China E-Commerce Technology Initiation of Coverage Software & Services

Deutsche Bank Research

Asia Industry Date China 27 May 2019

China E-commerce Technology Initiation of Coverage Software & Services

A tale of two camps - and we favor the one with strong growth prospects Han Joon Kim We have a growth bias in the China e-commerce landscape and hence favor Alibaba Research Analyst and Pinduoduo (PDD). We also like VIPS as a GARP stock. We reiterate Buy on Aliba- +852-2203 6157 ba, initiate coverage of PDD as a Buy, VIPShop (VIPS) as a Buy, and JD.com (JD) as a Hold. We adjusted Alibaba's valuation in synchronizing all our e-commerce Maria Ma Research Associate stocks, which lifts its target price to US$220 from US$197. In this report, we look +852-2203 6242 at the key themes reverberating across the China e-commerce landscape, which we have put together after our interviews with companies, industry experts and merchants. We look at the evolution of the FMCG segment and the demographic Key Changes and geographic penetration in China, along with a comparison of the key metrics Company Target Price Rating and market positioning of leading companies. BABA.N 197.00 to 220.00 - JD.OQ - to 29.40 - to Hold PDD.OQ - to 26.20 - to Buy We favor the growth-oriented camp VIPS.N - to 9.30 - to Buy At the risk of oversimplifying a dynamic and complex market, we see two camps Source: Deutsche Bank emerging in the Chinese e-commerce landscape. One camp comprises companies with a meaningful TAM (total addressable market) outlook but a weaker near-term profit momentum as they invest in operations. We include Alibaba and PDD in this Companies featured growth-oriented camp. The other camp consists of companies with slower top-line Alibaba (BABA.N), USD156.00 Buy growth but which are transitioning towards a focus on sustainable profit rather than 2019A 2020E 2021E P/E (x) 29.7 22.7 16.5 revenue growth. JD and VIPS are in this camp. Both camps are equally viable as EV/EBITDA (x) 21.7 16.6 11.6 investable stocks but we favor the growth-oriented camp for two reasons. 1) We are EV/FCF (x) 35.1 29.1 21.4 not paying for a significantly higher valuation of these stocks' underlying core oper- JD.com (JD.OQ), USD26.70 Hold ations. For example, Alibaba is trading at 17x EV/EBITDA vs. JD at 22x in CY19E and 2018A 2019E 2020E P/E (x) 69.7 35.7 25.0 PDD is trading at 7x EV/FCF vs. VIPS at 10x in CY20E. 2) The latter camp has shifted EV/EBITDA (x) 42.9 21.9 14.9 to a profit-focused strategy in the past few quarters and we are not yet sure whether EV/FCF (x) - 42.5 12.7 this strategy will be sustained and executed on a multi-year basis. After all, China Pinduoduo (PDD.OQ), USD20.53 Buy has a dynamic e-commerce scene that is prone to new competitive and regulatory 2018A 2019E 2020E risks. P/E (x) -30.3 -35.1 40.7 EV/EBITDA (x) -40.9 -20.7 35.4 EV/FCF (x) 18.3 21.5 7.2 KPI comparison across e-commerce platforms, including a merchant ROI analysis Vipshop (VIPS.N), USD7.50 Buy Given the notoriously different disclosure metrics and definitions across the com- 2018A 2019E 2020E P/E (x) 12.9 11.2 8.3 panies and data sources, we spent a meaningful amount of time curating the data EV/EBITDA (x) 7.2 6.1 4.3 shown herein . We compare and contrast key KPIs such as the GMV, fulfilled order EV/FCF (x) 13.5 18.2 10.0 volume and average ticket size, fulfillment cost and user acquisition efficiency of Source: Deutsche Bank leading e-commerce players. We took time to interview merchants and analyze

Deutsche Bank AG/Hong Kong Deutsche Bank does and seeks to do business with companies covered in its research reports. Thus, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report Distributed on: 26/05/2019 21:00:14 GMT as only a single factor in making their investment decision. DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1. MCI (P) 066/04/2019. THE CONTENT MAY NOT BE DISTRIBUTED IN THE PEOPLE'S REPUBLIC OF CHINA ("THE PRC") (EXCEPT IN COMPLIANCE WITH THE APPLICABLE LAWS AND REGULATIONS OF PRC), EXCLUDING SPECIAL ADMINISTRATIVE REGIONS OF HONG KONG AND MACAU.

7T2se3r0Ot6kwoPa 27 May 2019 Software & Services China E-commerce data on brands and customers, which resulted in our merchant ROI calculations of different e-commerce platforms. The results present a clearer picture of market positioning and the key pain points, which we advise investors to look out for. For one, we believe PDD will need to justify its merchant ROI over the coming quarters.

Valuations and key risks Our analysis of the historical valuations of the e-commerce stocks indicates that investors have valued growth significantly over value in this space; there is a wide range of valuations, depending on the perceived growth prospects. We use EV/ EBITDA and EV/FCF to focus on a cash-based earnings outlook. The key industry risks are increasing user acquisition cost due to competition, regulatory interven- tion, and an aggressive pace of investment.

Page 2 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Table Of Contents

Industry overview...... 5 Focus on New Retail for growth...... 5 Geographic expansion...... 8

Focal points for key e-commerce stocks in 2019...... 14 Profit margin trend to stabilize in 2019E; signs of a rising marg...... 14 Driver of profit margin #1: User acquisition cost...... 16 Driver of profit margin #2: Compare unit economics among merchant ...... 16

Valuations...... 18 Valuation framework ...... 18 Valuation details...... 18 Valuation comparisons...... 19

Alibaba...... 23

JD.com...... 25

Outlook and financial forecasts...... 27

Valuation and key risks...... 33 Valuation...... 33 Key risks...... 33

Company profile...... 34 Shareholding structure...... 34 Management profile...... 35

Pinduoduo...... 36

Outlook and financial forecast...... 38 Marketing cost is the key variable in turning profitable...... 39 Financial forecasts...... 40

Valuation and key risks...... 45 Valuation framework ...... 45 Key risks...... 45

Company profile...... 46 Shareholding structure...... 46 Management profile...... 47

Vipshop...... 48

Outlook and financial forecasts...... 50

Deutsche Bank AG/Hong Kong Page 3 27 May 2019 Software & Services China E-commerce

Table Of Contents

Valuation and key risks...... 55 Valuation framework ...... 55 Earnings sensitivity...... 55 Key downside risks...... 56

Company profile...... 57 Shareholding structure...... 57 Management profile...... 58

Page 4 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce Industry overview

We see two main industry trends driving the corporate strategy of major e-commerce players in China: 1) a category shift towards FMCG and a repositioning of core expertise, and 2) diverse demographic and geographic segmentation, which encourages companies to seek a larger user base.

Focus on New Retail for growth

Key growth focus in underpenetrated FMCG segment One of the key underlying themes in e-commerce continues to be the push towards FMCG (fast-moving consumer goods) segment penetration, as e-commerce evolves from standardized products with a longer shelf life (e.g. 3C - computer, communication, consumer electronics) towards non-standard products with a shorter shelf life (e.g. groceries). We believe China is still at an early stage of its investment cycle, which may continue for several more years before we enter a meaningful harvesting cycle.

To put the figures into perspective, Euromonitor data indicates that China's e-commerce penetration is 23% in 2018, one of the highest among other developed e-commerce markets. However, in the FMCG category, and in particular, the food and beverage segment, China still has room to scale up, with a penetration rate of 9%. In comparison, South Korea has high penetration in both total e-commerce and FMCG, at least providing an indication that FMCG penetration can rise meaningfully once infrastructure is developed.

Figure 1: E-commerce penetration comparison by country

25%

20%

15%

10%

China Korea Japan Brazil

Source : Euromonitor

Deutsche Bank AG/Hong Kong Page 5 27 May 2019 Software & Services China E-commerce

Figure 2: FMCG penetration and breakdown by sub-category Online penetration, 2018 China Korea US Japan Brazil FMCG 9.0% 21.1% 4.1% 3.6% 0.4% Food and drink 7.7% 22.1% 2.3% 3.2% 0.2% Consumer Health 22.2% 11.8% 11.5% 8.3% 1.4% Home Care 15.2% 10.5% 2.8% 2.1% 0.4% Pet Care 36.9% 36.0% 16.8% 11.7% 2.2%

Source : Euromonitor

Food and drink, which contributes nearly 80% of FMCG category, has only 7.7% online penetration, vs. Korea at 22.1%. Euromonitor estimates suggest food and drink's online penetration could rise to 10.4% in 2022E, within which we believe the upside will mostly come from the fresh food sub-category. Major market players such as Miss Fresh – an upcoming start-up in the fresh food delivery segment in China – and internet giant-backed Hema and Super Species leverage their online- offline integrated experience and logistics capability to educate users and drive online fresh food growth (aka New Retail). For other sub-categories, we also see further upside from a higher online penetration into consumer health (22.2% in 2018 to 30.0% in 2022E), home care (15.2% in 2018 to 19.2% in 2022E) and pet care (36.9% in 2018 to 45.2% in 2022E), according to Euromonitor. In theory, if China can triple the FMCG segment's online penetration from 9% in 2018 to 27% over the next few years, we believe the online e-commerce market size will grow from RMB4,315bn in 2018 to RMB8,603bn in 2022E.

Figure 3: Total retail market split by key categories Figure 4: Online retail market split by key categories

RMB bn RMB bn 30,000 8,000

25,000

6,000 3,896 20,000 3,397 13,410 12,722 2,880 11,991 15,000 11,231 4,000 2,376 10,411 1,835 10,000 1,111 5,004 1,002 4,261 4,624 2,000 3,607 3,919 5,000 2,428 2,586 2,032 2,144 2,282 1,908 2,088 1,370 1,547 1,728 2,490 2,648 2,809 2,972 3,136 0 0 2018 2019E 2020E 2021E 2022E 2018 2019E 2020E 2021E 2022E Apparel FMCG - food and drink FMCG - others Others Apparel FMCG - food and drink FMCG - others Others

Source : Euromonitor Source : Euromonitor

For a comparative measure, the 3C and apparel segments represent 24% of total retail consumption in China (online penetration of 37%), and FMCG is only 9% penetrated digitally in China, so in theory, there is a larger RMB1,120bn market opportunity for e-commerce players to capture.

The investment to secure the large TAM (total addressable market) is already under- way. China's National Bureau of Statistics (NBS) indicates that the food category and non-food FMCG category have been growing 34% and 26% yoy respectively, outpacing the growth of 7% yoy for apparel in 2018.

Page 6 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 5: NBS-reported online FMCG retail sales growth is faster than that of other categories in 2018

FMCG - food and FMCG - others Apparel drink

Source : NBS

According to Euromonitor and our own calculation, the 3C segment is already 37% digitally penetrated with JD capturing 47% market share overall while the apparel segment has 55% penetration with Alibaba holding 45% market share.

Figure 6: Online penetration and market share by key vertical Apparel 3C FMCG FMCG - Food and drink Online retail sales, RMBbn 1,370 749 362 279 Online penetration, % 55.0% 36.8% 9.0% 7.7% Market share, % BABA 45% 25% 42% 22% JD 6% 47% 12% 10% PDD 6% 2% 31% 20% VIPS 3% 1% 6% 1%

Source : Euromonitor, company data, Deutsche Bank estimates Note: Market share based on our estimation of fulfilled GMV ratio of company reported GMV.

Dominance and profitability in the FMCG segment is yet unclear One of the critical challenges to growing into the FMCG segment is that the tradi- tional core expertise that helped the e-commerce platform grow is less of a strength in succeeding in the FMCG segment. For example, competitive pricing may be a relatively high decision-making criterion for a consumer when deciding where/how to purchase a computer, but quality of goods or convenience/immediacy may be greater decision-making factors when a consumer decides where to shop for groceries. The end result is that e-commerce platforms are investing heavily into people, operations and infrastructure (e.g. cold chain logistics) to bolster their market position across brand positioning, product selection, delivery time and convenience to consumers. We believe existing offline retailers are also taking the threat from e-commerce players more seriously and now treat digital transformation as a critical part of their sustainability strategy.

Deutsche Bank AG/Hong Kong Page 7 27 May 2019 Software & Services China E-commerce

Figure 7: No single offline FMCG retailer has more than 10% market share 10.0%

8.0%

6.0% 5.4%

4.0% 3.0% 2.6% 2.0% 1.9% 2.0% 1.4%

0.0%

Source : Kantar

As a result, we believe investments and competition will cause overall profit margins for e-commerce players to fall. In fact, New Retail dragged Alibaba's non- GAAP EBITA margin down by ~7% to 28% in FY19 and we expect similar level of drag in FY20. While the TAM opportunity is large, we do not see a clear path for earnings recovery across the entire space in a systematic fashion as relating to New Retail initiatives.

Geographic expansion

Meanwhile, Chinese consumers' needs are quite diverse with meaningful difference in consumption patterns across income brackets and cultural backgrounds. Given the diverse nature of consumers in China, online platforms have remain focused on growing users, particularly in lower tier cities where penetration has room to scale further.

As shown below, the income disparity between Tier 3-5 cities and Tier 1 cities is more than 10 years' difference, showing how much room there is for consumption upgrade as the Chinese middle class grows. Tier 3-5 is also supposed to represent 50% of total Chinese income by 2022E at an estimated RMB20.3tn in disposable income.

Page 8 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 8: Disposable income of tier 3-5 cities will account Figure 9: Different Chinese cities’ positions on annual for 50% of total Chinese income in 2022E expenditure per capita S-curve

RMB 45,000

Beijing 40,000 Shanghai 35,000 Guangzhou Shenzhen 30,000 New Tier 1 25,000 Tier 2

20,000 Tier 3-5 15,000

10,000

5,000

Source : CEIC, Wind, NBS, Deutsche Bank estimates Source : CEIC, Wind, NBS, Deutsche Bank estimates

As a point of reference, China has 65% of its total population in Tier 3 and below cities, based on NBS data. Comparatively, our data analysis shows that China e-commerce players have ~50% of users from lower tier cities with PDD the most skewed towards Tier 3 and below city consumers, while JD has the highest portion of Tier 1-2 city consumers. The seasonal pick-up in lower tier city consumers during the Chinese New Year (typically in January and February) spending season, also indicates that lower tier city consumers are digitally connected and willing to spend online, but are yet to make it a recurring and frequent experience.

Figure 10: MAU mix across platforms vs. China total popu- Figure 11: Users from tier 3 cities and below as % of total lation mix by different tier cities users by MAU

70%

60%

50% VIPS Taobao

40%

China total Taobao PDD VIPS population 30% Tier 1-2 cities Tier 3 cities and below Jan 18 Apr 18 Jul 18 Oct 18 Jan 19 Apr 19

Source : NBS, Jiguang, Deutsche Bank Source : Jiguang, Deutsche Bank

Given the room for user expansion, e-commerce players have been marketing and investing aggressively to secure more users. Over the past 12 months, Alibaba and PDD have been more successful in growing users than JD and VIPS.

Deutsche Bank AG/Hong Kong Page 9 27 May 2019 Software & Services China E-commerce

Figure 12: Number of paying customers by key platform BABA JD PDD VIPS # of active customers, mn 2016 443 227 na 52 2017 515 293 245 58 2018 636 305 419 61 2019E 725 318 523 63 China total population, mn 1,395 as of 2018

Source : Company data, NBS, Deutsche Bank estimates

Also, while e-commerce players have been scaling up users in lower-tier cities, PDD appears to be shifting its focus to gaining more higher-tier city consumers as well, as evidenced by the sharp pick-up in total users as well as higher-tier city users recently. Although PDD's mix between higher- and lower-tier cities does not appears to be shifting significantly, we do note that PDD appears to be gaining trac- tion with higher-tier city consumers as well. Based on comments made by the man- agements of leading e-commerce players coming into 2019, we expect the fight for new users will continue to be a major driver of revenue and profit outlook for the coming quarters.

Figure 13: Indexed MAU in tier 1-2 cities (assuming Tao- Figure 14: Indexed MAU in tier 3 cities and below (assum- bao MAU in Jan18 as 100) ing Taobao MAU in Jan18 as 100)

140 120

120 Taobao 100 Taobao 100

VIPS VIPS 0 0 Jan 18 Apr 18 Jul 18 Oct 18 Jan 19 Apr 19 Jan 18 Apr 18 Jul 18 Oct 18 Jan 19 Apr 19

Source : Jiguang, Deutsche Bank Source : Jiguang, Deutsche Bank

Page 10 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 15: Indexed tier 1-2 cities new added users by Tao- Figure 16: Tier 3 cities and below new added users by Tao- bao and PDD (assuming Taobao May18 as 100) bao and PDD (assuming Taobao May18 as 100)

250 200

200 150

150 100 100

0 0 May 18 Jul 18 Sep 18 Nov 18 Jan 19 Mar 19 May 19 May 18 Jul 18 Sep 18 Nov 18 Jan 19 Mar 19 May 19 Taobao Taobao

Source : Jiguang, Deutsche Bank Source : Jiguang, Deutsche Bank

Figure 17: New users added in tier 3 cities and below as % of total new users

70%

60%

50%

40% May 18 Jul 18 Sep 18 Nov 18 Jan 19 Mar 19 May 19 Taobao

Source : Jiguang, Deutsche Bank

Demographic balance is slightly better than geographic balance Demographic segmentation across age and gender is more balanced than geographic mix. China has a relatively equal gender mix (male:female: 51%:49%), but most e-commerce players have more female users than male users. We believe this phenomenon is somewhat expected given the cultural backdrop. JD is an exception with 54% male, given its product focus on electronics categories. VIPS has 65% female users as it has more apparel-related products on its platform. Taobao and PDD's users have a relatively similar gender mix with 59% female users for Taobao and 56% female users for PDD. Regarding user age distribution, Taobao/PDD have more young users under 25 (~40% of total users), compared to JD/VIPS which have ~35% of users under 25 years-old. On a relative basis, we do not see e-commerce players focusing as much on demographic user shift in their new user acquisition strategies, relative to geographic shift. In general, we believe Taobao and PDD's cohorts are slightly better positioned than peers' in terms of ability to scale and con- sume more over time, as they tend to have a younger age distribution vs. peers.

Deutsche Bank AG/Hong Kong Page 11 27 May 2019 Software & Services China E-commerce

Figure 18: Gender mix by MAU across platform Figure 19: Age distribution by MAU across platform

China total Taobao PDD VIPS China total Taobao VIPS population population Under 25 26-35 36-45 Above 46 Male Female

Source : NBS, Jiguang, Deutsche Bank Source : NBS, Jiguang, Deutsche Bank

The difference in user profile results in a meaningful discrepancy between platforms, as indicated by frequency of purchase and average ticket size of purchases, as shown below.

Page 12 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 20: Summary of key operation metrics BABA JD PDD VIPS # of active customers, mn 2016 443 227 na 52 2017 515 293 245 58 2018 636 305 419 61 2019E 725 318 523 63 Net add in active customers, mn 2016 36 72 na 16 2017 72 66 na 6 2018 121 13 174 3 2019E 89 12 105 3 Orders per customer, mn 2016 53.4 7.8 na 5.2 2017 50.5 8.0 17.6 5.8 2018 42.2 9.7 26.5 7.2 2019E na 11.1 na 8.5 Annual ARPU per customer, RMB 2016 4,472 2,092 na 1,318 2017 4,880 2,376 577 1,516 2018 4,816 2,918 1,127 1,677 2019E 5,075 3,444 1,730 2,214 Average order size, RMB 2016 84 267 na 255 2017 97 296 33 262 2018 114 300 42 232 2019E na 310 na 261 # of merchants 2016 9,500,000 107,500 na na 2017 10,000,000 145,000 152,000 na 2018 10,500,000 187,500 2,075,000 1,000

Source : Company data, Deutsche Bank estimates Note: 1) all data based on calendar year. 2) ARPU and average order size based on fulfilled GMV , which we estimate is 55% of total GMV reported by Alibaba and 50%-54% for JD, 60% for PDD and 77%-81% for VIPS.

Deutsche Bank AG/Hong Kong Page 13 27 May 2019 Software & Services China E-commerce Focal points for key e- commerce stocks in 2019

Profit margin trend to stabilize in 2019E; signs of a rising margin a key criterion for stock rally

As discussed above in the industry section, the e-commerce industry in China has seen aggressive investment against a backdrop of robust TAM and growth prospects in terms of both category and user geographic expansion. The end result has been a decline in profit margin over the past few years. While multi-year growth prospects are rich, we believe the time value of money is an important criterion to consider in relation to investing in the Chinese e-commerce sector. Identifying turn- arounds in investment or a turn in profit trends will be key to generating alpha in Chinese e-commerce.

To that extent, we believe 2019 represents a year in which we see profit margin potentially stabilize from heavy investment in 2018. None of the e-commerce players appear to be disavowing the long-term growth prospects, but they have started to moderate spending as weaker macroeconomic conditions and reduced return on investment are tempering the outlook. In general, we believe stocks have recovered from troughs earlier in the year, as there have been signs of improving margins coming into CY19. If companies can sustain the margin recovery outlook into CY20, we believe there may be further room for upside. However, if the companies engage in aggressive growth campaigns again, we feel stocks may not perform as richly.

Figure 21: BABA non-GAAP EBITA margin Figure 22: JD non-GAAP net margin

45% 1.6% 1.4%

1.2% 28.4% 30% 26.9%

0.8%

15% 0.4%

0.0% FY18 FY19 FY20E 2017 2018 2019E

Source : Company data, Deutsche Bank estimates Source : Company data, Deutsche Bank estimates

Page 14 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 23: PDD non-GAAP net margin Figure 24: VIPS non-GAAP net margin

2017 2018 2019E 4.5% 0.0% 4.0%

3.0% -10.0%

1.5% -20.0% - -

-26.3% 0.0% -30.0% 2017 2018 2019E

Source : Company data, Deutsche Bank estimates Source : Company data, Deutsche Bank estimates

For Alibaba, we anticipate non-GAAP EBITA margin to further drop year-on-year, as the mix shifts increasingly towards low-margin New Retail business from high-margin online marketplace. We expect underlying core e-commerce marketplace business to grow stably with estimated non-GAAP EBITA growth of 26% yoy and stable margins in FY3/20. To a large extent, we believe Alibaba's margin decline is stabilizing, relative to the sharp drop between FY18 and FY19. We hope for and anticipate a recovery in FY21.

JD has been investing heavily into its logistics and new initiatives in 2018, resulting in a sharp drop in net margins. The company has been recalibrating its focus back to its core capabilities and streamlining business lines, which has resulted in a better-than-expected margin recovery in 1Q19 and there is room for further margin uplift if it can continue to scale back and focus on profitability.

For PDD, the key remains in stabilizing and improving its cohort. Currently, it is growing its GMV and users by 92% and 25% yoy in 2019, growing fastest among e-commerce players. What remains to be seen is whether the company can help merchants generate positive ROI and sustain consumer repeat purchases beyond sporadic cherry-picking behavior. We discuss merchant economics as a key factor to monitor for PDD further below. But the key to its financial forecasts lies in it reduc- ing its marketing to sales ratio, which stands at 108% of sales as of 1Q19. With marketing cost still exceeding revenues, we would need to see whether it can start to generate improving sales from its existing cohort and progressively drive down marketing cost as a % of sales.

For VIPS, the company is retrenching and focusing back on an inventory-clearing discounted model from a prior effort to move into in-season goods. The repositioning back to an inventory-clearing business model provides more clarity on its value proposition and thus, profit margin. The end result is that they may continue to see growth in order volume, while average ticket size may not grow significantly. The rising cost of fulfillment would thus weigh on margins over time. The company plans to focus on optimizing its cost structure to improve fulfillment cost (9% of sales). If successful, we may see improving net margin over the coming years.

Below, we highlight the two key variables that we believe investors should focus on as we think through the profit margin profile and sustainability of recovery.

Deutsche Bank AG/Hong Kong Page 15 27 May 2019 Software & Services China E-commerce

Driver of profit margin #1: User acquisition cost

One critical variable in e-commerce platforms' profit outlook relates to marketing and user acquisition cost. We believe 2018 saw a rapid rise in marketing cost, as platforms competed to gain new users, particularly in lower-tier cities. Not every business saw a similar efficacy in user acquisition. For a simplistic comparison, we have looked at marketing cost against net addition in new paying users as a metric for comparison. It shows that JD had one of the worst conversions in 2018, despite an increase in marketing cost.

Figure 25: User acquisition cost comparison BABA JD PDD VIPS Net add in active customers, mn 2016 36 72 na 16 2017 72 66 na 6 2018 121 13 174 3 2019E 89 12 105 3 S&M cost, RMBmn 2016 14,843 10,159 169 2,838 2017 23,990 14,918 1,345 2,979 2018 37,772 19,237 13,442 3,240 2019E 49,054 22,476 24,783 3,427 Paying customer acquisition cost (CAC), RMB 2016 412 142 na 183 2017 333 226 na 523 2018 312 1,503 77 1,200 2019E 551 1,840 236 1,358

Source : Company data, Deutsche Bank estimates

As a result, we believe JD has the most to benefit from rationalizing its marketing spend. We see PDD still gaining users at a reasonable acquisition cost and believe it can continue to gain users at an accelerated pace. As a result, we do not expect PDD to curb user acquisition-related marketing spend in the near future.

Driver of profit margin #2: Compare unit economics among merchants

While PDD has a stronger user acquisition cost, it also has among the lowest user purchasing behavior as well. The key focal point for PDD is merchant economics.

To illustrate, we simulated merchant ROI based on market benchmark data. Based on a sample of 552 consumer-related companies, we estimate that COGS ratio for an average brand or merchant is 60% of its revenue. We then looked at average fulfillment cost, taking into consideration: a) data from listed logistics companies and their pricing table for average parcels, b) discussions with companies on the average cost of parcel delivery, c) our own estimate based on analysis of financial data provided by companies, and d) our estimation of fulfilled and unfulfilled orders (since companies often provide GMV data inclusive of unfulfilled GMV).

Page 16 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 26: Merchant ROI 4Q18 Alibaba JD - 3P VIPS - 3P PDD Per unit: Average fulfilled order size, RMB 141 212 100 38 COGS 85 127 60 23 % of sales 60% 60% 60% 60% Fulfillment cost 12 23 13 8 % of sales 8.5% 10.7% 12.6% 21.1% Advertising cost and commissions 9 15 10 2 % of sales 6.6% 7.0% 10.0% 4.7% Other opex (G&A, R&D) 20 30 14 5 % of sales 13.9% 13.9% 13.9% 13.9% Operating profit, RMB 15 18 3 0 OP margin % 11.0% 8.4% 3.5% 0.3%

Source : Company data, Deutsche Bank estimates, Bloomberg Finance LP

One of our key findings is that even at a lower absolute dollar cost for fulfillment, of RMB8 for PDD (due to smaller/lighter parcel delivery), the % of fulfillment cost to an average merchant is higher, at 21% of sales. This compares to 8.5%~12.6% for peers.

The advertising and marketing cost is the platforms' reported advertising-related revenue in relation to its 3P operations, divided by an estimated amount of fulfilled parcels. The other operating expense ratio was calculated based on the average data of 522 sampled brand and intermediary consumer-related companies. The end conclusion is that PDD's merchants may be generating fewer returns than other platforms. This is because the average order size is smaller. The implication is that, if merchants cannot scale the size of their GMV or gross margin, then the amount of money they can deploy into PDD for advertising is also restricted. While we are positive on PDD to the extent that it can continue to scale and improve on its KPIs, we believe a lack of improvement to its KPIs will be a major risk factor in the outlook.

Deutsche Bank AG/Hong Kong Page 17 27 May 2019 Software & Services China E-commerce Valuations

Valuation framework

We value Chinese e-commerce businesses on a mixture of SOTP, EV/EBITDA, and EV/FCF-based approach. Ideally, we'd prefer to value assets on their cash-based earnings outlook, but leading e-commerce businesses in China are in various sta- ges of evolution, which requires a varied approach to valuation. While methods for each individual stock may differ, we ultimately ground our valuation on a cash earnings-based approach; even our SOTP valuations include valuation of core operations on an EV/EBITDA basis.

The below table summarizes our valuation multiple for each of the stocks under our coverage.

Figure 27: Summary of valuation multiples

Stock Valuation methodology Rationale Core EV/EBITDA Multiple Multiple rationale Consolidated EBITDA growth

SOTP to capture value in Ant Financial. Core business includes yet-to-scale cloud BABA SOTP 24x 28% Underlying core operations based on EV/EBITDA operations & high end of historic valuation

SOTP to capture value in profitable core Referencing mid-point of peers such as JD SOTP 20X 100% operations and value in JD Logistics Alibaba, Amazon

Valuing at the low-end of historic range as VIPS EV/EBITDA - 8X growth is slowing and turnaround has yet to 13% come

Currently EBITDA negative, but positive FCF as a Referencing mid-point of marketplace models PDD EV/FCF 30X (EV/FCF) Expect EBITDA loss untill 2020E marketplace model such as Alibaba, Amazon, Mercado Libre

Source : Deutsche Bank estimates

Valuation details

As an effort to standardize our valuation approach for e-commerce companies, we change Alibaba's SOTP to reflect EV/EBITDA for the core operations from a P/E approach. The change in valuation and synchronization results in our target price rising from US$197 to US$220, implying 41% upside potential. For JD, we use an SOTP-based valuation including: 1) 20x 2019E EBITDA of JD core retail operations; 2) JD Logistics (3rd party logistics) on 1.3x 2019 EV/Sales referencing logistics peers' multiples, 3) book value of JD property management at 1Q19, and 4) net cash position. Our JD target price of US$29 reflects 10% upside potential. We value VIPS on EV/EBITDA at 8x 2019E multiple, which implies 24% upside potential. For PDD, we adopt EV/FCF at 30x 2019E multiple, to arrive at a target price of US$26 (28% upside potential).

We also calculate forward years' fair value using implied valuation multiples to look at long-term outlook, which concludes that PDD has the highest implied 2-year growth at 85%, vs. BABA's 29%, JD's 24%, VIPS' 28%. The below table sets out our target prices, upside/downside and 2-year growth of forward fair value at implied valuation multiples.

Page 18 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 28: Summary of target prices and upside/downside US$ Target price Current price Upside/downside BABA 220.0 156.0 41% JD 29.4 26.7 10% PDD 26.2 20.5 28% VIPS 9.3 7.5 24%

Source : Deutsche Bank estimates

Figure 29: Fair value on forward years using implied valuation multiples US$ Fwd 1 year Fwd 2 years Fwd 3 years 2-year growth BABA 220.0 287.2 364.9 29% JD 29.4 36.2 45.2 24% PDD 26.2 58.9 89.6 85% VIPS 9.3 12.1 15.2 28%

Source : Deutsche Bank estimates

Valuation comparisons

Wide variance in valuations based on growth prospects We have analyzed and back-tested various valuation methods against historical stock performance. We believe Chinese e-commerce stocks exhibit the highest level of correlation with sales and earnings (in this case, EBITDA) growth. In fact, our observation is that globally, e-commerce companies lack consistency in valuation, and the range is quite wide depending on respective market positioning and growth outlook. Note that stocks such as JD and VIPS have been derating with the slowdown of top-line growth. In contrast, Alibaba's valuation has held up and trades at a noticeable premium to its peers, given its superior market position and outlook.

That being said, we believe Chinese e-commerce stocks are trading at a relatively attractive level versus global e-commerce peers.

Figure 30: EV/EBITDA multiples to 2-year EBITDA CAGR scatterplot

60.0x SFIX

50.0x

40.0x ETSY

ZAL 30.0x Kakaku ASOS

DA AMZN

T I

B 20.0x E / Rakuten MonotaRO V BABA E ASKUL Zozo 10.0x VIPS SRP EBAY GRPN 0.0x 10% 20% 30% 40% 50% 60% -10.0x PDD -20.0x -20.7x, 107% -21 EBITDA CAGR, %

Source : Deutsche Bank estimates, Bloomberg Finance LP Note: DBe for coverage companies, and Bloomberg consensus for non-coverage.

Deutsche Bank AG/Hong Kong Page 19 Page Page E-commerce China Services & Software 2019 May 27 Figure 31: Global e-commerce comp sheet 20 Current Target Ticker Rating Upside Mkt cap P/E (x) PEG 2-year (x) EV/EBITDA (x) EV/Sales (x) EV/FCF EPS growth (%) ROE (%) price price (%) (USD mn) 2019E 2020E 2019E 2020E 2019E 2020E 2019E 2020E 2019E 2020E 2019E 2020E 2019E 2020E E-commerce Alibaba BABA.N Buy 156.0 220.0 41% 438,427 22.7x 16.5x 0.7x 0.7x 16.6x 11.6x 5.3x 4.1x 29.1x 21.4x 32% 37% 16% 20% JD.com JD.OQ Hold 26.7 29.4 10% 42,616 35.7x 25.0x 1.0x 0.9x 21.9x 14.9x 0.4x 0.4x 45.3x 13.6x 95% 43% 10% 5% Pinduoduo PDD.O Buy 20.5 26.2 28% 26,386 NM 40.7x N/A 0.3x NM 35.4x 4.8x 2.5x 21.5x 7.2x N/A N/A -37% 4% Vipshop VIPS.N Buy 7.5 9.3 24% 5,470 11.2x 8.3x 0.4x 0.5x 6.1x 4.3x 0.3x 0.3x 18.2x 10.0x 20% 36% 13% 15% Amazon AMZN.OQ Buy 1,860 2,315 24% 915,580 58.5x 44.6x N/A N/A 20.1x 15.3x 3.3x 2.7x 32.1x 20.3x 34% 31% 25% 26% eBay EBAY.OQ Buy 36.3 NA NA 31,645 13.5x 11.7x 0.9x 1.4x 7.1x 6.3x 2.4x 2.2x 12.5x 9.6x 426% 15% 56% 27% ETSY ETSY. OQ NR 64.0 NA NA 7,693 64.5x 48.1x 1.8x 1.6x 37.2x 27.3x 9.1x 7.2x 37.0x 28.1x 54% 34% 26% 31% Farfetch FTCH.N Buy 22 31 40% 6,657 NM NM N/A N/A NM NM 7.4x 5.6x NM NM 52% 48% -27% -16% Groupon GRPN.OQ NR 3.5 NA NA 2,011 16.8x 14.8x 1.7x 1.6x 4.2x 3.2x 0.5x 0.4x 7.1x 4.5x 138% 14% 31% 26% MercadoLibre MELI.OQ Buy 569 600 5% 28,086 332.6x 132.7x 3.2x 2.0x 929.9x 170.5x 11.8x 8.6x 103.6x 85.9x 308% 151% 7% 8% Stitch Fix SFIX.OQ NR 24 NA NA 2,407 110.5x 87.6x 2.0x 0.8x 54.2x 39.6x 1.4x 1.1x 36.2x 27.4x -63% 26% 6% 8% ASKUL 2678.T Hold 2,878 3,100 8% 1,443 26.7x 25.7x N/A N/A 8.0x 6.8x 0.3x 0.3x N/A N/A 83% 4% 11% 10% Mercari 4385.T Buy 2,877 3,800 32% 3,913 NM 76.9x N/A N/A NM 24.3x 5.9x 4.9x NM 26.0x -12% 141% -44% 21% MonatoRO 3064.T Hold 2,252 2,300 2% 5,121 49.9x 43.6x 3.0x 2.3x 27.4x 23.1x 4.2x 3.5x 90.9x 330.9x 18% 15% 34% 31% Kakaku.com 2371.T Hold 2,284 2,700 18% 4,345 24.5x 21.4x N/A N/A 15.2x 13.7x 7.4x 6.4x N/A N/A 11% 14% 43% 43% Rakuten 4755.T Hold 1,089 900 -17% 14,173 13.5x 248.6x -0.3x N/A 9.9x 9.9x 1.4x 1.2x N/A N/A -24% -95% 13% 1% Zozo Inc 3092.T Buy 1,826 2,700 48% 5,163 23.1x 20.5x 1.9x N/A 14.1x 10.7x 4.0x 3.5x N/A N/A 51% 13% 77% 56% ShowRoomPrive SRP.FR NR 2 NA NA 136 89.4x 27.1x 0.4x N/A 7.0x 5.1x 0.1x 0.1x NM 35.9x 112% 430% 1% 2% Zalando ZAL.DE NR 38 NA NA 10,508 105.4x 75.7x 3.2x 2.8x 29.1x 22.8x 1.3x 1.1x NM NM 70% 39% 6% 8% ASOS PLC ASOS.L NR 35 NA NA 3,745 69.8x 44.8x 1.4x 1.1x 22.4x 16.2x 1.1x 0.9x NM 62.7x -51% 56% 10% 13% boohoo Group PLC BOOH.L NR 2.4 NA NA 3,525 47.9x 38.0x 2.1x 2.7x 23.4x 18.3x 2.3x 1.8x 51.9x 47.6x 34% 26% 20% 20% Average 62.0x 52.6x 1.6x 1.4x 69.7x 24.0x 3.6x 2.8x 40.4x 48.7x 69% 54% 14% 17% Median 41.8x 39.4x 1.7x 1.4x 18.3x 15.1x 2.4x 2.2x 34.2x 26.0x 42% 33% 13% 15%

Source : Company data, Deutsche Bank estimates, Bloomberg Finance LP for non-covered companies Note: data updated as of May 23, 2019 Deutsche Bank AG/Hong Kong AG/Hong Bank Deutsche Deutsche Bank AG/Hong Kong AG/Hong Bank Deutsche E-commerce China Services & Software 2019 May 27 We also looked at time series data using several different valuation methods, such as EV/sales, EV/EBITDA against earnings growth, and EV/FCF. We observe little consistency in the marketplaces in terms of valuation range and no single valuation that works for all the companies – even those within a similar marketplace – versus principal model businesses. What we have found is that companies with better market positioning and (perceived) growth tend to trade at higher valuations than the others.

Figure 32:Historical EV/sales against sales growth - China peers

Source :Deutsche Bank estimates, Bloomberg Finance LP

Figure 33: Historical EV/EBITDA against EBITDA growth - China peers

Source : Deutsche Bank estimates, Bloomberg Finance LP Note: JD EBITDA growth line only captures value between -100% to 100% in JD chart. PDD EV/EBITDA chart is not meaningful since PDD EBITDA is negative.

Figure 34: Historical EV/FCF - China peers Page Page

Source : Deutsche Bank estimates, Bloomberg Finance LP 21 Note: Average/+1 SD/-1 SD lines only capture EV/FCF multiples at 0x-80x for JD/VIPS. Page Page E-commerce China Services & Software 2019 May 27 Figure 35: Historical EV/EBITDA - global peers 22 20x Rakuten Mercari 40x Amazon 40x MELI 100x

15x 80x 30x 30x 14x 72x 28x 24x 11x 60x 59x 24x 10x 20x 20x 20x 20x 9x 47x 40x 17x 5x 10x 10x 20x

0x 0x 0x 0x Aug 09 Sep 10 Oct 11 Oct 12 Nov 13 Dec 14 Jan 16 Feb 17 Feb 18 Mar 19 Jul 18 Aug 18 Sep 18 Oct 18 Oct 18 Nov 18 Dec 18 Jan 19 Oct 08 Apr 10 Oct 11 Apr 13 Oct 14 Apr 16 Oct 17 Apr 19 Jun 09 May 10 Apr 11 Mar 12 Feb 13 Jan 14 Dec 14 Nov 15 Oct 16 Sep 17 EV/EBITDA (12mo fwd consen) +1 SD EV/EBITDA (12mo fwd consen) +1 SD EV/EBITDA (12mo fwd consen) +1 SD EV/EBITDA (12mo fwd consen) +1 SD Average -1 SD

Source : Deutsche Bank estimates, Bloomberg Finance LP

Figure 36: Historical EV/FCF - global peers

Source : Deutsche Bank estimates, Bloomberg Finance LP Deutsche Bank AG/Hong Kong AG/Hong Bank Deutsche 27 May 2019 Software & Services China E-commerce

Rating Company Han Joon Kim

Buy Alibaba Research Analyst +852 - - 2203 6157 Asia China Price at 23 May 2019 (USD) 156.00 Price target - 12mth (USD) 220.00 Technology Reuters Bloomberg BABA.N BABA US 210.86 - Software & Services 52-week range (USD) 130.60 NASDAQ 100 7,308 Alibaba - the catch-all retail platform in Price/price relative

China 250

200

Reiterate Buy on strong market positioning 150

We reiterate our Buy rating on Alibaba with a revised target price of US$197 from 100 US$220, as we synchronize valuations across our China e-commerce sector cover- Jul '17 Jan '18 Jul '18 Jan '19

age. We favor Alibaba and believe that it has and will maintain a leadership position Alibaba NASDAQ 100 (Rebased) in China’s online and offline retail and technology sphere, with a moat against com- Performance (%) 1m 3m 12m petitors formed of its innovation in technology and New Retail. Absolute -16.7-11.8-20.7 The next 12 months will revolve around the near-term earnings outlook, largely NASDAQ 100 -6.4 3.1 5.1 related to the aggression level of Alibaba’s investment into New Retail and how it Source: Deutsche Bank

plans to grow its share of lower-tier-city users. In particular, we believe Alibaba finds Key indicators (FY1) it beneficial to accelerate the upgrade behavior of lower-tier-city consumers suffi- ROE (%) 16.5 ciently, and that it is willing to forego its own monetization of merchants to help Net debt/equity (%) -25.8 them reach a broader audience with superior goods quality Book value/share (CNY) 237.05

That said, the company has a strong moat around its product and services, not only Price/book (x) 4.4 in Taobao and Tmall, but also in payments via Alipay, and other verticals such as Net interest cover (x) – Youku or Ele.me, which together provide a strong ecosystem of support and fuel for Operating profit margin (%) 18.7 each other, resulting in relatively low user acquisition cost versus peers. Within key Source: Deutsche Bank e-commerce services, product solutions are segmented into various consumption Comparatives behaviors, including a discount format, daily promotions, group buying, and video Alibaba (BABA.N),USD156.00 Buy shopping that caters to a variety of user experiences. The platform encompasses 2019A 2020E 2021E various price points within the same product category, catering to different tiers of consumer spending ability. P/E (x) 32.8 23.4 17.0 EV/EBITDA (x) 34.0 18.4 11.8 We expect the consolidated profit margin decline to continue in FY20 (or CY19), but Price/book (x) 6.3 4.4 3.5 anticipate a mild recovery in FY21 when the harvesting of new growth potentially Source: Deutsche Bank begins to outpace investments. We believe the stock price will rally significantly with any margin rebound.

Valuation We adjust our SOTP valuation to change the valuation of the underlying core operations of Alibaba from 33x forward P/E to 24x EV/EBITDA, largely to ensure a consistent valuation framework across our China e-commerce universe. The 24x is based on the +1 standard deviation for Alibaba’s trading history, but within levels seen for global comparables such as Amazon. We also believe Alibaba will likely see an upswing in profitability beyond the current heavy investment cycle into New Retail and see room for expanding multiples as ROE improves beyond the 12-month horizon. We see competition and faster-/longer-than-expected investment as key risks to Alibaba's share price.

Deutsche Bank AG/Hong Kong Page 23 27 May 2019 Software & Services China E-commerce

Below is our updated SOTP valuation.

Figure 37: Alibaba SOTP valuation

US$ mn, unless noted otherwise Valuation basis Multiple Valuation, US$ m Shareholding % Valuation Alibaba operating business CY2019 EV/EBITDA 24x 512,923 100% 512,923 Ant Financial Last private round 160,000 33% 52,800 Net cash Last fiscal quarter 11,817 100% 11,817 Valuation (US$ mn) 577,539 # of FD shares (m) 2,625 Value per share (US$) $220

Source : Deutsche Bank estimates

Forecasts and ratios Year End Mar 31 2018A 2019A 2020E 2021E 2022E Sales (CNYm) 250,266.0 376,844.0 499,858.9 643,698.5 785,222.2 EBITDA (CNYm) 85,223.0 82,773.0 124,805.6 182,977.7 234,051.2 Reported NPAT (CNYm) 63,599.0 87,886.0 91,796.3 142,191.2 187,272.2 Pro-forma NPAT (CNYm) – – – – – Pro-forma EPS (CNY) – – – – – Reported EPS FD(CNY) 24.37 33.50 34.11 52.63 69.06 DB EPS FD(CNY) 31.88 34.96 46.19 63.32 79.35 DB EPS growth (%) 41.8 9.7 32.1 37.1 25.3 PER (x) 33.9 32.8 23.4 17.0 13.6 EV/EBITDA (x) 30.4 34.0 18.4 11.8 8.4 DPS (net) (CNY) 0.00 0.00 0.00 0.00 0.00 Yield (net) (%) 0.0 0.0 0.0 0.0 0.0 Source: Deutsche Bank estimates, company data

Page 24 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Rating Company Han Joon Kim

Hold JD.com Research Analyst +852 - - 2203 6157 Asia China Price at 23 May 2019 (USD) 26.70 Price target - 12mth (USD) 29.40 Technology Reuters Bloomberg Software & Services JD.OQ JD US 52-week range (USD) 43.76 - 19.27 NASDAQ 100 7,308

Price/price relative JD - strong retailer with margin potential; 75

Hold 50

25 We're not yet convinced that margin recovery will persist into 2020; initiat- 0 ing with a Hold rating Jul '17 Jan '18 Jul '18 Jan '19

We initiate coverage with a US$29.4 per share target price and a Hold rating. We JD.com NASDAQ 100 (Rebased) see JD as a leading on & offline 'retailer' in China with strength in areas such as

logistics and asset value in its property asset value. That said, we believe the current Performance (%) 1m 3m 12m share price reflects JD's curbed spending in 2019 versus 2018 and margin recovery Absolute -10.3 2.9-27.3 profile to >1% non-GAAP net profit margin from 0.7% in 2018. While our analysis NASDAQ 100 -6.4 3.1 5.1 suggests there is meaningful room for margin improvement in the long-term as Source: Deutsche Bank growth matures, the company has periodically shifted back and forth in growth ver- Key indicators (FY1) sus profit strategy and a shift back to technology-driven growth initiatives could ROE (%) 10.0 drain margins again. Net debt/equity (%) -30.2 Profit margin expansion could be gradual and progressive Net Profit (CNYm) 6,809.2 We forecast JD Retail core non-GAAP OP margins to grow to 5% by 2026 from 2% Net Profit (CNYm) 6,809.2 in 2019 at a steady rate, somewhat consistent with the -1.1% to 1.2% trend DB EPS (CNY) 4.58 between 2015 and 2018. We do not foresee any immediate inflection in profit profile DB EPS (CNY) 4.58 for three key reasons: 1) we expect offline competitors, particularly in the 3C seg- Book value/share (CNY) 48.01 ment, to price aggressively to keep market share. We believe JD has scaled better Price/book (x) 3.8 than offline peers to date and remains more competitive, but we do not see JD Net interest cover (x) – enjoying as much price competitiveness as it did before. As long as key competitors Operating profit margin (%) 0.1 are willing to cede profit margin to maintain share, we believe JD may not be able Source: Deutsche Bank to eek out an accelerated pace of margin improvement. 2) We believe JD will continue to need to invest into technology and logistics to remain competitive, continuing Comparatives to see costs such as technology and marketing expense creep up over time, offset- JD.com (JD.OQ),USD26.70 Hold ting some benefits in operating leverage. Ultimately, the pace of margin expansion 2018A 2019E 2020E is up to management discretion, in our view. P/E (x) 97.5 40.3 28.2 EV/EBITDA (x) 98.7 28.6 17.5 Valuation and key risks Price/book (x) 3.3 3.8 3.5 We value JD on an SOTP basis. We value JD Retail on 20x 2019 EV/EBITDA referenc- Source: Deutsche Bank ing peer valuation, JD Logistics (3rd party logistics) on 1.3x 2019 EV/Sales referencing logistics peers' multiples, book value of JD property management at 1Q19 and JD's net cash position. Upside risks includes continuous improvement of core JD Retail margin, narrowing loss from JDL, and downside risks are a larger-than-expected loss from JDL, new initiatives, and fiercer competition.

Deutsche Bank AG/Hong Kong Page 25 27 May 2019 Software & Services China E-commerce

Forecasts and ratios Year End Dec 31 2017A 2018A 2019E 2020E 2021E Sales (CNYm) 362,331.8 462,019.8 548,186.3 626,555.0 686,807.6 EBITDA (CNYm) 3,357.2 2,940.9 7,682.5 11,923.3 16,102.6 Reported NPAT (CNYm) 123.7 -2,491.6 6,491.2 4,153.7 7,408.0 Pro-forma NPAT (CNYm) – – – – – Pro-forma EPS (CNY) – – – – – Reported EPS FD(CNY) 0.09 -1.69 4.36 2.74 4.79 DB EPS FD(CNY) 3.41 2.35 4.58 6.54 8.55 OLD DB EPS FD(CNY) 3.24 6.33 10.63 – – % Change 5.4% -62.8% -56.9% – – DB EPS growth (%) 133.6 -31.1 94.7 42.9 30.6 PER (x) 74.0 97.5 40.3 28.2 21.6 EV/EBITDA (x) 98.4 98.7 28.6 17.5 12.1 DPS (net) (CNY) 0.00 0.00 0.00 0.00 0.00 Yield (net) (%) 0.0 0.0 0.0 0.0 0.0 Source: Deutsche Bank estimates, company data

Page 26 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce Outlook and financial forecasts

We believe JD is in the midst of repositioning its business to a focus on online and offline retailing in China. We see JD's roots as a company that grew as a specialty online retailer with a focus on 3C segment. The company since then has expanded to focus on becoming a general purposes online retailer over the past few years. However, after several years of extensive investment without meaningful turnaround in its non-retail initiatives, the company is shifting back towards a focus on its core strength.

As a result, we see room for blended margins to be optimized higher, even if top-line growth slows down. To the extent that core JD Retail margins are lower than peer comparables, we see room for improvement over the long haul. We believe JD would need to show meaningful progress in optimizing the losses in its non-core operations, which it has yet to prove. Our forecasts assume improvement, which leads us to believe consensus and our forecasts already factor in improving opera- tional efficiency that it has yet to deliver. Thus, we see execution risk and therefore initiate with Hold.

Figure 38: JD Retail and other revenues margin in 2015-2022E 2015 2016 2017 2018 2019E 2020E 2021E 2022E Non-GAAP OP, RMB mn JD consolidated -3,233 371 2,886 1,913 5,465 9,604 13,648 17,516 JD Retail 152 2,269 4,956 7,049 10,238 14,052 17,928 21,642 Others -3,385 -1,898 -2,070 -5,137 -4,773 -4,449 -4,279 -4,126 Non-GAAP EBITDA, RMB mn JD consolidated -2,065 2,396 5,301 5,645 11,026 15,974 20,516 24,789 JD Retail -2,036 2,365 5,225 5,493 10,656 15,320 19,532 23,465 Others -30 31 76 151 370 654 985 1,324 Non-GAAP OP margin, % JD consolidated -1.8% 0.1% 0.8% 0.4% 1.0% 1.5% 2.0% 2.4% JD Retail 0.1% 0.9% 1.4% 1.6% 1.9% 2.3% 2.7% 3.1% Others -141.8% -58.0% -40.5% -41.5% -25.9% -17.3% -13.0% -10.6% Non-GAAP EBITDA margin, % JD consolidated -0.3% 0.1% 0.8% 0.4% 2.7% 2.9% 3.1% 3.1% JD Retail -1.1% 0.9% 1.5% 1.2% 2.0% 2.5% 3.0% 3.4% Others -1.2% 1.0% 1.5% 1.2% 2.0% 2.5% 3.0% 3.4%

Source : Company data, Deutsche Bank estimates

We forecast JD Retail margins at a non-GAAP OP margin at 1.9% in 2019 expanding to 3.1% by 2022 and 3.7% by 2026. The pace of improvement is largely consistent with the historical rate of progress as the organization gains scale. As a retailer, we believe the company should be able to reach mid-single-digit OPM, similar to the levels enjoyed by Suning or Gome, offline retailers in China, and Best Buy in the US.

Deutsche Bank AG/Hong Kong Page 27 27 May 2019 Software & Services China E-commerce

Figure 39: OP margin trend for Suning, Gome and Best Buy in 2009-2018

Best Buy

Suning

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 -2% Gome

-4% Suning Gome Best Buy

Source : Company data

We would note that offline retailer margins in China have progressively been reduced as offline retailers focus on defending market share by offering discounted pricing. Our latest check on key products shows that JD no longer enjoys a meaningful price advantage over products across 3C and home appliances, a gap we had seen several years ago.

Figure 40: Key product pricing comparison across key products in 3C, RMB

Product JD Suning JD vs. Suning 2 5,699 5,399 5.6% S5082 569 599 -5.0% iPhone XS Max 256G 8,999 8,588 4.8% Air13 13.3 I5-8265U 8G 256GB 4,999 4,999 0.0% 9 6GB+128GB 2,999 2,999 0.0% BCD-525WKPZM(E) 525 2,999 2,898 3.5% Dolce Gusto Genio 990 990 0.0% Bose SoundSport - 1,199 1,388 -13.6% T5 power 2,699 2,399 12.5% MateBook 14 i5-8265U 8GB+512GB 5,699 5,699 0.0% Average 0.8%

Source : Company data compiled by Deutsche Bank

While we think JD is quite competitive in being able to generate low-single digit profit margin while some competitors are loss-making, we believe the race to the bottom in pricing could limit JD's ability to expand its own profit margin meaningfully. As a result, we believe our progressive margin expansion to mid-single-digit in the coming years amply reflects JD's potential success and market leadership outlook.

Page 28 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Below is the full set of our financial forecasts.

Figure 41: JD financial snapshot (RMBm, except for GMV in RMBbn) 2017 2018 2019E 2020E 2021E Total GMV 1,294 1,677 2,055 2,382 2,633 YoY % 37.8% 29.5% 22.5% 15.9% 10.5% Direct sales GMV 723 910 1,042 1,169 1,268 % of total GMV 55.9% 54.3% 50.7% 49.1% 48.1% YoY % 31.1% 25.9% 14.4% 12.2% 8.5% Marketplace GMV 571 767 1,013 1,213 1,365 % of total GMV 44.1% 45.7% 49.3% 50.9% 51.9% YoY % 47.4% 34.2% 32.2% 19.7% 12.6%

Total orders FULFILLED (m) 2,344 2,972 3,531 4,019 4,459 YoY % 32% 27% 19% 14% 11% Average FULFILLED order size (RMB) 296 300 310 315 314 YoY % 11% 1% 3% 2% 0%

Net revenue 362,332 462,020 548,186 626,555 686,808 YoY % 40.3% 27.5% 18.6% 14.3% 9.6%

Net product revenues (Online direct sales) Revenue 331,748 416,109 487,590 550,367 596,854 YoY % 39.5% 25.4% 17.2% 12.9% 8.4% % of total revenue 91.6% 90.1% 88.9% 87.8% 86.9% Return, cancellation and unfulfillment rate 46% 47% 47% 47% 47% VAT % 17% 16% 14% 13% 13%

Net service revenues (Services and others) Revenue 30,584 45,911 60,596 76,188 89,954 YoY % 50% 50% 32% 26% 18% % of total revenue 8.4% 9.9% 11.1% 12.2% 13.1%

Marketplace and advertising 25,391 33,532 42,182 50,536 56,986 YoY % 49% 32% 26% 20% 13% Online marketplace commission 14,508 12,137 10,133 12,129 13,652 YoY % 34% -16% -17% 20% 13% % of service and others 47.4% 26.4% 16.7% 15.9% 15.2% Commission rate, % 2.5% 1.6% 1.0% 1.0% 1.0%

Advertising 10,883 21,395 32,048 38,407 43,334 YoY % 75% 97% 50% 20% 13% % of service and others 35.6% 46.6% 52.9% 50.4% 48.2% Take rate, % 1.9% 2.8% 3.2% 3.2% 3.2%

Reference to 3P GMV growth, YoY 47.4% 34.2% 32.2% 19.7% 12.6% Commission+Ads revenue growth, YoY 48.7% 32.1% 25.8% 19.8% 12.8%

Logistics and other service 5,116 12,379 18,414 25,652 32,967 YoY % 56% 142% 49% 39% 29% Logistics 5,034 11,752 18,010 25,208 32,523 YoY % 53% 133% 53% 40% 29% % of service and others 16.5% 25.6% 29.7% 33.1% 36.2% % of total revenue 1.4% 2.5% 3.3% 4.0% 4.7%

Other service revenue (tech initiatives & overseas busin 82 628 404 445 445

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 29 27 May 2019 Software & Services China E-commerce

Figure 42: JD P&L

(RMBm) 2017 2018 2019E 2020E 2021E Net revenue 362,332 462,020 548,186 626,555 686,808 YoY% 40% 28% 19% 14% 10%

Cost of revenues 311,517 396,066 469,169 532,479 580,141 SBC w/i COGS 28 72 92 105 115

Gross Profit 50,815 65,954 79,018 94,076 106,666 Gross margin 14.0% 14.3% 14.4% 15.0% 15.5%

Operating expenses 51,650 68,573 78,623 90,223 99,237 Fulfillment expenses 25,865 32,010 34,351 38,511 42,012 Marketing expenses 14,918 19,237 22,476 26,315 29,533 Technology and content expenses 6,652 12,144 15,623 16,917 18,544 G&A 4,215 5,160 6,256 8,480 9,149 Impairment of goodwill and intangible assets 0 22 -83 0 0 Operating Income -835 -2,619 395 3,852 7,429 YoY% -33% 213% -115% 875% 93% OP margin % -0.2% -0.6% 0.1% 0.6% 1.1%

SBC w/i Opex 2,753 3,588 4,257 4,866 5,334 Fulfillment 426 419 497 568 623 Marketing 136 190 226 258 283 Technology and content 671 1,163 1,379 1,577 1,728 G&A 1,520 1,816 2,155 2,463 2,700 Amortization of Intangible assets 1,778 1,806 1,806 1,806 1,806 Reversal of rev. from cooperation arrangements with equity -837 -956 -922 -920 -920 Impairment of goodwill, intangible assets, and investments 0 22 -83 0 0 Operating Income, non-GAAP 2,886 1,913 5,544 9,708 13,763 YoY% 677% -34% 190% 75% 42% Non-GAAP OP margin, % 0.8% 0.4% 1.0% 1.5% 2.0%

Interest Income 1,781 2,118 1,075 1,284 1,536 Interest expense 282 855 623 623 623 Net interest Income 1,499 1,263 452 661 912 Investment loss -1,927 -1,113 -717 0 0 Others 1,384 95 6,886 0 0 Pre-Tax Profit 121 -2,374 7,015 4,513 8,341 YoY% -106% -2062% -396% -36% 85% Income Tax 140 427 842 677 1,251 (Tax rate) 115.4% -18.0% 12.0% 15.0% 15.0%

Income (loss) from continuing operations -19 -2,801 6,173 3,836 7,090 Loss from discontinued operations, net of tax 7 0 0 0 0

Net income (loss) -12 -2,801 6,173 3,836 7,090 Net loss from continuing operations attributable to NCI -135 -309 -318 -318 -318 Net income/(loss) from continuing operations attributa 117 -2,492 6,491 4,154 7,408 YoY% -106% -2233% -361% -36% 78% NP margin % 0.0% -0.5% 1.2% 0.7% 1.1%

Non-GAAP net income from continuing operations attribu 4,968 3,460 6,809 9,930 13,230 YoY% 140% -30% 97% 46% 33% non-GAAP NP margin 1.4% 0.7% 1.2% 1.6% 1.9%

Source : Company data, Deutsche Bank estimates

Page 30 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 43: JD balance sheet (RMB mn) 2017 2018 2019E 2020E 2021E Current Assets 115,029 104,856 115,871 133,316 150,267 Cash and cash equivalents 25,688 34,262 37,718 46,078 56,152 Restricted cash 4,110 3,240 3,240 3,240 3,240 Short-term investments 8,588 2,036 2,036 2,036 2,036 Accounts receivable 16,359 11,110 13,182 15,066 16,515 Advance to suppliers 395 477 565 641 699 Inventories 41,700 44,030 48,845 55,436 60,398 Prepayments and other current assets 7,392 6,565 6,565 6,565 6,565 Amounts due from related parties 10,797 3,136 3,721 4,253 4,662 Assets held for sale 0 0 0 0 0 Others 0 0 0 0 0 Fixed Assets 69,026 104,309 107,204 114,532 122,160 Property equipment and software, net 12,574 21,083 17,824 21,957 26,391 Construction in progress 3,197 6,554 6,554 6,554 6,554 Intangible asset 6,693 5,012 5,012 5,012 5,012 Land use rights 7,051 10,476 10,476 10,476 10,476 Operating lease right of use assets 0 0 0 0 0 LT Investment 18,551 31,357 37,511 40,705 43,900 Goodwill 6,651 6,644 6,644 6,644 6,644 Other assets 14,310 23,185 23,185 23,185 23,185 Total Assets 184,055 209,165 223,075 247,847 272,426

Current Liabilities 118,251 120,862 124,342 140,412 152,568 Short-term borrowings 200 147 147 147 147 Nonrecourse securitization debt 12,685 4,398 4,398 4,398 4,398 Accounts payable 74,338 79,985 77,124 87,531 95,366 Advance from customers 13,605 13,018 15,420 17,501 19,068 Deferred revenues 1,592 1,980 1,980 1,980 1,980 Tax payable 658 826 980 1,120 1,227 Amounts due to related parties 54 216 216 216 216 Accrued expenses and other current liabilities 15,118 20,293 24,077 27,519 30,166 Long-term Liabilities 13,416 11,475 11,475 11,475 11,475 Deferred revenues 1,274 463 463 463 463 Noncourse securitization debt 4,475 0 0 0 0 Unsecured senior notes 6,447 6,786 6,786 6,786 6,786 Deferred tax liabilities 882 828 828 828 828 Other non-current liabilities 337 3,397 3,397 3,397 3,397 Total liabilities 131,666 132,337 135,817 151,887 164,042

Redeemable non-controlling interests 0 15,961 15,961 15,961 15,961

JD's shareholders' equity 52,041 59,771 70,202 78,903 91,327 Non-controlling interest 348 1,096 1,096 1,096 1,096 Total shareholders' equity 52,389 60,867 71,297 79,999 92,423 Total Liabilities and Shareholder's Equity 184,055 209,165 223,075 247,847 272,426

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 31 27 May 2019 Software & Services China E-commerce

Figure 44: JD cash flow statement

(RMBm) 2017 2018 2019E 2020E 2021E Cash flow from operating activities 26,857 20,881 13,638 23,759 26,376 Net Profit (losses) -19 -2,801 6,173 3,836 7,090 Depreciation & amortization 4,193 5,560 7,288 8,071 8,674 SBC 2,780 3,660 4,257 4,866 5,334 Allowance for doubtful accounts 0 0 0 0 0 Loss on disposal of PP&E 12 -11 0 0 0 Deferred income tax -221 -10 0 0 0 FX loss -213 192 0 0 0 Impairment on cost method investment, AFS, goodw 140 615 0 0 0 Share of results of equity investees 1,927 1,113 0 0 0 Cash flow from discontinued operating activities -2,486 0 0 0 0 WC Change 20,806 12,356 -4,080 6,986 5,278 AR -546 4,287 -2,072 -1,884 -1,449 Restricted cash 0 0 Inventories -12,788 -2,342 -4,815 -6,591 -4,962 Advance to suppliers -137 -75 -88 -76 -57 Prepayments and other current assets -328 -899 0 0 0 Amount due from related party 2,457 1,770 -585 -532 -409 AP 26,106 5,467 -2,861 10,407 7,835 Advance from customers 2,139 -746 2,403 2,081 1,567 Deferred revenue -374 -603 0 0 0 Taxes payable 93 166 154 140 108 Accrued exp and other current liabilities 4,624 5,158 3,785 3,442 2,646 Amount due to related party -66 129 0 0 0 Other -373 45 0 0 0 Other CFO -62 206 0 0 0

Cash flow from investing activities -39,815 -26,079 -10,183 -15,398 -16,302 ST investments -9,683 2,291 0 0 0 LT Investments -6,005 -15,792 -7,960 -5,000 -5,000 Purchase of property, equipment and software -3,294 -9,743 -2,223 -10,398 -11,302 Cash paid for CIP -3,267 -7,359 0 0 0 Purchases of land use right/office building -4,786 -4,136 0 0 0 Cash flow from discontinued investing activities -17,871 0 0 0 0 Others 5,091 8,661 0 0 0

Cash flow from financing activities 19,235 11,220 0 0 0 Ordinary shares 136 3,326 0 0 0 ST borrowings -1,657 -21 0 0 0 Nonrecourse securitization debt 5,611 -11,960 0 0 0 Cash flow from discontinued financing activities 14,055 0 0 0 0 Others 1,091 19,875 0 0 0

FX Adjustment -642 1,681 0 0 0

Change in cash 5,635 7,704 3,455 8,361 10,074 Begin Cash 24,164 29,799 37,502 40,957 49,318 End cash of discontinued operations 0 0 End Cash 29,799 37,502 40,957 49,318 59,392

Source : Company data, Deutsche Bank estimates

Page 32 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce Valuation and key risks

Valuation

We value JD on an SOTP basis to include 1) the value of JD Retail (e-commerce operations), 2) JD Logistics for its 3PL operations only, 3) JD property management value for property and land assets that JD plans to monetize, and 4) net cash.

For core operations, we value it on 20x EV/EBITDA, referencing a number of global peers such as Alibaba, Amazon or Mercado Libre. We believe JD is one of the largest and most successful on and offline retailers in China and deserves to trade at a valuation on a par with global peers. At the same time, the valuation multiple is lower than the 24x we ascribe to Alibaba as we think the core technological capabilities at Alibaba are stronger and give it a more sustainable growth outlook over time.

For JD Logistics, we reference EV/sales for a number of Chinese comparable logistics firms such as YTO, even though we are not yet sure if JDL is as price-competitive as stand-alone logistics firms (which are generating sustained profitability vs. JDL's losses). While JDL has received a stand-alone valuation appraisal of post-money US$13bn in April 2018 after Series A financing, we would note that the valuation includes both the value for internal orders and its external third-party 3PL operations. The internal order fulfillment is already captured in our core JD Retail value, so we only separately value JDL's 3PL operations at US$3.4bn. We value property at the book value that JD has earmarked for available for sale assets.

Figure 45: JD SoTP valuation

US$mn Valuation basis Valuation basis Value, RMB m Multiple, x Equity value, US$ m JD Retail 2019 EV/EBITDA 10,656 20.0x 35,098 JD Logistics (3PL only) 2019 EV/Sales 18,414 1.3x 3,482 JD Property management Book value @ 1Q19 7,159 1.0x 1,041 Net cash 2018 28,207 1.0x 4,102 Total valuation (USD, mn) 43,724 # of FD ADS (mn) 1,487 Value per share (US$) $29.4

Source : Company data, Deutsche Bank estimates

The conclusion is a US$29.4/share value, resulting in a Hold rating.

Key risks

n Upside risks include ongoing core JD Retail margin improvement, a narrowing loss from JD Logistics, and a rebound in 3C and home appliance consumption in China. n Downside risks include fiercer competition on logistics resulting in a higher loss ratio of JD Logistics, as well as pressure on the core JD Retail segment from e-commerce peers and offline electronics retailers. Larger-than-expected loss from new initiatives is also one of the downside risks.

Deutsche Bank AG/Hong Kong Page 33 27 May 2019 Software & Services China E-commerce Company profile

Shareholding structure

Figure 46: Shareholding structure

Source : Company data

Page 34 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Management profile

Figure 47: Management profile

Directors and Executive Officers Position/Title Profile

Richard Qiangdong Liu has been chairman and chief executive officer since JD's inception. Mr. Liu has over 15 years of experience in the retail and e-commerce industries. In June 1998, Mr. Liu started his own business in Chairman of the Board of Directors and Beijing, which was mainly engaged in the distribution of magneto-optical products. In January 2004, Mr. Liu Richard Qiangdong Liu Chief Executive Officer launched his first online retail website. He founded JD business later that year. Mr. Liu received a bachelor’s degree in sociology from Renmin University of China in Beijing and an EMBA degree from the China Europe International Business School. Lei Xu is chief executive officer of JD Retail, responsible for the development, operation and strategy of retail business, both online and offline. Since in 2009, Mr. Xu has held several leadership roles including head of Lei Xu Chief Executive Officer of JD Retail marketing and branding, head of JD Wireless, and head of marketing and platform operations. Mr. Xu holds an EMBA degree from China Europe International Business School. Zhenhui Wang is chief executive officer of JD Logistics. He joined JD in April 2010. Mr. Wang previously served as a senior vice president and the head of our fulfillment operations. Prior to that, he led smart devices business, Zhenhui Wang Chief Executive Officer of JD Logistics where he built the JD+ smart ecosystem, Alpha. Prior to that, Mr. Wang served as regional head, in charge of logistics operations in North China. Mr. Wang holds a bachelor’s degree in engineering from the University of Science and Technology Beijing and an EMBA from China Europe International Business School. Sidney Xuande Huang has served as chief financial officer since September 2013. Prior to that, Mr. Huang was the chief financial officer of VanceInfo Technologies Inc, and its successor company, Pactera Technology International Ltd., from July 2006 to September 2013. He was also the co-president of VanceInfo Technologies Sidney Xuande Huang Chief Financial Officer Inc. from 2011 to 2012 and its chief operating officer from 2008 to 2010. Mr. Huang obtained his masters of business administration with distinction from the Kellogg School of Management at Northwestern University as an Austin Scholar. He received his bachelor’s degree in accounting from Bernard M. Baruch College, where he graduated as class valedictorian. Yayun Li is chief compliance officer, overseeing compliance, legal affairs and internal audits, as well as information security. She joined JD in December 2007. Prior to her current role, Ms. Li served as vice president Yayun Li Chief Compliance Officer of compliance department has also been responsible for establishing effective compliance and internal controls to meet U.S. listing requirements. Ms. Li holds a master’s degree in law from Renmin University and an EMBA from China Europe International Business School. Martin Chiping Lau has served as director since March 2014. Mr. Lau is president and executive director of Tencent Holdings Limited. In December 2017, Mr. Lau was appointed as a director of Vipshop Holdings Limited. Martin Chiping Lau Director Mr. Lau received a bachelor of science degree in electrical engineering from the University of Michigan, a master of science degree in electrical engineering from Stanford University and an MBA degree from Kellogg Graduate School of Management, Northwestern University. Ming Huang has served as independent director since March 2014. Mr. Huang has been a professor of finance at the Johnson Graduate School of Management at Cornell University since July 2005 and a professor of finance Ming Huang Independent Director at China Europe International Business School (CEIBS) since July 2010. Professor Huang received his bachelor’ s degree in physics from Peking University, a Ph.D. in theoretical physics from Cornell University and a Ph.D. in finance from Stanford University. Louis T. Hsieh has served as independent director since May 2014. Mr. Hsieh has been the group chief financial officer for NIO Inc. since May 2017. Mr. Hsieh has served as the director of New Oriental Education & Technology Group Inc. since March 2007, and served as its chief financial officer from December 2005 to April Louis T. Hsieh Independent Director 2015 and its president from May 2009 to January 2016. Mr. Hsieh holds a bachelor’s degree in industrial engineering and engineering management from Stanford University, an MBA degree from the Harvard Business School, and a J.D. degree from the University of California at Berkeley. Dingbo Xu has served as independent director since May 2018. Professor Xu has served as a faculty member and professor in highly-respected universities for more than two decades. He is currently Essilor Chair Professor Dingbo Xu Independent Director in Accounting and an associate dean at China Europe International Business School in Shanghai. Professor Xu received his Ph.D in accounting from the University of Minnesota, as well as a master’s degree in management and a bachelor’s degree in mathematics, both from Wuhan University.

Source : Company data

Deutsche Bank AG/Hong Kong Page 35 27 May 2019 Software & Services China E-commerce

Rating Company Han Joon Kim

Buy Pinduoduo Research Analyst +852 - - 2203 6157 Asia China Price at 23 May 2019 (USD) 20.53 Price target - 12mth (USD) 26.20 Technology Reuters Bloomberg Software & Services PDD.OQ PDD US 52-week range (USD) 31.14 - 17.15 HANG SENG INDEX 27,267

Price/price relative PDD - poster child of social commerce 40

era; initiating with Buy 30

20 High risk stock but with meaningful upside on forward FCF 10 By our analysis, PDD's merchant economics are not yet proven, which is by far the Oct '18 Jan '19 Apr '19

most important focal point in relation to whether PDD is a sustainable business or Pinduoduo HANG SENG INDEX (Rebased) not. That being said, the company has proved its capability in growing users effi-

ciently and continues to scale its operations rapidly, a task which many other lead- Performance (%) 1m 3m 12m ing firms have failed to accomplish. While it remains in net loss on profits, positive Absolute -16.0-30.1 – FCF also provides a financial buffer for the company to weather through and finance HANG SENG INDEX -9.0 -5.4-11.1 its growth. We encourage investors to remain cognizant that PDD is a young com- Source: Deutsche Bank pany and may face execution hiccups along the way. That said, the stock has a Key indicators (FY1) strong two-year return profile where we could see the stock rise by 3.5x on the same ROE (%) -36.7 FCF multiple if it can execute on scaling not just users, but also purchase frequency and size. We see risk/reward skewed positively and rate PDD a Buy. Our target price Net debt/equity (%) -208.0 of US$26.2 implies 28% upside potential based on 2019 financials. Book value/share (CNY) 16.82 Price/book (x) 8.4 FCF buffer to work out operating kinks and growth pains Net interest cover (x) – PDD has lower frequency and average ticket size of orders compared to peers, indi- Operating profit margin (%) -31.7 cating a less sticky user base. The marketing to sales ratio has also been higher than Source: Deutsche Bank its sales, resulting in losses. Yet, we believe product mix and user retention can be Comparatives improved upon with better product merchandising. Marketing efficiency is also the strongest among peers, although absolute dollar losses are still high. Most of all, we Pinduoduo (PDD.OQ),USD20.53 Buy believe its marketplace model gives the business negative working capital and the 2018A 2019E 2020E FCF to weather a period when not all KPIs may be optimized and business remains P/E (x) – – 40.9 loss-making. We forecast 22% FCF margin versus -19% non-GAAP net margin in EV/EBITDA (x) – – – 2019. Price/book (x) 5.9 8.4 7.6

Source: Deutsche Bank Valuation and risks We apply 30x EV/FCF, slightly lower than the historical average of 31x. We broadly benchmark other global players with strong marketplace models such as Alibaba, Rakuten, Mercado Libre and Amazon. On a growth adjusted basis, we see PDD has significant room for a better valuation. The stock is currently trading at 24x 2019 EV/FCF, similar levels to where Alibaba bottomed in 2015-2017. A key risk is user growth stalling and not creating efficiency fast enough in P&L.

Page 36 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Forecasts and ratios Year End Dec 31 2017A 2018A 2019E 2020E 2021E Sales (CNYm) 1,744.1 13,120.0 26,711.4 44,455.1 64,674.5 EBITDA (CNYm) -583.5 -10,302.7 -8,426.9 -505.8 8,768.2 Reported NPAT (CNYm) -488.7 -10,297.6 -7,382.6 903.6 10,679.9 Pro-forma NPAT (CNYm) – – – – – Pro-forma EPS (CNY) – – – – – Reported EPS FD(CNY) -1.11 -13.88 -5.79 0.69 8.10 DB EPS FD(CNY) -0.84 -4.66 -4.02 3.47 12.15 OLD DB EPS FD(CNY) – – – – – % Change – – – – – DB EPS growth (%) – -452.1 13.7 – 250.2 PER (x) – – – 40.9 11.7 EV/EBITDA (x) – – – – 10.9 DPS (net) (CNY) 0.00 0.00 0.00 0.00 0.00 Yield (net) (%) – 0.0 0.0 0.0 0.0 Source: Deutsche Bank estimates, company data

Deutsche Bank AG/Hong Kong Page 37 27 May 2019 Software & Services China E-commerce Outlook and financial forecast

PDD is the poster child of the latest social commerce phenomenon in China, lever- aging social media platforms, such as Tencent's WeChat platform, to offer discounted group buying activity for consumers. The company helps distribute sub- stantially discounted products, which we liken to the white-label fast product model that the likes of Uniqlo or Muji have pioneered over the past several decades. While the company will need to deal with the challenges that arise from distributing goods that lie between counterfeit and white label goods, we believe PDD is in a strong position to leverage: 1) China as a manufacturing hub of many consumer products where production capabilities of non-branded manufacturers in China rise to match the quality of branded goods, and 2) demand from more price-sensi- tive consumers, whether they be the higher-tier-city consumer looking for price conscious alternatives or the lower-tier-city consumer with a tighter discretionary spending budget.

As discussed in the industry section, PDD has been and continues to scale its users rapidly, becoming the second largest e-commerce platform by user size. Numerous merchant interviews all indicate that the user behavior is meaningfully different from those on other platforms, indicating that PDD does indeed cater to a specific consumer psychology or demand profile. Surprisingly, the company has been able to achieve user scale with higher marketing efficiency than shown by other peers.

As a result, the number of merchants willing to sell their products on PDD has been scaling significantly, reaching 2m merchants on average in 2018, but 3.6m by 4Q18. Given that merchants are required to deposit funds and keep an open account with PDD at all times, to protect against potential claims or fraudulent activity, PDD operates as a marketplace model with negative working capital. As such, its balance sheet and cash flow are stronger than its P&L would indicate. To illustrate, we estimate PDD will have a net loss of -RMB5.1bn in 2019. However, we expect at least RMB33bn in payables to merchants and merchant deposits in 2019, up from RMB21.5bn in 2018, even if the average deposit or payables to merchant drops from RMB10,344 to RMB6,751 in 2019. The incremental cash held by PDD provides the business buffer on cashflow and to weather P&L losses.

Thus, we are less worried about PDD's long-term sustainability on its operating loss in the P&L, but more on whether it can justify a sufficient level of ROI for merchants to be able to provide a robust set of products on its website, and continue to convert users to higher frequency and ticket size of purchase over time. The metrics have been improving over the past two years, but we do not believe the level is yet high enough for higher quality merchants.

Page 38 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 48: Average orders per active customer, annualized Figure 49: Average ticket size, annualized

RMB

0 0 1Q17 2Q17 3Q17 4Q17 1Q18 2Q18 3Q18 4Q18 1Q17 2Q17 3Q17 4Q17 1Q18 2Q18 3Q18 4Q18

Source : Company data, Deutsche Bank estimates Source : Company data, Deutsche Bank estimates Note: Based on fulfillment GMV which is 60% of reported GMV (DBe)

Figure 50: Number of active merchants, annualized Figure 51: Payable to merchants + merchant deposits per active merchants

5.0 12,000 4.1 11,009 4.0 10,000

3.0 8,000 7,360

6,000 2.0 1.7 4,000 1.0 2,000

0.0 0 1Q18 2Q18 3Q18 4Q18 1Q19 1Q18 2Q18 3Q18 4Q18 1Q19

Source : Company data, Deutsche Bank estimates Source : Company data, Deutsche Bank estimates

As long as merchant ROI can improve, we believe merchants' ability to advertise more on PDD and scale PDD's revenue can also grow over time.

Marketing cost is the key variable in turning profitable

While merchant ROI is the key KPI to monitor, we believe the other key variable to PDD's financial turnaround is its marketing cost. As such, we provide earnings sensitivity around the marketing cost ratio to showcase the underlying earnings power to PDD.

Within marketing cost, nearly half of it is spent on advertising, including branding ads and performance-based ads, while the remainder has been mainly on promotions and coupons. Historically, PDD has focused on providing coupons and rebates to consumers to incentivize spending on the platform. Since 2016, the company has shifted its advertising to focus more on branding as well and continues to look for the right mix between branding and performance and user retention. Cur- rently, we forecast PDD's marketing cost at 88% of sales in 2019 and customer acquisition cost (CAC) at RMB242. Assuming the company can maintain its CAC level, we estimate that market cost could fall from 89% in 2019 to 60% in 2020 and

Deutsche Bank AG/Hong Kong Page 39 27 May 2019 Software & Services China E-commerce

45% in 2021. As a result, we believe non-GAAP net margin could improve from -19% to +25% by 2021, marking a turnaround in profits.

Given the competitive dynamics between Alibaba and PDD, we believe near-term challenges temper any hope of a CAC reduction.

Figure 52:Sales & marketing cost as % of sales vs. Non- Figure 53: Sales & marketing breakdown GAAP net margin in 2016-2021E

120% 100%

80% 80%

40% 60%

40%

- -40% - - 20%

-80% - 2016 2017 2018 2019E 2020E 2021E 2016 2017 2018 Branding advertising Performance marketing S&M as % of revenue non-GAAP NP margin Promotions and coupons Others

Source : Company data, Deutsche Bank estimates Source : Company data, Deutsche Bank estimates

Financial forecasts

Page 40 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 54: PDD key drivers (RMBmn except for GMV) 2017 2018 2019E 2020E 2021E

GMV (RMBbn) GMV, 12M ended 141 472 905 1,376 1,886 YoY % 987% 234% 92% 52% 37% GMV 141 472 905 1,376 1,886 YoY % 987.2% 233.9% 92.0% 52.0% 37.0% Fulfilled GMV 85 283 543 826 1,131 Return, cancellation and unfulfillment rate 40.0% 40.0% 40.0% 40.0% 40.0%

User/order metrics Active Buyers, mn, 12M ended 245 419 523 603 663 YoY % 71% 25% 15% 10% New active buyers 245 174 105 80 60 Annual ARPU (or order size), RMB 577 1,127 1,730 2,281 2,843 YoY % 95% 54% 32% 25% Monthly ARPU (or order size), RMB 48 94 144 190 237 Average MAU, mn 65 216

No. of fulfilled orders, mn, 12M ended 4,300 11,100 Average order size, RMB, 12M 33 42 Average fulfilled order size, RMB, 12M 20 25 Orders per active buyer, 12M 18 27

No. of active merchants, annualized 2,075,000 4,900,000 6,200,000 6,700,000 Avg. GMV per merchant, annualized 136,366 110,874 133,192 168,856 Avg. spending on PDD per merchant, annualized 6,323 5,451 7,170 9,653 % of revenue per merchant, annualized 4.6% 4.9% 5.4% 5.7%

Net revenue 1,744 13,120 26,711 44,455 64,675 YoY % 245% 652% 104% 66% 45% Online marketplace services 1,741 13,120 26,711 44,455 64,675 Online marketing services 1,209 11,516 23,542 38,537 54,681 Transaction services 531 1,604 3,169 5,918 9,993 Merchandise sales 3 0 0 0 0

Online marketplace services Revenue 1,741 13,120 26,711 44,455 64,675 YoY % 3506% 654% 104% 66% 45% % of total revenue 99.8% 100.0% 100.0% 100.0% 100.0% Take rate, % 1.2% 2.8% 3.0% 3.2% 3.4%

Online marketing services 1,209 11,516 23,542 38,537 54,681 YoY % n/a 852% 104% 64% 42% % of online marketplace revenue 69.5% 87.8% 88.1% 86.7% 84.5% Take rate, % 0.9% 2.4% 2.6% 2.8% 2.9%

Transaction services 531 1,604 3,169 5,918 9,993 QoQ % YoY % 1000.8% 201.9% 97.5% 86.7% 68.9% % of online marketplace revenue 30.5% 12.2% 11.9% 13.3% 15.5% Take rate, % 0.4% 0.3% 0.4% 0.4% 0.5%

Merchandise sales Revenue 3 0 0 0 0 YoY % -99% -100% n/a n/a n/a % of total revenue 0.2% 0.0% 0.0% 0.0% 0.0%

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 41 27 May 2019 Software & Services China E-commerce

Figure 55: PDD P&L

(RMBmn) 2017 2018 2019E 2020E 2021E Net revenue 1,744 13,120 26,711 44,455 64,675 YoY% 245% 652% 104% 66% 45%

Cost of revenues 723 2,905 6,917 11,976 18,479 SBC w/i COGS 0.8 3 7 12 17

Gross Profit 1,021 10,215 19,795 32,480 46,195 Gross margin 58.6% 77.9% 74.1% 73.1% 71.4%

Operating expenses 1,617 21,014 28,256 33,043 37,511 S&M 1,345 13,442 23,773 26,673 29,104 G&A 133 6,457 1,476 1,970 2,910 R&D 129 1,116 3,007 4,400 5,497 Impairment of a long-term investment 10 0 0 0 0

Operating Income -596 -10,800 -8,462 -564 8,684 YoY% 108% 1713% -22% -93% -1641% OP margin % -34.2% -82.3% -31.7% -1.3% 13.4%

SBC w/i Opex 116 6,838 2,252 3,659 5,323 S&M 2 406 826 1,375 2,000 G&A 108 6,296 1,149 1,823 2,652 R&D 6 136 277 461 671

Operating Income, non-GAAP -469 -3,958 -6,203 3,107 14,024 YoY% 66% 744% 57% -150% 351% Non-GAAP OP margin, % -26.9% -30.2% -23.2% 7.0% 21.7%

Interest Income 81 585 1,088 1,467 1,996 FX gain/(loss) -12 10 -2 0 0 Change in the fair value of warrant liability 0 0 0 0 0 Other income, net 1 -12 -7 0 0

Pre-Tax Profit -525 -10,217 -7,383 904 10,680 YoY% 80% 1846% -28% -112% 1082%

Income Tax 0 0 0 0 0 Tax rate, % 0.0% 0.0% 0.0% 0.0% 0.0%

Net income (loss) -525 -10,217 -7,383 904 10,680 Deemed distribution to certain holders of convertible preferred shares 0 -80 0 0 0 Contribution from a holder of convertible preferred shares 26 0 0 0 0

Net income (loss) attributable to ordinary shareholders -499 -10,298 -7,383 904 10,680 YoY% 55% 1965% -28% -112% 1082% NP margin % -28.6% -78.5% -27.6% 2.0% 16.5%

Net income (loss), non-GAAP -372 -3,456 -5,124 4,574 16,020 YoY% 17% 829% 48% -189% 250% non-GAAP NP margin -21.3% -26.3% -19.2% 10.3% 24.8%

Source : Company data, Deutsche Bank estimates

Page 42 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 56: PDD balance sheet

(RMBmn) 2017 2018 2019E 2020E 2021E Current Assets 13,138 40,391 56,829 75,092 102,149 Cash and cash equivalents 3,058 14,160 13,122 12,309 18,650 Restricted cash 9,371 16,379 31,448 47,802 65,488 Receivables from online payment platforms 88 248 475 723 990 Short-term investments 50 7,631 7,631 7,631 7,631 Amounts due from related parties 443 1,019 1,957 2,974 4,074 Prepayments and other current assets 128 954 2,195 3,654 5,316 Non-current assets 177 2,791 2,893 3,063 3,309 Property and equipment, net 9 29 131 301 547 Intangible asset 0 2,579 2,579 2,579 2,579 Long-term investment and other non-current assets 167 183 183 183 183 Total Assets 13,314 43,182 59,722 78,154 105,459

Current Liabilities 12,110 24,359 38,297 53,430 67,322 Amounts due to related parties 76 478 893 1,358 1,860 Customer advances 56 191 390 649 944 Payable to merchants 9,839 17,276 25,728 37,707 51,659 Accrued expenses and other liabilities 360 2,226 3,936 4,416 4,819 Merchant deposits 1,778 4,188 7,350 9,300 8,040 Other current liabilities 0 0 0 0 0 Non-current Liabilities 0 0 0 0 0 Total liabilities 12,110 24,359 38,297 53,430 67,322 21,464 5,962 Total mezzanine equity 2,197 0 0 0 0 Ordinary shares 0 0 0 0 0 Additional paid-in capital 61 29,115 36,840 35,566 32,958 Accumulated other comprehensive loss -23 1,036 1,036 1,036 1,036 Accumulated deficits -1,030 -11,328 -16,452 -11,877 4,143 Total shareholders' (deficits)/equity -992 18,823 21,425 24,724 38,137 Total liabilities, mezzanine equity, and shareholders' (deficits) equity 13,314 43,182 59,722 78,154 105,459

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 43 27 May 2019 Software & Services China E-commerce

Figure 57: PDD cash flow statement

(RMBmn) 2017 2018 2019E 2020E 2021E Cash flow from operating activities 9,686 7,768 6,442 17,042 26,966 Net Profit (losses) -525 -10,217 -7,383 904 10,680 Depreciation and amortization 2 497 35 58 84 Impairment of long-term investment 10 0 0 0 0 Change in the fair value of the warrant liability 0 0 0 0 0 Interest income -3 -78 0 0 0 Loss on disposal of property and equipment 0 0 0 0 0 Share-based compensation 13 6,842 2,259 3,671 5,340 WC Change 10,188 10,725 11,531 12,410 10,862 Receivables from online payment platforms -78 -159 -228 -247 -267 Amounts due from related parties -350 -576 -938 -1,017 -1,100 Prepayments and other current assets -88 -789 -1,241 -1,458 -1,662 Amounts due to related parties 51 402 415 464 502 Customer advances 54 135 198 259 295 Payables to merchants 8,722 7,437 8,452 11,980 13,952 Accrued expenses and other liabilities 318 1,864 1,711 480 402 Merchant deposits 1,559 2,410 3,162 1,950 -1,260 Others 0 0 0 0 0

Cash flow from investing activities 72 -7,549 -137 -227 -331 Purchase of short-term investments -1,393 -7,516 0 0 0 Proceeds from sales of short-term investments 1,633 50 0 0 0 Purchase of property and equipment -9 -27 -137 -227 -331 Others -159 -55 0 0 0

Cash flow from financing activities 1,399 17,344 7,726 -1,275 -2,607 Deemed distribution 0 0 0 0 0 Proceeds from issuance of convertible preferred shares 1,447 5,825 0 0 0 Cash raised from IPO 0 11,524 8,113 0 0 Repurchase of ordinary shares 0 0 -387 -1,275 -2,607 Others -48 -4 0 0 0

FX effect -48 547 0 0 0

Change in cash 11,109 18,111 14,031 15,540 24,028 Begin cash, cash equivalents and restricted cash 1,320 12,429 30,540 44,571 60,111 End cash, cash equivalents and restricted cash 12,429 30,540 44,571 60,111 84,139

Source : Company data, Deutsche Bank estimates

Page 44 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce Valuation and key risks

Valuation framework

We value PDD on 30x 2019 EV/FCF, slightly lower than the historical average of 31x. 30x is largely consistent with global leading players with a strong marketplace business model such as Alibaba, Rakuten, Mercado Libre and Amazon. While we would prefer the EV/EBITDA approach to make PDD valuation's cross-comparable with the valuation basis we apply to peers, the company is currently EBITDA-negative, given its heavy marketing cost. We also prefer a cash-flow based valuation over a sales growth-based valuation, as sales growth does not reflect the eventual value of a firm, which we believe should be grounded in its ability to generate positive cash as a reflection of sustainability. We also believe looking at FCF helps highlight that the company is FCF positive, even if P&L is negative, given that PDD has negative working capital needs.

As a reference, PDD and key comparables' EV/FCF are highlighted in the industry section on page 19.

Key risks

Downside risks include:

n Slowdown of growth in MAU and active customers resulting in slower GMV growth when peers penetrate into lower tier cities and low ticket-sized products; n Failure to monetize search/feed advertising from merchants; n Higher marginal marketing cost to acquire new customers and maintain existing customers, which puts continual pressure on margin;

Deutsche Bank AG/Hong Kong Page 45 27 May 2019 Software & Services China E-commerce Company profile

Shareholding structure

Figure 58: Shareholding structure as of March 2019

Source : Company data

Page 46 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Management profile

Figure 59: Management profile

Directors and Executive Officers Position/Title Profile

Zheng Huang is founder of the company and has served as the chairman of board of directors and chief executive officer since the company's inception. Mr. Huang is a serial entrepreneur with significant experience and expertise in the technology and internet sectors in China. Prior to founding the company, Mr. Huang Chairman of the Board of Directors and founded Xinyoudi Studio in 2011 to develop and operate online games. Prior to that, Mr. Huang founded Zheng Huang Chief Executive Officer Ouku.com, a company that operated an online B2C platform for consumer electronics and home appliances, which was subsequently sold in 2010. Mr. Huang started his career at Google's (Nasdaq: GOOG) headquarters in 2004 as a software engineer and project manager. Mr. Huang received his bachelor's degree in computer science from Zhejiang University and his master's degree in computer science with a focus on data mining from LeiUniversity Chen is of a Wisconsin-Madison. founding member of the company and has served as chief technology officer since 2016. Prior to joining the company, Mr. Chen served as chief technology officer of Xinyoudi Studio since 2011. Mr. Chen's prior Lei Chen Chief Technology Officer working experience includes internships with Google (Nasdaq: GOOG), Yahoo Inc. and IBM (NYSE: IBM) in the United States. Mr. Chen received his bachelor's degree in computer science from Tsinghua University and his doctoral degree in computer science from University of Wisconsin-Madison. Zhenwei Zheng is a founding member of the company and has served as senior vice president of product Senior Vice President of Product development since 2016. Prior to joining the company, Mr. Zheng served as chief executive officer of Xinyoudi Zhenwei Zheng Development Studio since 2011. Prior to that, he held various positions at Baidu (Nasdaq: BIDU) from 2008 to 2010. Mr. Zheng received his bachelor's degree and master's degree in computer science from Zhejiang University. Junyun Xiao is a founding member of the company and has served as senior vice president of operation since Junyun Xiao Senior Vice President of Operation 2016. Prior to joining the company, Mr. Xiao served as operation director of Xinyoudi Studio since 2011. Prior to that, he was a member of the founding team of Ouku.com and served as operation manager from 2007 to 2010. Haifeng Lin has served as director since June 2017. Mr. Lin received his bachelor's degree in engineering from Haifeng Lin Director Zhejiang University in June 1997 and his master's degree in business administration from the Wharton School of the University of Pennsylvania in June 2003. Zhen Zhang has served as director since November 2015. Mr. Zhang is one of the founders of Gaorong Capital Zhen Zhang Director and has served as its partner since 2014. Mr. Zhang received his dual bachelor's degree in engineering and law and his master's degree in management from Tsinghua University in 2002. Nanpeng Shen has served as director since April 2018. He has been the highest ranking Chinese investor on Forbes Midas List for the years from 2012 to 2018 and has ascended to the top of the list in 2018. Mr. Shen Nanpeng Shen Independent Director received his bachelor's degree from Shanghai Jiao Tong University and his master's degree from Yale University Qi Lu has served as independent director and the chairman of compensation committee since July 2018. Currently, he is the founding CEO of YC China and vice chairman of the board of directors of Baidu, Inc. Prior to Qi Lu Independent Director joining Baidu, Dr. Lu served as Microsoft's global executive vice president and led Applications and Services Group. Dr. Lu holds both bachelor and master degrees in computer science from Fudan University in Shanghai and a Ph.D. in computer science from Carnegie Mellon University. George Yong-Boon Yeo has served as independent director and chairman of our nominating and corporate governance committee since July 2018. Mr. Yeo served 23 years in the government of Singapore, and was George Yong-Boon Yeo Independent Director Minister for Information and the Arts, Health, Trade & Industry, and Foreign Affairs of Singapore. Mr. Yeo graduated with an MBA (Baker Scholar) from the Harvard Business School in 1985.

Source : Company data

Deutsche Bank AG/Hong Kong Page 47 27 May 2019 Software & Services China E-commerce

Rating Company Han Joon Kim

Buy Vipshop Research Analyst +852 - - 2203 6157 Asia China Price at 23 May 2019 (USD) 7.50 Price target - 12mth (USD) 9.30 Technology Reuters Bloomberg Software & Services VIPS.N VIPS US 52-week range (USD) 12.41 - 4.50 HANG SENG INDEX 27,267

Price/price relative VIPS - promising pivot back to its origins; initiating at Buy 20 10 Pivot back to core roots is encouraging; initiating at Buy 0 At 11x 2019E P/E against 16% yoy growth, we believe VIPS is a GARP (growth at a Jul '17 Jan '18 Jul '18 Jan '19

reasonable price) stock and rate it a Buy. We believe management's decision to piv- Vipshop HANG SENG INDEX (Rebased) ot back to its core competency as an online discount/inventory clearing channel

gives it a sustainable market position although top-line growth will be sacrificed. Performance (%) 1m 3m 12m While strategically sound, the pivot back to an inventory clearing model will require Absolute -6.7 13.0-37.4 optimization of its fulfillment cost and bear execution risk as to whether it can deliv- HANG SENG INDEX -9.0 -5.4-11.1 er on improving profit margins thereafter. Once normalized, we would be keen to Source: Deutsche Bank see if management is interested in improving shareholder return, as we see poten- Key indicators (FY1) tial for VIPS to shift further as a GARP story, one that could attract more value and ROE (%) 14.0 yield-focused investors. Net debt/equity (%) -21.9 Investment thesis Book value/share (CNY) 35.07 After a foray into in-season and an attempt to focus on mainstream online retailing, Price/book (x) 1.48 VIPShop is in the midst of pivoting its business back to its core roots - helping brands Net interest cover (x) – clear inventory, largely for off-season (apparel) products. The end result is contin- Operating profit margin (%) 3.4 ued growth in order volume as business growth continues, but lower ticket size per Source: Deutsche Bank order/parcel as the company helps shift focus to lower (discounted) products. As a Comparatives result, there may be pressure on fulfillment expense, which the company wishes to defray with improvement in logistics expenses, which is costlier than 3PL logistics Vipshop (VIPS.N),USD7.50 Buy in China. VIPS is strategizing ways to improve efficiency of its fulfillment cost. If 2018A 2019E 2020E successful, we think operating margins can begin to recover and revert back to ~6% P/E (x) 16.7 10.4 7.7 non-GAAP OPM over the next several years from 3.7% in 2018. EV/EBITDA (x) 10.4 4.7 3.0 Price/book (x) 1.2 1.5 1.2

Financial outlook Source: Deutsche Bank We anticipate 6% yoy revenue growth with 22% growth in orders but a 13% drop in average order size as product merchandising on its platform shifts back towards discounted products rather than full-priced items. We expect a modest recovery in top-line growth in 2020 as average order size stabilizes and order density continues to grow. Note that we expect single-digit yoy revenue growth, not double-digit. Gross margin was ~25% in 2016 and dropped to ~20% in 2018 as the company adjusted its business model. Its focus on a narrower product selection should bring some recovery. Operating expenses were ~20% of sales in 2016 and fell to 18.2% in 2018, and continuing efforts to reduce fulfillment cost, which is 9% of revenue, will be critical in driving the speed of improvement in its operating margin. In theory, our sensitivity analysis shows that the stock would be ~8x P/E if it converts per-order fulfillment cost to RMB8 (3PL benchmark) from ~RMB14 currently.

Page 48 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Valuation and key risks We value VIPS on 8x 2019E EV/EBITDA, the low end of its historical range. 8x EV/ EBITDA implies 14x non-GAAP P/E, which we believe is reasonable against a high teens earnings growth with potential for 30% earnings CAGR should it succeed in normalizing profits. Key downside risks include fiercer competition for users, a faster decline in ARPU or average order size and a change in strategy once more.

Forecasts and ratios Year End Dec 31 2017A 2018A 2019E 2020E 2021E Sales (CNYm) 72,912 84,524 89,392 97,405 105,358 EBIT (CNYm) 2,690 2,421 3,015 4,200 5,370 EBITDA (CNYm) 3,752 3,311 3,830 5,088 6,330 Reported NPAT (CNYm) 1,950 2,129 2,657 3,456 4,452 Reported EPS FD(CNY) 3.12 3.38 4.23 5.48 6.34 DB EPS FD(CNY) 4.67 4.32 5.00 6.71 7.53 OLD DB EPS FD(CNY) 4.82 6.00 7.26 – – % Change -3.1% -27.9% -31.1% – – DB EPS growth (%) 2.5 -7.5 15.7 34.2 12.2 DPS (net) (CNY) 0.00 0.00 0.00 0.00 0.00 BV/Shares (x) 24.5 29.4 35.1 42.0 45.8 Price/BV (x) 3.2 1.2 1.5 1.2 1.1 ROE (%) 19.5 13.5 14.0 15.2 16.2 Yield (net) (%) 0.0 0.0 0.0 0.0 0.0 EV/EBITDA (x) 10.3 10.4 4.7 3.0 1.8 PER (x) 16.2 16.7 10.4 7.7 6.9 Source: Deutsche Bank estimates, company data

Deutsche Bank AG/Hong Kong Page 49 27 May 2019 Software & Services China E-commerce Outlook and financial forecasts

We forecast 2019 revenue growth at 6% yoy and improving to 9% yoy in 2020 and 8% yoy in 2021. Benefiting from the return to an inventory-clearing model, we expect to see gross margin recover by 50bps per year from 2019, after deterioration for the last four years. Meanwhile, lower ticker size would be likely to result in less leverage of fulfillment cost on operating margin and net margin. We estimate fulfillment cost as a % of sales could decrease from 9.0% in 2019 to 8.1% in 2021, which brings our non-GAAP OP margin to 6.1% and non-GAAP net margin to 5.2% in 2021.

Below is the full set of our financial forecasts.

Page 50 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 60: VIPS key drivers

(RMBmn except for GMV) 2017 2018 2019E 2020E 2021E GMV (RMBbn) VIPS total GMV 108 131 140 153 169 YoY % 28% 21% 7% 10% 10% KPIs Active customers (mn), trailing 12 months 58 61 63 65 68 YoY % 11% 5% 4% 4% 4% Total number of orders (m) 335 437 534 603 663 YoY % 24% 31% 22% 13% 10% Order per active customer per quarter 3 4 4 4 4 YoY % 6% 21% 7% 5% 4% Total revenue 72,912 84,524 89,392 97,405 105,358 YoY % 29% 16% 6% 9% 8% Product revenue 71,172 81,510 85,679 92,901 99,950 YoY % 29% 15% 5% 8% 8% Other revenues 1,741 3,014 3,713 4,504 5,408 YoY % 33% 73% 23% 21% 20% % of total revs 2% 4% 4% 5% 5% 3P commission revenue 379 565 806 1,147 1,549 YoY % 10% 49% 43% 42% 35% % of other revs 22% 19% 22% 25% 29% Take rate % 7% 7% 9% 9% 9% Advertising 379 600 871 938 1,009 YoY % 58% 45% 8% 8% % of other revs 22% 20% 23% 21% 19% % of 1P GMV 0.4% 0.5% 0.7% 0.7% 0.7% Logistics/Colocation 169 255 307 368 441 YoY % 51% 20% 20% 20% % of other revs 10% 8% 8% 8% 8% Consumer finance revenue 250 585 304 368 436 YoY % 118% 134% -48% 21% 19% % of other revs 14% 19% 8% 8% 8% % of GMV processed by VIPS Finance 19% 23% 23% 26% 28% Attributable GMV 20.2 29.9 32.7 39.6 46.9 Yield, %, Monthly 0.41% 0.65% 0.31% 0.31% 0.31% 3PL 468 794 1,064 1,223 1,431 YoY % 70% 34% 15% 17% % of other revs 27% 26% 29% 27% 26% Super VIP member subscription revenue 16 146 261 350 420 YoY % 835% 79% 34% 20% % of other revs 1% 5% 7% 8% 8% ARPU 16 65 64 66 66 Others 80 68 100 110 121 YoY % -91% -15% 47% 10% 10% % of other revs 5% 2% 3% 2% 2%

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 51 27 May 2019 Software & Services China E-commerce

Figure 61: VIPS P&L (RMB m) 2017 2018 2019E 2020E 2021E Revenue 72,912 84,524 89,392 97,405 105,358 YoY % 29% 16% 6% 9% 8% Cost of services 56,618 67,455 70,888 76,755 82,495 Gross Profit 16,294 17,069 18,504 20,650 22,863 Gross margin, % 22.3% 20.2% 20.7% 21.2% 21.7%

Operating Expenses 14,134 15,405 16,290 17,322 18,436 Fulfillment expenses 6,900 7,489 8,068 8,201 8,570 Marketing expenses 2,979 3,240 3,427 3,896 4,214 Technology and content expenses 1,808 2,001 1,967 2,143 2,318 G&A expenses 2,448 2,674 2,828 3,082 3,333

Other income, net 531 757 801 872 944 Operating Income 2,690 2,421 3,015 4,200 5,370 YoY % -1% -10% 25% 39% 28% OP margin, % 3.7% 2.9% 3.4% 4.3% 5.1%

SBC expenses 667 671 710 774 837 SBC w/i fullfillment expenses 73 73 77 84 91 SBC w/i marketing expenses 40 41 43 47 51 SBC w/i technology and content expenses 206 204 215 235 254 SBC w/i G&A expenses 347 353 374 407 441

Amortization of intangible assets resulting from business a 340 46 0 0 0 Operating Income, non-GAAP 3,697 3,138 3,725 4,974 6,207 YoY % 6% -15% 19% 34% 25% Non-GAAP OP margin, % 5.1% 3.7% 4.2% 5.1% 5.9%

Non-operating income 157 571 510 349 433 Non-operating expenses 306 245 213 171 171 Non Operating Income (net) -150 326 297 178 262

Pre-Tax Profit 2,541 2,747 3,312 4,378 5,632 YoY % -5% 8% 21% 32% 29% Income tax expense 626 567 683 903 1,162 Tax rate % 25% 21% 21% 21% 21% Share of results of equity method investment -22 -47 47 0 0

Net income 1,892 2,133 2,676 3,475 4,471 Non-controlling interests -57 5 19 19 19 Net income attributable to shareholders 1,950 2,129 2,657 3,456 4,452 YoY % -4% 9% 25% 30% 29% NP margin, % 2.7% 2.5% 3.0% 3.5% 4.2%

Non-GAAP adjustment - net income SBC 667 671 710 774 837 Impairment loss in investments 133 20 0 0 0 Loss (gain) on disposal, revaluation and value changes -56 -192 -214 0 0 of investments Tax effect of investment gain 0 10 -45 0 0 Others 226 81 30 0 0

Net income attributable to shareholders, non GAAP 2,920 2,719 3,138 4,230 5,289 YoY % 2% -7% 15% 35% 25% Non-GAAP NP margin, % 4.0% 3.2% 3.5% 4.3% 5.0%

Source : Company data, Deutsche Bank estimates

Page 52 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 62: VIPS balance sheet

(RMB m) 2017 2018 2019E 2020E 2021E Current assets 25,916 27,326 29,481 33,369 38,650 Cash and cash equivalents 9,974 9,541 11,065 13,594 17,532 Restricted deposits 248 498 498 498 498 Held-to-maturity investments 246 2,321 2,321 2,321 2,321 Accounts receivable 4,804 5,986 6,330 6,898 7,461 Other receivables and prepayment 3,674 3,595 3,802 4,143 4,481 Inventories 6,960 5,368 5,447 5,898 6,339 Others 10 17 17 17 17 Non-current assets 12,067 16,237 18,462 20,496 22,170 Property and equipment, net 6,969 8,708 10,933 12,967 14,641 Land use right 3,078 3,886 3,886 3,886 3,886 Investment in equity/cost method investees 401 353 353 353 353 Available-for-sale investments 454 1,471 1,471 1,471 1,471 LT investments 146 667 667 667 667 Goodwill 367 367 367 367 367 Deferred tax assets 285 389 389 389 389 Others 367 396 396 396 396

Total assets 37,983 43,563 47,943 53,865 60,820

Current liabilities 19,258 25,946 26,940 28,614 30,261 Accounts payable 11,445 11,630 12,222 13,234 14,223 Short term loan 907 5,670 5,670 5,670 5,670 Advance from customers 2,340 1,473 1,558 1,698 1,836 Accrued expenses and other current liabilities 3,537 5,513 5,830 6,353 6,871 Amounts due to related parties 65 323 323 323 323 Deferred income 203 368 368 368 368 Securitization debt 760 969 969 969 969 Non-current liabilities 4,475 406 406 406 406 Deferred tax liabilities 17 5 5 5 5 Deferred income non-current 363 401 401 401 401 Long term interest bearing debt 4,095 0 0 0 0 Total liabilities 23,732 26,352 27,346 29,020 30,667

Additional paid-in capital 8,716 9,385 9,385 9,385 9,385 Retained earnings 5,603 7,907 11,274 15,504 20,793 Accumulated other comprehensive income (loss) -24 -31 -31 -31 -31 Non-controlling interest -44 -51 -32 -14 5 Total shareholders' equity 14,251 17,211 20,596 24,845 30,152 Total equity of parent entity 14,251 17,211 20,629 24,859 30,147

Total liabilities and shareholders' equity 37,983 43,563 47,942 53,865 60,819

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 53 27 May 2019 Software & Services China E-commerce

Figure 63: VIPS cash flow statement (RMB m) 2017 2018 2019E 2020E 2021E Net Profit 1,892 2,133 2,676 3,475 4,471 Allowance for doubtful accounts 131 175 0 0 0 Inventory write-down 207 441 0 0 0 Depreciation 721 770 815 888 960 Amortization/Impairment of intangible assets 341 119 0 0 0 SBC 667 671 710 774 837 WC Change -3,118 1,608 363 315 304 Others 140 -173 0 0 0 Cash from operating activities 981 5,746 4,564 5,451 6,572

Property and equipment -2,198 -2,520 -3,039 -2,922 -2,634 Land use right -158 -1,073 0 0 0 Purchases of held-to-maturity investments 443 -1,943 0 0 0 Investments in affiliates and other investments -17 -964 0 0 0 Acquisition of subsidiaries -5 0 0 0 0 Purchases of available for sale investments 39 0 0 0 0 Cash paid on loan originations -189 -764 0 0 0 Others 52 570 0 0 0 Cash from investing activities -2,033 -6,694 -3,039 -2,922 -2,634

Proceeds from/to bank borrowings 907 419 0 0 0 Issuance of ordinary shares 5,616 4 0 0 0 Others 646 164 0 0 0 Cash from financing activities 7,170 587 0 0 0

FX Adjustment -6 178 0 0 0 Other adjustments 0 0 0 0 0

Begin Cash 4,110 10,222 10,039 11,563 14,092 End Cash 10,222 10,039 11,563 14,092 18,030 Change in cash 6,112 -184 1,524 2,529 3,938

Source : Company data, Deutsche Bank estimates

Page 54 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce Valuation and key risks

Valuation framework

We value VIPS on 8x EV/EBITDA, the low end of its historical range. The stock has historically shown a correlation to its revenue growth outlook, which has slowed meaningfully to mid-single-digit in 2019. As the company pivots to a discounted inventory clearing model, we believe the defined TAM is smaller and relatively mature, implying that its top-line growth is not likely to accelerate back to 20% yoy. As a result, we think our 8x EV/EBITDA, on a par with an implied 14x 2019 P/E, is fair at an estimated 13% yoy EBITDA growth and 15% non-GAAP net profit growth in 2019.

In a sector where growth investors dominate versus value investors, we believe there is room for VIPS to attract incremental value-oriented investors. However, we believe it would need to fully stabilize and execute on its core business strategy, possibly even to the point of improving shareholder returns. Until then, we believe VIPS may remain relatively out of favor for growth-oriented investors.

Earnings sensitivity

One of the key challenges we see from the company strategy changing to an inventory-clearing focused model is fulfillment cost per order, given the lower ticket size of off-season products. We compare the fulfillment cost per order of VIPS with other logistics peers, per financials and quotes on parcel delivery. VIPS' cost of fulfillment is 75% higher than 3PL peers. There are clear differences in fulfillment expenses based on average weight of parcel, number of parcels per order, frequency of reverse logistics among other factors. As a result, the direct comparison of financial headline data is not meaningful. Nevertheless, we highlight the difference to point out that there is room for margin improvement should VIPS successfully optimize its fulfillment expenses.

Deutsche Bank AG/Hong Kong Page 55 27 May 2019 Software & Services China E-commerce

Figure 64: Fulfillment cost per order comparison of VIPS and peers - 2018

42.1

13.9

8.0 8.0

0 VIPS JDL SF Express YTO STO BEST ZTO Yunda

Source : Company data, Deutsche Bank estimates Note: 1) We estimate VIPS/JDL cost of fulfilled orders based on our estimation of non-fulfillment/returned/cancelation ratio. 2) We use SF Express (self-operated) revenue divided by no. of parcels delivered. We check quotes of parcel delivery for YTO/STO/BEST/ZTO/Yun- da since they are franchised model.

The fulfillment cost ratio of sales is currently 9%. Our sensitivity analysis assumes what the improvement to net margin could be if fulfillment cost per order is reduced or increased. As shown below, we believe the stock could be trading as low as 8x P/E if it can decrease its fulfillment cost by 75% to RMB8 per order.

Figure 65: Sensitivity analysis of fulfillment cost - 2019 Fulfillment cost per order Fulfillment cost as % of sales Non-GAAP net margin Non-GAAP EPS growth Implied P/E RMB8 6.0% 6.0% 95.7% 7.8x RMB10 7.5% 4.8% 56.7% 9.7x RMB12 9.0% 3.6% 17.8% 12.9x Base - RMB14 10.4% 2.5% -19.1% 18.9x RMB16 12.0% 1.2% -60.1% 38.2x RMB18 13.5% 0.0% -99.0% NM RMB20 15.0% -1.2% -137.9% NM

Source : Deutsche Bank estimates Note: we use 2018 fulfillment cost per order of RMB13.9 as base case.

Key downside risks

n Fiercer competition for user acquisition n A faster decline in ARPU or average order size. n A change in strategy once more is a risk to the outlook.

Page 56 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce Company profile

Shareholding structure

Figure 66: Shareholding structure as of March 2019

Source : Company data

Deutsche Bank AG/Hong Kong Page 57 27 May 2019 Software & Services China E-commerce

Management profile

Figure 67: Management profile

Directors and Executive Officers Position/Title Profile

Eric Ya Shen is co-founder and has served as the chairman of board of directors and chief executive officer since Vipshop inception in August 2010. He has over 20 years of experience in the distribution of consumer Chairman of the Board of electronic products in domestic and overseas markets. From 2001 to 2012, Mr. Shen served as the chairman of Eric Ya Shen Directors, Chief Executive Officer the board of directors of Guangzhou NEM Import and Export Co., Ltd. Mr. Shen received an EMBA degree from Cheung Kong Graduate School of Business in 2010 and an associate degree in telecommunication from Shanghai Railway College in 1990. Arthur Xiaobo Hong is co-founder and has served as the vice chairman of board of directors since January 2011. Mr. Hong has served as chief operating officer since August 2012. Mr. Hong has over 15 years of Vice Chairman of the Board of Arthur Xiaobo Hong experience in the distribution of consumer electronic products in overseas markets. From 1998 to 2011, Mr. Directors, Chief Operating Officer Hong served as chairman of the board of directors of Société Europe Pacifique Distribution since 1998. Mr. Hong graduated from Cheung Kong Graduate School of Business in 2010. Donghao Yang has served as chief financial officer since August 2011. Mr. Yang has held senior executive and managerial positions in various public and private companies. Mr. Yang received an MBA degree from Harvard Donghao Yang Chief Financial Officer Business School in 2003 and a bachelor's degree in international economics from Nankai University in 1993. Mr. Daniel Kao has served as chief technology officer from June 2012 to October 2016, and again since April 2019. Mr. Kao has over 20 years of experience with leading e-commerce and Internet companies in the United Daniel Kao Chief Technology Officer States and China. Mr. Kao received a bachelor's degree in computer science from Iowa State University in 1995. Yizhi Tang has served as senior vice president since November 2012. Before that, Mr. Tang served as vice president from September 2010 to November 2012. Mr. Tang has over 10 years of experience in the logistics Yizhi Tang Senior Vice President of Logistics industry. Prior to joining us, Mr. Tang served as an operating director of Best Logistics Technology Co., Ltd. from 2009 to 2010. Mr. Tang received a master's degree from Sun Yat-Sen University in 2003 and a bachelor's degree from Nanjing University of Aeronautics and Astronautics in 1997.

Martin Chi Ping Lau has served as director since December 2017. Mr. Lau is president and executive director of Tencent. He joined Tencent in 2005 as the chief strategy and investment officer. of Tencent. In 2007, he was Martin Chi Ping Lau Director appointed as an executive director of Tencent. Mr. Lau received a bachelor of science degree in electrical engineering from the University of Michigan, a master of science degree in electrical engineering from Stanford University and an MBA degree from Kellogg Graduate School of Management, Northwestern University.

Jacky Yu Xu is an angel investor of company and has served as director since January 2011. Mr. Xu is the Jacky Yu Xu Director director of several privately held companies in China. Mr. Xu graduated from Cheung Kong Graduate School of Business in 2009. Chun Liu has served as director since March 2013. Mr. Chun Liu is currently the chief culture officer of Zhong Nan Wen Hua. Prior to that, he was the senior vice president of iQiyi.com. Prior to joining iQiyi.com, he was vice Chun Liu Independent Director president and managing director of Soho.com Inc. and chief operating officer of Sohu Video. Mr. Chun Liu received an EMBA degree from Cheung Kong Graduate School of Business in China and a master's degree from the Communication University of China. Frank Lin has served as director since January 2011. Mr. Lin is a general partner of DCM. Prior to joining DCM in 2006, Mr. Lin was chief operating officer of SINA Corporation. Mr. Lin currently serves on the board of Frank Lin Independent Director directors of numerous DCM portfolio companies. Mr. Lin received an MBA degree from Stanford University and a bachelor's degree in engineering from Dartmouth College. Xing Liu has served as director since January 2011. Mr. Liu is a partner of Sequoia Capital China. Prior to joining Sequoia Capital China in 2007, Mr. Liu had over nine years of work experience in investment banking, Xing Liu Independent Director technology and product development and consulting. Mr. Liu received a master's degree in computer engineering from Syracuse University, an MBA degree from The Wharton School of the University of Pennsylvania and a bachelor's degree in management information systems from Fudan University. Kathleen Chien has served as director since March 2012. Ms. Chien is currently the chief operating officer and acting chief financial officer of 51job, Inc.. Prior to joining 51job, Inc., Ms. Chien worked in the financial services Kathleen Chien Independent Director and management consulting industries. Ms. Chien received her bachelor's degree in economics from the Massachusetts Institute of Technology and an MBA degree from the Walter A. Haas School of Business at University of California, Berkeley. Nanyan Zheng has served as director since March 2012. Mr. Zheng is currently the chairman of Plateno Group Ltd. Mr. Zheng founded Plateno Group Ltd. in 2013. Mr. Zheng co-founded 7 Days Groups Holdings Ltd. and Nanyan Zheng Independent Director has been serving as its chief executive officer since October 2004. . Mr. Zheng received a bachelor's degree from Sun Yat-Sen University in China.

Source : Company data

Page 58 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Figure 68: Summary of key financial metrics of China e-commerce players BABA JD PDD VIPS GMV, RMBbn 2016 3,602 939 13 85 2017 4,570 1,294 141 108 2018 5,569 1,677 472 131 2019E 6,690 2,055 905 140 GMV growth, % 2016 22.1% 103.0% na 38.7% 2017 26.9% 37.8% 987.2% 27.9% 2018 21.9% 29.5% 233.9% 20.8% 2019E 20.1% 22.5% 92.0% 6.5% Revenue, RMBmn 2016 143,878 258,290 505 56,591 2017 226,913 362,332 1,744 72,912 2018 345,278 462,020 13,120 84,524 2019E 471,432 548,186 26,711 89,392 Revenue growth, % 2016 52.4% 42.7% na 40.8% 2017 57.7% 40.3% 245.5% 28.8% 2018 52.2% 27.5% 652.3% 15.9% 2019E 36.5% 18.6% 103.6% 5.8% Gross margin, % 2016 62.8% 13.7% -14.5% 24.0% 2017 60.3% 14.0% 58.6% 22.3% 2018 46.8% 14.3% 77.9% 20.2% 2019E 45.1% 14.4% 74.1% 20.7% S&M cost, RMBmn 2016 14,843 10,159 169 2,838 2017 23,990 14,918 1,345 2,979 2018 37,772 19,237 13,442 3,240 2019E 48,389 22,476 23,773 3,427 S&M as % of sales, % 2016 10.3% 3.9% 33.5% 5.0% 2017 10.6% 4.1% 77.1% 4.1% 2018 10.9% 4.2% 102.5% 3.8% 2019E 10.3% 4.1% 89.0% 3.8% Paying customer acquisition cost (CAC), RMB 2016 412 142 na 183 2017 333 226 na 523 2018 312 1,503 77 1,200 2019E 544 1,770 238 1,358 Non-GAAP OP margin, % 2016 42.1% 0.1% -55.9% 6.2% 2017 39.5% 0.8% -27.5% 5.1% 2018 27.3% 0.4% -30.2% 3.7% 2019E 24.9% 1.0% -23.2% 4.2% Non-GAAP net margin, % 2016 38.3% 0.8% -63.1% 5.1% 2017 35.1% 1.4% -21.3% 4.0% 2018 25.3% 0.7% -26.3% 3.2% 2019E 25.0% 1.2% -19.2% 3.5% Non-GAAP EPS growth, % 2016 28.5% 152.5% na 30.4% 2017 42.4% 133.6% na 1.9% 2018 9.2% -31.1% na -16.4% 2019E 32.0% 94.7% na 16.1%

Source : Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 59 27 May 2019 Software & Services China E-commerce

Model updated: 23 May 2019 Fiscal year end 31-Mar 2017 2018 2019 2020E 2021E 2022E Running the numbers Financial Summary Asia DB EPS (CNY) 22.48 31.88 34.96 46.19 63.32 79.35 Reported EPS (CNY) 16.98 24.37 33.50 34.11 52.63 69.06 China DPS (CNY) 0.00 0.00 0.00 0.00 0.00 0.00 Software & Services BVPS (CNY) 113.3 144.5 193.4 237.1 296.3 374.1 Weighted average shares (m) 2,487 2,553 2,580 2,596 2,606 2,617 Average market cap (CNYm) 1,541,648 2,756,403 2,958,032 2,571,884 2,571,884 2,571,884 Alibaba Enterprise value (CNYm) 1,391,595 2,590,580 2,815,202 2,295,890 2,158,881 1,966,104 Reuters: BABA.N Bloomberg: BABA US Valuation Metrics P/E (DB) (x) 27.6 33.9 32.8 23.4 17.0 13.6 Buy P/E (Reported) (x) 36.5 44.3 34.2 31.6 20.5 15.6 P/BV (x) 6.40 8.42 6.33 4.41 3.53 2.79 Price (23 May 19) USD 156.0 FCF Yield (%) 4.1 3.5 2.9 3.5 4.5 6.3 Target Price USD 220.0 Dividend Yield (%) 0.0 0.0 0.0 0.0 0.0 0.0 EV/Sales (x) 8.8 10.4 7.5 4.6 3.4 2.5 52 Week range USD 130.60 - 210.86 EV/EBITDA (x) 23.8 30.4 34.0 18.4 11.8 8.4 EV/EBIT (x) 29.0 37.6 49.3 24.6 14.8 10.2 Market cap (m) USDm 371,904 EURm 333,247 Income Statement (CNYm) Sales revenue 158,273 250,266 376,844 499,859 643,699 785,222 Company Profile Gross profit 98,790 143,222 169,915 223,824 320,086 401,304 Founded in 1999, Alibaba leads the China retail market through EBITDA 58,461 85,223 82,773 124,806 182,978 234,051 Taobao (the largest online shopping platform in China based on Depreciation 5,284 8,789 14,962 18,495 23,817 29,053 GMV),Tmall (the largest 3rd party platform for retailers/brands Amortisation 5,122 7,614 10,727 12,812 12,812 12,812 in terms of GMV) and Juhuasuan (a leading China group EBIT 48,055 68,820 57,084 93,499 146,349 192,186 buying platform). The company caters to global wholesale Net interest income(expense) 5,888 26,929 38,916 4,535 8,840 14,282 market through Alibaba.com and China wholesale market Associates/affiliates -5,027 -20,792 566 623 685 753 through 1688.com. Alibaba also serves the global consumer Exceptionals/extraordinaries 0 0 0 0 0 0 market place via. AliExpress and also provides cloud computing Other pre-tax income/(expense) 6,086 4,160 221 4,288 4,862 5,449 services such as data mining, processing and storage. Profit before tax 60,029 99,909 96,221 102,322 160,050 211,917 Price Performance Income tax expense 13,776 18,199 16,553 19,565 27,803 35,583 225 Minorities -2,449 -2,681 -7,652 -8,417 -9,259 -10,185 200 Other post-tax income/(expense) 0 0 0 0 0 0 Net profit 43,675 63,599 87,886 91,796 142,191 187,272 175 150 DB adjustments (including dilution) 14,127 19,615 3,842 32,508 28,855 27,929 DB Net profit 57,802 83,214 91,728 124,304 171,046 215,201 125 100 Jul '17 Jan '18 Jul '18 Jan '19 Cash Flow (CNYm)

Alibaba NASDAQ 100 (Rebased) Cash flow from operations 80,326 125,171 150,975 162,588 204,661 266,050 Net Capex -17,546 -29,836 -66,665 -64,593 -77,084 -87,908 Margin Trends Free cash flow 62,780 95,335 84,310 97,995 127,577 178,142 Equity raised/(bought back) 1,512 12,824 26,052 27,695 19,058 20,319 40 Dividends paid -163 -112 0 0 0 0 Net inc/(dec) in borrowings 29,333 -3,590 3,000 0 0 0 30 Other investing/financing cash flows -59,275 -52,930 -84,395 12,660 0 0 Net cash flow 34,187 51,527 28,967 138,350 146,634 198,461 20 Change in working capital 7,259 22,082 4,356 19,789 9,798 21,795 10 17 18 19 20E 21E 22E Balance Sheet (CNYm) EBITDA Margin EBIT Margin Cash and other liquid assets 143,736 199,309 189,976 305,576 422,632 594,702 Tangible fixed assets 20,206 66,489 92,030 128,128 171,396 220,250 Growth & Profitibility Goodwill/intangible assets 144,219 198,991 333,211 269,193 266,381 263,569 80 24 Associates/investments 131,430 162,683 188,370 197,516 208,210 218,733 Other assets 67,221 89,652 161,489 229,161 251,524 273,528 60 22 Total assets 506,812 717,124 965,076 1,129,574 1,320,144 1,570,781 40 20 Interest bearing debt 82,783 125,553 119,190 119,190 119,190 119,190 Other liabilities 99,908 152,132 230,484 287,063 329,919 384,240 20 18 Total liabilities 182,691 277,685 349,674 406,253 449,109 503,430 0 16 Shareholders' equity 281,791 368,823 499,076 615,412 772,385 978,886 17 18 19 20E 21E 22E Minorities 42,330 70,616 116,326 107,909 98,650 88,465 Total shareholders' equity 324,121 439,439 615,402 723,321 871,034 1,067,351 Sales growth (LHS) ROE (RHS) Net debt -60,953 -73,756 -70,786 -186,386 -303,442 -475,512

Solvency Key Company Metrics 0 Sales growth (%) 56.5 58.1 50.6 32.6 28.8 22.0 -20 DB EPS growth (%) 34.6 41.8 9.7 32.1 37.1 25.3 EBITDA Margin (%) 36.9 34.1 22.0 25.0 28.4 29.8 -40 EBIT Margin (%) 30.4 27.5 15.1 18.7 22.7 24.5 Payout ratio (%) 0.0 0.0 0.0 0.0 0.0 0.0 -60 ROE (%) 17.5 19.6 20.3 16.5 20.5 21.4 17 18 19 20E 21E 22E Capex/sales (%) 11.1 11.9 17.7 12.9 12.0 11.2 Capex/depreciation (x) 3.3 3.4 4.5 3.5 3.2 3.0 Net debt/equity (LHS) Net interest cover (RHS) Net debt/equity (%) -18.8 -16.8 -11.5 -25.8 -34.8 -44.6 Han Joon Kim Net interest cover (x) nm nm nm nm nm nm +852 2203 6157 [email protected] Source: Company data, Deutsche Bank estimates

Page 60 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Model updated: 23 May 2019 Fiscal year end 31-Dec 2016 2017 2018 2019E 2020E 2021E Running the numbers Financial Summary Asia DB EPS (CNY) 1.46 3.41 2.35 4.58 6.54 8.55 Reported EPS (CNY) -2.38 0.09 -1.69 4.36 2.74 4.79 China DPS (CNY) 0.00 0.00 0.00 0.00 0.00 0.00 Software & Services BVPS (CNY) 24.2 36.6 41.5 48.0 52.9 60.0 Weighted average shares (m) 1,402 1,422 1,439 1,462 1,492 1,522 Average market cap (CNYm) 233,918 359,048 329,657 268,781 268,781 268,781 JD.com Enterprise value (CNYm) 218,870 330,376 290,391 219,905 208,350 195,082 Reuters: JD.OQ Bloomberg: JD US Valuation Metrics P/E (DB) (x) 114.2 74.0 97.5 40.3 28.2 21.6 Hold P/E (Reported) (x) nm nm nm 42.3 67.4 38.6 P/BV (x) 6.99 7.65 3.33 3.85 3.49 3.08 Price (23 May 19) USD 26.70 FCF Yield (%) 1.9 4.3 nm 4.2 4.9 5.4 Target Price USD 29.40 Dividend Yield (%) 0.0 0.0 0.0 0.0 0.0 0.0 EV/Sales (x) 0.8 0.9 0.6 0.4 0.3 0.3 52 Week range USD 19.27 - 43.76 EV/EBITDA (x) 91.9 98.4 98.7 28.6 17.5 12.1 EV/EBIT (x) nm nm nm 556.8 54.1 26.3 Market cap (m) USDm 38,867 EURm 34,827 Income Statement (CNYm) Sales revenue 258,290 362,332 462,020 548,186 626,555 686,808 Company Profile Gross profit 38,989 55,008 71,514 86,305 102,147 115,340 JD.com is Chinaâs leading one-stop e-commerce platform, EBITDA 2,382 3,357 2,941 7,682 11,923 16,103 offering a vast selection of products, across major categories Depreciation 2,025 2,415 3,754 5,482 6,266 6,868 (electronics, apparel and home furnishings, FMCG, fresh food, Amortisation 1,609 1,778 1,806 1,806 1,806 1,806 home appliances and others). EBIT -1,252 -835 -2,619 395 3,852 7,429 Net interest income(expense) 367 1,499 1,263 452 661 912 Associates/affiliates 0 0 0 0 0 0 Exceptionals/extraordinaries 0 0 0 0 0 0 Other pre-tax income/(expense) -997 -542 -1,018 6,169 0 0 Profit before tax -1,882 121 -2,374 7,015 4,513 8,341 Price Performance Income tax expense 166 140 427 842 677 1,251 60 Minorities -48 -135 -309 -318 -318 -318 50 Other post-tax income/(expense) -1,365 7 0 0 0 0 Net profit -3,366 124 -2,492 6,491 4,154 7,408 40 30 DB adjustments (including dilution) 5,434 4,845 5,951 318 5,776 5,822 DB Net profit 2,068 4,968 3,460 6,809 9,930 13,230 20 10 Jul '17 Jan '18 Jul '18 Jan '19 Cash Flow (CNYm)

JD.com NASDAQ 100 (Rebased) Cash flow from operations 8,767 26,857 20,881 13,638 23,759 26,376 Net Capex -4,410 -11,347 -21,239 -2,223 -10,398 -11,302 Margin Trends Free cash flow 4,357 15,510 -357 11,415 13,361 15,074 Equity raised/(bought back) -5,256 136 3,326 0 0 0 3 Dividends paid 0 0 0 0 0 0 2 Net inc/(dec) in borrowings 7,920 3,954 -11,981 0 0 0 Other investing/financing cash flows -5,113 -13,964 16,716 -7,960 -5,000 -5,000 1 Net cash flow 1,908 5,635 7,704 3,455 8,361 10,074 0 Change in working capital 4,333 20,806 12,356 -4,080 6,986 5,278 -1 16 17 18 19E 20E 21E Balance Sheet (CNYm) EBITDA Margin EBIT Margin Cash and other liquid assets 19,772 25,688 34,262 37,718 46,078 56,152 Tangible fixed assets 11,463 22,822 38,112 34,853 38,986 43,420 Growth & Profitibility Goodwill/intangible assets 14,838 13,343 11,655 11,655 11,655 11,655 80 20 Associates/investments 22,862 27,139 33,392 39,547 42,741 45,935 Other assets 91,439 95,063 91,743 99,302 108,386 115,264 60 10 Total assets 160,374 184,055 209,165 223,075 247,847 272,426 40 0 Interest bearing debt 20,259 23,807 11,331 11,331 11,331 11,331 Other liabilities 98,895 107,859 121,006 124,485 140,556 152,711 20 -10 Total liabilities 119,154 131,666 132,337 135,817 151,887 164,042 0 -20 Shareholders' equity 33,893 52,041 59,771 70,202 78,903 91,327 16 17 18 19E 20E 21E Minorities 7,327 348 17,057 17,057 17,057 17,057 Total shareholders' equity 41,220 52,389 76,828 87,259 95,960 108,384 Sales growth (LHS) ROE (RHS) Net debt 487 -1,881 -22,931 -26,387 -34,747 -44,821

Solvency Key Company Metrics 20 Sales growth (%) 42.7 40.3 27.5 18.6 14.3 9.6 0 DB EPS growth (%) 152.5 133.6 -31.1 94.7 42.9 30.6 -20 EBITDA Margin (%) 0.9 0.9 0.6 1.4 1.9 2.3 EBIT Margin (%) -0.5 -0.2 -0.6 0.1 0.6 1.1 -40 Payout ratio (%) nm 0.0 nm 0.0 0.0 0.0 -60 ROE (%) -10.4 0.3 -4.5 10.0 5.6 8.7 16 17 18 19E 20E 21E Capex/sales (%) 1.7 3.1 4.6 0.4 1.7 1.6 Capex/depreciation (x) 1.2 2.7 3.8 0.3 1.3 1.3 Net debt/equity (LHS) Net interest cover (RHS) Net debt/equity (%) 1.2 -3.6 -29.8 -30.2 -36.2 -41.4 Han Joon Kim Net interest cover (x) nm nm nm nm nm nm +852 2203 6157 [email protected] Source: Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 61 27 May 2019 Software & Services China E-commerce

Model updated: 22 May 2019 Fiscal year end 31-Dec 2017 2018 2019E 2020E 2021E Running the numbers Financial Summary Asia DB EPS (CNY) -0.84 -4.66 -4.02 3.47 12.15 Reported EPS (CNY) -1.11 -13.88 -5.79 0.69 8.10 China DPS (CNY) 0.00 0.00 0.00 0.00 0.00 Software & Services BVPS (CNY) 2.7 25.4 16.8 18.7 28.9 Weighted average shares (m) 441 742 1,274 1,319 1,319 Average market cap (CNYm) na 104,346 187,253 187,253 187,253 Pinduoduo Enterprise value (CNYm) na 65,993 134,869 119,329 95,301 Reuters: PDD.OQ Bloomberg: PDD US Valuation Metrics P/E (DB) (x) nm nm nm 40.9 11.7 Buy P/E (Reported) (x) nm nm nm 207.2 17.5 P/BV (x) 0.00 5.85 8.44 7.57 4.91 Price (23 May 19) USD 20.53 FCF Yield (%) na 7.4 3.5 9.0 14.2 Target Price USD 26.20 Dividend Yield (%) na 0.0 0.0 0.0 0.0 EV/Sales (x) nm 5.0 5.0 2.7 1.5 52 Week range USD 17.15 - 31.14 EV/EBITDA (x) nm nm nm nm 10.9 EV/EBIT (x) nm nm nm nm 11.0 Market cap (m) USDm 27,077 EURm 24,263 Income Statement (CNYm) Sales revenue 1,744 13,120 26,711 44,455 64,675 Company Profile Gross profit 1,021 10,215 19,795 32,480 46,195 Pinduoduo is a fast growing "new e-commerce" platform that EBITDA -583 -10,303 -8,427 -506 8,768 provides buyers with an innovative "team purchase" model and Depreciation 2 497 35 58 84 interactive shopping experiences. Amortisation 0 0 0 0 0 EBIT -586 -10,800 -8,462 -564 8,684 Net interest income(expense) 81 585 1,088 1,467 1,996 Associates/affiliates 0 0 0 0 0 Exceptionals/extraordinaries 0 0 0 0 0 Other pre-tax income/(expense) -10 -2 -9 0 0 Profit before tax -515 -10,217 -7,383 904 10,680 Price Performance Income tax expense 0 0 0 0 0 35 Minorities 0 0 0 0 0 Other post-tax income/(expense) 26 -80 0 0 0 30 Net profit -489 -10,298 -7,383 904 10,680 25 DB adjustments (including dilution) 117 6,842 2,259 3,671 5,340 20 DB Net profit -372 -3,456 -5,124 4,574 16,020 15 Sep '18 Nov '18 Jan '19 Mar '19 May '19 Cash Flow (CNYm)

Pinduoduo HANG SENG INDEX (Rebased) Cash flow from operations 9,686 7,768 6,442 17,042 26,966 Net Capex -9 -27 -137 -227 -331 Margin Trends Free cash flow 9,677 7,741 6,305 16,815 26,635 Equity raised/(bought back) 1,447 17,348 7,726 -1,275 -2,607 25 Dividends paid 0 0 0 0 0 0 Net inc/(dec) in borrowings 0 0 0 0 0 -25 Other investing/financing cash flows -15 -6,978 0 0 0 -50 Net cash flow 11,109 18,111 14,031 15,540 24,028 -75 Change in working capital -10,189 -10,688 -11,531 -12,410 -10,862 -100 17 18 19E 20E 21E Balance Sheet (CNYm) EBITDA Margin EBIT Margin Cash and other liquid assets 12,429 30,540 44,571 60,111 84,139 Tangible fixed assets 9 29 131 301 547 Growth & Profitibility Goodwill/intangible assets 0 2,579 2,579 2,579 2,579 1000 50 Associates/investments 217 7,813 7,813 7,813 7,813 Other assets 659 2,221 4,627 7,350 10,380 750 0 Total assets 13,314 43,182 59,722 78,154 105,459 500 -50 Interest bearing debt 0 0 0 0 0 Other liabilities 12,110 24,359 38,297 53,430 67,322 250 -100 Total liabilities 12,110 24,359 38,297 53,430 67,322 0 -150 Shareholders' equity 1,205 18,823 21,425 24,724 38,137 17 18 19E 20E 21E Minorities 0 0 0 0 0 Total shareholders' equity 1,205 18,823 21,425 24,724 38,137 Sales growth (LHS) ROE (RHS) Net debt -12,429 -30,540 -44,571 -60,111 -84,139

Solvency Key Company Metrics 0 Sales growth (%) nm 652.3 103.6 66.4 45.5 -100 DB EPS growth (%) na -452.1 13.7 na 250.2 EBITDA Margin (%) -33.5 -78.5 -31.5 -1.1 13.6 -200 EBIT Margin (%) -33.6 -82.3 -31.7 -1.3 13.4 Payout ratio (%) nm nm nm 0.0 0.0 -300 ROE (%) -40.6 -102.8 -36.7 3.9 34.0 17 18 19E 20E 21E Capex/sales (%) 0.5 0.2 0.5 0.5 0.5 Capex/depreciation (x) 3.9 0.1 3.9 3.9 3.9 Net debt/equity (LHS) Net interest cover (RHS) Net debt/equity (%) nm -162.3 -208.0 -243.1 -220.6 Han Joon Kim Net interest cover (x) nm nm nm nm nm +852 2203 6157 [email protected] Source: Company data, Deutsche Bank estimates

Page 62 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Model updated: 24 May 2019 Fiscal year end 31-Dec 2016 2017 2018 2019E 2020E 2021E Running the numbers Financial Summary Asia DB EPS (CNY) 4.56 4.67 4.32 5.00 6.71 7.53 Reported EPS (CNY) 3.24 3.12 3.38 4.23 5.48 6.34 China DPS (CNY) 0.00 0.00 0.00 0.00 0.00 0.00 Software & Services BVPS (CNY) 9.9 24.5 29.4 35.1 42.0 45.8 Weighted average shares (m) 580 584 587 588 592 658 Average market cap (CNYm) 49,833 44,087 42,322 27,237 27,237 27,237 Vipshop Enterprise value (CNYm) 48,101 38,716 34,465 17,875 15,364 11,445 Reuters: VIPS.N Bloomberg: VIPS US Valuation Metrics P/E (DB) (x) 18.9 16.2 16.7 10.4 7.7 6.9 Buy P/E (Reported) (x) 26.5 24.2 21.3 12.3 9.5 8.2 P/BV (x) 7.40 3.24 1.23 1.48 1.23 1.13 Price (23 May 19) USD 7.50 FCF Yield (%) 0.6 nm 5.1 5.0 8.2 11.5 Target Price USD 9.30 Dividend Yield (%) 0.0 0.0 0.0 0.0 0.0 0.0 EV/Sales (x) 0.8 0.5 0.4 0.2 0.2 0.1 52 Week range USD 4.50 - 12.41 EV/EBITDA (x) 13.1 10.3 10.4 4.7 3.0 1.8 EV/EBIT (x) 17.8 14.4 14.2 5.9 3.7 2.1 Market cap (m) USDm 3,938.6 EURm 3,529.2 Income Statement (CNYm) Sales revenue 56,591 72,912 84,524 89,392 97,405 105,358 Company Profile Gross profit 13,597 16,294 17,069 18,504 20,650 22,863 Vipshop, founded in 2008, is a leading online discount retailer EBITDA 3,683 3,752 3,311 3,830 5,088 6,330 for brands in China, offering high-quality branded products Depreciation 611 721 770 815 888 960 through flash sales mainly on Vipshop Online Platform. Amortisation 364 341 119 0 0 0 EBIT 2,708 2,690 2,421 3,015 4,200 5,370 Net interest income(expense) 22 19 83 124 178 262 Associates/affiliates -71 -22 -47 47 0 0 Exceptionals/extraordinaries 0 0 0 0 0 0 Other pre-tax income/(expense) -63 -168 243 172 0 0 Profit before tax 2,666 2,541 2,747 3,312 4,378 5,632 Price Performance Income tax expense 602 626 567 683 903 1,162 20 Minorities -44 -57 5 19 19 19 Other post-tax income/(expense) 0 0 0 0 0 0 15 Net profit 2,037 1,950 2,129 2,657 3,456 4,452 10 DB adjustments (including dilution) 830 970 590 481 774 837 5 DB Net profit 2,867 2,920 2,719 3,138 4,230 5,289 0 Jul '17 Jan '18 Jul '18 Jan '19 Cash Flow (CNYm)

Vipshop HANG SENG INDEX (Rebased) Cash flow from operations 2,831 981 5,746 4,564 5,451 6,572 Net Capex -2,545 -2,356 -3,593 -3,039 -2,922 -2,634 Margin Trends Free cash flow 286 -1,375 2,153 1,524 2,529 3,938 Equity raised/(bought back) -188 5,616 4 0 0 0 7 Dividends paid 0 0 0 0 0 0 6 Net inc/(dec) in borrowings -95 907 419 0 0 0 5 Other investing/financing cash flows 782 963 -2,760 0 0 0 4 Net cash flow 785 6,112 -184 1,524 2,529 3,938 3 Change in working capital -1,211 -3,118 1,608 363 315 304 2 16 17 18 19E 20E 21E Balance Sheet (CNYm) EBITDA Margin EBIT Margin Cash and other liquid assets 4,110 10,222 10,038 11,563 14,092 18,030 Tangible fixed assets 7,906 10,046 12,594 14,818 16,853 18,527 Growth & Profitibility Goodwill/intangible assets 367 367 367 367 367 367 50 60 Associates/investments 2,401 1,247 4,812 4,812 4,812 4,812 Other assets 10,310 16,100 15,751 16,382 17,741 19,083 40 50 Total assets 25,094 37,983 43,563 47,943 53,865 60,820 30 40 Interest bearing debt 4,729 6,142 7,045 7,045 7,045 7,045 20 30 Other liabilities 14,583 17,590 19,307 20,301 21,975 23,622 10 20 Total liabilities 19,313 23,732 26,352 27,346 29,020 30,667 0 10 Shareholders' equity 5,732 14,295 17,262 20,629 24,859 30,147 16 17 18 19E 20E 21E Minorities 50 -44 -51 -32 -14 5 Total shareholders' equity 5,782 14,251 17,211 20,596 24,845 30,152 Sales growth (LHS) ROE (RHS) Net debt 620 -4,080 -2,993 -4,518 -7,047 -10,985

Solvency Key Company Metrics 20 Sales growth (%) 40.8 28.8 15.9 5.8 9.0 8.2 0 DB EPS growth (%) 7.1 2.5 -7.5 15.7 34.2 12.2 EBITDA Margin (%) 6.5 5.1 3.9 4.3 5.2 6.0 -20 EBIT Margin (%) 4.8 3.7 2.9 3.4 4.3 5.1 Payout ratio (%) 0.0 0.0 0.0 0.0 0.0 0.0 -40 ROE (%) 43.9 19.5 13.5 14.0 15.2 16.2 16 17 18 19E 20E 21E Capex/sales (%) 4.5 3.2 4.3 3.4 3.0 2.5 Capex/depreciation (x) 2.6 2.2 4.0 3.7 3.3 2.7 Net debt/equity (LHS) Net interest cover (RHS) Net debt/equity (%) 10.7 -28.6 -17.4 -21.9 -28.4 -36.4 Han Joon Kim Net interest cover (x) nm nm nm nm nm nm +852 2203 6157 [email protected] Source: Company data, Deutsche Bank estimates

Deutsche Bank AG/Hong Kong Page 63 27 May 2019 Software & Services China E-commerce Appendix 1

Important Disclosures *Other information available upon request

Disclosure checklist Company Ticker Recent price* Disclosure Alibaba BABA.N 155.0 (USD) 24 May 2019 1, 7, 8, 14 JD.com JD.OQ 26.32 (USD) 24 May 2019 2, 8, 14, 15 Pinduoduo PDD.OQ 20.28 (USD) 24 May 2019 NA Vipshop VIPS.N 7.65 (USD) 24 May 2019 8, 14, 15 *Prices are current as of the end of the previous trading session unless otherwise indicated and are sourced from local exchanges via Reuters, Bloomberg and other vendors . Other information is sourced from Deutsche Bank, subject companies, and other sources. For disclosures pertaining to recommendations or estimates made on securities other than the primary subject of this research, please see the most recently published company report or visit our global disclosure look-up page on our website at https://research.db.com/Research/Disclosures/ CompanySearch. Aside from within this report, important risk and conflict disclosures can also be found at https://research.db.com/Research/Topics/Equities?topicId=RB0002. Investors are strongly encouraged to review this information before investing. Important Disclosures Required by U.S. Regulators Disclosures marked with an asterisk may also be required by at least one jurisdiction in addition to the United States.See Important Disclosures Required by Non-US Regulators and Explanatory Notes. 1. Within the past year, Deutsche Bank and/or its affiliate(s) has managed or co-managed a public or private offering for this company, for which it received fees. 2. Deutsche Bank and/or its affiliate(s) makes a market in equity securities issued by this company. 7. Deutsche Bank and/or its affiliate(s) has received compensation from this company for the provision of investment banking or financial advisory services within the past year. 8. Deutsche Bank and/or its affiliate(s) expects to receive, or intends to seek, compensation for investment banking services from this company in the next three months. 14. Deutsche Bank and/or its affiliate(s) has received non-investment banking related compensation from this company within the past year. 15. This company has been a client of Deutsche Bank Securities Inc. within the past year, during which time it received non-investment banking securities-related services.

Important Disclosures Required by Non-U.S. Regulators Disclosures marked with an asterisk may also be required by at least one jurisdiction in addition to the United States.See Important Disclosures Required by Non-US Regulators and Explanatory Notes. 1. Within the past year, Deutsche Bank and/or its affiliate(s) has managed or co-managed a public or private offering for this company, for which it received fees. 2. Deutsche Bank and/or its affiliate(s) makes a market in equity securities issued by this company. 7. Deutsche Bank and/or its affiliate(s) has received compensation from this company for the provision of investment banking or financial advisory services within the past year. For disclosures pertaining to recommendations or estimates made on securities other than the primary subject of this research, please see the most recently published company report or visit our global disclosure look-up page on our website at https://research.db.com/Research/Disclosures/CompanySearch Analyst Certification The views expressed in this report accurately reflect the personal views of the undersigned lead analyst about the subject issuers and the securities of those issuers. In addition, the undersigned lead analyst has not and will not receive any compensation for providing a specific recommendation or view in this report. Han Joon Kim.

Page 64 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Historical recommendations and target price: Alibaba (BABA.N) (as of 05/23/2019) 250.00 Current Recommendations Buy 8 Hold 200.00 Sell 6 7 10 16 11 17 Not Rated 9 5 15 Suspended Rating 4 12 13 3 150.00 12 14 ** Analyst is no longer at Deutsche Bank

100.00 Security price

50.00

0.00 Sep '17 Jan '18 May '18 Sep '18 Jan '19 May '19 Date

1. 06/12/2017 Buy, Target Price Change USD 161.00 Alan Hellawell** 10. 05/04/2018 Buy, Target Price Change USD 201.00 Hanjoon Kim 2. 06/18/2017 Buy, Target Price Change USD 158.00 Alan Hellawell** 11. 08/23/2018 Buy, Target Price Change USD 196.00 Hanjoon Kim 3. 07/02/2017 Buy, Target Price Change USD 201.00 Alan Hellawell** 12. 10/09/2018 Buy, Target Price Change USD 189.00 Hanjoon Kim 4. 08/17/2017 Buy, Target Price Change USD 208.00 Alan Hellawell** 13. 11/02/2018 Buy, Target Price Change USD 191.00 Hanjoon Kim 5. 09/06/2017 Buy, Target Price Change USD 199.00 Alan Hellawell** 14. 01/04/2019 Buy, Target Price Change USD 179.00 Hanjoon Kim 6. 11/02/2017 Buy, Target Price Change USD 209.00 Hanjoon Kim 15. 01/30/2019 Buy, Target Price Change USD 194.00 Hanjoon Kim 7. 01/19/2018 Buy, Target Price Change USD 208.00 Hanjoon Kim 16. 04/10/2019 Buy, Target Price Change USD 192.00 Hanjoon Kim 8. 02/01/2018 Buy, Target Price Change USD 218.00 Hanjoon Kim 17. 05/15/2019 Buy, Target Price Change USD 197.00 Hanjoon Kim 9. 04/04/2018 Buy, Target Price Change USD 204.00 Hanjoon Kim §§§§$$$$$§§§§§

Historical recommendations and target price: JD.com (JD.OQ) (as of 05/23/2019) 60.00 Current Recommendations Buy Hold 50.00 Sell 1 2 Not Rated Suspended Rating 40.00 ** Analyst is no longer at Deutsche Bank 30.00

Security price 20.00

10.00

0.00 Sep '17 Jan '18 May '18 Sep '18 Jan '19 May '19 Date

1. 07/25/2017 Buy, Target Price Change USD 50.00 Alan Hellawell** 2. 08/14/2017 Buy, Target Price Change USD 52.00 Alan Hellawell** §§§§$$$$$§§§§§

Deutsche Bank AG/Hong Kong Page 65 27 May 2019 Software & Services China E-commerce

Historical recommendations and target price: Pinduoduo (PDD.OQ) (as of 05/23/2019) 40.00 Current Recommendations Buy Hold Sell 30.00 Not Rated Suspended Rating

** Analyst is no longer at Deutsche Bank 20.00 Security price

10.00

0.00 Sep '18 Nov '18 Jan '19 Mar '19 May '19 Date

§§§§$$$$$§§§§§

Historical recommendations and target price: Vipshop (VIPS.N) (as of 05/23/2019) 25.00 Current Recommendations Buy Hold 20.00 Sell Not Rated Suspended Rating

15.00 ** Analyst is no longer at Deutsche Bank 1 2 10.00 Security price

5.00

0.00 Sep '17 Jan '18 May '18 Sep '18 Jan '19 May '19 Date

1. 06/30/2017 Hold, Target Price Change USD 12.60 Alan Hellawell** 2. 08/17/2017 Hold, Target Price Change USD 11.70 Alan Hellawell** §§§§$$$$$§§§§§

Page 66 Deutsche Bank AG/Hong Kong 27 May 2019 Software & Services China E-commerce

Equity Rating Key Equity rating dispersion and banking relationships

Buy: Based on a current 12- month view of total share-holder return (TSR = percentage change in share price from current price to projected target price plus pro-jected dividend yield ) , we recommend that investors buy the stock. Sell: Based on a current 12-month view of total share-holder return, we recommend that investors sell the stock. Hold: We take a neutral view on the stock 12-months out and, based on this time horizon, do not recommend either a Buy or Sell.

Newly issued research recommendations and target prices supersede previously published research.

Deutsche Bank AG/Hong Kong Page 67 27 May 2019 Software & Services China E-commerce

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Deutsche Bank AG/Hong Kong Page 71 David Folkerts-Landau Group Chief Economist and Global Head of Research

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