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It's taken me a while to get here, but in this, the last of my ten posts looking at publicly traded companies globally, I look at pricing differences across regions and sectors. I laid out my rationale for looking at pricing in my most recent post on the topic, where I drew a distinction between good companies, good management and good investments, arguing that investing is about finding mismatches between reality (as driven by cash flows, growth and risk) and perception (as determined by the market).

Multiple = Standardized Price

When looking at how stocks are priced and especially when comparing pricing across stocks, we almost invariably look at pricing multiples (PE, EV to EBITDA) rather than absolute prices. That is because prices per share are a function of the number of shares and are, in a sense, almost arbitrary. Before you respond with indignation, what I mean to say is that I can make the price per share decrease from $100/share to $10/share, by instituting a ten for one stock split, without changing anything about the company. As a consequence, a stock cannot be classified as cheap or expensive based on price per share and you can find Berkshire Hathaway to be under valued at $263,500 per share, while viewing a stock trading at 5 cents per share as hopelessly overvalued.

The process of standardizing prices is straight forward. In the numerator, you need a market measure of value of equity, the entire firm (debt + equity) or the operating assets of the firm (debt + equity -cash = enterprise value). If you confused about the distinction, you may want to review this post of mine from the archives. In the denominator, you can scale the market value to revenues, earnings, accounting estimates of value (book value) or cash flows.

As you can see, there is a very large number of standardized versions of value that you can calculate for firms, especially if you bring in variants on each individual variable in the denominator. With net income, for instance, you can look at income in the last fiscal year (current), the last twelve months (trailing) or the next year (forward). The one simple proposition that you should always follow is to be consistent in your definition of multiple.

The "Consistent Multiple" Rule: If your numerator is the market value of equity (market capitalization or price per share), your denominator has to be an equity measure as well (net income or earnings per share, book value of equity. For example, a price earnings ratio is consistent, since both the numerator and denominator are equity values, and so is an EV to EBITDA multiple. A Price to EBITDA or a Price to Sales ratio is inconsistent, since the numerator is an equity value and the denominator is to the entire business, and will lead to conclusions that are not merited by the fundamentals.

Pricing â A Global Picture

To see how stocks are priced around the world at the start of 2017, I focus on four multiples, the price earnings ratio, the price to book (equity) ratio, the EV/Sales multiple and EV/EBITDA. With each multiple, I will start with a histogram describing how stocks are priced globally (with sub-sector specifics) and then provide country specific numbers in heat maps.

PE ratio

The PE ratio has many variants, some related to what period the earnings per share is measured (current, trailing or forward), some relating to whether the earnings per share are primary or diluted and some a function of whether and how you adjust for extraordinary items. If you superimpose on top of these differences the fact that earnings per share reported by companies reflect very different accounting standards around the world, you can already start to see the caveats roll out. That said, it is still useful to start with a histogram of PE ratios of all publicly traded companies around the world:

Damodaran Online (data)

Note that of the 42,668 firms in my global sample, there were only 25,493 firms that made it through into this graph; the rest of the sample (about 40%) had negative earnings per share and the PE ratios was not meaningful. While the histogram provides the distributions by regional sub-groups, the heat map below provides the median PE ratio by country:

Live Heat Map

If you go to the live heat map, you will also be able to see the 25th and 75th quartiles within each country, or you can download the spreadsheet that contains the data. I mistrust PE ratios for many reasons. First, the more accountants can work on a number, the less trustworthy it becomes, and there is no more massaged, manipulated and mangled variable than earnings per share. Second, the sampling bias introduced by eliminating a large subset of your sample, by eliminating money losing companies, is immense. Third, it is the most volatile of all of the multiples as it is based upon earnings per share.

Price to Book

In many ways, the price to book ratio confronts investors on a fundamental question of whether they trust markets or accountants more, by scaling the marketâs estimate of what a company is worth (the market capitalization) to what the accountants consider the companyâs value (book value of equity). The rules of thumb that have been build around book value go back in history to the origins of value investing and all make implicit assumptions about what book value measures in the first place. Again, I will start with the histogram for all global stocks, with the table at the regional level imposed on it:

Damodaran Online (data)

The price to book ratio has better sampling properties than price earnings ratios for the simple reason that there are far fewer firms with negative book equities (only about 10% of all firms globally) than with negative earnings. If you believe, as some do, that stocks that trade at less than book value are cheap, there is good news: you have lots and lots of buying opportunities (including the entire Japanese market). Following up, letâs take a look in the heat map below of median price to book ratios, by country.

Live Heat Map

Again, you can see the 25th and 75th quartiles in either the live map or by downloading the spreadsheet with the data. Pausing to look at the numbers, note the countries shaded in green, which are the cheapest in the world, at least on a price to book basis, are concentrated in Africa and Eastern Europe, arguably among the riskiest parts of the world. The most expensive countries are China, a couple of outliers in Africa (Ivory Coast and Senegal, with very small sample sizes) and Argentina, a bit of a surprise.

EV to EBITDA

The EV to EBITDA multiple has quickly grown in favor among analysts, for some good reasons and some bad. Among the good reasons, it is less affected by different financial leverage policies than PE ratios (but it is not immune) and depreciation methods than other earnings multiples. Among the bad ones is that it is a cash flow measure based on a dangerously loose definition of cash flow that works only if you live in a world where there are no taxes, debt payments and capital expenditures laying claim on those cash flows. The global histogram of EV to EBITDA multiples share the positive skew of the other multiples, with the peak to the left and the tail to the right:

Damodaran Online (data)

Again, there will be firms that had negative EBITDA that did not make the cut, but they are fewer in number than those with negative EPS. Looking at the median EV to EBITDA multiple by country in the heat map below, you can see the cheap spots and the expensive ones.

Live Heat Map

As with the other data, you can get the lower and higher quartile data in the spreadsheet. As with price to book, the cheapest countries in the world lie in some of the riskiest parts of the world, in Africa and Eastern Europe. China remains among the most expensive countries in the world but Argentina which also made the list, on a price to book basis, drops back to the pack.

EV to Sales

If you share my fear of accounting game playing, you probably also feel more comfortable working with revenues, the number on which accountants have the fewest degrees of freedom. Letâs start with the histogram for global stocks:

Damodaran Online (Data)

Of all the multiples, this should be the one where you lose the least companies (though many financial service companies donât report conventional revenues) and the one that you can use even on young companies that are working their way through the early stages of the life cycle. The median EV/Sales ratio for each country are in the heat map below:

Live Heat Map

You can download more extensive numbers in the spreadsheet. By now, the familiar pattern reasserts itself, with East European and African companies looking cheap and China looking expensive. With revenue multiples, Canada and Australia also enter the overvalued list, perhaps because of the preponderance of natural resource companies in these countries.

Pricing â Sector Differences

All of the multiples that I talked about in the last section can also be computed at the industry level and it is worth doing so, partly to gain perspective on what comprises cheap and expensive in each grouping and partly to look for under and over priced groupings. The following table, lists the ten lowest-priced and highest priced industry groups at the start of 2017, based upon trailing PE:

Multiples by Sector

In many of the cheapest sectors, the reasons for the low pricing are fundamental: low growth, high risk and an inability to generate high returns on equity or margins. Similarly, the highest PE sectors also tend to be in higher growth, high return on equity businesses. I will leave the judgment to you whether any fit the definition of a cheap company. The entire list of multiples, by sector, can be obtained by clicking on this spreadsheet.

One comparison that you may consider making is to pick and multiple and trace how it has changed over time for an industry group. Isolating pharmaceutical and biotechnology companies in the United States, for instance, here is what I find when it comes to EV to EBITR&D for the two groups over time:

You can read this graph in one of two ways. If you are a firm believer in mean reversion, you would load up on biotech stocks and hope that they revert back to their pre-2006 premiums, but I think you would be on dangerous ground. The declining premium is just as much a function of a changing health care business (with less pricing power for drug companies), increasing scale at biotech companies and more competition.

Rules for the Road

Absolute rules of thumb are dangerous (and lazy): The investing world is full of rules of thumb for finding bargains. Companies that trade at less than book value are cheap, as are companies that trade at less than six times EBITDA or have PEG ratios less than one. Many of these rules have their roots in a different age, when data was difficult to access and there were no ready tools for analyzing them, other than abacuses and ledger sheets. In Ben Graham's day, the very fact that you had collected the data to run his "cheap stock" screens was your competitive advantage. In today's market, where you can download the entire market with the click of a button and tailor your Excel spreadsheet to compute and screen, it strikes me as odd that screens still remain based on absolute values. If you want to find cheap companies based upon EV to EBITDA, why not just compute the number for every company (as I have in my histogram) and then use the first quartile (25th percentile) as your cut off for cheap. By my calculations, a company with an EV/EBITDA of 7.70 would be cheap in the United States but you would need an EV to EBITDA less than 4.67 to be cheap in Japan, at least in January 2017.
Most stocks that look cheap deserve to be cheap: If your investment strategy is buying stocks that trade at low multiples of earnings and book value and waiting for them to recover, you are playing a game of mean reversion. It may work for you, but there is little that you are bringing to the investing table, and there is little that I would expect you to take away. If you want to price a stock, you have to bring in not just how cheap it is but also look at measures of value that may explain why the stock is cheap.
If you are paying a price, you are "estimating" the future: When I do an intrinsic valuation (as I did a couple of weeks ago with Snap), I am often taken to task by some readers for playing God, i.e., forecasting revenue growth, margins and risk for a company with a very uncertain future. I accept that critique but I don't see an alternative. If your view is that using a multiple lets you evade this responsibility, it is because you have chosen not to look under the hood, If you pay 50 times revenues for a company, which is what you might be with Snap, you are making assumptions about revenue growth and margins, whether you like it or not. The only difference between us seems to be that I am being explicit about my assumptions, whereas your assumptions are implicit. In fact, they may be so implicit that you don't even know what they are, a decidedly dangerous place to be in investing.

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Rats get a bad rap for fleeing sinking ships. After all, given that survival is the strongest evolutionary impulse and that rats are not high up in the food chain, why would they not? That idiom, unfortunately, is what came to mind as I took another look at Valeant, the vessel in my investment portfolio that most closely resembles a sinking ship. This is a stock that I had little interest in, during its glory days as the ultimate value investing play, but that I took first a look at, after its precipitous fall from grace in November 2015. While I stayed away from it then, I bought it in May 2016 after it had dropped another 60% and I found it cheap enough to add to my portfolio. I then compounded my losses when I doubled my holding in October 2016, arguing that while it was, at best, an indifferently managed company in a poor business, it was under priced at $14 . With the stock trading at less than $12 (and down to $10.50, as I write this post) and its biggest investor/promoter abandoning it, there is no way that I can avert my eyes any longer from this train wreck. So, here I go!

Valeant: A Short (and Personal) History

I won't bore you by repeating (for a third time) the story of Valeant's fall from investment grace, which happened with stunning speed in 2015, as it went from value investing favorite to untouchable, in the matter of months. My first post, from November 2015, examined the company in the aftermath of the fall, as it was touted as a contrarian bet, trading at close to $90, down more than 50% in a few months. My belief then was that the company's business model, built on acquisitions, debt and drug repricing was broken and that the company, if it became a more conventional drug business company, with low growth driven by R&D, was worth $73 per share. I revisited Valeant in April 2016, after the company had gone through a series of additional setbacks, with many of its wounds self inflicted and reflecting either accounting or management misplays. At the time, with the updated information I had and staying with my story of Valeant transitioning to a boring drug company, with less attractive margins, I estimated a value per share of $44, above the stock price of $33 at the time. I bought my first batch of shares. In the months that followed, Valeant's woes continued, both in terms of operations and stock price. After it announced a revenue drop and a decline in income in an earnings report in November 2016, the stock hit $14 and I had no choice but to revisit it, with a fresh valuation. Adjusting the valuation for the new numbers (and a more pessimistic take on how long it would take for the company to make its way back to being a conventional, R&D-driven pharmaceutical company, I valued the shares at $32.50. That may have been hopeful thinking but I added to my holdings at around $14/share.

Valeant: Updating the Numbers

Since that valuation, not much has gone well for the company and its most recent earnings report suggests that its transition back to health is still hitting roadblocks. While talk of imminent default seems to have subsided, there seems to be overwhelming pessimism on the company's operating prospects, at least in the near term. In its most recent earnings report, Valeant reported further deterioration in key numbers:

	2016 10K	2015 10K	% Change
Revenues	$9,674.00	$10,442.00	-7.35%
Operating income or EBIT	$3,105.46	$4,550.38	-31.75%
Interest expense	$1,836.00	$1,563.00	17.47%
Book value of equity	$3,258.00	$6,029.00	-45.96%
Book value of debt	$29,852.00	$31,104.00	-4.03%

Much as I would like to believe that this decline is short term and that the stock will come back, there is now a real chance that my story for Valeant, not an optimistic and uplifting story to begin with, is now broken. The company's growth strategy of acquiring other companies, using huge amounts of debt, raising prices on "under priced" drugs and paying as little in taxes as possible were perhaps legally defensible but they were ethically questionable and may have damaged its reputation and credibility so thoroughly that it is now unable to get back to normalcy. This can explain why the company has had so much trouble not only in getting its operations back on track but also why it has been unable to pivot to being a more traditional drug company. If researchers are leery about working in your R&D department, if every price increase you try to make faces scrutiny and push back and your credibility with markets is rock bottom, making the transition will be tough to do. It can also indirectly explain why Valeant may be having trouble selling some of its most lucrative assets, as potential buyers seem wary of the corporate taint and perhaps have lingering doubts about whether they can trust Valeant's numbers.

In fact, the one silver lining that may emerge from this experience is that I now have the perfect example to illustrate why being a business entity that violates the norms of good corporate behavior (even if their actions legal) can destroy value. At least in sectors like health care, where the government is a leading customer and predatory pricing can lead to more than just public shaming, the Valeant story should be a cautionary note for others in the sector who may be embarking on similar paths.

The Ackman Effect

You may find it strange that I would spend this much time talking about Valeant without mentioning what may seem to be the big story about the stock, which is that Bill Ackman, long the company's biggest investor and cheerleader and for much of the last two years, a powerful board member, has admitted defeat, selling the shares that Pershing Square (his investment vehicle) has held in Valeant for about $11 per share, representing a staggering loss of almost 90% on his investment. The reasons for my lack of response are similar to the ones that I voiced in this post, when I remained an Apple stockholders as Carl Icahn sold Apple and Warren Buffett bought the stock in April 2016. As an investor, I have to make my own judgments on whether a stock fits in my portfolio and following others (no matter how much regard I have for them) is me-too-ism, destined for failure.

Don't get me wrong! I think Bill Ackman, notwithstanding his Valeant setbacks, is an accomplished investor whose wins outnumber his losses and when he takes a position (long or short) in a stock, I will check it out. That said, I did not buy Valeant because Ackman owned the stock and I am not selling, just because he sold. In fact, and this may seem like a stretch, it is possible that Ackman's presence in the company and the potential veto power that he might have been exercising over big decisions may have become more of an impediment than a help as the company tries to untangle itself from its past. I am not sure how well-sourced these stories are, but there are some that suggest that it was Ackman who was the obstacle to a Salix sale last year.

Valeant: Three Outcomes

As I see it, there are three paths that Valeant can take, going forward.

1. Going Concern: To value Valeant as a going concern, I revisited my valuation from November 2016 and made its pathway to stable drug company more rocky by assuming that revenues would continue to drop 2% a year and margins will stay depressed at 2016 levels for the next 5 years and that revenue growth will stay anemic (3% a year) after that, with a moderate improvement in margins. With those changes put in and leaving the likelihood that the company will not make it at 10% (since the company has made some headway in reducing debt), the value per share that I get is $13.68.

Download spreadsheet

To illustrate the uncertainty associated with this value estimate, I ran a simulation with my estimated distributions for revenue growth, margins and cost of capital and arrived at the following distribution of values.

The simulation confirms the base case intrinsic valuation, insofar as the median value of $13.31 is close to the price at the time of the valuation ($12) but it provides more information that may or may not tilt the investment decision. There is a clear chance that the equity could go to zero (about 12%), if the value dips below the outstanding debt ($29 billion). At the same time, there is significant upside, if the company can find a way to alter its trajectory and become a boring, low growth drug company.

2. Acquisition Target: It is a sign of desperation when as an investor, your best hope is that someone else will acquire your company and pay a premium for it. I am afraid that the Valeant taint so strong and its structure so opaque and complex that very few acquirers will want to buy the entire company. I see little chance of this bailing me out.

3. Sum of its parts, liquidated: It is true that Valeant has some valuable pieces in it, with Bausch & Lomb and Salix being the biggest prices. While neither business has attracted as much attention as Valeant had hoped, there are two reasons why. The first is that Ackman, with significant losses on the stock and a seat on the board, may have exercised some veto power over any potential sales. The second is that potential buyers may be scared away by Valeant's history. One solution, now that Ackman is no longer at the company, is for Valeant to open its books to potential acquirers and sell its assets individually to the best possible buyers. Note that this liquidation value will have to exceed $29 billion, the outstanding debt, for equity investors to generate any remaining cash.

There is one other macro concern that may make Valeant's future more thorny. As a company that pays a low effective tax rate and borrows lots of money, the proposed changes to the tax law (where the marginal tax rate is likely to be reduced and the tax savings from interest expenses curbed), Valeant will probably have to pay a much higher effective tax rate going forward, one reason why I have shifted to a 30% tax rate for the future.

The Bottom Line

Let's start with the easy judgment. This was not an investment that I should have made and much as I would like to blame macro forces, the company's management and Bill Ackman for my losses, this was my mistake. I was right in my initial post in concluding that the company's old business model (of acquiring growth with borrowed money and repricing drugs) was broken but I clearly underestimated how much damage that model has done to the company's reputation and how much work it will take for it to become a boring, drug company. In fact, it is possible that the damage is so severe, the company will not be able to make the adjustments necessary to survive as a going concern.

So, now what? I cannot reverse the consequences of my original sin (of buying Valeant at $32) in April 2017 and the secondary sin (of doubling down, when Valeant was trading at $14) by selling now. The question then becomes a simple one. Would I buy Valeant at today's price? If the answer is yes, I should hold and if the answer is no, I should fold. My intrinsic value per share has dropped to just above where the stock is trading at now, and at this stage, my judgment is that, valued as a going concern, it would be trading slightly under value. In a strange way, Bill Ackman's exit is what tipped the scales for me, since it will give Valeant's management, if they are so inclined, the capacity to make the decisions that they may have been constrained from making before. In particular, if they recognize that this may be a clear case where the company is worth more as the sum of its liquidated parts than as a going concern, there is still a chance that I could reduce my losses on this investment. Note, though, that based on my numbers, I don't expect to make my original investment (which averages out to $21/share) back. I am not happy about that but sunk costs are sunk!

As I continue to hold Valeant, I am also aware that I might be committing one of investing's biggest sins, which is an aversion to admitting mistakes by selling losers. My discounted cash flow valuations may be an after-the-fact rationalizing of something that I don't want to do, i.e., sell a big loser. To counter this, I briefly considering selling the shares and rebuying them back immediately; that makes me admit my mistake and take my losses while restarting the investment process with a new buy, but the "wash sales" rule is an impediment to this cleansing exercise. The bottom line is that if I am holding on to Valeant, not for intrinsic value reasons (as I am trying to convince myself) but because I have an investing blind spot, I will be last one to know!

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Valeant Valuation: March 2017

"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.â 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 three possible explanations and they are not mutually exclusive. In fact, I believe that all three contribute to the dichotomy.

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.
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.
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.

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.
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.

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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 companyâs 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. Uberâs 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 Uberâs 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 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 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.

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.
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.
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 has been with its consequences. 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 thereâll 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; there 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 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:

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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 storm 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.

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Uber valuation spreadsheets

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.

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.
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.
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.
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:

The value of a user increases with user stickiness and loyalty (captured in the expected lifetime of a user and the annual renewal rate).
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).
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.
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:

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.
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.
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.

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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):

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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:

Company	Most Recent Pricing (in $ millions)	# Users (in millions)	Price/User
Uber	$69,000	40.00	$1,725.00
Lyft	$7,500	5.00	$1,500.00
Didi Chuxing	$50,000	250.00	$200.00
Ola	$3,000	10.00	$300.00
GrabTaxi	$4,200	3.80	$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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In my last post, I tried valuing Uber by estimating how much an existing user was worth to the company and then using that number to extrapolate to the value of all existing users and the value added by new users. As always, I got many useful comments on what I was missing, what I could do better and what could be simplified, and I thank you (really). While I could spend this entire post rehashing assumptions, I don't intend to! To me, the most useful part of valuation is not the destination, i.e., the value that you get at the end, but the journey, i.e., the process of doing valuation, since it is the process that allows us to isolate the key drivers of value, which, in turn, focuses discussions on those variables, rather than on distractions. Consequently, I decided to revisit my Uber user-based valuation to see what I could eke out as implications for user or subscriber-based businesses.

Estimation versus Economic Risk
I will start by conceding the obvious. I made a lot of assumptions to arrive at the value of a user at Uber, but I will go further. There was not a single fact in that valuation, since every number was an estimate. That said, you could say that about the valuation of any company, with the divergence really being one of the degree of uncertainty you face, not in whether it exists. At the risk of restating points that I have made in my other writing, here are three general points that I would make about uncertainty in valuation.

1. Estimation uncertainty versus Economic uncertainty
To deal with uncertainty in a sensible way, you first have to categorize it. One of the categorizations that I find useful is to break the uncertainty you face when you are trying to value a business or an asset into estimation and economic uncertainty. Estimation uncertainty comes from incomplete, missing or misleading information provided by the company that you are valuing, whereas economic uncertainty is driven by forthcoming changes in the business that the company operates in, as well as macro economic factors. Estimation uncertainty can be reduced by obtaining better and more complete information but estimation uncertainty will remain resistant, no matter how time you put in and what data analysis that you do. Using my Uber user valuation, it is true that some of the noise in the valuation comes from Uber being a private, secretive company and but most of the uncertainty comes from the ride sharing business being in a state of flux, as regulators and competitors work out how best to deal with shifting consumer tastes and changing technologies. This has two implications. The first is that even if you had access to more information, either because Uber decides to go public or you are an insider in the company, much of the uncertainty in estimated value per user will remain. The second is that your estimated value will change considerably over time, as the facts on the ground change, and that volatility in value cannot be viewed as a shortcoming of the model.

2. Uncertainty is an integral part of valuation
One critique that leaves me unmoved is that valuing a business or an asset, in the face of significant uncertainty, is pointless because you will be wrong. So what? Uncertainty is part and parcel of doing business and you cannot wish it, pray it or analyze it away. As I see it, you have two choices when it comes to uncertainty. You can deal with it frontally by making explicit assumptions or you can go into "denial" model and make implicit assumptions. When I tried to value a user at Uber, I made explicit assumptions about user life, renewal rates and a host of other variables, and I will cheerfully admit that I will be wrong on every one of them, but what is the alternative? When pricing a user by looking at what others are paying for users in similar companies, you are making assumptions about all of the variables as well, but those assumptions are implicit. In fact, they are hidden so well that you may not be aware of your own assumptions, a dangerous place to be when investing.

3. Uncertainty can (and should) be visualized
Here is my response to uncertainty. Where data exists but I do not have access to that data, I will try to make my best estimates based upon the existing information, noisy, dated or second hand though it might be. Where I have access to data, I will check it against other data, common sense and economic first principles. Where there is no data, I will make my best estimates and to the extent that these estimates come with probability distributions, my value itself is a distribution, not a number. Illustrating this process, with the Uber user valuation:

Excel Add On: Crystal Ball (Oracle), Simulation Output

I have made distributional assumptions on four of my inputs: the portion of Uber's expenses that go to servicing existing users, the life time of a user, the proportion of expenses that are variable and the cost of capital (discount rate) to compute today's value. Since these distributions are all centered on my base case assumptions, it should come as no surprise that the median value of a user ($414) is very close to my base case value ($410). However, there is a wide spread around that value, with the numbers ranging a low of $74, when the user life is short, the expenses of servicing a use are high, most of the costs are variable and the cost of capital is low, to a high of more than $1000 per user, when the opposite conditions hold. Note that at the current pricing of $69 billion, you are valuing each user close to $900, at the upper end of the distribution.

User Economics: Cost Propositions
It is true that the end game for every business is to make money for its investors. That said, there is a tendency to over react, when a young company reports a loss, as was the case when Uber reported an operating loss of $2.8 billion for 2016, a few months ago. The pessimists on Uber viewed this as further evidence that the company was on a pathway to nowhere and that investors in the company must be delusional to attach any value to it. The optimists argued that it is natural for young companies to lose money and that Uber should be judged on other dimensions such as user growth and market potential instead. At the risk of angering both groups, I will use my Uber user valuation to argue that while I agree with the second group that losing money is typical at young companies, I will also take sides with the first group that you still need a pathway to profitability amidst the losses, for value to exist.

1. Servicing existing users versus acquiring new users
In my Uber user valuation, I started with the operating losses reported by the company ($2.8 billion), backed into the total operating expenses for the company ($9.3 billion) and then allocated that expense across three categories: servicing existing user (48.17%), acquiring new users (41.08%) and corporate expenses (10.75%). While I based this breakdown on the information (on increase in users and contribution margins in ride sharing) that I had on Uber in 2016, that information is dated, noisy and second hand. It is entirely possible that the actual break down of expenses is different from my estimate. If you are wondering why it matters, since the end result (that Uber lost $2.8 billion) is not changing, there are consequences that you can see in the table below:

Uber User Value: Existing User versus New User Costs

% of Operating Expenses spent on acquiring new users	Value of Existing Users	Value of New Users	Uber User Value	% of Value from Existing users
0%	$6,167	$18,147	$24,314	25.36%
20%	$10,619	$19,035	$29,654	35.81%
40%	$15,071	$19,923	$34,994	43.07%
60%	$19,523	$20,811	$40,334	48.40%
80%	$23,974	$21,699	$45,673	52.49%
100%	$28,426	$22,587	$51,013	55.72%

As you increase the proportion of the operating expenses that are spent on acquiring new users, the value of an existing user goes up because you are spending less money on providing service to that user, but the value of a new user also increases, as the net value added (the difference between the user value and the cost of acquiring a user) goes up. Ironically, as you spend more on acquiring new users and less on servicing existing users, the proportion of your value that comes from existing users increases.
User Value Proposition 1: A money-losing company that is losing money providing service to existing users/customers is worth less than a company with equivalent losses, where the primary expenses are coming from customer acquisitions.

This is, of course, neither profound nor surprising, and it explains why, left to their own devices and without any monitoring, young companies will claim that most or all of their expenses are for acquiring new customers. If you are investing in a young company, you will have to do your own assessment of whether managers are misrepresenting, by looking at expense growth over time versus new customers. If the number of total customers remains fixed and expenses keep rising, you should be skeptical about managerial claims (that most of the costs are for acquiring new customers).

2. Cost Structure
One reason that investors are willing to accept losses at young companies is because they believe that as the company grows its operations, there will be economies of scale. In income statement terms, this will result in expenses growing less quickly than revenues and improving operating margins. That said, you cannot take it on faith that this will always happen or that it will happen at the same rate for every company. To see the impact on user value of this dimension, I adjusted the portion of Uber's expenses that are variable (and will grow with revenues) and those that are fixed (and grow at a lower rate) and captured the value effect in this table:

Uber User Value and Cost Structure

% of current expenses that are fixed	Value of Existing Users	Value of New Users	Uber User Value	% of Value from Existing users
0%	$14,733	$15,250	$29,983	49.14%
20%	$16,412	$20,191	$36,603	44.84%
40%	$17,834	$24,373	$42,207	42.25%
60%	$19,040	$27,924	$46,964	40.54%
80%	$20,068	$30,949	$51,017	39.34%
100%	$20,947	$33,536	$54,483	38.45%

As the proportion of expenses that are fixed rises, the value of both existing and new users goes up but the latter goes up at a faster rate. Put simply, the economies of scale increase as you increase the rate at which you are adding scale.
User Value Proposition 2: A company whose expenses are primarily fixed (will not grow with revenues) will be worth more than an otherwise identical company whose expenses are variable (track revenues).

If unchallenged, young growth companies will always claim that they have massive economies of scale but that claim has to be backed up by the numbers. Specifically, investors should pay attention to the rate of change in revenues and expenses, since with large economies of scale, the former should change more than the latter. The caveat, though, is that having more fixed costs can increase risk, because it will increase the risk of failure at young companies and earnings volatility for more mature firms. As user growth levels off, having more fixed costs will reduce value rather than increasing it.

User Economics: Growth Propositions
For young companies, we generally view growth as good and while that is generally true, not all growth is created equal. In fact, even with young companies, there are some strategies that deliver growth in users or revenues, while destroying value. In a user or subscriber based model, there are two ways you can grow your revenues. One is to get existing users to buy more or your products or services and the other is by trying to acquire new users. While both can increase value, the former will be more value incremental, for two reasons. First, since it comes from existing customers, you donât have to pay to acquire these users and it is thus less costly to the firm. Second, by increasing the value of a user, it increases the value of any new users as well, creating a secondary impact on value. Using by Uber user valuation, you can see the impact of changing the annual growth rate in revenues for an existing user in the chart below:

As revenue growth rate increases, the value of both existing and new users increases, with the value of Uber hitting $90 billion at high annual growth rates. If there is no growth in revenues, the value of Uber collapses as new users actually destroy value (because the cost of adding a new user exceeds the value of that user). Now consider how Uber's value is affected, if we hold existing user assumptions fixed and change the compounded annual growth rate (for the next 10 years) in the number of users:

While value increases with user growth rates, it increases at a lower rate than it did when we varied revenue growth from existing users.
User Value Proposition 3: A company that is growing revenues by increasing revenues/user is worth more than an otherwise similar growth company that is deriving growth from increasing the number of users/customers.

Young companies face the question of whether to allocate resources to get new users or try to sell more to existing users is one of those. At least in the case of Uber, the numbers seem to indicate that the payoff is greater in getting existing users to use the service more than in looking for new users.

User Economics: Business Propositions
At the risk of stretching the user value model too far, it can be used to discuss business models in the space, from the networking benefits that so many companies in this space claim to possess to how the revenue model you choose (subscription, transaction or advertising) plays out in user values.

1. Competitive Dynamics and Networking Benefits

Is it better to operate in a business where the cost of acquiring a new user is low or high? Holding all else constant, the answer is obvious. A firm will maximize its value if can generate both high value per user and have a low cost of acquiring new users. That said, if everyone in the business shares these characteristics, one or another of these variables has to change. If the cost of acquiring new users is low for everyone, competition will drive down the value per new user, and if the value per user remains high, competition will drive up the cost of acquiring new users. The trade off is captured in the picture below:

User Value Proposition 4: The exceptional firm will be the one that is able to find a pathway to high value per user and a low cost to adding a new user in a market, where its competitors struggle with either low value per user or high costs of acquiring users.
So how do the exceptional companies pull off this seeming impossible combination of high value per user and low cost per new user? I may be stretching, but it is at the heart of two terms that we see increasingly used in business, network benefits and big data.

Network Benefits: If network benefits exist, the cost of acquiring new users will decrease as a company's presence in a market increases, reaching a tipping point where the biggest player will face much lower costs in acquiring new users than the competition, allowing it to capture the market and perhaps use its market dominance to increase the value of each user. In the case of Uber and ride sharing business, the argument for networking benefits is strong on a localized basis, since there are clearly advantages for both drivers and customers to shift to the dominant ride sharing company in any locality, the former because they will generate more income and the latter because they will get better service. The argument is much weaker on a global basis, though ride sharing companies are trying to create networking benefits by allying with airlines and credit care companies, and how this attempt plays out may well determine Uber's ultimate value.
Big Data: While I remain a skeptic on the "big data" claims that every company seems to be making today, it is inarguable that there are companies that use big data to augment value. These companies collect data on their existing users/subscribers/customers and use that information to (a) customize existing products/services to meet user preferences, (b) create new products or services that meet perceived user needs and/or (c) for differential pricing. All of these increase user value by altering one or more of the inputs into the equation, with customization increasing user life and new products & differential the growth in revenues/user. In my view, the best users of big data (Netflix, Amazon, Google and Facebook) have used the data to increase their existing user value. Uber is still in the nascent stages, but its attempts at using data have expanded from surge pricing to differential pricing.

2. Revenue Models
In my version of user valuation, I look at revenues per user, drawing no distinction on how those revenues are derived. Broadly speaking, there are three revenue models that a user/subscriber based company can use, a subscription-based model where users or subscribers pay a subscription fee to continue to use the service or product, a transaction-based model where users or subscribers pay only when they use the service of product and an advertising-based model where users or subscribers get to use the product or service for free, but are targeted in advertising. Netflix operates on a subscription-based model, Uber is a transaction-based firm and Facebook generates its revenues from advertising. Some companies like LinkedIn have hybrid models, generating revenues from subscriptions (from premium members), transactions (from recruitments) and advertising. There are other inputs into the valuation that will be affected by a company's revenue model and I have tried to capture them in the table below:

	Subscription	Transaction	Advertising
User Stickiness (User life & Renewal Probability)	High (High life & renewal probability)	Intermediate (Intermediate life & renewal probability)	Low (Low life & renewal probability)
Revenue per User Predictability (Discount rate)	High (Low Discount Rate)	Low Predictability (High Discount Rate)	Intermediate (Average Discount Rate)
Revenue per User Growth (Annual Growth Rate)	Low (Low growth rate in revenues/user)	Low (High growth rate in revenues/user)	Intermediate (Intermediate growth rate in revenues/user)
Growth rate in users (CAGR in # Users)	Low (Low CAGR in # users)	Intermediate (Intermediate CAGR in # users)	High (High CAGR in # users)
Cost of adding new users (Cost/New User)	High (High Cost/New User)	Intermediate (Middling Cost/New User)	Low (Low Cost/New User)

There is no one dominant revenue model, since each has its pluses and minuses. An advertising-based model will allow for much more rapid growth in a firm's early years, a subscription-based model will generate more sustainable growth and a transaction-based model has the greatest potential for revenue growth from existing users.
User Value Proposition 5: The "optimal" revenue model may vary for a firm depending upon where it is in the life cycle and across firms depending on their product or service offerings and across investors, depending on whether they are focused on user growth, revenue growth or revenue sustainability.

3. Real Options
When valuing a company based upon its expected cash flows, there is a chance that you will under value the company, if it has control of a resource that could be used for other purposes in the future, even if that usage makes no economic sense today. That is why a technology or natural resource reserve that is not viable today can still have value, and this is the basis for the real option premium. In the context of a user-based business, optionality can become a component of value, to the extent that companies may be able to exploit their user bases to sell other products and services in the future. While the intuition of real options is simple, valuing real options is notoriously difficult and after much hand waving, most of us (including me) give up, but the user-based valuation model provides a framework to at least eke out some general propositions about optionality and value.

There should be no surprises in this picture, with the value of a real option in a user base tied to the inputs into an option pricing model.
User Value Proposition 6: The value of optionality from a user base will be greatest at firms with lots of sticky, intense users in businesses where the future is unpredictable because of changes in product/service technology and customer tastes.

The Bottom Line
The most direct applications of a user or subscriber based model is in the valuation of companies like Uber, Facebook and Netflix. That said, more and more companies are seeing benefits in shifting from their traditional business models to user-based ones. Apple is a cash machine built around a smartphone but it is also accumulating information on more than a billion users of these phones, to whom it may be able to offer other products and services. Amazon started life as an online retail company but there is no denying the power of its seventy million Prime members in generating revenues for the company. I have used Microsoft and Adobe products for as long as they have been around, but with both companies, but my relationship with both companies has changed. I am now a subscriber (Office 365 and Creative Cloud member) who pays annual fees, rather than a customer who buys and upgrades software on a discretionary basis. Understanding user economics and value is central to not only investors in these companies, when valuing and pricing them, but to managers of these companies, in their day-to-day business decisions. I will admit, without shame, that my knowledge of user-based companies is rudimentary and that my user-based model may be amateurish, in what it misses or mangles. That said, if you are an expert on user-based businesses, I hope that you can build on the model to make it more realistic and useful.

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The inexorable push towards globalization has stalled in the last few years, but the change it has created is irreversible. The largest companies in the world are multinationals, deriving large portions of their revenues from outside domestic markets, and even the most inward looking investors are dependent upon global economies for their returns. As a consequence, measuring and incorporating country risk into decision making is a requirement in both corporate finance and valuation. It is in pursuit of that objective that I revisit the country risk issue twice every year, once at the start of the year and once mid-year, at which time I also update a paper that I have on the topic, that you are welcome to read or browse or ignore.

The Globalization of Companies

There are some investors, especially in the United States, who feel that they can avoid dealing with risk in other countries, by investing in just US stocks. That is a delusion, though, because a company that is incorporated and traded in the United States can derive a significant portion of its revenues and earnings from outside the country. In 2015, the companies in the S&P 500, the largest market cap stocks in the US, derived approximately 44% of its revenues from foreign markets, down from 48% in the prior year.

Source: S&P

The composition of foreign sales is also changing, though gradually, over time, shifting away from the UK and Europe to emerging markets, as evidenced in the graph below:

Source: S&P

Lest you feel that this graph is skewed by the biggest companies in the index, 239 of the 500 companies in the index reported that foreign sales represented between 15% and 85% of their total sales and 13 companies reported that more than 85% of their sales came from outside the US. In 2014, two companies, Accenture and Seagate Technology, reported that all their sales were foreign, making them US companies only in name. This phenomenon is not restricted to US companies, as the largest companies in most markets exhibit similar characteristics. While we can debate whether these trend lines are good or bad for consumers and investors, the consequences are real:

Fraying link to domestic economies: For decades, the conventional wisdom has been that the stock market in a country is closely tied to how well the economy of that country is doing. That relationship has been weakened by globalization and equity market performance around the world is disconnecting from domestic economic growth. Taking the US as an example, consider that equity markets in the US have been on a bull run, with indices up 170% to 200%, cumulatively since 2009, even as the US economy has been posting anemic growth.
Central Banking power is diluted: In the decades since the great depression, we have to come to accept that central banks can use the policy levers that they have at their disposal to move long term interest rates and to strongly influence overall economic growth, but that power too has been reduced by globalization and its unpredictable flows. It should come as no surprise then that the frantic efforts of central banks\ in the US, Europe and Japan, in the last decade, to use the interest rate lever to pump up economic growth or to alter the trajectory of long term interest rates have failed.
Taxing questions: When writing tax code, governments have generally assumed that companies incorporated in their domiciles have little choice but to accede to tax laws eventually and pay their share of taxes. While companies have historically played the tax game by delaying and deferring taxes due, their global reach now seems to have shifted the balance of power in their direction. In the United States, in particular, where the government has tried to tax companies on their global income, this push back has taken the form of trapped cash, as companies hold trillions of dollars of cash on foreign shores, and inversions, where some US companies have chosen to move their home base to more favorable tax locales.
Declining cross-market correlations: As companies globalize, it should come as no surprise that the correlations across global equity markets have climbed, with two immediate consequences. The first is that global crises are now an almost annual occurrence rather than uncommon surprises, as pain in one market quickly spreads across the world. The second is that the salve of geographic diversification, long touted as protection against domestic market shocks, provides far less protection than it used to.

The bottom line is that there is no place to hide from country risk, and as with any other type of risk, it is best to face up to it and deal with it explicitly.

Country Risk - Default Risk Measures

The simplest and most easily measured country risk is the risk of sovereign default. When countries default on their obligations, it is not just the government that feels the pain but companies, consumers and investors do, as well.

Sovereign Default: Frequency and Consequences

Governments borrow money, both from their own citizens and from foreign entities, and they sometimes borrow too much. Some of these government default, not only on their foreign currency debt but also on their local currency debt, with the latter having become more common over time:

Source: Fitch Ratings

You may be puzzled by local currency debt defaults, since governments do have the capacity to print more of their own currency, but faced with a choice between defaulting or debasing their currencies, many governments choose the latter. When default occurs, the immediate pain is felt by the government and lenders, the former because it loses the capacity to borrow more, and the latter because they don't get paid., but there is collateral damage:

Capital Market Turmoil: Liquidity dries up, as investors withdraw from equity and bond markets, making it more difficult for private enterprises in the defaulting country to raise funds for projects and resulting in sharp price drops in both bond and stock markets.
Real growth: Sovereign defaults are generally followed by economic recessions, as consumers hold back on spending and firms are reluctant to commit resources to long-term investments.
Political Instability: Default can also strike a blow to the national psyche, which in turn can put the leadership class at risk. The wave of defaults that swept through Europe in the 1930s, with Germany, Austria, Hungary and Italy all falling victims, allowed for the rise of the Nazis and set the stage for the Second World War. In Latin America, defaults and coups have gone hand in hand for much of the last two centuries.

Sovereign Ratings

The most accessible measures of sovereign default risk are sovereign ratings, with S&P, Moody's and Fitch all providing both local currency and foreign currency ratings for most countries around the world. While there are many who mistrust these ratings, they are widely used as proxies of country risk and changes in ratings, especially down grades, are news worthy and affect markets. The process and metrics used to arrive at the ratings are described more fully here and here but the picture below summarizes the sovereign ratings assigned to countries in July 2017 and the data can be downloaded at this link:

Link for live map

The last decade has turned the spotlight on both the pluses and minuses of ratings. On the plus side, as the ratings agencies are quick to point out, ratings and default spreads are highly correlated. On the minus side, ratings agencies seem to have regional biases (under rating emerging markets and over rating developed markets) and are slow to change ratings.

Sovereign CDS Spreads

In the last decade, we have seen the growth of a market-based measure of default risk in the Credit Default Swap (CDS) market, where you can buy insurance against sovereign default by buying a sovereign CDS. Since the insurance is priced on annual basis, the price of a sovereign CDS becomes a market measure of the default spread for that country. In July 2017, there were 68 countries with sovereign CDS and the picture below captures the pricing (with the data available for download at this link). One of the limitations of the CDS market is that there is still credit risk in the market and to allow for the upward bias this creates in the spreads, I compute a netted version of the spread, where I net out the US sovereign CDS spread of 0.34% from each country's CDS spread.

Link for live map

To provide a comparison between the CDS and sovereign rating measures of default risk, let me offer two example. The sovereign CDS for Brazil on July 1, 2017, was 3.46%. On the same day, Moody rated Brazil at Ba2, with an estimated default spread of 3.17%, close to the CDS value. For India, the sovereign CDS spread on July 1, 2017, was 2.42%, very close to the default spread of 2.32% that would have been assigned to it based upon its Baa3 rating.

Country Risk - Institutional Risk

When investing in a company, the sovereign default risk is just one of many risks that you have to factor into your decision making. In fact, default risk may pale in comparison to risks you face because of the institutional structure, or lack of it, in a country. At the risk of picking at scabs, here is my shot at assessing some of these risks.

1. Corruption

Much as we like to inveigh against its consequences, corruption is not just part and parcel of operating in some parts of the world, but it takes on the role of an implicit tax, one that is paid to free agents, acting in their own interests, rather than to governments. Transparency International, an entity that measures corruption risk around the world, estimates corruption scores for individual countries and heir findings for 2016 are summarized in the picture below. To see where a country falls on the corruption continuum, you can either click on the live link below the picture or download the data by country by clicking here.

Link to live map

While it is easy to fall back on cultural stereotypes to explain differences across countries, there is a high correlation between economic well being and corruption. Thus, while much of Latin America scores low on the corruption, Chile and Uruguay rank much higher, as do South Korea and Japan in Asia.

2. Legal Protections

Even the very best investments are only as good as the legal protections that you have as an investor, against expropriation or theft, which is why the property right protections rank high on investor wish lists. To measure the strength of property rights, I turned to the International Property Rights Index (IPRI), and report the scores they assigned in their most recent update in 2016, to countries in the picture below. You can click on the live link below the picture or download the data here.

Link to live map

Europe, North America, Japan and Australia all score high on property rights, but the hopeful sign is that index itself has seen increasing respect for property rights across time and Venezuela and Myanmar are now more the exception, than the rule.

3. Risk of violence

It is difficult to do business, when you have bullets whizzing by and bombs going off around you. Holding all else constant, you would prefer to operate in parts of the world that are safer rather than riskier. To measure exposure to violence, I again turn to an external entity, Vision of Humanity, and reproduce their Global Peace Index in the picture below (with link to live map and to data):

Link to live map

In keeping with the adage that when it rains, it pours, the countries that are most susceptible to corruption and have weak property rights also seem to be most exposed to physical violence.

Country Risk - Equity Risk

As you can see, there are multiple dimensions on which you can measure country risk, leading to different scores and rankings. As an investor in the country, you are exposed to all of these risks, albeit to varying degrees, and you have to consider all these risks in making decisions. Consequently, you would like (a) a composite measure of risk that (b) you can convert into a metric that easily fits into your investment framework.

1. Country Risk Scores

There are several services that provide composite measures of country risk, including the Economist, Euromoney and Political Risk Services (PRS). These country risk measures take the form of numerical scores, and in the heat map below, I report the change in the PRS country risk score between July 2016 and July 2017 and categorize countries based on the direction and magnitude of the change. Here, as in the prior pictures, you can see the PRS scores and the change, by country, by either clicking on the live map link below the picture or download the data by clicking here).

Link for live map

Based on the PRS scores, the vast majority of emerging markets became safer during the time period between July 2016 and July 2017, with the biggest improvements in Latin America and Asia. The North American countries saw risk go up, as did pockets of Africa and South East Asia. The problem with country risk scores, no matter how well they are measured, is that they do not fit a standardized framework. Just to provide an illustration, PRS scores are low for risky countries and high for safe countries, whereas the Economist risk scores are high for risky countries and low for safe countries.

3. Equity Risk Premiums

To incorporate and adjust for country risk into investing and valuation, I try to estimate the equity risk premiums for country, with riskier countries having higher equity risk premiums. I start with the implied equity risk premium for the US, which I estimate to be 5.13% at the start of July 2017 as my mature market premium and add to it a scaled up version of the default spread (based upon the rating); the scaling factor of 1.15 is based upon the relative volatility of emerging market equities versus bonds. You can see a more detailed description of the process in the paper that is linked at the end of this post. You can look up the equity risk premium for an individual country by clicking on the live map link or download the data by clicking here.

Link for live map

These equity risk premiums are central to how I deal with country risk in valuation, as I will explain in the last section of this post.

Closing the Loop

When valuing companies that have substantial exposure to country risk, it is easy to get overwhelmed by the variety of risks. To keep the process under your control, you should start by breaking country risk into three buckets: risk that is specific just to that country, risk that is macro/global and discrete risks that are potentially catastrophic (such as nationalization or terrorism). Each has a place in valuation, with country specific risks incorporated into expected cash flows, macro economic risks in the discount rate and discrete risks in a post-valuation adjustment.

1. Adjusting discount rates

The key to a clean country risk adjustment, when estimating discount rates, is to make sure that you do not double or even triple count it. With the cost of equity for a company, for instance, where there are only three inputs that drive the cost, it is only the equity risk premium that should be conduit for country risk (hence explaining my earlier focus on equity risk premiums, by country). The risk free rate is a function of the currency that you choose to do your valuation in and the relative risk measure (or beta, if that is how you choose to measure it) should be determined by the business or businesses that the company operates in.

If you are discounting the composite cash flows of a multinational company, the equity risk premium should be a weighted average of the equity risk premiums of the countries that the company operates in, with the weights based on revenues or operating assets. If you are valuing just the operations in one country, you would use the equity risk premium just for that country.

2. Expected cash flows

With risks that are specific to a country, it is better to incorporate the risks into the expected cash flows. Thus, if a country is rife with corruption, you could treat the resulting costs as part of operating expenses, reducing profits and cash flows. When legal and regulatory delays are a feature of business in a country, you can build in the delay as lags between investing and operations. When violence (from terrorism or war) is part and parcel of operations, you may want to include a cost of insuring against the risk in your cash flows.

None of these adjustments are easy to make, but it is worth remembering that incorporating the risk into your cash flows is not risk adjusting the cash flow, since the latter requires replacing the expected cash flow with a certainty equivalent one. Where does currency risk play out? When converting cash flows from one currency (foreign) to another (domestic), you should bring in expected devaluation or revaluation into expected exchange rates. If you want to hedge exchange rate risk, you can incorporate the cost of heeding into your cash flows but it is not clear that you should be adjusting discount rates for that risk, since investors can diversify it away.

3. Post-Valuation Adjustment

There are some risks that are rare, but if they occur, can be devastating, at least for investors in a business. Included in this grouping would be the risk of nationalization and terrorism. These risks cannot be incorporated easily into discount rates and adjusting expected cash flows in a going concern valuation (DCF) for risk that a company will be nationalized or will not survive is messy.

Thus, to estimate the effect that nationalization risk will have on the value of a business, you will have to assess the probability that the business will be nationalized and the value that you will receive as owners of the business, in the event of nationalization.

Danger and Opportunity

One of my favorite definitions of risk is the Chinese symbol for it, a combination of the symbols for danger and opportunity.

é¢¨éª

With risky emerging markets, this comes into , I am reminded that to have one (opportunity), I have to be willing to live the other (danger). Blindly ignoring these markets, as some conservative developed market companies are inclined to do, because there is danger will lead to stagnation, but blindly jumping into them, drawn by opportunity, will cause implosions. The essence of risk management is to measure the danger in markets and then gauge whether the opportunities are sufficient to compensate you for the dangers. That is what I hope that I have laid the foundations for, in this post.

YouTube Video

Attachment

Country Risk: Determinants, Measures and Implications - The 2017 Edition

Data Links

I am a teacher. That is how I describe myself to anyone who chooses to ask me what I do for a living. I am not a professor (sounds pedantic and pompous), definitely not an academic (how boring is that..) and don't consider myself anything more than a dilettante on almost every topic that I hold forth on. It is in pursuit of my teaching mission that I have put my regular classes online for most of the last two decades, though technology has made that sharing easier. For those of you who have read my postings before, I usually announce a few weeks ahead of every semester, the classes that I will be teaching at Stern, what each class is about and how you can access it, as I did in January with my Spring 2017 valuation and corporate finance classes. As September 2018 approaches, I was going to skip that ritual, since I will be on sabbatical next year (and if you have no idea what a sabbatical is, more on that later..) but I will be teaching, nevertheless, during the year.

Online Education

I still remember the first semester that I shared a class with an online audience was in the 1990s, when the internet was still in its infancy, we were still using dial-up modems and phones were connected to landlines. I recorded my regular classes using a VHS camcorder onto tapes, and then converted the tapes into videos of woeful quality, but with passable audio. I posted these online, but with only minimal additional material, since sharing was both time consuming and difficult to do. Needless to say, the internet has grown up and made sharing much easier, with class recordings now being made with built-in cameras in classrooms and converted to high quality videos quickly, to be watched on tablets on smart phones. Here, for instance, is my entire Spring 2017 valuation class, with links to the videos as well as almost every scrap of material that I provide for the class and even the emails I sent to the class.

I have long believed that the traditional university model not only is ripe for, but is deserving of , disruption, saddled with legacy costs and a muddled mission. That said, the attempts by online education to upend the university model have, for the most part, had only marginal success and it is in trying to answer why that I started thinking about how we teach, and learn online. In particular, online classes have proved a imperfect substitutes for regular classes due to three shortcomings:

No personal touch: This may be a reflection of my age, but there is a difference between being in a live and watching a video of the same class, no matter how well it is recorded and presented.
No interaction: We forget how much of the learning in a classroom comes, not from lectures, but from interaction, not just between the teacher and students but between students, often in informal and serendipitous exchanges. With online education, the interaction, if it exists, is highly formalized and there is less learning.
Tough to stay disciplined: When you were in college, and enrolled for an 8.30 am class, did you feel like not going to class? I certainly did, but what kept me going was the fact that my absence would be noticed, not just by the professor, but by other students in the class. In fact, it is that group pressure and class structure that keeps us focused on project deadlines and exam dates, with regular classes. With online classes, that discipline has to come from within, and it should be therefore no surprised that most people who start online classes never finish them.

It is perhaps easiest to see the challenges and limits of online teaching by looking at what it is that makes for a good class, in person or online. In my view, the measure of good teaching is that students don't get just content (tools, techniques, models) but that they learn how to create their own content, i.e., the capacity to devise their own tools to meet their needs. In the context of a regular class, you use readings, problem sets, quizzes and exams to deliver the former (content) but the latter (learning) requires a more complex mix of classroom and informal interaction, real life projects and intellectual curiosity (and I believe that it is partly a teacher's responsibility to evoke that). The time schedule of a regular class also puts limits on how much students can procrastinate, and peer pressure, from others taking the class or working with you on assignments, serves to keep most on task.

With this framework, the challenges of teaching online become clear. You have to find ways to keep students engaged, disciplined and interactive, and you have to do it online. While there are technical solutions to each one of these challenges (great videos for engagement, a time schedule and online exams for discipline, and discussion boards for interaction), and we have come a long way in the last few years, there is still a great deal of work to be done.

Online Classes: My learning curve

My search for a better way of delivering what I teach online started about five years ago, with a simple first step. I decided to try to take each of my regular lectures, which go for 80 minutes, and see if I could compress it into a 10-12 minute slot and the results were both revealing and humbling. It was not that difficult to compress my classes, a testimonial to how much buffer I build into my regular classes to ramble and pontificate. (If you have been in one of my regular classes or watched one, you probably know that there is nothing I enjoy more than going off on a riff on a topic or news story and I think you need a few of these in a 80-minute class to keep your class engaged.) I also started developing short post-session quizzes with solutions that someone watching the class could take, to check on whether they were "getting" the session material. I organized and sequenced the sessions and you can click to see the online versions of my corporate finance, valuation and investment philosophy classes.

I was under no illusions that I had unlocked the key to online learning with these classes, and these classes had significant limitations. First, packing material densely into 10-12 minute chunks can make watching even these short sessions taxing. Second, the videos that I made (with the help of a friend who was a camera man) were lacking in bells and whistles, basic talking-head videos with slides in the background. Third, there is no personal touch or interaction, since the videos are recorded. Finally, given the number of people in each of these classes, there was no way for me to give and grade exams, look over valuations or corporate financial analysis (a key ingredients of my regular classes) or provide certification that someone had taken the class.

Valuation Certificate Class

Just over a year ago, the Stern School of Business, which is where I teach, asked me whether I would be willing to teach an online certificate class. My initial response was to say no for two reasons. First, universities always seem to operate at deficits, no matter how much revenue they collect from tuition, and I knew that Stern would extract its pound of flesh from those who took the certificate. Second, I was concerned that if I did do a certificate class, and it became a money generator, that I would be asked to remove my free online classes. Stern must have wanted to do this certificate really badly since they offered to leave my online material untouched, if I agreed to work on the certificate course. It was this assurance, in conjunction with the opportunity to have videos shot in a studio, a platform that would allow me to offer exams and quizzes and discussion boards that finally led me to yes.

So, what makes the valuation certificate class different from the free online version? It is certainly not the content, since everything I teach in the certificate class is available on my website in multiple forms, but here are a few of the primary differences:

Studio-shot videos: A studio, with professionals manning cameras, sound and lights, does allow for much better videos. With the help of a talented group that knows a lot more about editing and animation than I ever will, the final versions of the online classes are better than my online videos. There are, in all, 28 video sessions, with two sessions each week, over a 14 week time period.
Supporting material: In addition to the post class tests and the supporting slides, I have links to papers, spreadsheets, data, YouTube videos and blog posts that go with each session. While I am a realist and know that much of this additional material will go untouched, having it accessible will make it easier for you to use it, if you feel the urge.
Live Webex sessions: Every two weeks, through the semester, we will have a live webex session, where you (if you are enrolled in the class) can ask questions, not just about material covered in the previous week's sessions but news stories and happenings. I know it is not much, but it is a step in the right direction.
Announcements and outreach: I contact the students in my regular classes about once a day, but I will spare you that level of harassment. You will hear from me a couple of times every week, checking in on how you are doing and keeping you updated on the course.
Exams/Quizzes: There will be three quizzes and a final exam for the class. While they will be scheduled on specific dates, you can take them any time during a 24-hour time period and if you miss a quiz, the points will be moved to the remaining quizzes. So, if life gets in the way and you are unable to take a quiz, it is not the end of the world.
Valuation Project: Each person in the class can pick any company he or she want to value and value it, over the course of the class. Midway through the semester, I will offer feedback, if you want, to allow you to tweak your valuation, and at the end of the semester, it will become a significant part of your overall grade.
Certificate: After the final exam and valuation are graded, you will receive a certificate for the class, if you complete the requirements. If you do exceptionally well (and you will have to leave that judgment to me), your certificate will come "with honors".

There were 66 people who signed up for the pilot version of the class, which started in January 2017 and 39 completed the class in May 2017. I learned as much from my students as I hope they learned from me, and here are a few lessons. First, I discovered that the discussion boards were effective at creative interactive discussions, among the students, if I did my job and organized the boards by topic. Second, in perhaps the most rewarding part of the class, a few students, who found the material both interesting and easy to grasp, took on the role of teachers helping others deal with mechanical and conceptual questions. Since the most effective way to learn something is to explain it to someone who does not quite "get" it, I restrained myself from jumping into the discussion boards, unless absolutely necessary. Third, I was impressed with both the work that was put into and the quality of the valuations that were turned in by those who finished the class. Of the 39 who were certified at the end of the class, about a third did well enough to get "with honors" attached to the certificate. I would have been proud with any of these students in my regular classes.

This fall, Stern will be offering the valuation certificate class to a bigger audience, with a class of several hundred. The good news is that the class will be tweaked to reflect the lessons learnt from the pilot class. I will continue to do what I did for the pilot, with my webex sessions, and provide feedback and grades not only for your exams but on the companies that you choose to value. The bad news is that Stern will charge "university level" prices for the class and I will not try to tell you that it is "worth it", since that depends on your circumstances. It is entirely possible that you will decide that the price charged is too much for a certificate, that you cannot afford it, or that you are more interested in the learning than in the certification, and if so, I hope that you give the free online version of the class a shot. If you are interested in enrolling in the class, the webpage where you can start the process is here. Incidentally, a pilot version of my corporate finance class, also offered as a certificate class, will be run in Spring 2018, and if you are interested, here is that link.

My Sabbatical

I mentioned, at the start of this post, that I would be on sabbatical, and at the risk of evoking envy, I will tell you what that involves. I am taking the 2017-18 academic year (September 2017- September 2018) off from my regular teaching, as I am allowed to do every seventh year. It is an entitlement that people in most other professions don't have and I recognize how incredibly lucky I am to be able to take a paid break from work. I do have a few odds and ends to take care off during the year, including teaching the certificate classes that I just listed and writing the third edition of The Dark Side of Valuation, but I plan to spend much of the year idling my time away, thinking about nothing in particular. That may sound wasteful, but I have discovered that my mind is most productive, when I am not trying too hard to be insightful. At least, that's my hope and if it does happen, that would be great. I But then again, if I don't have a single creative thought all year, that too was meant to be!

YouTube Video

My Free Online Classes

Corporate Finance (YouTube Playlist version)
Valuation (YouTube Playlist version)
Investment Philosophies (YouTube Playlist version) (New version will be out at the start of 2018)

Stern Certificate Classes

When it comes to any finance-related questions, I am fair game, and those questions usually span the spectrum, from what I think about Warren Buffett (or why I don't agree with everything he says) to whether tech stocks are in a bubble (a perennial question for worry warts). In the last few months, though, I have noticed that I have been getting more and more questions about crypto currencies, especially Bitcoin and Ether, and whether the price surges we have seen in these currencies are merited. While I have an old post on bitcoin, I have generally held back from talking about crypto currencies in this blog or in my other teaching for two reasons. First, I find that any conversation about bitcoin quickly devolves into an argument rather than a discussion, since both proponents and critics tend to hold strong views on its use (or uselessness). Second, I find that some of the technical underpinnings of bitcoin, ether and other cryptocurrencies are beyond my limited understanding of block chains and technology and I risk saying something incredibly ill informed. While both reasons still persist, I am going to throw caution to the winds and put down my thoughts about the rise, the mechanics and the future, at least as I see it, of crypto currencies in this post.

The Market Boom

Any discussion of crypto currencies has to start with the recognition that the experiment is still young. Satoshi Nakamoto's paper on bitcoin was made public in October 2008 and implemented as open source in January 2009. Less than ten years later, the market capitalization of bitcoin alone is in excess of $40 billion and the success story, at least in terms of bitcoin as an investment, can be seen in the graph below:

The initial rise could have been a flash in the pan, a fad attracting speculators, but in the last two years, Bitcoin seems to have found new fans, as can be seen below:

Bitcoin's success, at least in the financial markets, has attracted a host of competitors, with Ethereum (Ether) being the most successful. Ether's rise in market price, since its introduction in 2015 has been even more precipitous that Bitcoin's, though it has pulled back in recent weeks:

The list of crypto currencies gets added to, by the day, with a complete list available here, with the market caps of each (in US dollars) listed. At least from a market perspective, there is no doubting the fact that crypto currencies have arrived, and enriched a lot of people along the way.

The Mechanics

While the crypto currencies emphasize their differences, the most successful ones share a base architecture, the block chain. A block chain is a shared digital ledger of transactions in an asset where the validation of transactions is decentralized. I know that sounds mystical, but the picture below (using bitcoin to illustrate) should provide a better sense of what's involved:

The key features of a block chain are:

Decentralized verification: The validation and verification of a transaction is sourced to members, called miners in the crypto currency world. Verification usually involves trying different algorithms (hashes) to find the unique one that matches the transaction block, and the successful miner is rewarded, currently with the crypto currency. At least, as I understand it, this process requires more brute force (powerful processors trying different algorithms before you find a match) than intellectual firepower.
Complete and open records: Every transaction, once validated and verified, is converted into a block of data that is recorded in the block chain ledger, which is accessible to everyone in the network. If you are worried about privacy, the transaction records do not include personal data but take the form of encrypted data (hashes).
Incorruptible: A block chain, once recorded and shared, cannot be changed since those changes are visible to everyone in the network and are quickly tagged as fraudulent. Thus, the ledger, once created, becomes almost incorruptible.

In effect, a block chain is a digital intermediation process where transactions are checked by members of the network, and recorded, and once that is done, cannot be altered fraudulently. As you can see from its description, the block chain technology is about far more than crypto currencies. It can be used to record transactions in any asset, from securities in financial markets to physical assets like houses, and do so in a way that replaces the existing intermediaries with decentralized models. It should come as no surprise that banks and stock exchanges, which make the bulk of their money from intermediation, not only see block chains as a threat to their existence but have been early investors in the technology, hoping to co-opt it to their own needs.

The Currency Question

If you define success as a rise in market capitalization and popular interest, crypto currencies have clearly succeeded, perhaps more quickly than its original proponents ever expected it to. But the long term success of any crypto currency has to answer a different question, which is whether it is a "good" currency. Harking back to Money 101, you measure a currency's standing by looking at how well it delivers on its three purposes:

Unit of account: A key role for a currency is to operate as a unit of account, allowing you to value not just assets and liabilities, but also goods and services. To be effective as a unit of account, a currency has to be fungible (one unit of the currency is identical to any other unit), divisible and countable.
Medium of exchange: Currencies exist to make transactions possible, and this is best accomplished if the currency in question is easily accessible and transportable, and is accepted by buyers and sellers as legal tender. The latter will occur only if people trust that the currency will maintain its value and if transactions costs are low.
Store of value: To the extent that you hold some or all of your wealth in a currency, you want to feel secure about leaving it in that currency, knowing that it will not lose its buying power while stored.

Given these requirements, you can see why there are no perfect currencies and why every currency has to measured on a continuum from good to bad. Broadly speaking, currencies can take one of three forms, a physical asset (gold, silver, diamonds, shells), a fiat currency (usually taking the form of paper and coins, backed by a government) and crypto currencies. Gold's long tenure as a currency can be attributed to its strength as a store of value, arising from its natural scarcity and durability, though it falls short of fiat currencies, in terms of convenience and acceptance, both as a unit of account and as medium of exchanges. Fiat currencies are backed by sovereign governments and consequently can vary in quality as currencies, depending upon the trust that we have in the issuing governments. Without trust, fiat currency is just paper, and there are some fiat currencies where that paper can become close to worthless. For crypto currencies, the question then becomes how well they deliver on each of the purposes. As units of account, there is no reason to doubt that they can function, since they are fungible, divisible and countable. The weakest link in crypto currencies has been their failure to make deeper inroads as mediums of exchange or as stores of value. Using Bitcoin, to illustrate, it is disappointing that so few retailers still accept it as payment for goods and services. Even the much hyped successes, such as Overstock and Microsoft accepting Bitcoin is illusory, since they do so on limited items, and only with an intermediary who converts the bitcoin into US dollars for them. I certainly would not embark on a long or short trip away from home today, with just bitcoins in my pocket, nor would I be willing to convert all of my liquid savings into bitcoin or any other crypto currency. Would you?

So, why has crypto currency not seen wider acceptance in transactions? There are a few reasons, some of which are more benign than others:

Inertia: Fiat currencies have a had a long run, and it is not surprising that for many people, currency is physical and takes the form of government issued paper and coins. While people may use credit cards and Apple Pay, their thinking is still framed by the past, and it may take a while, especially for older consumers and retailers, to accept a digital currency. That said, the speed with which consumers have adapted to ride sharing services and taken to social media suggests that inertia cannot be the dominant reason holding back the acceptance of crypto currencies.
Price volatility: Crypto currencies have seen and continue to see wild swings in prices, not a bad characteristic in a traded asset but definitely not a good one in a currency. A retailer or service provider who prices his or her goods and services in bitcoin will constantly have to reset the price and consumers have little certitude of how much the bitcoin in their wallers will buy a few hours from now.
Competing crypto currencies: The crypto currency game is still young and the competing players each claim to have found the "magic bullet" for eventual acceptance. As technologies and tastes evolve, you will see a thinning of the herd, where buyers and sellers will pick winners, perhaps from the current list or maybe something new. It is possible that until this happens, transactors will hold up, for fear of backing the wrong horse in the race.

Ultimately, though, I lay some of the blame on the creators of the crypto currencies, for their failure, at least so far, on the transactions front. As I look at the design and listen to the debate about the future of crypto currencies, it seems to me that the focus on marketing crypto currencies has not been on transactors, but on traders in the currency, and it remains an unpleasant reality that what makes crypto currencies so attractive to traders (the wild swings in price, the unpredictability, the excitement) make them unacceptable to transactors.

The Disconnect

You can see the disconnect in how crypto currencies have been greeted, by contrasting the rousing reception that markets have given them with the arms length at which they have been held by merchandisers and consumers. In the graph below, I focus on the divergence between the market price rise of bitcoin and the increase in the number of transactions involving bitcoin:

While the price of bitcoin has increase more than a thousand fold, since the start of 2012, the number of transactions involving bitcoin was only about thirty two times larger in July 2017 than what it was at the start of 2012. In my view, there are three possible explanations for the divergence, and they are not mutually exclusive:

Markets are forward looking: If you are a believer in crypto currencies, the most optimistic explanation is that markets are forward looking and that the rise in the prices of Bitcoin and Ether reflects market expectations that they will succeed as currencies, if not right away, in the near future.
Speculative asset: I am second to none in having faith in markets, but there is a simpler and perhaps better explanation for the frenzied price movements in crypto currencies. I have long drawn a distinction between the value game (where you try to attach a value to an asset based upon fundamentals) and the pricing game, where mood and momentum drive the process. I would argue, based upon my limited observations of the crypto currency markets, that these are pure pricing games, where fundamentals have been long since forgotten. If you don't believe me, visit one of the forums where traders in these markets converse and take note of how little talk there is about fundamentals and how much there is about trading indicators.
Loss of trust in centralized authorities (governments & central banks): There can be no denying that the creators of Bitcoin and Ether were trying to draw as much inspiration for their design from gold, as they were from fiat currencies. Thus, you have miners in crypto currency markets who do their own version of prospecting when validating transactions and are rewarded with the currency in question. For ages, gold has held a special place in the currency continuum, often being the asset of last resort for people who have lost faith in fiat currencies, either because they don't trust the governments backing them or because of debasement (high inflation). While gold will continue to play this role, I believe that for some people (especially younger and more technologically inclined), bitcoin and ether are playing the same role. As surveys continue to show depleting trust in centralized authorities (governments and central banks), you may see more money flow into crypto currencies.

The analogy between gold and crypto currency has one weak link. Gold has held its value through the centuries and is a physical asset. For better or worse, it is unlikely that we will decide a few years from now that gold is worthless. A crypto currency that few people use as currency ultimately will not be able to sustain itself, as shiner and newer versions of it pop up. Ironically, if traders in bitcoin and ether want their investments in the crypto currencies to hold their value, the currencies have to become less exciting and lucrative as investments, and become more accepted as currencies. Since that will not happen by accident, I would suggest that the winning crypto currency or currencies will share the following characteristics;

Transaction, not trading, talk: From creators and proponents of the currency, you will hear less talk about how much money you would make by buying and selling the currency and more on its efficacy in transactions.
Transaction, not trading, features: The design of the crypto currency will focus on creating features that make it attractive as a currency (for transactions), not as investments. Thus, if you are going to impose a cap (either rigid like Bitcoin or more flexible, as with other currencies), you need to explain to transactors, not traders, why the cap makes sense.
Trust in something: I know that we live in an age where trust is a scarce resource and I argued that that the growth in crypto currencies can be attributed, at least partly, to this loss of trust. That said, to be effective as a currency, you do need to be able to trust in something and perhaps accept compromises on privacy and centralized authority (at least on some dimensions of the currency).

It is also worth noting that the real tests for crypto currencies will occur when they reach their caps (fixed or flexible). After all, bitcoin and ether miners have been willing to put in the effort to validate transactions because they are rewarded with issues of the currency, feasible now because there is slack in the currency (the current number is below the cap). As the cap becomes a binding constraint, the rewards from miners have to come from transactions costs and serious thought has to go into currency design to keep these costs low. Hand waving and claiming that technological advances will allow this happen are not enough. I know that there are many in the crypto currency world who recognize this challenge, but for the moment, their voices are being drowned out by traders in the currency and that is not a good sign.

If you expected a valuation of bitcoin or ether in this post, you are probably disappointed by it, but here is a simple metric that you could use to determine whether the prices for crypto currencies are "fair". Currencies are priced relative to each other (exchange rates) and there is no reason why the rules that apply to fiat currencies cannot be extended to crypto currencies. A fair exchange rate between two fiat currencies will be on that equalizes their purchasing power, an old, imperfect and powerful theorem. Consequently, the question that you would need to address, if you are paying $2,775 for a bitcoin on August 1, 2017, is whether you can (or even will be able to) but $2,775 worth of goods and services with that bitcoin. If you believe that bitcoin will eventually get wide acceptance as a digital currency, you may be able to justify that price, especially because there is a hard cap on bitcoin, but if you don't believe that bitcoin will ever acquire wide acceptance in transactions, it is time that you were honest with yourself and recognized that is just a lucrative, but dangerous, pricing game with no good ending.

Conclusion

Crypto currencies, with bitcoin and ether leading the pack, have succeeded in financial markets by attracting investors, and in the public discourse by garnering attention, but they have not succeeded (yet) as currencies. I believe that there will be one or more digital currencies competing with fiat currencies for transactions, sooner rather than later, but I am hard pressed to find a winner on the current list, right now, but that could change if the proponents and designers of one of the currencies starts thinking less about it as a speculative asset and more as a transaction medium, and acting accordingly. If that does not happen, we will have to wait for a fresh entrant and the most enduring part of this phase in markets may be the block chain and not the currencies themselves.

YouTube Video

These are certainly exciting times for Tesla. The first production version of the Tesla 3 was unveiled on July 28, with few surprises on the details and plenty of good reviews. Elon Musk was his usual self, alternating between celebrating success and warning investors in the stock that the company was approaching "manufacturing hell", as it ramped up its production schedule to meet its target of producing 10,000 cars a week. It is perhaps to cover the cash burn in manufacturing hell that Tesla also announced that it planned to raise $1.5 billion in a junk bond offering. Investors continued to be unfazed by the negative and lapped up the positive, as the stock price soared to $365 yesterday. With all of this happening, it is time for me to revisit my Tesla valuation, last updated in July 2016, and incorporate, as best as I can, what I have learned about the company since then.

Tesla: The Story Stock

I have been following Tesla for a few years and rather than revisit the entire history, let me go back to just my most recent post on the company in July 2016, where I called Tesla the ultimate story stock. I argued that wide differences between investors on what Tesla is worth can be traced to divergent story lines on the stock. I used the picture below to illustrate the story choices that you had when it came to Tesla and how those choices affected the inputs into the valuation.

In that post, I also traced out the effect of story choices on value, by estimating how the numbers vary, depending upon the business, focus and competitive edge that you saw Tesla having in the future:

With my base case story of Tesla being an auto/tech company with revenues pushing towards mass market levels and margins resembling those of tech companies, I estimated a value of about $151 a share for the company and my best case estimate of value was $316.46.

Tesla: Operating Update

If you are invested in or have been following Tesla for the last year, you are certainly aware that the market has blown through my best case scenario, with the stock trading this morning at $365 a share, completing a triumphant year in markets:

As Tesla's stock price rose, it broke through milestones that guaranteed it publicity along the way. It's market capitalization exceeded that of Ford and General Motors in April 2016, and in June 2016, Tesla leapfrogged BMW to become the fourth largest market cap automaker in the world, though it has dropped back to fifth since.

Largest Auto Companies (Market Capitalization) on August 9, 2017

While Tesla's market cap has caught up with those larger auto makers, its production and revenues are a fraction of theirs, leading some to use metrics like enterprise value per car sold to conclude that Tesla is massively over valued. I don't have faith in these pricing metrics since they can be misleading, especially when comparing a company with massive potential to companies that are in decline, as I think many of the conventional auto companies in this table are currently.

As I noted at the start of the post, it has been an eventful year for Tesla, with the completion of the Solar City acquisition and the imminence of the Tesla 3 dominating news, and its financial results reflect its changes as a company. In the twelve months ended June 30, 2017, Tesla's revenues hit $10.07 billion, up from $7 billion in its most recent fiscal year, which ended on December 31, 3016; on an annualized basis, that translates into a revenue growth rate of 107%. That positive news, though, has to be offset at least partially with the bad news, which is that the company continued to lose money, reporting an operating loss of $638 million in the most recent 12 months, with R&D expensed, and a loss of $103 million, with capitalized R&D. The growth in the company can be seen graphically by looking at how quickly its operations have scaled up, over the last few years:

Tesla's growth has not just been in the operating numbers but in its influence on the automobile sector. While it was dismissed by the other automobile companies as a newcomer that would learn the facts of life in the sector, as it aged, the reverse has occurred. It is the conventional automobile companies that are, slowly but surely, coming to the recognition that Tesla has changed their long-standing business. Volvo, a Swedish automaker not known for its flair, announced recently that all of its cars would be either electric or hybrid by 2019, and Ford's CEO was displaced for not being more future oriented. A little more than a decade after it burst on to the scene, it is a testimonial to Elon Musk that he has started the disruption of one of the most tradition-bound sectors in business.

Tesla: Valuation Update

The production hiccups notwithstanding, the company continues to move towards production of the Tesla 3, with the delivery of the handful to start the process. There is much that needs to be done, but I consider it a good sign that the company sees a manufacturing crunch approaching, since I would be concerned if they were to claim that they could ramp up from 94,000 to 500,000 cars effortlessly. My updated story for Tesla then is close to the story that I was telling in July 2016, with two minor changes. The first is that the production models of the Tesla 3 indicate that the company is capable of delivering a car that can appeal to a much broader market than prior models, putting it on a pathway to higher revenues. My expected revenues for Tesla in ten years are close to $93 billion, a nine-fold increase from last year's revenues and a higher target than the $81 billion that I projected in my July 2016 valuation. Second, the operating margins, while still negative, have become less so, reducing reinvestment needs for funding growth. The free cash flows are still negative for the next seven years, a cash burn that will require about $15.5 billion in new capital infusions over that period. With those changes, the value per share that I estimate is about $192/share, about 20% higher than my $151 estimate a year ago, but well below the current price per share of $365.

Download spreadsheet

As with every Tesla valuation that I have done, I am sure (and I hope) that you will disagree with me, with some finding me way too pessimistic about Tesla's future, and others, much too optimistic. As always, rather than tell me what you think I am getting wrong, I would encourage you to download the spreadsheet and replace my assumption with yours. I think I am being clear eyed about the challenges that Tesla will face along the way and here are the top three:

Can Tesla sell millions of cars? One of Tesla's accomplishments has been exposing the potential of the hybrid/electric car market, even in an era of restrained fuel prices. That is good news for Tesla but it has woken up the established automobile companies as well, as is evidenced by not only the news from Volvo and Ford, but also in increased activity on this front at the other automobile companies. In my valuation, the revenues that I project in 2010 will require Tesla to sell close to 2 million cars, in the face of increased competition.
Can it make millions of cars? Tesla's current production capacity is constrained and there are two production tests that Tesla has to meet. The first is timing, since the deliveries have been promised for the middle of 2018 and the assembly lines have to be humming by then. The second is cost, since a subtext of the Tesla story, reinforced by Elon Musk, is that the company has found new and innovative ways of scaling up production at much lower costs than conventional automobile companies.
Can it generate double digit margins? In my valuation, I assume an operating margin of 12% for Tesla, almost double the average of 6.33% for global auto companies. For Tesla to generate this higher margin, it has to be able to keep production costs low at its existing and new assembly plants and to be able to charge a premium price for its automobiles, perhaps because of its brand name.

Tesla has shown a capacity to attract and keep customers and I think it is more than capable of meeting the first challenge, i.e., sell millions of cars. It is the production challenge that is the more daunting one, simply because this has always been Tesla's weakest link. Over the last few years, Tesla has consistently had trouble meeting logistical and delivery targets it has set for itself and those targets will only get more daunting in the years to come. Furthermore, if its production costs run above expectations, it will be unable to deliver on higher margins. To succeed, Tesla will require vision, focus and operating discipline. With Elon Musk at its helm, the company will never lack vision, but as I argued in my July 2016 post, Mr. Musk may need a chief operating officer at his side to take care of delivery deadlines and supply chains.

Financing Cash Burn: Tesla's Odd Choice

There is much to admire in the Tesla story but there is one aspect of the story that I find puzzling, and if I were an equity investor, troubling. It is the way in which Tesla has chosen to, and continues to, finance itself. Over the last decade, as Tesla has grown, it has needed substantial capital to finance its growth. That is neither surprising nor unexpected, since cash burn is part of the pathway to glory for companies like Tesla. However, Tesla has chosen to fund its growth with large debt issues, as can be seen in the graph below:

That debt load, already high, given Teslaâs operating cash flows is likely to get even bigger if Tesla succeeds in its newest debt issue of $1.5 billion, which it is hoping to place with an interest rate of 5.25%, trying to woo bond buyers with the same pitch of growth and hope that has been so attractive to equity markets. That suggests that those making the pitch either do not understand how bonds work (that bondholders don't get to share much in upside but share fully in the downside) or are convinced that there are enough naive bond buyers out there, who think that interest payments can be made with potential and promise.

But setting aside concerns about bondholders, the debt issuance makes even less sense from Tesla's perspective. Unlike some, I donât have a kneejerk opposition to the use of debt. In fact, given that the tax code is tilted to benefit debt, it does make sense for many companies to use debt instead of equity. The trade off, though, is a simple one:

If you look at the trade off, you can see quickly that Tesla is singularly unsuited to using debt. It is a company that is not only still losing money but has carried forward losses of close to $4.3 billion, effectively nullifying any tax benefits from debt for the near future (by my estimates, at least seven years). With Elon Musk, the largest stockholder at the company, at the helm, there is no basis for the argument that debt will make managers more disciplined in their investment decisions. While the benefits from debt are low to non-existent, the costs are immense. The company is still young and losing money, and adding a contractual commitment to make interest payments on top of all of the other capital needs that the company has, strikes me as imprudent, with the possibility that one bad year could its promise at risk. Finally, in a company like Tesla, making large and risky bets in new businesses, the chasm between lenders and equity investors is wide, and lenders will either impose restrictions on the company or price in their fears (as higher interest rates). So, why is Tesla borrowing money? I can think of two reasons and neither reflects well on the finance group at Tesla or the bankers who are providing it with advice.

The Dilution Bogeyman: The first is that the company or its investment bankers are so terrified of dilution, that a stock issue is not even on the table. Once the dilution bogeyman enters the decision process, any increase in share count for a company is viewed as bad, and you will do everything in your power to prevent that from happening, even if it means driving the company into bankruptcy.
Inertia: Auto companies have generally borrowed money to fund assembly plants and the bankers may be reading the capital raising recipe from that same cookbook for Tesla. That is incongruent with Elon Muskâs own story of Tesla as a company that is more technology than automobile and one that plans to change the way the auto business is run.

Teslaâs strengths are vision and potential and while equity investors will accept these as down payments for cash flows in the future, lenders will not and should not. In fact, I cannot think of a better case of a company that is positioned to raise fresh equity to fund growth than Tesla, a company that equity investors love and have shown that love by pushing stock prices to record highs. Issuing shares to fund investment needs will increase the share count at Tesla by about 3-4% (which is what you would expect to see with a $1.5 billion equity issue) but that is a far better choice than borrowing the money and binding yourself to make interest payments. There will be a time and a place for Tesla to borrow money, later in its life cycle, but that time and place is not now. If Tesla is dead set on not raising its share count, there is perhaps one way in which Tesla may be able to eat its cake and have it too, and that is to exploit the dilution bogeyman's blind spot, which is a willingness to overlook potential dilution (from the issuance of convertibles and options). In fact, why not issue long term, really low coupon convertible bonds, very similar to this one from 2014, a bond only in name since almost all of its value came from the conversion option (which is equity with delayed dilution)?

Conclusion

The Tesla story continues to evolve, and there is much in the story that I like. It is changing the automobile business, a feat in itself, and it is starting to deliver on its production promises. The next year may be manufacturing hell, but if the company can make its through that hell and find ways to deliver the tens of thousands of Tesla 3s that it has committed to delivering, it will be well on its way. I still find the stock to be too richly priced, even given its promise and potential, for my liking, but I understand that many of you may disagree. That said, though, I do think that the company's decision to use debt to fund its operations makes no sense, given where it is in the life cycle.

YouTube Video

Previous Blog Posts

Tesla: It's a story stock, but what's the story? (July 2016)

Spreadsheet Attachments

Every decade or two, the political class in the United States wakes up to the reality that the US tax code, as written, is an abomination that encourages and rewards bad behavior, and works on a tax reform package. In each iteration (and I have had a front row seat with the 1986, 1993 and 2001 attempts), the reformers start with the claim that the changes they make will make the system âfairerâ and âsimplerâ, with the added bonus of increasing economic growth. And with each one, the end result is that we end up with a system that is more complex and less fair. I am not a utopian and I understand that tax reform is a political exercise where different interests have to be balanced, but as we start to see the contours of the 2017 reform package, the big question becomes whether, on balance, it does more good than bad. As with prior tax debates, this one follows a predictable path, with support or opposition to the package, depending on who is initiating the reform. Since this version of tax reform comes from Republicans, Democrats are vehement that this reform will benefit the rich and devastate the middle class. The Republicans are just as assertive in their claims that this reform will help US companies compete better in the global economy, and increase economic growth. I would love to tell you that I am completely unbiased on this issue, but I cannot, because no one is objective when it comes to taxes. We all have our priors on taxes and look for data and evidence to back up those preconceptions. Nevertheless, my intent in this post is to start with a general assessment of how taxes affect value and to then look at both the current and proposed corporate tax models, with the objective of evaluating how the planned changes will affect value at companies.

Taxes and Value
To understand how the tax code affects the value of a business, let's go back to basics, and link the value of a business to three component parts: the cash flows generated from existing assets, the value of future growth and a risk adjustment, usually taking the form of a cost of capital or discount rate.

Where does the tax rate show up in value? Everywhere, since each of these drivers is affected by not just the tax rate, but also by other provisions in the tax code.

Cash flows from existing investments: The cash flow from existing investments is estimated by starting with after-tax operating income and then subtracting out the reinvestment needed to sustain future growth. Since the cash flow is an after-tax cash flow, the effective tax rate paid by a firm will affect that cash flow, with higher effective tax rates resulting in lower after-tax cash flows. The statutory tax rate in the tax code is a driver, albeit not the only one, of the effective tax rate, but so are the provisions of the code that relate to the taxation of foreign income, as well as tax credits and special tax deductions that are directed at specific sectors.
Cost of capital (or discount rate): The cost of capital is a weighted average of the cost of equity and after-tax cost of debt, with the weights reflecting how much of each is used to fund operations. The most direct effect of the tax code arises from its tilt being towards debt, in much of the world. In particular, the tax benefit of debt takes the form of tax deductible interest expenses and the benefits of borrowing will increase with the statutory tax rate (or the marginal tax rate). There are more subtle effects, as well, that come from how the tax code treats investment income in the hands of investors, since changing tax rates on dividends and capital gains can affect the price charged by investors for taking equity risk (i.e., the equity risk premium) and altering the tax rates on interest income earned by investors can affect the price charged by investors in the bond market (i.e., default spreads).
Value of growth: The value of growth can be traced back to the amount that companies reinvest back into themselves (measured as a reinvestment rate) and the excess returns generated on those investments (captured as an excess return, or the difference between return on invested capital and the cost of capital). The tax code can affect both the reinvestment rate and excess returns, with provisions either encouraging or discouraging more investment and the after-tax earnings showing up in the return on capital and excess returns. It is on this dimension that the effects of changes in the tax code become most unpredictable, since they affect both returns and costs of capital. Lwering the statutory tax rate can increase after-tax cash flows and returns but also increase the cost of capital, by reducing the tax benefits from debt.

The figure below captures the full picture of how taxes affect almost every input into value, and thus value.

The Current Tax Code
It is no secret that I think that the current US tax code is a mess, creating perverse incentives to under invest in the US and over borrow, and from that perspective, I welcome change. To see how the current tax code plays out in the numbers, I have taken the picture where I have connected taxes to value and looked at the tax code, as it exists today.

The US has one of the highest statutory tax rates for corporate income in the world, at 35% (and this is before state and local taxes, which push it up to 40%) and it combines this rate with a âglobalâ tax model, where it aims to tax foreign income earned by US companies, at the US tax rate, after allowing a credit for foreign taxes paid. In theory, then, a US company that earns income in a foreign market with a 20% corporate tax rate would first pay those taxes and then pay an extra 15% (the difference between the US marginal rate of 35% and the foreign country's tax rate of 20%) to the US government. In practice, this seldom happens because the US also has a provision in the code that specifies that this extra tax is due only when foreign income is remitted back to the US. The result is no surprise. US multinationals have held off on remitting foreign income back to the US, resulting in âtrapped cashâ of $2.5 trillion or more, âtrappedâ because this cash cannot be invested back in the US or used to pay dividends or buy back stock. This behavior also, in large part, explains why the aggregate effective tax rate paid by US companies in 2016 amount was just above 26%, well below the statutory tax rate. At the same time, the high statutory tax rate encourages US companies to borrow and often in the US, where the tax benefits from debt are the highest (because of the high marginal tax rate). At the start of 2017, non-financial service US companies funded themselves with a debt ratio of 26.3%, partly because the after-tax cost of debt (at 2.22% for the typical US company) was so much lower than the average cost of equity of 8.59%. Finally, the US taxes dividends and capital gains income at a maximum rate of 23.8%, at the investor level, lower than the federal tax rate of 40% (at the highest bracket) that these investors pay on their other income (including earned and interest income).

The Proposed Tax Code
There is many a slip between the cup and the lip and I am sure that there will not only be many changes that will be made between now and the eventual legislation, but also a chance that there may be no change at all. At least, as described by its proponents last week, there are four significant changes being planned to the tax code:

Statutory Tax Rate: If this reform passes in the current form, the statutory tax rate for corporate income generated in the United States will become 20%, almost halving the existing statutory tax rate of 35%.
Foreign Income: In almost as significant a shift, the US will shift to a territorial tax model, used by most other countries in the world, resulting in foreign income being taxed at the foreign tax rate, with no additional assessments for US taxes. Thus, if a corporation generates income in a country with a 15% tax rate, it will pay the 15% in taxes but no more. Twinned with this change, and perhaps with the intent of generating some revenues, there will be a one-time tax that will be assessed on trapped foreign income (rumored to be about 10%), and after the tax is paid, the cash will be effectively untrapped, to be used for new investments, dividends and stock buybacks.
Expensing & Capitalizing: In an upending of accounting tradition, the tax code will allowing for the expensing of capital investments, at least for tax purposes, for a period of five years. Thus, rather than amortize/depreciate these expenses, which spreads the tax benefits over time, companies will get the tax deduction up front, which increases value.
Interest Expense Deduction: While there were rumors initially that the entire interest tax deduction would be done away with, it looks more likely that there will be limits put on how much interest expense will be deducted for tax purposes, and only for some types of corporations.

In the table below, I take each of these changes and look at the potential impact on after-tax cash flows, the value of growth and the cost of capital:

	After-tax Cash Flows	Cost of Capital	Value of Growth
1. Lower Statutory tax rate on US income	Lower effective tax rate, leading to higher after-tax cash flows and returns on capital. Bigger effect on firms that derive most or all of their income in US.	Lower tax benefits from debt, raising after-tax cost of debt & capital, and more so for firms with a lot of debt.	Depends on how much return on capital changes, relative to cost of capital. Firms with little debt & high effective tax rates will see biggest benefit and firms with high debt & low effective tax rates will be hurt.
2. Taxes on Foreign income	Lower effective tax rate & higher after-tax cash flows. Bigger effect on firms that derived & repatriated substantial foreign income.	May induce more borrowing outside US in higher tax countries.	One-time release of trapped cash could increase reinvestment, but value will depend upon whether investments generate excess returns.
3. Expensing & Capitalizing	Reduce cost of investing, by moving tax benefits up front rather than spread over time.	None.	Will increase value of growth at firms with substantial physical assets. Low or no effect at companies with intangible assets.
4. Interest Tax Deduction Limits	None.	Will increase cost of capital at companies that test the limits. (Too much debt or debt in the wrong places)	Will decrease value of growth and more so at firms that violate interest deduction limits.

Overall, if this tax reform is put into the code, you can expect to see after-tax cash flows and returns on capital rise, costs of capital also go up and the effects on the value of growth will vary across companies.

Winners and Losers
Looking at the list of effects, it is clear that not all companies will win with the new tax code but that should come as no surprise and is good news for taxpayers in general. Looking at the big picture, the biggest winners will be companies that have the following features:

Pay high effective tax rates, either because they derive most or all of their income in the US or because they repatriate foreign income
Have low or no debt in their capital structure, thus immunizing themselves from the loss of tax benefits of debt.
Earn healthy returns on capital, which will allow them to reinvest their higher earnings back to generate value.
Have more physical assets than intangible assets, enabling them to get a bigger boost from the immediate expensing of capital expenditures.

To screen for these firms, I used a simple test. Taking all 7000+ publicly traded companies, listed in the US in October 2017, I looked for companies that met the following screens:

Effective tax rate > 30%, the 75th percentile for US companies
Total Debt/EBITDA = 0, i.e., the company has no debt
Return on capital > 20%, the 75th percentile for US companies
Capital expenditures/sales > 2%, the median for US companies

A list of companies that passed all four screens is available at the bottom of this post. Note that these are crude screens, based upon the most recent twelve months of data, and that you could refine them by looking at the averages across time or using other proxies.

The biggest losers will be companies that pay low effective tax rates currently, have substantial debt in their capital structure and low returns on capital. Though some of these firms may gain from the one-time release of trapped cash in overseas locales, that cash will most likely be returned to shareholders in the form of dividends and buybacks and there will be little benefit from new investments, and will be small if the cash balance is small. To find these companies, I looked for the following:

Had effective tax rate < 10%, the 25th percentile for US companies, while also reporting positive taxable income
Had Total Debt/EBITDA >4, the 75th percentile for US companies
Had return on capital < 5%, the 25th percentile of returns on capital for money-making companies

I also eliminate real estate investment trusts and master limited partnerships, which pay no corporate taxes currently, but pass through income to their shareholders, since they will be unaffected by the change in corporate tax rates and may even benefit from having a lower tax rate on pass through income. The list of screened companies is at the bottom of the post but here again, there are refinements that you could add to come up with a better listing of companies.

As for the overall market, if this tax reform comes into effect, the aggregate effective tax rate will decrease, pushing up after-tax earnings, cash flows and returns on capital. The cost of capital will increase, as the cost of debt goes up, but that increase should be small and become smaller as companies adjust to the new tax code, reducing debt. There are two unknowns that will determine the effect on aggregate equity value. The first is the impact that the reform will have on real economic growth in the US since higher real growth will allow firms to generate higher earnings, cash flows and value. The second is how it will affect interest rates, both through the effects on real growth as well as on budget deficts in the future. I am no market timer but while I see this tax package as a net positive for markets, I donât see it, standing alone, as an impetus for a new bull market. That has to come from other fundamentals changing.

Taking Stock: The Good and the Bad
I think that US tax code is vastly over due for change and I think that there are components of this tax reform package that move us in the right direction. By lowering the US statutory tax rate on corporate income towards that of most other industrialized countries and shifting from a global to a territorial tax system, the reform package moves the US towards a healthier system, where companies will spend less time on transfer pricing and managing trapped cash, and more on core businesses. I also think that the changes that are designed to reduce the tax tilt towards debt are sensible and will hopefully shift the focus of corporate restructuring from recapitalization (where the bulk of the value comes from increasing debt) to real operating changes. There are changes in this tax reform, though, that will create costs and unintended consequences.

1. Tax Books versus Reporting Books: I understand the motives behind the immediate expensing of capital expenditures, but it will make the gap between reporting books and tax books into a chasm. Companies will eagerly expense their capital investments, in their tax books, report low income and pay low taxes, but will keep to GAAP rules in their reporting books, with the only clue to the divergence being very low effective tax rates.

2. Divergent Tax Rates: I remember a time when individual investors were taxed at rates as high as 70%, capital gains were taxed at 28% and corporations were taxed at 40%, and the tax game playing that those divergent tax rates created. In fact, the 1986 tax reform act was specifically focused on eliminating these differences, trying to bring the tax rate to 28% for all income. This tax reform act moves us in the opposite direction, creating divergent tax rates (federal) again:

While most wage earners have no choice but to pay the individual earned income tax rate, a business owner will now pay very different taxes, depending on whether he or she files as an individual, a partner in a business or as a corporation. I know that the reform act plans to counteract this by requiring owners of pass through entities to pay themselves salaries (which will be taxed as individual earned income), but I, for one, donât feel comfortable, asking the revenue authorities to make judgments on what comprises âreasonableâ salaries.

My Tax Reform Package
I am not a tax expert, but if I were given a chance, there are a few changes that I would make to this package. First, I would eliminate the provision on the expensing of capital equipment, since the benefits in terms of additional corporate investment will be small, relative to the costs of the complexity that it will add to financial statements. Second, I would try to push for convergence in tax rates on all types of income (investment, earned, pass through and corporate income), since that will reduce the incentives to play tax games and I would .make the targeted tax rate about 25% (to keep it close to corporate tax rates elsewhere in the world). Third, I would remove the tax credits and deductions that have been added over time to the tax code; they skew business decisions and almost never accomplish the objectives that they were designed to accomplish. Fourth, I would start a weaning away from debt, by putting limits on interest tax deductions that would become more stringent over time. To those who would accuse me of being politically naive, since this package would never pass, I plead guilty. To those who would argue that I am giving too much away to the rich (who will see their marginal tax rates cut from 39.6% to 25%), my answer is that no matter how egalitarian you make your tax code, the very rich will find a way to pay little in taxes and all you will do is enrich tax lawyers and tax havens, on that path.

YouTube Video

The Tax Reform Proposal

The 2017 Tax Reform Proposal (in outline)

Data Links

Effective Tax Rates by Industry (for US companies)

Blog Posts on Taxes

Tax Winners (High effective tax rate + No debt + High Return on capital + High cap ex/sales)

Company Name	Exchange:Ticker	Effective Tax Rate	Return on Capital	Cap Ex/Sales
Ulta Beauty, Inc. (NasdaqGS:ULTA)	NasdaqGS:ULTA	35.88%	132.46%	7.85%
Anika Therapeutics, Inc. (NasdaqGS:ANIK)	NasdaqGS:ANIK	35.31%	14.36%	7.24%
AAON, Inc. (NasdaqGS:AAON)	NasdaqGS:AAON	31.87%	23.57%	7.19%
R1 RCM Inc. (NasdaqCM:RCM)	NasdaqCM:RCM	49.65%	63.13%	6.87%
Sanderson Farms, Inc. (NasdaqGS:SAFM)	NasdaqGS:SAFM	34.40%	20.84%	6.39%
CorVel Corporation (NasdaqGS:CRVL)	NasdaqGS:CRVL	37.90%	33.19%	5.89%
Sturm, Ruger & Company, Inc. (NYSE:RGR)	NYSE:RGR	35.14%	32.01%	5.59%
Texas Pacific Land Trust (NYSE:TPL)	NYSE:TPL	32.37%	106.64%	5.29%
Insteel Industries, Inc. (NasdaqGS:IIIN)	NasdaqGS:IIIN	33.64%	14.02%	5.26%
Capella Education Company (NasdaqGS:CPLA)	NasdaqGS:CPLA	35.72%	21.90%	5.24%
The Boston Beer Company, Inc. (NYSE:SAM)	NYSE:SAM	33.96%	21.91%	4.61%
Exponent, Inc. (NasdaqGS:EXPO)	NasdaqGS:EXPO	30.07%	17.05%	4.33%
Monster Beverage Corporation (NasdaqGS:MNST)	NasdaqGS:MNST	33.37%	21.83%	3.84%
Zix Corporation (NasdaqGS:ZIXI)	NasdaqGS:ZIXI	42.00%	13.09%	3.42%
Trex Company, Inc. (NYSE:TREX)	NYSE:TREX	33.73%	53.07%	3.27%
PetMed Express, Inc. (NasdaqGS:PETS)	NasdaqGS:PETS	37.20%	26.32%	3.14%
Omega Flex, Inc. (NasdaqGM:OFLX)	NasdaqGM:OFLX	32.04%	31.57%	3.03%
Jewett-Cameron Trading Company Ltd. (NasdaqCM:JCTC.F)	NasdaqCM:JCTC.F	40.00%	13.08%	2.58%
Dorman Products, Inc. (NasdaqGS:DORM)	NasdaqGS:DORM	36.84%	18.37%	2.45%
F5 Networks, Inc. (NasdaqGS:FFIV)	NasdaqGS:FFIV	32.60%	35.44%	2.35%
Lancaster Colony Corporation (NasdaqGS:LANC)	NasdaqGS:LANC	34.30%	22.97%	2.25%
Nutrisystem, Inc. (NasdaqGS:NTRI)	NasdaqGS:NTRI	31.21%	45.46%	2.17%
Collectors Universe Inc. (NasdaqGM:CLCT)	NasdaqGM:CLCT	35.76%	110.70%	2.01%

Tax Losers (Low Effective Tax Rate + High Debt + Low Return on Capital)

Company Name	Exchange:Ticker	Industry Group	Effective Tax Rate	Total Debt/EBITDA	Return on Capital
Lions Gate Entertainment Corp. (NYSE:LGF.A)	NYSE:LGF.A	Consumer Discretionary (Primary)	0.00%	9.00	3.38%
AV Homes, Inc. (NasdaqGS:AVHI)	NasdaqGS:AVHI	Consumer Discretionary (Primary)	8.63%	11.60	4.36%
Smart & Final Stores, Inc. (NYSE:SFS)	NYSE:SFS	Consumer Staples (Primary)	0.00%	4.88	3.19%
Orchids Paper Products Company (AMEX:TIS)	AMEX:TIS	Consumer Staples (Primary)	0.00%

I am an Amazon Prime member and have been one for a long time, and I am completely hooked. Not only do I (and my family) use Amazon Prime for items ranging from tissue paper to big screen televisions, but it has become my go-to for every possession that I need in my working and personal life. In fact, I know (and am completely at peace with the fact) that it has subtly affected my buying, as I substitute slightly more expensive Prime items for non-Prime equivalents, even when I shop on Amazon. It is not just the absence of shipping costs that draws me to Prime, but the reliability of delivery and the ease of return. In short, it makes shopping painless. As I tally how much we save each year because of Prime and weigh it against the $99 that we pay for it, I am convinced that we are getting far more value from it than what we pay, and that leads to an interesting follow up. If many of the 85 million other Prime members in October 2017 are getting the same bargain that we are, is this not an indication that Amazon has not just under priced Prime, but is perhaps selling it below cost? As someone who has wrestled with valuing Amazon over the last 20 years, I have learned never to under estimate the company. In this post, I would like to take the process I used to value a user at Uber and apply it to value not just a Prime member to Amazon but the collective value of Amazon Prime to the company.

The Growth of Amazon Prime

Amazon introduced Prime in 2005 and the service was slow to take off. At the end of 2011, only about 4% of Amazon customers were Prime members. In the years since, though, the service has seen explosive growth:

As I have noted with my earlier posts on crypto currencies, in general, and bitcoin, in particular, I find myself disagreeing with both its most virulent critics and its strongest proponents. Unlike Jamie Dimon, I don't believe that bitcoin is a fraud and that people who are "stupid enough to buy it" will pay a price for that stupidity. Unlike its biggest cheerleaders, I don't believe that crypto currencies are now or ever will be an asset class or that these currencies can change fundamental truths about risk, investing and management. The reason for the divide, though, is that the two sides seem to disagree fundamentally on what bitcoin is, and at the risk of raising hackles all the way around, I will argue that bitcoin is not an asset, but a currency, and as such, you cannot value it or invest in it. You can only price it and trade it.

Assets, Commodities, Currencies and Collectibles
Not everything can be valued, but almost everything can be priced. To understand the distinction between value and price, let me start by positing that every investment that I will look at has to fall into one of the following four groupings:

Cash Generating Asset: An asset generates or is expected to generate cash flows in the future. A business that you own is definitely an asset, as is a claim on the cash flows on that business. Those claims can be either contractually set (bonds or debt), residual (equity or stock) or even contingent (options). What assets share in common is that these cash flows can be valued, and assets with high cash flows and less risk should be valued more than assets with lower cash flows and more risk. At the same time, assets can also be priced, relative to each other, by scaling the price that you pay to a common metric. With stocks, this takes the form of comparing pricing multiples (PE ratio, EV/EBITDA, Price to Book or Value/Sales) across similar companies to form pricing judgments of which stocks are cheap and which ones are expensive.
Commodity: A commodity derives its value from its use as raw material to meet a fundamental need, whether it be energy, food or shelter. While that value can be estimated by looking at the demand for and supply of the commodity, there are long lag and lead times in both that make that valuation process much more difficult than for an asset. Consequently, commodities tend to be priced, often relative to their own history, with normalized oil, coal wheat or iron ore prices being computed by averaging prices across long cycles.
Currency: A currency is a medium of exchange that you use to denominate cash flows and is a store of purchasing power, if you choose to not invest. Standing alone, currencies have no cash flows and cannot be valued, but they can be priced against other currencies. In the long term, currencies that are accepted more widely as a medium of exchange and that hold their purchasing power better over time should be see their prices rise, relative to currencies that don't have those characteristics. In the short term, though, other forces including governments trying to manipulate exchange rates can dominate. Using a more conventional currency example, you can see this in a graph of the US $ against seven fiat currencies, where over the long term (1995-2017), you can see the Swiss Franc and the Chinese Yuan increasing in price, relative to the $, and the Mexican Peso, Brazilian Real, Indian Rupee and British Pound, dropping in price, again relative to the $.
Collectible: A collectible has no cash flows and is not a medium of exchange but it can sometimes have aesthetic value (as is the case with a master painting or a sculpture) or an emotional attachment (a baseball card or team jersey). A collectible cannot be valued since it too generates no cash flows but it can be priced, based upon how other people perceive its desirability and the scarcity of the collectible.

Viewed through this prism, Gold is clearly not a cash flow generating asset, but is it a commodity? Since gold's value has little to do with its utilitarian functions and more to do with its longstanding function as a store of value, especially during crises or when you lose faith in paper currencies, it is more currency than commodity. Real estate is an asset, even if it takes the form of a personal home, because you would have had to pay rental expenses (a cash flow), in its absence. Private equity and hedge funds are forms of investing in assets, currencies, commodities or collectibles, and are not separate asset classes.

Investing versus Trading

The key is that cash generating assets can be both valued and priced, commodities can be priced much more easily than valued, and currencies and collectibles can only be priced. So what? I have written before about the divide between investing and trading and it is worth revisiting that contrast. To invest in something, you need to assess its value, compare to the price, and then act on that comparison, buying if the price is less than value and selling if it is greater. Trading is a much simpler exercise, where you price something, make a judgment on whether that price will go up or down in the next time period and then make a pricing bet. While you can be successful at either, the skill sets and tool kits that you use are different for investing and trading, and what makes for a good investor is different from the ingredients needed for good trading. The table below captures the difference between trading (the pricing game) and investing (the value game).

	The Pricing Game	The Value Game
Underlying philosophy	The price is the only real number that you can act on. No one knows what the value of an asset is and estimating it is of little use.	Every asset has a fair or true value. You can estimate that value, albeit with error, and price has to converge on value (eventually).
To play the game	You try to guess which direction the price will move in the next period(s) and trade ahead of the movement. To win the game, you have to be right more often than wrong about direction and to exit before the winds shift.	You try to estimate the value of an asset, and if it is under(over) value, you buy (sell) the asset. To win the game, you have to be right about value (for the most part) and the market price has to move to that value
Key drivers	Price is determined by demand & supply, which in turn are affected by mood and momentum.	Value is determined by cash flows, growth and risk.
Information effect	Incremental information (news, stories, rumors) that shifts the mood will move the price, even if it has no real consequences for long term value.	Only information that alter cash flows, growth and risk in a material way can affect value.
Tools of the game	(1) Technical indicators, (2) Price Charts (3) Investor Psychology	(1) Ratio analysis, (2) DCF Valuation (3) Accounting Research
Time horizon	Can be very short term (minutes) to mildly short term (weeks, months).	Long term
Key skill	Be able to gauge market mood/momentum shifts earlier than the rest of the market.	Be able to âvalueâ assets, given uncertainty.
Key personality traits	(1) Market amnesia (2) Quick Acting (3) Gambling Instincts	(1) Faith in âvalueâ (2) Faith in markets (3) Patience (4) Immunity from peer pressure
Biggest Danger(s)	Momentum shifts can occur quickly, wiping out months of profits in a few hours.	The price may not converge on value, even if your value is ârightâ.
Added bonus	Capacity to move prices (with lots of money and lots of followers).	Can provide the catalyst that can move price to value.
Most Delusional Player	A trader who thinks he is trading based on value.	A value investor who thinks he can reason with markets.

As I see it, you can play either the value or pricing game well, but being delusional about the game you are playing, and using the wrong tools or bringing the wrong skill set to that game, is a recipe for disaster.

What is Bitcoin?

The first step towards a serious debate on bitcoin then has to be deciding whether it is an asset, a currency, a commodity or collectible. Bitcoin is not an asset, since it does not generate cash flows standing alone for those who hold it (until you sell it) and it is not a commodity, because it is not raw material that can be used in the production of something useful. The choice then becomes whether it is a currency or a collectible, with its supporters tilting towards the former and its detractors the latter. I argued in my last post that Bitcoin is a currency, but it is not a good one yet, insofar as it has only limited acceptance as a medium of exchange and it is too volatile to be a store of value. Looking forward, there are three possible paths that I see for Bitcoin as a currency, from best case to worst case.

The Global Digital Currency: In the best case scenario, Bitcoin gains wide acceptance in transactions across the world, becoming a widely used global digital currency. For this to happen, it has to become more stable (relative to other currencies), central banks and governments around the world have to accept its use (or at least not actively try to impede it) and the aura of mystery around it has to fade. If that happens, it could compete with fiat currencies and given the algorithm set limits on its creation, its high price could be justified.
Gold for Millennials: In this scenario, Bitcoin becomes a haven for those who do not trust central banks, governments and fiat currencies. In short, it takes on the role that gold has, historically, for those who have lost trust in or fear centralized authority. It is interesting that the language of Bitcoin is filled with mining terminology, since it suggests that intentionally or otherwise, the creators of Bitcoin shared this vision. In fact, the hard cap on Bitcoin of 21 million is more compatible with this scenario than the first one. If this scenario unfolds, and Bitcoin shows the same staying power as gold, it will behave like gold does, rising during crises and dropping in more sanguine time periods.
The 21st Century Tulip Bulb: In this, the worst case scenario, Bitcoin is like a shooting star, attracting more money as it soars, from those who see it as a source of easy profits, but just as quickly flares out as these traders move on to something new and different (which could be a different and better designed digital currency), leaving Bitcoin holders with memories of what might have been. If this happens, Bitcoin could very well become the equivalent of Tulip Bulbs, a speculative asset that saw its prices soar in the sixteen hundreds in Holland, before collapsing in the aftermath.

I would be lying if I said that I knew which of these scenarios will unfold, but they are all still plausible scenarios. If you are trading in Bitcoin, you may very well not care, since your time horizon may be in minutes and hours, not weeks, months or years. If you have a longer term interest in Bitcoin, though, your focus should be less on the noise of day-to-day price movements and more on advancements on its use as a currency. Note also that you could be a pessimist on Bitcoin and other crypto currencies but be an optimist about the underlying technology, especially block chain, and its potential for disruption.

Reality Checks

Combining the section where I classified investments into assets, commodities, currencies and collectibles with the one where I argued that Bitcoin is a "young" currency allows me to draw the following conclusions:

Bitcoin is not an asset class: To those who are carving out a portion of their portfolios for Bitcoin, be clear about why you are doing it. It is not because you want to a diversified portfolio and hold all asset classes, it is because you want to use your trading skills on Bitcoin to supercharge your portfolio returns. Lest you view this as a swipe at cryptocurrencies, I would hasten to add that fiat currencies (like the US dollar, Euro or Yen) are not asset classes either.
You cannot value Bitcoin, you can only price it: This follows from the acceptance that Bitcoin is a currency, not an asset or a commodity. Any one who claims to value Bitcoin either has a very different definition of value than I do or is just making up stuff as he or she goes along.
It will be judged as a currency: In the long term, the price that you attach to Bitcoin will depend on how well it will performs as a currency. If it is accepted widely as a medium of exchange and is stable enough to be a store of value, it should command a high price. If it becomes gold-like, a fringe currency that investors flee to during crises, its price will be lower. Worse, if it is a transient currency that loses all purchasing power, as it is replaced by something new and different, it will crash and burn.
You don't invest in Bitcoin, you trade it: Since you cannot value Bitcoin, you don't have a critical ingredient that you need to be an investor. You can trade Bitcoin and become wealthy doing so, but it is because you are a good trader.
Good trader ingredients: To be a successful trader in Bitcoin, you need to recognize that moves in its price will have little do with fundamentals, everything to do with mood and momentum and big price shifts can happen on incremental information.

Would I buy Bitcoin at $6,100? No, but not for the reasons that you think. It is not because I believe that it is over valued, since I cannot make that judgment without valuing it and as I noted before, it cannot be valued. It is because I am not and never have been a good trader and, as a consequence, my pricing judgments are suspect. If you have good trading instincts, you should play the pricing game, as long as you recognize that it is a game, where you can win millions or lose millions, based upon your calls on momentum. If you win millions, I wish you the best! If you lose millions, please don't let paranoia lead you to blame the establishment, banks and governments for why you lost. Come easy, go easy!

YouTube Video

Past Blog Posts on Crypto Currencies

My last post on Bitcoin got me some push back and I am glad that it did. I would rather be read, and disagreed with, than not read at all. I have been told that I know very little about crypto currencies and that I have much to learn, and I agree. The crux of the disagreements though lay in my classifying Bitcoin as a currency, not as an asset or as a commodity. Since this classification is central to how you should think about investing versus trading, and value versus price, and goes well beyond Bitcoin, I decided to dig deeper into the classification and provide even more ammunition for those who disagree with me to tell me how wrong I am.

Classifying Investment: The What and the Why

We are products of our own world views, and mine, for better or worse, are built around my interest in valuation. It is that perspective that led me to classifying investments into cash flow generating assets, commodities, currencies and collectibles. To value an investment, I need that investment to generate future cashflows (at least on an expected basis) and that was my basis for separating cash flow generating assets (which range the spectrum from a bond to a stock to a business) from the rest.

The pushback that I got did not surprised me, partly because my definition may be at odds with the definitions used by other entities. Accountants, for instance, classify items as assets that I think are pure fiction, such as goodwill. There are others who argue that any investment on which you can make money is an asset, broadening it to include just about everything from baseball cards to government bonds. In fact, crypto currencies have been at the center of many of these disagreements, with the SEC recently deciding to treat ICOs as securities (and thus assets) and the Korean central bank categorizing Bitcoin as a commodity. Since the judgment made by these entities have regulatory and tax consequences, I am sure that they will be debated, discussed and disagreed with.

Why Bitcoin is a currency and not an asset..

One reason that people are uncomfortable drawing the line between currency, commodity and asset is that the line can sometimes shift quickly. Take the US dollar, for instance. Its primary purpose is to serve as a medium of exchange and as a store of value, and it is thus a currency. However, you can lend US dollars to a business or individual and generate interest income. That is true, but it is not the currency that is then the asset, but the loan that you make with it, or the bond that is denominated in it. Building further, if I create a bank that takes in deposits in dollars (and pays an interest rate on them) and lends out those dollars as loans, I have a business and that business is an asset. I can value the loan and the bond based upon the interest rate you earn and the default risk that you face, or the bank, based upon the interest rate spread it earns and the risk of default that it faces on its collective portfolio, but I cannot value the US dollar.

Can I construct investments denominated in Bitcoin or another crypto currency that earn me interest or a return? Of course, but I can do that in any currency, and it is in fact one of the functions of a currency. That does not make Bitcoin an asset! You can already see that the question of whether Initial Coin Offerings (ICO) are currencies or assets becomes trickier, because an ICO can be constructed to give you a share of the ownership in a business (and the cash flows from that business), making it more of an asset than a currency (thus giving credence to the SEC's view that it is a security). The lack of standardization in ICO structures, though, makes it difficult to generalize, since loosely put, an ICO can be constructed to be anything from a donation (at least, according to Kathleen Breitman at Tezos) to quasi common stock (without the voting rights).

A few of you have pointed to the networking benefits that might create value for Bitcoin, but I am afraid that I don't see that as a basis for assigning value to it. A network can become an asset, but only when you can make money off the network. The value of Facebook to me, as an investor, is not that I am part of the Facebook network (I am not, since I have not posted on Facebook in almost three years) but that I get a share of the money made from selling advertising to those on the network. Unless you can trace monetary benefits to being part of the Bitcoin network, there is no value to being part of the network. (Visa and MasterCard are assets, not because they have wide networks and are accepted globally, but because every time they are used, they make 1-2% of the transaction value.) To the argument that Bitcoin miners can make money as the network expands, that value is for providing a service, not for holding Bitcoin.

Why Bitcoin is more currency than commodity

The essence of a currency is that its primary uses are as a medium of exchange or as a store of value. The key to a commodity is that it is an input into a process that has a utilitarian function. Oil and coal are clearly commodities, since they derive their value from the fact that they can be used to produce energy. It is true, as with currencies, that you can create an asset based upon a commodity. A share of an oil well is an asset not because you like or even need oil, it is because you hope to sell the oil to generate cash flows. It is also true that gold is a commodity, but as I noted in the prior post, I think it is more currency than commodity, because the quantity of gold that we have on the face of the earth vastly exceeds whatever utilitarian needs it might serve. It is shiny, durable, makes beautiful jewelry and has some industrial uses, but if that is all we valued gold for, it would be worth a lot less than it is trading for, and there would be less of it around.

The question with Bitcoin then becomes whether it can become (or perhaps already is) like gold. Here is my test: If tomorrow, humanity collectively decided to abandon its attachment to gold as a value store, would its price go to zero? I don't think so, because it does have uses and while its price will drop, it will be priced like based on those uses. Applying the same test to Bitcoin, I am left nonplussed about what value to attach to a digital currency if at the end, no one uses it in transactions, it has no aesthetic value and it produces nothing utilitarian.

A Commodity Argument for Crypto Currencies (but perhaps not for Bitcoin)

Some of you have pointed to Bitcoin's scarcity (created by the hard cap on production) and the fact that time and energy are spent on its production. Scarcity is neither a sufficient nor even a necessary condition for something to be a commodity. Sand is a scarce resource but it is not a commodity because I cannot think of a good use for it; so is bull manure, but that is a discussion for another time and day. The fact that time and energy went into the production of Bitcoin cannot be used to justify paying for it unless you can show that it is necessary for something that does create utility or value. If, as argued by someone who commented on my last post, Bitcoin is a synthetic commodity, I can see that it is synthetic but what conceivable use does it have that makes it a commodity? Therein lies an opening for a âcrypto currency as commodityâ defense, though it works better for crypto currencies like Ethereum than it does for Bitcoin, and it require three building blocks:

Block Chains and Smart Contracts will create large disruptions in businesses: You have to believe that block chains and the smart contracts that emerge from them will replace conventional contracts in many businesses, and that will generate cash flows to the contract providers. Your argument can be based upon either economic (that the transactions costs willl be lower) or security (that the contracts will be more secure) rationales.
Crypto Currencies are the lubricants for smart contracting: The discussion of block chains and crypto currency have become entangled into one discussion, but it is worth remembering that block chains predate crypto currencies and can work with fiat currencies. Thus, you will have to argue that crypto currencies are a necessary ingredient to make smart contracts work efficiently, and that the demand for them will then rise as smart contracting expands.
âYourâ crypto currency will be one of the winners: Even if you can make the first two legs of this argument, it remains an argument for growth in digital or crypto currencies, not an argument for a specific one. To seal the deal, you will have to explain why your crypto currency of choice (Bitcoin, Ethereum etc.) will become the winner or at least one of the winners in the smart contracting currency race, perhaps because it has the âbest technologyâ for smart contracting or has the most buy in by the institutional players in the game.

I think that the first leg of this argument will be easy to make, the second leg a little more difficult and the third leg will need the most convincing. Even if you can show, based upon today's technology, that you have the "best" smart contracting currency, how do you build barriers to entry that prevent you being pre-empted by another innovation or technology down the road?

Conclusion

The game is still early, and there is much that we do not know about crypto currencies. I remain willing to learn both from people who know more than I do (and there are many out there) as well as events on the ground. As you listen to arguments for or against crypto currencies, my only advice is that you go back to basics about the needs that they are filling and that you ask questions about their long term staying power. I think it is also time for us to separate arguments about block chains/smart contracts from arguments about crypto currencies, since you can have one without the other, and to differentiate between crypto currencies, rather than defend them or abandon them all, as a bundle. To me, Bitcoin, Ethereum, Ripple and ICOs are different enough from each other, not only in structure but also in terms of end game, that they need to be assessed independently.

YouTube Video

Past Blog Posts on Crypto Currencies

Every year, since 1992, I have spent the first week of my year, paying homage to the numbers gods. I collect raw accounting and market data from a variety of raw data providers, and I am grateful to all of them for making my life easier, and I summarize the data on many dimensions, by geography, by industry and by market capitalization. That summarized data, for the start of 2018, can be found on my website, as can the archived data from prior years.

The What?

My dataset includes every publicly traded firm that has a market price available for it, in my raw dataset, and at the start of 2018, it included 43,848 firms, up from the 42,678 firms at the start of 2017. To the question of why I don't restrict myself to just the biggest, the most liquid or the most heavily followed firms, my answer is a statistical one. Any decision that I make on screening the data or sampling will create biases that will color my results, and while I will not claim to be bias-free (no one is), I would prefer to not initiate it with my sampling.

There are 135 countries that are represented in the data, though many have only a handful of firms that are incorporated there. That said, it is worth noting that while the companies are classified by country of incorporation, many have operations in multiple countries. I have classified my firms into five "big" groups: the United States, Europe (EU, UK), Emerging Markets, Japan and Australia/Canada/New Zealand. The pie chart below provides the breakdown:

Download spreadsheet

Since the emerging market grouping includes firms from Asia, Latin America, Africa and Eurasia, I also have the data for sub-groups including India, China, Small Asia (other than India, China and Japan), Latin America, Africa & MidEast and Russia/Eurasia. That is pictured in the second pie chart above.

Within each geographic group, I break the companies down into 94 industry groupings and the numbers in each grouping are summarized at this link. While some would prefer a finer breakdown, I prefer this coarser grouping because it allows for larger sample sizes, especially as I go to sub-groups. Finally, I compute a range of numbers for each grouping, reflecting my corporate finance biases, and classify them into risk, profitability, leverage and cash return measures in the table below:

Risk Measures	Cost of Funding	Pricing Multiples
1. Beta	1. Cost of Equity	1. PE &PEG
2. Standard deviation in stock price	2. Cost of Debt	2. Price to Book
3. Standard deviation in operating income	3. Cost of Capital	3. EV/EBIT, EV/EBITDA and EV/EBITDA
4. High-Low Price Risk Measure		4. EV/Sales and Price/Sales
Profitability	Financial Leverage	Cash Flow Add-ons
1. Net Profit Margin	1. D/E ratio & Debt/Capital (book & market) (with lease effect)	1. Cap Ex & Net Cap Ex
2. Operating Margin	2. Debt/EBITDA	2. Non-cash Working Capital as % of Revenue
3. EBITDA, EBIT and EBITDAR&D Margins	3. Interest Coverage Ratios	3. Sales/Invested Capital
Returns	Dividend Policy	Risk Premiums
1. Return on Equity	1. Dividend Payout & Yield	1. Equity Risk Premiums (by country)
2. Return on Capital	2. Dividends/FCFE & (Dividends + Buybacks)/ FCFE	2. US equity returns (historical)
3. ROE - Cost of Equity
4. ROIC - Cost of Capital

The links in the table will lead you to the html versions of the US data, but you can find the excel versions of this data and for the other groupings on my webpage. Since I report more than 150 data items, you may have to work to find what you are looking for but it (or a close variant) should be available somewhere on the site. Since there can be variations on how metrics are computed (like EV/EBITDA or even PE), I summarize my definitions at this link.

The Why?

Much as I would like to claim that my data sharing is driven by altruism and making the world a better place, the reasons are more prosaic. I do this for myself. I enjoy analyzing the data for many reasons:

Perspective: As our access to data increases, partly because of increased information disclosure on the part of firms, and partly because technology has made it easier to download data, it is ironic that we are more likely to develop tunnel vision now than before we had access to this data. When valuing individual companies, I find that knowing the industry and geographic averages gives me perspective on the numbers that I use for the company. Thus, when valuing Indofoods, an Indonesian food processing company, I can look at typical profit margins for food processing companies in South East Asia, in making my estimates for inputs, and compare my valuation to the pricing of other South East Asian food companies, when I am done.
Rules of Thumb: Investing is full of rules of thumb that we devised in a different time for a different market, but still are used by investors, often without question. The notion that a stock that trades at a PEG ratio less than one or at a price less than its book value is cheap is deeply engrained in value investing books, but is it true? Looking at the cross sectional distributions of PEG and Price to Book ratios across all companies should give us the answer and allow us to eliminate the rules of thumb that no longer work.
Curiosity: There are questions that all of us have about companies that the numbers can help answer. Do US companies pay less in taxes than their foreign counterparts? Does growth create or destroy value at companies? The answers to these questions are in the numbers and I find that they provide an antidote to experts who try to pass off opinions as facts.
Trends and Shifts: Companies change over time, albeit slowly, and these changes have consequences not just for investors, but for governments, taxpayers and workers. One reason that I do not make jarring changes in the way that I classify and report my numbers is to see how these numbers change over time.

In the next two weeks, I will try to summarize what I learn from the data about corporate investment, financing and dividend policy in a series of posts that I have tentatively listed at the end of this post, starting with an update on US equities (and risk premiums) and ending with the a look at market pricing multiples at the end of 2017. Along the way, I will grapple with the rise of crypto currencies and what they might or might not mean for valuation. The motivations for creating these datasets are selfish but I find it pointless to keep them to myself. After all, there is no secret sauce in this data that will lead me to riches, and nothing that someone else with access to the raw data could not generate themselves. If, in the process, a few people are able to use my data in their analyses, I consider them deposits in my "good karma" bank.

The Quirks

Each year that I update the data, there are four challenges that await me. The first relates to data timing, where I try to put myself in the shoes of an investor making investment choices on January 2, 2018. The second is how best to deal with missing data, par for the course since my dataset includes some very small companies in under developed markets. The third is to clean up after the accountants, who are not always consistent in their rules across sectors and geographies. The fourth and final challenge is to find and correct mistakes in the data.

Timing: All of the data that I have used in my analysis was collected after the close of trading on the last trading day of 2017 (December 29 for most markets) and reflects the most updated data, as of that day. That said, it is worth noting that not all data gets updated at the same rate, with market-set numbers (risk free rate, stock prices, risk premiums) being as of close of trading at the end of the year, but accounting numbers reflecting the most recent financial reports (from October, November and December of 2017). The accounting numbers that I use to compute my financial and pricing ratios are therefore trailing 12-month numbers, if they are updated every quarter, or even 2016 numbers, if they are not updated.
Missing Data: Information disclosure requirements vary widely across markets and since my dataset spans all markets, there are some items that are available in some markets and not in others. Rather than eliminate companies with missing data, which will both decimate and bias my sample, I keep them in the sample and deal with them the best that I can. For instance, US companies report stock based compensation as an expense item but many non-US companies do not. I report stock based compensation as a percent of total revenues in every market but they are close to reality only in the US data.
Accounting inconsistencies: I have argued in prior posts that accountants are inconsistent in their treatment of capital expenditures and debt across companies, treating the biggest capital expenditures (R&D) at technology and pharmaceutical companies as operating expenses and ignoring the primary debt (leases) at retail and restaurant companies. Rather than wait for accounting rules to come to their senses, which may take decades, I have capitalized both R&D and lease commitments for all companies and that has consequences for my earnings, invested capital and debt numbers.
Data mistakes: Working with a spreadsheet with 43,848 companies and 150 data items, I am sure that there are mistakes that have found their way into my summaries, notwithstanding my attempts to catch them. Some of these mistakes are mine but some reflect errors in the raw data. The datasets that are least likely to be affected by mistakes are the US and Global dataset, where I have a combination of the law of large numbers and good disclosure backing me up. Needless to say, if you do find mistakes, please draw my attention to them.

The Caveats

If you find my data useful in your investing, valuation or corporate finance analysis, you are welcome to partake of it. That said, as a number cruncher who both loves numbers and views them with caution, here are a few things to keep in mind.

Numbers â Facts: While the numbers, once reported, look precise, they are not facts. Thus, when you look at the debt ratios that I report for a sector, it is worth emphasizing that I have capitalized lease commitments and added them to all interest bearing debt (short and long term) to arrive at total debt, yielding a different number than what you may see on a different service. I have tried to be as transparent as I can in making my estimates but they reflect my judgment calls.
Past is not always prologue: There are some numbers where I report historical trend lines and averages. That is not because I am a die-hard believer in mean reversion, the driving force in many investment philosophies. I believe that knowing history is useful in investing, but trusting it to repeat itself is dangerous.
Just because everyone does it does not make it right: As you look at the datasets, you will see patterns in investment, financing and dividend policy in sectors. Some sectors, such as telecommunications, are more debt funded than others, say pharmaceuticals, and other pay more dividends (utilities) than others (technology). While there are often good reasons for these differences, there are also bad ones, with inertial on top of that list. The reality is that there are established corporate finance policies in many sectors that no longer make sense, because the sectors have changed fundamentally over time.

As you browse through the numbers, you will notice that I report almost no numbers at the company level. While I do have that data, I am constrained from sharing that data, because I risk stepping on the toes and the legal rights of my raw data providers.

Conclusion

At the end of my data week, I am both exhilarated and exhausted, exhilarated because I can now analyze the data and exhausted because even a number cruncher can get tired of working with numbers. There is information in this data but it will take more care than I have given it so far, but I have the rest of the year to spend looking for those nuggets.

YouTube Video

Links

Data Update Posts

January 2018 Data Update 1: Numbers don't lie, or do they?
January 2018 Data Update 2: US Equities, Let the Good Times Roll!
January 2018 Data Update 3: A New Tax Code - Value Consequences?
January 2018 Data Update 4: The Currency Question
January 2018 Data Update 5: Country Risk
January 2018 Data Update 6: Cost of Capital - A Global Update
January 2018 Data Update 7: Growth and Value - Investment Returns
January 2018 Data Update 8: Debt and Value
January 2018 Data Update 9: The Cash Harvest - Dividend Policy
January 2018 Data Update 10: The Pricing Prerogative

If you were an investor in US stocks, 2017 was a very good year for you. Faced with a wall of macro economic and political worries, the US equity market proved more than up to the challenge and delivered good returns, proving the experts wrong again. Looking back at the year, the word that I used to describe US equities at the start of last year, which was "resilient", best described US stocks in 2017 as well. As we enter 2018 with US stocks at historical highs, worries remain, but stocks are on a healthier footing now, than a year ago, in terms of fundamentals. At the same time, the long promised surge in T.Bond rates that the Fed watchers promised us would happen in 2017 was nowhere to be seen, which raises interesting questions about whether we should waste our time listening to either stock market prognosticators and Fed watchers. But then again, without them, how would CNBC fill all its time?

The Year that Was

The best way that I can think of mapping out the year is to look at how stocks and bonds performed on a month by month basis through the entire year. In the table below, I look at returns on the S&P 500 and on bonds, through the year:

Start of month	S&P 500	Price Appreciation in Month	T.Bond Rate	Monthly return
1-Jan-17	2239		2.45%
1-Feb-17	2279	1.79%	2.47%	0.03%
1-Mar-17	2364	3.73%	2.40%	0.82%
1-Apr-17	2363	-0.04%	2.39%	0.29%
1-May-17	2384	0.89%	2.30%	1.00%
1-Jun-17	2412	1.17%	2.21%	0.99%
1-Jul-17	2423	0.46%	2.30%	-0.61%
1-Aug-17	2470	1.94%	2.30%	0.19%
1-Sep-17	2418	-2.11%	2.12%	1.80%
1-Oct-17	2519	4.18%	2.33%	-1.68%
1-Nov-17	2575	2.22%	2.37%	-0.16%
1-Dec-17	2648	2.83%	2.42%	-0.24%
1-Jan-18	2674	0.98%	2.41%	0.29%
Dividend Yield		2.22%		-
Total Return		21.65%		2.80%

The return on the S&P 500 for the year was 21.65%, with price appreciation accounting for 19.43% in returns and dividend yield representing the remaining 2.22%. In fact, the S&P 500 increased in ten of twelve months, with August representing the only significant down month; stocks were barely down in April. The T.Bond rate stayed within a tight bound for much of the year, with rates dropping to 2.12% at the start of September, from 2.45% at the start of the year, before rebounding to end the year little changed at 2.41%. Given that rates changed so little over the course of the year, the return on a 10-year T.Bond, with coupon and price change included, was 2.80%.

Putting 2017 in perspective, adding the 2017 returns for stocks, T.Bonds and T.Bills to the historical data yields the following historical annual average returns for the three asset classes:

Download historical returns spreadsheet

For devotees of mean reversion (and I am not one), this table becomes the basis for estimating equity risk premiums, with the geometric average returns pointing to an equity risk premium of 4.77% over the 10-year T.Bond rate, i.e., the difference between the geometric average return on stocks (9.65%) and the geometric average return on bonds (4.88%).

When stocks have as good a year as they did in 2017, you would normally expect the fundamentals to weaken, at least relative to prices, but stocks ended the year in a healthier state than at the start. That can be seen by comparing the earnings, dividends and cash returned in 2017, by the S&P 500 companies, relative to 2016:

	2016	2017	% Change for year	10-Year Average
Earnings	106.26	124.94	17.58%	93.00
Dividends	45.7	49.73	8.82%	32.76
Dividends + Buybacks	108.02	109.89	1.73%	82.28
Payout Ratio	43.01%	39.80%		42.05%
Cash Return Ratio	101.66%	87.95%		89.35%

Note that earnings almost kept track with stock prices for the year, but the change is in the cash returned, where you saw a leveling off in the buyback boom. While that would normally be a negative for stocks, the draw back in buybacks left stocks looking healthier by reducing the cash returned as a percent of earnings from an unsustainable 101.66% in 2016 to 87.95% in 2017.

To evaluate whether the T.Bond rate is at a level that can be justified by fundamentals, I fall back on an approach that I have used before, where I compare the T.Bond rate to an intrinsic risk free rate that I compute by adding the inflation rate for the year to real growth rate in the economy (GDP real growth rate). While those numbers are still not final for 2017, using the most recent values for both allows for an update of my intrinsic interest rate chart:

Download spreadsheet with data

The intrinsic risk free rate, using the estimated numbers as of January 1, 2018, is 4.50%, 2.09% higher than the US treasury bond rate of 2.41%, suggesting that there will be upward pressure on the US treasury bond rate over the next year.

Looking Forward

While it is tempting to continue to dissect last year's numbers, it is healthier to turn our attention to the future. It is why I have increasingly moved away from using historical risk premiums, like the 4.77% premium that I computed by looking at the 1928-2017 return table, and towards implied equity risk premiums, where I back out what investors are demanding as a premium for investing in stocks by looking at how much they pay for stocks and what they expect to generate as cash flows. (Think of it as an IRR for stocks, analogous to the yield to maturity on a bond). At the start of 2018, putting this approach into play, I estimated an equity risk premium of 5.08% for the S&P 500:

Download implied premium spreadsheet

It is instructive to look at how the inputs have changed since the start of 2017, when my estimate of the implied ERP was 5.69%. The S&P 500 has risen 19.43%, while cash returned has remained stable; the drop in buybacks has been offset by an increase in dividends. Analysts have become more optimistic about future earnings growth, partly because US companies had a healthy earnings year and partly because of the expected drop in corporate tax rates. It is true that there are judgment calls that I had to make in estimating the implied premium, including using the analyst estimates of earnings growth for the S&P 500 (7.05%), but the resulting error pales in comparison to the standard error in the historical risk premium estimate.

While I take this implied equity risk premium as a market price for risk, and will use it in my individual company valuations in January 2018, there are some who like playing the market timing game. If you are so inclined, the question that you are asking is whether 5.08% is a high, low or reasonable number. If you believe that the current implied premium is too low (high), you also have to believe that stocks are over priced (under priced), and to help you make that judgment, I have graphed the implied equity risk premium for the S&P 500 from 1960 to 2017 in the graph below:

Historical Implied ERP spreadsheet

There is a reason why those who are intent on claiming that the market is in a bubble have a tough sell. Unlike the end of 1999, when implied equity risk premiums were at historical lows (close to 2%), the current implied ERP is well within the bounds of historic norms. It is only if you read this graph, in conjunction with the earlier one on risk free rates, that you should be concerned, since one reason that the premium is at 5.08% is because the US treasury bond rate is 2.41%. If the T.Bond rate moves towards 4.50%, and nothing else changes, the implied ERP will drop below comfort levels.

Worried about Equities?

There has never been a time in the last three decades where I have felt sanguine about equity markets and I am thankful for that, since that is a sure sign of denial about the risk that is always under the surface, with stocks. That said, my worries shift from year to year and in this new year, I will continue to watch how the changing tax code will play out in both earnings and cash flows, since both are likely to be significantly affected, the former, because a lower tax rate should raise after-tax earnings, and the latter, because of the release of hundreds of billions of trapped cash. My macro crystal ball is always hazy but I expect T. Bond rates to rise, but if those higher rates go with a more robust economy, the market will take it in stride. There is the very real possibility that the economy stumbles, while rates rise, in which case US equities will be hard pressed to repeat their 2017 performance next year.

YouTube Video

Data Links

Data Update Posts

January 2018 Data Update 1: Numbers don't lie, or do they?
January 2018 Data Update 2: US Equities, Let the Good Times Roll!
January 2018 Data Update 3: A New Tax Code - Value Consequences?
January 2018 Data Update 4: The Currency Question
January 2018 Data Update 5: Country Risk
January 2018 Data Update 6: Cost of Capital - A Global Update
January 2018 Data Update 7: Growth and Value - Investment Returns
January 2018 Data Update 8: Debt and Value
January 2018 Data Update 9: The Cash Harvest - Dividend Policy
January 2018 Data Update 10: The Pricing Prerogative

If you have read my prior posts on taxes, you already know my views on the US tax code, especially as it relates to corporate taxes. Without mincing words, the US corporate tax code, as it existed in 2017, was an abomination, a carry over from a prior century where the US was the center of the global economy and companies would do anything demanded of them, to preserve their US incorporation. I was therefore predisposed to favoring tax reform and Congress delivered its version towards the end of 2017. While the process was messy and partisan, it represents the most significant change in corporate taxation in the United States in the my lifetime, and as with all tax reform, it is a mix of the good, the bad and the ugly, with your political priors determining which one you believe dominates. No matter what you think about the tax reform package, there is the one thing that is not debatable: it will impact equity value and affect corporate behavior in the coming year.

The 2017 Tax Reform: Key Changes

The tax reform package that passed Congress is more than a 1000 pages long and it is easy to get lost in the details. While it makes changes in individual, private business and corporate tax law, I will focus this post on the corporate tax law changes. In my view, there are four big changes embedded in this packet that deserve attention:

Corporate Tax Rate: The federal corporate tax rate on the income that corporations generate ion the United States has been lowered from 35%, at the federal level, to 21%. This is the portion of the bill that attracted the most media attention, primarily because of the magnitude of the drop, bringing corporate taxes in the United States down to levels not seen in the country since the second world war.
Treatment of Foreign Income: The other big change in corporate taxation that attracted less attention but my be just as consequential in the long term is that the US has now joined the rest of the world, replacing its global tax with a regional tax model. Put simply, until 2017, US companies were required to pay the US tax rate on all of their global income, though the differential tax on foreign income does not have to be paid, until repatriated to the US. Starting in 2018, US companies will have to pay only the foreign taxes due on foreign income and will be free to bring the money back, when they want. There are two ancillary changes that the package makes to foreign income. First, it tries to clean up for past sins by imposing a one-time tax to un-trap cash that companies are holding in foreign locales. As I noted in this earlier post, the trapped cash is a predictable side effect of the global tax model, and not surprisingly, companies with global revenues have built up more than $2 trillion in foreign cash cash balances. The one-time tax rate will be 15.5% on cash invested in liquid assets and 8% on harder-to-sell assets. Second, the tax code also tries to put in disincentives for companies moving intangible assets to tax havens, by imposing a minimum tax rate of 13.1% (rising to 16.4% in 2025) on excess profits (over and above a 10% cost of capital) earned in foreign subsidiaries. This seems to be specifically directed at technology and pharmaceutical companies that have found ways to create foreign subsidiaries for intangible assets.
Limitation on Interest Deductibility: For the first time, the US tax code will put a limit on the deductibility of interest expenses, restricting it to 30% of the "adjusted taxable income" (with taxable income defined as EBITDA through 2022 and EBIT thereafter). To provide a cushion for companies that may have cyclical income, the lost (non-tax deductible) interest expense deductions can be carried forward and used in future years, with no expiration date.
Capital Expensing: US companies will be allowed to deduct their investments in tangible assets in the year of the investment, for taxable income calculations, rather than have to depreciate it over time. This provision will remain intact until 2023 and be phased out by 2027.

The two best features of the tax reform package, in my view, are the changes in the taxation of foreign income and in the treatment of debt, and I will trace out the consequences for value in the next section. There are three features of the tax reform that I do not like. First, the package does little to reduce the complexity in the code, and in some cases, adds to that complexity. In particular, I don't like either the capital expensing rule change or the way in which it deals with intangible assets overseas. Second, I don't believe that tax codes are good instruments to do economic engineering and I don't think that the provisions that are in the changed code to encourage companies, especially in old-economy sectors, to reinvest more will make a significant difference. Third, by increasing the divergence in tax rates between individual income, pass-through business income and corporate income (the highest marginal federal tax rates will be 37%, 29.6% and 21% respectively), it is going to encourage tax gaming on the part of those who have a choice.

The Value Change

As I read the many assessments of how the tax reform bill will affect stock prices and values, I am reminded of the old parable of the seven blind men and the elephant, where each one after feeling a different part of the elephant's body gives a very different description of the animal. Analysts seem to be picking either one aspect of the tax code (lower tax rates, debt interest restrictions, foreign income taxation) or one dimension of value (cash flows, risk or growth) to arrive at a conclusion that reflects their political biases. Thus, I have seen supporters of the bill zero in on the drop in the tax rate from 35% to 21%, assume that this will increase after-tax income proportionately and extrapolate to a value increase of more than 20%. At the other end of the bias spectrum, there are pessimists who argue that the loss of the tax benefits from debt, from both lower tax rates and interest deductibility restrictions, will push up the after-tax cost of debt and capital for firms, and lower value. Both analyses are incomplete because they are focused on pieces of the valuation puzzle, rather than the entire valuation. The tax code, after all, affects every dimension of value, as can be seen in the picture below:

To assess the impact of tax reform on overall equity value, we have to move through each dimension of value. In making these assessments, I will focus on non-financial service firms, partly because the tax effects on debt and value are cleaner and more transparent.

The Cash Flow Effect: The cash flows that a firm generates on operations are after taxes, but the relevant tax rate is not the statutory tax rate but the effective rate. It is true that the reduction of the statutory tax rate from 35% to 21%, will reduce taxes paid, but the reduction will be from the aggregated effective tax rate that companies paid in 2017, not the marginal rate. Based upon my estimates, in 2017, US non-financial service companies reported $330.8 billion in taxes on taxable income of $1,342.1 billion, translating into an effective tax rate of 25.19%. Since this tax rate includes state and local taxes and taxes on global income, these companies were paying an effective federal tax rate of closer to 23% on all of their taxable income in 2017. With the drop in the US corporate tax rate and the shift to a regional tax model, we would expect this tax rate to drop, but the magnitude of the decline is likely to be far smaller than optimists are assuming. My guess is that the effective tax rate next year will be about 20%, including state and local taxes, after the tax rate changes, resulting in an increase in after-tax operating earnings of approximately 6.67% [(1-.20)/(1-.2519)] in the next year.
The Cost of Capital Effect: The cost of capital is a weighted average of the cost of equity and the after-tax cost of debt. In computing the after-tax cost of debt, the tax rate that matters is the marginal tax rate on US income, since even companies that have low effective tax rates, like Apple, have found it in their best interests to borrow money in the US and set off interest expenses against their highest-taxed income. The marginal tax rate for a US company in 2017 was close to 38%, with state and local taxes added to the US federal tax rate of 35%. Moving that tax rate down to 24% (my estimate of the marginal corporate tax rate, with state and local taxes, in 2018) will increase the after-tax cost of debt. In 2017, US non-financial service firms collectively reported a debt to capital ratio, in market value terms, of 23.5% and faced a cost of equity of 7.85% and a pre-tax cost of debt of 3.91%. With a 38% marginal tax rate, that would have resulted in an after-tax cost of debt of 2.42% and a cost of capital of 6.57%. Keeping the pre-tax cost of debt and debt ratio fixed, and reducing the marginal tax rate to 24% will increase the cost of capital to 6.70%.
The Growth Effect: The growth effect is the trickiest one to assess, since the value of growth is a function of both how much companies reinvest but also how well they reinvest, measured as the return they earn on investments over and above their cost of capital. We do know that the incentive to reinvest has increased, especially at companies with physical and depreciable assets, because of the capital expensing provision and we also know that excess returns will change, as after-tax earnings and the cost of capital go up. In 2017, non-financial service companies in the US collectively reinvested 59.27% of their after-tax operating income back into their businesses and earned a return of 12.76% on their capital employed; the sustainable growth rate, if those numbers are maintained, is 7.56%. Increasing the return on capital to reflect the growth in after-tax earnings yields 13.65%, and assuming that reinvestment increases marginally to 65% of the after-tax earnings, because of the capital expensing rule change, yields an expected growth rate of 8.87%.

With these inputs in place, we can value US companies collectively, pre and post tax reform, and the effect on firm value is captured in the table below:

Download spreadsheet

In making my estimates, I have assumed that the revenues and Note that this is the estimated increase in firm value, but equity value will rise proportionately, if the debt ratio remains unchanged. Does this mean that stock prices will rise 9.70% over the next year? No, and here is why. This tax reform package has been floating around for almost a year now and investors have had a chance to not only read it but incorporate its effects into prices. While the final package contained some surprises, the final version of the bill preserved the key ingredients that we introduced in April 2017. The strong returns posted by US stocks last year already include some of the value effects of the tax law. Note that this does not mean that the effects of the new tax code have already worked their way into prices since we still do not know how companies or the US economy will respond to the changes. This analysis is static, insofar as it does not allow for the changes in investing, financing and dividend behavior that we will see, as a consequence of the tax change. For instance, firms may decrease how much they borrow, since the tax benefit to debt has decreased, and that will lower debt ratios and change the cost of capital further.

Value Redistribution

While much of the discussion about the tax reform has been about its impact on the overall economy and equity values, the bigger effect of the changes to the code will be redistributive, with some sectors gaining and other losing. To identify the winners and the losers across sectors, we can use the same framework that we used to assess the value change and isolate the value effect on a sector to three variables:

Variable	Effect on Value	Proxy
Effective tax rate	Companies that are currently paying high effective tax rates (>23%) will benefit the most from the tax reform. Companies that are paying low effective tax rates under existing law may pay higher taxes, if their tax deductions /credit have been removed or restricted.	Effective Tax Rate
Reinvestment in fixed assets	Companies that invest large amounts in tangible assets (that are capitalized under existing law) will benefit the most from the capital expensing provision. Companies that invest in R&D or intangible assets, which are already expensed, will benefit less.	Capital Expenditures as % of Sales
Debt Ratio	Companies that have high debt ratios will see bigger increases in costs of capital, and value decreases, as the tax benefits from debt are reduced. Companies with little or no debt will see little change in the cost of capital.	Debt/ (Debt + Equity), in market value terms

Put simply, companies (sectors) that are currently paying high effective tax rates, invest large amounts in tangible (depreciable) assets and have little or no debt will benefit the most from the tax code changes. Companies (sectors) that are currently paying low effective tax rates, invest little or nothing in tangible (depreciable) assets and have high debt will be hurt the most by the tax code changes. To identify the sectors that will benefit the most or will be hurt the most by the tax reforms, I looked at effective tax rates, capital expenditures/sales and debt ratios across all non-financial service sectors in 2017 and used the market aggregate value as the comparison to identify which side of the divide (higher or lower than the market aggregate) each sector fell. The full list is at the link at the end of this post, but the sectors that delivered the benefit trifecta (high effective tax rate, high cap ex as a percent of sales and low debt ratio) and cost trifecta are listed below:

Download full sector spreadsheet

All the caveats apply, insofar as we are using effective tax rates and capital expenditures for one year (2017) to make the comparisons. There is one sector, real investment trusts (REITs) that showed up the loser trifecta but it's special tax treatment (where its income is not taxed, but passed through) led to its removal from the lists. Again, this should not be taken as an indication that the market will look favorably on the benefited sectors and punish the hurt sectors, since market prices have had time to adjust to the expected tax code changes. In a later post on how the pricing varies across the sectors, we will revisit this question.

Conclusion
It would be hubris to argue that we know what will happen over the next year, as a result of the tax code, but we know what we should be watching out for:

Taxable income and tax rates: Facing a more benign domestic tax environment, will companies to be more expansive in their measurement of taxable income? How much of this income will they pay out in effective taxes?
Capital Expenditures in tangible asset sectors: The capital expensing provision should make it more investing in depreciable assets more attractive, but will that be sufficient to induce companies to reinvest more? If so, how much?
The Untrapping of Cash: How much of the trapped cash will companies bring back home, paying the one-time tax penalty? Will they reinvest this cash or return it (in the form of dividends and buybacks)?
The Debt Shift: Will highly levered businesses react to the reduction in tax benefits from debt by retiring debt? What effects will a system-wide delevering have on bond default spreads?

On top of these company-level concerns are questions about how the economy will react to the tax changes, how much of the benefit will be redirected to employees and what effect there will be on interest rates. It is going to be an interesting year!

YouTube Video

Data/Spreadsheet Links

Data Update Posts

January 2018 Data Update 1: Numbers don't lie, or do they?
January 2018 Data Update 2: The Buoyancy of US Equities!
January 2018 Data Update 3: Taxing Questions on Value
January 2018 Data Update 4: The Currency Question
January 2018 Data Update 5: Country Risk
January 2018 Data Update 6: Cost of Capital - A Global Update
January 2018 Data Update 7: Growth and Value - Investment Returns
January 2018 Data Update 8: Debt and Value
January 2018 Data Update 9: The Cash Harvest - Dividend Policy
January 2018 Data Update 10: The Pricing Prerogative

There is perhaps no more mangled nor misunderstood part of financial analysis than the handling of currencies, and globalization has only made the problems worse. From the laziness of assuming that government bond rate in a currency is always the risk free rate in that currency, to nonsensical notions like a global risk free rate, to bad practices like discounting peso cash flows with dollar discount rates, the list of currency sins is long. In this post, I look at three of the most common misconceptions related to currencies and use them to update currency related numbers at the start of 2018.

In my last post, I looked at the currency confusions that globalization has brought into financial analysis, and how to clean up for them. In this post, I discuss the other aspect of globalization that is forcing analysts to change long accepted practices in estimating equity risk premiums for companies. Taking what they have learned from finance textbooks blindly, practitioners have taken what they learned about equity risk premiums to emerging and frontier equity markets, often with disastrous results. Not only have they practiced denial when it comes to the additional risk that investors face in many markets, from political, economic and legal sources, but they have also considered risk by looking at where a company is incorporated, instead of where it does business. In this post, I will update my country risk measures for the start of 2018, and build on them to measure the equity risk premiums for companies.

I have long described the cost of capital as the Swiss Army Knife of finance, since it shows up in so many places in finance, albeit in different forms. In corporate finance, it is not only the cost of raising funding for a business but also the hurdle rate to use in capital budgeting and an optimizing tool for capital structure and dividend policy. In valuation, it is the discount rate that we use to value a business and the only mechanism for incorporating the risk of a business into its value. Along the way, it picks up a variety of other names that are used to describe it (with my least favorite one being the WACC acronym) and gets confused or used interchangeably with the cost of equity. In short, it is not surprising that there seems to be little consensus on how to estimate the cost of capital for a business.

The Cost of Capital: Definition

It is unfortunate that the name that we have attached to this ubiquitous number is the cost of capital, since it seems to suggest that it is the cost of raising funding for a company. While that definition may sometimes fit, it often leads to destructive consequences, where companies that are safe and can raise equity or borrow money at low rates (and hence have a low cost of funding) think that they are adding value when they go out and take risky investments that earn more than that cost. A company that has a 5% cost of capital is not always adding value if it takes an investment that generates an 8% return, if the investment is risky enough to require a much higher return. A healthier definition of the cost of capital is to think of it as an opportunity cost, i.e., a rate of return that you (as an investor or by extension, a company that the investor has put money in) can make on an investment of equivalent risk. The key words in this definition are "equivalent risk", because that effectively eliminates the subsidy mistake that occurs when a safe company's cost of capital is used to justify taking a risky investment. This is, of course, one of the first principles of finance and it is astonishing that it is open for debate and that so many companies violate it, in their practices. If you are skeptical of my claim, consider the following manifestations of this malpractice:

Many multi-business companies continue to have a "single" hurdle rate in capital budgeting: In a survey of "best" practices across companies and advisors, the authors note that almost half of all companies (and advisors) surveyed used a single cost of capital across all investments. That is not only not good practice, but over time, it will ensure that your entire company will become a riskier company that takes bad investments. While I appreciate the work that went into this survey, I would suggest that the authors seriously reconsider using the word "best" to describe many of the horrendous practices that companies use in computing cost of capital. Looking at surveys of how companies compute costs of capital around the world, it seems clear to me that bad practices drive out good ones, a manifestation of Gresham's law in corporate finance practice.
In acquisitions, it is routine for companies (and bankers) to use the acquiring company's cost of capital to value the target company: While I cannot point to surveys to back up this statement, in my experience, this happens in more than 60% of acquisitions, with the logic being that it is the acquiring firm that raises the capital and that its costs should therefore be covered. The fact that will lead safe firms to find any risky firm that they look at to be cheap is glossed over. If you are waffling, let me be absolutist. Valuing a target company using an acquiring company's cost of capital is valuation malpractice, and if you do it, you should be stripped of your license to do valuation.
Cash is viewed as a value destroying asset: If you follow GAAP or IFRS, for an asset to be categorized with cash and short term investments, it has to be invested in liquid and close to riskless assets. In the last decade, these investments, not surprisingly, have generated extraordinarily low returns, but it is true, no matter what interest rate environment you are in, that cash will earn lower returns than operating investments. There are analysts, and I use the word loosely, who compare the returns generated on cash to the cost of capital of the firm to conclude that cash is a value-destroying asset and that it should be returned. While there are legitimate arguments that can be made that companies should return cash to stockholders, this is not one of them. In fact, cash, if invested in treasury bills or commercial paper, is a value-neutral investment, earning exactly the return that you need it to earn, given its liquid, diskless status.
A company that earns a higher return on its projects (higher ROIC) should be valued more highly than a company that earns a lower return on its projects: Without controlling for risk, this is not true. In fact, the right assessment would require comparing the ROIC to the cost of capital to estimate an excess return and a company that earns a higher positive excess return should be valued more highly than one that earns a lower excess return.

The key, then, to estimating cost of capital is to to link it directly to a risk measure that can be computed not just for entire companies but for individual projects. It is that pursuit that will drive my estimation process for cost of capital, described in the next section.

The Cost of Capital: Estimation Process

There are ultimately only two ways of raising funds to finance a business. One is to borrow the money (debt) and the other is to use your own money (equity). This is captured in one of my favorite corporate finance devices, the financial balance sheet:

With a small private business, the debt will take the form of a bank loan and the equity will be your savings, but as businesses scale up, debt may expand to include corporate bonds and equity may transition to venture capital, private equity and publicly traded stock. The structure also allows us to boil the cost of capital down to its three ingredients: a cost of equity, an after-tax cost of debt and the weights to attach to the two.

Cost of equity

The End game: In principle, the cost of equity is the rate of return that equity investors in your business need to make to compensate for the risk that they are exposed to.

The Practice: For the last few decades, corporate finance has tried, with mixed success, to devise a risk and return model to estimate the cost of equity. While these models vary in complexity and inputs, they generally share a common theme. They estimate the cost of equity to the marginal investors in the business, i.e., investors who own and trade large blocks of shares, and assume that these investors are diversified. These models all share a common structure; they start with a risk free rate and then estimate a risk premium for an investment, by measuring its relative risk (on one or more market risk factors) and the price of risk or risk premiums (for these factors). While it is the subject of substantial abuse, the capital asset pricing model continues to be the default model that most practitioners use in estimating cost of equity. The resulting inputs are shown below:

I still use the capital asset pricing model in my valuations and I offer no apologies for doing so, since I find it simple, intuitive and at least as effective as the next best alternative models, most of which add more complexity and deliver little in results. For those who are truly disturbed my the CAPM's limitations, there is an alternative approach worth considering that is agnostic in its assumptions about investor diversification and risk aversion. It is to back out the "implied" cost of equity for stocks within a sector and to use that implied number as the cost of equity in individual companies. If you are puzzled about what this implies, take a look at how I estimated the implied equity risk premium for the S&P 500 in my second data post from a couple of weeks ago and consider extending that approach to the banking index, to get an implied cost of equity for banks, and the energy sector, to estimate the cost of equity for oil companies.

Cost of Debt

The End Game: The cost of debt for a firm is the rate at which it can borrow money, long term and today. The after-tax cost of debt is this borrowing rate, adjusted for any tax benefits that accrue to borrowing money.

The Practice: By defining the cost of debt as a current cost of borrowing, rather than the rate at which the firm has borrowed money in the past, I have simplified my estimation problem, since the cost of debt can then be written as the sum of the riskless rate and a default spread, reflecting the company's credit risk:

Pre-tax cost of debt = Risk free Rate + Default Spread for the Company

To estimate the default spread, you can use one of three approaches, in order of ease.

If the firm in question has corporate bonds outstanding, you can use the interest rate on the bond as your pre-tax cost of debt for the firm since it is a current, market-set rate.
If a firm has corporate bonds and they are not traded enough or have features that skew the interest rate, you can use the bond rating for the company to estimate a default spread.
If the firm has neither bonds nor a rating, a combination that holds for most companies, I would assess a "synthetic rating" for the company, based upon the strength of its financials and its capacity to repay debt.

To bring the tax benefit of debt into the after-tax cost of debt, you should use the marginal tax rate, since interest expenses save you taxes at the margin:

After-tax cost of debt = (Risk free Rate + Default Spread) (1- Marginal Tax Rate)

This cost of debt will be much lower than your cost of equity, for almost all firms.

Debt & Equity Weights

Market or Book? This choice, at least for me, is an easy one. The cost of capital is a measure for what it will cost you to raise money to fund the business, investment or project today, and since you can raise money only at market value, it is the only relevant number.

Current or Target? This is an argument that often consumes analyst time and often misses the point. It is true that the debt ratio for a company can change over time, and if management does have a target, the actual debt ratio may move to the target. Unless this change is instantaneous, it is likely to occur over time and my answer to the question is to use the current debt ratio to estimate the cost of capital at the start of the investment and as the debt ratio is changed over time to the optimal, to change the cost of capital as well.

Cross Sectional Estimation

In choosing my estimation approach to getting cost of capital, do keep in mind that there are 43,848 firms in my sample and since looking at each one individually is out of the question, I will have to make some bludgeon assumptions (that I would not have made if I were estimating the cost of capital for an individual company). The table below summarizes my estimation choices, with the limitations of each:

	Estimation Approach used	Possible limitations
Risk Free Rate	US T.Bond Rate	Cost of equity estimated in US dollars.
Beta	Started with unlevered beta for sector & levered up using company's D/E (including leases as debt)	Used only the primary business that the company was in. With multi-business companies, I am missing the effect of oither businesses on beta.
ERP	ERP of country that the company is incorporated in.	If company operates in other countries, the ERP should be a weighted average.
Default Spread	Used bond rating, if available, to estimate the default spread. Used interest coverage ratio to estimate ratings and default spread, otherwise.	Interest coverage ratios may not capture default risk fully, Bringing in other ratios might have provided more refined estimate.
Marginal tax rate	Use the statutory tax rate of the country in which the company is incorporated.	If company operates in many countries, it may be able to place its debt in a country with the higher marginal tax rae.
Weights	Current market value of equity and debt (including leases) used for weights.	Insufficient information to estimate market value of interest-bearing debt.

If you want to estimate the cost of capital, using more refined estimates (country weightings for ERP and business mixes for betas), you are welcome to try my cost of capital calculator. If you are working in another currency, converting my estimates of cost of capital to an alternate currency should be a simple exercise of adding the differential inflation rate between the currency in question and the US dollar to my estimate.

The Cost of Capital - Going Concern Concept

There is one important caveat to add about cost of capital specifically and discount rates, in discounted cash flow valuations, more generally. In a discounted cash flow valuation, we are implicitly assuming that the business that we are valuing is a going concern that will either survive for a long time or is on its path to a specified and clearly determined liquidation point.

So what? The reality is that business is risky and the essence of risk is that it can sometime deal out bad enough outcomes to put a company out of business. With a young start up, this may take the form of running of cash and access to capital. With a declining company, it can the failure to make a debt payment and distress. With a bank, it can take the form of a drop in regulatory capital below levels acceptable to the regulatory authorities and a shutting down of the bank. With an emerging market company, even a healthy company may see its survival threatened by a nationalization. These are risks that I call truncation risks and analysts often struggle with how best to bring them into value. One path that they try is to push discount rates (or costs of capital) higher for companies that face significant amounts of truncation risk, but discount rates are blunt instruments for dealing with this type of risk and my suggestion is that you not try to adjust them for the risk. Instead, you should consider using a decision tree front on your valuation, where you can bring in your truncation risk concerns separately from your DCF. With a distressed firm or start up, for instance, where you worry about survival risk, the decision tree will look as follows:

This will not only relieve you of the stress of trying to adjust discount rates for risk that they were never meant to convey but will allow you to focus on the truncation risk more directly. Thinking about the probability that you will not survive as a firm and what you will get, if you don't, is a much healthier exercise than arbitrarily pushing up your discount rate another 2%, because you feel the firm is riskier.

The Cost of Capital - Perspective

The cost of capital discussion is permeated with rules of thumb about what comprises reasonable, high or low numbers, many developed in a different time, and for a different market. These rules of thumb skew estimates, since analysts feel the urge to adjust the costs of capitals that they get from models or metrics to match their preconceptions about what they should be. It is my primary objection to the build-up approach for the cost of capital, where analysts add multiple premiums (small cap, illiquidity, company specific) to arrive at a cost of capital that matches what they would have liked to see in the first place. It is to counter this temptation that I will compute costs of capital for US and global companies and present both sector averages as well as the entire distributions for the market.

US Companies

To provide perspective on what the cost of capital for the median US company will look like, start with the US 10-year T.Bond rate of 2.41% on January 1, 2018, as the risk free rate and my estimate of the implied ERP of 5.08% for the US on the same date. For an average risk stock, with a beta of one, that would translate into a cost of equity of 7.49%. Bringing in the debt ratio of 23.51% for the typical US firm and a pre-tax cost of debt of 3.91% (1.5% higher than the risk free rate), results in a cost of capital of 6.43%, if we use the marginal tax rate of 24%, post tax reform:

Cost of capital for median US firm = (2.41%+5.08%)(1-.2351)+3.91%(1-.24) (.2351) = 6.43%

Using the sector-specific debt ratios and betas yields costs of capital for US companies in individual sectors and the resulting costs of capital are reported in the table below:

Download full sector cost of capital spreadsheet

You can download the spreadsheet with the details of the cost of capital calculation by clicking on the link below. There is information in the company-specific costs of capital estimates that I have for 7.247 US firms in my sample that I try to capture in a histogram:

To the question of what comprises a high, low or average cost of capital, I would offer the deciles for the cost of capital estimation in 2018, also shown in the histogram.

Global Companies

I estimate the costs of capital for global companies, in US dollars, and using the same template that I use for the US. There are two key differences. The first is that I shift from using the US ERP of 5.08% to a GDP-weighted global average ERP of 6.20%, from a US-average debt ratio of 23.51% to to a global-average debt to capital ratio of 26.67%, from a pre-tax cost of debt of 3.91% to 4.91% (reflecting country default risk) and from a marginal tax rate of 24% to a weighted average of 24.63%. The resulting cost of capital for a median global firm is higher than for the US:

Cost of capital for median global firm = (2.41%+6.20%)(1-.2667)+4.91%(1-.2463) (.2667) = 7.30%

As with the US data, I compute sector averages, using sector average betas and debt ratios and the results are summarized in the picture below:

Download full sector cost of capital spreadsheet

Finally, the distribution of costs of capital across global companies are captured in the histogram, with deciles specified:

Here again, I would use this distribution to make judgments of what a high, low or average cost of capital would look like in January 2018, and adding inflation differentials would provide analogous numbers in other currencies.

The Conclusion

Notwithstanding the length of this post, and the ones leading up to it, I do not believe that the cost of capital is the biggest driver of the value of companies. When you make mistakes in valuation, it is almost always true that the big mistakes are in your cash flow and growth estimates, rather than in your cost of capital. This is especially true when you value young companies, and it is one reason that I am almost casual in my choice of costs of capital in my valuation of Twitter, Uber and Snap, where I have attached costs of capital reflective of the 90th percentile in risk. It is true that as companies mature, the cost of capital becomes a more critical input, but even in these valuations, I would argue that if you are spending more than 20% to 25% of your time estimating it, you have lost your way.

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