Wednesday, June 28, 2017

User/Subscriber Economics: An Alternative View of Uber's Value

In the week since I posted my Uber valuation, I have received many suggestions on what I should have done differently in the valuation, with many of you arguing that I was being a over optimistic in my forecasts of total market, market share and margin improvements and some of you positing that I was too pessimistic. I don't claim to have any certitude about these numbers but the spreadsheet that I used to value Uber is an open one, and you are welcome to convert your suggestions into valuation inputs and make the valuation your own. In just the last few days, though, I have been watching an argument unfold among people that I respect. about whether the reason for my low valuation for Uber is that I am using a DCF model, with the critics making the case that valuing a company based upon its expected cash flows is an old economy framework that will not yield a reasonable estimate of value for new economy companies, driven less by infrastructure investments and returns on those investments, and more by user and subscriber economics.  I have long argued that DCF models are much more flexible than most people give them credit for, and that they can be modified to reflect other frameworks. So, rather than deflect the criticism, I will try to build a user based model to value Uber and contrast with my conventional valuation.

Aggregated versus Disaggregated Valuation
If you are doing an intrinsic valuation, the principle that the value of a business is the present value of the expected cash flows from that business, with the discount rate adjusted for risk, cannot be contested. That is true for any business, manufacturing or service, small or large, old economy or new economy. Since that is what a discounted cash flow valuation is designed to do, I have to believe that what critics find objectionable in my Uber DCF model is not with the model itself but in how I estimated the cash flows for Uber, and adjusted for risk. I followed the aggregated model for discounted cash flow valuation where I estimated the cash flows to Uber as a company, starting with its revenues and working through the consolidated expenses and total reinvestment each year and discounted these cash flows at a cost of capital that I estimated for the entire company. Along the way, I had to make assumptions about a total market that Uber would go after, the market share that I expect the company to get in that market and the operating margins in steady state. 

Disaggregated Valuation
Value is additive and you can value any company on a disaggregated basis, breaking it down into different divisions/businesses, geographical areas or by units:
  • Business Units: In a sum of the parts valuation (SOTP), you can break a multi-business company into its individual business units and value each unit separately.  I have a paper where I describe the process of doing a SOTP valuation, using United Technologies, a conglomerate, as my example. If that SOTP valuation is much higher than the value that the market attaches to the company, you may very well find an activist investor targeting the company for a break up. 
  • Geographical Groupings: When valuing a multinational, you can break the company's operations down geographically and value each geographical grouping (Asia, Latin America, North America, Europe) separately, not only using different assumptions about growth and risk in region but even different currencies for each region. 
  • Unit-based Valuation: More generally, when valuing any company, you can try to value it on a unit-basis, building up to its value by valuing each unit separately and then aggregating across units. Thus, a pharmaceutical company can be valued by taking each of the drugs that are in its portfolio, including those in the pipeline, and valuing that drug based upon its cash flows and risk and then adding up the values across the entire portfolio. A retail business can be valued by valuing individual stores and adding up the store values and a subscription-based company can be valuing by valuing a subscription and multiplying by the number of subscriptions, current and forecasted.
I may be misreading the critics of my Uber valuation but it seems to me that some of them, at least are making the argument it is better to value Uber, by valuing an individual Uber user first, and then scaling the value up to reflect not just the number of users that Uber has today (existing users) but also new users it expects to add in the future. 

Aggregated versus Disaggregated Valuations: Weighing the Trade offs
Valuation on a disaggregated basis allows you to be much more flexible in your assumptions, allowing them to vary across each grouping but there are four reasons why you seldom see them practiced (or at least practiced well) in company valuation.
  1. Law of large numbers: As companies get larger and more diverse, there is an argument to be made that you are better off estimating on an aggregated basis rather than a disaggregated one. The reason is statistical. To the extent that your estimation errors on a unit basis are uncorrelated or lightly correlated, your estimates on an aggregated level will be more precise than the unit-based estimates. For example, you will have a much better chance of estimating the aggregate revenues for Pfizer correctly than you do of estimating the revenues of each of its dozens of drugs.
  2. Information Vacuums: Information on a disaggregated basis is difficult to get for individual businesses, geographies, products or users, if you are an investor looking at a company from the outside. If you are doing your valuation from inside the company (as an owner or venture capitalist), you may be able to get this information, but as you will see with my Uber user valuation, even insiders will face limits.
  3. Missing Value Pieces: When valuing a company on a disaggregated business, it is easy to overlook some items that are consequential for value. In sum of the parts valuation, for instance, analysts are so caught up in estimating the values of individual businesses that they sometimes forget to value "corporate costs", which can be a multi-billion drag on value.  
  4. Corporate Structure: There are some items that are easier to deal with at the aggregate level, because that is where they affect the business. Thus, you can model when taxes come due and the effect of losses easier when you are valuing an aggregated business than when you are valuing it on a disaggregated level. Similarly, if you are concerned about legal penalties or corporate governance, these are better addressed at the aggregated level.
It is true that aggregation comes with costs, starting with the blurring of differences across disaggregated units (business, geographies, products, users) as well as the missing of competitive advantages that apply only to some units of the business and not to others. It is also true that using an aggregated valuation can result in a process that is disconnected from how the owners and managers at user-based companies think about their companies and thus cannot help them in managing these companies or valuing them better.

User Based Valuation
Now that we have laid out the pluses and minuses of aggregated versus disaggregated valuation, let us think about how you would construct a disaggregated valuation of a company that derives its value from users or subscribers. In general, the value of such a company can be written as the sum of three components:
Value of user-based company = Value of existing users + Value added by new users - Value drag from corporate expenses

1. Valuing Existing Users
The key step in a user-based valuation is estimating the value of a user and that value is a function of many variables: the cash flows that you are currently generating from a typical user, the length of time you expect that user to use your product or service, your expectations of how much growth you can expect in cash flows from a user over time and the uncertainty that you feel about all of these judgments:

Consider the implications that emerge from this simple framework:
  1. The value of a user increases with user stickiness and loyalty (captured in the expected lifetime of a user and the annual renewal rate).
  2. The value of a user is directly proportional to the profitability of that user (captured as the difference between the revenues from that user and the cost of servicing that user). 
  3. The value of a user is directly proportional to the growth that you can generate in profits over time, by either getting the user to use more of your product or service or coming up with other products or services that you can sell that user. 
  4. The value of a user decreases as you become more uncertain about future cash flows from that user, with that uncertainty being a function of the revenue model that you use and the discretionary nature of the product or service. A subscription-based model, where users agree to pay a fixed amount every period, will generally be less risky and more valuable than a transaction-based model or an advertising-based model, that delivers the same cash flows. A product or service that delivers a necessity (transportation) is less risky than one that meets a more discretionary need (travel). 
If you can value a user, you can then estimate the value of an existing user base, by multiplying the value/user by the number of existing users. If you have multiple types of users, with perhaps different revenue models for each, as is the case with LinkedIn's premium and regular members, you can value each user group separately. 

Value Added by New Users
The second segment of value is the value added by new users that you expect to see added in the future. To estimate this value, you can start with the value per user from the last section but you have to net out the cost of acquiring a new user, which can take the form of advertising, introductory discounts and/or infrastructure investments to enter new markets. That net value added by a new user  (value per user minus cost of acquiring a user) then has to be multiplied by the number of new users that you expect to add each period and brought back to the present, adjusting for both the risk in the cash flows and the time value of money.

Again, I will agree that this is simplistic but consider the common sense implications:
  1. The value added by a new user increases with the value of a user, estimated in the last section. A strategy of going for fewer and more intense users may create more value than one with more and less engaged users, a warning that pursuing user growth at any cost can be dangerous for value.
  2. The value added by a new user decreases as the cost of adding users increases. That cost will be a function of the competitiveness of the business (increasing as competition increases) but also of networking effects. If you have strong networking effects, the cost of adding new users will decrease as you accumulate new users, thus creating a value accelerator for your business.
  3. The value added by a new user decreases as you become more uncertain about user growth. That uncertainty will be a function of competition and whether the technology that you have built your product or service on is sustainable.
Corporate Expenses and Value
To get from user value to the value of the business, you have to bring in the rest of the company into your analysis. To the extent that you have expenses that are unrelated to servicing existing users or adding new ones, i.e., corporate expenses, for lack of a better term, you have to compute the value of these expenses over time and reduce your value as a company by this amount:

While at first sight, this item may look like wasteful that should be eliminated, it represents both a danger and an opportunity for young companies. It is a danger to the extent that bloated corporate expenses can drag a company's value down, but it can be an opportunity insofar as it is at the basis of economies of scale. If corporate expenses represent necessary expenses to keep a business going, and they grow at a rate much lower than the growth rate in users and revenues, you will see margins improve quickly as a company scales up.

Valuing Uber: A User based Model
Can Uber be valued using a user-based model? Yes, but it will require assumptions about users that are, at best, tentative and at worst, based upon little information. While I will attempt with the limited information that I have on Uber to do a user-based valuation, I will leave it to someone who has access to more information than I do (a VC invested in Uber or an Uber manager) to tweak the numbers to get better estimates of value.

Deconstructing the Financials
The numbers that we have on Uber's operations are minimalist, reflecting both its standing as a private company and its general secretiveness. In 2016, according to the financials that Uber provided to a Bloomberg reported, Uber reported $20 billion in gross billings, $6.5 billion in net revenues (counting all revenues from UberPool) and a loss of $2.8 billion (not counting the $1 billion loss on the China operations). According to other reports, Uber had about 40 million users at the end of 2016, up from 24 million users at the end of 2015. Finally, other (dated) reports suggest Uber's contribution margins (revenues minus variable costs) in its most profitable cities ranges from 3-11% of gross billings and its contribution margin in San Francisco, its longest standing and most mature market, is 10.1%. Bringing in these noisy and diverse estimates together, here are my estimates of user statistics:

These numbers are stitched together from diverse sources and vary in reliability, but based upon my judgments, I break down Uber's operating expenses in 2016 into three categories: to service existing users (48.17%), to get new users (41.08%) and corporate expenses (10.75%); the last estimate is a shot in the dark, since there is no information available on the value. The annual profit from an existing user, based on 2016 numbers, is about $50.50 (Net Revenues - Expense/user) and the  cost of adding a new user is about $238/75, and both will be key inputs in my valuation.

Valuing Existing Users
To value Uber's existing users, I use the framework developed in the last section, in conjunction with the estimates that I obtained from the limited financial information provided by Uber. I valued existing users, assuming four additional parameters: a lifetime of 15 years for users, an annual renewal likelihood of 95%, a compounded growth rate of 12% in annual revenues from users expanding their user of Uber services and a growth rate of 9.9% a year in annual user servicing expenses (on the assumption that 80% of the servicing cost is variable). Assuming a cost of capital of 10% (in the 75th percentile of US firms), the resulting value per user and the overall value of existing users is shown below:
Download spreadsheet
The value per existing user is about $410 and the overall value of Uber's 40 million existing users is $16,412 million. Not surprisingly, this value is sensitive to user stickiness (as measured by user lifetime) and user growth potential (as measured by the growth rate in annual revenues):

In a market where investors swoon at user numbers, this table makes an obvious point. Not all users are created equal, with more intense, sticky users being worth a great deal more than transient, switching users.

Value Added by New Users
To estimate the value added by new users, I start with the value per user (estimated in the last section to be $410), which I grow at the inflation rate to get expected value per user over time, and use the cost of acquiring a new user from 2016 (about $240/user). Assuming a growth rate of 25% a year for the next five years, 10% between years six and ten and overall economic growth after year ten, I estimate the value added by new users over time. (With those growth rates, I more than quadruple the number of users over the next ten years to 164 million.) In coming up with value, I assume that new user growth is more uncertain than the value created by existing users, and use a 12% cost of capital (at the 90th percentile of US firms) to get today's value.
Download spreadsheet
The value added by new users, based upon my estimates, is $20,191 million. That value is sensitive to the net value created by each new user (value of a new user minus the cost of adding a new user) and the growth rate in the number of users:
This table illustrates the point made earlier about how some companies will be better off trading off higher value added per user for lower user growth, since there are clearly lower growth/ higher value added scenarios that dominate higher growth/lower value added scenarios in terms of value creation.  

Corporate Expenses and overall Value
The final loose end is the corporate expense component, a number that I estimated (arbitrarily) to be $1 billion in 2016. Allowing for the tax savings that these expenses will generate and assuming a 4% compounded growth rate, well below the 15.16% compounded growth rate in total users, I estimate a value for these corporate expenses (using the 10% cost of capital that I used for existing users):
Download spreadsheet
The value drag created by corporate expenses is about $10,369 million. Bringing together all three components, we get a value for Uber's operations of $26.2 billion
Value of Uber's Operating Assets:
= Value of Existing Users+  Value added by New Users - Value drag from corporate expenses
= $16.4 billion + $20.2 billion + $10.4 billion = $26.2 billion
Adding the cash balance ($5 billion) and the holding in Didi Chuxing (estimate value of $6 billion) results in an overall value of equity of $37.2 billion for the company (and its equity, since it has no debt):
Value of Uber Equity = Value of Operating Assets + Cash - Debt = $26.2 + $5.0 + $6.0 = $37.2 billion
This is close to the value that I obtained for Uber on an aggregated basis, but that is a reflection of my understanding of the company's economics.

Pricing versus Valuing Users
As you can see, valuing users requires assumptions about users that can be difficult to make. So, how do venture capitalists and other early stage investors come up with per user or per subscriber numbers? The answer is that they do not. Drawing on an earlier post that I had on how venture capitalists play the pricing game, venture capitalists price users, rather than value them. What does that involve? Very simply put, the price per user at Uber, given its most recent pricing of $69 billion and the estimated 40 million users is $1,725/user ($69,000/40).  To make a judgment on whether that number is a high or a low number, you would compare that price to what you the market is pricing a user at Lyft or Didi Chuxing and if naive, argue that the lower the price per user, the cheaper the company. Using the most recent estimates of pricing and users for the five big ride sharing companies, here is what we get:

CompanyMost Recent Pricing (in $ millions)# Users (in millions)Price/User
Uber$69,00040.00$1,725.00
Lyft$7,5005.00$1,500.00
Didi Chuxing$50,000250.00$200.00
Ola$3,00010.00$300.00
GrabTaxi$4,2003.80$1,105.26
If you follow the user valuation in the last section, you can see why this pricing comparison can be dangerous. The aggregate pricing that you get for individual companies reflects not only existing users but also new users, and dividing by the existing users will give you much higher numbers for companies that expect to grow their user base more. Even if every company is correctly priced, you should expect to see users at companies with less cash flows per user, lower user growth, less intense and loyal users and more uncertainty about future cash flows to be priced much lower than at companies with intense and sticky users, with more growth potential.

The Bottom Line
If your argument against using discounted cash flow valuation (at least in the aggregated form that it is usually done) is that you have to make a lot of assumptions, I hope that this process of valuing users brings home the reality that you cannot escape having to make those assumptions. In fact,  the assumptions that you need to make to value a company on a disaggregated basis (based on users or subscribers) are often more involved and complex than the ones that you have to make in an aggregated valuation. That said, I do agree that looking at value on a disaggregated basis can not only give you insights about value drivers but also about questions that you would want to ask (and get answered) if you are thinking about investing in or building a young company whose value is coming from its user or subscriber base. 

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Attachments
  1. Uber User-based Valuation
  2. Uber aggregated DCF
Previous Posts on Uber

Wednesday, June 21, 2017

Uber's bad week: Doomsday Scenario or Business Reset?

Uber just cannot seem to help itself, finding a way to get in the news, and often in ways that leave its image in tatters. You could see this pattern in full display last week, where Travis Kalanick, its founder and CEO took a leave of absence to reinvent himself as Travis 2.0, and David Bonderman, founding partner at TPG and Uber director, had to step down after making a sexist remark at a meeting with Uber employees about countering sexism. Today, Travis made his departure permanent, throwing the company into chaos as the board searches for a replacement. As someone who has been collecting stories almost obsessively about the company since June 2014, this is just the latest in a long string of news events, where Uber has been portrayed as a bad corporate citizen. As with prior episodes, there are many who are writing the company’s epitaph but I would not be in too much of a hurry. This is a company that built itself by breaking rules, and while I believe that the latest controversies will damage Uber, they will not disable it.

Uber: Retracing history
If you are just starting to pay attention to Uber, after the last week, let me start by bringing you up to date with the company. Founded in 2009, by Travis Kalanick and Garrett Camp, in San Francisco as UberCab, and going into operation in 2010, the company has redefined the car service business, making the taxi cab a relic, at least for some segments of the population. Uber’s initial business model, which became the template for the ride sharing business, was a simple one. The company entered the car service business, and did so without buying any cars or hiring any drivers, essentially letting independent contractors use their own cars and operating as match-maker (with customers). That low capital intensity model has allowed the company to grow at an astronomical rate, with almost no large infrastructure or capital investments through much of its life.

My first brush with Uber was in June 2014, when I tried to value the company. While many have since reminded me how wrong I was in my judgment, I have no qualms about repeating the story that I said about Uber at the time and the resulting valuation. Framing Uber as an urban, car-service company with local networking benefits and a low capital intensity model, I valued the company at about $6 billion. In fact, Bill Gurley, a partner at Benchmark Capital and an early investor in Uber, took me to task for the narrowness of my story, arguing that I was missing how much Uber would change the logistics market with his offerings.

Bill was right, I was wrong, and I did underestimate Uber’s growth potential, both in terms of geography and in attracting new users into the car service business. In October 2015, I revisited my Uber valuation and told a more expansive story of the company, incorporating its global reach and the influx of new users, while also noting that the pathway to profitability now faced far more roadblocks (as Didi Chuxing, Ola and GrabTaxi all found investors with open pockets and ramped up the competition). That resulted in a much higher revenue forecast, combined with more subdued operating margins, to yield a value of about $23 billion for the company.

In August 2016, I took another look at Uber, after it exited the Chinese market (the largest potential ridesharing market in the world) ceding the market to Didi Chuxing in return for Uber getting a 20% stake in Didi. I argued that this was a good development, since China had become a money pit for the company, sucking up more than a billion dollars in cash in the prior year. While there was some positive movement on some of my assumptions (slightly smaller losses and continued revenue growth), they were offset by some negative movement in other assumptions, leaving my value at about $28 billion, with almost all of the change in value from the prior year coming from the Didi stake that Uber got in exchange for leaving the China market. These are, of course, my stories about Uber and valuations and they matter little in how Uber is perceived by the market. In fact, there is clear evidence that notwithstanding all of the negativity around the company, investors have consistently pushed up its pricing from $ 60 million in 2011 to $3.5 billion in 2013 to $17 billion in June 2014 to almost $70 billion in the most recent capital round.

Uber: An Operations Update
The problem with Uber is that as a private business, albeit one with a high profile, its financial statements are not public. For much of its life, the only numbers that have been made public about the company have been leaked and my valuations have been based on this leaked information. Early this year, Uber finally departed from the script, partly with the intent of drawing attention away from negative stories about the company, and revealed selected financials for 2016. In particular, it reported that it generated more than $20 billion in gross billings in 2016, doubling its 2015 numbers, and that its share of these billings was $6.5 billion (which represents its net revenues). The latter number is puzzling since the company's stated share of the billings is only 20% (which would have meant only $4 billion in revenues) but part of the difference can be explained by the fact that Uber reported its gross billings from UberPool, its car pooling service, as revenues. The revenue growth has been dazzling but the losses continued to mount as well. Uber reported a loss of $2.8 billion for 2016, but that number would have been worse (closer to $3.8 billion) if losses in its defunct China operations had been counted. Overall, though, like all of its financial disclosures, leaked or otherwise, the number paint a mixed picture of Uber. On the plus side, they show a company growing explosively, adding cities, drivers and gross billings as it goes along. On the minus side, you are not seeing the rapid improvements in margins that you would expect to see as a company scales up, if it has economies of scale. 

One reason why losses at Uber have continued to mount, even as revenues rise, is that the competition has not cooperated in Uber's quest for world domination. Rather than be intimidated by the Uber presence and capital advantage, some competitors (like Lyft) have adapted and narrowed their focus to markets, where they can compete. In fact, it is ironic that Lyft, which has long been viewed as the weaker competitor, reported an increase in market share in the US ride sharing market in 2016 and may be first to turn a profit in this business. Others, like Didi Chuxing, have attacked Uber's strength with strength, showing the capacity to raise capital and burn through it just as fast and recklessly as Uber has. Still others, like Ola, have played to local advantages to establish a beachhead against Uber. If Uber's original intent was to use shock and awe to wipe out its competition and emerge as the only player standing, it will have to rethink its plans.

The final leaked reports from the first quarter of 2017 seem to offer some glimmers of hope for Uber, as net revenues continued to increase (rising 18% from the prior quarter's numbers to 3.4 billion) and losses shrunk to $708 million from the $991 million in the prior quarter. Uber optimists found reasons to celebrate in these numbers, arguing that the much awaited margin improvement is now observable, but I would hold off until we not only get fuller financials but also are able to see how much the company paid out in stock based compensation. Using the same indefensible practice that other technology companies have adopted, Uber reports its profits (or in its case, its losses) before stock based compensation.

Uber: The Extracurricular Activity
With Uber, it has never just been about the numbers, because the company finds a myriad of ways to get in the news. Early on its life, some of this was by design, especially when the news stories were about the company evading rules and regulations to offer service in a city, since it burnished the company's reputation for getting things done first and worrying about the rules afterwards. In the last few months, it looks like the news cycle has spun out of Uber's control and that the stories have the potential, at least, to do real damage.
  1. The Google/Waymo Legal Tangle: Uber has not been shy about its desires to one day have self driving cars be its vehicles of choice, increasing investment needs in the business and potentially profit margins. The problem with this strategy it that it has brought Uber head to head against Google, a player with not only a head start in this business but also pockets so deep that it make's Uber's access to capital look paltry. That is perhaps why Uber announced with fanfare that it had hired Anthony Levandowski, a key player on the Google Waymo team, to lead its self driving car project. Any positive payoff from this announcement has been more than erased by subsequent developments, starting with Google accusing Mr. Levandowski of stealing proprietary information and suing Uber for being complicit in the deception,  and with Uber folding, by firing Mr. Levandowski. I am not sure how far this has set Uber back in the driverless car business, but it certainly could not have helped.
  2. Travis YouTube Meltdown: You would think that someone with Travis Kalanick's tech savvy would know better, but his public confrontation with an Uber driver about whether Uber was squeezing drivers was recorded and went public. While this was a small misstep, relative to Uber's much bigger public relations fiascos, the incident reinforced the view among some that Kalanick was too impetuous and immature to be the CEO of a high profile company.
  3. Sexism and Boorishness: The stories about boorish behavior at Uber have been around a long time, and for a while, the company seemed to not just ignore these stories but feed off them. In the last few months, the stories acquired a darker edge with Susan Fowler, an ex-Uber engineer, writing about sexual harassment during her tenure at the company and the unwillingness of the company to do anything about it.  Susan Fowler's chronicling of sexism at Uber had consequences, since the company hired Eric Holder and Tammy Albaran  to look at corporate behavior and culture. Their report not only contained a listing of Uber's cultural problems but also included forty seven recommendations on how Uber could create an inclusive workplace, leading off with the one that Uber's board of directors "should evaluate the extent to which some of the responsibilities that Mr.Kalanick has historically possessed should be shared or given outright to other members of senior management".
The Covington report could not be ignored and the last week was consequential. Travis Kalanick announced that he was taking a break from his role as CEO "to work on Travis 2.0 to become the leader that this company needs and that you deserve". It was in a follow-up meeting with Uber employees that Arianna Huffington chaired, with the intent of making Uber a more welcoming environment for women, that David Bonderman quipped about how having more women as directors would make it "much more likely there’ll be more talking" at meetings. Talk about being stone deaf!

What now?
In a post from long ago, I talked about how news events can alter valuations by affecting the stories that you tell about companies and classified these story alterations into three groups:
  • In a story break, you learn something about a company that renders your story moot and makes your valuation irrelevant (perhaps making it zero). This is the take that some have taken with Uber, when they have argued that the most recent news stories have doomed the company by breaking its story.
  • In a story change, the news that you acquire can lead to you significantly expanding or contracting the story that you were telling about the company, with the former increasing value and the latter reducing it. My story for Uber dramatically expanded from the urban, car service company, with a value of $6 billion in June 2014, to a global logistics company facing challenges in turning revenues to profits, with a value of $23 billion, in September 2015.
  • In a story shift, your basic story stays unchanged but with shifted contours. With Uber, that is what transpired, at least for me, between September 2015 and September 2016, where notwithstanding all of the news about the company, the story remained mostly unchanged, with perhaps higher revenue growth and lower profitability offsetting each other to leave value unchanged at about $25 billion.
So, are the events of the last few months at Uber a story break (which would be catastrophic for its business and value), a story change (where Uber will continue to operate but with much more restraint in going for growth) or just a story shift (where after a few bumps and bruises, the company will continue on its current path)? To answer this question, you have to look how the different constituent groups, that are key to the company's pathway to profits, will react to these latest news stories. On the operations side, there are the regulators, who set the entry and operating rules in the cities that Uber operates in, the drivers who provide the life blood for the ride sharing operations and the customers, who choose to uber rather than use their own cars, mass transit or cabs. On the business side, there are the managers, from the top levels down to middle management, who will chart the future growth map for the company, and the engineers and technical staff, who make it a functional company. On the financing side, there are the venture capitalists who provided the initial capital for the company to go from start up to operations and the public equity investors (mutual funds and sovereign funds). Each of these groups has the potential to alter the Uber story and thus its value:
The doomsday scenario is embedded in this picture. For this crisis to take Uber down, millions of Uber customers will have to delete their apps, droves of Uber drivers will quit, regulators will rescind permissions already granted to operate in cities, Uber managers will be paralyzed, engineers will refuse to work for the company and investors (both venture capital and public equity) will not only cut off access to fresh capital and mark down their existing investments. Could these events unfold? It is possible, but unlikely, because each of these groups, I think, has too much to lose, if Uber implodes:
  • Customers use Uber because it is cheap, convenient and quick and I seriously doubt that the corporate culture makes it even to the top ten list of considerations for most customers. Remember that the much publicized #DeleteUber movement a few months ago resulted in about 200,000 people deleting the app, about 0.5% of Uber's 40 million users. When moral arguments conflict with basic economics, economics almost always wins, and I seriously doubt that Uber will face much of a customer backlash.
  • Without its drivers, there would be no Uber but of all of the constituent groups, drivers are likely to have the fewest delusions about the company, since they have been at the receiving end of its ruthless competitiveness. Given their need to make an income, it is both unfair and unrealistic to expect a significant number of drivers to stop driving for Uber just because of recent news stories, especially since most of these stories reaffirm what the drivers have always believed about the company.
  • It is true that Uber has handed regulators another cudgel to beat them with and perhaps use as an excuse for crimping their operations, but given how ineffective regulators have been in slowing the company down, especially in the fact of backlash from Uber customers, I don't see the recent news changing the dynamics by enough to make a difference.
  • On the managerial front, several news stories over the last week suggest that while Travis Kalanick was away on his reinvention mission, the company would be run by a committee of thirteen lieutenants (the people reporting to Kalanick), not a good development, especially when you have to make decisions quickly, but since these are people who were all hand picked by Kalanick, and are therefore more likely to think alike than disagree, it may work. This morning's news story that Kalanick had quit as CEO does create some uncertainty about future direction, which will not be resolved until a new CEO is hired.
  • Susan Fowler, the author of the blog post that led Uber to their current woes, was an engineer at Uber and she indicates that Uber's actions resulted in female engineers fleeing the company, dropping from 25% to less than 3% of the engineering workforce.  There is the danger that Uber's environment is viewed as so toxic that engineers will refuse to work for the company and that could be devastating for the company. While I think that this will weigh, at least in the near term, on Uber's capacity to attract investors, there will be enough engineers who will still be swayed by the company's resources and the excitement of working on the next big thing in sharing economy.
  • The investors (venture capitalists and public investors) who seeded this company clearly have the most to lose (in potential profits) from the company imploding and the desire to preserve capital will lead them to do whatever needs to be done to save the company. Consequently, it is extremely unlikely that they will abandon their investments, just because of public outrage, or stop providing more capital to the firm, if the failure to do so is a complete loss in value. In fact, I believe that Kalanick's resignation today was prompted by investor pressure to move on; they have too much money at stake for them for them to let personal friendship or loyalty get in the way. That said, these investors play the pricing game and much of how investors will react will depend on what the pricing is for the next round of financing. If that happens at a price greater than the most recent round, all will be forgiven and investors will view this episode as a bump in the road to one of the most lucrative IPOs of all time. If not, and this is the biggest risk that Uber faces, you can see a shrinking story (and value) for the company.

The bottom line is that I don't see the events as story breaks. There is the possibility that it is a story change, but that new story cannot be told until we find out who will head the company. For the moment, my story for Uber is mostly unchanged from September 2016 with two shifts: there is now a change, albeit a small one (5%), that the company could fail and I believe that these events have increased the likelihood that Uber will have to follow a more conventional business path of treating drivers as employees (lowering target operating margins). The resulting valuation is below:
Download spreadsheet
The value that I attach to the operating assets stays at the $25 billion that I estimated in September 2015 and 2016, with the additional value of close to $11 billion coming from cash on hand and the Didi Chuxing stake.  Could the new CEO affect this value? Yes, and here is why. Uber's value requires that the company continue to be audacious in its reach for new markets, aggressive in challenging competition and willing to be dependent on new capital for growth. If, as some news stories suggest, Uber's directors are thinking of playing it safe and hiring a corporatist and a rule follower, you may need to reassess the story to a safer, smaller one, delivering less value. This is still a company that needs a visionary CEO, but one with a little more self-restraint than Travis Kalanick.  Good luck with that!

In Closing
My conclusion is that the Uber's value, notwithstanding the sturm und drang of the last week, is intact but at a number that is far lower than investors have priced it at recently. The effect of the last week may be to bring the pricers back to earth, by reminding investors that there is a long way to go for Uber to convert potential to profits. Prior to these news stories, Uber was a rule breaking company with a business model that delivered revenue growth but offered a very narrow path to profitability. After these news stories, the story remains the same but Uber has just made its narrow path even narrower and much rests on who will head the company on this path.

YouTube video

Blog Posts on Uber
  1. A Disruptive Cab Ride to Riches (June 2014)
  2. Possible, Plausible and Probable: Big Markets and Networking Effects (July 2014)
  3. Up, Up and Away: A Crowd Valuation of Uber (December 2014)
  4. On the Uber Rollercoaster: Narrative Tweaks, Twists and Turns (October 2015)
  5. The Ride Sharing Business: Is a Bar Mitzvah moment coming? (August 2016)
Uber valuation spreadsheets
  1. Uber valuation (June 2014)
  2. Uber valuation (September 2015)
  3. Uber valuation (August 2016)
  4. Uber valuation (June 2017)


Tuesday, June 6, 2017

A Tale of Two Markets: Politics and Investing!


"It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way.” That Charles Dickens opening to The Tale of Two Cities is an apt description of financial markets today. While disagreement among market participants has always been a feature of markets, seldom has there been such a divide between those who believe that we are on the verge of a massive correction and those who equally vehemently feel that this is the cusp of a new bull market, and between those who see unprecedented economic and policy uncertainty and market indicators that suggest the exact opposite. Is one side right and the other wrong? Is it possible that both sides are right? Or that both sides are wrong?

The Divergence
The investor divide is visible, and sometimes dramatically so, in almost every aspect of markets, from risk indicators to fund flows to consumer behavior.

1. Risk on? Risk off?
Do we live in risky or safe times? It depends on who you ask and what indicator to look at. Over the last two decades, the VIX (Volatility Index) has become a proxy for how much risk investors see in  equity markets and the graph below captures the movement of the index (and a similarly constructed index for European stocks) over much of that period:
VIX: S&P 500, Euro VIX: Euro Stoxx 50
Last year, the volatility measures in both the US and Europe not only took Brexit and the Trump election in stride but they have, in the months since the US presidential elections, continued their downward move, ending May 2017 at close to historic lows.
Lest you believe that this drop in volatility is restricted to stocks, you see similar patterns in other measures of risk including treasury yield volatility (shown in the graph) and in corporate bond volatility. This volatility swoon is also not restricted to the US, since measures of global volatility have also leveled off or decreased over the last few months. In fact, the volatility in currency movements has also dropped close to all-time lows. 

In sum, the market seems to be signaling a period of unusual stability. That is at odds with what we are reading about economic policies, where there is talk of major changes to the US tax code and trade policies, signaling a period of high volatility for global economies. The economic policy uncertainty index, is an index constructed by looking at news stories, CBO lists of temporary tax code provisions and disagreement among economic forecasters, has been sending a very different signal to the market than the market volatility indices:

In the months since the election, the indices have spiked multiple times, breaking through records set during the 2008 crisis. In short, we are either on the cusp of unprecedented stability (at least as measured with the market volatility indices) or explosive change (according to the economic policy indices).

2. Funds in? Funds out?
The ultimate measure of how comfortable investors feel about risk is whether they are putting money into stocks or taking them out and fund flows have historically been a good measure of that comfort. Put simply, if investors are wary and risk averse about an asset class or market, you should expect to see money flow out of that market and if they are sanguine, you should see money flow in. In the graph below, we look at fund flows into equity, bond and commodity funds, by month, from the start of 2016 to the April 2017:
Source: Investment Company Institute
More money has flowed into both equity and bond funds, on a monthly basis, since November 2016 than in the first ten months of 2016.  While the fund flow picture is consistent with the drop in volatility that you see across the market-based risk measures, there are discordant notes here as well. First, and perhaps least surprisingly, the perennial market bears have become even more bearish, with concerns about macroeconomic risk augmenting their long-standing concerns about stocks trading at high PE ratios. Second, there are big name investors who are cautioning that a market correction is around the corner, with Jeff Gundlach being the latest to argue that it is time to sell the S&P 500 and buy emerging market stocks. Finally, there is some evidence that money is leaving US stocks, with the Wall Street Journal reporting that money going into US stocks is at a 9-year low, while inflows into European stocks hit a five-year high.

3. Corporate and Business Behavior
Ultimately, risk does not come from market perceptions or newsletters but is reflected in consumer spending and business investment. On these dimensions as well, there is enough ammunition for both sides to see what they want to see. With consumer confidence, the trend lines are clear cut, with consumers becoming increasingly confident about both their current and future prospects:

That confidence, though, is not carrying through into consumer spending, where the numbers indicate more uncertainty about the future:

While consumer spending has increased since November, the rate of change has not accelerated from growth in prior years. You can see similar divergences between confidence and spending numbers at the business level, with business confidence up strongly since November 2016 but business investment not showing any significant acceleration.  In short, both consumers and businesses seem to be feeling better about future prospects but they don't seem willing to back up that confidence with spending.

The Diagnostics
So, how do we go about explaining these stark differences between different indicators? Has risk gone up or has it gone down in the last few months? Is money coming into stocks or is it leaving stocks? Why, if consumers and businesses are feeling better about the future, are they not spending and investing more? There are four possible explanations and they are not mutually exclusive. In fact, I believe that all four contribute to the dichotomy.
  1. Markets have become inured to crises: The last decade has been one filled with crises, in different regions and with different origins, with each one described as the one that is going to tip markets into collapse. Each time, after the debris has cleared, markets have emerged resilient and sometimes stronger than they went in. It is possible that investors have learned to take these market shocks in stride. Like the boy who cried wolf, it is possible that market pundits are viewed by investors as prone to hysteria, and are being ignored.
  2. Disagreement about economic policy changes/effects: It is also possible that economic pundits and investors are parting ways on both the likelihood of economic policy shocks and/or the consequences. On economic policy changes, the skepticism on the part of investors can be explained by the fact that governments across the globe seem to be more interested in talking about making big changes than they are in making those changes. On the effects of changes, the logic that policy uncertainty leads to economic uncertainty which, in turn, causes market uncertainty is being put to the test as governments and central banks are discovering that policy changes, on everything from interest rates to tax rates, are having a much smaller impact on both economic growth and investor behavior than they used to, perhaps because of globalization. 
  3. Macro to Micro Risk: One of the residual effects of the 2008 crisis was an increase in correlation across stocks, with the proportion of risk attributable to market risk in individual stocks rising, relative to firm-specific risk, with that effect persisting into 2016.  Since November 2016, the correlation across stocks has dropped, as investors try to assess how new policies on taxes and infrastructure will help or hurt individual stocks.and this may explain the drop in the VIX, even as individual stocks are perhaps getting riskier.
  4. Politics first, analysis later: It is no secret that we live in partisan times, where almost every news story is viewed through political lens. Why should financial markets be immune from political partisanship? I have seen no research to back this up, but my very limited sampling of investor views (on politics and markets) indicates a convergence of the two in recent months. Put simply, Trump supporters are more likely to be bullish on stocks and confident about the future of the economy, and Trump opponents are more likely to be bearish about both stocks and the economy. Both sides see what they want to see in news stories and data releases and ignore that which does not advance their theses.
So, who is right here? I think that both sides have reasonable cases to make and both have their blind spots. On crisis weariness, it is true that market watchers have been guilty of hyping every crisis over the last decade, but it is also true that not all crises are benign and that one of them may very well be the next "big one". On economic policy changes and effects, I am inclined to side with those who feel that the powers of governments and central banks to guide economies is overstated but I also know that both entities can cause serious damage, if they pursue ill-thought through policies. On the political front, I won't tip my hand on my political affiliations but I believe that viewing economics and markets through political lens can be deadly for my portfolio. 

My Sanity Check:  Equity Risk Premiums
As you can see, it is easy to talk yourself on to the cliff or off the cliff but after all the talking is done, it remains just that, talk. So, I will fall back on a calculation that lets the numbers do the talking (rather than my biases) and that is my computation of the implied equity risk premium for US stocks. On June 1, 2017, as I have at the start of every month since September 2008 and every year going back to 1990, I backed out the rate of return that investors can expect to make on the S&P 500, given where it was trading at on that day (2411.8) and expected cash flows from dividends and buybacks on the index in the future (estimated from the cash flows in the most recent twelve months and consensus estimates of earnings growth over the next five years in earnings). Given the index level and cash flows on June 1, 2017, the expected annual return on stocks (the IRR of the cash flows) is 7.50%. Netting out the 10-year treasury bond rate (2.21%) on June 1 yields an implied equity risk premium of 5.29%.
Download spreadsheet
To put this in perspective, I have graphed out the implied equity risk premiums for the S&P 500, by year, going back to 1960.
Download historical data
To the extent that the equity risk premium is higher than median values over values over the 1960-2017 time period, you should feel comforted, but the market's weakest links are visible in this graphs as well. Much of the expansion in equity risk premiums in the last decade has been sustained by two forces.
  1. Low interest rates: If the US treasury bond rate was at its 2007 level of 4.5%, the implied equity risk premium on June 1, 2017, would have been 3%, dangerously close to all time lows. 
  2. High cash return: US companies have been returning immense amounts of cash in the form of buybacks over the last decade and it is the surge in the collective cash flow that pushes premiums up. As earnings at S&P 500 companies flattened and dropped in 2015 and 2016, you can argue that the current rate of cash return is not just unsustainable but also incompatible with the infrastructure-investment driven growth stories told by some market bulls.
The first half of 2017 delivered some good news and some bad news on this front. The good news is that notwithstanding rumors of Fed tightening, treasury bond rates dropped from 2.45% on January 1, 2017 to 2.21% on June 1, 2017, and S&P 500 companies reported much stronger earnings for the first quarter, up almost 17% from the first quarter of 2016. The bad news is that it seems a near certainty that Fed will hike the Fed Funds rate soon (though its impact on longer term rates is debatable) and that there is preliminary evidence that companies have slowed the pace of stock buybacks.  The bottom line, and this may disappoint those of you who were expecting a decisive market timing forecast, is that stocks are richly priced, relative to history, but not relative to alternative investments today. Paraphrasing Dickens, we could be on the verge of a sharp surge in stock prices or a sharp correction, entering an extended bull market or on the brink of a bear market, at the cusp of an economic boom or on the precipice of a bust. I will leave it to others who are much better than me at market timing to make these calls and continue to muddle along with my stock picking.

YouTube Video


Attachments

  1. Implied Equity Risk Premium for S&P 500 - June 2017
  2. Historical ERP for S&P 500: 1961-2017