, SYF.N, 8630.T, TSO.N, VLP.N, WHR.N, TSN.N, TTI.N, TLIT.MI, FOXA.OQ, SHP.L, SLB.N, STNG.N, WPL.AX, RR.L, 2379.TW, KIJA.JK, TKAG.DE, TOU.TO, SIAL.SI, TRE.MC, WCP.TO, RIO.L, RAD.N, 046890.KQ, VFC.N, SKFb.ST, X.N, SOWG.DE, WCG.N, SPLS.OQ, VII.TO, 000660.KS, SHB.L, TEMN.S, WBA.OQ, 6273.T, 4208.T, 000810.KS, WM.N, 6841.T, WMT.N, STO.AX, 4005.T, VACN.S, 4004.T, SKPE.KL, INT.N, 8729.T, CKH.N, 4043.T, PTTEP.BK, 4555.T, TRP.TO, RDN.N) within the next 3 months. Credit Suisse has received compensation for products and services other than investment banking services from the subject company (DANSKE.CO, CARR.PA, FDC.N, ABC.N, AET.N, DPS.N, GE.N, XOM.N, EQN.L, ESRX.OQ, LMT.N, HPQ.N, HON.N, HUM.N, ORG.AX, NFX.N, LLOY.L, HCA.N, INTC.OQ, GS.N, PPG.N, NSC.N, GM.N, SCP.AX, UNBP.AS, SHBa.ST, SWEDa.ST, RSG.N, WFC.N, UNH.N, SEBa.ST, SIEGn.DE, KO.N, RBS.L, TEVA.N, X.N, WM.N, CKH.N) within the past 12 months As of the date of this report, Credit Suisse makes a market in the following subject companies (DDS.N, DVN.N, CXO.N, FLR.N, DKS.N, DOW.N, DOV.N, DHR.N, CYH.N, EXPE.OQ, CMCSA.OQ, CSCO.OQ, EMR.N, FTI.N, DF.N, AIG.N, AAL.OQ, CCK.N, CTSH.OQ, DECK.N, BBY.N, DO.N, DAL.N, DISCA.OQ, DUK.N, CVS.N, CVX.N, AON.N, APA.N, APC.N, FIS.N, FDX.N, CAH.N, CAG.N, GOOGL.OQ, EOG.N, CLF.N, FL.N, EA.OQ, ACN.N, AMZN.OQ, CAT.N, CRZO.OQ, APD.N, BLL.N, CDNS.OQ, FSLR.OQ, CHTR.OQ, KMX.N, MMM.N, COP.N, EXPD.OQ, BWA.N, AMAT.OQ, CAR.OQ, ANF.N, CNX.N, CHK.N, CMI.N, AAPL.OQ, F.N, ABC.N, COST.OQ, AET.N, AEP.N, ETN.N, ADM.N, DD.N, ETR.N, BMY.N, DPS.N, ESV.N, COH.N, CI.N, ATW.N, DE.N, CLR.N, MT.N, GE.N, XOM.N, D.N, GD.N, CF.N, BHI.N, AMD.OQ, ATVI.OQ, DISH.OQ, EBAY.OQ, ESRX.OQ, CPB.N, LMT.N, KR.N, HAL.N, NFLX.OQ, LB.N, KMT.N, HPQ.N, MCK.N, GPOR.OQ, NKE.N, 7201.T, LNTH.OQ, K.N, MDSO.OQ, HBI.N, PSX.N, KORS.N, MOH.N, GWR.N, MNST.OQ, HON.N, 7267.T, MON.N, OI.N, HUM.N, HD.N, PEP.N, JEC.N, OXY.N, KBR.N, IP.N, PCG.N, KMI.N, NFX.N, HOS.N, MOS.N, IPG.N, KSS.N, PNR.N, PXD.N, HCA.N, PX.N, JWN.N, KEX.N, NEE.N, PTEN.OQ, MTG.N, NVDA.OQ, JCP.N, PH.N, INTC.OQ, KLAC.OQ, 6701.T, PDCE.OQ, LOW.N, NBL.N, HLX.N, MUR.N, GS.N, NOC.N, NUE.N, M.N, LH.N, OMC.N, PPG.N, INGR.N, MCD.N, NSC.N, JBLU.OQ, MRO.N, 6971.T, LRCX.OQ, JNJ.N, MU.OQ, GM.N, PVH.N, NBR.N, KSU.N, HP.N, GIS.N, OIS.N, JBHT.OQ, HES.N, SPN.N, RTN.N, WCN.N, TGT.N, DGX.N, SHW.N, RS.N, DIS.N, VLO.N, LUV.N, UHS.N, SOHU.OQ, PCLN.OQ, TSS.N, VAL.N, STLD.OQ, UPS.N, RL.N, TXN.OQ, TJX.N, UA.N, RSG.N, TER.N, GPS.N, TRIP.OQ, WFC.N, UNH.N, VIAB.OQ, UTX.N, RDC.N, WNR.N, TWX.N, WWW.N, UNP.N, TDW.N, RRC.N, WDC.OQ, V.N, KO.N, SLCA.N, TEVA.N, ROK.N, PWR.N, 6758.T, SNPS.OQ, QCOM.OQ, TSO.N, WHR.N, TSN.N, FOXA.OQ, SLB.N, RAD.N, VFC.N, X.N, WCG.N, SPLS.OQ, THC.N, WBA.OQ, WM.N, WMT.N, INT.N, RDN.N). Credit Suisse may have interest in (BUAB.KL, MAHM.NS, ONGC.NS, MAHN.NS, MRTI.NS, SKPE.KL) Please visit https://credit-suisse.com/in/researchdisclosure for additional disclosures mandated vide Securities And Exchange Board of India (Research Analysts) Regulations, 2014 Credit Suisse may have interest in (EXID.NS, APLO.NS, BFRG.NS, ARBN.NS, BOSH.NS, ARVN.NS, TEML.NS, TAMO.NS, WABC.BO) As of the end of the preceding month, Credit Suisse beneficially own 1% or more of a class of common equity securities of (DKSH.S, 6462.TWO, EXPE.OQ, FHZN.S, CTSH.OQ, 1301.TW, AGGK.L, CHC.AX, 2393.TW, DLX.AX, 2357.TW, CARR.PA, 2311.TW, FREG.DE, 4904.TW, 2409.TW, EXPN.L, FUNO11.MX, FDC.N, DOKA.S, 8069.TWO, AMFW.L, 5264.TW, 1476.TW, EZJ.L, CNA.L, CNK.N, AZJ.AX, 6147.TWO, AMA.MC, 9910.TW, ENAV.MI, 2353.TW, 2448.TW, AKS.N, KMT.N, 1477.TW, 2454.TW, MGGT.L, 6239.TW, HYPE3.SA, 2301.TW, ITRK.L, 2439.TW, PFD.L, 3481.TW, 8464.TW, IENOVA.MX, HIAG.S, MRFG3.SA, MILS3.SA, NS.N, LXSG.DE, MGR.AX, FIN.S, 0857.HK, 2317.TW, KUD.S, 2049.TW, 3034.TW, 4966.TWO, HES.N, 2303.TW, SUBC.OL, RTEC.N, WNRL.N, 6176.TW, VAL.N, 2330.TW, SFSN.S, 0386.HK, TET.TO, 3673.TW, UA.N, 3401.T, UNH.N, TA.TO, WDIG.DE, TATE.L, YPSN.S, SUN.S, TSO.N, TLIT.MI, SHP.L, RR.L, ROR.L, 2379.TW, 3702.TW, TEMN.S, VACN.S, 4043.T). As of the end of the preceding month, Credit Suisse beneficially own between 1-3% of a class of common equity securities of (EVE.S, OERL.S). Credit Suisse beneficially holds >0.5% long position of the total issued share capital of the subject company (097950.KS, GOOGL.OQ, FREG.DE, 090430.KS, 012330.KS, 161390.KS, 000720.KS, MILS3.SA, 066570.KS, 073240.KS, 051900.KS, 002241.SZ, 005380.KS, 000270.KS, 011210.KS, 034220.KS, 004170.KS, SMLP.N, 005930.KS, 018260.KS, 034730.KS, WNRL.N, UNBP.AS, TET.TO, 009150.KS, 006400.KS, TEP.N, TSO.N, 000660.KS, 000810.KS, CKH.N). Credit Suisse beneficially holds >0.5% short position of the total issued share capital of the subject company (CTSH.OQ, HYPE3.SA, MDR.N, 7988.T, 6861.T, JCP.N, NS.N, 6273.T). Credit Suisse has a material conflict of interest with the subject company (CSNA3.SA) . The analyst Ivano Westin has a relationship with a natural person who may provide remunerated services to one or more of the companies covered in this report. I, Ivano Westin, hold directly or indirectly, securities referenced in the research reports I prepare [VALE, CSNA3]. Credit Suisse has a material conflict of interest with the subject company (ABI.BR) . Credit Suisse are acting as financial advisor to Altria Group, Inc in connection with AB InBev’s proposed merger with SABMiller plc Credit Suisse has a material conflict of interest with the subject company (DOV.N) . Credit Suisse acted as exclusive financial advisor to Wayne Fueling Systems in relation to its potential sale to Dover Corp. (DOV). Credit Suisse has a material conflict of interest with the subject company (ASML.AS) . Credit Suisse is financial advisor to ASML Holding NV (ASML) in relation to its potential acquisition of Hermes Microvision Inc. (HMI). Credit Suisse has a material conflict of interest with the subject company (CPI.L) . Gillian Sheldon, a Senior Advisor of Credit Suisse, is a board member of Capita Plc (CPI.L). Credit Suisse has a material conflict of interest with the subject company (AIG.N) . Credit Suisse is acting as financial adviser to Arch Capital Group Ltd (ACGL) in relation to its proposed offer to acquire United Guaranty Corporation and AIG United Guaranty Insurance (Asia) Limited from American International Group (AIG). Credit Suisse has a material conflict of interest with the subject company (2311.TW) . Credit Suisse is acting as a financial advisor to Advanced Semiconductor Engineering, Inc. in relation to the proposed merger with Siliconware Precision Industries Co. Ltd. Credit Suisse has a material conflict of interest with the subject company (FUNO11.MX) . Credit Suisse is acting as financial advisor to Fibra Uno Administracion S.A. de C.V. on their announced acquisition of a portfolio of commercial properties held by MRP Group LP. Credit Suisse has a material conflict of interest with the subject company (MMM.N) . Credit Suisse Securities (USA) LLC is acting as financial advisor to 3M on the proposed acquisition of Ceradyne, Inc.

14 November 2016


Credit Suisse has a material conflict of interest with the subject company (AMAT.OQ) . A member of the analyst's team received compensation from the subject company (AMAT) within the past 12 months. Credit Suisse has a material conflict of interest with the subject company (ABC.N) . Credit Suisse is acting as financial adviser to PharMedium Healthcare Holdings, Inc. in relation to its definitive agreement to be acquired by AmerisourceBergen (ABC). Credit Suisse has a material conflict of interest with the subject company (CI.N) . Credit Suisse is acting as financial advisor to Anthem Inc. (ANTM) on its announced acquisition of Cigna Corporation (CI). Credit Suisse has a material conflict of interest with the subject company (AGL.AX) . Peter Wilson has approx. A$1,000 worth of AGL shares as part of an employee share purchase plan. They won’t become unrestricted for 3 years. Credit Suisse has a material conflict of interest with the subject company (ENB.TO) . Credit Suisse is acting as lead financial advisor to Enbridge Inc. (ENB) as it relates to its potential merger with Spectra Energy Corp. (SE). Credit Suisse has a material conflict of interest with the subject company (GE.N) . Credit Suisse is acting as financial advisor to General Electric Company (GE) in connection with the announced proposed acquisition of certain assets from Alstom S.A. Credit Suisse is acting as exclusive financial advisors to Capital One Financial in relation to their potential acquisition of General Electric's U.S. Healthcare Finance Unit. Credit Suisse is acting as a financial advisor to General Electric Co. (GE) in relation to their potential sale of GE Capital’s Commercial Distribution Finance, North American Vendor Finance and Corporate Finance platforms to Wells Fargo & Co. (WFC). Credit Suisse is acting as as financial advisor General Electric Co. (GE) in relation to their potential sale of GE Capital, Transportation Finance business in the U.S. and Canada to BMO Financial Group (BMO). Credit Suisse has a material conflict of interest with the subject company (EEP.N) . Credit Suisse Securities (Canada), Inc. acted as Lead Financial Advisor and delivered an opinion to Enbridge’s Board of Directors. Credit Suisse has a material conflict of interest with the subject company (XOM.N) . Kofi Adjepong-Boateng, a Senior Advisor of Credit Suisse, is a Senior Advisor to Exxon Mobile (XOM). Credit Suisse has a material conflict of interest with the subject company (EVKn.DE) . Werner Müller, a Senior Advisor of Credit Suisse, is a supervisory board member of Evonik Industries AG Credit Suisse has a material conflict of interest with the subject company (GATE.S) . Credit Suisse is acting as financial advisor to Gategroup Holding AG with respect to the proposed acquisition by HNA Group International Co LTD Credit Suisse has a material conflict of interest with the subject company (CPB.N) . Credit Suisse Securities (USA) LLC acted as financial advisor to Bolthouse Holding Corp in connection with the announced sale of the company to Campbell Soup Company. As of the date of this report, an analyst involved in the preparation of this report has the following material conflict of interest with the subject company (CVS.N). Training As of the date of this report, an analyst involved in the preparation of this report has the following material conflict of interest with the subject company (AL.N). As of the date of this report, Moshe Orenbuch had a long position in the common equity of the company. Credit Suisse has a material conflict of interest with the subject company (3658.TWO) . Credit Suisse is financial advisor to ASML Holding NV (ASML) in relation to its potential acquisition of Hermes Microvision Inc. (HMI). Credit Suisse has a material conflict of interest with the subject company (NXPI.OQ) . Credit Suisse is Sell-Side Advisor to NXP on the sale of its Standard Products Business. Credit Suisse is Financial Advisor to NXP Semiconductors (NXPI.OQ) on their sale to Qualcomm Incorporated (QCOM.OQ). Credit Suisse has a material conflict of interest with the subject company (MON.N) . Credit Suisse is acting as joint lead financial advisor to Bayer in relation to the proposed offer for Monsanto. Credit Suisse has a material conflict of interest with the subject company (PEP.N) . Laurent Grandet was formerly employed by Pepsico Inc. within the past 12 months and received compensation from the company during that period. Credit Suisse has a material conflict of interest with the subject company (IENOVA.MX) . Credit Suisse is acting as financial advisor to Fisterra Energy as it relates to their potential sale of a 100% equity interest in the Ventika I and Ventika II wind generation facilities to IEnova. Credit Suisse has a material conflict of interest with the subject company (PBR.N) . Andre Natal was formerly employed by Petroleo Brasileiro SA. within the past 12 months and received compensation from the company during that period. A household member of the research analyst Andre Natal is employed by Petroleo Brasileiro SA. Credit Suisse has a material conflict of interest with the subject company (POU.TO) . Credit Suisse is acting as a strategic advisor on Seven Generations' acquisition of Paramount Resources Ltd's Montney Nest assets. Credit Suisse has a material conflict of interest with the subject company (PX.N) . Credit Suisse is acting as advisor to Praxair Inc. (PX.N) relating to their preliminary discussions with Linde AG (LING.DE) regarding a potential merger. Credit Suisse has a material conflict of interest with the subject company (NEE.N) . Credit Suisse Securities (USA) LLC is serving as lead financial advisors to NextEra Energy. Credit Suisse has a material conflict of interest with the subject company (INTC.OQ) . Credit Suisse Securities (USA) LLC is acting as financial advisor to Intel Corp (INTL) on its announced proposed acquisition of LSI’s Axxia Networking Business from Avago Technologies Limited (AVGO). Credit Suisse has a material conflict of interest with the subject company (0857.HK) . Any Nielsen Media Research material contained in this report represents Nielsen Media Research's estimates and does not represent facts. NMR has neither reviewed nor approved this report and/or any of the statements made herein. Credit Suisse has a material conflict of interest with the subject company (VLO.N) . Credit Suisse Securities (USA) LLC is acting as financial advisor to Valero Energy Corp. on their announced decision to pursue separation of their retail business. Credit Suisse has a material conflict of interest with the subject company (TSS.N) . Credit Suisse is acting as financial adviser to Vista and TransFirst Inc. in relation to it's potential sale to Total Systems Services Inc. (TSS) Credit Suisse has a material conflict of interest with the subject company (WMB.N) . Credit Suisse is acting as financial advisor to Energy Transfer Equity (ETE) on its announced acquisition of The Williams Companies (WMB). Credit Suisse has a material conflict of interest with the subject company (WFC.N) . Credit Suisse is acting as a financial advisor to General Electric Co. (GE) in relation to their potential sale of GE Capital’s Commercial Distribution Finance, North American Vendor Finance and Corporate Finance platforms to Wells Fargo & Co. (WFC).

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Credit Suisse has a material conflict of interest with the subject company (RRC.N) . Credit Suisse Securities (USA) LLC acted as exclusive financial advisor to Range Resources Corporation in its acquisition of Memorial Resource Development Corporation. Credit Suisse has a material conflict of interest with the subject company (2325.TW) . Credit Suisse is acting as a financial advisor to Advanced Semiconductor Engineering, Inc. in relation to the proposed merger with Siliconware Precision Industries Co. Ltd. Credit Suisse has a material conflict of interest with the subject company (QCOM.OQ) . Credit Suisse is Financial Advisor to NXP Semiconductors (NXPI.OQ) on their sale to Qualcomm Incorporated (QCOM.OQ). Credit Suisse has a material conflict of interest with the subject company (FOXA.OQ) . “Tidjane Thiam, the CEO of Credit Suisse is a non-executive Director of 21st Century Fox Inc. (FOXA)” Credit Suisse has a material conflict of interest with the subject company (SLB.N) . Credit Suisse is acting as financial advisor to Cameron International (CAM) on its announced acquisition by Schlumberger (SLB). Credit Suisse has a material conflict of interest with the subject company (TOU.TO) . Credit Suisse Securities (Canada), Inc. is acting as a financial advisor to Shell Canada Energy in relation to their announced sale of non-core oil and gas properties located in Western Canada to Tourmaline Oil Corp. (TOU.TO). Credit Suisse has a material conflict of interest with the subject company (VII.TO) . Credit Suisse is acting as a strategic advisor on Seven Generations' acquisition of Paramount Resources Ltd's Montney Nest assets. As of the date of this report, an analyst involved in the preparation of this report has the following material conflict of interest with the subject company (WFC.N). As of the date of this report, an analyst involved in the preparation of this report, Susan Katzke, has following material conflicts of interest with the subject company. The analyst or a member of the analyst's household has a long position in the preferred stock Wells Fargo & Company (WFC).

For other important disclosures concerning companies featured in this report, including price charts, please visit the website at https://rave.credit-suisse.com/disclosures or call +1 (877) 291-2683. For date and time of production, dissemination and history of recommendation for the subject company(ies) featured in this report, disseminated within the past 12 months, please refer to the link: https://rave.credit-suisse.com/disclosures/view/report?i=270235&v=-2ynspab0wp7g0ab6syyty38mx .

Important Regional Disclosures Singapore recipients should contact Credit Suisse AG, Singapore Branch for any matters arising from this research report. The analyst(s) involved in the preparation of this report may participate in events hosted by the subject company, including site visits. Credit Suisse does not accept or permit analysts to accept payment or reimbursement for travel expenses associated with these events. Restrictions on certain Canadian securities are indicated by the following abbreviations: NVS--Non-Voting shares; RVS--Restricted Voting Shares; SVS--Subordinate Voting Shares. Individuals receiving this report from a Canadian investment dealer that is not affiliated with Credit Suisse should be advised that this report may not contain regulatory disclosures the non-affiliated Canadian investment dealer would be required to make if this were its own report. For Credit Suisse Securities (Canada), Inc.'s policies and procedures regarding the dissemination of equity research, please visit https://www.credit-suisse.com/sites/disclaimers-ib/en/canada-research-policy.html. Credit Suisse Securities (Europe) Limited (Credit Suisse) acts as broker to (CCC.L, BOY.L, ABF.L, EZJ.L, EXO.L, PFD.L, HLMA.L, MONY.L, ISA.L, ITV.L, WG.L, MRW.L). The following disclosed European company/ies have estimates that comply with IFRS: (ASSAb.ST, DAST.PA, ABI.BR, A3M.MC, ENEI.MI, ASML.AS, ADP.PA, ENI.MI, CCC.L, CARLb.CO, FHZN.S, ATCOa.ST, 3407.T, BBY.N, BAES.L, ERICb.ST, BOY.L, DANSKE.CO, DNB.OL, BLND.L, CAH.N, CARR.PA, FREG.DE, ATOS.PA, BNZL.L, AKZO.AS, APD.N, AIRF.PA, DC.L, EXPN.L, MMM.N, DK.N, F.N, ABF.L, DCG.L, BT.L, BMY.N, DPWGn.DE, EZJ.L, MT.N, CNA.L, ELUXb.ST, ALFA.ST, XOM.N, BEIG.DE, ALSO.PA, DANO.PA, LHAG.DE, LEGD.PA, MGGT.L, 7201.T, METSO.HE, ITRK.L, PFD.L, HLMA.L, 6806.T, LUN.CO, PFC.L, HEIN.AS, HAYS.L, LLOY.L, NOKIA.HE, DSMN.AS, NG.L, ISA.L, 6701.T, LXSG.DE, FIN.S, OUT1V.HE, NXT.L, SBRY.L, KUD.S, MKS.L, ORAN.PA, LAND.L, HMSO.L, MS.MI, ITV.L, IHG.L, IMI.L, OREP.PA, IDR.MC, PHG.AS, PRTP.PA, PUBP.PA, TSCO.L, TRN.MI, SRG.MI, TECF.PA, UNc.AS, TENR.MI, TUPRS.IS, VOD.L, VOES.VI, WPP.L, SHBa.ST, SWEDa.ST, RAND.AS, SOLB.BR, UCB.BR, TCFP.PA, REP.MC, STL.OL, SAND.ST, VLLP.PA, SASY.PA, SCHN.PA, SEBa.ST, TATE.L, YPSN.S, SIEGn.DE, SPMI.MI, TFFP.PA, RBS.L, SUN.S, WG.L, MRW.L, TLIT.MI, RR.L, TKAG.DE, SKFb.ST, THC.N, TEMN.S). As of the end of the preceding month, the subject company (CARR.PA) beneficially owned 5% or more of the total issued share capital of Credit Suisse Group. An analyst involved in the preparation of this report received third party benefits in connection with this research report from the subject company (CVS.N, HPQ.N, SPG.NZ). Credit Suisse has acted as lead manager or syndicate member in a public offering of securities for the subject company (DVN.N, CXO.N, AENA.MC, ABI.BR, ENF.TO, BERY.N, BTE.TO, ENEI.MI, ENBL.N, CYH.N, ADP.PA, ADI.OQ, EXPE.OQ, CMCSA.OQ, CSCO.OQ, ABEV3.SA, FANG.OQ, ALRM.OQ, AIG.N, AAL.OQ, DO.N, DAL.N, DISCA.OQ, ALFAA.MX, DUK.N, ALLY.N, AL.N, DANSKE.CO, BUAB.KL, DNB.OL, APC.N, DIFu.BK, ALSN.N, GLOP.N, 2311.TW, GOOGL.OQ, EOG.N, CLF.N, FREG.DE, CRZO.OQ, EVE.S, CDNS.OQ, BETR.N, 0883.HK, FUNO11.MX, ATCA.AS, CHTR.OQ, AXTA.N, MMM.N, DLNG.N, COP.N, APFH.N, BVI.PA, FDC.N, AMAT.OQ, AER.N, CNX.N, CHK.N, AAPL.OQ, F.N, ABC.N, AET.N, AEP.N, ENLK.N, DD.N, ELE.MC, BMY.N, DPS.N, BZUN.OQ, CQP.A, DE.N, MT.N, CNA.L, 600875.SS, CMRE.N, ENB.TO, GE.N, XOM.N, D.N, EXO.L, ENAV.MI, EVDY.N, EQN.L, AMD.OQ, ATVI.OQ, EBAY.OQ, EVKn.DE, ESRX.OQ, FIBRAPL14.MX, LHAG.DE, AKS.N, CPB.N, NAO.N, HAL.N, HPQ.N, MPSX.N, NVA.TO, GPOR.OQ, HCLP.N, LNTH.OQ, NXPI.OQ, MRL.MC, KTB.BK, KEL.TO, PSX.N, PFD.L, PPL.TO, MONY.L, 7267.T, PSXP.N, OI.N, HUM.N, HD.N, OERL.S, 8464.TW, IENOVA.MX, HEIN.AS, HIAG.S, KMI.N, NFX.N, GEI.TO, LLOY.L, KSS.N, PXD.N, HCA.N, PX.N, NEE.N, NG.L, GAPB.MX, ISA.L, PDCE.OQ, FIN.S, 073240.KS, 0857.HK, GS.N, NOC.N, KUD.S, 005380.KS, HUO.AX, M.N, KEY.TO, LH.N, PPG.N, NDA1V.HE, HMSP.JK, IFXGn.DE, MCD.N, BTU.N, NLSN.N, MS.MI, IMG.L, MU.OQ, GM.N, GEL.N, ORIG.OQ, ASURB.MX, GIS.N, HES.N, RTN.N, ITMG.JK, SNCR.OQ, RGC.N, WPG.L, SKI.AX, PTT.BK, DIS.N, 2303.TW, SMLP.N, VLO.N, VOC.AX, WES.N, SDA.AX, VESTA.MX, TEGP.N, KINO.JK, RFRG.AS, SFSN.S, SHBa.ST, WMB.N, SWEDa.ST, WCHG.DE, WAFGn.DE, WFC.N, UNH.N, SOLB.BR, SEE.N, TWX.N, WGP.N, RXN.N, 2727.HK, UNP.N, KHC.OQ, SEBa.ST, TRGP.N, SATS.SI, RRC.N, WDC.OQ, SAF.PA, KO.N, RBS.L, TEVA.N, PWR.N,

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14 November 2016


TEP.N, SUN.S, SCG.AX, SYF.N, VLP.N, TLIT.MI, SHP.L, SLB.N, STNG.N, WPL.AX, SIAL.SI, RAD.N, 046890.KQ, VFC.N, X.N, VII.TO, 000660.KS, PSPN.S, WM.N, WMT.N, VACN.S, PTTEP.BK, TRP.TO) within the past 3 years. Principal is not guaranteed in the case of equities because equity prices are variable. Commission is the commission rate or the amount agreed with a customer when setting up an account or at any time after that. For Thai listed companies mentioned in this report, the independent 2014 Corporate Governance Report survey results published by the Thai Institute of Directors Association are being disclosed pursuant to the policy of the Office of the Securities and Exchange Commission: Digital Telecom Infrastructure Fund () , BEC World Public Company Limited (Good) , Energy Absolute (), Krung Thai Bank (Excellent) , P.C.S. Machine Group Holding (Good) , Indorama Ventures PCL (Excellent) , Global Power Synergy (), PTT Public Company Limited (Excellent) , True Corp PCL (Very Good) , Siam Commercial Bank (Excellent) , Thai Stanley Electric (Good) , PTT Global Chemical (Excellent) , Thai Oil (Excellent) , Somboon Advance Technology (Excellent) , PTT Exploration & Production (Excellent) Credit Suisse has entered into a strategic partnership with First NZ Capital ("FNZC"). Pursuant to this agreement, (SPG.NZ) is jointly covered by Credit Suisse and First NZ Capital. This research report is authored by: Credit Suisse International .................................................. Richard Kersley ; Eugene Klerk ; Stephanie MacAulay ; Marcelo Preto ; Brandon Vair To the extent this is a report authored in whole or in part by a non-U.S. analyst and is made available in the U.S., the following are important disclosures regarding any non-U.S. analyst contributors: The non-U.S. research analysts listed below (if any) are not registered/qualified as research analysts with FINRA. The non-U.S. research analysts listed below may not be associated persons of CSSU and therefore may not be subject to the NASD Rule 2711 and NYSE Rule 472 restrictions on communications with a subject company, public appearances and trading securities held by a research analyst account. Credit Suisse International .................................................. Richard Kersley ; Eugene Klerk ; Stephanie MacAulay ; Marcelo Preto ; Brandon Vair

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14 November 2016


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