- 1 Technology Primer for Investment Banking
- 2 E-Commerce and Online Shopping
- 3 Traffic, Advertising and Search
- 4 Key Metrics for Internet/Information Technology Companies
- 5 Valuation of Technology Stocks
- 5.1 Sum of the Parts Net Asset Value for Technology Companies
- 5.2 Price/Earnings-Growth for Tech Companies
- 5.3 Share Based Compensation for Technology Companies
- 5.4 Major Chinese Internet Stocks – BATs versus FANGs
- 5.5 High P/E Ratios and Price-to-Sales on Tech Stock Valuation
- 5.6 Stranded International Cash and Effective Taxes
- 5.7 Other Bets – Big Tech Investments in Associates, Subsidiaries and Venture Capital
- 6 Major Developments in Technology
- 7 Related Reading for Technology
Technology Primer for Investment Banking
There are other great technology primers for investment banking elsewhere on the web, so this primer is focused on major technology trends going forward and the companies that will be involved – namely internet companies.
Major prevailing themes in the technology space include artificial intelligence (AI), digitalization and the lessening of physical footprint across various industries, disintermediation, mobile connectivity and the internet of things (IoT) and smart machines.
Major technology firms include:
E-Commerce and Online Shopping
E-Commerce is the purchase and sale of goods online. E-Commerce has grown exponentially every year and will transition from an effective way of doing business to the standard way of doing business. To put into perspective, Alibaba’s China Gross Merchandise Value (GMV) already exceeds Wal-Mart’s.
E-Commerce is segmented into business-to-business (B2B), business-to-consumer (B2C), and consumer-to-consumer (C2C).
B2B – Alibaba
B2C – Amazon, JD.com, Tmall, AliExpress
B2C – Taobao, EBay, Amazon
Business-to-Consumer (B2C) – Online Shopping – TMall, Amazon
B2C entails businesses selling to customers. Companies can sell via their own platforms, but this is not necessarily the core competency of a retail company – so it is often white labeled (they have their own store website but the underlying platform is actually a third party’s work) or increasingly sold via platforms such as TMall or Amazon.
TMall is quickly realizing its vision to be a fully digital mall, signing up marquee names every year to set up shop online. Some companies with the largest volumes on TMall include Huawei, UNIQLO, Xiaomi and Suning. TMall is also looking to pick up more luxury brands such as Louis Vuitton.
Until now, grocers have been relatively immune to the retail disruption. However, concepts such as Amazon Fresh (and Amazon’s purchase of Whole Foods) and TMall Supermarket are looking to take over this space as well – in the end, there is no beating data driven, centralized planning and a superior logistics network for traditional grocers. TMall Supermarket will look to deliver fresh produce within a guaranteed number of hours.
For B2C platforms such as AliExpress, TMall and Tencent-backed JD.com, the current strategy is growth given the size of the market. Even though online transaction volumes are unprecedented relative to US peers, there is still massive customer value by increasing market penetration, as there are still a lot of people who do not shop online, as well as via increasing the average spend per customer.
Accordingly, Alibaba and competitors have been extremely aggressive in providing subsidies via vendor rebates for special events such as Singles Day – for example, Alibaba will offer rebates for vendors who discount their wares to drive volume for major sales events.
Payments is a developing space and China has the highest penetration globally for mobile payments as they have widely passed over credit card adoption. The smartphone has become an all-purpose device, with many urban centres in China being notoriously difficult for not taking cash. Alipay, Wepay and Apple Pay are quick, traceable and curiously do not serve as a conduit for personal debt.
Retailing Trends Due to B2C E-Commerce
Online shopping has been one of the most dramatic changes that the internet has been a catalyst for. Retailers, especially department stores, were historically considered cash cows by investors with steady cash flows able to comfortably service debt. As such, a lot of retailers have had major debt piles and been private equity darlings for leveraged buy outs due to their cash flow profile.
Major retailers for clothing and electronics are no longer competitive, and while grocers have been relatively protected for now due to the logistical puzzle behind fresh produce not having been tackled in earnest, companies such as RadioShack, BCBGMAXAZRIA, and Toys R Us have gone under – some of them will continue to operate after being restructuring and being purchased at a distressed price, but the trend is clear – a store with client-facing staff, loss prevention officers to address shrink, stockers, rent, overhead and inventory planning cannot compete with a centralized warehouse supported with the data analytics of Amazon or Google if they sell the same product.
The real estate dedicated to retailing has also suffered as struggling retailers default on lease obligations or ask to renegotiate. In high-traffic, class A commercial areas, they have been repurposed or rezoned (to be redeveloped as residential properties). A very interesting trend with companies such as Tesla is where retail outlets are not for sales but for showcasing new product. Instead of making a purchase, you can test the product and ask questions. Nonetheless, for lower quality retail real estate, property prices have fallen immensely (property prices are in a way the present value of future leases).
Retailing is evolving – although there are ample job losses due to retail outlets shuttering, plenty of new jobs are created via the warehousing and storage arms of Amazon and Alibaba. In addition, higher value jobs such as operations and logistics planning for engineers and trend analysis by data scientists appear – the value of human capital becomes greater.
E-Commerce and Logistics – Cainiao and Amazon Warehouses
The scale and various networks that E-Commerce companies must work with to fulfil orders made on their platforms make logistics a key part of their business.
Amazon and Alibaba invest heavily in logistics to optimise their ecommerce platforms to reduce costs and allow for higher volumes.
Alibaba has taken control of a major logistics affiliate, Cainiao, and is ramping up spending to meet growth. According to Alibaba founder Jack Ma, Chinese couriers are expected to handle 1 billion parcels a year in 5-8 years. Cainiao has also outlined its vision to realize delivery anywhere in China within 24 hours and globally within 72 hours.
Cainiao is an interesting addition to Alibaba in strengthening its logistics platform – but Cainiao is not a physical logistics firm – it is a platform that connects logistics firms with shippers. Partners for Cainiao include STO Express, YTO Express, ZTO Express and SF Express. Cainiao optimizes paths and coordinates relationships between these parties, warehouses (that they themselves may control) and pickup stations.
Traffic, Advertising and Search
Traditional advertising in print media and television have been declining steadily. American tech companies have taken all of the advertising revenues with data-driven, targeted approaches that are getting smarter and smarter. For instance, viewers used to be eager to skip Youtube advertisements but are now intrigued by offerings due to the effectiveness of algorithms.
Facebook and Google are advertising giants via their traffic. Google is the dominant search engine across the globe while Facebook is the dominant social networking platform. DAUs, MAUs and total users are a magnitude larger than any other websites while the products are free – essentially, the user is the product.
Google sells ads via their AdWords network, allowing for owners of individual websites to advertise via AdSense. Facebook has ad outreach to its users across all of its channels – Instagram, Messenger and eventually WhatsApp.
Key Metrics for Internet/Information Technology Companies
Traffic – Monthly Active Users (MAUs) and Daily Active Users (DAUs)
MAUs and DAUs are important for all information technologies company but companies who are not yet profitable and even pre-revenue companies will have special attention paid to these numbers.
MAUs and DAUs constitute the monetizable base – so growth in MAUs and DAUs are tracked very closely. MAUs represent the total breadth of outreach while DAUs represent the core base where companies would evaluate the time spent (length of stay) on the platform and monetization capabilities (conversion to profits).
Gross Merchandise Value (GMV)
This figure is the total dollar value of goods sold over a certain time period – usually measured monthly, quarterly and annually – often annually on a last twelve months (LTM) basis. GMV is one of the major metrics that analysts look at when e-commerce companies such as Amazon or Alibaba report earnings – a GMV that beats expectations, especially on the back of major shopping seasons such as Christmas or Golden Week can move the stock substantially.
Keep in mind that GMV is not revenue – the commission that the ecommerce firm charges will be. As such, GMV will not flow directly to cash flow or profits because it depends on how much the company can capture of this GMV. As online shopping penetration across the population increases, investors will be more keen on looking at rising numbers versus profits as companies continue to fight for a larger market share.
This rate is the % of GMV that is converted into sales. Essentially, this is commission for sales over an ecommerce platform or for advertising. The higher the monetization rate the better, and a move up (as measured in basis points) will be taken positively by analysts if it is seen as sustainable.
Monetization rate will be segmented into mobile and desktop to reflect the growing use of mobile devices as the main computer. Previously, mobile advertising was not as widespread or efficient, but these figures are ticking up across the board. If $100 million of GMV is transacted over Sell Side Handbook and SSHB realizes $3 million in commissions, the monetization rate is 3%.
EBITDA Margin for Technology
This is a standard measure of profitability across many industries. For tech, this takes into account the very short asset life of investments leading to high D&A figures, resulting in a good cash flow proxy.
Valuation of Technology Stocks
Technology stocks have the widest assortment of valuation methodologies applied to them. A major reason is that technology is hard to define – is a company a technology company because they conduct most of their business on the internet? Is it a company that has something to do with computers?
Subsegments within technology will vary widely in terms of valuation metrics and multiples as well. For instance, a software company with a mature program and recurring subscriptions is relatively simple to value via a DCF or an EBITDA multiple.
A growth sub-sector within technology may be widely not-profitable and be valued on Price/Sales (technically we should use Enterprise Value to Sales, but given the lack of meaningful debt most analysts will use P/S).
Major internet companies are conglomerates that dabble in ventures across various industries and sub-sectors – as such, a sum-of-the-parts valuation is often used by equity research analysts. Even then, SOTP can be difficult, especially if divisions are opaque.
Sum of the Parts Net Asset Value for Technology Companies
Each division of the tech firm will be valued separately. For instance, Alibaba investors and equity analysts will look at its core business – ecommerce, as well as cloud computing, media and entertainment and its proportionate share of its investments. Similarly, Google’s core business is search, and other divisions will be valued separately.
Usually the core business for internet companies is a cash cow with growing revenues. These will either be valued via a discounted cash flow methodology or a multiple – usually EV/EBITDA or P/E.
Cloud computing will often be valued at price/sales or EV/sales as they are not necessarily major profit generators yet and are fighting for market share that will be the base for profitability later.
Divisions that are more conventionally aligned with other industries will be valued as such.
Afterwards, the value of investments will have to be added to the total assets of the firm. As we allude to below, major internet companies have many investments in other internet and technology companies at various ownership levels.
After subtracting claims by debtholders and adding back cash, we get to a value that is available for shareholders (the Net Asset Value). This is divided by shares outstanding for an appropriate share price.
Google Valuation Example
- Core Search Business: Discounted Cash Flow with 8% WACC and 3% terminal growth rate
- Youtube 7x Price/Sales
- Cloud 9x Price/Sales
- Investments in Other Bets $300 million, $1.6 billion, $500 million
- Subtract Debt
- Add Cash
Alibaba Valuation Example
- Ecommerce Core Business 30x Price/Earnings supported by DCF for sanity check
- Cloud 12x Price/Sales
- Youku and Media – 10x Price/Sales
- Add proportionate share of investments
- Subtract Debt
- Add Cash
Price/Earnings-Growth for Tech Companies
The PEG ratio is the price/earnings ratio divided by the growth rate. Accordingly, if P/E is 20x and the growth rate is 20%, the PEG ratio is 1.0x. PEG is seen as an equalization metric for tech companies, as looking at PE only would result in fast growing companies being punished from a multiple perspective while not accounting for their growth.
Conventionally, a PEG ratio of 1 has been seen as fairly valued – most major tech companies trade above this, but investors have been validated by their superior stock price performance (Tencent/Google).
PEG is more of a secondary or sanity check valuation method.
Technology – in particular, major internet companies and unicorn startups (startups with a valuation over $1 billion) has replaced finance as the most coveted entry level position out of university. High technology is a fiercely competitive space and accordingly, average salaries for programmers and developers is a very large expense.
Due to the large cash requirements of technology companies for research and development (Amazon being most well known for reinvesting almost all operating cash flows), companies will often have a deferred stock based component to their compensation. For instance, a new hire at a well funded tech company from Stanford may receive a $150,000 salary, $25,000 signing bonus, $25,000 year-end bonus and $100,000 in equity. This equity does not vest right away – the employee is obligated to 1) stay (as many precocious programmers may desire to start their own business); and 2) work to the best of his or her ability given the share price appreciation incentive to perform.
The equity compensation may be physically settled, which means that the company will issue shares instead of purchasing them on the open market, meaning that existing shareholders will be diluted.
Technology companies may add back share/stock based compensation to their adjusted EBITDA figures as they are often physically settled/non-cash. From a firm valuation multiple perspective, this makes sense – the company size (the EV) is compared to the cash costs of the firm. However, as an investor, share based compensation is a very real cost because despite the company growing bigger, the relative stake in the company falls.
Two common ways to address this – one, for a DCF, do not add back SBC to free cash flow. Two – model out shares outstanding and solve for the equity value per share.
Major Chinese Internet Stocks – BATs versus FANGs
For the major Chinese internet firms – Baidu, Alibaba, Tencent (BAT), their market dominance is so absolute (covering all connected China) and difficult to scale as a new entrant in the market that they can command a premium due to their impenetrable business “moat”.
Stock market analysts frequently compare BAT to the US FANGs (Facebook, Amazon, Netflix, Google (Alphabet) due to their control over various business models.
However, analysts justify a premium on top of this for BAT stocks due to the intricacies of dealing with the Chinese government. Without the Communist Party of China’s (CPC) sanction, internet companies cannot operate – however, this is not so much a function of economic protectionism as it is conducting business according to the frameworks set based on what is important to the CPC.
For instance, the CPC requires servers to be set up in China and for data collected to be handed over for security purposes. For companies such as Facebook or Google, this may be difficult when there is connectivity between China and jurisdictions with differing rules on privacy – as such, they are unable to penetrate communications and search in Mainland China. However, the BATs benefit from the converse – they are widely able to operate in the US and other major markets.
High P/E Ratios and Price-to-Sales on Tech Stock Valuation
For stocks such as Amazon, a lot of talking heads shun the stock because of a perceived bubble. A recent look on Google Finance (which is just FactSet data), shows a P/E of 281 with the P/E having been in excess of 1000x on occasion.
This is a lazy way of looking at stocks because investors have to look at why profitability is so low when revenues are going up every year. For companies such as Amazon or any other marquee information technology name, most of the cash flow is being reinvested into the business to keep ahead of the competition as well as to fund high growth initiatives. Many of these investments into software and research are immediately expensed or amortized quickly.
If a company has a higher growth rate and return on capital, it makes more sense to reinvest money instead of paying it out as a dividend to investors or sit on cash – both of which offer an inferior return to shareholders. Amazon generates a lot of cash and spends a lot of cash – similar to Google, Microsoft and Alibaba. However, if Amazon stopped reinvesting cash and kept all its cash flows, it would turn a very strong profit for years to come until it lost its competitive advantage.
Just because companies are technology companies does not mean that they deviate from the basic tenets of valuation – when they do, it becomes a bubble like in any other asset class. What is important is the underlying business and a deeper dive into the fundamentals. Amazon is already a derisked story with a business moat – it has an ostensibly unassailable lead in B2C E-Commerce in North America and proven cash flow generation. In comparison, Twitter is not even profitable yet. Snapchat is not even cash flow positive yet, never mind profitable.
P/E ratios are not especially meaningful for information technology companies due to the dynamics of the space and because comparable companies they are weighted against do not have the same business model in the way that a carmaker has in common with another carmaker. Google and Facebook have similarities but are inherently different businesses. Comparing Google and a semiconductor company (which is “tech”) is just stupid.
Stranded International Cash and Effective Taxes
Despite being some of the most profitable enterprises in corporate America, tech firms in this domicile have been known to pay very low effective taxes. For instance, Facebook roughly pays tax on 10% of its earnings while the US corporate tax rate is one of the highest in the developed world.
This is due to tech firms not repatriating a large amount of foreign earnings back into the US and shuffling them into tax havens. The result is very large cash piles that sit on their balance sheets and are reinvested into bonds and other financial assets. US lawmakers have looked at ways to get the cash back into the US economy, with the Trump Administration looking at ways to incentivize repatriation – from a reduced repatriation tax to tax-free repatriation given reinvestment that creates jobs.
From a valuation perspective, this cash pile is already addressed with an EV/EBITDA multiple, but P/E valuations must have a cash adjustment.
Other Bets – Big Tech Investments in Associates, Subsidiaries and Venture Capital
There is no entity better suited to picking the technology winners of tomorrow than the reigning incumbents of the tech world. Google, Amazon, Tencent and Alibaba all have investments in other tech companies. This is sensible from a capital allocation perspective as tech companies eventually get to a point where they can no longer keep growing at the same rate – any company that grows at 20% a year forever is going to end up bigger than the US economy. Once the core niche becomes mature, capital needs to be redeployed in high growth areas elsewhere.
The most removed method is through non-strategic investments through the purchase of shares of a public tech company or a piece of a private tech company.
The next step is through large strategic investments/relationship investments where they can work with the affiliate to realize synergies between the two companies while the bigger tech company has a vested interest in the affiliate’s success.
Given the immense cash generation of a dominant firm in search or e-commerce, mega-tech companies have the luxury of being able to afford propping up cash burning subsidiaries that have revolutionary potential in new frontiers – artificial intelligence, financial technology (fintech), security and data protection, blockchain/payments and the Internet of Things (IoT). Google calls these ventures “moonshots” – unproven technologies that would result in ten-thousand-fold returns on investment upon success.
Tech firms will also usually have venture capital arms across all stages in the company life cycle. Investments made here will be relatively hands off and not recorded as subsidiaries.
From a valuation standpoint, these investments have to be added in via the sum-of-the-parts analysis. For example, if Google’s core business is search and that is valued via a DCF, the subsidiaries (Nest, Waymo) will have to be valued separately. Investments that Google partially owns will have their valuation multipled by Google’s proportional ownership.
Separately, the founders of the mega-cap tech firms may have their own personal VC funds wrapped into their family offices.
Major Developments in Technology
Artificial intelligence is when machines that can learn from their environment and improve their ability to achieve a certain goal.
AI has come to the forefront with Elon Musk and Stephen Hawking mentioning that it is humanity’s greatest opportunity but also an existential threat that can eradicate humanity. Right now, AI is limited in scope but has surprised technology experts in terms of how intelligent machines have become.
Google’s subsidiary DeepMind has prominently showcased its AlphaGo technology as an illustration of how AI can under certain parameters outdo the greatest humans with thousands of years of experience on their side. There is a multitude of literature online documenting AlphaGo’s victory over top Go players, but we will quickly summarize why AlphaGo’s rise was unprecedented.
Computers have long been able to beat the world’s best chess players. This is because the different paths a chess game could go into on an 8 by 8 board given the constraints on the movements of pieces can be entirely addressed via brute force computing power. As such, computers simply have an answer for every scenario and can therefore always win – this is not true artificial intelligence.
Go is a game with possibilities orders of magnitude larger. There is not even close to enough processing power required to “solve” Go. As such, AI had to figure out the game as a human would, something that Go experts did not think of possible for a very long time. AlphaGo and its successors have annihilated the world’s top Go players with a program that learned from its own mistakes playing against itself from scratch. Ke Jie, the world’s number 1 Go player has been incorporating what he has learned from AlphaGo into his play – erasing what was known to be conventional wisdom in the game accumulated from experience over thousands of years.
Of course, if AI was only used to solve board games and puzzles, it would be limited as a commercial enterprise. Although not transferable to everything, AlphaGo algorithms and thinking processes can be applied to real world applications – healthcare, data protection, resource extraction.
Theoretically, this could be groundbreaking in extending lifespans, identifying problems and adding value to society in general. Assuming that this is commercialized, pundits have pointed out successful AI enterprises as multitrillion dollar opportunities.
Mobile Payments and Financial Technology (Fintech)
Payments have changed over the course of humanities – from a barter system to metal coins to paper money to credit cards to online and mobile payments.
China has skipped the plastic altogether and mobile wallets are heavily integrated into every day activity in urban centers to the point where it is a largely cashless society. This removes a lot of friction pertaining to the physical encumbrance of money, fraud and money laundering as the ease of traceability by authorities diminishes transfers as a conduit for illicit activities.
On the financial technology front, applying for insurance or a loan has gone from a week or month long process to a very short term approval cycle via a variety of competitive platforms. Banks themselves save a large physical footprint via the expedited app process while savings can be passed on to consumers.
Additionally, initiatives such as LendingClub have disintermediated banks to a certain extent by allowing for borrowers to borrow at much lower rates and savers to get a much higher interest rate by directly participating in loans.
Automation and Electric Vehicles (EV)
Countries have set out targets to get rid of gasoline fueled cars at certain checkpoints into the future – 2030, 2040, 2050. Not only will electric vehicles become the norm, but the idea is that they will become driverless too – eliminating accidents caused by human error. This is incredible for safety as well as efficiency, as paired with AI optimizing logistical routes, goods and people will be transported safely in the fastest time possible while there is minimal carbon footprint.
Google’s Waymo, Uber, Tencent, Baidu, Tesla and Dyson, as well as traditional carmakers, have been aggressively investing into autonomous vehicle technology.
For smaller package deliveries, drones are also becoming smarter – with airborne delivery making accessing customers without good road infrastructure or in dangerous neighbourhoods where couriers currently do not want to venture to, improving standard of living.