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Microstrategy
2 [email protected] 6 September 2017
Contents
Executive summary .......................................................................... 3
Investment thesis ............................................................................. 4
Genesis of a multibagger .................................................................13
A multibagger framework ................................................................19
Price of sustainable growth .............................................................51
Multibagger case studies .................................................................57
Appendix: Multibagger strategy .......................................................79
All prices quoted herein are as at close of business 1 September 2017, unless otherwise stated
Past performers
Find CLSA research on Bloomberg, Thomson Reuters, Factset and CapitalIQ - and profit from our evalu@tor proprietary database at clsa.com
For important disclosures please refer to page 84.
Desh Peramunetilleke [email protected] +852 2600 8293
Mahesh Kedia, CFA +852 2600 8291
Shrikant Kale +852 2600 8489
Our microstrategy view on individual stocks may differ from our fundamental recommendations
Executive summary Microstrategy
6 September 2017 [email protected] 3
Future hall of fame Picking Asian multibaggers has always been a rewarding strategy for the long-term investor with the underlying economies delivering spectacular growth along with favourable demographics. However, in a world increasingly dominated by passive flows, high-frequency trading and central-bank influences, identifying future candidates remains a challenge fraught with risk. In this report, we provide a quantitative framework to identify multibaggers. We blend the traditional quant signals with some of the fundamental sources of secular earnings growth, such as R&D, SG&A and overseas expansion, to understand what differentiates a multibagger from its peers.
Underlying growth in the economy remains a key cornerstone of stock-market returns over the longer term. Since the 1997 Asian financial crisis, emerging Asia has witnessed spectacular economic growth, moving from 5.8% of global GDP to 21.4%. The region weathered the global financial crisis (GFC) much better than developed markets (DM) and its future also looks bright, given that population growth is still 1.0% per annum, compared to just 0.5% in developed nations. In sync with the higher economic growth, the MSCI EM Asia index has been up 450% over the past 15 years (versus 250% for the MSCI DM) and has created many multibaggers.
Some 14.6% of Asian companies have been multibaggers, delivering returns of more than 200%, over any five-year period since 2000. While the multibaggers have now become concentrated in a few markets and sectors, Asia’s ability to deliver multibaggers remains strong. Indeed, despite the rising market penetration in most businesses, 10.2% of companies have been multibaggers over the past five years. India, China and emerging Asean have had the highest multibagger hit rate since 2000 but India stands out for its consistency. Also, given the commodity and investment cycle in the early part of 2000, cyclicals such as energy, materials and industrials have had a high hit rate. However, healthcare, consumer and tech sectors are now in focus.
Our backtests and characteristics analysis shows that companies that operate in growth markets/sectors with leading products (including brands) and good management are most likely to become multibaggers. This forms the core of our stock-selection strategy. Indeed, we have considered both industry-specific drivers such as R&D/SG&A spend and overseas exposure; and generic drivers such as growth track record, profitability and size. Using these factors, we can boost the multibagger hit rate from 14.6% to 22.1%. This is a significant increase considering that multibaggers outperform by an average 256% over the next five years, implying that the expected excess return from multibaggers rises from 37.4% to 56.6%. Our strategy shows even better results post-GFC, with the hit rate doubling from 10.3% to 21.8%.
In addition to providing a multibagger framework, we present a few case studies such as how to deal with inaccurate forecasts for the high-growth stocks. We also find that small-cap multibaggers rerate by almost 50% when they become large-caps. Lastly, we focus on the fate of past multibaggers such as Tencent and Alibaba when their market cap crossed US$300bn. We found that globally, only three out of 19 companies ever witnessed a doubling of the share price, while five had negative returns after reaching the threshold. Also, for Tencent and Alibaba, current high stock valuations are a function of their high future growth but it will become increasingly difficult to grow earnings at a similarly fast pace given the larger base.
Strong economic growth in the region underpins
the potential for creating multibaggers
Historically, 14.6% of the universe has delivered
200%+ returns over any five-year period
India has the best consistency; healthcare,
consumer and tech sectors are in focus
Our strategy increases the multibagger hit rate
from 14.6% to 22.1%
Results are even better post-GFC with the hit rate
doubling from 10.3% to 21.8%
Existing multibaggers face the challenge of
growing earnings from a large base
Asian multibaggers - a rewarding opportunity
Investment thesis Microstrategy
4 [email protected] 6 September 2017
Multibagger framework Below we present a framework to identify multibagger characteristics. Our backtests and characteristics analysis show companies that operate in growth markets/sectors with leading products (including brands) and good management are most likely to be multibaggers.
Microstrategy: Multibagger framework - influencing drivers
Source: CLSA
Below, we bring together the drivers to calculate the increase in the probability of identifying multibaggers through a quantitative framework. Our analysis shows that on average, some 14.6% of companies turn into multibaggers over the next five years. However, using the factors highlighted above, we can boost the hit rate to 22.1%. Our multibagger picks based on this methodology have strong momentum behind them.
Multibagger strategy: Average hit rate (since 2000) Microstrategy multibagger picks: Historical returns
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming over the next 5 years. ‘Higher’ implies above median factor values. Source: CLSA, Factset
Multi-baggers
Market
Sector(product)
Product superiority (R&D vs capex)
Branding & channel building (SG&A)
Overseas expansion
Manage-ment
quality
22.1
14.6 1.2
1.7 1.4
1.4 1.6
0
4
8
12
16
20
All multi-baggers
Step 1 Step 2 Step 3 Step 4 Step 5 Finalresult
Quarterly average hit rate of multibaggers (%, since 2000)
Hig
her
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itab
ility
(N
2Y a
vg R
OE)
Hig
her
grow
th
(L3Y
EPS
Cag
r)
Hig
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R&
D, SG
&A a
nd
over
seas
exp
osur
e
Avo
id la
rge
caps
(Mar
ket
cap
< U
S$5
bn)
Avo
id m
id c
aps
(Mar
ket
cap
< U
S$1
bn)
90
140
190
240
290
340
390
440
490
540
Dec
11
Jun
12
Dec
12
Jun
13
Dec
13
Jun
14
Dec
14
Jun
15
Dec
15
Jun
16
Dec
16
Jun
17
Asian potential multibaggers
MSCI APxJ
Cumulative index (FF adj mcap-wtd, US$ TR, x)
38.9% Cagr
8.9% Cagr
A quantitative framework to capture
qualitative characteristics
Our strategy increases the
multibagger hit rate from 14.6% to 22.1%
Investment thesis Microstrategy
6 September 2017 [email protected] 5
Key Asian potential multibaggers Asian potential multibaggers (sorted by last three-years EPS Cagr) Code Name Cty Sector Mkt cap FY1-FY2 L3Y EPS R&D/ SG&A/ Foreign 12MF FY1-FY2 NDE TR (US$m) ROE Cagr sales sales sls exp PE EPS Cagr (latest, (L12M,
(avg, %) (%) (FY0, %) (%) (x) (%) %) %) China & HK 1302 HK LifeTech Sci CN Healthcare 950 21.1 81.7 16.3 37.7 19.6 35.8 68.3 (51.3) 16.2 1548 HK Genscript Biotech CN Pharma 932 16.4 44.2 8.3 36.2 81.1 28.5 15.5 (76.8) 181.3 2869 HK Greentown Service CN Comm svcs 1,608 23.4 42.4 na 7.6 0.0 23.0 22.3 (126.9) 64.0 1558 HK YiChang HEC CN Pharma 1,109 18.0 35.4 6.8 26.5 0.0 12.7 28.1 (45.7) 11.5 6068 HK Wisdom Education CN Cons svcs 763 17.0 30.3 na 15.3 0.0 15.2 29.1 (26.1) 89.5 520 HK Xiabuxiabu Catering CN Cons svcs 1,101 22.4 26.5 na 40.8 0.0 15.7 15.2 (87.2) 117.3 1316 HK Nexteer HK Autos 4,188 27.7 26.0 3.2 3.4 100.0 11.2 14.0 1.3 23.5 425 HK Minth CN Autos 4,897 18.6 19.5 4.2 11.3 38.0 13.8 21.0 (14.1) 29.5 India MNDA IN Minda IN Autos 954 22.6 187.3 1.7 13.2 20.2 25.3 29.0 7.3 206.8 VKI IN Vakrangee IN Software 3,707 28.8 69.9 na 1.1 0.0 33.4 20.2 (23.0) 139.7 CANF IN Can Fin Homes IN Banks 1,159 23.9 37.4 nm nm nm 22.0 27.9 nm 87.6 WHIRL IN Whirlpool IN Cons dur 2,353 23.1 36.2 0.9 24.6 7.9 35.1 24.8 nm 28.0 EDEL IN Edelweiss Fin svcs IN Div fin 3,231 18.1 34.4 nm nm nm 21.7 37.7 nm 116.2 TELX IN Tata Elxsi IN Software 798 32.9 33.8 1.4 53.8 84.8 22.1 21.8 (45.0) 2.3 VGRD IN V-Guard IN Cap gds 1,180 25.1 28.3 0.4 18.3 0.0 38.6 21.8 (16.0) 48.0 ABB IN ABB India IN Cap gds 4,467 15.3 28.0 3.5 8.7 14.5 48.0 31.1 (29.4) 16.9 NFIL IN Navin Fluorine IN Materials 512 17.1 27.9 1.9 20.2 na 22.5 21.8 (7.1) 45.1 PVRL IN PVR IN Media 934 16.0 17.7 na 41.1 0.0 33.5 46.7 72.5 6.0 Korea 147760 KS Microfriend KR Semis 111 22.7 64.1 4.2 6.6 0.0 9.6 40.4 (47.0) 84.9 145020 KS Hugel KR Pharma 1,569 19.4 56.8 3.3 20.4 0.0 24.9 34.2 (46.3) 23.1 041830 KS InBody KR Healthcare 355 20.0 40.0 6.7 36.8 76.7 17.5 21.1 (46.4) (16.0) 083310 KS LOT Vacuum KR Semis 181 24.4 39.0 5.1 18.3 0.0 8.3 74.6 1.3 13.8 089590 KS Jeju Air KR Transport 896 25.5 31.6 na 11.7 0.0 11.0 35.1 (113.3) 27.7 098460 KS Koh Young Tech KR Semis 726 20.0 28.7 10.8 31.2 91.9 21.5 17.1 (45.5) 41.0 048260 KS Osstem Implant KR Healthcare 852 23.6 27.4 2.4 46.3 0.0 26.9 40.2 63.3 19.7 089600 KS Nasmedia KR Media 386 20.8 24.9 1.7 74.3 0.0 17.1 48.3 (24.3) 23.1 Taiwan 4968 TT Richwave Tech TW Semis 204 25.5 101.2 10.6 12.5 56.2 21.2 51.2 (49.9) 98.1 5269 TT Asmedia Tech TW Semis 599 36.8 58.2 20.7 6.1 43.2 21.1 66.4 (76.1) 61.5 2723 TT Gourmet Master TW Cons svcs 1,973 23.4 44.7 0.1 47.2 81.6 25.3 20.1 (62.2) 35.9 8436 TT TCI TW HPC 507 21.2 40.3 5.1 16.3 65.5 19.8 26.9 (41.3) 46.8 5274 TT ASPEED Tech TW Semis 789 34.1 36.0 10.6 6.7 61.1 29.8 38.7 (60.2) 81.8 4919 TT Nuvoton Tech TW Semis 365 24.1 33.3 26.6 7.1 96.9 12.0 28.4 (53.3) 47.0 1536 TT Hota Industrial TW Autos 1,156 29.7 30.6 2.5 10.4 95.4 21.0 21.1 31.6 (13.5) 4551 TT Global PMX TW Autos 450 21.8 28.6 2.0 7.1 97.8 18.8 26.2 11.2 26.1 5306 TT KMC TW Cons dur 544 23.9 24.5 0.7 14.7 97.4 14.7 16.4 22.7 26.5 2421 TT Sunonwealth TW Cap gds 456 22.3 23.2 5.7 10.3 100.0 13.5 39.9 (12.4) 120.3 3152 TT Advanced Ceramic TW Tech HW 849 29.6 19.4 5.1 5.8 81.7 24.3 18.4 (88.4) 130.3 3665 TT Bizlink TW Cap gds 876 22.2 10.8 2.5 16.0 96.4 18.1 30.7 (21.2) 30.2 Asean markets PPRO IJ PP Properti ID Property 970 na 61.9 na 2.4 0.0 27.2 16.4 30.4 2.6 SRIL IJ Sritex ID Cons dur 490 17.0 61.0 na 4.9 52.5 5.9 17.0 137.3 32.0 MYEG MK My E.G. Services MY Software 1,758 41.0 58.7 na 21.7 0.0 26.9 36.9 (10.9) 51.2 BEAUTY TB Beauty Community TH Retail 1,236 72.7 46.5 na 35.6 0.0 36.0 37.0 (77.8) 50.7 MTLS TB Muangthai Leasing TH Div fin 2,071 30.9 44.0 nm nm nm 23.7 48.0 nm 76.3 LINK IJ PT Link Net Tbk ID Telecom 1,152 22.7 31.7 na 20.2 0.0 14.2 19.8 (9.0) 8.5 JMT TB JMT Network Svcs TH Comm svcs 338 17.3 17.7 na 37.4 0.0 28.3 69.9 nm 106.6 SCC PM Semirara Mining PH Energy 3,518 37.1 17.0 na 12.9 0.0 11.1 17.6 31.6 60.6 8002 HK IGG SG Software 2,132 57.3 10.1 11.2 32.2 100.0 10.7 72.6 (93.9) 218.0 Australia & New Zealand BWX AU BWX AU HPC 400 21.1 467.2 1.2 28.0 20.0 21.6 48.7 51.3 17.9 ATM NZ a2 Milk NZ FBT 2,628 47.7 75.2 0.8 17.5 20.0 29.1 47.3 (62.2) 170.8 ALU AU Altium AU Software 888 27.0 25.6 13.6 49.1 100.0 25.3 23.8 (27.6) (0.8) Note: For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Total return is based on local currency. Source: Factset, CLSA
Investment thesis Microstrategy
6 [email protected] 6 September 2017
Understanding the multibagger picks Below we highlight the business description of the top multibagger picks, especially the qualitative statements that support the continued presence of important multibagger characteristics such as focus on R&D/SG&A spend, rising overseas exposure or high market growth. We also highlight the EPS trend for the past-five and next-three years (where the relevant history and forecasts are available). Most of our picks have steadily rising earnings growth, which has been a hallmark of multibaggers in the past.
Asian potential multibaggers: Main growth theme, supporting drivers and EPS trends
Note: EPS trend is based on non-GAAP adjusted earnings per share. Source: CLSA, Factset
Code Name Description R&D SG&A Overseas EPS trendexposure (11A-19F)
China & HK
1302 HK LifeTech Sci¹ Strong R&D spender in the cardiovascular-diseases-related products. Products getting approval across the world, which could lead to growing exports.
1548 HK Genscript Biotech
Originally based in New Jeresy, its main focus is biological research services (DNA sequencing, etc) but it is also increasing its footprint in cancer cures. Higher R&D and advertising spending, plus rising sales in China could drive future growth.
2869 HK Greentown ServiceTop-rated property-management services, property-consulting and community-services company in China benefitting from rising demand for premium residential services.
1558 HK YiChang HECA rising player in the China drug manufacturing market with 33 pharma products. One of its product, Kewei (oseltamivir phosphate), has been the No.1 selling influenza drug in China from 2013 to 2016.
6068 HK Wisdom EducationLargest provider of private education in South China operating premium primary and secondary schools (high margin), as measured by student enrolment as of 1 Sep 2015, according to the Frost & Sullivan Report.
520 HK Xiabuxiabu CateringRestaurant company with chains in 30-plus cities in China that is upgrading and expanding its network as well as entering several new concept areas in the dining business.
1316 HK NexteerSteering and driveline-systems company with a global footprint. Customers include BMW, FCA, Ford, GM, PSA, Toyota, VW and automakers in India and China. It is also one of the beneficiaries of autonomous driving theme.
425 HK Minth China’s leading auto-bodyparts supplier with growing export sales (with higher margin) due to substantially lower cost base compared to its Japanese peers.
Korea
147760 KS Microfriend Top MEMS (Micro Electro Mechanical System) specialist company with strong FCF.
145020 KS HugelBotox manufacturer controlling 30% of the botox market, a lucrative industry in Korea due to rising domestic demand for dermatology and cosmetic surgery as well as the increasing popularity of cosmetic-surgery tourism.
041830 KS InBodyAccounts for 90% of domestic and 60% of global body-composition analysis market with a well-diversified overseas exposure. It is launching new products (such as InBody watch) and targeting the IoT-based healthcare market.
083310 KS LOT Vacuum Provision of dry vaccum pumps for semiconductor manufacturing with strong R&D growth.
089590 KS Jeju Air
Biggest LCC by market share in Korea. Benefitted from the lifestyle changes as more Koreans are preferring to travel overseas using lower cost airlines. Low exposure to THAAD issue as only a small percentage of revenue is from Chinese charter flights.
098460 KS Koh Young Tech A global leader in 3D measurement technology for electronics assembly with a stable growth profile and increasing sales exposure to the US and Europe.
048260 KS Osstem ImplantOne of the key players in the global dental implant and prosthetic market. According to the report by Market Research Future, the market is expected to post a 4.6% Cagr from 2015-22 with Apac being the fastest-growing region.
089600 KS NasmediaTop digital media rep agency in Korea with 20% market share. High exposure to the fast-growing online mobile advertising with 71% of total revenue coming from the segment.
Our multibagger picks have steadily
rising EPS
Investment thesis Microstrategy
6 September 2017 [email protected] 7
Asian potential multibaggers: Main growth theme, supporting drivers and EPS trends (continued)
Source: CLSA, Factset
Code Name Description R&D SG&A Overseas EPS trend
exposure (11A-19F)
India
MNDA IN MindaTier-1 electrical-autoparts supplier to OEM with global presence. International clients include Toyota, BMW, Honda, Volkswogen, Ford, Piaggio along with all major domestic Indian autos companies.
VKI IN VakrangeeE-governance/digital is a growing business segment in India and the company has a vast network of retail acces points to deliver financial and other G2C services to unserved rural, semi-urban and urban markets.
CANF IN Can Fin Homes
Small but rising player in the fast-growing housing-finance market in India with loan book enjoying a 32% Cagr since 2014. 75% of loan book coming from Salaried & Professional segment with low overall gross NPA ratio at 0.38%.
WHIRL IN Whirlpool Leading manufacturers and marketers of major home appliances in India with a strong brand focus.
EDEL IN Edelweiss Fin svcsLeading diversified financial services (capital markets) in India with growing market share as evidenced by rising profits even during the volatile equity market periods of 2012-14.
TELX IN Tata ElxsiEngaged in product design and engineering; and system integration and support services for enterprise customers. It has also ventured into emerging tech such as IoT, Virtual Reality, Big data, Cloud, AI etc.
VGRD IN V-Guard Electronic and electro mechanical product company with a strong brand presence in India and it is further boosting its marketing and R&D expenses.
ABB IN ABB IndiaPart of the ABB group, it manufactures and distributes products for power systems, generation and automation in India. It's a play on improving quality of Indian power grids and networks.
NFIL IN Navin FluorineIndia's largest integrated specialty fluorochemical company. Fluorochemicals is a high-growth industry mostly due to focus on underpenetrated products such as air conditioning, refrigration, autos, pharma etc.
PVRL IN PVRPVR, the largest movie multiplex company in India, has a strong brand image, right locations and leadership in key markets/box-office circuits. Strong industry outlook led by an under-screened market and growing consolidation.
Asean markets
PPRO IJ PP Properti
Property subsidiary of PT PP (60% ownership) and is newly listed in 2015. Large increase in bookings this year due to new projects. Landbank increase to 280ha versus 70ha last year, which should translate into more new projects.
SRIL IJ SritexAsean's largest vertically-integrated textile and garment manufacturer. The garments OEM segment is lucrative supported by military uniform orders from UAE, EU and NATO; global fashion lines such as Guess, H&M, Disney and Lee.
MYEG MK My E.G. ServicesMalaysia's sole provider of government e-services. Its broad strategy focuses on going into services where there is a renewal requirement on a regular basis, leading to recurring cashflow.
BEAUTY TB Beauty CommunityCosmetics company with a focus on beauty, personal care, skincare and makeup. Thailand's personal-care market is growing at 6-7% but the company's topline is growing by more than 30%.
MTLS TB Muangthai LeasingVast potential in micro-lending should support growth. The farming sector accounts for 40% of Muangthai's loan book, and it could benefit from rising government support for the agri sector.
LINK IJ PT Link Net TbkCable TV and internet broadband provider operating in several major cities including Jakarta. Low broadband penetration in Indonesia could remain supportive of growth.
JMT TB JMT Network SvcsThailand's biggest bad-debt collection company and beneficiary of the rising NPLs in the sytem. It can expand into neighbouring countries using partners who do not have such services.
SCC PM Semirara MiningLargest coal producer in the Philippines. The company has ventured into power generation primarily to take advantage of the cost and operational synergies between the two businesses.
8002 HKIGG
(Singapore stock)
A play on the global gaming market with geographically well-diversifed revenue, and two big hit games titled Lords Mobile and Castle Clash. It has >380m registered users with about 17m monthly active users across over 200 countries.
Investment thesis Microstrategy
8 [email protected] 6 September 2017
Asian potential multibaggers: Main growth theme, supporting drivers and EPS trends (continued)
Source: CLSA, Factset
Code Name Description R&D SG&A Overseas EPS trendexposure (11A-19F)
Taiwan
4968 TT Richwave TechIC development and design with focus on WiFi and is foraying into IoT, smarthome, automotives etc. It benefits from rising WiFi demand and its growing R&D budget should keep the product pipeline strong.
5269 TT Asmedia Tech A USB play with first SuperSpeed USB 3.1 (10Gbps) technology. Very high R&D budget, could be industry leader.
2723 TT Gourmet MasterSince its establishment in 2004, Gourmet Master's 85C café brand has grown to become the largest coffee house/bakery in Taiwan. It also aggresively expanding its coffee brand in China and the USA.
8436 TT TCI
Bioscience company with dietary suppliements, function drinks and skincare products. Strong R&D focus to help with new product development and it has a high China exposure (including a China plant) along with exports to 41 countries.
5274 TT ASPEED Tech Fabless IC-design company and with an increased focus on Cloud business and strong R&D budget.
4919 TT Nuvoton TechCompany engaging in R&D and sales of IC products and provision of wafer foundry services with lot of new product successes. It has also launched an IoT solution.
1536 TT Hota Industrial
Leading automotive-transmission-system partsmaker in Taiwan and sole supplier of gearboxes to Tesla. Its inhouse equipment supports high precision and flexibility, and has helped secure orders from BorgWarner, Tesla and Eaton.
4551 TT Global PMX
High-precision mechanical autoparts maker in Taiwan, focusing on engine parts and ABS/ESC parts. With GDI parts, it rides the structural trend of better fuel economy and lower gas emissions, boasting a strong overseas customer base.
5306 TT KMCKMC is the largest bicycle-chain manufacturer globally, with a market share of 70-80%. It has a close relationships with its brand customers and is the only supplier offering a wide range of products from low- to high-speed chain.
2421 TT Sunonwealth
Strong R&D focus in core motor technology with numerous patents and industry-leading products such as the first magnetic levitation motor fan (Maglev), smallest /thinnest fan (Mighty Mini) in the world, thermal modules for LED panels, etc.
3152 TT Advanced CeramicIntegrated device manufacturer (IDM) that designs & manufactures LTCC components/filters used in all connectivity devices. Benefits from rising connectivity and RF content increases in 4G+/5G smartphones and WiFi MIMO.
3665 TT BizlinkWiring-harness and cable-assemblies manufacturer and the sole supplier of wiring harnesses for Tesla’s battery-management systems, Superchargers, Powerwall and Powerpack. It is expanding its automotive business in Europe.
Australia & New Zealand
BWX AU BWX
A natural skincare products and distribution company with strong export growth in the UK, China and Canada. It owns a successful brand (Sukin) in its home market and just bought "Mineral Fusion", the No.1 natural cosmetics brand in USA.
ATM NZ a2 MilkThe pioneer producer of milk with natural A2 protein with rising sales in AU/NZ and China. It is the leading premium fresh milk brand in Australian supermarkets, with a grocery value market share of approximately 9.3%.
ALU AU AltiumDesign and engineering software company with strong R&D spending and well-distributed global earnings with growth across USA and EM (especially China). One of the peers (Cadence) has a market cap of US$10bn.
Investment thesis Microstrategy
6 September 2017 [email protected] 9
Asia has produced a lot of multibaggers over the past 15 years
Contribution to global GDP by EM Asia since 1995 Global regions/markets - GDP growth vs return (L15Y)
Source: Factset, IMF, CLSA
Hit rate of stocks becoming multibaggers (since 2000) Multibagger strategy: Average hit rate (since 2000)
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
APxJ markets: Latest contribution to 5Y triple-baggers APxJ sectors: Latest contribution to 5Y triple-baggers
Note: Only includes companies with at least US$100m market cap at the start of the period. Source: CLSA, Factset
5.8
21.4
0
5
10
15
20
25
95A
96A
97A
98A
99A
00A
01A
02A
03A
04A
05A
06A
07A
08A
09A
10A
11A
12A
13A
14A
15A
16F
17F
18F
Contribution to global nominal GDP (%)
EM Asia's contribution to global GDP has increased from 5.8% in 1995 to 21.4% in 2016
Australia
China
HK
India
Indonesia
Korea
Malaysia
Philippines
SingaporeTaiwan
Thailand
Japan
USA
Latin America
DM Europe
EM Asia
3
5
7
9
11
13
15
17
19
0 2 4 6 8 10 12 14 16
Nominal GDP growth (L15Y Cagr, %)
Total return US$ (L15Y Cagr, %)
y = 0.69x + 7.20; R2 = 0.55
17.6
25.1
7.9
14.6 13.9
19.9
10.7
22.6
4.2
10.2
7.0
21.2
0
5
10
15
20
25
30
+100%in 3 yrs
+100%in 5 yrs
+200%in 3 yrs
+200%in 5 yrs
+500%in 10 yrs
+500%in 15 yrs
Double-baggers Triple-baggers Multibaggers
Quarterly average hit rate (since 2000)
Latest hit rate
Hit rate of stocks becoming multibaggers (%)
Key multibagger indicator
22.1
14.6 1.2
1.7 1.4
1.4 1.6
0
4
8
12
16
20
All multi-baggers
Step 1 Step 2 Step 3 Step 4 Step 5 Finalresult
Quarterly average hit rate of multibaggers (%, since 2000)
Hig
her
prof
itab
ility
(N
2Y a
vg R
OE)
Hig
her
grow
th
(L3Y
EPS
Cag
r)
Hig
her
R&
D, SG
&A a
nd
over
seas
exp
osur
e
Avo
id la
rge
caps
(Mar
ket
cap
< U
S$5
bn)
Avo
id m
id c
aps
(Mar
ket
cap
< U
S$1
bn)
India33%
China11%
Korea11%
Taiwan11%
Aust10%
HK7%
Thai5%
Indo3%
Malay3%
Others6%
Latest contribution of 5-year triple-baggers in APxJ region (%)
Cons disc18%Cons
stap9%
Energy1%
Financials13%
H'care13%
Industrials12%
Info tech16%
Materials10%
Property5%
Telecom1%
Utilities2%
Latest contribution of 5-year triple-baggers in APxJ region (%)
Strong economic growth resulted in good market performance, creating many multibaggers
Some 14.6% of companies deliver 200%+ return in five years; our strategy increases the hit rate to 22.1%
India, China, Korea, and consumer and tech sectors contributed the most to multibaggers over past 5-years
Investment thesis Microstrategy
10 [email protected] 6 September 2017
Industry specific drivers - R&D, SG&A and overseas exposure
MSCI regions (ex-fin): R&D as a % of sales APxJ: R&D spend of multibaggers relative to industry
Note: Regional ratios are bottom-up aggregated with freefloat adjustment based on current MSCI universe. R&D spending data based on industry median within broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
MSCI regions (ex-fin): SG&A (ex-R&D) as a % of sales APxJ: SG&A (ex-R&D) spend of multibaggers vs ind
Note: Regional ratios are bottom-up aggregated with freefloat adjustment based on current MSCI universe. SG&A spending data based on industry median within broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
MSCI regions: Regional sales geographical breakdown APxJ mkts (ex-fin): GDP gr vs foreign sales exp (L5Y)
Source: CLSA, Factset, IMF
3.0
2.7
2.3
1.9
0.5
1.0
1.5
2.0
2.5
3.0
3.5
00A
01A
02A
03A
04A
05A
06A
07A
08A
09A
10A
11A
12A
13A
14A
15A
16A
USA Japan
Europe AsiaxJ
R&D as a % of sales
0
2
4
6
8
10
12
0.7
0.9
1.1
1.3
1.5
1.7
1.9
Sof
twar
e
Tech
hw
Inte
rnet
Pers
pro
d
Sem
is
Aer
o&de
f
H'c
are
E&S
Elec
I&
C
Bio
tech
Phar
ma
Com
m e
quip
Mac
hine
ry
Aut
o pa
rts
H'h
old
dur
Elec
equ
ip
Multibaggers rel to industry (avg 2000-12)Current - FY0 R&D to sales (RHS)
(x) (%)
Multibaggers have much higher R&D spending in most relevant
industries
17
15.1
15.7
14.4
10.0
8
9
10
11
12
13
14
15
16
17
18
00A
01A
02A
03A
04A
05A
06A
07A
08A
09A
10A
11A
12A
13A
14A
15A
16A
USA Japan
Europe AsiaxJ
SG&A (ex-R&D) as a % of sales
51015202530354045
1.0
1.1
1.2
1.3
1.4
1.5
Com
m e
quip
Div
con
s sv
cEl
ec e
quip
Air
lines
Pape
rSof
twar
eEn
ergy
E&
SC
emen
tM
ulti-
reta
ilU
nive
rse
Med
iaFo
od p
rod
Aut
o pa
rts
IT S
ervi
ces
Tex/
app/
lux
Bio
tech
Toba
cco
H'h
old
dur
Dev
elop
ers
Hot
els
Mac
hine
ryAut
osBld
g pr
od
Multibaggers rel to industry (avg 2000-12)Current FY0 SG&A (ex-R&D) to sales (RHS)
(x) (%)
Multibaggers have much higher SG&A spending in many relevant industries
1.73
80.4
11.5 14.3 15.4 23.4
9.7
68.2
17.2 20.9
38.1
57.5 10.2
7.213.0
8.4
52.8
20.9
5.0 8.5 7.5
0
10
20
30
40
50
60
70
80
90
100
AxJ USA Japan Europe World
AxJ USA Japan Europe OtherSales geographical breakdown (%)
Philippines
Malaysia
Singapore
China
Taiwan
IndiaKorea
Indonesia
Thailand
Australia
APxJxHK
0
10
20
30
40
50
60
2 4 6 8 10 12 14
Foreign revenue as % of sales (L5Y avg)
Nominal GDP growth in lcl ccy (L5Y Cagr, %)
y = -3.9x + 50.7; R2 = 0.41
Asian R&D spend has doubled since 2008; multibaggers had higher R&D spend for most relevant industries
Asia’s SG&A spend still below USA; multibaggers had higher SG&A spend in 26 out of 46 industries
Companies can grow not only by capturing market share, but also by opening up new markets
Investment thesis Microstrategy
6 September 2017 [email protected] 11
Fundamentals relevant across industries - growth, size, profitability
Characteristics analysis - since 2000 Characteristics analysis - since 2010
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
APxJ: Hit rate of high growth multibaggers APxJ: Hit rate of high profitability multibaggers
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
APxJ: Hit rate of becoming multibaggers by mkt cap Multibaggers relative PE premium within mcap ranges
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
0.8
0.9
1.0
1.1
1.2
EPSg
(L3Y
)
Gea
ring
Sus
tg
EPSg
(L5Y
)
EPSg
(N2Y
)
RO
E (L
3Y)
RO
E (N
2Y)
RO
IC
Mgn
(Avg
L3Y)
Mgn
(FY
0)
PB (
trl)
SLS
g (L
3Y)
SLS
g (N
2Y)
PE (
fwd)
Cas
h/TA
Siz
e
Quarterly median (since 2000)
Exposure of multibaggers relative to broader universe (x)
0.60.70.80.91.01.11.21.3
RO
IC
EPSg
(L3Y
)
Sus
tg
RO
E (L
3Y)
RO
E (N
2Y)
PB (
trl)
EPSg
(L5Y
)
EPSg
(N2Y
)
SLS
g (L
3Y)
Mgn
(Avg
L3Y)
SLS
g (N
2Y)
Mgn
(FY
0)
PE (
fwd)
Cas
h/TA
Gea
ring
Siz
e
Quarterly median (since 2010)Exposure of multibaggers relative to broader universe (x)
14.6
16.2 16.3
18.1
10.210.7 11.2
11.7
8
10
12
14
16
18
EPS Cagr (N2Y) Sustg EPS Cagr (L3Y)
All multibaggers Above median
Quarterly average hit rate (since 2000)Latest hit rate (+200% since 2012)
Hit rate of stocks becoming multibaggers (%)
14.6
15.8 15.9
10.2
11.9 11.9
89
1011121314151617
All multibaggers All multibaggers(ex-fin, ROIC >
median)
All multibaggers(N2Y ROE > median)
Quarterly average hit rate (since 2000)Latest hit rate (+200% since 2012)
Hit rate of stocks becoming multibaggers (%)
14.6 15.5 13.9
9.0
10.2 11.9
7.9
4.2 02468
1012141618
All multi-baggers
Small-cap<US$1bn
Mid-capUS$1-5bn
Large-cap>US$5bn
Market capitalisation
Quarterly average hit rate (since 2000)
Latest hit rate (+200% since 2012)
Hit rate of stocksbecoming multibaggers (%)
0.90
1.22
1.35
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
<US$1bn US$1-5bn >=US$5bn
Market cap ranges
MultibaggersMedian relative PE versus MSCI APxJ (x)
34.6% valuation premium
11.1% valuation premium
Growth, profitability and size are main factors that have mattered over the long term
Above-median three-year earnings Cagr increases the multibagger hit rate from 14.6%to 18.1%
Large-caps have low multibagger probability. Small cap multibaggers rerate when they become large-caps
Investment thesis Microstrategy
12 [email protected] 6 September 2017
What happens to large-cap multibaggers?
Market cap trend: Tencent versus Facebook Market cap trend: Alibaba versus Amazon
Source: CLSA, Factset
US$ TR after surpassing US$300 Mcap threshold EPS gr (N5Y vs L5Y) after reaching US$300bn Mcap
Source: CLSA, Factset
Tencent: fwd PE and 1Y forward growth Alibaba: fwd PE and 1Y forward growth
Source: CLSA, Factset
397
491
0
50
100
150
200
250
300
350
400
450
500
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
Tencent
(US$bn)
443
474
0
50
100
150
200
250
300
350
400
450
500
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
Alibaba
Amazon
(US$bn)
265 256
163
82 55 39 35 35 29 24 23 8 4 3
(5)(30)
(55)(79)
(89)(150)(100)(50)
050
100150200250300
App
le
Mic
roso
ft
Exxo
n
Alp
habe
t
Wal
-Mar
t
Ber
kshi
re BP
J&J
ICBC
Pfiz
er GE
JPM
orga
n
Vod
afon
e
Inte
l
Chi
na M
obile
Cis
co
Petr
oChi
na
Gaz
prom
Eric
sson
US$ total returns after surpassing US$300bn Mcap(%)
Jan-
11 Oct
13
Sep
00Nov
98
Mar
00
Oct
13
Dec
98
Jun
00
Oct
07
Sep
14
Sep
99
May
14
Dec
99
Nov
07
Sep
07
Dec
99
Sep
07Jan
00
Mar
00
Yellow box represents the month during which the stock surpassed the US$300bn mark
13.8
15.8
19.0
8.9
(10.
5)
23.3
(5.1
) 12.7
(2.0
) 8.2
10.1
8.2 14
.5
20.5
12.6
2.1
25.7
(20)
0
20
40
60
80
100
Gaz
prom
App
le
Cis
co
Mic
roso
ft
Eric
sson
ICBC
Petr
oChi
na
Alp
habe
t
Inte
l
Chi
na M
obile
Ber
kshi
re GE
Wal
-Mar
t
Exxo
n
Pfiz
er J&J
BP
Previous 5YEPS Cagr
(%) After surpassing US$300bn Mcap mark, 14 of the 17 stocks have witnessed growth slowdown with average growth decelerating from 26.6% over the previous five years to 10.5% over the next five
15
20
25
30
35
40
45
Dec
-09
Jun-
10
Dec
-10
Jun-
11
Dec
-11
Jun-
12
Dec
-12
Jun-
13
Dec
-13
Jun-
14
Dec
-14
Jun-
15
Dec
-15
Jun-
16
Dec
-16
Jun-
17
1yr fwd growth
12MF PE (x)
PE and growth (x, %)
Correlation = 0.40
Tencent derated from 36x to 17x
15
20
25
30
35
40
45
Sep
-14
Dec
-14
Mar
-15
Jun-
15
Sep
-15
Dec
-15
Mar
-16
Jun-
16
Sep
-16
Dec
-16
Mar
-17
Jun-
17
12MF PE (x)
1yr fwd growth
PE and growth (x, %)
Alibaba derated from 40x to 20x
Correlation = 0.59
Large-caps tied to ecommerce/internet themes have seen a market cap surge beyond US$400bn
After surpassing US$300bn mark, only 3/19 became double-bagger while five delivered negative returns
Alibaba & Tencent: High correlation between PE and future growth forecast
Section 1: Genesis of a multibagger Microstrategy
6 September 2017 [email protected] 13
Genesis of a multibagger The Asian financial crisis (AFC) of 1997 severely impacted the potential of the tiger economies. Crumbling currencies and a defunct banking system led many investors to question the region’s future. Fast-forward 20 years and emerging Asia has witnessed spectacular economic growth, moving from 5.8% of global GDP to 21.4%. Indeed, with domestic demand underpinning growth, Asia weathered the global financial crisis (GFC) much better than developed markets. Its future also looks bright when you consider that population growth is still 1.0% per annum, compared to just 0.5% in developed nations, while there is also a favourable middle-young (MY) ratio in most emerging-Asia countries.
Figure 1 Figure 2
Contribution to global GDP by EM Asia since 1995 Population Cagr (next 2-years) for global major markets
Source: IMF, CLSA Source: IMF, CLSA
MSCI EM Asia - total return of 450% over the past 15 years Asian markets have benefitted immensely from the steep rise in economic growth over the past 15 years. This is especially true for markets such as China, emerging Asean and India. Despite different drivers, they have all witnessed significant economic growth. While emerging Asean and India have relied on consumption-led growth, China has relied heavily on investment-led growth. These markets have delivered total returns of 550-750% during this period, outperforming the rest of Asia and global developed markets. In the process, they have been instrumental in creating multibaggers.
Figure 3 Figure 4
Performance of MSCI EM Asia markets vs DM since 2003 Global regions/markets - GDP growth vs return (L15Y)
Nominal GDP growth based on change in US-dollar GDP data. Source: Factset, IMF, CLSA
5.8
21.4
0
5
10
15
20
25
95A
96A
97A
98A
99A
00A
01A
02A
03A
04A
05A
06A
07A
08A
09A
10A
11A
12A
13A
14A
15A
16F
17F
18F
Contribution to global nominal GDP (%)
EM Asia's contribution to global GDP has increased from 5.8% in 1995 to 21.4% in 2016
1.0
0.5
(0.5)
0.0
0.5
1.0
1.5
2.0
Phil
Mal
ay
Aus
t
Indi
a
Indo
Sin
g
EM A
sia
HK
USA
UK
Chi
na DM
Fran
ce
Kor
ea
Ger
man
y
Taiw
an
Thai
Ital
y
Japa
n
Population Cagr (17-18F, %)
EM Asia's populationgrowth far higher than DM
0100200300400500600700800900
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
China EM Asean IndiaDM EM Asia
Index(US$ TR)
DM up only 250%
Total return of 550-750% for China, India and EM Asean
Australia
China
HK
India
Indonesia
Korea
Malaysia
Philippines
SingaporeTaiwan
Thailand
Japan
USA
Latin America
DM Europe
EM Asia
3
5
7
9
11
13
15
17
19
0 2 4 6 8 10 12 14 16
Nominal GDP growth (L15Y Cagr, %)
Total return US$ (L15Y Cagr, %)
y = 0.69x + 7.20; R2 = 0.55
Emerging Asia has risen to 21.4% of global GDP,
from just 5.8% during the Asian financial crisis
Strong economic growth resulted in good market
performance, creating many multibaggers
Section 1: Genesis of a multibagger Microstrategy
14 [email protected] 6 September 2017
Asia still producing a lot of multibaggers... Our analysis of returns over the past 15 years suggests that 21.2% of the broader Asia-Pacific ex-Japan companies with a market cap of more than US$100m have delivered returns of over 500%, while outperforming the relevant market index. A similar exercise for different time periods shows that Asia is still producing multibaggers. For example, over the past five years, 10.2% of companies have tripled and 22.6% have doubled while outperforming the relevant market returns. Even on a three-year basis, 4.2% of companies have tripled while 10.7% companies have doubled. While it is true that these multibaggers have now become concentrated in a few markets and sectors, Asia’s ability to deliver multibaggers remains strong.
Figure 5
APxJ: Hit rate of stocks becoming multibaggers (since 2000, quarterly rebalance)
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
. . . but the hit rate will come down given the market peak The ability to identify multibaggers is greater at a market bottom as a rising tide lifts all boats. In that respect, the current Asian market peak makes it harder to find future multibaggers. Investors will need to be more selective and focus on sustainable long-term structural stories rather than mean-reversion plays to identify multibaggers in the current market context.
Figure 6
APxJ: Negative correl between future multibagger hit rate and past market return
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
17.6
25.1
7.9
14.6 13.9
19.9
10.7
22.6
4.2
10.2
7.0
21.2
0
5
10
15
20
25
30
+100%in 3 yrs
+100%in 5 yrs
+200%in 3 yrs
+200%in 5 yrs
+500%in 10 yrs
+500%in 15 yrs
Double-baggers Triple-baggers Multibaggers
Quarterly average hit rate (since 2000)Latest hit rate
Hit rate of stocks becoming multibaggers (%)
Key multibagger indicator
5
10
15
20
25
30
(60)
(30)
0
30
60
90
120
150
180
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
Last 5-years return (US$ TR)Hit rate of stocks becoming triple-baggers in 5 years (RHS)
Hit rate (%)(%)
Correl: (0.66)
Markets up over the past fiveyears , multibaggers will be hard
to find over next five years
>200%
Some 21.2% of companies have delivered more than a 500% return
over the past 15 years
Inverse relation between future hit rate of
multibaggers and historical market return
In the past five years, 10.2% have tripled and
22.6% have doubled
Strong market returns over the past five years
will make it more difficult to find multibaggers
Section 1: Genesis of a multibagger Microstrategy
6 September 2017 [email protected] 15
Domestic demand-driven markets have a higher multibagger hit rate Markets with strong economic growth are naturally the best hunting grounds for multibaggers, since they have a significant advantage in terms of a growing market pie. However, companies residing outside these markets can also benefit from developing economies’ higher growth if they have the right product and strategy to expand overseas. Below we highlight the latest contribution of five-year triple-baggers from different markets in Asia-Pacific ex-Japan and also highlight the hit rate of finding these multibaggers across different markets.
Figure 7 Figure 8
APxJ markets: Hit rate of stocks becoming triple-bagger APxJ markets: Latest contribution to 5Y triple-baggers
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
India stands out in its consistency of generating multibaggers A study of the historical trends in generating multibaggers suggests that India has the most consistent track record along with the highest hit rate. Emerging Asean and China have also been a strong source of multibaggers but they have lagged in terms of their hit rate over the past five years. Among the historically low hit-rate markets, Taiwan and Australia are keeping pace with their historical averages, but Singapore, Hong Kong and Malaysia have witnessed a drop. Indeed, with Asian markets up significantly over the past five years, the hit rate of finding multibaggers could be even lower over the next five years.
Figure 9
APxJ markets - Hit rate of stocks becoming triple-baggers (+200%) in five years
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
0
5
10
15
20
25
30
IN ID PH CN TH KR APxJ MY HK SG AU TW
Quarterly average hit rate (since 2000)
Latest hit rate (+200% since 2012)
Hit rate of stocks becoming triple-baggers in 5 years (%)
India33%
China11%
Korea11%
Taiwan11%
Aust10%
HK7%
Thai5%
Indo3%
Malay3%
Others6%
Latest contribution of 5-year triple-baggers in APxJ region (%)
0
10
20
30
40
50
60
Dec
99
Jun
00
Dec
00
Jun
01
Dec
01
Jun
02
Dec
02
Jun
03
Dec
03
Jun
04
Dec
04
Jun
05
Dec
05
Jun
06
Dec
06
Jun
07
Dec
07
Jun
08
Dec
08
Jun
09
Dec
09
Jun
10
Dec
10
Jun
11
Dec
11
India China EM Asean
Hit rate of stocks becoming triple-baggers in 5 years (%)
India, emerging Asean and China have had the highest multibagger hit
rate since 2000
India’s hit rate of generating multibaggers
has been consistently strong
Both China and EM Asean have witnessed a drop in multibagger hit rate over
the past five years
Section 1: Genesis of a multibagger Microstrategy
16 [email protected] 6 September 2017
Cyclicals dominated pre-GFC, consumer thereafter The strong pre-GFC commodity cycle produced a number of multibaggers in the energy and materials sectors. However, the current economic conditions are very different given the volatile commodity prices. On the other hand, consumer and healthcare sectors have dominated since the GFC. Indeed, Asian healthcare has been the most consistent sector, given its current and long-term average hit rate of more than 20%. Also, consumer staples and discretionary sectors’ hit rates are higher than the market despite dropping against their long-term averages. Furthermore, the tech (infotech) sector is starting to deliver more multibaggers than its long-term average, especially given the emergence of Chinese internet stocks.
Figure 10 Figure 11
APxJ sectors: Hit rate of stocks becoming triple-baggers APxJ sectors: Latest contribution to 5Y triple-baggers
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
Healthcare a stand out, but infotech is in focus The healthcare sector has one of the highest hit rates of generating multibaggers, along with good consistency. However, the tech sector is enjoying a big increase in the hit rate. Looking forward, technology will remain a key focus area with artificial intelligence (AI) and robotics being prime growth prospects. Later in the report, we highlight some of the key ideas in this space from our fundamental analysts and thematic research.
Figure 12
APxJ sectors - Hit rate of stocks becoming triple-baggers in five years
Note: Only includes companies with at least US$100m market cap at the time of each rebalancing and the analysis does not have survivorship bias. Source: CLSA, Factset
0
5
10
15
20
25
Ener
gy
Con
s st
ap
Hea
lthca
re
Mat
eria
ls
Indu
stri
als
Con
s di
sc
APx
J
Fina
ncia
ls
Util
ities
Tele
com
Prop
erty
Info
tec
hQuarterly average hit rate (since 2000)Latest hit rate (+200% since 2012)
Hit rate of stocks becoming triple-baggers in 5 years (%)
Cons disc18%Cons
stap9%
Energy1%
Financials13%
H'care13%
Industrials12%
Info tech16%
Materials10%
Property5%
Telecom1%
Utilities2%
Latest contribution of 5-year triple-baggers in APxJ region (%)
0
2
4
6
8
10
12
14
16
18
20
5
10
15
20
25
30
Dec
99
Jun
00D
ec 0
0Ju
n 01
Dec
01
Jun
02D
ec 0
2Ju
n 03
Dec
03
Jun
04D
ec 0
4Ju
n 05
Dec
05
Jun
06D
ec 0
6Ju
n 07
Dec
07
Jun
08D
ec 0
8Ju
n 09
Dec
09
Jun
10D
ec 1
0Ju
n 11
Dec
11
Healthcare
Info tech (RHS)
Hit rate of stocks becoming triple-baggers in 5 years (%)
Avg for Healthcare: 20.5%
Avg for Info tech: 7.3%
Healthcare best place to find multibaggers, along
with consumer
Healthcare has consistently delivered
multibaggers
Tech sectors’ multibagger ability boosted by
smartphones proliferation and the internet sector
Section 1: Genesis of a multibagger Microstrategy
6 September 2017 [email protected] 17
Multibaggers over the past 15 years - large-caps In this screen, we highlight the large-cap stocks (market cap over US$5bn) with the highest returns over the past 15 years within Asian markets.
Figure 13
APxJ large-cap stocks with highest returns over the past 15 years (sorted by the return within each market) Code Name Cty Sector Mkt cap Return 12MF Trl 12MF L3Y FY1-FY2 FY1-FY2 NDE (US$m) (L15Y, PE PB div yld EPS Cagr EPS Cagr ROE (latest, %) (x) (x) (%) (%) (%) (avg, %) %) Australia FMG AU Fortescue AU Materials 14,446 93,142 12.1 1.5 4.6 (8.7) (24.6) 12.1 42.9 REA AU REA AU Media 7,058 58,513 30.0 10.7 1.7 15.1 22.3 31.6 16.7 CTX AU Caltex AU Energy 6,748 2,708 14.5 2.8 3.5 7.9 (0.4) 17.4 16.2 RHC AU Ramsay Healthcare AU Healthcare 12,027 2,545 25.1 6.8 2.1 17.1 10.7 25.5 140.5 CSL AU CSL AU Pharma 45,589 2,010 28.0 13.8 1.6 2.0 17.3 41.5 98.8 China NTES US NetEase CN Software 36,062 44,241 16.7 5.3 1.5 37.0 15.2 29.2 (82.1) 1177 HK Sino Biopharm CN Pharma 6,167 9,220 20.8 4.8 0.9 22.6 12.2 22.1 (53.5) SINA US Sina CN Software 7,087 6,238 28.3 2.4 0.0 8.4 63.0 7.0 (59.8) 688 HK Coli CN Property 35,704 5,156 7.4 1.2 3.6 16.2 (0.5) 15.0 8.1 257 HK Everbright Intl CN Comm svcs 6,038 4,861 11.9 2.4 2.8 24.0 23.0 18.9 80.9 Hong Kong 27 HK Galaxy HK Cons svcs 25,821 11,012 22.8 4.1 1.3 (15.6) 21.0 16.7 (29.8) 316 HK OOIL HK Transport 5,758 5,770 27.2 1.2 1.0 nm nm 4.4 45.9 388 HK HK Exchanges HK Div fin 32,669 3,438 33.7 7.6 2.7 6.4 16.4 22.1 nm 1031 HK Kingston Financial HK Div fin 6,591 2,406 nm nm na 10.3 na na nm JS SP Jardine Strategic HK Cap gds 25,071 2,009 14.8 1.0 0.8 (2.6) 10.8 6.0 20.4 India BAF IN Bajaj Finance IN Div fin 14,430 51,688 32.6 8.2 0.3 32.8 36.1 25.0 nm EIM IN Eicher Motors IN Cap gds 13,383 50,161 35.1 14.5 0.5 61.5 28.8 36.9 (16.2) SRCM IN Shree Cement IN Materials 9,308 42,315 30.7 7.2 0.3 10.0 31.0 21.5 7.3 MSS IN Motherson Sumi IN Autos 10,513 39,742 26.7 7.6 1.1 27.9 30.9 26.6 73.8 HZ IN Hindustan Zinc IN Materials 19,182 22,520 12.4 3.7 2.5 6.1 12.4 27.0 (78.7) Indonesia UNTR IJ United Tractors ID Energy 8,075 15,254 13.9 2.5 2.9 1.1 26.8 16.7 (41.3) KLBF IJ Kalbe Farma ID Pharma 6,180 5,510 30.1 6.4 1.6 6.2 11.0 18.9 (26.1) BBCA IJ BCA ID Banks 34,719 5,178 18.7 3.8 1.3 13.0 11.8 18.7 nm HMSP IJ HM Sampoerna ID FBT 31,278 4,794 30.2 11.9 3.0 3.9 5.3 38.3 (35.2) ASII IJ Astra Intl ID Autos 23,880 4,607 14.9 2.6 3.0 (8.0) 21.1 16.9 39.3 Korea 010130 KS Korea Zinc KR Materials 7,775 3,035 12.6 1.6 1.9 9.8 10.4 12.0 (31.2) 051900 KS LG H&H KR HPC 14,154 2,800 22.6 5.5 0.9 16.7 14.3 22.2 16.6 018880 KS Hanon Systems KR Autos 5,390 2,013 17.7 3.3 2.6 (0.5) 12.0 17.3 10.0 011170 KS Lotte Chemical KR Materials 11,813 1,725 6.4 1.3 1.0 85.4 5.5 19.0 10.3 002790 KS Amorepacific Group KR HPC 9,142 1,516 33.2 2.7 0.4 29.5 (1.6) 10.9 (47.3) Malaysia HAP MK Hap Seng Cons MY Cap gds 5,244 3,294 nm nm na 13.9 na na 48.9 DIGI MK Digi MY Telecom 8,778 2,984 24.2 70.1 4.1 (1.4) (2.4) 286.4 405.4 PETD MK Petronas Dagangan MY Energy 5,562 1,680 24.4 4.3 3.1 5.2 2.0 17.1 (42.2) PEP MK PPB MY FBT 4,607 1,359 18.0 0.9 1.6 1.7 3.5 5.1 (3.5) PBK MK Public Bank MY Banks 18,537 1,040 14.7 2.2 3.0 6.2 2.9 14.6 nm Philippines URC PM URC PH FBT 6,422 7,121 25.6 nm 2.0 14.7 na 15.9 41.9 JGS PM JG Summit PH Cap gds 9,724 5,514 16.5 2.0 0.3 29.0 1.0 11.5 57.2 AEV PM AEV PH Cap gds 8,011 5,314 16.1 3.0 2.4 1.8 8.7 17.2 136.1 MER PM Meralco PH Utilities 6,073 1,576 16.4 4.2 5.5 4.3 (1.4) 25.6 (17.0) TEL PM PLDT PH Telecom 7,269 1,296 17.1 3.3 3.6 (10.4) (12.3) 19.1 106.3 Singapore SGX SP SGX SG Div fin 5,873 1,404 21.4 7.7 4.1 (0.2) 3.2 34.5 nm GENS SP Genting Singapore SG Cons svcs 10,471 595 22.5 1.7 2.6 (22.9) 58.1 7.9 (47.6) KEP SP Keppel Corp SG Cap gds 8,335 530 12.6 0.9 3.6 (18.1) 9.5 7.1 58.9 CT SP CapitaMall Trust SG Property 5,523 471 18.4 1.1 5.3 4.2 1.3 6.0 40.5 CAPL SP CapitaLand SG Property 11,642 425 17.7 0.9 2.8 16.5 6.6 5.8 54.4 Taiwan 3008 TT Largan TW Tech HW 24,622 6,221 20.2 8.3 1.7 33.4 34.3 35.1 (85.1) 2474 TT Catcher Tech TW Tech HW 9,440 3,498 10.8 2.1 3.1 16.4 13.9 18.4 (48.0) 2207 TT Hotai Motor TW Retail 6,143 2,366 nm 4.2 na 12.0 na na 198.1 1216 TT Uni-President TW FBT 11,189 1,336 20.8 3.2 3.8 4.3 7.1 13.8 36.5 2395 TT Advantech TW Tech HW 5,101 1,003 23.0 5.8 3.0 10.8 11.5 24.4 (34.8) Thailand BDMS TB Bangkok Dusit TH Healthcare 9,266 8,016 34.7 5.3 1.5 10.8 3.6 15.0 60.2 MINT TB Minor International TH Cons svcs 5,137 4,203 27.2 4.1 1.1 16.3 (0.1) 14.3 132.8 CPN TB CPN TH Property 9,106 3,310 25.9 5.4 1.5 13.2 16.2 18.9 32.0 BJC TB Berli Jucker TH Cap gds 5,399 1,812 27.3 1.7 1.6 3.6 6.6 6.0 145.6 PTT TB PTT TH Energy 33,741 1,757 10.3 1.3 4.2 (0.4) 8.3 12.5 26.0
Note: Universe is broader Asia Pacific ex-Japan companies with market cap over US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Total return is based on local currency. Source: Factset, CLSA
Section 1: Genesis of a multibagger Microstrategy
18 [email protected] 6 September 2017
Multibaggers over the past five years - large-caps Similar to the previous screen, we highlight large-cap stocks (market cap over US$5bn) with the highest returns over the past five years within Asian markets.
Figure 14
APxJ large-cap stocks with highest returns over the past five years (sorted by the return within each market) Code Name Cty Sector Mkt cap Return 12MF Trl 12MF L3Y FY1-FY2 FY1-FY2 NDE (US$m) (L5Y, PE PB div yld EPS Cagr EPS Cagr ROE (latest, %) (x) (x) (%) (%) (%) (avg, %) %) Australia ALL AU Aristocrat AU Cons svcs 10,724 833 21.6 10.5 2.1 60.0 16.1 44.0 66.5 BSL AU BlueScope AU Materials 5,026 437 10.2 1.2 1.2 78.0 (3.5) 10.2 10.8 QAN AU Qantas AU Transport 8,339 419 10.1 2.8 2.9 nm 9.8 25.7 88.9 REA AU REA AU Media 7,058 359 30.0 10.7 1.7 15.1 22.3 31.6 16.7 MQG AU Macquarie AU Div fin 22,301 338 13.0 1.9 5.6 11.0 4.2 14.5 nm China 2382 HK Sunny Optical CN Tech HW 14,944 3,249 31.4 15.7 0.8 38.6 65.3 41.7 (16.2) XRS US TAL Edu CN Cons svcs 8,689 2,107 69.2 21.4 0.0 14.9 58.3 31.4 (102.5) 285 HK BYD Electronic CN Tech HW 6,047 1,171 17.5 3.1 0.8 23.8 40.1 16.9 (27.3) HTHT US China Lodging CN Cons svcs 7,770 714 34.8 8.6 0.4 36.3 44.6 21.6 (37.3) 2020 HK Anta Sports CN Cons dur 10,409 676 20.5 5.6 3.5 21.9 18.1 26.3 (77.6) Hong Kong 607 HK Fullshare HK Property 7,967 567 28.3 nm 0.0 nm na na (5.0) 1031 HK Kingston Financial HK Div fin 6,591 357 nm nm na 10.3 na na nm 669 HK Techtronic HK Cons dur 8,974 266 17.0 3.4 1.8 17.7 17.0 18.7 7.3 1910 HK Samsonite HK Cons dur 5,481 141 18.5 3.5 2.2 13.1 10.7 17.8 102.7 1299 HK AIA HK Insurance 89,171 136 17.2 2.4 1.9 16.7 14.5 13.4 nm India BAF IN Bajaj Finance IN Div fin 14,430 1,630 32.6 8.2 0.3 32.8 36.1 25.0 nm EIM IN Eicher Motors IN Cap gds 13,383 1,345 35.1 14.5 0.5 61.5 28.8 36.9 (16.2) ARBP IN Aurobindo Pharma IN Pharma 6,355 1,246 14.9 3.9 0.5 25.1 12.0 23.0 19.3 IHFL IN Indiabulls HFC IN Banks 7,935 811 13.0 4.0 3.7 12.7 22.6 28.2 nm BRIT IN Britannia Industries IN FBT 7,932 806 45.6 17.1 0.7 30.7 18.3 33.9 (6.7) Indonesia TLKM IJ Telkom ID Telecom 35,394 198 18.4 5.2 3.6 10.0 17.2 26.2 16.8 ICBP IJ ICBP ID FBT 7,578 177 24.5 5.4 1.9 17.4 8.7 21.1 (35.6) BBCA IJ BCA ID Banks 34,719 157 18.7 3.8 1.3 13.0 11.8 18.7 nm BBRI IJ BRI ID Banks 27,972 138 12.1 2.4 2.8 7.4 11.0 18.4 nm KLBF IJ Kalbe Farma ID Pharma 6,180 134 30.1 6.4 1.6 6.2 11.0 18.9 (26.1) Korea 000660 KS SK Hynix KR Semis 41,659 224 4.8 1.6 1.7 1.1 83.0 31.0 (1.5) 002790 KS Amorepacific Group KR HPC 9,142 216 33.2 2.7 0.4 29.5 (1.6) 10.9 (47.3) 021240 KS Coway KR Cons dur 6,197 207 18.7 5.9 3.8 (0.1) 27.9 30.3 51.0 018880 KS Hanon Systems KR Autos 5,390 183 17.7 3.3 2.6 (0.5) 12.0 17.3 10.0 090430 KS Amorepacific KR HPC 16,959 168 28.2 4.5 0.7 33.6 7.8 13.8 (20.9) Malaysia HAP MK Hap Seng Cons MY Cap gds 5,244 615 nm nm na 13.9 na na 48.9 TNB MK Tenaga MY Utilities 18,771 138 10.9 1.4 3.7 18.3 (2.3) 12.8 47.6 GENM MK Genting Malaysia MY Cons svcs 8,352 100 18.5 1.7 1.7 (1.9) 11.5 8.7 (0.2) IHH MK IHH MY Healthcare 11,579 96 43.5 2.2 0.7 9.5 19.1 4.8 19.7 MISC MK MISC MY Transport 7,455 85 14.8 0.8 3.8 7.4 (8.0) 5.5 16.2 Philippines URC PM URC PH FBT 6,422 176 25.6 nm 2.0 14.7 na 15.9 41.9 SMPH PM SM Prime PH Property 19,326 164 33.1 4.0 0.9 9.9 14.5 11.7 62.2 BDO PM BDO PH Banks 11,046 144 17.3 2.0 1.0 6.1 6.1 11.4 nm GLO PM Globe Telecom PH Telecom 5,288 134 18.0 4.2 4.3 11.3 (2.1) 23.1 174.9 SM PM SM Investments PH Cap gds 19,372 130 25.7 3.2 1.3 3.7 14.2 11.7 90.0 Singapore AVGO US Broadcom SG Semis 101,347 668 14.8 4.8 2.2 58.2 22.3 28.4 46.9 FLEX US Flextronics SG Tech HW 8,272 138 12.7 2.9 0.0 9.5 9.7 20.6 50.4 DBS SP DBS SG Banks 38,483 66 10.4 1.1 3.3 3.3 11.0 10.5 nm GLP SP GLP SG Property 11,150 54 32.1 1.3 2.1 4.3 17.2 4.8 54.9 AREIT SP Ascendas SG Property 5,699 53 15.8 1.3 6.1 3.7 3.0 7.7 52.7 Taiwan 3008 TT Largan TW Tech HW 24,622 949 20.2 8.3 1.7 33.4 34.3 35.1 (85.1) 2408 TT Nanya Technology TW Semis 5,701 313 9.0 1.8 4.2 37.9 (8.9) 18.9 11.3 4938 TT Pegatron TW Tech HW 7,762 222 9.7 1.5 6.2 25.7 15.1 15.0 (58.1) 2330 TT TSMC TW Semis 180,895 208 14.9 3.7 3.7 21.1 7.0 23.3 (31.9) 2395 TT Advantech TW Tech HW 5,101 203 23.0 5.8 3.0 10.8 11.5 24.4 (34.8) Thailand AOT TB Airports of Thailand TH Transport 22,007 772 30.0 5.5 1.6 6.2 12.3 17.4 (29.2) THBEV SP ThaiBev TH FBT 16,884 224 19.3 nm 3.3 (0.4) na 22.2 31.2 MINT TB Minor International TH Cons svcs 5,137 192 27.2 4.1 1.1 16.3 (0.1) 14.3 132.8 CPN TB CPN TH Property 9,106 176 25.9 5.4 1.5 13.2 16.2 18.9 32.0 BDMS TB Bangkok Dusit TH Healthcare 9,266 112 34.7 5.3 1.5 10.8 3.6 15.0 60.2
Note: Universe is broader Asia Pacific ex-Japan companies with market cap over US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Total return is based on local currency. Source: Factset, CLSA
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 19
A multibagger framework Below we present a framework to identify multibagger characteristics. Our backtests and characteristics analysis show that companies that operate in growth markets/sectors with leading products (including brands) and good management are most likely to be multibaggers. This forms the core of our strategy to pick multibaggers. Apart from the historical track record, we rely on the consensus earnings forecast after passing them through our quantitative framework to ensure that we are focusing on companies in the right markets and sectors. Since identifying futuristic products is beyond the scope of quantitative studies, we utilise the work done by our fundamental analysts in the thematic space to capture some tech-driven product ideas as summarised on page 65.
Figure 15
Microstrategy: Multibagger framework - influencing drivers
Source: CLSA
In terms of product superiority, R&D spending for companies in the tech and healthcare sectors, branding spend in the case of consumer products and channel building in B2B industries is increasingly becoming the most relevant factor, along with the ability to expand overseas. We further examine these issues in our characteristics study of Asian multibaggers.
Also, while earnings growth is the ultimate driver of long-term returns, good stocks can remain depressed due to corporate-governance issues. Hence, management quality and track record are also important for investors to judge whether a company can deliver earnings growth on a sustained basis rather than being just a temporary success. This is particularly true in the context of Asia, where corporate governance has been a big concern and short-sellers have been targeting companies in markets such as Hong Kong. Hence, we have utilised our risk scores, including Benford scores (a test of fraudulent accounts) to assess the risk of potential multibaggers turning out to be disappointments through our Red flags framework.
Multi-baggers
Market
Sector(product)
Product superiority (R&D vs capex)
Branding & channel building (SG&A)
Overseas expansion
Manage-ment
quality
A quantitative framework to capture qualitative
characteristics
R&D and SG&A spending becoming increasingly
important
Section 2: A multibagger framework Microstrategy
20 [email protected] 6 September 2017
R&D: A key differentiator in knowledge driven industries Research and development (R&D) expenditure has a direct impact on profitability because it cannot be capitalised. However, it remains a key source of long-term competitive advantage for companies in the knowledge-driven industries. Asia’s obsession with capex in the past has been well documented but we are witnessing a significant change in attitude towards R&D spending with the R&D-to-capex ratio rising consistently since 2008. While Asian R&D spend still has to catch up with global norms, it doubled from 0.9% of sales in 2008 to around 1.9% by the end of 2016. After being led by Japan for many years, the USA has become the global R&D leader (3.0%), improving consistently since the trough in 2005. Europe’s ratio has been steady with a range of 1.5-2.5%. However, Asia is on the brink of breaking through the 2% mark at the index level.
Figure 16 Figure 17
MSCI regions (ex-fin): R&D as a percentage of sales MSCI AsiaxJ (ex-fin): R&D versus capex
Note: Ratios are bottom-up aggregated with freefloat adjustment based on current MSCI universe. Source: CLSA, Factset
Rise of R&D has been broadbased The rise of R&D spending is not limited to just the large-cap index companies. Data for the broader sphere of Asia Pacific ex-Japan firms show that the median R&D-to-sales ratio has been on a steady rise since 2008, growing from 0.8% to close to 2% in 2016, based on data for over 1,800 companies.
Figure 18
Broader APxJ (ex-fin): Median FY0 R&D to sales ratio
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
3.0
2.7
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R&D as a % of sales
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Broader APxJ universe (median FY0 R&D to sales ratio)(%)
Median R&D to sales ratio has moved close to 2%
Data for over 1,800 companies with market
cap more than US$100m
Asian R&D as a percentage of sales has
doubled since the trough in 2008
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 21
R&D spend rising for most knowledge-driven industries R&D spending has been on the rise for most knowledge-driven industries. Indeed, our analysis shows that out of the top-10 industries based on R&D spend as a percentage of sales, the ratio is at a 15-year peak for seven of them. We believe that these R&D-driven sectors will remain a rich source of multibaggers, given their focus on product superiority and their ability to deliver products that will provide sustainable competitive advantage. It is particularly interesting to note that for several industries the R&D spend as a percentage of sales has more than doubled. In the case of pharma, the ratio has increased by 4.4x, highlighting that Asia is increasingly investing in developing inhouse competitive advantages.
Figure 19
Median FY0 R&D to sales ratio for major APxJ industries
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
R&D growth still strong in a number of sectors Given the low-growth environment last year, Asian companies did dial back their R&D spending. Yet some R&D-heavy industries witnessed strong growth, led by internet, biotech, healthcare equipment/services and pharma. Also, a few other industries such as defence, personal/leisure products, autos and autoparts also saw strong R&D growth.
Figure 20
Median FY0 R&D growth for relevant APxJ industries
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
Biotech Software Internet Healthcare Equip & svcs
Communica-tions equip
Semis Pharma Tech hardware Electronic instruments
Auto componenets
0
5
10
15
20
25
30
Bio
tech
Pers
pro
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Aer
o&de
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hw
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Elec
equ
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FY0 R&D growth (%)
R&D spending at peak levels for majority of the
top-10 industries
While R&D growth was dialed back to 5% last
year, capex growth was negative
R&D to sales ratio for pharma sector has
increased from 0.9% to 3.9%
Biotech, personal product, defence, internet and
healthcare leading R&D growth
Section 2: A multibagger framework Microstrategy
22 [email protected] 6 September 2017
Multibaggers have higher R&D spend To further understand the impact of R&D spend policy on returns, we selected the top-15 industries based on the highest R&D-to-sales ratio and compared the R&D-to-sales ratio of the multibaggers to that of the overall industry. In the majority of cases, the multibaggers basket had a higher median R&D-to-sales ratio than the overall industry. The difference in R&D spending of multibaggers versus the rest is most clear in the case of various tech-related industries. Among nontech industries, personal products, defence and healthcare sectors are the standouts.
Figure 21
Broader APxJ (ex-fin): FY0 R&D spend of multibaggers relative to industry
Note: Broader APxJ companies with market cap of more than US$100m. R&D spending data based on industry median. Source: CLSA, Factset
R&D spend higher for multibaggers in most industries Figure 22
Broader APxJ industries: FY0 R&D spend of multibaggers relative to industry versus the industry
Note: Broader APxJ companies with market cap of more than US$100m. The bubble size represents the count of companies with FY0 R&D to sales data. Source: CLSA, Factset
0
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Multibaggers rel to industry (avg 2000-12)Current - FY0 R&D to sales (RHS)
(x) (%)
Multibaggers have much higher R&D spending in most relevant industries
17
Tech hw
Pers prodSemis
Aero&def
Oil&Gas
H'care E&SElec I&CPharma
Comm equip
Machinery
Autoparts
Autos
H'hold durElec equip
IT Services
Chemicals
Bldg prod
Tex/app/lux
Met & min
MediaCont & pkg
Const & engg
Food prod
Ind conglos
Paper
Cement
Hotels
0.4
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0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
Median R&D/sales (FY0, %)
Multibaggers rel to industry (avg 2000-12, %)
Biotech (16.9, 1.2, 51)
Software (11.8, 1.7, 49)
Internet (7.9, 1.5, 30)
Multibaggers had higher R&D spend for majority of
the top-15 industries
R&D spend has been a key differentiating factor
for the tech sector
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 23
Asian small-/midcaps with high and rising R&D intensity Our analysis has shown that multibaggers in various industries feature significantly higher R&D intensity. R&D spending will continue to be a key differentiator, given the advent of new technologies such as robotics and AI. Keeping this in mind, we highlight a list of Asian small- to midcap companies (market cap between US$100m to US$5bn) that have the highest R&D intensity along with robust R&D growth:
Figure 23
Asian small-/midcap companies with high R&D-to-sales ratio and strong R&D growth (sorted by R&D to sales ratio) Code Name Cty Sector Mkt cap R&D to sales (%) R&D growth (%) FY1-FY2 EPS 12M fwd
(US$m) FY-2 FY-1 FY0 FY-1 FY0 L5Y Cagr Cagr (%) PE (x) SPADV IN Sun Pharma Adv IN Pharma 1,501 122.5 139.2 168.4 17.6 35.8 na na nm 3529 TT eMemory Tech TW Semis 1,015 31.1 31.2 34.6 9.2 23.2 13.2 31.0 37.6 2379 TT Realtek TW Semis 1,849 25.1 28.0 27.5 13.3 20.1 19.7 12.9 15.2 777 HK Netdragon CN Software 1,505 25.9 35.1 27.2 79.0 70.3 36.7 nm nm 6462 TT Egis Tech TW Tech HW 618 329.4 50.2 23.2 79.2 44.9 36.6 280.4 14.1 XRO NZ Xero NZ Software 2,689 25.2 22.5 20.0 48.9 27.2 na nm nm 4947 TT On-Bright Elec CN Semis 373 16.3 18.2 18.0 18.8 14.1 27.8 6.7 13.2 SIMO US Silicon Motion TW Semis 1,467 21.1 19.7 16.6 16.8 29.9 17.9 (1.9) 12.9 1302 HK LifeTech Sci CN Healthcare 950 11.8 15.2 16.3 41.8 21.8 20.4 68.3 35.8 4966 TT Parade Tech TW Semis 1,131 11.8 14.3 15.7 40.8 38.9 34.9 21.1 17.6 6510 TT Chunghwa Precision TW Tech HW 1,330 10.1 10.8 14.2 73.5 96.9 na 43.0 35.7 NAN AU Nanosonics AU Healthcare 558 22.1 17.1 14.1 48.9 30.0 24.8 53.0 29.6 5490 TT XAC Automation TW Tech HW 189 14.7 10.4 14.0 18.5 15.1 13.2 na nm 3454 TT Vivotek Inc TW Tech HW 257 13.1 13.4 13.3 15.2 15.3 16.1 na nm 205100 KS EXEM KR Software 132 na 8.5 11.8 na 85.5 na na nm 877 HK O-Net CN Tech HW 464 12.7 11.9 11.8 27.5 39.0 31.1 51.5 13.1 8002 HK IGG SG Software 2,132 8.4 13.3 11.2 56.6 33.5 46.6 72.6 10.7 098460 KS Koh Young Tech KR Semis 726 7.0 9.5 10.8 39.1 34.2 26.0 17.1 21.5 4968 TT Richwave Tech TW Semis 204 11.1 11.0 10.6 23.2 21.3 3.6 51.2 21.2 5274 TT ASPEED Tech TW Semis 789 13.0 12.1 10.6 7.6 18.8 18.8 38.7 29.8
Note: Universe is broader Asia Pacific ex-Japan companies with market cap between US$100m to US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Asian large-cap companies leading the R&D effort While the broader Asian list contains a number of small-cap companies, we also provide a list of top-10 R&D leaders in Asia based on their actual dollar spending last year. While large-cap companies have a natural disadvantage in terms of their size when it comes to becoming multibaggers, these R&D leaders will remain strong performers, given their investment in developing competitive advantage through R&D spend.
Figure 24
Top 10 Asian companies with the highest R&D dollar-amount (sorted by R&D dollar amount) Code Name Cty Sector Mkt cap R&D amount (US$m) R&D/sales R&D gr FY1-FY2 EPS 12M fwd
(US$m) FY-2 FY-1 FY0 (FY0, %) (FY0, %) Cagr (%) PE (x) 005930 KS Samsung Electronics KR Tech HW 283,600 12,845 12,238 12,601 7.0 3.0 43.7 7.5 AVGO US Broadcom SG Semis 101,347 695 1,049 2,674 20.2 154.9 22.3 14.8 BABA US Alibaba CN Software 428,095 1,607 2,079 2,572 10.8 23.7 35.2 30.6 2330 TT TSMC TW Semis 180,895 1,884 2,173 2,361 7.5 8.6 7.0 14.9 2454 TT MediaTek TW Semis 14,120 1,437 1,642 1,846 20.2 12.4 1.7 19.2 700 HK Tencent CN Software 394,835 1,047 1,255 1,786 7.8 42.4 39.5 35.8 763 HK ZTE CN Tech HW 13,681 1,247 1,707 1,776 11.6 4.0 nm 14.7 2317 TT Hon Hai TW Tech HW 65,724 1,620 1,740 1,696 1.2 (2.6) 10.3 11.6 390 HK China Railway CN Cap gds 27,113 1,464 1,550 1,571 1.6 1.3 13.6 7.8 BIDU US Baidu CN Software 61,015 1,053 1,534 1,530 14.4 (0.2) 24.5 27.0
Note: Universe is broader Asia Pacific ex-Japan companies with market cap over US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Companies with high R&D to sales and
robust R&D growth
R&D leaders in Asia based on actual dollar spending
Section 2: A multibagger framework Microstrategy
24 [email protected] 6 September 2017
Branding & channel building: Asia lags developed markets While Asia might be catching up on its R&D effort, it still lags significantly when it comes to brand and sales-related spending. In the top-100 global brands by interbrand.com only five belong to the Asia Pacific ex-Japan region. In a similar study by WPP/BrandZ (http://www.brandz.com), only 15 are from this region, including China financials. Given the lack of explicit reporting of the brand and channel-building expenses, we use SG&A (selling, general and administrative) expense as a proxy. Indeed, Asia ex-Japan’s SG&A spend (ex-R&D) as a percentage of sales was just 10.0% last year, much lower than the 15.1% by the USA and well behind other developed markets. On a more positive note, SG&A spending growth has been strong, with the SG&A-to-sales ratio rising consistently since 2011 and a significant increase in the SG&A spending growth last year.
Figure 25 Figure 26
MSCI regions (ex-fin): SG&A (ex-R&D) as a % of sales MSCI AsiaxJ (ex-fin): SG&A (ex-R&D) growth
Note: Ratios are bottom-up aggregated with freefloat adjustment based on current MSCI universe. Source: CLSA, Factset
Asian companies starting to focus on brand and channel building Asian companies are slowly but surely realising the power of building strong brands and sales networks as highlighted by the broadbased increase in the SG&A-to-sales ratio. Data for the broader Asia Pacific ex-Japan universe show that the median SG&A-to-sales ratio has been on a steady rise since 2012, reaching over 13% in 2016, based on data for over 4,200 companies.
Figure 27
Broader APxJ (ex-fin): Median FY0 SG&A (ex-R&D) to sales ratio
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
15.1
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Broader APxJ universe (median FY0 SG&A (ex-R&D) to sales ratio)(%)
Median SG&A to sales ratio has moved
beyond 13%
Data for over 4,200 companies with market
cap more than US$100m
Asia’s SG&A to sales ratio is far below the developed
markets such as USA
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 25
SG&A spend rising for a number of industries SG&A spending has been on the rise for many Asian industries. While the increase is not consistent as in the R&D space, it is still high for a number of important industries such as software and consumer-discretionary sectors. We believe that industries with high SG&A spending will remain a rich source of multibaggers, given their focus on product superiority and sustainable competitive advantage through brand or channel building. It is particular interesting to note that for several industries, the SG&A (ex-R&D) spend as a percentage of sales has increased by more than 40%. For example, in the case of software, the ratio has risen from around 20% to almost 45%, highlighting the increased investment in brand building.
Figure 28
APxJ industries with high SG&A spend: Median FY0 SG&A (ex-R&D) to sales ratio
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
SG&A growth strong in a number of sectors Despite the weak capex growth, SG&A growth has been robust in a number of Asian industries. For example, the high SG&A growth in the ecommerce and personal-products spaces highlights the focus on capturing consumer mind-share. Other sectors with high SG&A growth include biotech, professional services, internet and healthcare.
Figure 29
Broader APxJ industries with the highest median FY0 SG&A growth
Note: Broader APxJ companies with market cap of more than US$100m. SG&A data including R&D. Source: CLSA, Factset
Professional services Software Biotech Internet
softwareDiv consumer
services
Leisure products Multi-line retail Speciality retail Personal
products Beverages
02468
101214161820
Bio
tech
e-co
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Pers
pro
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H'c
are
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FY0 SG&A growth (%)27
SG&A spending rising in software and consumer-
discretionary sectors
New-economy and consumer-related sectors
witnessed the highest growth in SG&A spend
SG&A spend ratio on an uptrend for seven out of
the top-10 industries with high SG&A spend
Ecommerce, personal products and internet
witnessed growth of more than 15% last year
Section 2: A multibagger framework Microstrategy
26 [email protected] 6 September 2017
Multibaggers have higher SG&A spend in a number of industries To further understand the impact of SG&A spending on returns, we selected all the industries with SG&A-to-sales higher than 8% and compared the SG&A-to-sales ratio of the multibaggers to that of the overall industry. In 26 out of 46 industries, the multibaggers basket had a higher median ratio than the overall industry. Data show that SG&A spending matters not only in the consumer-driven industries but also in many of the industries that also had higher R&D spending. The fact that SG&A is only a proxy for brand and channel-building spend may have brought some irrelevant industries into the fray. However, overall spending under the SG&A head still seems to be an important factor when it comes to identifying multibaggers.
Figure 30
Broader APxJ (ex-fin): FY0 SG&A (ex-R&D) spend of multibaggers vs industry
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
SG&A spend higher for multibaggers in most industries Figure 31
Broader APxJ industries: FY0 SG&A spend of multibaggers relative to industry versus the industry
Note: Broader APxJ companies with market cap of more than US$100m. The bubble size represents the count of companies with FY0 SG&A (ex-R&D) to sales data. Source: CLSA, Factset
51015202530354045
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els
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hine
ry
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os
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g pr
od
Multibaggers rel to industry (avg 2000-12)Current FY0 SG&A (ex-R&D) to sales (RHS)
(x) (%)
Multibaggers have much higher SG&A spending in many relevant industries
1.73
Elec equip
AirlinesPaper
Energy E&S CementMulti-retailTech hw
Media
Food prod
Auto partsIT Services
Elec I&C
Tex/app/lux
TobaccoH'hold dur
DevelopersHotels
MachineryAutos
Bldg prodComm svc Wireless tel Pharma Spec retail
Pers prodH'care prov
H'care E&S
DistributorsBeverages
Fd/stp ret e-commInd conglos
Cont & pkg Div telecomRoad/rail AirFt&Log
IPPs
Oil&Gas
Trans infra
Chemicals
Semis
Met & min
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7 9 11 13 15 17 19 21 23 25 27
Median SG&A (ex-R&D)/sales (FY0, %)
Multi-baggers rel to industry (avg 2000-12, %)Aero&def
(8.2, 1.6, 15)
Internet (36.3, 0.7, 51)Leis prod (27.2, 0.5, 16)
Div cons svc (35.6, 1.4, 34)Software (44.5, 1.3, 86)
Comm equip (11.3, 1.7, 52)
Biotech (43.2, 1.1, 54)
Prof svc (52.6, 0.9, 16)
TradingCos (7.2, 0.6, 46)
Multibaggers had higher SG&A spend in 26 out of
46 industries
SG&A spend encompasses expenses beyond just
those related to advertisement spend
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 27
Asian small/midcaps with high and rising SG&A intensity Our analysis has shown that multibaggers in various industries feature a significantly higher SG&A-to-sales ratio. SG&A spending is on the rise in Asia and will continue to be a key differentiator, given the focus on consumption-led growth. Keeping this in mind, we highlight a list of broader Asian small-to-midcap companies that have the highest SG&A-to-sales ratio, along with robust SG&A growth.
Figure 32
Asian Small/mid-caps with high SG&A (ex-R&D)-to-sales ratio and strong SG&A growth (sorted by SG&A/sales) Code Name Cty Sector Mkt cap
(US$m) SG&A (ex-R&D)
to sales (%) SG&A (ex-R&D) growth
(%) FY1-FY2
EPS Cagr 12M fwd
PE (x)
FY-2 FY-1 FY0 FY-1 FY0 L5Y Cagr (%) 194510 KS Pati Games KR Software 112 73.9 96.5 97.1 23.3 34.4 na na nm 039130 KS Hana Tour KR Cons svcs 808 87.5 88.1 93.5 20.0 37.6 18.8 141.5 23.1 EHE AU Estia Health AU Healthcare 549 77.4 80.3 83.5 61.3 23.2 na 2.8 17.6 MMYT US MakeMyTrip IN Retail 3,096 46.9 64.9 83.2 54.9 70.8 37.0 nm nm JHC AU Japara Healthcare AU Healthcare 406 83.5 82.8 83.0 470.1 17.3 na 6.0 16.2 8158 HK Regenerative Medicine HK Pharma 481 3,640 742 81.9 100.9 41.8 39.7 na nm MTCL IN MindTree IN Software 1,210 68.0 70.3 75.3 35.6 20.1 21.3 15.9 15.2 060280 KS CUREXO KR Healthcare 284 47.2 69.1 74.6 54.4 17.9 22.1 na nm 089600 KS Nasmedia KR Media 386 69.9 71.3 74.3 55.4 60.2 31.0 48.3 17.1 PSYS IN Persistent Systems IN Software 780 74.5 77.2 74.0 26.7 19.2 23.3 11.2 14.1 PRG AU Programmed Maintenance AU Comm svcs 613 61.2 68.0 73.1 71.2 30.9 16.9 8.0 16.7 016170 KS Loen Entertainment KR Media 1,839 73.0 73.1 71.2 10.8 22.8 20.8 25.3 22.5 CTD AU Corporate Travel AU Cons svcs 1,825 75.9 74.6 70.5 29.6 17.5 36.6 19.0 28.3 192080 KS DoubleUGames KR Software 750 56.8 69.5 65.5 110.4 19.8 na 57.4 9.0 060240 KS LONGTU KOREA KR Cons svcs 141 95.5 91.5 64.1 13.7 225.7 16.0 na nm 1707 TT Grape King TW HPC 809 61.7 61.7 60.6 15.4 24.4 18.3 17.1 14.8 IPH AU IPH AU Comm svcs 690 52.4 57.0 59.1 89.6 22.2 na 10.8 15.0 RFMD SP Raffles Medical SG Healthcare 1,457 50.9 52.3 54.0 12.5 19.3 12.8 0.0 28.0 WEB AU Webjet AU Retail 908 49.6 51.6 52.5 27.6 32.0 33.2 30.9 20.2 078340 KS Com2us KR Software 1,232 43.4 51.0 52.2 117.3 20.9 80.3 8.8 8.3 Note: Universe is broader Asia Pacific ex-Japan companies with market cap between US$100m to US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Asian large-cap companies leading the SG&A effort While the broader Asian list contains a number of small-cap companies, we also provide a list of the top-10 SG&A-leaders in Asia based on their actual dollar spending last year. While large-cap companies have a natural disadvantage in terms of their size when it comes to becoming multibaggers, these brand or channel leaders will remain strong performers, given their investment in developing a competitive advantage through brand building.
Figure 33
Top 10 Asian companies with the highest SG&A (ex-R&D) dollar-amount (sorted by SG&A dollar amount) Code Name Cty Sector Mkt cap SG&A (ex-R&D) SG&A (ex- SG&A (ex- FY1-FY2 12M (US$m) amount (US$m) R&D) to sales R&D) gr (EPS fwd PE
FY-2 FY-1 FY0 (FY0, %) (FY0, %) Cagr, %) (x) 005930 KS Samsung Electronics KR Tech HW 283,600 33,437 32,219 33,249 18.4 3.2 43.7 7.5 TTMT IN Tata Motors IN Autos 19,986 10,651 12,733 12,221 29.0 (4.0) 53.0 10.6 WES AU Wesfarmers AU Fd & drug 38,354 9,424 10,565 11,028 20.3 4.4 2.4 16.7 WOW AU Woolworths AU Fd & drug 27,473 9,947 10,615 11,008 24.9 3.7 10.0 20.5 TCS IN Tata Consultancy IN Software 75,279 9,039 9,768 10,798 58.5 10.5 5.3 18.0 066570 KS LG Electronics KR Cons dur 11,985 9,925 9,646 10,356 20.9 7.4 371.1 7.9 005380 KS Hyundai Motor KR Autos 34,913 9,632 9,796 10,248 12.3 4.6 5.0 7.0 023530 KS Lotte Shopping KR Retail 6,643 6,025 6,373 6,673 25.3 4.7 53.7 23.3 3396 HK Legend CN Tech HW 5,706 5,129 6,406 6,250 14.1 (2.4) 7.3 7.0 JM SP Jardine Matheson HK Cap gds 47,478 5,973 5,941 6,030 16.3 1.5 10.4 14.9 Note: Universe is broader Asia Pacific ex-Japan companies with market cap over US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Companies with high SG&A to sales and robust
SG&A growth
SG&A leaders in Asia based on actual dollar spending
Section 2: A multibagger framework Microstrategy
28 [email protected] 6 September 2017
Asian small-/midcaps with high and rising advertising expense Asian companies have often been accused of focusing on capex rather than brand building. A strong brand can lead to a sustainable competitive advantage but requires investment in terms of advertisement expense. Not many companies explicitly provide this data as it forms part of SG&A spending. Indeed, companies providing this data can be assumed to have a high enough advertising budget that necessitates separate reporting. Below we highlight a list of broader Asian small-to-midcap companies with high and rising advertising expense.
Figure 34
Asian small-/midcaps with high advertising exp-to-sales ratio and strong adv exp (sorted by adv exp/sales ratio) Code Name Cty Sector Mkt cap Adv exp to sales (%) Adv exp growth (%) FY1-FY2 EPS 12M fwd
(US$m) FY-2 FY-1 FY0 FY-1 FY0 L5Y Cagr Cagr (%) PE (x) MMYT US MakeMyTrip IN Retail 3,096 14.3 32.4 50.1 155.0 106.0 67.6 nm nm 1513 HK Livzon Pharma CN Pharma 3,838 36.1 35.0 36.6 15.7 20.8 27.4 17.5 18.9 057050 KS HDHS KR Retail 1,401 33.4 36.7 36.0 13.4 6.2 12.5 15.0 11.9 NETM IN Network18 Media IN Media 812 26.4 30.8 34.6 (42.9) 9.6 (4.1) na nm BKL AU Blackmores AU HPC 1,237 17.1 17.7 16.6 40.4 42.6 39.0 21.4 19.2 SOHU US Sohu CN Software 2,131 18.6 10.2 16.4 (36.6) 37.2 26.4 nm nm BLOOM PM Bloomberry PH Cons svcs 2,102 9.6 12.6 13.9 36.6 33.0 na 75.6 15.5 973 HK L'Occitane HK Retail 3,339 11.1 12.5 12.9 23.4 6.3 13.1 7.5 20.0 SKB IN GSK Consumer IN FBT 3,526 16.6 13.2 12.9 (24.1) (5.4) 3.3 10.5 30.1 000080 KS Jinro KR FBT 1,575 10.6 10.0 10.3 (4.1) 1.6 8.4 38.4 28.5 001800 KS Orion KR FBT 440 9.8 9.0 9.3 (0.3) 3.0 3.3 (9.0) 3.0 TGBL IN Tata Global Bev IN FBT 1,927 16.6 8.7 8.6 (56.4) 1.2 (11.9) 17.9 24.3 005300 KS Lotte Chilsung KR FBT 1,815 8.8 8.1 7.9 (3.4) 1.4 5.9 0.8 31.7 AGI PM Alliance Global PH Cap gds 2,681 9.9 8.1 7.9 (8.0) (1.4) 42.5 9.6 8.2 069960 KS HDS KR Retail 1,884 6.2 6.6 6.8 14.8 14.2 1.6 2.4 7.5 005990 KS Maeil Dairy KR FBT 123 5.0 5.1 5.7 8.7 19.9 11.9 13.7 3.1 009240 KS Hanssem KR Cons dur 2,639 5.9 5.2 5.3 14.3 15.9 27.2 7.8 22.0 004370 KS Nongshim KR FBT 1,693 3.5 3.9 4.9 18.5 25.9 6.9 (26.4) 18.5 004990 KS Lotte Confectionery KR FBT 2,403 4.1 4.2 4.5 4.1 6.1 7.5 21.1 27.7 001040 KS CJ Corp KR Cap gds 4,324 3.5 3.5 3.3 9.0 6.6 5.4 24.7 14.9
Note: Universe is broader Asia Pacific ex-Japan companies with market cap between US$100m to US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Asian large-cap companies leading the advertising effort Below we also provide a list of the top-10 advertising-leaders in Asia based on their actual dollar spending last year.
Figure 35
Top-10 companies with the highest advertising expense dollar-amount (sorted by advertising exp dollar amount) Code Name Cty Sector Mkt cap Adv exp amount (US$m) Adv exp Adv exp FY1-FY2 EPS 12M fwd
(US$m) FY-2 FY-1 FY0 to sales growth Cagr (%) PE (x) (FY0, %) (FY0, %) 005930 KS Samsung Electronics KR Tech HW 283,600 10,299 9,782 10,280 5.7 5.1 43.7 7.5 000270 KS Kia Motors KR Autos 12,568 1,630 1,892 2,031 4.3 7.4 (3.8) 6.0 005380 KS Hyundai Motor KR Autos 34,913 1,833 1,850 1,994 2.4 7.8 5.0 7.0 880 HK SJM HK Cons svcs 4,909 4,319 2,359 1,920 35.9 (18.6) (16.7) 22.9 030200 KS KT KR Telecom 6,905 2,483 1,816 1,923 9.5 5.9 8.7 9.6 066570 KS LG Electronics KR Cons dur 11,985 1,774 1,596 1,861 3.8 16.6 371.1 7.9 TTMT IN Tata Motors IN Autos 19,986 1,330 1,372 1,361 3.2 (0.8) 53.0 10.6 BABA US Alibaba CN Software 428,095 198 833 1,327 5.6 59.3 35.2 30.6 BIDU US Baidu CN Software 61,015 743 1,478 1,167 11.0 (21.0) 24.5 27.0 BHARTI IN Bharti Airtel IN Telecom 26,123 na 1,290 1,117 7.5 (13.4) (6.4) 49.9
Note: Universe is broader Asia Pacific ex-Japan companies with market cap over US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Companies with high advertising expense to
sales along with a rising advertisement budget
Top-10 advertising leaders in Asia based on
actual dollar spending
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 29
Overseas expansion: New sources of growth While capturing market share is an important step towards becoming a leader, multibaggers also benefit from the growing market pie. In that sense, most Asian companies benefitted from the sharp pickup in economic growth in their home markets. In the case of semi-developed markets such as Korea and Taiwan, exports have become the key source of topline growth. Indeed, Asia’s intra-region revenue (80%) is still the highest, outstripping the slower-growing developed markets of the USA, Europe and Japan. This implies that most Asian markets, irrespective of their economic growth had the opportunity to benefit from the rise of China, India and emerging Asean.
Figure 36
Regional sales geographical breakdown (based on current MSCI World universe)
Note: Export data without specific breakdown is distributed among rest of the regions in proportion to the 2016 nominal GDP (US$). Source: CLSA, Factset
Developed markets have the highest overseas exposure in Asia In Figure 37, we plot the average overseas exposure of the broader Asian universe with market cap more than US$100m. While the trend is volatile, it has an upward bias. Furthermore, the market-wise figures show that developed and semi-developed markets such as Singapore and Taiwan (ex-financials) are most exposed to outside markets, followed by Australia, Malaysia and Korea. On the other hand, emerging Asean and China’s listed universe is more inwardly focused.
Figure 37 Figure 38
Broader APxJ (ex-fin): Foreign revenue as % of sales Broader APxJ markets (ex-fin): Foreign sales exposure
Note: Broader APxJ (ex-finance) companies with market cap more than US$100m. Market aggregate based on simple average of underlying stocks. We do not include HK in these calculations as it is hard to ascertain whether the companies belong to HK or China. Source: CLSA, Factset
80.4
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AxJ USA Japan Europe OtherSales geographical breakdown (%)
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12
Dec
13
Dec
14
Dec
15
Dec
16
Broader APxJ universe (ex-HK&TW)
Broader APxJ universe (ex-HK, RHS)
Average foreign sales exposure (FY0,%)
(%)
0
10
20
30
40
50
60
SG
TW AU
APx
JxH
K MY
KR IN TH CN PH ID
Current
L5Y average (since 2012)
(%)
Most developed markets have a higher overseas exposure
Some 80% of Asia ex-Japan revenue is derived domestically from higher
growth markets
Companies can grow not only by capturing market
share, but also by opening up new markets
Emerging Asean and China have the lowest
overseas revenue exposure
Section 2: A multibagger framework Microstrategy
30 [email protected] 6 September 2017
Foreign exposure favoured by lower domestic growth markets Markets with slower domestic growth are more likely to look outside their home markets to expand topline. This is certainly true for Asian markets, where we find a negative correlation with the historical GDP growth and foreign sales exposure. This idea also seems to hold from a forward-looking perspective since the higher-growth emerging-Asean markets and China have much lower foreign exposure. On the other hand, the lower-domestic-growth markets of Singapore, Taiwan and Australia have much higher exposure. India is an outlier with high foreign exposure, despite high growth.
Figure 39 Figure 40
APxJ mkts (ex-fin): GDP gr vs foreign sales exp (L5Y) APxJ mkts (ex-fin): N2Y GDP growth vs foreign sales
Note: Broader APxJ (ex-HK) companies, excluding financials with market cap > US$100m. We do not include HK in these calculations as it is hard to ascertain whether the companies belong to HK or China Source: CLSA, Factset, IMF
Tech and energy have the highest overseas exposure Tech companies have the highest foreign exposure with an average 49% of sales coming from outside the domestic market, which is higher than the 28% exposure witnessed by the overall region. Energy and materials sectors are the other two major contributors to overseas sales. On the other hand, telecom and utilities have the lowest overseas exposure, along with staples and property.
Figure 41
Broader APxJ sectors (ex-fin): Average foreign sales exposure
Note: Broader APxJ companies, excluding financials with market cap > US$100m. Sector aggregate based on simple average of underlying stocks. We do not include HK in these calculations as it is hard to ascertain whether the companies belong to HK or China Source: CLSA, Factset
Philippines
Malaysia
Singapore
China
Taiwan
IndiaKorea
Indonesia
Thailand
Australia
APxJxHK
0
10
20
30
40
50
60
2 4 6 8 10 12 14
Foreign revenue as % of sales (L5Y avg)
Nominal GDP growth in lcl ccy (L5Y Cagr, %)
y = -3.9x + 50.7; R2 = 0.41
PhilippinesMalaysia
Singapore
China
Taiwan
IndiaKorea
Indonesia
Thailand
AustraliaAPxJxHK
0
10
20
30
40
50
60
2 4 6 8 10 12 14
Foreign revenue as % of sales (current)
Avg nominalGDP growth lcl
ccy (17-18F, %)
y = -4.26x + 56.7; R2 = 0.53
0
10
20
30
40
50
Info
Tech
Ener
gy
APx
JxH
K
Mat
eria
ls
Indu
strial
s
Con
s di
sc
Hea
lthca
re
Con
s st
pl
Prop
erty
Util
ities
Tele
com
Current L5Y average (since 2012)(%)
GDP growth is negatively correlated with foreign
sales exposure
On average, tech-sector companies derive some
49% of their revenue from overseas . . .
. . . while telecom, utilities, property and
staples are focused locally
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 31
Low-growth market multibaggers have higher overseas exposure After establishing that companies from low-growth markets are more likely to expand outside, we searched for further evidence to determine whether such a move boosts returns. Our analysis shows that for a number of sectors from low-growth markets, the multibaggers have a higher foreign-sales exposure than the peers. On the other hand, for a number of sectors within the higher-growth markets, multibaggers have a much lower foreign-sales exposure than their peers. This suggests that for companies facing slow domestic economic growth, overseas exposure is a key differentiator. We believe that the slower economic-growth conditions are likely to persist in most developed and semi-developed markets such as Australia, Korea, Taiwan, Hong Kong and Singapore. Hence, for such markets, higher sales exposure is likely to be a key consideration when searching for multibaggers.
Figure 42 Figure 43
Dev Asia: Multibaggers with higher overseas exposure EM Asia: Multibaggers with lower overseas exposure
Note: Broader APxJ (ex-HK) companies, excluding financials with market cap > US$100m. Sectors are based on GICS Level I classifications. We do not include HK in these calculations as it is hard to ascertain whether the companies belong to HK or China. Source: CLSA, Factset
Relative foreign exposure for multibaggers Below we highlight a more detailed data set of the multibagger overseas exposure relative to peers for various market-sector groups. It shows that investors need to be selective even within low-growth markets.
Figure 44
Broader APxJ (ex-fin): Foreign sales exposure of multibaggers relative to peers (2010-11)
Note: Broader APxJ (ex-HK) companies, excluding financials with market cap > US$100m. Sectors are based on GICS Level I classifications. We do not include HK in these calculations as it is hard to ascertain whether the companies belong to HK or China. Source: CLSA, Factset
0
20
40
60
80
1.01.11.21.31.41.51.61.7
KR
,Con
s st
pl
TW,C
ons
disc
KR
,Ind
ustr
ials
AU
,Mat
eria
ls
TW,M
ater
ials
TW,I
nfoT
ech
KR
,Con
s di
sc
AU
,H'c
are
SG
,Ind
ustr
ials
TW,C
ons
stpl
Multibaggers rel to industry (2010-11)Current - Foreign sales exposure (RHS)
(x) (%)
0
5
10
15
20
25
30
35
40
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
IN,C
ons
disc
TH,M
ater
ials
IN,I
ndus
tria
ls
CN
,Inf
oTec
h
MY,
Ener
gy
CN
,Con
s di
sc
MY,
Indu
stri
als
MY,
Con
s di
sc
TH,I
ndus
tria
ls
ID,M
ater
ials
Multibaggers rel to industry (2010-11)Current - Foreign sales exp (RHS)
(x) (%)
Cons disc Cons stpl Energy Healthcare Industrials InfoTech Materials
Australia 0.88 na na 1.11 0.82 0.68 1.49
China 0.62 na 1.44 0.49 1.04 0.69 na
India 0.91 0.99 na 1.09 0.84 1.04 0.58
Indonesia na 1.46 na na 0.27 na 0.36
Korea 1.32 1.69 na 0.25 1.56 0.64 0.93
Malaysia 0.60 0.88 0.68 1.18 0.61 na 0.56
Singapore na 0.79 na na 1.10 0.99 na
Taiwan 1.57 1.09 na 1.02 0.84 1.39 1.41
Thailand 1.98 na na na 0.37 0.96 0.89
Overseas focus needs to be selective even within the low-growth markets
Higher growth market multibaggers have lower
overseas exposure
Section 2: A multibagger framework Microstrategy
32 [email protected] 6 September 2017
Asian companies with high or rising overseas exposure Our analysis has shown that multibaggers from markets with low economic growth are more likely to have higher overseas exposure. This overseas exposure, especially to higher-growth markets, allows them to increase their potential market size. Below, we highlight two screens from low-growth markets, one for large-cap companies with high overseas exposure and another for small- to midcap companies with rising foreign exposure.
Figure 45
Large-cap companies (ex-fin & commodities) with high overseas exposure (sorted by the foreign sales exposure) Code Name Cty Sector Mkt cap Foreign sales 12MF 18F Sales FY1-FY2 FY1-FY2 FCF conv NDE (US$m) exposure (%) PE growth EPS Cagr ROE (FY0, (latest, FY0 FY-1 (x) (%) (%) (avg, %) %) %) Australia WFD AU Westfield AU Property 12,475 100.0 100.0 17.4 8.9 6.5 6.7 (71.4) 66.7 COH AU Cochlear AU Healthcare 7,080 99.0 99.0 34.9 8.8 13.1 42.4 82.0 23.8 BXB AU Brambles AU Comm svcs 12,146 92.5 93.2 18.4 12.3 6.6 21.1 10.4 87.2 CSL AU CSL AU Pharma 45,589 90.3 91.3 28.0 12.9 17.3 41.5 28.9 98.8 Korea 000660 KS SK Hynix KR Semis 41,659 93.6 93.6 4.8 7.7 83.0 31.0 (31.7) (1.5) 034220 KS LG Display KR Tech HW 9,771 93.1 92.2 6.5 (1.2) 28.1 12.5 (54.5) 17.8 005930 KS Samsung Electronics KR Tech HW 283,600 90.0 89.6 7.5 8.7 43.7 19.5 98.7 (27.8) 161390 KS Hankook Tire KR Autos 6,601 82.3 81.4 8.8 7.2 1.4 12.6 53.8 29.3 Malaysia IHH MK IHH MY Healthcare 11,579 81.5 80.2 43.5 14.1 19.1 4.8 (24.0) 19.7 SIME MK Sime Darby MY Cap gds 14,690 70.5 67.9 23.7 4.0 0.3 6.7 60.5 28.3 AXIATA MK Axiata MY Telecom 10,152 69.4 64.1 28.3 5.1 3.5 6.4 51.3 54.5 GENT MK Genting Bhd MY Cons svcs 8,452 62.9 62.4 14.8 8.1 7.0 6.2 99.2 (24.9) Singapore STE SP ST Engineering SG Cap gds 8,156 98.7 98.6 20.4 3.9 5.8 23.8 90.9 10.3 CAPL SP CapitaLand SG Property 11,642 67.8 67.3 17.7 (2.3) 6.6 5.8 276.4 54.4 ST SP Singtel SG Telecom 44,773 52.6 54.8 14.4 2.3 3.6 14.2 72.4 37.5 CIT SP City Developments SG Property 7,564 51.5 50.4 16.8 3.1 0.7 6.2 176.4 21.9 Taiwan 3008 TT Largan TW Tech HW 24,622 100.0 100.0 20.2 30.6 34.3 35.1 87.7 (85.1) 2382 TT Quanta TW Tech HW 8,849 100.0 100.0 13.2 5.5 20.0 14.2 277.2 (21.5) 2317 TT Hon Hai TW Tech HW 65,724 99.3 99.0 11.6 7.5 10.3 13.8 81.3 (33.4) 2474 TT Catcher Tech TW Tech HW 9,440 96.7 95.1 10.8 18.9 13.9 18.4 81.6 (48.0)
Note: Universe is broader Asia Pacific ex-Japan (ex-financials and commodities) companies with market cap over US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Figure 46
Small-/midcap companies (ex-fin & commodities) with rising overseas exposure (sorted by increase in foreign exp) Code Name Cty Sector Mkt cap Foreign sales 12MF 18F Sales FY1-FY2 FY1-FY2 FCF conv NDE (US$m) exposure (%) PE growth EPS Cagr ROE (FY0, (latest, FY0 FY-1 Diff (x) (%) (%) (avg, %) %) %) Australia AAC AU Australian Agricultural AU FBT 681 78.5 68.4 10.1 15.0 7.7 39.4 2.8 nm 31.8 BKL AU Blackmores AU HPC 1,237 27.7 21.0 6.7 19.2 10.3 21.4 39.5 69.7 48.2 IEL AU IDP Education AU Cons svcs 1,024 83.0 76.4 6.6 24.7 14.1 19.9 51.7 86.9 (26.7) ACX AU Aconex Ltd AU Software 723 67.0 61.7 5.3 74.4 16.6 47.5 10.1 25.7 (37.8) WEB AU Webjet AU Retail 908 36.4 34.1 2.3 20.2 33.6 30.9 18.8 167.6 (18.1) Korea 090460 KS BH KR Tech HW 627 30.6 13.9 16.8 11.5 43.1 nm 37.0 nm 147.7 079160 KS CJ CGV KR Media 1,152 31.9 20.5 11.5 26.2 12.3 124.0 11.9 (28.6) 267.9 081660 KS Fila KR Cons dur 751 65.1 54.0 11.1 10.7 5.0 39.0 8.6 (212.3) 156.0 000990 KS Dongbu HiTek KR Semis 625 49.0 41.3 7.8 5.6 5.7 24.2 27.5 154.4 63.5 041510 KS SM Entertainment KR Media 529 55.0 48.1 6.9 26.2 62.0 184.9 6.0 41.3 (37.0) Malaysia FNH MK Fraser & Neave (MY) MY FBT 2,112 46.5 41.6 4.9 20.3 6.0 8.1 18.9 87.4 (1.2) GAM MK Gamuda MY Cap gds 3,074 18.8 14.4 4.4 16.9 19.0 11.8 10.3 (8.7) 52.3 PEP MK PPB MY FBT 4,607 25.1 22.1 3.0 18.0 4.2 3.5 5.1 22.5 (3.5) YTL MK YTL MY Utilities 3,440 71.6 68.7 2.8 16.1 6.4 16.4 5.8 104.2 176.3 Singapore CDREIT SP CDL Hosp Trust SG Property 1,234 50.6 43.8 6.9 16.9 10.6 19.8 6.1 201.4 61.0 WINGT SP Wing Tai SG Property 1,183 28.5 22.8 5.7 29.3 12.8 174.9 1.6 (395.2) 6.7 Taiwan 8341 TT Sunny Friend Envir TW Comm svcs 634 82.4 20.8 61.6 23.7 27.4 18.1 24.8 136.8 (44.1) HIMX US Himax Technologies TW Semis 1,440 75.1 63.2 11.9 30.2 23.1 1.7 9.4 148.4 (18.4) 3081 TT LandMark TW Semis 1,124 68.0 57.5 10.5 31.5 39.7 19.8 26.1 125.8 (56.5) 8436 TT TCI TW HPC 507 65.5 55.2 10.3 19.8 25.4 26.9 21.2 122.3 (41.3) 4105 TT TTY Biopharm TW Pharma 749 27.4 20.1 7.3 16.8 6.2 8.3 23.5 51.9 (28.6)
Note: Universe is broader Asia Pacific ex-Japan (ex-financials and commodities) companies with market cap between US$100m to US$5bn and 3M ADTO over US$1m. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Low-growth market companies benefit most from overseas exposure
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 33
Capex not a major differentiator of multibaggers Overinvestment has been a key concern for Asian companies. The 2000-07 period was particularly characterised by high capital intensity (capex/sales) along with contracting margins. In their quest to boost revenue, companies overspent on capex while cutting back on more value-added expenses such as R&D and brand building. However, over the past five years, there has been a marked decrease in capex growth. While Asian capital intensity remains the highest across regions, companies are increasingly focused on R&D and SG&A spend. Indeed, capex is of greatest use when the market is growing fast. But with most markets now witnessing slower nominal GDP growth, product superiority will be more important for companies to establish a sustainable competitive advantage.
Figure 47 Figure 48
MSCI regions (ex-fin): Capital intensity (capex/sales) MSCI AsiaxJ (ex-fin): Capex growth
Note: Ratios are bottom-up aggregated with freefloat adjustment based on current MSCI universe. Source: CLSA, Factset
For the broader universe, capital intensity started falling after 2008 Data for the broader Asia Pacific ex-Japan companies show the median capital intensity has been on a steady decline after peaking in 2008, dropping to just over 4.5% in 2016, based on data for over 3,700 companies. Hence, while large-cap companies have already been witnessing slower capital intensity since 2005, this trend became broadbased only after the end of 2008. Figure 49
Broader APxJ (ex-fin): Median FY0 capital intensity
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
6.6
6.9
7.7
8.6
5
6
7
8
9
10
11
12
13
14
15
00A
01A
02A
03A
04A
05A
06A
07A
08A
09A
10A
11A
12A
13A
14A
15A
16A
USA Japan
Europe AsiaxJ
Capital intensity (capex/sales, %)
(15)
(10)
(5)
0
5
10
15
20
25
30
00A
01A
02A
03A
04A
05A
06A
07A
08A
09A
10A
11A
12A
13A
14A
15A
16A
(%)38.2 40.2
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
Broader APxJ universe (median FY0 capital intensity)(%)
Data for over 3,700 companies with market
cap more than US$100m
Asian capital intensity is high but capex growth
has slowed down significantly
Median capital intensity has fallen to 4.5%
Section 2: A multibagger framework Microstrategy
34 [email protected] 6 September 2017
Higher capital intensity no longer a powerful signal In an environment of strong topline growth, a company with high levels of capital intensity is better enabled to service demand, which would translate into higher future sales and earnings. However, given overcapacity and slowing topline growth, the effectiveness of higher capital intensity has diminished significantly over time. In Figure 50 we highlight the trend in median-capital-intensity ratio of the multibaggers versus the relevant industry, averaged across all the industries. The last data point is 1.05, which suggests that on average; the multibaggers over the past five years only had 5% higher capex than the industry median.
Figure 50
Broader APxJ (ex-fin): Average FY0 capex spend of multibaggers vs industry
Note: Broader APxJ companies with market cap of more than US$100m. Source: CLSA, Factset
Multibaggers in many industries had lower capex Figure 51
Broader APxJ industries: FY0 Capex spend of multibaggers relative to industry versus the industry
Note: Broader APxJ companies with market cap of more than US$100m. The bubble size represents the count of companies with FY0 Capex to sales data. Source: CLSA, Factset
1.05
0.9
1.0
1.1
1.2
1.3
1.4
1.5
Dec
99
Jun
00
Dec
00
Jun
01
Dec
01
Jun
02
Dec
02
Jun
03
Dec
03
Jun
04
Dec
04
Jun
05
Dec
05
Jun
06
Dec
06
Jun
07
Dec
07
Jun
08
Dec
08
Jun
09
Dec
09
Jun
10
Dec
10
Jun
11
Dec
11
Average across industries (median capital intensity ofmultibaggers vs the industry)
Effectiveness of capex fading over time
AirlinesAero&def
Gas utilH'care prov
Comm svc
MediaPharma
Marine
Trans infra
Cont & pkg
Met & min
Autos
Multi-retailPers prod Ind conglos
BeveragesOil&Gas
Food prod
Hotels
Energy E&S
Bldg prodElec I&C
H'hold prodDiv cons svc
Autoparts CementChemicalsAirFt&Log
Road/rail
SemisElec util
Tobacco
Leis prod
Tex/app/lux
Elec equip
H'hold dur
Software
Internet
Fd/stp ret
Machinery
IT Services
Developers
Spec retail
Comm equip
Const & engg
Tech hw
Distributors
TradingCos
0.60
0.70
0.80
0.90
1.00
1.10
1.20
1.30
1.40
1.50
1.60
0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5
Median capital intensity (FY0, %)
Multibaggers rel to industry (avg 2000-12, %)
Wireless tel (20.7, 1.3, 23)
Paper (5.6, 2, 32)
Biotech (24.6, 0.6, 53)IPPs (25.5, 0.6, 41)
H'care E&S (9.6, 1.9, 48)
Div telecom (21.1, 1.1, 36)
Multibaggers over the past five years, only had a
5% higher capex versus their industry
Higher capital intensity is a good signal when
topline growth is strong
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 35
Quantitative signals through fundamental factors Earlier we used industry-specific indicators to understand the genesis of multibaggers. In this section, we explore the fundamental factors relevant across industries to identify potential multibaggers. Some of the important considerations include past and future earnings growth (including drivers), profitability, size and balance-sheet quality. A characteristics study shows that past earnings growth has been useful in identifying multibaggers with future multibaggers witnessing higher earnings growth over the past three years compared to the overall universe. It also shows that consensus growth forecasts have been relatively less helpful. Profitability was another key indicator with ROE a better metric than ROIC over the long term. However, ROIC has become quite important post-GFC. Lastly, size is an important factor with small-caps more likely to turn into multibaggers.
Figure 52
Characteristics analysis - (median since 2000, quarterly rebalance)
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
Characteristics changed post-GFC but historical growth still important There has been a significant change in the characteristics of multibaggers post-GFC. ROIC has become significantly more important, along with ROEs. Also, given the higher quality of companies that become multibaggers, they tend to be more expensive. Lastly, it has become even harder for large-cap companies to become multibaggers since 2010.
Figure 53 Figure 54
Characteristics analysis - before 2010 Characteristics analysis - since 2010
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
1.17 1.16 1.16
1.09 1.08 1.07 1.06
1.03
0.96 0.94 0.93 0.93 0.92 0.89 0.88
0.85 0.8
0.9
1.0
1.1
1.2
EPSg
(L3Y
)
Gea
ring
Sus
tg
EPSg
(L5Y
)
EPSg
(N2Y
)
RO
E (L
3Y)
RO
E (N
2Y)
RO
IC
Mgn
(Av
gL3Y
)
Mgn
(FY
0)
PB (
trl)
SLS
g (L
3Y)
SLS
g (N
2Y)
PE (
fwd)
Cas
h/TA
Siz
e
Quarterly median (since 2000)
Exposure of multibaggers relative to broader universe (x)
0.8
0.9
1.0
1.1
1.2
1.3
Gea
ring
EPSg
(L3Y
)
Sus
tg
EPSg
(N2Y
)
RO
E (L
3Y)
RO
E (N
2Y)
EPSg
(L5Y
)
RO
IC
Mgn
(Avg
L3Y)
Mgn
(FY
0)
SLS
g (L
3Y)
SLS
g (N
2Y)
Siz
e
PB (
trl)
Cas
h/TA
PE (
fwd)
Quarterly median (before 2010)
Exposure of multibaggers relative to broader universe (x)
0.60.70.80.91.01.11.21.3
RO
IC
EPSg
(L3Y
)
Sus
tg
RO
E (L
3Y)
RO
E (N
2Y)
PB (
trl)
EPSg
(L5Y
)
EPSg
(N2Y
)
SLS
g (L
3Y)
Mgn
(Avg
L3Y)
SLS
g (N
2Y)
Mgn
(FY
0)
PE (
fwd)
Cas
h/TA
Gea
ring
Siz
e
Quarterly median (since 2010)Exposure of multibaggers relative to broader universe (x)
Growth, profitability and size are main factors that
have mattered over the long term
ROIC and quality factors have become quite
important post-GFC
Focusing on factors that matter across industries
Section 2: A multibagger framework Microstrategy
36 [email protected] 6 September 2017
Multibaggers versus rest of the universe: Factor trends Below we highlight the trends in median-factor values for stocks that went on to become multibaggers over the next five years and compare it to the median-factor values of the overall universe. The charts highlight that quality factors have become increasingly important and that potential multibaggers no longer trade at a discount to the market.
Figure 55 Figure 56
APxJ: Multibaggers versus universe - ROIC (FY0) APxJ: Multibaggers versus universe - ROE (N2Y)
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
Figure 57 Figure 58
APxJ: Multibaggers vs universe - EPS growth (L3Y) APxJ: Multibaggers vs universe - EPS growth (N2Y)
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
Figure 59 Figure 60
APxJ: Multibaggers vs universe - Sales growth (L3Y) APxJ: Multibaggers vs universe - 12-month trailing PB
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
6
8
10
12
14
16
18
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Multi-bagger UniverseMedian ROIC (FY0,%)
1011121314151617181920
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Multi-bagger UniverseMedian ROE (N2Y,%)
579
1113151719212325
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Multi-bagger UniverseMedian EPSg (L3Y,%)
10
12
14
16
18
20
22
24
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Multi-bagger UniverseMedian EPSg (N2Y,%)
5
7
9
11
13
15
17
19
21
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Multi-bagger UniverseMedian Slsg (L3Y,%)
0.50.70.91.11.31.51.71.92.12.32.5
Dec
99
Dec
00
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Multi-bagger UniverseMedian PB (trl,%)
ROE has been consistently important since 2004
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 37
Historical earnings growth increases the multibagger hit rate Our characteristics analysis has identified historical earnings track record over the past three years to be an important factor in identifying potential multibaggers, even more so than the next two-year consensus forecast. To further understand the impact of earnings growth on long-term returns we calculated the multibagger hit rate of companies with above-median growth numbers. Data show that the hit rate of identifying multibaggers increases from 14.6% to around 16.2% for companies with above-median next-two-year growth forecasts or above-median sustainable growth. However, using the past-three-year earnings growth data, the hit rate is even higher at 18.1%. This suggests that multibaggers are more likely to be companies that are already witnessing strong earnings momentum.
Figure 61
Broader APxJ: Hit rate of high growth stocks becoming multibaggers
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
Look for companies with more than 10% historical earnings Cagr A further breakdown of the multibagger hit rate for different growth ranges based on historical and forward growth shows that companies with historical growth of more than 10% have a higher likelihood of success. However, when using forward-growth data, 10-30% is the sweetspot with the hit rate dropping sharply for growth forecasts of more than 30%.
Figure 62 Figure 63
Hit rate of multibaggers in different EPSg (L3Y) ranges Hit rate of multibaggers in different EPSg (N2Y) ranges
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
14.6
16.2 16.3
18.1
10.2 10.7 11.2 11.7
8
10
12
14
16
18
EPS Cagr (N2Y) Sustg EPS Cagr (L3Y)
All multibaggers Above median
Quarterly average hit rate (since 2000)Latest hit rate (+200% since 2012)
Hit rate of stocks becoming multibaggers (%)
14.6 15.6 15.4
19.5 17.0
18.3
10.3 9.1
12.5 13.7 14.2
11.0
68
101214161820
All multi-baggers
<0% 0-10% 10-20% 20-30% >30%
EPSg (L3Y)
Quarterly average hit rate (since 2000)
Quarterly average hit rate (since 2010)
Percentage of multibaggers (%)
14.6 13.4 14.2
17.2 17.0 14.9
10.3
7.5
10.0
12.1 13.1
9.5
6
9
12
15
18
All multi-baggers
<0% 0-10% 10-20% 20-30% >30%
EPSg (N2Y)
Quarterly average hit rate (since 2000)
Quarterly average hit rate (since 2010)
Percentage of multibaggers (%)
Measuring the hit rate of identifying multibaggers
for different growth factors
Above median three-year earnings Cagr increases the multibagger hit rate
to 18.1% from 14.6%
When using forward growth, 10-30% is the sweetspot
Section 2: A multibagger framework Microstrategy
38 [email protected] 6 September 2017
Historical growth important for most markets and sectors Further analysis at the market and sector level for companies with above-median past three-year earnings Cagrs suggests that the likelihood of identifying multibaggers increases across most markets and sectors. The largest increases in the multibagger hit rate were in the Hong Kong, Malaysian and Philippine markets; and in healthcare, financials and commodities, among sectors. The factor has been relatively less important for only the Singapore and Taiwan market; and for the property sector.
Figure 64 Figure 65
APxJ mkts: Hit rate of high growth (L3Y) multibaggers APxJ sctrs: Hit rate of high growth (L3Y) multibaggers
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. ‘High growth’ implies above median past 3-year earnings Cagr. Source: CLSA, Factset
Profitability has become an important factor The early part of the previous decade was dominated by multibaggers from commodities players with lower profitability levels. However, since the GFC, quality has become an important factor, led by both ROE and ROIC. We have already shown earlier during the characteristics analysis of multibaggers that ROE has been a more consistent factor than ROIC. A further examination of the multibagger hit rate of companies with above-median ROE (next two-year average) and ROIC (last reported full-year data) shows that ROE also has a marginally better hit rate. With ROIC nonapplicable to the financial sector, we decided to focus on ROE as the main profitability indicator. The latest set of multibaggers with high ROE mostly comes from India, Australia and China.
Figure 66 Figure 67
APxJ: Hit rate of high profitability multibaggers APxJ: Latest contribution to high ROE multibaggers
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. ‘High ROE’ implies above median next 2-year average ROE. Source: CLSA, Factset
5
10
15
20
25
30
IN ID PH CN KR TH APxJ HK MY AU SG TW
Above median L3Y EPS Cagr
All stocks
Hit rate of stocks becoming multibaggers (avg since 2000, %)
5
10
15
20
25
30
Ener
gy
Hea
lthca
re
Con
s st
ap
Mat
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Indu
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Fina
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APx
J
Util
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Con
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Tele
com
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Above median L3Y EPS Cagr
All stocks
Hit rate of stocks becoming multibaggers (avg since 2000, %)
14.6
15.8 15.9
10.2
11.9 11.9
89
1011121314151617
All multibaggers All multibaggers(ex-fin, ROIC >
median)
All multibaggers(N2Y ROE > median)
Quarterly average hit rate (since 2000)Latest hit rate (+200% since 2012)
Hit rate of stocks becoming multibaggers (%)
India49%
Aust13%
China12%
Korea7%
Taiwan7%
Thai5%
Indo4%
HK1%
Malay1%
Sing1%
Latest contributionof multibaggers in APxJ region (%)
The factor was less relevant for only the
Singapore and Taiwan; and the property sector
ROE has been a more consistent factor ROIC,
and its hit rate is also marginally better
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 39
ROE and ROIC cutoffs have increased post-GFC A study of the historical trends since 2000 suggests that companies with ROE of more than 10% have a higher multibagger hit rate than the broader universe. Similarly, over the longer term, 5-20% was the sweetspot for ROIC. However, post-GFC, quality has become an even more important factor with multibagger cutoff rising for both ROE and ROIC. For example, the multibagger hit rate of all the ranges for ROE above 10% have been similar since 2000. However, since 2010, the multibagger hit rate for ROE less than 15% is below the overall universe, while that of ROE of more than 20% is significantly higher than that of the 15-20% range. Similarly, the ROIC sweetspot has moved from 5-15% when using data since 2000 to more than 10% when considering the period since 2010.
Figure 68 Figure 69
Hit rate of multibaggers in different ROE ranges Hit rate of multibaggers in different ROIC ranges
Note: Broader APxJ universe with market cap of more than US$100m. Source: CLSA, Factset
ROE has been important within industries than within markets A similar analysis at the market and sector level shows that profitability adds more value on an intra-sector basis than within markets. For example, the multibagger hit rate is lower for the above-median ROE basket in Korea, Malaysia and Singapore. However, within sectors, the hit rate is higher for the above-median ROE basket in nine out of the 11 sectors, and is almost similar for the remaining two sectors (consumer staples and industrials).
Figure 70 Figure 71
APxJ (ex-fin) mkts: Hit rate of high ROE multibaggers APxJ (ex-fin) sctrs: Hit rate of high ROE multibaggers
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years.. ‘High ROE’ implies above median next 2-year average ROE. Source: CLSA, Factset
14.6
12.1
13.9 15.6 15.6 15.7
10.3
5.8 6.7
8.7
11.5
14.2
4
8
12
16
All multi-baggers
<5% 5-10% 10-15% 15-20% >20%
ROE (N2Y)
Quarterly average hit rate (since 2000)Quarterly average hit rate (since 2010)
Percentage of multibaggers (%)
14.8
12.3
17.0 18.4 15.6
14.3
10.3
5.9
9.6
13.6 12.2 12.7
4
8
12
16
20
All multi-baggers(Ex-fin)
<5% 5-10% 10-15% 15-20% >20%
ROIC (FY0)
Quarterly average hit rate (since 2000)
Quarterly average hit rate (since 2010)
Percentage of multibaggers (%)
5
10
15
20
25
30
ID IN PH TH CN APxJ KR HK AU MY TW SG
Above median N2Y average ROE
All stocks
Hit rate of stocks becoming multibaggers (avg since 2000, %)
0
5
10
15
20
25
Ener
gy
Hea
lthca
re
Con
s st
ap
Mat
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ls
Fina
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ls
Con
s di
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Util
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APx
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Indu
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Tele
com
Prop
erty
Info
tec
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Above median N2Y average ROE
All stocks
Hit rate of stocks becoming multibaggers (avg since 2000, %)
Multibagger hit rate higher for above-median
ROE in 9 out of 11 sectors
Post-GFC, ROE more than 15% and ROIC more than
10% leads to higher multibagger hit rate
Section 2: A multibagger framework Microstrategy
40 [email protected] 6 September 2017
Small-caps multibaggers have delivered the highest median returns Small-cap risk premium has been a well-researched factor and the main thesis has been that the expected returns from small-caps have to be higher than the large-caps to compensate investors for the additional risks. This notion has been in question given the recent outperformance of large-caps and arguments have been put forth challenging the entire small-cap premium concept, most notably by Aswath Damodaran in a 2015 blog. Our data on Asian stocks with a market cap of more than US$100m also shows that small-cap returns are not inherently higher over a three-to-five -year period on a median basis. However, when it comes to multibaggers, small-cap returns are definitely higher than the midcap and large-caps. Indeed, on a five-year basis, small-cap multibaggers outperformed the relevant market benchmark by 276%, while midcaps and large-caps outperformed by 212 and 195%.
Figure 72 Figure 73
APxJ: Performance of multibaggers by mkt cap APxJ: Outperformance of multibaggers by mkt cap
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
Multibagger hit rate lowest for the large caps Large-caps also have a natural disadvantage to becoming multibaggers. Analysis across different market-cap ranges shows that large-caps only have 9% multibagger hit rate as compared to the overall average of 14.6%. Midcaps also scored less than the overall average, suggesting that small-caps have the highest multibagger hit rate. This is further supported by the fact that 78% of the latest set of multibaggers were small-caps.
Figure 74 Figure 75
APxJ: Hit rate of becoming multibaggers by mkt cap APxJ: Latest contribution to multibaggers by mkt cap
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
28 27 31 26 52 51 57 47
169 177 155 155
346 363
307 300
050
100150200250300350400
All-
cap
<U
S$1
bn
US$1
-5bn
>U
S$5
bn
All-
cap
<U
S$1
bn
US$1
-5bn
>U
S$5
bn
Next 3-year return Next 5-year return
All stocks
Multibaggers
Avg median lcl ccy TR (%, since 2000)
120 129 101 92
256 276
212 195
0
50
100
150
200
250
300
All-
cap
<U
S$1
bn
US$1
-5bn
>U
S$5
bn
All-
cap
<U
S$1
bn
US$1
-5bn
>U
S$5
bn
Next 3-year OPF Next 5-year OPF
Multibaggers
Avg median lcl ccy OPF (%, since 2000)
14.6 15.5 13.9
9.0
10.2 11.9
7.9
4.2 02468
1012141618
All multi-baggers
Small-cap<US$1bn
Mid-capUS$1-5bn
Large-cap>US$5bn
Market capitalisation
Quarterly average hit rate (since 2000)
Latest hit rate (+200% since 2012)
Hit rate of stocksbecoming multibaggers (%)
Small-cap78%
Mid-cap18%
Large-cap4%
Latest contributionof multibaggers in APxJ region (%)
Multibagger hit rate of both large caps and mid-caps is smaller than the
overall average
Median return of all small-caps is similar to
the large-caps . . .
. . . but those of multibagger small-caps is
much higher than large-caps
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 41
Small-cap multibagger hit rate higher for most markets and sectors With small-caps forming 70-80% of the overall universe it is naturally harder for their hit rate to be very different from the overall universe. However, the small-cap hit rate is still marginally higher than the overall data for most markets and sectors. Size has been most effective in markets such as India, the Philippines and Australia, while being the least effective in Thailand. Among sectors, the size effect is the highest for utilities and financials.
Figure 76 Figure 77
APxJ markets - Hit rate of small-cap multibaggers APxJ sectors - Hit rate of small-cap multibaggers
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
China used to be dominated by large-cap multibaggers Below we highlight multibaggers’ median outperformance, hit rate and contribution data for different markets and sectors. In China, the large-cap multibagger hit rate has been higher than for small-caps because of the large SOE listings during 2000-05, which had strong returns until 2009-10.
Figure 78
Broader APxJ: Performance, contribution and hit rate of stocks becoming multibaggers (+200% since 2012)
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming the relevant market returns in 5 years. Source: CLSA, Factset
5
10
15
20
25
30
IN ID PH CN KR TH APxJ MY SG HK AU TW
Small caps (market cap less than US$1bn)
All stocks
Hit rate of stocks becoming multibaggers (avg since 2000, %)
5
10
15
20
25
Ener
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Con
s st
ap
Hea
lthca
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Mat
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APx
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Small caps (market cap less than US$1bn)
All stocks
Hit rate of stocks becoming multibaggers (avg since 2000, %)
<US$1bn US$1-5bn >US$5bn <US$1bn US$1-5bn >US$5bn <US$1bn US$1-5bn >US$5bn <US$1bn US$1-5bn >US$5bn <US$1bn US$1-5bn >US$5bnAPxJ 129.1 101.4 92.1 275.6 212.4 195.5 15.5 13.9 9.0 78.1 17.6 4.3 11.9 7.9 4.2
Australia 125.2 110.5 86.2 286.0 215.9 193.1 11.6 7.1 5.3 69.4 22.2 8.3 14.0 7.1 7.0China 165.4 143.4 180.1 324.6 258.2 331.8 19.6 17.1 23.4 55.8 37.2 7.0 8.1 9.9 3.9Hong Kong 143.6 101.7 74.1 276.7 253.0 139.4 12.0 18.0 4.7 84.0 12.0 4.0 8.9 6.0 2.2India 145.3 98.7 88.4 310.7 216.5 225.5 30.7 24.8 17.7 74.2 21.0 4.8 30.9 22.0 12.0Indonesia 189.7 86.8 83.2 436.5 164.2 179.3 27.3 27.7 26.6 66.7 25.0 8.3 11.1 5.6 5.9Korea 131.2 139.9 76.6 291.0 257.8 198.9 18.3 17.6 9.5 97.7 2.3 0.0 9.2 1.1 0.0Malaysia 104.0 98.4 81.6 243.6 227.4 190.7 13.4 12.2 3.8 91.7 8.3 0.0 9.6 2.5 0.0Philippines 167.2 83.6 112.9 287.0 178.6 70.7 23.8 14.8 1.8 100.0 0.0 0.0 8.0 0.0 0.0Singapore 133.9 121.9 106.2 263.3 263.7 337.2 12.0 10.1 1.6 75.0 0.0 25.0 2.4 0.0 4.0Taiwan 130.7 124.6 67.3 267.2 250.8 216.9 8.1 5.1 5.0 95.1 4.9 0.0 7.7 2.2 0.0Thailand 103.8 106.3 91.7 226.7 257.3 166.3 17.5 24.1 18.4 70.6 23.5 5.9 11.3 13.3 5.9
Cons disc 128.3 98.3 97.2 283.1 228.2 216.1 15.4 13.7 10.2 78.8 19.7 1.5 13.0 9.6 2.7Cons stap 117.9 107.0 70.0 258.7 224.9 188.6 22.8 25.2 8.7 66.7 30.3 3.0 13.7 15.9 2.9Energy 143.3 116.1 92.9 355.3 246.0 214.3 23.0 27.1 28.2 40.0 40.0 20.0 2.0 5.1 3.1Financials 134.4 71.8 104.3 249.9 172.3 148.9 16.8 12.2 5.4 81.3 14.6 4.2 26.9 6.7 2.7Healthcare 111.4 92.5 125.5 260.8 230.1 261.3 21.2 15.0 20.4 83.3 14.6 2.1 24.1 19.4 14.3Industrials 148.1 137.4 81.6 307.7 264.1 186.9 17.3 14.5 3.3 75.0 22.7 2.3 8.6 6.8 1.9Info tech 128.4 130.8 152.8 278.5 268.9 289.2 7.3 6.4 10.6 83.1 10.2 6.8 9.9 9.7 12.1Materials 139.9 122.2 106.1 289.5 242.6 186.9 18.1 19.3 15.8 85.0 10.0 5.0 10.2 3.7 5.3Property 131.6 112.5 183.5 255.4 212.6 327.3 12.3 9.5 13.4 68.4 21.1 10.5 6.5 5.4 6.3Telecom 153.1 133.7 91.4 358.3 241.5 167.5 13.6 14.1 6.1 60.0 20.0 20.0 13.0 4.8 4.8Utilities 124.1 133.4 46.8 228.9 209.4 89.3 16.8 11.8 0.8 71.4 28.6 0.0 11.4 5.0 0.0
Market
Sector
Median N3Y multi-bagger OPF (lcl ccy, avg since 2000, %)
Median N5Y multi-bagger OPF (lcl ccy, avg since 2000, %)
Average hit rate of multi-baggers (%, since 2000)
Latest contrib to multi-baggers (%, +200% since 2012)
Latest multi-bagger hit rate (%, +200% since 2012)
Market cap Market cap Market cap Market cap Market cap
Size has been most effective in markets such as India, the Philippines
and Australia
India and Indonesia have the highest median
outperformance for small cap multibaggers
Section 2: A multibagger framework Microstrategy
42 [email protected] 6 September 2017
Microstrategy: Quantitative multibagger strategy So far in the report, we have analysed various multibagger drivers in isolation. We have considered both industry-specific drivers such as R&D spend, SG&A spend and overseas exposure; and generic drivers such as growth track record, profitability and size. The later set of drivers also allows us to focus on the right sectors by highlighting the profitable growth areas in the market. In this part, we put together all of these drivers to calculate the increase in the probability of identifying multibaggers through a quantitative framework. Our analysis shows that on average, some 14.6% of companies turn into multibaggers over the next five years. However, including the factors that we discussed earlier, we can boost the hit rate to 22.1%. This is a significant increase considering multibaggers outperform by an average 256% over the next five years, implying that the expected excess return from multibaggers rises from 37.4% to 56.6%.
Figure 79
Microstrategy multibagger strategy: Average hit rate (since 2000)
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming over 5 years. ‘Higher’ implies above median values. Source: CLSA, Factset
The strategy has been more effective post-GFC Our strategy shows even better results post-GFC (since 2010), with the hit rate increasing from 10.3% to 21.8%. The post-GFC hit rate is in line with the long-term average, implying that despite the drop in overall multibagger hit rate post-GFC, we do not see a similar drop when using our strategy.
Figure 80 Figure 81
Multibagger strategy: Average hit rate (pre-GFC) Multibagger strategy: Average hit rate (post-GFC)
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming over the next 5 years. ‘Higher’ implies above median factor values. Source: CLSA, Factset
22.1
14.6 1.2
1.7 1.4
1.4 1.6
0
4
8
12
16
20
All multi-baggers
Step 1 Step 2 Step 3 Step 4 Step 5 Finalresult
Quarterly average hit rate of multibaggers (%, since 2000)
Hig
her
prof
itabi
lity
(N2Y
avg
RO
E)
Hig
her
grow
th
(L3Y
EPS
Cag
r)
Hig
her
R&
D, SG
&A a
nd
over
seas
exp
osur
e
Avo
id la
rge
caps
(Mar
ket
cap
< U
S$5
bn)
Avo
id m
id c
aps
(Mar
ket
cap
< U
S$1
bn)
22.2
14.61.2
1.71.4
1.41.6
0
4
8
12
16
20
All multi-baggers
Step 1 Step 2 Step 3 Step 4 Step 5 Finalresult
Quarterly average hit rate of multibaggers (%, pre-2010)
Hig
her
prof
itab
ility
(N
2Y a
vg R
OE)
Hig
her
grow
th
(L3Y
EPS
Cag
r)
Hig
her
R&
D, SG
&A a
ndov
erse
as e
xpos
ure
Avo
id la
rge
caps
(Mar
ket
cap
< U
S$5
bn)
Avo
id m
id c
aps
(Mar
ket
cap
< U
S$1
bn)
21.8
10.3
2.8 1.1
2.1 2.2
3.3
0
4
8
12
16
20
All multi-baggers
Step 1 Step 2 Step 3 Step 4 Step 5 Finalresult
Quarterly average hit rate of multibaggers (%, since 2010)
Hig
her
prof
itab
ility
(N
2Y a
vg R
OE)
Hig
her
grow
th
(L3Y
EPS
Cag
r)
Hig
her
R&
D, SG
&A a
ndov
erse
as e
xpos
ure
Avo
id la
rge
caps
(Mar
ket
cap
< U
S$5
bn)
Avo
id m
id c
aps
(Mar
ket
cap
< U
S$1
bn)
Post-GFC, our strategy boosts the hit rate from
10.3% to 21.8%
Our strategy increases the multibagger hit rate
from 14.6% to 22.1%
Strategy works across most markets and sectors
(see Appendix 1)
We combine the industry-specific and generic
drivers to formulate our multibagger strategy
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 43
Asian potential multi-baggers Our research suggests that small-to-mid cap companies with a tangible earnings growth record and higher profitability are more likely to turn into multibaggers. Larger R&D budgets, higher SG&A (including advertisement) spending and focus on overseas markets are the additional signals of strong growth potential for specific industries and markets. We also apply our EQRS/BQRS scores to eliminate companies with earnings-quality and balance-sheet-quality risk; and use our Benford scores to remove companies with potentially manipulated financial statements.
These quantitative checks yield a list of almost 280 Asian stocks with US$100m-US$5bn market cap and a daily turnover of more than US$1m. However, given that finding multibaggers is not just a quantitative exercise, we apply our discretion to identify certain stocks that may have been missed out due to borderline factor values. We also use discretion to remove stocks where the factors are impacted by one-off numbers and where the price action suggests deeper issues that are not captured in the reported financial statements. This exercise leaves us roughly 150 candidates to choose from. We then do a very high-level thematic check and deeper data checks to identify the top-50 candidates for our multibaggers portfolio.
The broad quantitative criteria are summarised below but there are a few exceptions to these rules:
Universe: Broader Asia Pacific ex-Japan companies with US$100m-US$5bn market cap and average daily turnover of more than US$1m.
Strong growth: Last three-year EPS Cagr and next two-year EPS Cagr of more than 15%.
Robust profitability: Next two-year average ROE more than 15%.
Industry/market specific drivers: R&D & SG&A spend higher than relevant industries and high overseas exposure for relevant markets.
Balance sheet and quality checks: Net gearing less than 75% and does not fail our EQRS/BQRS/Benford checks.
Below we highlight the price performance and the relevant characteristics of these stocks compared to the overall Asian universe. The universe has strong price and earnings momentum, along with good profitability, free cashflow and solid balance sheets.
Figure 82 Figure 83
Microstrategy multibagger picks: Historical returns Multibagger picks: Characteristics analysis
Note: Performance is US$ total return using freefloat adjusted market cap weights and monthly rebalancing. Characteristics analysis data is based on median values. Source: Factset, CLSA
90
140
190
240
290
340
390
440
490
540
Dec
11
Jun
12
Dec
12
Jun
13
Dec
13
Jun
14
Dec
14
Jun
15
Dec
15
Jun
16
Dec
16
Jun
17
Asian potential multibaggers
MSCI APxJ
Cumulative index (FF adj mcap-wtd, US$ TR, x)
38.9% Cagr
8.9% Cagr
0.5
1.0
1.5
2.0
2.5
3.0
EPSg
(L3Y
)R
&D
/sal
esEP
S r
evL1
Y re
turn
PB (
trl)
RO
ICEP
Sg
(N2Y
)C
ash/
TASus
tgR
OE
(N2Y
)SG
&A/
sale
sPE
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Asian potential multibaggers vs MSCI APxJ(x)
Factor checks to identify potential candidates
Going beyond just the quantitative checks to
narrow down to 50 picks
Specific criteria used to identify multi-baggers -
focus on growth, profitability and quality
Strong momentum and characteristics for our
chosen picks
Section 2: A multibagger framework Microstrategy
44 [email protected] 6 September 2017
Key Asian potential multi-baggers Figure 84
Asian potential multibaggers (sorted by last three-years EPS Cagr) Code Name Cty Sector Mkt cap FY1-FY2 L3Y EPS R&D/ SG&A/ Foreign 12MF FY1-FY2 NDE TR (US$m) ROE Cagr sales sales sls exp PE EPS Cagr (latest, (L12M,
(avg, %) (%) (FY0, %) (%) (x) (%) %) %) China & HK 1302 HK LifeTech Sci CN Healthcare 950 21.1 81.7 16.3 37.7 19.6 35.8 68.3 (51.3) 16.2 1548 HK Genscript Biotech CN Pharma 932 16.4 44.2 8.3 36.2 81.1 28.5 15.5 (76.8) 181.3 2869 HK Greentown Service CN Comm svcs 1,608 23.4 42.4 na 7.6 0.0 23.0 22.3 (126.9) 64.0 1558 HK YiChang HEC CN Pharma 1,109 18.0 35.4 6.8 26.5 0.0 12.7 28.1 (45.7) 11.5 6068 HK Wisdom Education CN Cons svcs 763 17.0 30.3 na 15.3 0.0 15.2 29.1 (26.1) 89.5 520 HK Xiabuxiabu Catering CN Cons svcs 1,101 22.4 26.5 na 40.8 0.0 15.7 15.2 (87.2) 117.3 1316 HK Nexteer HK Autos 4,188 27.7 26.0 3.2 3.4 100.0 11.2 14.0 1.3 23.5 425 HK Minth CN Autos 4,897 18.6 19.5 4.2 11.3 38.0 13.8 21.0 (14.1) 29.5 India MNDA IN Minda IN Autos 954 22.6 187.3 1.7 13.2 20.2 25.3 29.0 7.3 206.8 VKI IN Vakrangee IN Software 3,707 28.8 69.9 na 1.1 0.0 33.4 20.2 (23.0) 139.7 CANF IN Can Fin Homes IN Banks 1,159 23.9 37.4 nm nm nm 22.0 27.9 nm 87.6 WHIRL IN Whirlpool IN Cons dur 2,353 23.1 36.2 0.9 24.6 7.9 35.1 24.8 nm 28.0 EDEL IN Edelweiss Fin svcs IN Div fin 3,231 18.1 34.4 nm nm nm 21.7 37.7 nm 116.2 TELX IN Tata Elxsi IN Software 798 32.9 33.8 1.4 53.8 84.8 22.1 21.8 (45.0) 2.3 VGRD IN V-Guard IN Cap gds 1,180 25.1 28.3 0.4 18.3 0.0 38.6 21.8 (16.0) 48.0 ABB IN ABB India IN Cap gds 4,467 15.3 28.0 3.5 8.7 14.5 48.0 31.1 (29.4) 16.9 NFIL IN Navin Fluorine IN Materials 512 17.1 27.9 1.9 20.2 na 22.5 21.8 (7.1) 45.1 PVRL IN PVR IN Media 934 16.0 17.7 na 41.1 0.0 33.5 46.7 72.5 6.0 Korea 147760 KS Microfriend KR Semis 111 22.7 64.1 4.2 6.6 0.0 9.6 40.4 (47.0) 84.9 145020 KS Hugel KR Pharma 1,569 19.4 56.8 3.3 20.4 0.0 24.9 34.2 (46.3) 23.1 041830 KS InBody KR Healthcare 355 20.0 40.0 6.7 36.8 76.7 17.5 21.1 (46.4) (16.0) 083310 KS LOT Vacuum KR Semis 181 24.4 39.0 5.1 18.3 0.0 8.3 74.6 1.3 13.8 089590 KS Jeju Air KR Transport 896 25.5 31.6 na 11.7 0.0 11.0 35.1 (113.3) 27.7 098460 KS Koh Young Tech KR Semis 726 20.0 28.7 10.8 31.2 91.9 21.5 17.1 (45.5) 41.0 048260 KS Osstem Implant KR Healthcare 852 23.6 27.4 2.4 46.3 0.0 26.9 40.2 63.3 19.7 089600 KS Nasmedia KR Media 386 20.8 24.9 1.7 74.3 0.0 17.1 48.3 (24.3) 23.1 Taiwan 4968 TT Richwave Tech TW Semis 204 25.5 101.2 10.6 12.5 56.2 21.2 51.2 (49.9) 98.1 5269 TT Asmedia Tech TW Semis 599 36.8 58.2 20.7 6.1 43.2 21.1 66.4 (76.1) 61.5 2723 TT Gourmet Master TW Cons svcs 1,973 23.4 44.7 0.1 47.2 81.6 25.3 20.1 (62.2) 35.9 8436 TT TCI TW HPC 507 21.2 40.3 5.1 16.3 65.5 19.8 26.9 (41.3) 46.8 5274 TT ASPEED Tech TW Semis 789 34.1 36.0 10.6 6.7 61.1 29.8 38.7 (60.2) 81.8 4919 TT Nuvoton Tech TW Semis 365 24.1 33.3 26.6 7.1 96.9 12.0 28.4 (53.3) 47.0 1536 TT Hota Industrial TW Autos 1,156 29.7 30.6 2.5 10.4 95.4 21.0 21.1 31.6 (13.5) 4551 TT Global PMX TW Autos 450 21.8 28.6 2.0 7.1 97.8 18.8 26.2 11.2 26.1 5306 TT KMC TW Cons dur 544 23.9 24.5 0.7 14.7 97.4 14.7 16.4 22.7 26.5 2421 TT Sunonwealth TW Cap gds 456 22.3 23.2 5.7 10.3 100.0 13.5 39.9 (12.4) 120.3 3152 TT Advanced Ceramic TW Tech HW 849 29.6 19.4 5.1 5.8 81.7 24.3 18.4 (88.4) 130.3 3665 TT Bizlink TW Cap gds 876 22.2 10.8 2.5 16.0 96.4 18.1 30.7 (21.2) 30.2 Asean markets PPRO IJ PP Properti ID Property 970 na 61.9 na 2.4 0.0 27.2 16.4 30.4 2.6 SRIL IJ Sritex ID Cons dur 490 17.0 61.0 na 4.9 52.5 5.9 17.0 137.3 32.0 MYEG MK My E.G. Services MY Software 1,758 41.0 58.7 na 21.7 0.0 26.9 36.9 (10.9) 51.2 BEAUTY TB Beauty Community TH Retail 1,236 72.7 46.5 na 35.6 0.0 36.0 37.0 (77.8) 50.7 MTLS TB Muangthai Leasing TH Div fin 2,071 30.9 44.0 nm nm nm 23.7 48.0 nm 76.3 LINK IJ PT Link Net Tbk ID Telecom 1,152 22.7 31.7 na 20.2 0.0 14.2 19.8 (9.0) 8.5 JMT TB JMT Network Svcs TH Comm svcs 338 17.3 17.7 na 37.4 0.0 28.3 69.9 nm 106.6 SCC PM Semirara Mining PH Energy 3,518 37.1 17.0 na 12.9 0.0 11.1 17.6 31.6 60.6 8002 HK IGG SG Software 2,132 57.3 10.1 11.2 32.2 100.0 10.7 72.6 (93.9) 218.0 Australia & New Zealand BWX AU BWX AU HPC 400 21.1 467.2 1.2 28.0 20.0 21.6 48.7 51.3 17.9 ATM NZ a2 Milk NZ FBT 2,628 47.7 75.2 0.8 17.5 20.0 29.1 47.3 (62.2) 170.8 ALU AU Altium AU Software 888 27.0 25.6 13.6 49.1 100.0 25.3 23.8 (27.6) (0.8) Note: For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Total return is based on local currency. Source: Factset, CLSA
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 45
Understanding the multibagger picks Below we highlight the business description of the top multibagger picks, especially the qualitative statements that support the continued presence of important multibagger characteristics such as focus on R&D/SG&A spend, rising overseas exposure or high market growth. We also highlight the EPS trend for the past five and the next three years (where the relevant history and forecasts are available). Most of our picks have steadily rising earnings growth, which has been a hallmark of multibaggers in the past.
Figure 85
Asian potential multi-baggers: Main growth theme, supporting drivers and EPS trends
Note: EPS trend is based on non-GAAP adjusted earnings per share. Source: CLSA, Factset
Code Name Description R&D SG&A Overseas EPS trendexposure (11A-19F)
China & HK
1302 HK LifeTech Sci¹ Strong R&D spender in the cardiovascular-diseases-related products. Products getting approval across the world, which could lead to growing exports.
1548 HK Genscript Biotech
Originally based in New Jeresy, its main focus is biological research services (DNA sequencing, etc) but it is also increasing its footprint in cancer cures. Higher R&D and advertising spending, plus rising sales in China could drive future growth.
2869 HK Greentown ServiceTop-rated property-management services, property-consulting and community-services company in China benefitting from rising demand for premium residential services.
1558 HK YiChang HECA rising player in the China drug manufacturing market with 33 pharma products. One of its product, Kewei (oseltamivir phosphate), has been the No.1 selling influenza drug in China from 2013 to 2016.
6068 HK Wisdom EducationLargest provider of private education in South China operating premium primary and secondary schools (high margin), as measured by student enrolment as of 1 Sep 2015, according to the Frost & Sullivan Report.
520 HK Xiabuxiabu CateringRestaurant company with chains in 30-plus cities in China that is upgrading and expanding its network as well as entering several new concept areas in the dining business.
1316 HK NexteerSteering and driveline-systems company with a global footprint. Customers include BMW, FCA, Ford, GM, PSA, Toyota, VW and automakers in India and China. It is also one of the beneficiaries of autonomous driving theme.
425 HK Minth China’s leading auto-bodyparts supplier with growing export sales (with higher margin) due to substantially lower cost base compared to its Japanese peers.
Korea
147760 KS Microfriend Top MEMS (Micro Electro Mechanical System) specialist company with strong FCF.
145020 KS HugelBotox manufacturer controlling 30% of the botox market, a lucrative industry in Korea due to rising domestic demand for dermatology and cosmetic surgery as well as the increasing popularity of cosmetic-surgery tourism.
041830 KS InBodyAccounts for 90% of domestic and 60% of global body-composition analysis market with a well-diversified overseas exposure. It is launching new products (such as InBody watch) and targeting the IoT-based healthcare market.
083310 KS LOT Vacuum Provision of dry vaccum pumps for semiconductor manufacturing with strong R&D growth.
089590 KS Jeju Air
Biggest LCC by market share in Korea. Benefitted from the lifestyle changes as more Koreans are preferring to travel overseas using lower cost airlines. Low exposure to THAAD issue as only a small percentage of revenue is from Chinese charter flights.
098460 KS Koh Young Tech A global leader in 3D measurement technology for electronics assembly with a stable growth profile and increasing sales exposure to the US and Europe.
048260 KS Osstem ImplantOne of the key players in the global dental implant and prosthetic market. According to the report by Market Research Future, the market is expected to post a 4.6% Cagr from 2015-22 with Apac being the fastest-growing region.
089600 KS NasmediaTop digital media rep agency in Korea with 20% market share. High exposure to the fast-growing online mobile advertising with 71% of total revenue coming from the segment.
Our multibagger picks have steadily rising EPS
Section 2: A multibagger framework Microstrategy
46 [email protected] 6 September 2017
Figure 86
Asian potential multi-baggers: Main growth theme, supporting drivers and EPS trends (continued)
Source: CLSA, Factset
Code Name Description R&D SG&A Overseas EPS trendexposure (11A-19F)
India
MNDA IN MindaTier-1 electrical-autoparts supplier to OEM with global presence. International clients include Toyota, BMW, Honda, Volkswogen, Ford, Piaggio along with all major domestic Indian autos companies.
VKI IN VakrangeeE-governance/digital is a growing business segment in India and the company has a vast network of retail acces points to deliver financial and other G2C services to unserved rural, semi-urban and urban markets.
CANF IN Can Fin Homes
Small but rising player in the fast-growing housing-finance market in India with loan book enjoying a 32% Cagr since 2014. 75% of loan book coming from Salaried & Professional segment with low overall gross NPA ratio at 0.38%.
WHIRL IN Whirlpool Leading manufacturers and marketers of major home appliances in India with a strong brand focus.
EDEL IN Edelweiss Fin svcsLeading diversified financial services (capital markets) in India with growing market share as evidenced by rising profits even during the volatile equity market periods of 2012-14.
TELX IN Tata ElxsiEngaged in product design and engineering; and system integration and support services for enterprise customers. It has also ventured into emerging tech such as IoT, Virtual Reality, Big data, Cloud, AI etc.
VGRD IN V-Guard Electronic and electro mechanical product company with a strong brand presence in India and it is further boosting its marketing and R&D expenses.
ABB IN ABB IndiaPart of the ABB group, it manufactures and distributes products for power systems, generation and automation in India. It's a play on improving quality of Indian power grids and networks.
NFIL IN Navin FluorineIndia's largest integrated specialty fluorochemical company. Fluorochemicals is a high-growth industry mostly due to focus on underpenetrated products such as air conditioning, refrigration, autos, pharma etc.
PVRL IN PVRPVR, the largest movie multiplex company in India, has a strong brand image, right locations and leadership in key markets/box-office circuits. Strong industry outlook led by an under-screened market and growing consolidation.
Asean markets
PPRO IJ PP Properti
Property subsidiary of PT PP (60% ownership) and is newly listed in 2015. Large increase in bookings this year due to new projects. Landbank increase to 280ha versus 70ha last year, which should translate into more new projects.
SRIL IJ SritexAsean's largest vertically-integrated textile and garment manufacturer. The garments OEM segment is lucrative supported by military uniform orders from UAE, EU and NATO; global fashion lines such as Guess, H&M, Disney and Lee.
MYEG MK My E.G. ServicesMalaysia's sole provider of government e-services. Its broad strategy focuses on going into services where there is a renewal requirement on a regular basis, leading to recurring cashflow.
BEAUTY TB Beauty CommunityCosmetics company with a focus on beauty, personal care, skincare and makeup. Thailand's personal-care market is growing at 6-7% but the company's topline is growing by more than 30%.
MTLS TB Muangthai LeasingVast potential in micro-lending should support growth. The farming sector accounts for 40% of Muangthai's loan book, and it could benefit from rising government support for the agri sector.
LINK IJ PT Link Net TbkCable TV and internet broadband provider operating in several major cities including Jakarta. Low broadband penetration in Indonesia could remain supportive of growth.
JMT TB JMT Network SvcsThailand's biggest bad-debt collection company and beneficiary of the rising NPLs in the sytem. It can expand into neighbouring countries using partners who do not have such services.
SCC PM Semirara MiningLargest coal producer in the Philippines. The company has ventured into power generation primarily to take advantage of the cost and operational synergies between the two businesses.
8002 HKIGG
(Singapore stock)
A play on the global gaming market with geographically well-diversifed revenue, and two big hit games titled Lords Mobile and Castle Clash. It has >380m registered users with about 17m monthly active users across over 200 countries.
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 47
Figure 87
Asian potential multi-baggers: Main growth theme, supporting drivers and EPS trends (continued)
Source: CLSA, Factset
Code Name Description R&D SG&A Overseas EPS trendexposure (11A-19F)
Taiwan
4968 TT Richwave TechIC development and design with focus on WiFi and is foraying into IoT, smarthome, automotives etc. It benefits from rising WiFi demand and its growing R&D budget should keep the product pipeline strong.
5269 TT Asmedia Tech A USB play with first SuperSpeed USB 3.1 (10Gbps) technology. Very high R&D budget, could be industry leader.
2723 TT Gourmet MasterSince its establishment in 2004, Gourmet Master's 85C café brand has grown to become the largest coffee house/bakery in Taiwan. It also aggresively expanding its coffee brand in China and the USA.
8436 TT TCI
Bioscience company with dietary suppliements, function drinks and skincare products. Strong R&D focus to help with new product development and it has a high China exposure (including a China plant) along with exports to 41 countries.
5274 TT ASPEED Tech Fabless IC-design company and with an increased focus on Cloud business and strong R&D budget.
4919 TT Nuvoton TechCompany engaging in R&D and sales of IC products and provision of wafer foundry services with lot of new product successes. It has also launched an IoT solution.
1536 TT Hota Industrial
Leading automotive-transmission-system partsmaker in Taiwan and sole supplier of gearboxes to Tesla. Its inhouse equipment supports high precision and flexibility, and has helped secure orders from BorgWarner, Tesla and Eaton.
4551 TT Global PMX
High-precision mechanical autoparts maker in Taiwan, focusing on engine parts and ABS/ESC parts. With GDI parts, it rides the structural trend of better fuel economy and lower gas emissions, boasting a strong overseas customer base.
5306 TT KMCKMC is the largest bicycle-chain manufacturer globally, with a market share of 70-80%. It has a close relationships with its brand customers and is the only supplier offering a wide range of products from low- to high-speed chain.
2421 TT Sunonwealth
Strong R&D focus in core motor technology with numerous patents and industry-leading products such as the first magnetic levitation motor fan (Maglev), smallest /thinnest fan (Mighty Mini) in the world, thermal modules for LED panels, etc.
3152 TT Advanced CeramicIntegrated device manufacturer (IDM) that designs & manufactures LTCC components/filters used in all connectivity devices. Benefits from rising connectivity and RF content increases in 4G+/5G smartphones and WiFi MIMO.
3665 TT BizlinkWiring-harness and cable-assemblies manufacturer and the sole supplier of wiring harnesses for Tesla’s battery-management systems, Superchargers, Powerwall and Powerpack. It is expanding its automotive business in Europe.
Australia & New Zealand
BWX AU BWX
A natural skincare products and distribution company with strong export growth in the UK, China and Canada. It owns a successful brand (Sukin) in its home market and just bought "Mineral Fusion", the No.1 natural cosmetics brand in USA.
ATM NZ a2 MilkThe pioneer producer of milk with natural A2 protein with rising sales in AU/NZ and China. It is the leading premium fresh milk brand in Australian supermarkets, with a grocery value market share of approximately 9.3%.
ALU AU AltiumDesign and engineering software company with strong R&D spending and well-distributed global earnings with growth across USA and EM (especially China). One of the peers (Cadence) has a market cap of US$10bn.
Section 2: A multibagger framework Microstrategy
48 [email protected] 6 September 2017
Earnings quality (EQRS) check for multibagger picks Our earnings-quality-risk scores (EQRS) focuses on five fundamental issues that determine the earnings quality of stocks. A score of 4/5 or 5/5 suggests higher risk. However, none of our multibagger picks have such a high-risk score.
Figure 88
Asian potential multi-baggers based on earnings-quality risk score (EQRS) Code Name Cty Sector Mkt cap Rising Burning cash Capex Rising Poor cash EQRS (US$m) working (Op CF or indiscipline noncore/ conversion score capital FCF level) intangibles China & HK 1302 HK LifeTech Sci CN Healthcare 950 1 0 0 0 0 1/5 1548 HK Genscript Biotech CN Pharma 932 1 0 0 1 1 3/5 2869 HK Greentown Service CN Comm svcs 1,608 0 0 1 0 1 2/5 1558 HK YiChang HEC CN Pharma 1,109 0 0 1 1 0 2/5 6068 HK Wisdom Education CN Cons svcs 763 0 0 0 0 0 0/5 520 HK Xiabuxiabu Catering CN Cons svcs 1,101 0 0 0 0 0 0/5 1316 HK Nexteer HK Autos 4,188 0 0 1 1 0 2/5 425 HK Minth CN Autos 4,897 1 0 0 0 0 1/5 India MNDA IN Minda IN Autos 954 0 0 0 0 0 0/5 VKI IN Vakrangee IN Software 3,707 1 0 0 0 0 1/5 WHIRL IN Whirlpool IN Cons dur 2,353 1 0 0 1 0 2/5 TELX IN Tata Elxsi IN Software 798 1 0 0 0 1 2/5 VGRD IN V-Guard IN Cap gds 1,180 0 0 1 0 0 1/5 ABB IN ABB India IN Cap gds 4,467 0 0 0 1 0 1/5 NFIL IN Navin Fluorine IN Materials 512 0 0 1 0 0 1/5 PVRL IN PVR IN Media 934 1 0 1 1 0 3/5 Korea 147760 KS Microfriend KR Semis 111 1 0 1 0 0 2/5 145020 KS Hugel KR Pharma 1,569 1 0 0 0 0 1/5 041830 KS InBody KR Healthcare 355 1 0 1 0 0 2/5 083310 KS LOT Vacuum KR Semis 181 0 1 1 0 0 2/5 089590 KS Jeju Air KR Transport 896 0 0 1 1 0 2/5 098460 KS Koh Young Tech KR Semis 726 1 0 1 0 0 2/5 048260 KS Osstem Implant KR Healthcare 852 0 0 1 1 1 3/5 089600 KS Nasmedia KR Media 386 0 0 0 1 0 1/5 Taiwan 4968 TT Richwave Tech TW Semis 204 0 0 1 0 0 1/5 5269 TT Asmedia Tech TW Semis 599 1 0 0 0 1 2/5 2723 TT Gourmet Master TW Cons svcs 1,973 1 0 1 0 0 2/5 8436 TT TCI TW HPC 507 0 0 1 0 0 1/5 5274 TT ASPEED Tech TW Semis 789 1 0 1 1 0 3/5 4919 TT Nuvoton Tech TW Semis 365 0 0 1 0 1 2/5 1536 TT Hota Industrial TW Autos 1,156 0 0 1 0 0 1/5 4551 TT Global PMX TW Autos 450 0 0 1 0 0 1/5 5306 TT KMC TW Cons dur 544 1 0 1 0 0 2/5 2421 TT Sunonwealth TW Cap gds 456 1 0 1 0 1 3/5 3152 TT Advanced Ceramic TW Tech HW 849 0 0 0 0 0 0/5 3665 TT Bizlink TW Cap gds 876 0 0 1 0 0 1/5 Asean markets PPRO IJ PP Properti ID Property 970 1 1 0 0 1 3/5 SRIL IJ Sritex ID Cons dur 490 0 1 0 0 0 1/5 MYEG MK My E.G. Services MY Software 1,758 0 0 1 0 1 2/5 BEAUTY TB Beauty Community TH Retail 1,236 0 0 0 0 1 1/5 LINK IJ PT Link Net Tbk ID Telecom 1,152 1 0 0 0 0 1/5 SCC PM Semirara Mining PH Energy 3,518 0 0 0 1 0 1/5 8002 HK IGG SG Software 2,132 0 0 1 0 0 1/5 Australia & New Zealand BWX AU BWX AU HPC 400 1 0 0 0 0 1/5 ATM NZ a2 Milk NZ FBT 2,628 0 0 1 0 1 2/5 ALU AU Altium AU Software 888 1 0 1 0 1 3/5 Source: Factset, CLSA
None of the multibaggers have poor earnings
quality based on EQRS
Section 2: A multibagger framework Microstrategy
6 September 2017 [email protected] 49
Balance sheet quality (BQRS) check for multibagger picks Our balance-sheet-quality risk scores (BQRS) focus on five fundamental issues that determine the balance-sheet quality of stocks. A score of 4/5 or 5/5 suggests a higher risk. However, none of our multibagger picks have such a high-risk score.
Figure 89
Asian potential multibaggers based on balance-sheet-quality-risk score Code Name Cty Sector Mkt cap Liquidity Frequent Excessive Burning cash Operational BQRS (US$m) concerns fundraising leverage (Op CF or FCF level) stress score China & HK 1302 HK LifeTech Sci CN Healthcare 950 0 0 0 0 0 0/5 1548 HK Genscript Biotech CN Pharma 932 0 0 0 0 0 0/5 2869 HK Greentown Service CN Comm svcs 1,608 0 0 0 0 0 0/5 1558 HK YiChang HEC CN Pharma 1,109 0 0 0 0 0 0/5 6068 HK Wisdom Education CN Cons svcs 763 0 0 0 0 0 0/5 520 HK Xiabuxiabu Catering CN Cons svcs 1,101 0 0 0 0 0 0/5 1316 HK Nexteer HK Autos 4,188 0 0 0 0 0 0/5 425 HK Minth CN Autos 4,897 0 0 0 0 1 1/5 India MNDA IN Minda IN Autos 954 0 0 0 0 0 0/5 VKI IN Vakrangee IN Software 3,707 0 0 0 0 0 0/5 WHIRL IN Whirlpool IN Cons dur 2,353 0 0 0 0 1 1/5 TELX IN Tata Elxsi IN Software 798 0 0 0 0 1 1/5 VGRD IN V-Guard IN Cap gds 1,180 0 0 0 0 0 0/5 ABB IN ABB India IN Cap gds 4,467 0 0 0 0 0 0/5 NFIL IN Navin Fluorine IN Materials 512 0 0 0 0 1 1/5 PVRL IN PVR IN Media 934 0 0 0 0 1 1/5 Korea 147760 KS Microfriend KR Semis 111 0 0 0 0 1 1/5 145020 KS Hugel KR Pharma 1,569 0 0 0 0 1 1/5 041830 KS InBody KR Healthcare 355 0 0 0 0 1 1/5 083310 KS LOT Vacuum KR Semis 181 1 0 0 1 0 2/5 089590 KS Jeju Air KR Transport 896 0 0 0 0 0 0/5 098460 KS Koh Young Tech KR Semis 726 0 0 0 0 0 0/5 048260 KS Osstem Implant KR Healthcare 852 0 0 1 0 0 1/5 089600 KS Nasmedia KR Media 386 1 0 1 0 0 2/5 Taiwan 4968 TT Richwave Tech TW Semis 204 0 0 0 0 0 0/5 5269 TT Asmedia Tech TW Semis 599 0 0 0 0 1 1/5 2723 TT Gourmet Master TW Cons svcs 1,973 0 0 0 0 1 1/5 8436 TT TCI TW HPC 507 0 0 0 0 0 0/5 5274 TT ASPEED Tech TW Semis 789 0 0 0 0 1 1/5 4919 TT Nuvoton Tech TW Semis 365 0 0 0 0 0 0/5 1536 TT Hota Industrial TW Autos 1,156 0 0 1 0 0 1/5 4551 TT Global PMX TW Autos 450 0 0 0 0 0 0/5 5306 TT KMC TW Cons dur 544 1 0 1 0 0 2/5 2421 TT Sunonwealth TW Cap gds 456 0 0 1 0 0 1/5 3152 TT Advanced Ceramic TW Tech HW 849 0 0 0 0 0 0/5 3665 TT Bizlink TW Cap gds 876 0 0 0 0 0 0/5 Asean markets PPRO IJ PP Properti ID Property 970 0 0 1 1 0 2/5 SRIL IJ Sritex ID Cons dur 490 0 0 1 1 1 3/5 MYEG MK My E.G. Services MY Software 1,758 0 0 0 0 0 0/5 BEAUTY TB Beauty Community TH Retail 1,236 0 0 0 0 0 0/5 LINK IJ PT Link Net Tbk ID Telecom 1,152 0 0 0 0 1 1/5 JMT TB JMT Network Svcs TH Comm svcs 338 0 0 0 1 1 2/5 SCC PM Semirara Mining PH Energy 3,518 0 0 0 0 0 0/5 8002 HK IGG SG Software 2,132 0 0 0 0 0 0/5 Australia & New Zealand BWX AU BWX AU HPC 400 0 0 1 0 1 2/5 ATM NZ a2 Milk NZ FBT 2,628 0 0 0 0 0 0/5 ALU AU Altium AU Software 888 0 0 0 0 0 0/5 Source: Factset, CLSA
None of the multibaggers have poor balance sheet
quality based on BQRS
Section 2: A multibagger framework Microstrategy
50 [email protected] 6 September 2017
Benford (fraud detection) check for multibagger picks Benford analysis follows the law of first digit and is violated when numbers are manipulated or forced to deviate from their natural results. None of our stocks fail the Benford test, where a goodness-of-fit p-value below 0.05 for the financials statements’ first digit distribution suggests nonconformity.
Figure 90
Asian potential multi-baggers: First digit distribution conformity to Benford’s Law Code Name Cty Sector Mkt Cap
(US$m) Fiscal
year Goodness-of-fit test
p-value
Data pts
Absolute deviation from Benford's distribution 1
(%) 2
(%) 3
(%) 4
(%) 5
(%) 6
(%) 7
(%) 8
(%) 9
(%) China & HK
1302 HK LifeTech Sci CN Healthcare 950 06/17 0.66 88 1.7 2.8 3.4 0.5 1.2 2.4 0.1 4.0 1.1
1548 HK Genscript Biotech CN Pharma 932 12/16 0.36 103 10.7 6.0 0.1 2.9 3.1 2.0 0.9 0.7 0.7
2869 HK Greentown Service CN Comm svcs 1,608 06/17 0.12 90 7.7 2.1 4.7 0.8 1.3 1.1 2.5 6.0 1.2
1316 HK Nexteer HK Autos 4,188 06/17 0.36 103 8.7 0.1 1.1 0.0 0.8 2.0 2.0 4.6 1.7
425 HK Minth CN Autos 4,897 06/17 0.15 95 10.1 1.3 3.3 1.9 1.6 1.7 4.7 2.3 2.8 India
MNDA IN Minda IN Autos 954 03/17 0.45 81 3.2 6.5 1.4 2.3 2.0 0.5 0.4 1.1 4.1
ABB IN ABB India IN Cap gds 4,467 06/17 0.15 90 5.7 4.6 7.5 3.6 3.5 1.1 1.4 1.8 2.4
Korea
147760 KS Microfriend KR Semis 111 06/17 0.84 192 0.1 4.8 2.6 2.9 0.9 0.4 1.5 0.6 2.0
145020 KS Hugel KR Pharma 1,569 06/17 0.72 249 1.6 1.9 0.0 3.2 0.9 2.9 2.2 1.3 2.6
041830 KS InBody KR Healthcare 355 06/17 0.67 229 7.9 4.5 0.6 1.8 1.3 1.0 3.2 0.1 0.7
083310 KS LOT Vacuum KR Semis 181 06/17 0.30 250 2.7 3.6 3.3 1.5 3.1 1.7 1.4 5.3 0.2
089590 KS Jeju Air KR Transport 896 06/17 0.16 229 3.9 7.7 3.3 2.3 0.1 2.8 1.9 4.5 2.0
098460 KS Koh Young Tech KR Semis 726 06/17 0.82 253 1.2 1.4 0.5 4.1 2.8 1.2 2.6 0.8 0.2
048260 KS Osstem Implant KR Healthcare 852 06/17 0.07 276 0.4 2.8 2.3 4.4 4.7 2.0 0.4 6.5 0.9
089600 KS Nasmedia KR Media 386 06/17 0.89 191 4.5 1.4 1.0 1.8 1.0 2.0 1.0 2.0 2.0
Taiwan
4968 TT Richwave Tech TW Semis 204 06/17 0.14 194 4.8 6.3 2.7 5.8 3.4 3.1 0.6 3.1 1.0
5269 TT Asmedia Tech TW Semis 599 06/17 0.93 201 1.2 0.3 1.9 0.7 0.5 2.3 2.8 1.6 0.1
2723 TT Gourmet Master TW Cons svcs 1,973 06/17 0.15 265 10.1 5.0 0.4 2.1 1.9 2.7 2.1 4.7 0.0
8436 TT TCI TW HPC 507 06/17 0.87 254 5.3 2.5 3.0 1.8 0.7 0.4 0.7 2.4 1.0
5274 TT ASPEED Tech TW Semis 789 06/17 0.72 201 7.2 1.8 3.9 1.2 0.0 0.8 0.8 0.1 2.9
4919 TT Nuvoton Tech TW Semis 365 06/17 0.94 214 0.2 3.4 2.0 0.3 1.0 1.1 1.6 2.3 0.8
1536 TT Hota Industrial TW Autos 1,156 06/17 0.84 235 2.2 1.0 1.1 3.7 1.5 0.1 1.1 3.0 1.0
4551 TT Global PMX TW Autos 450 06/17 0.21 214 3.9 4.1 0.1 2.9 1.9 5.9 3.9 0.0 1.0
5306 TT KMC TW Cons dur 544 06/17 0.36 245 3.0 7.8 1.1 0.9 0.6 4.7 0.9 0.6 2.4
2421 TT Sunonwealth TW Cap gds 456 06/17 0.98 232 2.5 2.2 1.3 0.6 0.6 2.4 0.6 1.7 0.2
3152 TT Advanced Ceramic TW Tech HW 849 06/17 0.29 172 4.2 1.6 5.5 0.4 0.2 4.4 4.1 1.0 1.7
3665 TT Bizlink TW Cap gds 876 06/17 0.71 264 0.6 2.5 1.1 0.2 5.7 0.3 1.6 0.6 1.2
Asean markets
PPRO IJ PP Properti ID Property 970 06/17 0.97 167 3.4 2.0 0.1 0.1 1.7 1.9 0.4 0.9 1.6
SRIL IJ Sritex ID Cons dur 490 06/17 0.91 164 0.4 1.1 1.5 0.7 4.3 0.6 0.3 1.6 0.9
MYEG MK My E.G. Services MY Software 1,758 06/17 0.16 168 0.3 6.3 4.2 7.6 0.4 0.7 0.4 3.2 0.8
BEAUTY TB BeautyCommunity TH Retail 1,236 06/17 0.87 189 2.1 2.0 0.3 1.4 1.6 2.8 1.0 2.5 1.2
LINK IJ PT Link Net Tbk ID Telecom 1,152 06/17 0.32 169 2.9 4.6 0.5 5.7 3.3 0.8 1.3 0.8 3.4
JMT TB JMT Network Svcs TH Comm svcs 338 06/17 0.73 181 5.3 2.8 0.3 2.0 1.8 4.5 0.3 0.4 0.4
SCC PM Semirara Mining PH Energy 3,518 06/17 0.34 183 1.0 8.3 1.7 2.6 2.5 3.7 1.9 1.3 1.4
Australia & New Zealand
ATM NZ a2 Milk NZ FBT 2,628 06/17 0.79 85 0.7 0.0 4.0 0.9 0.3 0.4 0.1 3.9 1.0
ALU AU Altium AU Software 888 06/17 0.65 90 3.4 3.5 2.0 0.8 1.0 1.1 4.7 1.6 0.1
Note: The first-digit distribution is calculated using a combination of standardised accounting items from P&L, balance sheet, and cashflow statement of the last four quarters (or the last two semi-annuals). Absolute deviation of 5% or more from Benford’s Law for any digit is highlighted in bold. We have excluded stocks with less than 80 data points to avoid noise in the p-value. Source: CLSA, Factset
Our multibagger picks pass the Benford test
Section 3: Price of sustainable growth Microstrategy
6 September 2017 [email protected] 51
Price of sustainable growth Our main multibagger strategy uses historical earnings growth to identify companies in growing businesses. We have also shown that consensus-growth forecasts are not as reliable. We believe this is largely due to two factors. Firstly, consensus numbers often prove inaccurate both at the company and aggregate level. Secondly, markets may already overprice the high-growth stocks. In this section, we focus on overcoming the overpricing and inaccuracy-related issues of high-growth-forecast stocks.
Stocks with high-growth potential trade at a premium . . . It is no surprise that high-growth stocks demand higher valuations. Companies with strong earnings growth (Q1 and Q2) have, on average, traded at 4.2% and 8.0% premiums to the region, while companies with low growth (Q4 and Q5) have traded at 4.5% and 5.3% discounts.
Figure 91
Broader Asia ex-Japan: Valuation of baskets based on earnings growth
Source: CLSA, Factset
. . . however, are attractively valued after adjusting for future growth Given their high valuations, such companies are generally avoided by value managers, which could then lead to missing quality investments that have attractive future growth profiles.
Figure 92
Asia ex-Japan: 12M fwd and 36M fwd PE of future growth quintiles
Source: CLSA, Factset
4.2
8.0
1.7
(4.5)(5.3)
(40)
(30)
(20)
(10)
0
10
20
30
40
(10)(8)(6)(4)(2)02468
10
Q1 (high) Q2 Q3 Q4 Q5 (low)
Quintiles based on next 2-year EPS growth
Avg valuation prem/disc (rel to region)
Average next 2-year EPS growth (RHS)
(%) (%)
High growth (Q1 & Q2) stocks are generally missed by value investors
given their premium valuations
61
(49.8)
(9.2)
3.3 13.5
55.7
(6)
(4)
(2)
0
2
4
6
8
10
(60)
(40)
(20)
0
20
40
60
80
Q1 (high) Q2 Q3 Q4 Q5 (low)
Quintiles based on next 2-year EPS growth
Pre/Disc based on 36M fwd PEPre/Disc based on 12M fwd PE (RHS)
(%) (%)
High growth stocks looks attractive afterfactoring in future growth
While the ones with low growth trade at discount
High growth stocks trade at premium to the region
However, after adjusting for future growth, high-
growth stocks look attractive on valuations
Expensive valuations and overoptimism two major challenges for the high-growth-forecast stocks
Section 3: Price of sustainable growth Microstrategy
52 [email protected] 6 September 2017
Delivery of growth is important, chances of disappointment are high Looking beyond the traditional valuation methodology to identify stocks with strong long-term growth potential, will help identify compelling investment opportunities. However, we recommend investors exercise caution while analysing these companies with high growth potential. Generally for such firms, consensus expectations are far too optimistic relative to their real growth potential. Our analysis in Figure 93 highlights that there is a clear disconnect between consensus growth expectations and the actual growth delivered by the company over that period. For instance, the baskets of companies that have been expected to deliver more than 25% annualised earnings growth have a median growth expectation of 38.7%. However, the basket actually delivered just a 23.9% earnings Cagr over the next three years. That translates into a 14.8ppt disappointment. Unsurprisingly, the degree of disappointment falls as the growth exceptions recede. Indeed, companies with negative growth expectations have a tendency to surprise positively.
Figure 93 Figure 94
APxJ: Median growth in each growth estimate bucket APxJ: Hit rate of meeting the expectations
Source: CLSA, Factset
Base effect reduces efficacy of history in predicting growth Against this backdrop, it is essential to identify factors that will help ascertain the growth potential with more conviction. Our analysis highlights that historical earnings growth has been a poor indicator of future growth due to the base effect. However, sustainable growth potential has been a far better signal to judge a company’s growth prospects.
Figure 95 Figure 96
APxJ: Median N3Y EPS growth for L3Y EPS gr ranges APxJ: Median N3Y EPS growth for sustainable gr ranges
Source: CLSA, Factset
(7.7)
5.7
12.4
17.4
22.3
38.7
21.3
(4.0)
2.7
7.3 10.7
14.3
23.9
13.6
(10)(5)05
10152025303540
<=0 0-10 10-15 15-20 20-25 >25 >10
Next 2-year EPS growth estimate range
Estimate (N2Y Cagr)
Actual delivered growth (N3Y Cagr)
EPS Cagr (median, %) 58.1
53.6
51.0
48.3
45
47
49
51
53
55
57
59
>10% >15% >20% >25%
Next 2-year EPS growth expectation of more than
Hit-rate of delivering promised growth(%)
58.1% of the companies met the expectations of delivering more than 10% growth over the next three years
13.9
6.3 6.7
8.8
5.8
4
6
8
10
12
14
16
Q1 (lowest) Q2 Q3 Q4 Q5 (highest)
Quintiles based on last-3-year EPS Cagr
Actual next-3-year EPS Cagr (median, %)
9.0
6.6 7.0
7.6
10.3
5
6
7
8
9
10
11
Q1 (lowest) Q2 Q3 Q4 Q5 (highest)
Quintiles based on sustainable growth
Actual next-3-year EPS Cagr (median, %)
Sustainable growth provides a good signal to
judge growth prospects
Avoid high growth stocks that have high probability
of disappointment
Section 3: Price of sustainable growth Microstrategy
6 September 2017 [email protected] 53
Topline growth has been a better predictor than margins Differentiating between topline versus margins also provides a good signal regarding a company’s growth potential. Our analysis highlights that firms that have managed to deliver strong topline growth have better potential to deliver high earnings growth. On the other hand, companies that have witnessed stable margins over the previous five years have delivered low earnings growth over the next three years versus ones with far more volatile margin profiles. Both factors demonstrate a clear trend in terms of their relationship with earnings-growth potential. We believe the robust topline growth delivered by a company (generally at the expense of margins) helps it garner additional market share, which then facilitates commanding wider margins in the future, leading to strong earnings growth. Margins on the other hand, are cyclical and mean reverting; and thus a poor indicator of a company’s growth potential.
Figure 97 Figure 98
APxJ: Median N3Y EPS growth for L3Y sales gr ranges APxJ: Median N3Y EPS gr for last 5Y margin cert ranges
Source: CLSA, Factset
Earnings momentum and incremental ROIC too work well Additionally factors such as positive earnings momentum and incremental ROIC have been good signals to gauge growth potential. Our analysis highlights that companies that have witnessed strong earnings-positive momentum over the previous 12 months have delivered the strongest earnings growth over the next three years. Likewise, incremental ROIC too, helps in improving the future delivery of growth.
Figure 99 Figure 100
APxJ: Median N3Y EPS growth for 12M EPS rev ranges APxJ: Median N3Y EPS growth for wIROIC chg ranges
Source: CLSA, Factset
6.0 5.6
7.4 7.7
11.5
4
5
6
7
8
9
10
11
12
Q1 (lowest) Q2 Q3 Q4 Q5 (highest)
Quintiles based on last 3-year sales Cagr
Actual next-3-year EPS Cagr (median, %)10.6
8.4
7.2 7.9
6.1
5
6
7
8
9
10
11
Q1 (lowest) Q2 Q3 Q4 Q5 (highest)
Quintiles based on margin certainty (L5Y)
Actual next-3-year EPS Cagr (median, %)
2.6
4.8
7.2
9.9
13.8
0
2
4
6
8
10
12
14
16
Q1 (lowest) Q2 Q3 Q4 Q5 (highest)
Quintiles based on last 12M EPS revision
Actual next-3-year EPS Cagr (median, %)
10.5
3.2
0
2
4
6
8
10
12
Positive wIROIC change Negative wIROIC change
Actual next-3-year EPS Cagr (median, %)
Strong topline growth presages high future
earnings growth
Strong earnings momentum and positive
wIROIC momentum helps in identifying winners
Section 3: Price of sustainable growth Microstrategy
54 [email protected] 6 September 2017
Asia Pacific ex-Japan - Attractively valued high growth stocks Our analysis suggests that stocks with high growth potential are a good investment if they are attractively valued after adjusting for future growth. Furthermore, it is crucial to make sure the future growth that is being used to discount the valuations is not subject to large-scale disappointment. Our characteristics analysis helps identify the factors to ascertain this. In the screen below, we highlight the stocks and screening criteria is as follows:
Strong earnings growth: FY1-FY2 EPS Cagr > 10%
Valuations: 12-month forward PE > 20x and 36-month forward PE < 16x
Strong topline growth: Last three-year sales Cagr > 10%
Positive 12-month EPS revision and sustainable growth > 5%
Figure 101
Asia Pacific ex-Japan companies with high growth and attractive valuations (sorted by forward PE, 3 years later) Code Name Cty Sector Mkt cap 12MF FY1-FY2 EPS Fwd PE 12M EPS rev Sustg L3Y Sales (US$m) PE (x) Cagr (%) 3Y later (x) (FY1, %) (%) Cagr (%) 1478 HK Q Technology CN Cons dur 2,092 23.6 81.3 6.1 126.8 17.0 52.4 MOMO US Momo Inc CN Software 6,952 22.6 59.1 7.1 138.0 25.9 461.2 SAWAD TB1 Srisawad Corp TH Div fin 1,569 16.6 29.5 7.8 16.8 26.9 nm DBEL IN Dalmia Bharat IN Materials 3,588 28.5 70.5 8.9 11.4 9.7 34.9 MTLS TB Muangthai Leasing TH Div fin 2,071 23.7 48.0 9.1 42.6 18.7 nm 2382 HK Sunny Optical CN Tech HW 14,944 31.4 65.3 9.2 67.2 24.7 36.0 1317 HK1 Maple Leaf Edu CN Cons svcs 1,123 15.9 23.5 9.5 13.2 10.4 20.8 SINA US Sina CN Software 7,087 28.3 63.0 10.1 49.7 5.9 15.7 LTFH IN L&T Finance IN Div fin 4,878 20.9 36.5 10.1 4.6 11.2 nm 1590 TT Airtac TW Cap gds 2,355 21.1 37.6 10.1 24.6 10.2 13.3 2018 HK AAC CN Tech HW 18,393 20.0 27.2 10.4 17.1 19.4 24.2 068270 KS Celltrion KR Pharma 11,841 31.2 60.3 10.7 6.5 13.6 43.7 WB US Weibo CN Software 9,991 41.0 75.2 10.8 48.5 23.5 51.6 ATM NZ a2 Milk NZ FBT 2,628 29.1 47.3 10.8 34.9 23.8 55.2 CANF IN Can Fin Homes IN Banks 1,159 22.0 27.9 11.2 15.4 19.7 nm 2313 HK1 Shenzhou Intl CN Cons dur 10,522 18.3 19.4 11.5 10.6 11.4 14.5 1448 HK Fu Shou Yuan CN Cons svcs 1,429 20.0 23.6 11.8 5.3 10.5 27.5 TLKM IJ1 Telkom ID Telecom 35,394 18.4 17.2 12.3 8.0 8.5 11.9 027410 KS1 BGF Retail KR Fd & drug 3,859 18.9 14.6 12.6 1.7 16.0 17.3 IIFL IN India Infoline IN Div fin 2,866 20.8 18.8 12.8 11.0 15.1 nm ATHM US Autohome CN Software 7,573 24.4 22.5 13.3 36.8 23.4 71.7 BABA US Alibaba CN Software 428,095 30.6 35.2 13.4 16.2 25.2 44.5 BBCA IJ1 BCA ID Banks 34,719 18.7 11.8 13.4 5.6 15.3 nm EXID IN Exide IN Autos 2,671 20.0 15.6 13.4 2.6 11.8 10.5 AC PM1 Ayala Corp PH Div fin 10,861 18.9 12.6 13.5 3.2 10.4 nm BJFIN IN Bajaj Finserv IN Insurance 12,946 25.5 27.4 13.5 8.8 16.2 nm MOFS IN Motilal Oswal IN Div fin 2,614 27.8 38.5 13.5 48.8 7.1 nm 2020 HK Anta Sports CN Cons dur 10,409 20.5 18.1 13.6 5.7 8.5 22.4 1910 HK1 Samsonite HK Cons dur 5,481 18.5 10.7 13.6 3.3 10.4 11.3 ALL AU Aristocrat AU Cons svcs 10,724 21.6 16.1 13.8 30.8 18.1 42.5 BIDU US Baidu CN Software 61,015 27.0 24.5 14.1 12.0 23.4 30.2 700 HK Tencent CN Software 394,835 35.8 39.5 14.6 9.4 25.6 36.0 BAF IN Bajaj Finance IN Div fin 14,430 32.6 36.1 14.8 16.1 19.3 nm 2723 TT Gourmet Master TW Cons svcs 1,973 25.3 20.1 15.5 0.3 12.8 13.4 RRHI PM Robinsons Retail PH Fd & drug 2,392 21.2 11.6 15.7 1.1 8.8 16.1 EDU US2 New Oriental Edu CN Cons svcs 12,934 31.9 30.1 16.2 7.4 16.2 16.5 ALI PM2 Ayala Land PH Property 12,285 23.7 14.9 16.3 2.4 10.0 15.2 CTD AU2 Corporate Travel AU Cons svcs 1,825 28.3 19.0 18.4 15.3 8.5 43.4 1 12MFPE criteria relaxed. 2 Forward PE for 3-year later criteria relaxed. Note: For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Stocks are attractively valued after adjusting for
future growth
Section 3: Price of sustainable growth Microstrategy
6 September 2017 [email protected] 55
Valuation upside for stocks moving from small-to-midcap Earlier in the report we highlighted that the small-cap multibaggers outperform their large-cap peers. Indeed, one of the advantages of focusing on small-cap multibaggers is that they also benefit from a valuation rerating once they transition from the small-cap to the midcap universe. A median PE analysis of the broader Asian universe suggests that the small-caps (market cap less than US$1bn) trade at a 26% discount to midcap peers (market cap between US$1-5bn). This is understandable given the increased focus from institutional investors and sellside analysts, and the index-inclusion effect following the transition from the small-cap to midcap universe. In this section, we quantify the valuation rerating impact on the small-caps as their market cap increases to over US$1bn and then to over US$5bn.
Figure 102 Figure 103
Relative PE of APxJ stocks within different mcap ranges Small caps with suppressed relative valuation over time
Note: Broader Asia Pacific ex-JP companies with market cap more than US$100m. Stocks with negative PE are excluded. Source: CLSA, Factset
PE rerating potential across markets and sectors Below we highlight the potential PE rerating of small-caps transitioning to midcaps for different markets and sectors. Hong Kong and Philippine small-caps have the highest potential, along with the staples and healthcare sectors.
Figure 104
Mid-cap versus small-cap relative PE premium since 2002 (past-15 years)
Note: Broader Asia Pacific ex-JP companies with market cap more than US$100m. Stocks with negative PE are excluded. Source: CLSA, Factset
0.87
1.09 1.13
0.7
0.8
0.8
0.9
0.9
1.0
1.0
1.1
1.1
1.2
Small cap(<=US$1B)
Mid cap(US$1-5bn)
Large cap(>US$5bn)
Quarterly average since 2002
(Median relative PE versus MSCI APxJ, x)
26% valuation premium
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
Dec
01
Dec
02
Dec
03
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
Dec
10
Dec
11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
Small cap (<=US$1bn)Mid cap (US$1bn to $5bn)Large cap (>US$5bn)
(Median relative PE versus MSCI APxJ, x)
Cons disc
Cons stap Energy Finan-
cials H'care Indust-rials
Info tech
Mater-ials
Prop-erty
Tele-com
Utili-ties Market
Australia 25.5 15.0 9.1 3.0 15.6 37.6 35.1 35.8 17.8 26.2 (18.0) 19.5
China 31.2 67.9 24.3 (22.1) 58.3 21.8 47.1 31.2 42.8 na 1.9 23.3
Hong Kong 58.3 na na na na 40.5 71.0 na 77.7 13.1 na 43.8
India 40.9 77.4 18.3 18.8 52.2 35.7 34.8 27.0 39.0 na 0.9 30.5
Indonesia 25.3 17.5 6.0 32.6 117.6 72.8 na 17.0 58.2 na na 22.6
Korea 23.0 46.5 na 23.4 60.1 32.4 85.3 10.9 na na 21.2 23.8
Malaysia 19.3 23.3 39.8 3.7 79.7 43.7 na 74.0 93.8 na 22.9 33.7
New Zealand 40.8 na (5.4) na 48.1 43.9 na na na na na 27.8
Philippines 68.7 78.3 na 41.0 na na na 72.8 69.5 na na 41.0
Singapore 61.0 21.8 na na 4.3 54.8 71.2 na 16.3 na na 33.6
Taiwan 19.7 44.6 na na na 33.7 7.9 13.9 16.4 na na 14.1
Thailand 43.4 42.5 2.6 (1.2) 35.2 45.4 24.9 52.9 69.5 (23.0) (11.7) 20.5
Sector 32.8 42.5 12.8 13.7 41.3 30.0 26.4 28.8 32.3 (3.1) 19.4 25.5
Healthcare and staples witnessed the most
rerating among sectors
A 26% rerating when a stock moves from small-
cap transitions to midcap
Among markets, Hong Kong and Philippines
witnessed the most rerating
Section 3: Price of sustainable growth Microstrategy
56 [email protected] 6 September 2017
Small-cap multibagger rerating is even more pronounced A further analysis of the valuation changes for multibaggers that have transitioned from small-caps to large-caps highlights that the rerating is even more pronounced. On a median basis, these small-cap multibaggers initially traded at a 10% discount to the MSCI Asia Pacific ex-Japan benchmark. Once they reached the midcap stage, they were trading at a 22% premium to the benchmark and after becoming large-caps they are now trading at a 35% premium. Korea Zinc (010130 KR) is a typical example of this phenomenon with its relative PE rising along with the market cap. The stock traded at a 0.3x to 0.7x relative PE range when its market cap was below US$1bn but is now trading at the same PE as the market.
Figure 105 Figure 106
Multibaggers relative PE premium within mcap ranges Korea Zinc relative PE and mcap since 2002
Note: Only includes broader Asia Pacific ex-JP small cap multibaggers that have grown into large caps as of 30 Jun 2017. Stocks with negative PE are excluded. Source: CLSA, Factset
Small-cap multibagger rerating across markets and sectors A similar analysis for the Asian market and sectors highlights that valuation rerating is most prominent in small-cap multibaggers from the Philippines and Indonesia; and the healthcare and staples sectors. Rerating was the smallest in Singapore, Taiwan and Thailand; and the property sector.
Figure 107
Relative PE premium of small cap multibaggers that became large caps (since 04)
Note: Only includes broader Asia Pacific ex-JP small cap multibaggers that have grown into large caps as of 30 Jun 2017. Stocks with negative PE are excluded. Source: CLSA, Factset
0.90
1.22
1.35
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
<US$1bn US$1-5bn >=US$5bn
Market cap ranges
MultibaggersMedian relative PE versus MSCI APxJ (x)
34.6% valuation premium
11.1% valuation premium
0123456789
0.30.40.50.60.70.80.91.01.11.2
Dec
01
Oct
02
Aug
03
Jun
04Apr
05
Feb
06D
ec 0
6O
ct 0
7Aug
08
Jun
09Apr
10
Feb
11D
ec 1
1O
ct 1
2Aug
13
Jun
14Apr
15
Feb
16D
ec 1
6
Relative PE Mcap (RHS) (US$B)(x)
Median rel PE: 0.48x
Median rel PE: 0.55x
Median rel PE: 0.93x
Cons disc
Cons staps Energy Finan-
cials H'care Indust-rials
Info tech
Mater-ials
Real estate
Tele-com
Utilit-ies Market
Australia 40.1 na 88.9 (6.5) 12.0 349.5 na 7.5 na na 106.2 20.0
China 74.9 51.0 (25.1) (47.3) 100.7 (4.4) 145.1 29.7 1.6 na 32.4 37.9
Hong Kong 114.2 na na na na 119.3 15.5 na na na na 76.3
India 26.8 132.7 (17.7) 94.6 89.9 122.9 na 15.8 na na na 58.5
Indonesia 360.5 90.5 421.2 432.9 287.4 na na 58.6 na na na 113.4
Korea 166.7 154.7 na na na 474.0 59.8 58.0 na na na 34.6
Malaysia na 66.3 173.7 na na na na na na 28.2 na 59.8
New Zealand na na na na na 57.0 na na na na na 57.0
Philippines na 357.5 na 40.6 na 127.2 na na na na 138.0 120.7
Singapore na 28.3 na 29.4 na na na na 19.6 na na 14.7
Taiwan 38.5 na na na na na (18.7) na na na na 14.8
Thailand 125.9 124.1 na 74.2 125.0 293.2 na (34.2) 125.2 143.5 na 14.4
Sector 40.5 84.9 37.1 67.3 105.7 64.2 62.6 30.7 13.1 19.0 42.5 49.6
Philippines and Indonesia have the highest rerating
Property and telecom have the smallest rerating
Almost a 50% rerating for small-cap multibaggers
that have become large-caps
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 57
Multibagger case studies Our analysis of the past multibagger stocks highlights that there are several factors responsible for fuelling the rise of companies over the long term. Indeed, attaining the multibagger status necessitates delivery of stable growth over the course of years/decades on a consistent basis. History is replete with examples of such companies. Below we examine a few sectors/companies that have become multibaggers over the long term and analyse the underlying reasons that differentiate them from the rest.
1. Household and personal products (HPC): The HPC sector has been a breeding ground for multibaggers in Asia. The sector itself has been a 26-bagger since 1995, the second-best performer after software. Regardless of its defensive characteristics, investors have been richly rewarded, given the sector’s strong/stable growth profile, and more importantly, exposure to high-growth markets such as China, India and Indonesia. The key question however is, will the sector continue to remain a bright spot? Our analysis suggests that in markets with strong economic growth and favourable demographics, the HPC sector will remain the core investment holding over the long term.
Figure 108
MSCI Asia Pac ex-JP sectors: Total returns since 1995
Note: Semis and software performance since 1998. Source: CLSA, Factset
Figure 109 Figure 110
MSCI Asia Pac ex-JP: HPC versus the benchmark MSCI Asia Pac ex-JP HPC sector: YoY OPF since 1996
Source: CLSA, Factset Source: CLSA, Factset
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
Sof
twar
e
HPC
Phar
ma
Food
&dr
ug
Aut
o
Sem
is
Ener
gy
Div
fin
FBT
Ban
ks
Util
ities
APx
J
Mat
eria
ls
Tech
HW
Hea
lthca
re
Rea
l est
ate
Insu
ranc
e
Ret
ail
Con
s du
r
tran
spor
t
Tele
com
Med
ia
Con
s sv
cs
Cap
goo
ds
Total returns since 1995 (%, local currency)
HPC sector has been a 26-bagger since 1995, second-best to software
26.8x
0
500
1,000
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06
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10
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MSCI Asia Pac ex-JP HPC
MSCI Asia Pac ex-JP
Index since 199526.8x returns
4.2x retuns
(20)
(10)
0
10
20
30
40
1996
1997
1998
1999
2000
2001
2002
2003
2004
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2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
MSCI Asia Pac ex-JP HPC79.2 46.6
-30.9
YoY OPF (%)
Outperformance in 14 of the 23 years
Hit-rate has been the lowest for China,
Japan and Taiwan
HPC sector has been a breeding ground for
multibaggers
Consistent performer
Analysis of multibaggers in detail
Section 4: Multibagger case studies Microstrategy
58 [email protected] 6 September 2017
Breakdown of five-baggers by markets Within Asian markets, Indonesia, Singapore and Australia have only one HPC company (well-traded) and each has been at least a five-bagger over the long term. More notably, eight out of 11 Indian HPC companies have been at least five-baggers, while the hit rate has been lowest for China and Japan.
Figure 111
Broader Asia Pac markets: Percentage of five-baggers in each market
Source: CLSA, Factset
India dominates the 10-bagger list Unilever Indonesia has delivered 369x returns since 1996 - the best-performing Asian HPC stock over the past 22 years. From the trough in October 1998, the stock price has increased by more than 500x. Of the 22 Asian HPC stocks that have at least become 10-baggers since 1996, seven are from India, delivering on average 116x returns with the likes of Godrej Consumer returning 238x, Emami 230x and Marico 141x. From Japan and Korea, there are five each, while from China, surprisingly, there has been only one 10-bagger - Hengan, delivering 41x returns. From both Korea and Japan, cosmetics companies (Amorepacific, LG H&G and Kose) have been at the forefront and have benefitted immensely from their China exposure. From Australia, only Blackmores made it to the list with 92x returns.
Figure 112
Asian HPC sectors: 10-baggers since 1996
Source: CLSA, Factset
100 100 100
7367
40
2524
14
0 01 1 1
11
3
20
8
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2 1
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Indo
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Percentage of five-baggers since 1996 Total eligible HPC stocks (RHS)(%) (#)
0
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Uni
leve
r In
do
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rej Con
s
Emam
i
Am
oreP
acifi
c
Mar
ico
Dab
ur I
ndia
Bla
ckm
ores
Lead
ers
Cos
m
LG H
&H
P&G
H&
H
KO
LMAR
Bes
t W
orld
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gan
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an U
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BTI
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Pige
on C
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gate
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pe K
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e
Uni
char
m
Asian 10-baggers since 1996Total returns since 1996 (%, local currency)
Unilever Indo, Godrej, Emami, Amorepacific and Marico have been more than 100-baggers since 1996
Eight out of 11 Indian HPC companies have been
more than five-baggers
Hit rate has been the lowest for China, Japan
and Taiwan
Unilever Indo has been more than 500-bagger
since October 1998
Seven Indian HPC Stocks have been more than
10-baggers since 1996
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 59
Does exposure to high-growth economies matter? We have already seen that HPC companies within India and Indonesia have delivered the best returns over the long term, given their exposure to the strong domestic growth component. It is surprising that despite delivering the highest GDP growth over the past few years, China has only one HPC stock (Hengan) in the 10-bagger list, achieving close to a 41x return. However, companies within low-growth markets such as Japan and Korea have been handsomely rewarded for their strong and growing exposure to the China market. Overall in Japan, there are around 21 HPC stocks, of which only five (23% hit-rate) have managed to attain the 10-bagger status, thanks to their exposure to fast-growing Asian markets. The hit-rate is slightly better for Korea with eight out of 20 HPC stocks becoming 10-baggers, though this is still low compared to the high-growth market peers.
Figure 113
Broader Asia Pac markets: Real GDP Cagr since 2003 and 1995
Source: CLSA, IMF
Focus on future growth markets The IMF forecasts that Indian real GDP growth will accelerate to 9.1% over the next five years, followed by China and Indonesia. If these forecasts hold true, HPC companies exposed to these markets have the highest potential to become future multibaggers.
Figure 114
Broader Asia Pac markets: Real GDP Cagr over the next five years (2016-21F)
Source: CLSA, IMF
9.2
7.6
5.6 5.3 5.0
3.9 3.5 3.5 3.5 2.9
0.6
0123456789
10
Chi
na
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a
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g
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ay HK
Kor
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Taiw
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Japa
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Real GDP Cagr since 2003 Real GDP Cagr since 1995(%)
High growth versus low-growth markets
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Real GDP cagr (2016-21F, %)(%)
Per IMF, India will be fastest-growing Asian
market in Asia over the next five years
HPC companies within India, Indonesia have
delivered the best returns over the long term . . .
. . . given their exposure to the strong domestic
growth component
China delivered the highest GDP growth over
the past several years . . .
. . . however, only a HPC company (Hengan) made
it to the 10-bagger list . . .
. . . although exposure to China helped Korean and Japanese HPC companies
HPC companies exposed to India/China/Indo have
the potential to become the future multibaggers
Section 4: Multibagger case studies Microstrategy
60 [email protected] 6 September 2017
Exposure to growth-markets has also been the key As highlighted earlier, the HPC sector is the direct beneficiary of strong domestic growth. As a result India/Indonesia-focused HPC companies have delivered consistent performance over the past few years. However, companies exposed to mature markets such as Japan and Korea, where the domestic-growth component is weak, have delivered subdued returns compared to their Asian peers. To compensate for the lack of domestic growth, however, some companies such as Amorepacific/LG H&H from Korea, and Kao/Unicharm from Japan have expanded overseas, to tap the nascent growth potential of markets such as China. These efforts have indeed been rewarded in the form of incremental revenue streams originating out of China and thereby boosting the topline growth of these companies. In the case of Amorepacific, the revenue contribution from China has increased from 7.4% in 2011 to close to 20% last year. While for Unicharm, the contribution rose to 21% in 2014 from 12% in FY3/11 and narrowed slightly to 15% last year.
Figure 115 Figure 116
Amorepacific: Revenue exposure to China Unicharm: Revenue exposure to China
Source: CLSA, Factset Source: CLSA, Factset
Market cap is a crucial factor to detect future multibagger Within the HPC space, micro/small-caps have the highest potential to become future multibaggers, while large-caps have lost half their value.
Figure 117
Performance of HPC stocks broken down by market-cap
Source: CLSA, Factset
7.4
9.1
10.9 12.0
16.1
19.3
5
7
9
11
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15
17
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21
2011 2012 2013 2014 2015 2016
Sales exposure to China (%)
Close to 20% revenuederived out of China
11.9 13.2
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21.1
17.9
15.2
0
5
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25
Mar 11 Mar 12 Mar 13 Mar 14 Dec 14 Dec 15 Dec 16
Sales exposure to China (%)
661.0
346.3
96.4 10.5
(4.4)
50.0
(41.9)(100)
0
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<US$50m US$50-100m
US$100-300m
US$300-500m
US$500-700m
US$700-1000m
>US$2bn
Breakdown by market cap (as of start of 1996 or as of listing)
Median performance over the next 22 years(%)
Small-caps have the highest potential to become the
future multibagger
Revenue exposure of some of Japanese/Korean companies to high-growth markets has been the key
Small-cap companies have most potential to become multibaggers
While large-caps have lost half their value
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 61
Unilever Indonesia: 286-bagger since 1990 Indonesian behemoth and the only major HPC company in the market, Unilever Indonesia, has been an extremely rewarding stock for long-term investors. Since listing in the 1990s, the stock has delivered negative returns in only four of the past 26 years and not once in the past 12 years back to 2005. Although focus on quality since the start of the GFC has led to a strong stock rerating from the beginning of 2009, over the long term, the company has managed to grow earnings by 127x and sales by 71x, with a strong improvement in operating margins across these years. Its market cap has surged from around US$100m in 1990 to close to US$37bn now. Although the stock will continue to remain a core holding in Asian portfolios, given the expectation of strong domestic growth over the next few years, the steep valuations and large market cap could limit the degree of future returns.
Figure 118 Figure 119
Unilever Indonesia: Price vs sales vs earnings Unilever Indonesia: Ebit margin
Source: CLSA, Factset Source: CLSA, Factset
Godrej Consumer: The best within India HPC Similarly, within India’s HPC space, Godrej Consumer has been the most rewarding stock with 105x returns, underpinned by 30x growth in earnings and 18x improvement in revenue. Compared to peers, Godrej Consumer has delivered the second-best earnings improvement with Dabur being the best. Going forward though, premium valuations could limit upside.
Figure 120 Figure 121
Godrej Consumer: Price vs sales vs earnings trend India consumer: Earnings growth since FY961
Source: CLSA, Factset ¹For companies with listing later than 1995, the reporting year has
been used as the starting point. Source: CLSA, Factset
0
5,000
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35,000
1990
1992
1994
1996
1998
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2002
2004
2006
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Sales
Net Income
Price
(Index)
286x
71x
127x
Unilever Indo has increased earnings by 127x versus price increasing by 286x since 1990
0
5
10
15
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25
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1992
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Price Sales Profit(Index)
105x
30x
18x 0
500
1,000
1,500
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3,500
4,000
Dab
urIn
dia
God
rej
Con
s
Mar
ico
Hin
dust
anU
ni
Emam
i
P&G
H&
H
Jyot
hyLa
b
Col
gate
-Pa
lm
Gill
ette
Indi
a
Baj
ajC
orp
Ever
eady
Net income growth since FY96(%)
Unilever Indonesia has delivered 286x
returns . . .
. . . underpinned by strong earnings and
revenue growth
Godrej has been the best consumer story within
India over the past 16 years
Section 4: Multibagger case studies Microstrategy
62 [email protected] 6 September 2017
2. Riding the ecommerce wave While consumption growth has been one of the key catalysts fuelling the rise of multibaggers in the past, the ongoing wave of consumerism is being led by the ecommerce sector. Indeed, companies exposed to this theme have strong potential to become multibaggers as the industry continues to record strong growth and enhance market share at the expense of the traditional brick-and-mortar retailers. In her $trillion opportunity report, our Head of Asia Telecom & Internet Research, Elinor Leung, highlights that the global online grocery market (eGrocery) will hit a growth inflection in 2017, with China leading the way. China’s grocery market, already the world’s largest, will increase by 30% to US$1.4tn by 2021.
The current listed global ecommerce space is primarily dominated by the US and Chinese markets. Within the listed universe, the USA and China account for 62% and 32% by market cap and 65% and 27% by revenue. Thus, the ecommerce theme in the other global markets is still in its infancy and has a strong potential to grow. While most Chinese ecommerce plays such as Alibaba and JD.com have been recently listed, the USA has a longer track record with companies such as Amazon, Ebay and Priceline being listed since 1997. Overall, the global ecommerce basket has delivered strong returns both on a weighted and median basis since 1995 (driven by Amazon).
Figure 122 Figure 123
Global ecommerce-related stocks: Mcap breakdown Global ecommerce-related stocks: Revenue breakdown
Note: Analysis based on 32 global ecommerce related stocks (mainly the stocks with GICS level-4 industry classification as Internet & Direct Marketing Retail. Also includes few stocks such as Alibaba and eBay that are classified as internet). Source: CLSA, Factset
Figure 124 Figure 125
Global ecommerce: Fcap-weighted index (US$ TR) Global ecom: Index based on median perf (US$ TR)
Note: Index performance is calculated based on custom global ecommerce universe of 32 stocks (stocks with GICS level-4 industry classification as Internet & Direct Marketing Retail, also includes few stocks such as Alibaba and eBay that are classified as internet). Source: CLSA, Factset
USA62%
China34%
Japan2%
Germany1%
Others1%
USA65%
China27%
Japan4%
Korea2%
Germany1%
Others1%
66,146
0
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20,000
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Dec
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Global ecommercesector (Fcap weighted)
(Index)2,457
0
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Global ecommerce sector(based on median perf)
(Index)
Ongoing wave of consumerism is being led
by ecommerce sector
Ecommerce theme outside USA and Chia is still
in its infancy
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 63
Around 14 ecommerce stocks have been five-baggers since 2009 As highlighted, the ecommerce sector has been a long-term multibagger both on a weighted (661x) and median basis (24x). The strong returns on a weighted basis are primarily a reflection of Amazon’s performance (658x), which has currently around a 50% weight in the index, followed by Alibaba with 11%. Given most ecommerce stocks were unlisted before the GFC, we highlight performance since 2009. Around 10 stocks have been at least 10-baggers, while 14 have been at least five-baggers. Netflix has been the best performer with 34x returns, followed by Vipshop, Priceline and Start Today, which all have been more than 20-baggers. China’s large-caps ecommerce plays, Alibaba and JD.com, have been listed over the past three years and both have delivered around 50% returns since their IPOs, while Ctrip, which was listed in 2003, has been around an eight-bagger since 2009.
Figure 126
Global ecommerce plays: US$ total returns since 2009
Source: CLSA, Factset
Both Amazon and Priceline have been on a tear since GFC Amazon is the world biggest ecommerce play by market cap, followed by Alibaba. The stock has delivered more than 10x returns since 2008, with market cap soaring from US$45bn to as high as US$476bn recently. Given the large increase in market cap, the hurdle rate to deliver similar future returns is extremely high.
Figure 127 Figure 128
Amazon: Market cap versus sales since 1998 Priceline: Market cap versus sales since 1998
Source: CLSA, Factset Source: CLSA, Factset
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
Net
flix
Vip
shop
Pric
elin
e
Sta
rt T
oday
Expe
dia
Web
jet
Am
azon
Info
mar
t
Mer
cado
Libr
e
F@n
Com
m
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bal T
op
Libe
rty
Inte
rac
Ctr
ip
GS
Hom
e
eBay
Evol
able
Asi
a
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O
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tton
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uten
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e M
e
ASK
UL
Cor
p
JD.c
om
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aba
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isor
US$ total returns since 2009 (since IPO for the once listed later)(%)
14 five-baggers and 10 ten-baggers since 2009
15
45
476
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Mcap
(US$bn)
17F sales:
166
5.8
91.3
1.4
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Mcap
Sales
17F sales
(US$bn)
US$486mn
Netflix has been the best ecommerce stocks since
2009 followed by Vipshop and Priceline
JD and Alibaba are up close to 50% since
listing in 2014
Amazon’s market cap increased by 10-times
from US$45bn in 2008 to US$476 currently
Section 4: Multibagger case studies Microstrategy
64 [email protected] 6 September 2017
Global ecommerce plays While ecommerce is an outstanding theme to play the next leg of consumerism, it must be noted that although the large-cap players such as Amazon and Alibaba will continue to grow, the potential to deliver another 5x return is significantly limited. The hurdle rate has increased significantly as the companies have grown. To identify the next multibagger within the ecommerce space, investors should focus on small-caps from the below list, which have strong prospects of scaling-up in the future. Companies such as Infomart, Webjet and F@N Communication continue to remain below the US$1bn mark, despite being 10-baggers since 2009.
Figure 129
Global ecommerce companies (sorted by market cap) Code Name Cty Sector Mkt cap TR since FY1-FY2 FY1-FY2 Sustg 12MF Fwd PE PE/G NDE
(US$m) 2009 (%)1 ROE EPS Cagr (%) PE Reilly (x) (latest,
(avg, %) (%)
(x) (10Y, %)
%)
AMZN US Amazon US Retailing 457,176 1,757 16.3 29.1 13.0 141.8 100.0 4.9 (59.3)
BABA US Alibaba CN Software 442,639 86 21.9 35.7 25.2 31.2 55.6 0.9 (19.8)
PCLN US Priceline US Retailing 89,063 2,365 29.6 14.9 27.9 22.0 75.3 1.5 18.3
NFLX US Netflix US Retailing 72,590 3,837 21.3 116.8 14.1 96.5 96.7 0.8 85.8
JD US JD.com CN Retailing 50,196 101 9.7 180.4 (4.5) 57.2 0.0 0.3 (21.6)
EBAY US eBay US Software 37,391 494 18.1 8.8 34.0 16.2 49.8 1.9 21.5
CTRP US Ctrip CN Retailing 27,675 788 5.9 nm 4.6 33.0 22.3 nm 15.1
EXPE US Expedia US Retailing 22,753 2,001 16.9 21.8 11.4 24.5 86.6 1.1 (13.3)
4755 JP Rakuten JP Retailing 16,317 132 11.3 51.3 8.0 21.8 29.3 0.4 92.8
ZAL GR Zalando GE Retailing 11,680 86 11.6 21.7 10.6 53.3 18.2 2.5 (69.4)
QVCA US Liberty Interac US Retailing 11,658 820 36.6 20.0 24.0 16.6 55.0 0.8 113.4
MELI US MercadoLibre US Software 10,758 1,430 33.4 30.0 27.2 53.5 42.9 1.8 (57.5)
3092 JP Start Today JP Retailing 9,959 3,249 59.1 27.8 36.5 43.3 100.0 1.6 (55.7)
TRIP US TripAdvisor US Retailing 6,010 58 8.6 (6.5) 10.2 36.2 64.6 nm (47.0)
VIPS US Vipshop CN Retailing 4,669 1,573 34.8 11.7 41.4 11.0 0.0 0.9 0.9
002640 CH Global Top CN Retailing 4,238 725 18.2 73.4 12.0 25.8 16.7 0.4 7.1
MMYT US MakeMyTrip IN Retailing 3,142 16 nm nm 0.0 nm na nm (29.3)
BTOW3 BZ B2W Companhia BR Retailing 2,748 (7) nm nm 0.0 nm na nm 56.2
600640 CH Besttone CN Retailing 2,252 165 7.3 na 0.5 nm na nm (61.9)
2678 JP ASKUL Corp JP Retailing 1,545 102 8.5 135.8 2.7 52.9 90.9 0.4 (52.7)
057050 KS Hyundai Home KR Retailing 1,435 14 9.3 15.0 7.6 12.1 90.9 0.8 (56.4)
TME NZ Trade Me NZ Retailing 1,295 95 13.5 7.7 2.1 17.7 34.3 2.3 13.8
028150 KS GS Home KR Retailing 1,206 491 10.8 7.3 6.3 12.1 88.2 1.7 (77.6)
035760 KS CJ O KR Retailing 1,149 227 15.5 177.6 7.9 10.8 42.0 0.1 39.4
WEB AU Webjet AU Retailing 884 1,555 18.8 30.9 10.0 19.7 58.8 0.6 (18.1)
400 HK Cogobuy CN Retailing 875 15 16.5 29.1 17.4 7.3 1.0 0.3 41.3
002315 CH Focus Tech CN Software 858 (23) 9.8 41.8 2.8 27.5 25.2 0.7 (29.8)
2492 JP Infomart JP Software 813 1,845 16.0 45.5 6.6 48.1 71.1 1.1 (44.6)
2461 JP F@n Comm JP Software 758 1,487 23.1 12.5 16.9 17.2 34.0 1.4 (93.7)
6191 JP Evolable Asia JP Retailing 385 194 26.5 66.5 37.4 42.0 na 0.6 (71.9)
108790 KS Interpark KR Retailing 269 (47) 10.3 193.4 3.6 16.0 5.3 0.1 (19.5)
3688 JP Voyage Gr JP Software 201 (43) 17.6 38.8 17.3 15.6 34.0 0.4 (51.1)
¹ For companies that were listed after 2009, performance is since the IPO. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Identifying next ecommerce multibagger
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 65
3. Capturing technological evolution Throughout history, the advent of any new technology with a potential to disrupt the status quo and introduce new growth opportunities has been an ideal source of future multibaggers. Identifying such breakthrough technologies in their nascent form has always been the key. Some prime examples of this over the past decade have been companies exposed to themes such as ecommerce, the internet and social networking. As highlighted earlier, sectors such as consumer staples, which is essentially tied to the economic growth prospects of any given country, could continue to provide strong long-term multibagger opportunities. However, the list is strictly limited to high-growth markets. On the other hand, the benefits of technological disruption could snowball beyond the providers of technology and multiple sectors could witness productivity/efficiency improvement.
Our global head of thematic research Shaun Cochran, in his report The AI Era, published in May 2017, introduces in detail, similar technological disruption that could unfold with the advancement in AI. This technological evolution has repercussions beyond just the tech sector. Shaun reckons AI will fundamentally reshape diverse and unrelated industries. Below we highlight some excerpts from this report and also the potential implications on various global sectors.
Intelligent machines are inevitable and ultimately the source of future global growth. We are fast approaching a world in which humans and artificial intelligence (AI) are bound together in a constant exchange of information and goals - where people and software will not be much use without the other. And while we opine that AI will restore global productivity, the first five to 10 years will see a challenging transition and turmoil in job markets. Diverse and unrelated industries will be fundamentally reshaped. We profile six sectors where the impact is already profound and highlight winning Asian AI innovator stocks.
We are convinced that a truly capable AI ecosystem - one that is as integral to the global economy of tomorrow as the internet is today - will prove to be the most important development in all of human history. If you are unsure what AI is, how it relates to investing or what the key questions and starting assumptions should be, read The AI Era.
Leaders have worried about technology taking jobs for centuries. But logic, economic theory and the long arc of history tell us to ignore the luddites’ fallacy (that technology and automation destroy jobs). If we had listened to it, we would all still be farming. AI will create more jobs than it replaces, but the transition will be painful.
We focus on six industries in which our sector heads see material changes that investors must track, and where we can provide value-added analysis. Areas in order of estimated impact are: autos, healthcare, robotics, financial services, consumer and technology.
Governments will be called upon to ease the pain. Universal basic income will gain support, but we prefer negative income taxes. Bonds will benefit in this disruptive but disinflationary world. It’s probably also dollar-bullish. For other asset classes, the implications are less clear. Tech and robotics will see sustained growth while autos and oil will see massive disruption. We profile 10 Asian stocks that can provide meaningful bottom-up insight into how AI is
Birth of new technology is a source of rewarding
opportunities
AI will create more jobs than it destroys, but the transition will
be painful
We profile six sectors where AI’s impact is
already profound
Sovereign bonds are the winning asset
class; TSMC, SEC and Fanuc are our large-
cap favourites
Shaun Cochran Global Head of Thematic Research [email protected] +82 2 397 8427
Section 4: Multibagger case studies Microstrategy
66 [email protected] 6 September 2017
being implemented in the real world. Our large-cap profiles include TSMC, SEC, Fanuc, Baidu, Nissan, TCS and Hikvision. Midcap beneficiaries are Xero, Domino’s and Koh Young.
Reshaping industries We focus on six industries where AI is already having an impact, or is likely to do so meaningfully in the foreseeable future. While we won’t pretend this is an exhaustive list, we are confident it will serve as a useful starting point whatever your area of specialisation, be it autos, healthcare, robotics, financial services, consumer or technology.
The core conclusion is: AI is already more advanced in many industries than one might imagine. We were surprised at the breadth of case studies we were able to uncover. We chose to focus on six sectors, partly because they are the areas where we see the greatest potential impact and partly because the related analysts could point to specific developments within their coverage.
Below is a guestimate as to how significant that impact may be in changing the fundamental business models within a sector and how immediate the impact is. This is a structural change that has only just begun, we are happy to discuss with investors where and why they might disagree with these guesses. We have tried to order the discussion as a function of the potential disruption. Our conclusions are that the autos industry will see the biggest change, possibly eliminating dominant players and completely shifting the business model from car sales to mobility services. Healthcare is ideally suited to digitisation, virtualisation and expansive disruption via AI. Robotics, technology, media and telecommunications (TMT), consumer and financial services are all aggressive adopters of AI but will primarily use it to accelerate their current course of development.
Figure 130
Six sectors where AI’s impact is already profound
Source: CLSA
1. Auto: Progressing . . . possibly faster than Autocalypse Our January 2016 Autocalypse report suggested that consumers purchasing true self-driving cars were probably still a 2025+ timeframe, not 2020. Meanwhile, in our August 2016 Choosing lanes report, we wrote: ‘While driverless cars are a hot topic with the media, mass-market adoption of fully autonomous vehicles is at least a decade away, despite some commercialised
TMT Consumer
Financial services
Robotics
Auto
Healthcare
Industryimpact
Timing
Shiftsbusinessmodel
Impactsbusiness
lines
Imminent Later
Six sectors where AI impact is profound
Order driven by timing and magnitude
of expected change
Auto and healthcare will see the most profound change
Geoff Boyd Regional Head of Autos & Steel Research [email protected] +65 6416 7853
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 67
city-taxi services starting sooner. In the interim, increasing Adas (advanced driver assistance system) content is a growth opportunity and we expect a 38% global-revenue Cagr for the segment from 2015 to 2020. Our numbers are ahead of industry forecasts with consensus in the 20-30% range, but regulation and OEM branding are dual drivers that will help Adas technology become the standard package earlier than many of our peers predict.’
Figure 131
Levels of autonomous vehicles
Level 1 - Function specific automation: Automation of specific control functions, such as cruise control, lane guidance and automated parallel parking. Drivers are fully engaged and responsible for overall vehicle control (hands on the steering wheel and foot on the pedal at all times).
Level 2 - Combined function automation: Automation of multiple and integrated control functions, such as adaptive cruise control with lane centring. Drivers are responsible for monitoring the roadway and are expected to be available for control at all times, but under certain conditions can be disengaged from vehicle operation (hands off the steering wheel and foot off the pedal simultaneously).
Level 3 - Limited self-driving automation: Drivers can cede all safety critical functions under certain conditions and rely on the vehicle to monitor for changes in those conditions that will require transition back to driver control. Drivers are not expected to constantly monitor the roadway.
Level 4 - Full self-driving automation: Vehicles can perform all driving functions and monitor roadway conditions for an entire trip, and so may operate with occupants who cannot drive and without human occupants.
Source: CLSA, NHTSA (Aas shown in Litman, Todd, Victoria Transport Policy Institute. “Autonomous Vehicle Implementation Predictions.” 24 August 2015).
2. Healthcare: Digital doctors The healthcare industry is uniquely positioned to benefit from the rise of AI. Ideal starting sector conditions are: supply-constrained, data-rich environments with a high dependence of cognitive processes. Technologies that can speed, and or lower, the cost of decisions are likely to increase demand in these industries rather than shrink revenue. This absolutely describes healthcare. The additional upside is that improvements in qualitative healthcare outcomes can have a quantitative impact in the rest of the economy. We would argue that the broad gamut of solutions already seeking commercialisation in the market validates our view.
Figure 132
The broader spectrum of potential commercialisation with time
Source: CLSA, IBM Watson, Wikimedia commons, GRAIL, HealthTap, Skin cancer foundation
IBM Watson using machine learning to find an application for Parkinson’s disease for an already proven drug
IBM Watson for Oncology, an actual product used in hospitals including Jupiter Medical Centre in Florida and University of Tokyo
AI can better predict heart attacks than humans (built by University of Nottingham researchers)
Narrow application
AI can diagnose skin cancer better than dermatologists (built by Stanford University researchers)
Mobile app triaging like a real doctor –holds potential to become the future general practitioner
GRAIL combining liquid biopsy with machine learning to truly cure cancer
General application
Broader application
IBM Watson Health
David Stanton Head of Regional Healthcare Research [email protected] +61 2 8571 4247
Section 4: Multibagger case studies Microstrategy
68 [email protected] 6 September 2017
3. Robotics: Learning machines Big data and machine learning are extending the potential, impact and capability of industrial-automation solutions. We have seen first-hand how the internet of things (IoT) is taking centre stage at all industrial trade shows, and how machine learning and connected services enhance manufacturers’ productivity, efficiency and quality. With payback periods often below two years and quantifiable results, we expect rapid industry adoption. Companies with global scale have a significant advantage worth embracing, and those selling sensors and machine vision will benefit as IoT requires a higher level of data collection. Fanuc and Keyence are our top thematic picks.
The aggregate value of new connected services in factory automation will increase from less than US$2bn today to US$25bn by 2023, enjoying a 44% Cagr. Manufacturers’ insatiable appetite for higher productivity and lower cost of ownership will drive growth. In factory automation, the most important new IoT services will be predictive maintenance; efficiency optimisation; visualisation and advanced monitoring; and self-programming.
4. Financial services: Smart robo-banks (New robber banks) Intuitively, financial services, banking, insurance and asset management sit right at the epicentre of the looming tsunami of AI disruption. We would concede financial services are particularly prone to bouts of speculation about technology-driven Armageddon - remember Y2K, ATM/internet banking displacement of branches and more recently blockchain! However, having done the work, we conclude the risks and opportunities are real. Traditional business models are driven by high volumes of low-value transactions that generate material amounts of data and drive product offerings and customer-service processes. There are also severe consequences for inconsistent decisions (ie, bank earnings often falter, but they also plunge and banks do fail) and there are direct linkages between regulatory capital intensity and earnings volatility.
5. Consumer: Intelligent shopping The motivations for shopping clearly vary significantly from person to person. The penniless student has a different thought process to the CEO on holiday. Retail has always sought to provide different options to different buyers; changing the offerings in different stores to provide the right one. However, the big difference in ecommerce and physical retailing is mostly in the amount of data that the consumer is sharing and the ability of the retailer to capture, analyse and act on it. Brands are equally keen to discover more about the most effective use of their marketing budget, and build the best products. In this section we look at how AI is already starting to influence the consumer sector as follows, and give one example or more, in each case.
1. Helping brands build the best product (Unicharm)
2. Optimising inventory (Fast Retailing/Coupang)
3. Improving the offer to consumers (Ebates/Rakuten/Naver)
4. Highlighting the offer to consumers at the right time (Askul/Korean Department stores)
5. Making it easier to find what people want (NTT)
6. Delivering it more efficiently (Yamato/LINE)
Morten Paulsen Head of Japan Research [email protected] +81 3 4578 8052
Brian Johnson [email protected] +61 2 8571 4252
Oliver Matthew Head of Asia Consumer Research [email protected] +81 3 4578 8041
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 69
6a. Tech: AI’s impact on the server market The server market bifurcated into a stagnant (or slightly declining) Wintel segment for traditional enterprises and a booming Linux-Tel segment adopted by internet hyperscale firms starting in 2008-10. The internet segment is now adopting new processors that are better suited to some types of workloads - deep learning is the common threat to this new segment. We believe this ongoing evolution will benefit two types of firms: the Chinese server vendors such as Huawei and the Taiwanese customised server designers, Inventec, Quanta and Wistron.
6b. Tech: AI’s impact on semiconductors With AI, machine learning and cognitive computing gaining critical mass, a seachange in IT architecture is taking place as new types of processors are developed to carry out massive, complex computations. This will benefit the semicon ecosystem on several fronts: from foundry, outsourced assembly and testing (OSAT), to intellectual-property and electronic-design automation tools. Leaders in each segment with the capability to design and manufacture these advanced chips will be winners.
Playing the AI theme AI offers new growth for tech, supporting our bullish view on TSMC and SEC. Our preferred component plays are Hikvision and Koh Young. Autos manufacturers will see profits contract; we profile Nissan to highlight the Asian implications. Autonomous cars are negative for oil prices and all companies where earnings are a direct function of that. The robotics industry is not ex-growth and will see intelligence-related solutions commercialising from this year. Fanuc is key play on the theme.
Figure 133
10 focus stocks on AI (sorted by market cap) Code Name Market Mkt cap 3M ADTO 17F 18F
(US$m) (US$m) PE (x) PE (x)
005930 KS Samsung Electronics Korea 283,600 456.6 7.9 7.0
2330 TT TSMC Taiwan 180,895 183.0 16.5 14.9
TCS IN Tata Consultancy India 75,279 44.1 18.4 17.1
BIDU US Baidu China 61,015 575.9 31.5 24.1
7201 JP Nissan Motor Japan 41,749 117.2 7.0 6.9
002415 CH Hikvision China 41,723 226.5 31.1 24.0
6954 JP Fanuc Japan 37,276 152.4 28.4 26.1
DMP AU Domino's Pizza Australia 3,147 19.8 29.4 24.0
XRO AU Xero Australia 2,651 1.2 nm 235.9
098460 KS Koh Young Tech Korea 726 2.5 25.4 19.9
Source: Factset, CLSA
Sebastian Hou, CLST Taiwan, Technology [email protected] +886 2 2326 8165
Nicolas Baratte Head of Technology Research [email protected] +852 2600 8325
Section 4: Multibagger case studies Microstrategy
70 [email protected] 6 September 2017
Global stocks to play robotics and automation theme While application of AI will have potentially widespread implications across diverse sectors, the growing adoption of automation will certainly have a direct impact on the companies providing these services. Below we identify some of the robotics and automation firms across the world by going through the business description of each company. For some, automation/robotics could be a small part of the overall business currently, however, as global corporations start to embrace the automation theme, the growing demand could lead it to become the dominant revenue driver in the near future.
Figure 134
Global companies to play robotics and automation theme (sorted by market cap) Code Name Cty Sector Mkt cap FY1-FY2 ROIC FY1-FY2 Sustg 12MF Fwd PE PE/G NDE
(US$m) ROE (FY0, %) EPS Cagr (%) PE Reilly (x) (latest,
(avg, %) (%) (x) (10Y, %) %)
SIE GR Siemens GE Cap gds 112,032 16.8 7.4 11.9 7.8 13.9 74.1 1.2 47.1
HON US Honeywell Intl US Cap gds 103,848 28.5 15.9 8.5 16.8 18.1 99.0 2.1 32.7
6861 JP Keyence JP Tech HW 63,036 14.2 97.0 30.5 11.4 35.9 95.0 1.2 (53.7)
ABBN VX ABB CH Cap gds 49,315 19.5 11.2 3.4 4.2 17.5 67.5 5.2 14.1
SU FP Schneider Electric FR Cap gds 47,232 11.0 8.2 7.1 3.4 16.1 84.2 2.3 24.7
6954 JP Fanuc Corp JP Cap gds 37,276 10.8 21.0 11.5 4.3 26.6 29.0 2.3 (55.5)
EMR US Emerson Electric US Cap gds 37,131 22.5 13.0 (1.2) 7.6 20.1 78.0 nm 25.4
6503 JP Mitsubishi Electric JP Cap gds 32,078 11.5 13.5 11.6 8.5 14.0 14.5 1.2 (17.5)
ETN US Eaton Corp US Cap gds 31,421 13.6 8.2 10.0 6.3 14.3 55.7 1.4 49.9
6273 JP SMC Corp JP Cap gds 23,010 11.3 20.2 7.5 9.1 19.8 9.3 2.6 (46.1)
267250 KS Hyundai Robotics KR Semis 23,000 16.7 na na 16.6 5.7 na nm nm
ROK US Rockwell Automation US Cap gds 20,561 43.7 25.8 10.9 21.0 22.1 72.7 2.0 (35.5)
AME US AMETEK US Cap gds 14,427 16.6 10.7 10.4 14.2 23.1 96.0 2.2 52.5
2308 TT Delta Electronics TW Tech HW 13,904 16.2 17.6 11.1 5.1 19.1 72.8 1.7 (36.9)
6645 JP OMRON Corp JP Tech HW 10,694 11.9 13.0 17.1 7.7 19.7 15.0 1.2 (26.6)
CDNS US Cadence Design US Software 10,418 34.4 22.3 11.9 26.7 25.2 20.7 2.1 (1.6)
SKFB SS SKF AB SE Cap gds 8,999 18.4 8.5 19.3 7.5 13.1 53.2 0.7 45.7
6506 JP Yaskawa Electric JP Tech HW 7,889 16.1 10.1 22.3 10.5 23.5 36.4 1.1 (0.2)
9962 JP Misumi Group JP Cap gds 7,210 15.2 17.3 23.8 10.3 29.9 51.9 1.3 (34.1)
4684 JP OBIC JP Software 5,523 13.2 64.5 7.2 9.0 23.4 83.7 3.3 (53.5)
KU2 GR KUKA GE Cap gds 5,470 14.6 11.3 11.5 10.5 33.8 29.5 2.9 11.5
300024 CH SIASUN CN Cap gds 5,032 8.7 6.1 20.0 7.9 60.1 51.4 3.0 (4.4)
7012 JP Kawasaki Heavy JP Cap gds 4,980 8.9 4.0 31.0 5.6 13.5 6.9 0.4 82.0
FLS US Flowserve Corp US Cap gds 4,955 12.1 6.8 (4.0) 5.8 20.9 73.9 nm 63.7
6268 JP Nabtesco Corp JP Cap gds 4,333 13.8 13.8 14.6 7.4 20.6 43.1 1.4 (11.1)
6481 JP THK JP Cap gds 4,213 8.7 8.7 27.6 4.9 18.2 10.1 0.7 (20.3)
COB LN Cobham UK Cap gds 4,112 12.2 (37.9) (13.7) (16.7) 23.7 100.0 nm 46.4
6841 JP Yokogawa Electric JP Tech HW 4,056 10.2 12.3 6.6 8.2 15.8 6.0 2.4 (15.0)
1590 TT Airtac Intl TW Cap gds 2,407 24.7 11.2 37.6 10.3 21.5 75.0 0.6 77.1
2049 TT HIWIN Tech TW Cap gds 2,388 16.2 4.4 48.3 9.2 26.7 91.7 0.6 73.3
1504 TT Teco Electric TW Cap gds 1,858 7.4 9.4 10.1 3.5 14.0 76.1 1.4 (9.0)
012450 KS Hanwha Techwin KR Cap gds 1,800 5.3 5.4 (35.1) 4.7 15.3 31.0 nm 37.4
Note: For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: CLSA, Factset
Stocks to play robotics and automation theme
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 71
4. Capturing market share vs margins leaders The decision between growing market share versus defending margins is the crucial differentiator between companies over the long term. Typically companies focused on growth by expanding market share could do it at the expense of margins. The Asian margin/profitability decline during the pre-GFC period, despite improvement in asset turnover, is a classic example of this. At the company level, such behaviour is typically observed during the early-growth phase of the business cycle, when the company has the highest potential to evolve into a multibagger. However, reckless investment decisions could lead to chronic margin destruction, which is indeed counterproductive for future earnings growth. On the other hand, margin leaders are typically established companies which consistently strive to defend margins, but may or may not focus on growth.
The capturing-market-share basket has delivered strong topline growth over the past three years and also delivered impressive YoY outperformance over the same period. However, margin leaders have come back strongly over the past two years. Against the backdrop of peaking margins, defending current margins will be crucial and therefore in the medium term, margin leaders could remain in favour. Nonetheless, for investors looking for multibaggers, the capturing-market-share basket, which essentially consists of companies with strong track records of delivering growth and the promise to deliver more in the future, is an ideal investment strategy from an Asian perspective.
Figure 135 Figure 136
Performance - Margin leaders vs capturing market share YoY OPF - Margin leaders vs capturing market share
Note: Performance is calculated based on freefloat adjusted market cap. Source: Factset, CLSA
Figure 137 Figure 138
MSCI USA vs Asia ex-JP: Ebitda margin MSCI AsiaxJ (ex-fin): DuPont® breakdown of ROEs
Note: Ratios are bottom-up aggregated with freefloat adjustment based on current universe. Source: Factset, CLSA
0
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Capturing market share
Margin leaders
MSCI APxJ
(Index)26.6% Cagr
15.7% Cagr
(30)
(20)
(10)
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Capturing market share
Margin leaders
(YoY OPF, %)
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Ebitda margin (%)
Margin turning around in Asia
US margins compressed in 2014, after four years of consistent improvement
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Ebit margin ROE Asset turnover (RHS)(%) (x)
Sharp drop in asset turnover implies that Asia ROEs are now held up by margins
Capturing markets-share basket refers to firms
with strong promise to deliver growth . . .
. . . while margin leaders are the one who can
defend their margins successfully
Capturing market share basket consist of
potential multibaggers
Section 4: Multibagger case studies Microstrategy
72 [email protected] 6 September 2017
Asian margin leaders Competitive advantage is hard to maintain but some stocks have managed to keep a strong margin profile over the long term and with lower variability. Indeed, better variability is a key criterion when looking for margin leaders, along with rising trends.
The screening criteria for our margin-leaders list are as follows:
Broader ex-finance universe with market cap more than US$2bn
Ebitda margin forecast (FY1-FY2 average) > past 10Y average
Low margin variability with coefficient of variation (10-year CoV) of Ebitda margins less than 50%
Positive slope of margins over the past 10 years
Figure 139
Asian margin leaders (sorted by market cap) Code Name Cty Sector Mkt cap Ebitda margin (%) ROE 12M trl PB (x)
(US$m) FY1-FY2 L10Y L10Y CoV FY1-FY2 (x) 10Y Reilly avg avg slope (x) avg, %) (%) BABA US Alibaba CN Software 428,095 46.5 32.6 4.12 0.40 21.9 8.9 82.4
005930 KS Samsung Electronics KR Tech HW 283,600 31.9 19.8 1.08 0.19 19.5 1.6 62.6
2330 TT TSMC TW Semis 180,895 66.2 60.7 0.87 0.05 23.3 3.7 72.1
AVGO US Broadcom SG Semis 101,347 52.7 26.8 2.14 0.32 28.4 4.8 28.0
ITC IN ITC IN FBT 53,476 36.6 35.2 0.50 0.05 27.0 7.4 29.9
CSL AU CSL AU Pharma 45,589 32.9 31.3 0.24 0.08 41.5 13.8 81.8
000660 KS SK Hynix KR Semis 41,659 61.8 39.1 2.42 0.30 31.0 1.6 51.0
HUVR IN Hindustan Unilever IN HPC 40,276 20.4 14.9 0.55 0.12 93.0 38.8 100.0
1928 HK Sands China HK Cons svcs 36,154 32.3 26.7 1.59 0.21 37.0 7.8 67.0
HCLT IN HCL Tech IN Software 19,426 21.8 20.9 0.28 0.12 24.1 nm na
914 HK Conch CN Materials 18,813 31.1 29.0 0.30 0.15 14.1 1.6 6.5
PWGR IN Power Grid IN Utilities 17,951 88.7 84.0 0.78 0.03 17.1 2.2 40.8
SCC TB Siam Cement TH Materials 17,602 18.8 13.7 0.16 0.26 19.4 2.2 39.3
CPALL TB CP All TH Fd & drug 16,538 8.1 7.4 0.39 0.28 33.3 9.1 48.8
ADVANC TB AIS TH Telecom 16,175 44.0 37.1 1.97 0.18 62.5 11.6 50.5
288 HK WH Group CN FBT 14,866 10.4 7.7 0.37 0.38 16.6 2.2 96.0
AMC AU Amcor AU Materials 14,706 16.3 11.0 0.79 0.24 72.2 16.4 98.7
YUMC US Yum China CN Cons svcs 14,382 17.6 13.7 0.79 0.10 21.2 5.3 na
051900 KS LG H&H KR HPC 14,154 17.4 13.8 0.50 0.15 22.2 5.5 14.7
2308 TT Delta TW Tech HW 13,708 14.2 13.8 0.22 0.11 16.2 3.2 44.4
RHC AU Ramsay Healthcare AU Healthcare 12,027 15.4 13.4 0.23 0.07 25.5 6.8 77.4
1099 HK Sinopharm CN Healthcare 11,404 4.3 4.0 0.13 0.11 14.7 2.1 20.1
1216 TT Uni-President TW FBT 11,189 10.8 8.5 0.19 0.10 13.8 3.2 70.5
2196 HK Fosun Pharma CN Pharma 10,914 18.1 14.9 1.30 0.14 14.2 2.4 50.2
2313 HK Shenzhou Intl CN Cons dur 10,522 28.7 25.3 0.74 0.16 21.9 4.2 86.6
669 HK Techtronic HK Cons dur 8,974 12.5 9.5 0.47 0.15 18.7 3.4 79.1
151 HK Want Want CN FBT 8,883 25.8 23.9 0.46 0.10 25.1 4.4 9.9
1169 HK Haier Electronics CN Cons dur 7,604 5.9 4.5 0.11 0.19 16.6 2.6 24.4
CDH IN Cadila Healthcare IN Pharma 7,553 24.8 19.8 0.34 0.12 26.4 6.4 62.8
161390 KS Hankook Tire KR Autos 6,601 22.0 21.9 1.05 0.08 12.6 1.2 17.4
PIDI IN Pidilite IN Materials 6,501 21.4 16.5 0.50 0.16 24.4 11.3 74.6
1910 HK Samsonite HK Cons dur 5,481 17.6 13.3 1.06 0.34 17.8 3.5 73.6
DMP AU Domino's AU Cons svcs 3,147 22.9 13.9 1.13 0.26 53.0 10.1 50.0
Note: CoV = 100*standard deviation/average. For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA
Strong margin profile with low variability
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 73
Asian companies capturing market share Companies with solid free-cashflow-generating ability are ready to exploit value-accretive opportunities, regardless of their stage in the business lifecycle, while those with weaker cashflows struggle for survival. Such companies outperformed during the last downturn and came out even stronger. In the figure below, we highlight stocks that have grown their topline, even during the GFC, while generating positive FCF. These companies withstood the strong test presented by the GFC and have managed to thrive since the crisis. Even over the next two years, they are expected to deliver strong earnings growth. The screening criteria are as follows:
Positive YoY sales growth during GFC (2008/09)
Positive free cashflows: FY0 and last 5-year average
Double-digit YoY sales growth forecast for 17F and 18F
EPS Cagr (FY1-FY2) greater than 10%
Net gearing less than 50%
Figure 140
Asia Pacific ex-Japan (ex-finance): Growing while generating free cashflow (sorted by 18F sales growth) Code Name Cty Sector Mkt cap Sales growth (%) FCF conv (%) EPS Cagr Net gearing
(US$m) 08A 09A 16A 17F 18F FY0 L5Y avg (FY1-2, %) (latest, %) XRS US TAL Edu CN Cons svcs 8,689 319.2 86.1 68.3 59.5 47.7 234.2 167.3 58.3 (102.5) MYEG MK My E.G. Services MY Software 1,758 72.0 19.8 99.1 30.0 40.1 7.9 67.0 36.9 (10.9) 700 HK Tencent CN Software 394,835 87.2 73.9 47.7 51.7 32.8 118.8 122.6 39.5 (6.8) 175 HK Geely CN Autos 21,123 3,107 228 78.3 63.7 27.4 107.5 85.6 51.1 (66.9) 1530 HK 3SBio CN Pharma 3,162 35.5 30.3 67.2 28.1 26.4 81.9 106.0 28.7 31.0 CTD AU Corporate Travel AU Cons svcs 1,825 50.1 15.8 32.0 23.0 25.1 150.1 88.3 19.0 (18.0) EDU US New Oriental Edu CN Cons svcs 12,934 45.6 32.0 21.7 24.5 24.6 204.6 162.7 30.1 nm SRCM IN Shree Cement IN Materials 9,308 28.5 34.0 52.9 20.0 24.2 68.5 67.6 31.0 7.3 NTES US NetEase CN Software 36,062 39.4 21.8 67.4 41.3 24.0 123.6 112.6 15.2 (82.1) JBH AU1 JB Hi-Fi AU Retail 2,320 42.7 27.3 8.3 42.3 20.7 75.5 90.7 8.2 56.9 2020 HK Anta Sports CN Cons dur 10,409 54.8 27.0 20.0 19.6 18.2 77.1 86.3 18.1 (77.6) WHIRL IN Whirlpool IN Cons dur 2,353 9.9 28.8 14.6 19.9 17.9 111.4 86.7 24.8 nm TTAN IN Titan IN Cons dur 8,511 27.9 22.0 15.1 19.1 17.7 187.7 43.8 25.6 nm 1093 HK CSPC Pharma CN Pharma 9,408 37.0 3.0 8.6 16.3 16.1 81.7 66.0 26.6 (20.7) MSIL IN Maruti Suzuki IN Autos 35,400 12.5 46.3 18.2 18.9 16.1 91.2 74.9 16.9 (4.7) APNT IN Asian Paints IN Materials 16,986 24.0 22.3 7.1 17.5 15.8 43.5 65.4 15.1 (26.3) VGRD IN V-Guard IN Cap gds 1,180 13.9 43.3 15.5 13.3 15.6 49.7 69.5 21.8 (16.0) 867 HK CMS CN Pharma 4,196 28.2 30.6 37.9 20.5 15.4 71.9 45.7 18.1 18.2 SUNTV IN Sun TV IN Media 4,422 19.5 39.8 7.0 12.4 15.2 104.6 72.6 16.1 (33.1) 570 HK China TCM CN Pharma 2,464 14.1 49.2 76.1 16.4 15.2 21.9 34.2 18.4 13.0 1109 HK CR Land CN Property 20,372 64.9 77.8 5.2 13.3 14.3 69.7 109.0 17.0 29.7 3339 HK Lonking CN Cap gds 1,340 15.8 12.3 6.6 27.1 13.8 319.9 200.0 20.2 7.4 036570 KS NCsoft KR Software 7,044 5.2 83.0 17.3 74.6 13.8 33.9 81.4 42.2 (35.7) TNE AU Technology One AU Software 1,284 40.6 11.1 13.9 14.3 13.4 94.0 104.4 18.4 (46.1) 1999 HK Man Wah HK Cons dur 3,589 27.3 49.3 6.2 23.8 13.3 67.6 53.9 17.6 (21.9) EXID IN Exide IN Autos 2,671 14.3 16.9 17.7 13.2 12.9 69.3 76.4 15.6 (34.1) JFC PM Jollibee PH Cons svcs 4,943 13.4 9.3 13.0 13.3 12.2 130.5 97.4 13.4 (9.5) UNVR IJ Unilever Indo ID HPC 27,618 24.2 17.1 9.8 11.1 11.7 76.4 85.5 14.2 1.0 KLBF IJ Kalbe Farma ID Pharma 6,180 12.5 15.4 8.3 9.8 10.8 47.0 45.4 11.0 (26.1) 2383 TT Elite Material TW Tech HW 1,731 3.3 10.8 5.7 13.5 10.4 75.1 78.3 18.1 (37.5) WNS US WNS IN Software 1,892 18.9 11.8 7.2 22.8 10.1 131.8 145.9 12.9 (17.6) TLKM IJ Telkom ID Telecom 35,394 8.0 5.5 13.5 11.4 10.0 98.7 105.2 17.2 16.8 1 Net gearing criteria relaxed. Note: For Australia and New Zealand companies, FY1 refers to 18F and for others FY1 refers to 17F. Source: Factset, CLSA Source: CLSA, Factset
We look for stocks that flourish during downturns
while others worry about survival
Screening for positive FCF companies that grew
sales during GFC and are set to grow in 2017-18
Section 4: Multibagger case studies Microstrategy
74 [email protected] 6 September 2017
5. Ecommerce/internet - Analysing the potential threats As highlighted in the previous case studies, ecommerce and the internet are the most prominent themes to play the next leg of consumerism. However, investors must note that for large-cap companies such as Alibaba and Tencent, the potential to deliver another 3x returns are significantly limited. The hurdle rate has increased significantly as the companies have grown bigger. Moreover, if companies fail to sustain growth momentum, their premium valuations could come off. We analyse the potential risks faced by these two stocks by comparing them against previous megacaps and their experience of growth slowdown, and the implications on valuations and price.
Tencent and Alibaba: Time to take profit? Global large-caps tied to ecommerce and internet themes have already witnessed a market-cap surge beyond US$400bn (Tencent is close). Especially, the acceleration has been extremely steep in recent few years.
Figure 141 Figure 142
Market cap trend: Tencent versus Facebook Market cap trend: Alibaba versus Amazon
Source: CLSA, Factset Source: CLSA, Factset
Tencent has been a 350-bagger since 2004 Tencent has been a classic multibagger delivering 350x returns since 2004, during which, its sales and profit multiplied by 202x and 140x.
Figure 143
Tencent: Price vs sales vs net profits since 2004
Source: CLSA, Factset
397
491
0
50
100
150
200
250
300
350
400
450
500
Dec
04
Dec
05
Dec
06
Dec
07
Dec
08
Dec
09
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10
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11
Dec
12
Dec
13
Dec
14
Dec
15
Dec
16
Tencent
(US$bn)
443
474
0
50
100
150
200
250
300
350
400
450
500D
ec 0
4
Dec
05
Dec
06
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07
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16
Alibaba
Amazon
(US$bn)
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Price Sales Net profit351x
140x
202x
Rebased to 100
Tencent has been 351-bagger since 2004
For Alibaba and Tencent, the potential to deliver another 3x returns are
significantly limited
Large-caps tied to ecommerce/internet themes have seen a
market cap surge beyond US$400bn
Tencent has been a classic multibagger
delivering 350x returns since 2004
Over the same period, its sales and profit have
increased by 202x and 140x
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 75
What are the potential obstacles? While there are always several threats any company/industry inherently is exposed to, in the case of Tecent and Alibaba, the biggest existential concerns are their size and rich valuations which are reliant on their ability to maintain high levels of growth. Any catalyst, be it regulatory or company-specific, threatening the sustainability of future growth, could prove to be catastrophic for their future price action. We analyse previous episodes.
1. Size is the biggest hindrance In order to understand the implications of size on future price action, we analysed all the large-caps that have surpassed the US$300bn market-cap barrier. In the figure below, we highlight 19 such examples and their price performance since crossing the threshold. Only three out of 19 have become double-baggers, while five have delivered negative returns.
Figure 144
US$ total returns after surpassing US$300bn Mcap threshold
Source: CLSA, Factset
2. Premium valuations are not sustainable if the growth slows down Both Tencent and Alibaba are trading at valuations that are not only expensive relative to the underlying market valuations but also relative to their own history. Tencent at c.35x and Alibaba at 32x are both above +1sd levels and have witnessed 37% and 25% reratings this year alone.
Figure 145 Figure 146
Tencent: 12-month forward PE bands since 2010 Alibaba: 12-month forward PE bands since 2010
Source: CLSA, Factset Source: CLSA, Factset
265 256
163
82 55 39 35 35 29 24 23 8 4 3
(5)(30)
(55)(79) (89)
(150)(100)(50)
050
100150200250300
App
le
Mic
roso
ft
Exxo
n
Alp
habe
t
Wal
-Mar
t
Ber
kshi
re BP
J&J
ICBC
Pfiz
er GE
JPM
orga
n
Vod
afon
e
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na M
obile
Cis
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Petr
oChi
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Gaz
prom
Eric
sson
US$ total returns after surpassing US$300bn Mcap(%)
Jan-
11 Oct
13
Sep
00Nov
98
Mar
00
Oct
13
Dec
98
Jun
00
Oct
07
Sep
14
Sep
99
May
14
Dec
99
Nov
07
Sep
07
Dec
99
Sep
07
Jan
00
Mar
00
Yellow box represents the month during which the stock surpassed the US$300bn mark
Avg, 28.5
+1SD, 33.3
-1SD, 23.7
+2SD, 38.1
-2SD, 18.9
15
20
25
30
35
40
45
Dec
-09
Dec
-10
Dec
-11
Dec
-12
Dec
-13
Dec
-14
Dec
-15
Dec
-16
12M fwd PE (x)
Tencent derated from 36x to 17x
Avg, 27.1
+1SD, 31.7
-1SD, 22.5
+2SD, 36.3
-2SD, 17.915
20
25
30
35
40
45
Sep
-14
Dec
-14
Mar
-15
Jun-
15
Sep
-15
Dec
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Mar
-16
Jun-
16
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-16
Mar
-17
Jun-
17
12M fwd PE (x)
Alibaba derated from 40x to 20x
Analysing the potential threats
After surpassing US$300bn Mcap mark,
only three out of 19 could become double bagger. . .
. . . while five delivered negative returns
Tencent and Alibaba trading above +1sd
valuation level
Section 4: Multibagger case studies Microstrategy
76 [email protected] 6 September 2017
Valuations have tracked growth strongly Both Tencent and Alibaba are trading at expensive valuations, but the rerating has come on the back of a strong acceleration in earnings-growth momentum over the past few years. Indeed, if growth momentum continues, the companies will remain attractive investments. At the same time, any slowdown in growth momentum historically has come in conjunction with a valuation derating. Tencent derated from 36x to 17x during 2010-12, when growth decelerated from 40% to 20%. Similarly, Alibaba derated from 40x to 20x during 2014-15, when growth marginally slowed. Therefore, if these companies are exposed to a growth slowdown from current 35% expectations, both are vulnerable to a valuation-derating-driven price correction in the near term.
Figure 147 Figure 148
Tencent: fwd PE and 1Y forward growth Alibaba: fwd PE and 1Y forward growth
Source: CLSA, Factset Source: CLSA, Factset
Is 35% earnings growth sustainable? In order to understand the implications of size on the growth environment, we took the same set of large-cap companies that managed to surpass the US$300bn mark and analysed their growth track record. The analysis highlights that after surpassing the US$300bn market-cap mark, 14 of the 17 stocks witnessed a growth slowdown, with average growth decelerating from 26.6% over the previous five years to 10.5% over the next five.
Figure 149
EPS growth (next 5Y vs previous 5Y) of companies after reaching US$300bn Mcap
Source: CLSA, Factset
15
20
25
30
35
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45
Dec
-09
Jun-
10
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-10
Jun-
11
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-11
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12
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15
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Jun-
171yr fwd growth
12MF PE (x)
PE and growth (x, %)
Correlation = 0.40
Tencent derated from 36x to 17x
15
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45
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-14
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Jun-
17
12MF PE (x)
1yr fwd growth
PE and growth (x, %)
Alibaba derated from 40x to 20x
correlation = 0.59
13.8
15.8
19.0
8.9
(10.
5)
23.3
(5.1
) 12.7
(2.0
)
8.2
10.1
8.2 14
.5
20.5
12.6
2.1
25.7
(20)
0
20
40
60
80
100
Gaz
prom
App
le
Cis
co
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Eric
sson
ICBC
Petr
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obile
Ber
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Wal
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Exxo
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Pfiz
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BP
Previous 5Y EPS Cagr
Next 5Y EPS Cagr
(%) After surpassing US$300bn Mcap mark, 14 of the 17 stocks have witnessed growth slowdown with average growth decelerating from 26.6% over the previous five years to 10.5% over the next five
Historically slowdown in growth momentum has
come in conjunction with valuations derating
After surpassing US$300bn mark, 14 of the 17 stocks have witnessed
growth slowdown . . .
. . . with average growth falling from 26.6% over
the previous five years to 10.5% over the next five
Section 4: Multibagger case studies Microstrategy
6 September 2017 [email protected] 77
Margin deterioration is an ominous sign for Tencent Both Tencent and Alibaba are well known for their ability to deliver strong growth on a consistent basis. For instance, Tencent’s sales growth has remained in excess of 30% since 2006. Delivering such a high level of growth on a consistent basis is indeed a phenomenal feat. This trend was matched by another internet company - Baidu, which delivered sales growth in excess of 30% on a consistent basis during 2003-15, but witnessed a steep fall in growth to 6% in 2016. Preceding the topline growth decline, Baidu has also witnessed an operating-margin decline since 2014. During this period, the stock price corrected and failed to recover to the previous peak. This is important from Tencent’s perspective as well, because despite delivering strong growth, it has witnessed margin contraction over the past 12 months. The operating margins have fallen from 35.5% in June 2016 to around 30.5% based on the latest financials. On the other hand, Alibaba has witnessed a strong margin recovery from 27% two years ago to 32% now.
Figure 150 Figure 151
Baidu: Price versus operating margin Tencent and Alibaba: Operating margin trend
Source: CLSA, Factset Source: CLSA, Factset
A structural story, but beware of growth slowdown Alibaba is already the dominant ecommerce player in China, where the online retail share is still rising. However, a key risk is that the sector could face headwinds similar to the telecom stocks, whose prices peaked despite low and rising mobile penetration. For example, Bharti Airtel’s share price peaked in 2007 while mobile penetration in India was still only 20%. While the mobile penetration has increased to 88%, the stock never reached previous highs.
Figure 152 Figure 153
Internet (as a % of retail sales) Mobile phone penetration versus stock price
Source: CLSA, Factset Source: IDC, statista, ITU, GSMA, FactSet, CLSA
10
15
20
25
30
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40
140150160170180190200210220230240
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17
Price Operating margin (RHS) (%)
35.5
30.5
26.8
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45Ju
n 11
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17
Tencent AlibabaOperating margin (%)
10.4
17.1
0
2
4
6
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12
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16
18
20
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2003
2004
2005
2006
2007
2008
2009
2010
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2016
USA
China
Internet (% of retail sales)
Internet sales already a significant portion of overall sales in China
19.8
88.2 2461
2107
0
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100
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Dec
16
Mobile phone penetration (India)
Bharti Airtel (RHS)
(%) (Price index)
Bharti Airtel stockprice peaked in Oct'07 when mobile phone penetration in India was just 20%
Tencent has been witnessing operating
margin decline over the past 12 months
Historically margins decline did not bode well
for Baidu price action
Telecom stocks peaked in 2007, despite strong
increase in subscribers /data usage since then
Section 4: Multibagger case studies Microstrategy
78 [email protected] 6 September 2017
What if growth slows down? Taking into consideration past cases, it is important for investors to be mindful of the implications of a growth slowdown on valuations and prices. Below is a simple scenario analysis on both Tencent’s and Alibaba’s price action over the next three years, calculated based on current valuations using 12-month forward consensus EPS forecasts.
Tencent: Price implications if growth slows Over the next 12 months, Tencent is expected to deliver 35% earnings growth and is trading close to 35x. Historically, the relationship between the two variables has been tight. Below we highlight that from current levels, if Tencent earnings growth decelerates to a 20% Cagr over the next three years and trades at in-line valuations of 20x PE, the stock would deliver -4% returns. A slightly higher 20% return, if it trades at 25x valuations.
Figure 154
Tencent price up/downside1 scenario analysis based on growth and valuations
1Based on 25 Aug 2017 closing price and 12MF EPS forecast of 7.74 CNY. Source: CLSA, Factset
Alibaba: Price implications if growth slows down A similar analysis for Alibaba highlights 16% returns over the next three years, if growth slows to 20% and PE derates to 20x.
Figure 155
Alibaba price up/downside1 scenario analysis based on growth and valuations
1Based on 25 Aug 2017 closing price and 12M forward EPS forecast of 38.29 CNY. Source: CLSA, Factset
5 10 15 20 25 30 35 40
5 (84) (82) (79) (76) (73) (70) (66) (62)
10 (68) (63) (58) (52) (46) (39) (32) (24)
15 (52) (45) (37) (28) (19) (9) 2 14
20 (36) (26) (16) (4) 8 22 36 52
25 (20) (8) 5 20 35 52 70 90
30 (4) 11 26 44 62 83 104 128
35 12 29 47 68 89 113 139 166
40 28 47 68 91 116 143 173 204
45 44 66 90 115 143 174 207 242
50 60 84 111 139 170 204 241 280
Next 3-year EPS cagr (%)
12
MF
PE
(x)
Price up /downside (%)
5 10 15 20 25 30 35 40
5 (81) (78) (75) (71) (67) (63) (59) (54)
10 (61) (55) (49) (42) (35) (26) (18) (8)
15 (42) (33) (24) (13) (2) 10 24 38
20 (22) (11) 2 16 31 47 65 84
25 (3) 12 27 45 64 84 106 130
30 16 34 53 74 96 121 147 176
35 36 56 78 103 129 158 189 222
40 55 78 104 132 162 194 230 268
45 75 101 129 161 195 231 271 314
50 94 123 155 190 227 268 312 360
Price up /downside (%)
Next 3-year EPS cagr (%)
12
MF
PE
(x)
Scenario analysis to understand implications
of growth slowdown on prices
Negative returns if the growth slows down to
20% Cagr over the next years and PE derates 20x
Some 20% returns over the next three years if growth slows down to
20% and PE at 25x
Relatively better returns profile for Alibaba
To achieve 16% returns over the next three years, if growth falls to 20% and
PE derates to 20x
Appendix Microstrategy
6 September 2017 [email protected] 79
Appendix: Multibagger strategy Below we highlight the multibagger strategy results for different markets and sectors.
Figure 156 Figure 157
Multibagger strategy (mkt): Avg hit rate (since 2000) Multibagger strategy (sctr): Avg hit rate (since 2000)
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming over the next 5 years. Source: CLSA, Factset
Figure 158 Figure 159
Multibagger strategy (mkt): Avg hit rate (before 2010) Multibagger strategy (sctr): Avg hit rate (before 2010)
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming over the next 5 years. Source: CLSA, Factset
Figure 160 Figure 161
Multibagger strategy (mkt): Avg hit rate (since 2010) Multibagger strategy (sctr): Avg hit rate (since 2010)
Note: Broader APxJ universe with market cap of more than US$100m. Multibaggers are stocks that have tripled while outperforming over the next 5 years. Source: CLSA, Factset
29
19
15
12
18
10
16
7
38
26
23
20 2018 18
5
0
5
10
15
20
25
30
35
40
India China AsiaxJ HK Korea Aust Asean Taiwan
All multibaggers
Final result
Quarterly average hit rate of multibaggers (%, since 2000)
20
14 13
24
1816 15
23
11
7
12
3330 30
24 2423 23 22
17
14
7
0
5
10
15
20
25
30
35
Hea
lthca
re
Fina
ncia
ls
Util
ities
Ener
gy
Mat
eria
ls
Indu
stri
als
Con
s di
sc
Con
s st
ap
Prop
erty
Info
tec
h
Tele
com
All multibaggers
Final result
Quarterly average hit rate of multibaggers (%, since 2000)
30
22
14
17
20 17
10 8
39
31
23 2322
17 17
3
0
5
10
15
20
25
30
35
40
India China HK AsiaxJ Korea Asean Aust Taiwan
All multibaggers
Final result
Quarterly average hit rate of multibaggers (%, before 2010)
26
7
1013
7 8 9
16 17
3
6
34
29 2827
22 2119
15
5 5
1
0
5
10
15
20
25
30
35
Hea
lthca
re
Util
ities
Fina
ncia
ls
Con
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sc
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ls
Indu
stri
als
Info
tec
h
Con
s st
ap
Tele
com
Ener
gy
Prop
erty
All multibaggers
Final result
Quarterly average hit rate of multibaggers (%, before 2010)
22
910
1110
6 6 7
34
2221
20
12 12
7 6
0
5
10
15
20
25
30
35
India Aust AsiaxJ Asean Korea Taiwan China HK
All multibaggers
Final result
Quarterly average hit rate of multibaggers (%, since 2010)
19
15
29
15
21
24
18
1315
7
10
3331 30 30
25 2423 22 21
12
8
0
5
10
15
20
25
30
35
Hea
lthca
re
Fina
ncia
ls
Ener
gy
Util
ities
Mat
eria
ls
Con
s st
ap
Indu
stri
als
Prop
erty
Con
s di
sc
Info
tec
h
Tele
com
All multibaggers
Final result
Quarterly average hit rate of multibaggers (%, since 2010)
Important disclosures Microstrategy
80 [email protected] 6 September 2017
Companies mentioned 3SBio (1530 HK - HK$11.26 - BUY)¹ a2 Milk (N-R) AAC (2018 HK - HK$142.10 - SELL)¹ ABB India (N-R) ABB Ltd (N-R) Aconex Ltd (N-R) Advanced Ceramic X (3152 TT - NT$416.5 - BUY)² Advantech (2395 TT - NT$221.0 - SELL)² AEM (N-R) AEV (N-R) AIA (1299 HK - HK$60.50 - BUY)¹ Airports of Thailand (AOT TB - BT55.0 - U-PF)¹ Airtac (1590 TT - NT$412.5 - BUY)² AIS (ADVANC TB - BT190.5 - U-PF)¹ Alibaba (BABA US - US$171.04 - BUY)¹ Alliance Global (N-R) Altium (N-R) Amazon (N-R) Amcor (AMC AU - A$16.17 - O-PF)¹ Ametek (N-R) Amorepacific (090430 KS - ₩289,000 - O-PF)¹ Amorepacific Group (002790 KS - ₩133,500 - U-PF)¹ Anta Sports (2020 HK - HK$30.95 - O-PF)¹ Aristocrat (ALL AU - A$21.11 - O-PF)¹ Ascendas (AREIT SP - S$2.66 - O-PF)¹ Asian Paints Ltd. (N-R) Asian Seafoods (N-R) Askul (N-R) Asmedia Technology Inc. (N-R) ASPEED Technology Inc. (N-R) Astra (ASII IJ - RP7,875 - O-PF)¹ Aurobindo Pharma (ARBP IB - RS758.0 - O-PF)¹ Australian Agri (N-R) Autohome (ATHM US - US$65.33 - O-PF)¹ Axiata (AXIATA MK - RM4.93 - O-PF)¹ Ayala (AC PM - P920.00 - BUY)¹ Ayala Land (ALI PM - P42.00 - O-PF)¹ B2W Companhia (N-R) Baidu (BIDU US - US$232.64 - BUY)¹ Bajaj Finance (N-R) Bajaj Finserv Limited (N-R) Bangkok Dusit (BDMS TB - BT20.7 - BUY)¹ Bank Central Asia (BBCA IJ - RP18,950 - O-PF)¹ Bank Rakyat (BBRI IJ - RP15,125 - U-PF)¹ BDO Unibank (BDO PM - P127.10 - O-PF)¹ Beauty Community PCL (N-R) Bellamy's (BAL AU - A$7.72 - SELL)¹ Best World (BEST SP - S$1.18 - SELL)¹ Besttone (N-R) BGF Retail (027410 KS - ₩87,600 - O-PF)¹ BH Co., Ltd. (N-R) Bharti Airtel Limited (N-R) Bizlink (3665 TT - NT$264.0 - BUY)²
BJC (BJC TB - BT48.3 - SELL)¹ Blackmores (BKL AU - A$111.20 - SELL)¹ Bloomberry (N-R) BlueScope (BSL AU - A$10.78 - BUY)¹ Brambles (N-R) Britannia Industries (N-R) Broadcom (N-R) Bubs Australia Ltd. (N-R) BWX (BWX AU - A$5.69 - U-PF)¹ BYD Electronic (N-R) Cadence Design (N-R) Cadila Healthcare (CDH IB - RS507.7 - BUY)¹ Caltex (N-R) Can Fin Homes Ltd. (India) (N-R) CapitaLand (CAPL SP - S$3.78 - BUY)¹ CapitaLand Mall (CT SP - S$2.17 - O-PF)¹ Caplin Point Laboratories Limited (N-R) Catcher Tech (2474 TT - NT$383.5 - U-PF)¹ CDL Hosp Trust (N-R) Celltrion, Inc. (N-R) Central Pattana (CPN TB - BT71.3 - O-PF)¹ China Cord Blood (N-R) China Lodging (N-R) China Overseas Land (688 HK - HK$27.05 - BUY)¹ China Railway (390 HK - HK$6.40 - O-PF)¹ China Regenerative (N-R) China TCM (N-R) CHP Test Tech (N-R) Cirtek Holdings Philippines Corporation (N-R) City Developments (CIT SP - S$11.71 - BUY)¹ Cityneon (N-R) CJ CGV (N-R) CJ Corporation (N-R) CJ O Shopping (N-R) CMS (867 HK - HK$14.30 - BUY)¹ Cobham (N-R) Cochlear (COH AU - A$156.65 - U-PF)¹ Cogobuy (N-R) Com2us (078340 KS - ₩113,900 - BUY)¹ Conch (914 HK - HK$29.45 - O-PF)¹ Concraft Holding Co., Ltd. (N-R) Corporate Travel (N-R) CO-TECH DEVELOPMENT CORP. (N-R) Coway (021240 KS - ₩96,200 - O-PF)¹ CP All (CPALL TB - BT61.8 - O-PF)¹ CR Land (1109 HK - HK$24.50 - BUY)¹ CSL (CSL AU - A$130.99 - O-PF)¹ CSPC Pharma (1093 HK - HK$12.52 - O-PF)¹ Ctrip (CTRP US - US$50.63 - O-PF)¹ CUREXO Inc. (N-R) Dagang Nexchange (N-R) Dalmia Bharat Ltd. (N-R) DBS (DBS SP - S$20.62 - BUY)¹ Delta Dunia (N-R)
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6 September 2017 [email protected] 81
Delta Electronics (2308 TT - NT$164.0 - O-PF)² Digi (DIGI MK - RM4.84 - U-PF)¹ Domino's Pizza (DMP AU - A$42.47 - BUY)¹ Dongbu HiTek (N-R) DoubleUGames (N-R) Dwarikesh Sugar Industries Limited (N-R) Eaton (N-R) eBay (N-R) Edelweiss Financial Services Limited (N-R) EEI (N-R) Egis Technology (6462 TT - NT$305.0 - BUY)² Eicher Motors Limited (N-R) Ekovest (N-R) Elite Material (N-R) eMemory Technology, Inc. (N-R) Emerson (N-R) Estia Health (EHE AU - A$3.15 - O-PF)¹ Everbright (257 HK - HK$10.36 - BUY)¹ Evergrande (3333 HK - HK$23.00 - SELL)¹ Evolable Asia (N-R) EXEM Co., Ltd. (N-R) Exide Industries (EXID IB - RS204.2 - SELL)¹ Expedia (N-R) F@N Communications (2461 JP - ¥1,161 - SELL)¹ Fanuc (6954 JP - ¥21,345 - BUY)¹ FDG Kinetic (N-R) Fila (N-R) Filinvest Land (FLI PM - P1.91 - BUY)¹ Flextronics (N-R) Flowserve (N-R) Focus Tech (N-R) Fortescue (FMG AU - A$5.95 - U-PF)¹ Fosun Pharma (2196 HK - HK$29.20 - BUY)¹ Fraser & Neave (MY) (N-R) Fu Shou Yuan (N-R) Fullshare (N-R) Galaxy Entertainment (27 HK - HK$51.00 - O-PF)¹ Galaxy Resources Limited (N-R) Gamuda (GAM MK - RM5.34 - U-PF)¹ GD Nanzi (N-R) Geely (N-R) Genscript (N-R) Genting (GENT MK - RM9.71 - O-PF)¹ Genting Malaysia (GENM MK - RM5.87 - U-PF)¹ Genting Singapore (N-R) Global PMX (4551 TT - NT$172.5 - BUY)² Global Top (N-R) Globe Telecom (GLO PM - P2,000.00 - O-PF)¹ GLP (GLP SP - S$3.24 - O-PF)¹ Gourmet Master (2723 TT - NT$360.0 - BUY)² Grape King (N-R) Greentown Service Group Co. Ltd. (N-R) GS Home Shopping Inc. (N-R) GSK Consumer (SKB IS - RS5,334.9 - BUY)¹ Haier Electronics (1169 HK - HK$20.85 - BUY)¹
Haitian Antenna (N-R) Hana Tour (039130 KS - ₩83,200 - BUY)¹ Hankook Tire (161390 KS - ₩58,700 - O-PF)¹ Hanon Systems (N-R) Hanssem (009240 KS - ₩168,000 - BUY)¹ Hanwha Techwin (012450 KS - ₩38,650 - O-PF)¹ Hap Seng Cons (N-R) HCL Tech (HCLT IB - RS865.2 - BUY)¹ HDHS (N-R) HDS (069960 KS - ₩95,300 - U-PF)¹ Heveaboard Bhd. (N-R) Hikvision (002415 CH - RMB32.94 - BUY)¹ Himax Technologies (N-R) Hindustan Unilever (HUVR IB - RS1,215.7 - O-PF)¹ Hindustan Zinc (N-R) Hiwin (2049 TT - NT$270.0 - BUY)² HK Exchanges (388 HK - HK$215.00 - SELL)¹ Hon Hai (2317 TT - NT$117.5 - SELL)¹ Honeywell (N-R) Hota Industrial (1536 TT - NT$139.0 - BUY)² Hotai Motor (N-R) HS Industries (N-R) Hugel (N-R) Hyundai Motor (005380 KS - ₩143,000 - U-PF)¹ Hyundai Robotics (267250 KS - ₩440,500 - BUY)¹ IDP Education (N-R) IGG, Inc. (N-R) IHH (IHH MK - RM5.99 - U-PF)¹ IIFL (N-R) InBody (N-R) Indiabulls Housing Finance Ltd. (N-R) Indika Energy (N-R) Indofood CBP (ICBP IJ - RP8,725 - U-PF)¹ Infomart (N-R) Interpark (N-R) Inti Kapuas Arowana (N-R) IPH (N-R) ITC (ITC IB - RS283.6 - U-PF)¹ Japara Healthcare (JHC AU - A$1.70 - U-PF)¹ Jardine Matheson (JM SP - US$65.71 - O-PF)¹ Jardine Strategic (JS SP - US$43.85 - O-PF)¹ JB Hi-Fi (JBH AU - A$22.80 - O-PF)¹ JD.com (JD US - US$41.99 - BUY)¹ Jeju Air Co., Ltd. (N-R) JG Summit (N-R) Jinro (N-R) JMT Network Services Co., Ltd. (N-R) Jollibee (JFC PM - P238.20 - O-PF)¹ Kalbe Farma (KLBF IJ - RP1,710 - BUY)¹ KEI Industries (N-R) Keppel Corp (KEP SP - S$6.31 - BUY)¹ Keyence (6861 JP - ¥57,390 - O-PF)¹ KHI (7012 JP - ¥340 - O-PF)¹ Kia Motors (000270 KS - ₩35,550 - U-PF)¹ Kingpak (N-R)
Important disclosures Microstrategy
82 [email protected] 6 September 2017
Kingston Financial (N-R) KMC (5306 TT - NT$140.0 - BUY)² Koh Young Technology Inc. (N-R) Korea Zinc (010130 KS - ₩510,000 - BUY)¹ KT (030200 KS - ₩31,150 - BUY)¹ KUKA (N-R) L&T Finance Holdings Limited (N-R) LandMark (3081 TT - NT$397.0 - BUY)² Largan (3008 TT - NT$5,870.0 - SELL)¹ Legend (N-R) Leyou Technologies Holdings Limited (N-R) LG Display (034220 KS - ₩30,750 - U-PF)¹ LG Electronics (066570 KS - ₩83,600 - SELL)¹ LG H&H (051900 KS - ₩953,000 - O-PF)¹ Liberty Interac (N-R) Liberty Interactive (N-R) LifeTech Scientific Corporation (N-R) Livzon Pharma (1513 HK - HK$42.80 - BUY)¹ L'Occitane (973 HK - HK$18.48 - O-PF)¹ Loen Entertainment Inc. (N-R) LONGTU KOREA Inc. (N-R) Lonking (3339 HK - HK$3.07 - BUY)¹ LOT Vacuum Co., Ltd. (N-R) Lotte Chemical (011170 KS - ₩403,000 - U-PF)¹ Lotte Chilsung Beverage Co., Ltd (N-R) Lotte Confectionery (N-R) Lotte Shopping (023530 KS - ₩243,500 - SELL)¹ Macquarie (MQG AU - A$86.81 - BUY)¹ MAEIL HOLDINGS CO. LTD. (N-R) Man Wah (1999 HK - HK$7.30 - BUY)¹ Manila Electric (MER PM - P271.00 - O-PF)¹ Maple Leaf Edu (1317 HK - HK$6.79 - BUY)¹ Maruti Suzuki (MSIL IB - RS7,812.7 - BUY)¹ MediaTek (2454 TT - NT$272.0 - SELL)¹ Meere Company Incorporated (N-R) Mega Expo Holdings Ltd. (N-R) Megawide (MWIDE PM - P17.50 - BUY)¹ MercadoLibre (N-R) Microfriend, Inc. (N-R) Minda Industries Limited (N-R) MindTree (N-R) Minor (MINT TB - BT39.8 - O-PF)¹ Minth (425 HK - HK$37.35 - BUY)¹ MISC (N-R) MISUMI (N-R) Mitsubishi Electric (6503 JP - ¥1,680 - BUY)¹ Mobile Internet (China) Holdings Limited (N-R) Momo (MOMO US - US$38.20 - O-PF)¹ Motherson Sumi Systems Limited (N-R) Motilal Oswal Financial Services Limited (N-R) Moya Holdings Asia Ltd. (N-R) Muangthai Leasing (N-R) MYEG (MYEG MK - RM2.12 - BUY)¹ Nabtesco (6268 JP - ¥3,890 - O-PF)¹ Nanya Technology (N-R)
Nasmedia (089600 KS - ₩49,600 - BUY)¹ Navin Fluorine International Limited (N-R) NCsoft (036570 KS - ₩396,000 - SELL)¹ Netdragon (N-R) NetEase (NTES US - US$269.89 - U-PF)¹ Netflix (N-R) Network18 Media & Investments Ltd. (N-R) New Oriental Edu (EDU US - US$84.12 - O-PF)¹ Nexteer (N-R) Nissan Motor (7201 JP - ¥1,096 - BUY)¹ Nongshim (N-R) Nuvoton Technology Corporation (N-R) Obic (N-R) Omron (N-R) On-Bright Electronics Co. Ltd. (N-R) O-Net (N-R) OOIL (N-R) Orion (N-R) Osstem Implant (N-R) Parade Technologies, Ltd. (N-R) Pati Games Corp. (N-R) Pegatron (4938 TT - NT$94.3 - U-PF)¹ Persistent Systems Limited (N-R) Petronas Dagangan (N-R) Pidilite Industries Limited (N-R) Pilbara Minerals Limited (N-R) PLDT (TEL PM - P1,730.00 - BUY)¹ Power Grid (PWGR IB - RS216.6 - BUY)¹ PPB (N-R) Priceline (N-R) Programmed Maintenance Services Limited (N-R) PT Link Net Tbk (N-R) PT PP Properti Tbk (N-R) PT Sitara Propertindo Tbk (N-R) PTG Energy Public Co. Ltd. (N-R) PTT (PTT TB - BT400.0 - BUY)¹ Public Bank (PBK MK - RM20.60 - U-PF)¹ PVR Limited (N-R) Q Technology (1478 HK - HK$19.60 - BUY)¹ Qantas (N-R) Quanta (2382 TT - NT$68.7 - BUY)¹ Raffles Medical (RFMD SP - S$1.10 - SELL)¹ Rakuten (4755 JP - ¥1,304 - O-PF)¹ Ramelius Res (N-R) Ramsay Health Care (RHC AU - A$67.06 - BUY)¹ REA (N-R) Realord Group Holdings Limited (N-R) Realtek (2379 TT - NT$115.0 - BUY)² Richwave (N-R) RM Group Holdings Ltd. (N-R) Robinsons Retail (RRHI PM - P90.75 - O-PF)¹ Rockwell (N-R) S.M. Entertainment Co., Ltd. (N-R) Sampoerna (HMSP IJ - RP3,640 - U-PF)¹ Samsonite (1910 HK - HK$32.55 - BUY)¹
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6 September 2017 [email protected] 83
Samsung Electronics (005930 KS - ₩2,324,000 - BUY)¹ Sands China (1928 HK - HK$36.50 - O-PF)¹ Schneider Electric (N-R) Semirara (SCC PM - P173.60 - BUY)¹ Shenzhou (2313 HK - HK$63.40 - BUY)¹ Shree Cement (SRCM IB - RS17,780.0 - U-PF)¹ Siam Cement (SCC TB - BT496.0 - O-PF)¹ Siasun Robot (N-R) Siemens AG (N-R) Silicon Motion (N-R) Sime Darby (SIME MK - RM9.00 - BUY)¹ Sina (SINA US - US$106.66 - O-PF)¹ Singapore Exchange (SGX SP - S$7.50 - O-PF)¹ Singtel (ST SP - S$3.70 - O-PF)¹ Sino Biopharm (1177 HK - HK$7.14 - BUY)¹ Sinopharm (1099 HK - HK$36.20 - BUY)¹ SJM (880 HK - HK$7.12 - SELL)¹ SK Hynix (000660 KS - ₩68,700 - BUY)¹ SKF AB (N-R) SM Investments (N-R) SM Prime (SMPH PM - P33.40 - SELL)¹ SMC (N-R) Sohu (N-R) Srisawad (N-R) Sritex (N-R) ST Engineering (STE SP - S$3.65 - O-PF)¹ Start Today (N-R) Sun Pharma Adv (N-R) Sun TV (SUNTV IB - RS768.0 - BUY)¹ Sunny Friend (N-R) Sunny Optical (2382 HK - HK$114.60 - O-PF)¹ Sunonwealth (N-R) Synnex (Thailand) Public Co., Ltd. (N-R) TAL Education Group Sponsored ADR Class A (N-R) Tapaco Public Co., Ltd. (N-R) Tata Consultancy (TCS IB - RS2,463.2 - BUY)¹ Tata Elxsi (N-R) Tata Global Beverages Limited (N-R) Tata Motors (TTMT IB - RS390.7 - SELL)¹ TCI Co. Ltd. (N-R) TechnologyOne (N-R) Techtronic (N-R) Teco (N-R) Telkom (TLKM IJ - RP4,690 - BUY)¹ Tenaga (TNB MK - RM14.28 - SELL)¹ Tencent (700 HK - HK$326.20 - BUY)¹ ThaiBev (THBEV SP - S$0.93 - BUY)¹ Thirumalai Chemicals Limited (N-R)
THK (6481 JP - ¥3,695 - O-PF)¹ Tianneng Power (N-R) Titan (TTAN IB - RS613.0 - BUY)¹ Trade Me Group Limited (N-R) Tripadvisor (N-R) TSMC (2330 TT - NT$216.5 - BUY)² TTY Biopharm (N-R) UMS (N-R) Unilever Indo (UNVR IJ - RP50,550 - O-PF)¹ Union Semiconductor Equipment Co., Ltd. (N-R) Uni-President (1216 TT - NT$63.8 - BUY)² Unisem M (N-R) United Tractors (UNTR IJ - RP30,300 - BUY)¹ Universal Robina (URC PM - P146.10 - BUY)¹ Vakrangee (N-R) V-Guard Industries Limited (N-R) Vipshop (VIPS US - US$9.12 - BUY)¹ Vitarich (N-R) Vivotek Inc (N-R) Voyage Gr (N-R) VS Industry (N-R) Want Want (151 HK - HK$5.25 - U-PF)¹ Webjet (N-R) Weibo (WB US - US$104.72 - BUY)¹ Wesfarmers (WES AU - A$42.44 - BUY)¹ Westfield (WFD AU - A$7.58 - O-PF)¹ WH (288 HK - HK$8.41 - BUY)¹ Whirlpool Of India Limited (N-R) Wing Tai (N-R) Wisdom Edu (6068 HK - HK$3.30 - BUY)¹ WNS (Holdings) Limited Sponsored ADR (N-R) Woolworths (WOW AU - A$25.79 - SELL)¹ Workpoint (N-R) Xero (XRO AU - A$23.60 - BUY)¹ Xero Limited (N-R) Xiabuxiabu Catering Management (China) Holdings Co., Ltd. (N-R) Yaskawa Electric (6506 JP - ¥3,335 - O-PF)¹ YFC-BonEagle Electric Co., Ltd. (N-R) YiChang HEC ChangJiang Pharmaceutical Co. Ltd. Class H (N-R) YMC Co., Ltd. (Korea) (N-R) Yokogawa Electric (N-R) YTL (N-R) Yuan Feng (N-R) Yum China (N-R) Zalando (N-R) ZTE (N-R)
¹ Covered by CLSA; ² Covered by CLST The above shows our fundamental ratings on these stocks.
Important disclosures Microstrategy
84 [email protected] 6 September 2017
Analyst certification The analyst(s) of this report hereby certify that the views expressed in this research report accurately reflect my/our own personal views about the securities and/or the issuers and that no part of my/our compensation was, is, or will be directly or indirectly related to the specific recommendation or views contained in this research report.
Important disclosures The policy of CLSA (which for the purpose of this
disclosure includes its subsidiary CLSA B.V.) and CL Securities Taiwan Co., Ltd. (“CLST”) is to only publish research that is impartial, independent, clear, fair, and not misleading. Analysts may not receive compensation from the companies they cover. Regulations or market practice of some jurisdictions/markets prescribe certain disclosures to be made for certain actual, potential or perceived conflicts of interests relating to a research report as below. This research disclosure should be read in conjunction with the research disclaimer as set out at www.clsa.com/disclaimer.html and the applicable regulation of the concerned market where the analyst is stationed and hence subject to. This research disclosure is for your information only and does not constitute any recommendation, representation or warranty. Absence of a discloseable position should not be taken as endorsement on the validity or quality of the research report or recommendation.
To maintain the independence and integrity of CLSA’s
research, our Corporate Finance, Sales Trading and Research business lines are distinct from one another. This means that CLSA’s Research department is not part of and does not report to CLSA Corporate Finance (or “investment banking”) department or CLSA’s Sales and Trading business. Accordingly, neither the Corporate Finance nor the Sales and Trading department supervises or controls the activities of CLSA’s research analysts. CLSA’s research analysts report to the management of the Research department, who in turn report to CLSA’s senior management.
CLSA has put in place a number of internal controls
designed to manage conflicts of interest that may arise as a result of CLSA engaging in Corporate Finance, Sales and Trading and Research activities. Some examples of these controls include: the use of information barriers and other information controls designed to ensure that confidential information is only shared on a “need to know” basis and in compliance with CLSA’s Chinese Wall policies and procedures; measures designed to ensure that interactions that may occur among CLSA’s Research personnel, Corporate Finance and Sales and Trading personnel, CLSA’s financial product issuers and CLSA’s research analysts do not compromise the integrity and independence of CLSA’s research.
Neither analysts nor their household members/associates/may have a financial interest in, or be an officer, director or advisory board member of companies covered by the analyst unless disclosed herein. In circumstances where an analyst has a pre-existing holding in any securities under coverage, those holdings are grandfathered and the analyst is prohibited from trading such securities.
Unless specified otherwise, CLSA/CLST did not receive
investment banking/non-investment banking income from, and did not manage/co-manage a public offering for, the listed company during the past 12 months, and it does not expect to receive investment banking compensation from the listed company within the coming three months. Unless mentioned otherwise, CLSA/CLST does not own a material discloseable position, and does not make a market, in the securities.
As analyst(s) of this report, I/we hereby certify that
the views expressed in this research report accurately reflect my/our own personal views about the securities and/or the issuers and that no part of my/our compensation was, is, or will be directly or indirectly related to the specific recommendation or views contained in this report or to any investment banking relationship with the subject company covered in this report (for the past one year) or otherwise any other relationship with such company which leads to receipt of fees from the company except in ordinary course of business of the company. The analyst/s also state/s and confirm/s that he/she/they has/have not been placed under any undue influence, intervention or pressure by any person/s in compiling this research report. In addition, the analysts included herein attest that they were not in possession of any material, nonpublic information regarding the subject company at the time of publication of the report. Save from the disclosure below (if any), the analyst(s) is/are not aware of any material conflict of interest.
Key to CLSA/CLST investment rankings: BUY: Total
stock return (including dividends) expected to exceed 20%; O-PF: Total expected return below 20% but exceeding market return; U-PF: Total expected return positive but below market return; SELL: Total return expected to be negative. For relative performance, we benchmark the 12-month total forecast return (including
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6 September 2017 [email protected] 85
dividends) for the stock against the 12-month forecast return (including dividends) for the market on which the stock trades.
We define as “Double Baggers” stocks we expect to
yield 100% or more (including dividends) within three years at the time the stocks are introduced to our “Double Bagger” list. "High Conviction" Ideas are not necessarily stocks with the most upside/downside, but those where the Research Head/Strategist believes there is the highest likelihood of positive/negative returns. The list for each market is monitored weekly.
Overall rating distribution for CLSA/CLST only
Universe: Overall rating distribution: BUY / Outperform - CLSA:
64.52%; CLST only: 67.61%, Underperform / SELL - CLSA: 35.48%; CLST only: 32.39%, Restricted - CLSA: 0.00%; CLST only: 0.00%. Data as of 30 June 2017.
Investment banking clients as a % of rating category:
BUY / Outperform - CLSA: 4.77%; CLST only: 0.00%, Underperform / SELL - CLSA: 2.98%; CLST only: 0.00%, Restricted - CLSA: 0.00%; CLST only: 0.00%. Data for 12-month period ending 30 June 2017.
There are no numbers for Hold/Neutral as CLSA/CLST
do not have such investment rankings. For a history of the recommendations and price
targets for companies mentioned in this report, as well as company specific disclosures, please write to: (a) CLSA, Group Compliance, 18/F, One Pacific Place, 88 Queensway, Hong Kong and/or; (b) CLST Compliance (27/F, 95, Section 2 Dun Hua South Road, Taipei 10682, Taiwan, telephone (886) 2 2326 8188). © 2017 CLSA Limited and/or CLST.
© 2017 CLSA Limited, and/or CL Securities Taiwan Co., Ltd. (“CLST”)
This publication/communication is subject to and
incorporates the terms and conditions of use set out on the www.clsa.com website (www.clsa.com/disclaimer.html.). Neither the publication/communication nor any portion hereof may be reprinted, sold, resold, copied, reproduced, distributed, redistributed, published, republished, displayed, posted or transmitted in any form or media or by any means without the written consent of CLSA group of companies (“CLSA”) and/or CLST.
CLSA and/or CLST have produced this
publication/communication for private circulation to professional, institutional and/or wholesale clients only.
This publication/communication may not be distributed or redistributed to retail investors. The information, opinions and estimates herein are not directed at, or intended for distribution to or use by, any person or entity in any jurisdiction where doing so would be contrary to law or regulation or which would subject CLSA and/or CLST to any additional registration or licensing requirement within such jurisdiction. The information and statistical data herein have been obtained from sources we believe to be reliable. Such information has not been independently verified and we make no representation or warranty as to its accuracy, completeness or correctness. Any opinions or estimates herein reflect the judgment of CLSA and/or CLST at the date of this publication/communication and are subject to change at any time without notice. Where any part of the information, opinions or estimates contained herein reflects the views and opinions of a sales person or a non-analyst, such views and opinions may not correspond to the published view of CLSA and/or CLST. This is not a solicitation or any offer to buy or sell. This publication/communication is for information purposes only and does not constitute any recommendation, representation, warranty or guarantee of performance. Any price target given in the report may be projected from one or more valuation models and hence any price target may be subject to the inherent risk of the selected model as well as other external risk factors. This is not intended to provide professional, investment or any other type of advice or recommendation and does not take into account the particular investment objectives, financial situation or needs of individual recipients. Before acting on any information in this publication/communication, you should consider whether it is suitable for your particular circumstances and, if appropriate, seek professional advice, including tax advice. CLSA and/or CLST do/does not accept any responsibility and cannot be held liable for any person’s use of or reliance on the information and opinions contained herein. To the extent permitted by applicable securities laws and regulations, CLSA and/or CLST accept(s) no liability whatsoever for any direct or consequential loss arising from the use of this publication/communication or its contents. Where the publication does not contain ratings, the material should not be construed as research but is offered as factual commentary. It is not intended to, nor should it be used to form an investment opinion about the non-rated companies.
Subject to any applicable laws and regulations at any
given time, CLSA, CLST, their respective affiliates or companies or individuals connected with CLSA /CLST may have used the information contained herein before publication and may have positions in, may from time to time purchase or sell or have a material interest in any of
Important disclosures Microstrategy
86 [email protected] 6 September 2017
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Important disclosures Microstrategy
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© 2017 CLSA Limited (“CLSA”) and/or CL Securities Taiwan Co. Ltd (“CLST”). Key to CLSA/CLST investment rankings: BUY: Total stock return (including dividends) expected to exceed 20%; O-PF: Total expected return below 20% but exceeding market return; U-PF: Total expected return positive but below market return; SELL: Total expected return to be negative. For relative performance, we benchmark the 12-month total forecast return (including dividends) for the stock against the 12-month forecast return (including dividends) for the market on which the stock trades. • We define as “Double Baggers” stocks we expect to yield 100% or more (including dividends) within three years at the time the stocks are introduced to our “Double Bagger” list. "High Conviction" Ideas are not necessarily stocks with the most upside/downside but those where the Research Head/Strategist believes there is the highest likelihood of positive/negative returns. The list for each market is monitored weekly. 06/07/2017
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