Wednesday, February 19, 2020

Data Update 4: Country Risk and Currency Questions!

In my last post, I looked at the risk premiums in US markets, and you may have found that focus to be a little parochial, since as an investor, you could invest in Europe, Asia, Africa or Latin America, if you believed that you would receive a better risk-return trade off. For some investors, in countries with investment restrictions, the only investment options are domestic, and US investment options may not be within their reach. In this post, I will address country risk, and how it affects investment decisions not only on the part of individual investors but also of companies, and then look at the currency question, which is often mixed in with country risk, but has a very different set of fundamentals and consequences.

Country Risk
There should be little debate that investing or operating in some countries will expose you to more risk than in other countries, for a number of reasons, ranging from politics to economics to location. As globalization pushes investors and companies to look outside of their domestic markets, they find themselves drawn to some of the riskiest parts of the world because that is where their growth lies. 

Drivers and Determinants
In a post in early August 2019, I laid out in detail the sources of country risk. Specifically, I listed and provided measures of four ingredients:
  1. Life Cycle: As companies go through the life cycle, their risk profiles changes with risk dampening as they mature. Countries go through their own version of the life cycle, with developed and more mature markets having more settled risk profiles than emerging economies which are still growing, changing and generally more risky. High growth economies tend to also have higher volatility in growth than low growth economies. 
  2. Political Risk: A political structure that is unstable adds to economic risk, by making regulatory and tax law volatile, and adding unpredictable costs to businesses. While there are some investors and businesses that believe autocracies and dictatorships offer more stability than democracies, I would argue for nuance. I believe that autocracies do offer more temporal stability but they are also more exposed to more jarring, discontinuous change. 
  3. Legal Risk: Businesses and investments are heavily dependent on legal systems that enforce contracts and ownership rights. Countries with dysfunctional legal systems will create more risk for investors than countries where the legal systems works well and in a timely fashion.
  4. Economic Structure: Some countries have more risk exposure simply because they are overly dependent on an industry or commodity for their prosperity, and an industry downturn or a commodity price drop can send their economies into a tailspin. Any businesses that operate in these countries are consequently exposed to this volatility.
The bottom line, if you consider all four of these risks, is that some countries are riskier than others, and it behooves us to factor this risk in, when investing in these countries, either directly as a business or indirectly as an investor in that business.

Measures
If you accept the proposition that some countries are riskier than others, the next step is measuring this country risk and there are three ways you can approach the task:
a. Country Risk Scores: There are services that measure country risk with scores, trying to capture exposure to all of the risks listed above. The scores are subjective judgments and are not quite comparable across services, because each service scales risk differently. The World Bank provides an array of governance indicators (from corruption to political stability) for 214 countries (https://databank.worldbank.org/source/worldwide-governance-indicators#) , whereas Political Risk Services (PRS) measures a composite risk score for each country, with low (high) scores corresponding to high (low) country risk. 
b. Default Risk: The most widely accessible measure of country risk markets in financial markets is country default risk, measured with a sovereign rating by Moody’s, S&P and other ratings agencies for about 140 countries and a market-based measure (Sovereign CDS) for about 72 countries. The picture below provides sovereign ratings and sovereign CDS spreads across the globe at the start of 2020:
Download spreadsheet
c. Equity Risk: While there are some who use the country default spreads as proxies for additional equity risk in countries, I scale up the default spread for the higher risk in equities, using the ratio of volatility in an emerging market equity index to an emerging market bond index to estimate the added risk premium for countries: 


Note that the base premium for a mature equity market at the start of 2020 is set to the implied equity risk premium of 5.20% that we estimated for the S&P 500 at the start of 2020. The picture below shows equity risk premiums, by country, at the start of 2020:
Looking back at these equity risk premiums for countries going back to 1992, and comparing the country ERP at the start of 2020 to my estimates at the start of 2019, you see a significant drop off, reflecting a decline in sovereign default spreads of about 20-25% across default classes in 2019 and a drop in the equity risk, relative to bonds.

Company Risk Exposure to Country Risk
The conventional practice in valuation, which seems to be ascribe to all countries incorporated and listed in a country, the country risk premium for that country, is both sloppy and wrong. A company’s risk comes from where and how it operates its businesses, not where it is incorporated and traded. A German company that manufactures its products in Poland and sells them in China is German only in name and is exposed to Polish and Chinese country risk. One reason that I estimate the equity risk premiums for as many countries as I need them in both valuation and corporate finance, even if every company I analyze is a US company.

Valuing Companies 
If you accept my proposition that to value a company, you have to incorporate the risk of where it does business into the analysis, the equity risk premium that you use for a company should reflect where it operates. The open question is whether it is better to measure operating risk exposure with where a company generates its revenues, where its production is located or a mix of the two. For companies like Coca Cola, where the production costs are a fraction of revenues and moveable, I think it makes sense to use revenues. Using the company’s 2018-19 revenue breakdown, for instance, the equity risk premium for the country is:

For companies where production costs are higher and facilities are less moveable, your weights for countries should at least partially based on production. At the limit, with natural resource companies, the operating exposure should be based upon where it produces those resources. Thus, Aramco’s equity risk premium should be entirely based on Saudi Arabia’s, since it extracts all its oil there, but Royal Dutch’s will reflect its more diverse production base:

Put simply, the exposure to country risk does not come from where a company is incorporated or where it is traded, but from its operations.

Analyzing Projects/Investments
 If equity risk premiums are a critical ingredient for valuation, they are just as important in corporate finance, determining what hurdle rates multinationals should use, when considering projects in foreign markets. With L’Oreal, for instance, a project for expansion in Brazil should carry the equity risk premium for Brazil, whereas a project in India should carry the Indian equity risk premium. The notion of a corporate cost of capital that you use on every project is both absurd and dangerous, and becomes even more so when you are in multiple businesses.

The Currency Effect
When the discussion turns to country risk, it almost always veers off into currency risk, with many conflating the two, in their discussions. While there are conditions where the two are correlated and draw from the same fundamentals, it is good to keep the two risks separate, since how you deal with them can also be very different.

Decoding Currencies: Interest Rates and Exchange Rates
When analyzing currencies, it is very easy to get distracted by experts with macro views, providing their forecasts with absolute certainty, and distractions galore, from governments keeping their currencies stronger or weaker and speculative trading. To get past this noise, I will draw on the intrinsic interest rate equation that I used in my last post to explain why interest rates in the United States have stayed low for the last decade, 
Intrinsic Riskfree Rate = Inflation + Real GDP Growth
That identity can be used to both explain why interest rates vary across currencies as well as variation in exchange rates over time. 

Risk free Rates
If you accept the proposition that the interest rate in a currency is the sum of the expected inflation in that currency and a real interest that stands in for real growth, it follows that risk free rates will vary across currencies. Getting those currency-specific risk rates can range from trivial (looking up a government bond rate) to difficult (where the government bond rate provides a starting point, but needs cleaning up) to complex (where you have to construct a risk free rate out of what seems like thin air).

1. Government Bond Rates
There are a few dozen governments that issue ten-year bonds in their local currencies, and the search for risk free rates starts there. To the extent that these government bonds are liquid and you perceive no default risk in the government, you can use the government bond rate as your risk free rate. It is that rationale that we use to justify using the Swiss Government’s Swiss Franc 10-year rate as the risk free rate in Swiss Francs and the Norwegian government’s ten-year Krone rate as the riskfree rate in Krone. It is still the rationale, though you are likely to start to get some pushback, in using the US treasury bond rate as the risk free rate in dollars and the German 10-year Euro as the risk free rate in Euros. The pushback will come from some who argue that the US treasury can choose to default and that the German government does not really control the printing of the Euro and could default as well. While I can defend the practice of using the government bond rate as the risk free rate in these scenarios, arguing that you can use the Nigerian government’s Naira bond rate or the Brazilian government’s Reai bond rate as risk free is much more difficult to do. In fact, these are government’s where ratings agencies perceive significant risk even in the local currency bonds and attach ratings that reflect that risk. Moody’s rates Brazil’s local currency bonds at Ba2 and India’s local currency bonds at Baa2. In my pursuit of a risk free rate in currencies like these (where there is no Aaa-rated entity issung a bond), I compute a risk free rate by netting out the default spread:
  • Riskfree Rate in currency = Government bond rate – Default Spread for sovereign local-currency rating
Using this approach on the Indian rupee and the Brazilian reai,
  • Riskfree Rate in Rupees on January 1, 2020 = Indian Government Rupee Bond rate on January 1, 2020 – Default spread based on Baa2 rating = 6.56% - 1.59% = 4.95%
  • Riskfree Rate in Brazilian $R = Brazilian Government $R Bond rate on January 1, 2020 – Default spread based on Ba2 rating = 6.77% - 2.51% = 4.26%
Extending this approach to all countries where a local currency government bond is available, we get the following risk free rates:
Download spreadsheet
Note that these estimates are only as good as the three data inputs that go into them. First, the government bond rates reported have to reflect a traded and liquid bond, clearly not an issue with the US treasury or German Euro bond, but a stretch for the Zambian kwacha bond. Second, the local currency rating is a good measure of the default risk, a challenge when ratings agencies are biased or late in adjusting. Third, the default spread, given the ratings class, is estimated without bias and reflects the market at the time of the assessment. 

2. Synthetic Risk free Rates
If you have doubts about one or more of three assumptions needed to use the government-bond approach to getting to risk free rates, don’t fear, because there is an alternative that I will call my synthetic risk free rate. To use this approach, let’s start with a currency in which you feel comfortable estimating a risk free rate, say the US dollar. If the key driver of risk free rates is expected inflation, the risk free rate in any other currency can be estimated using the differential inflation between that currency and the US dollar. In the short cut, you add the differential inflation to the US T.Bond rate to get a risk free rate:
 Local Currency Risk free rate = US T.Bond Rate + (Inflation rate in local currency - Inflation rate in US dollars)
In the full calculation, you incorporate the compounding effects of the differential inflation
This approach can be used in almost any setting to estimate a local currency risk free rate, including the following:
  1. Currencies with no government bonds outstanding: There are more than 120 currencies, where there are no government bonds in the local currency; the country borrows from banks and the IMF, not from markets. Without a government bond rate, the approach described above becomes moot.
  2. Currencies where the government bond rate is not trustworthy: There are currencies where there is a government bond, with a rate, but an absence of liquidity and/or the presence of institutions being forced to buy the bond by the government that may make the rates untrustworthy. I don't mean to cast aspersions, but I seriously doubt that the Zambian Kwacha bond, whose rate I specified in the last section, has a deep or wide market.
  3. Pegged Currencies: There are some currencies that have been pegged to the US dollar, either for convenience (much of the Middle East) or stability (Ecuador). While analysts in these markets often use the US T.Bond rate as the risk free rate, there is a very real danger that what is pegged today may be unpegged in the future, especially when the fundamentals don't support the peg. Specifically, if the local inflation rate is much higher than the inflation rate in the US, it may be more prudent to use the synthetic risk free rate instead of the US T.Bond rate as the risk free rate.
The key inputs here are the expected inflation rate in the US dollar and the expected inflation rate in the local currency. The former can be obtained from market data, using the difference between the US T.Bond rate and the TIPs rate, but the latter is more difficult. While you can always use last year’s inflation rate, but that number is not only backward looking but subject to manipulation. I prefer the forecasts of inflation that you can get from the IMF, and I have used those to get expected risk free rates in other currencies, using the US T.Bond rate as my base risk free rate, and you can find them at this link.

Currency Choice
Having belabored the reasons for why riskfree rates vary across currencies, let’s talk about how to pick a currency to use in valuing a company. The key word is choice, since you can value any company in any currency, though it may be easiest to get financial information on the company, in a local currency. An Indian company can be valued in US dollars, Indian Rupees or Euros, or even in real terms, and if you are consistent about dealing with inflation in your valuation, the value should be the same in every currency. At first sight, that may sound odd, since the risk free rate in US dollars is much lower than the risk free rate in Indian rupees, but the answer lies in looking at all of the inputs into value, not just the discount rate. In fact, inflation affects all of your numbers:

With high inflation currencies, the damage wrought by the higher discount rates that they bring into the process are offset by the higher nominal growth you will have in your cash flows, and the effects will cancel out. With low inflation currencies, any benefits you get from the lower discount rates that come with them will be given back when you use the lower nominal growth rates that go with them. In practice, there is perhaps no other aspect of valuation where you are more likely to be see consistency errors than with currencies, and here are some scenarios:
  1. Casual Dollarization: In casual dollarization, you start by estimating your costs of equity and capital in US dollars, partly because you do not want to or cannot estimate risk free rates in a local currency. You then convert your expected future cash flows in the local currency and convert them to dollars using the current exchange rate. That represents a fatal step, since the inflation differentials that cause risk free rates to be different will also cause exchange rates to change over time. Purchasing power parity may be a crude approximation of reality, but it is a reality that will eventually hold, and ignoring can lead to valuation errors that are huge.
  2. Corporate hurdle rates: I have long argued against computing a corporate cost of capital and using it as a hurdle rate on investments and acquisitions, and that argument gets even stronger, when the investments or acquisitions are cross-border and in different currencies. If a European company takes its Euro cost of capital and uses it to value Hungarian, Polish or Russian companies, not correcting for either country risk or currency differentials, it will find a lot of “bargains”.
  3. Mismatched Currency Frames of Reference: We all have frames of reference that are built into our thinking, based upon where we live and the currencies we deal with. Having lived in the US for 40 years and dealt with more US companies than companies in any other market, I tend to think in US dollar terms, when I think of reasonable, high or low growth rates. While that is understandable, I have to remember that when conversing with an Indian analyst in Mumbai, whose day-to-day dealings in rupees, the growth rates that he or she provides me for a company will be in rupees. Consequently, it behooves both of us to be explicit about currencies (my expected growth rate for Infosys, in US dollars, is 4.5% or my cost of capital, in Indian rupees, is 10%) when making statements, even though it is cumbersome.
One of the side costs of globalization is that you can no longer assume, especially if you are a US investor or analysts, that the conversations that you will be having will always be on your currency terms (presumably dollars). Understanding how currencies are measurement tools, not instruments of risk or asset classes, will make that transition easier.

Conclusion
In this post,  I looked at two variables, country and currency, that are often conflated in valuation, perhaps because risky countries tend to have volatile currencies, and separated the discussion to examine the determinants of each, and why they should not be lumped together. I can invest in a company in a risky country, and I can choose to do the valuation in US dollars, but only if I recognize that the currency choice cannot make the country risk go away. In other words, a Russian or Brazilian company will stay risky, even if you value it in US dollars, and a company that gets all of its revenues in Northern Europe will stay safe, even if you value it in Russian Rubles.

YouTube Video


Data Links

  1. Ratings and Sovereign CDS spreads, by country (January 2020)
  2. Country Equity Risk Premiums in January 2020
  3. Government Bond Rates and Riskfree Rates by Currency in January 2020
  4. Synthetic Riskfree Rates in 2020 (with inflation rates by currency)

Data Update Posts
  1. Data Update 1 for 2020: Setting the Table
  2. Data Update 2 for 2020: Retrospective on a Disruptive Decade
  3. Data Update 3 for 2020: The Price of Risk!
  4. Data Update 4 for 2020: Country and Currency Effects


Monday, February 10, 2020

Data Update 3 for 2020: The Price of Risk!

When investing, risk is a given and if you choose to avoid it, at any cost, you will and in the last decade, you have borne a staggering cost in terms of returns unearned. At the other extreme, seeking out risk for the sake of taking risk is more suited to casinos than to financial markets, and as in casinos, the end game is almost always disastrous. The middle ground on risk is to accept that it is part and parcel of investing, to try to gauge how exposed you are to it and to make sure that your expected return is high enough to compensate you for taking that risk. Put simply, you are charging a price to take risk, and that price will reflect not only your history and experiences as an investor, but how risk averse you are, as an individual. In this post, rather than focus on your or my price of risk. I want to talk about the market price of risk, as assessed by all investors, and how that price changed in 2019.

The Price of Risk
There are almost as many definitions of risk, as there are investors, but I find many of them wanting. There is, of course, the definition of risk as uncertainty, a circular play on words, since it just replaces one nebulous word (risk) with another. There is the definition of risk as encompassing all the bad outcomes you can have on an investment, which by making risk into a negative and something to be avoided, leads you right into the arms of those selling your protection against it (in the form of hedging). In finance, we have become so used to measuring risk in statistical terms (standard deviation, variance, covariance etc.) that we have taken to defining risk with these measures, an arid and antiseptic view of risk.  The truth is that risk, at least in business, is neither a good nor a bad, but a given. It is a combination of danger (the likelihood that bad things will happen to you) and opportunity (often emerging from exposing yourself to danger, and I think that the Chinese symbol for crisis captures its essence perfectly:
(I know! I know! I have been corrected and recorrected on both the symbols and the definition by people who know far more Chinese than I do, which is pretty much everyone in the world… So, please cut me some slack!) It is this definition of risk that allows us to frame the risk/return trade off that lies at the heart of investing. While you can choose a pathway of taking no risk and earning guaranteed returns, those returns in today’s markets would be close to zero in the United States and Europe. If you want to earn higher returns, you have no choice but to expose yourself to risk, and when you do, the key question becomes whether you are being compensated sufficiently for taking that risk. 
  • When you invest in fixed income securities (bonds), your compensation takes the form of a default spread, i.e., what you charge over and above the risk free rate to invest in that bond.
  • · When you invest in equities, the payoff to taking risk comes in the form of an equity risk premium, i.e., the premium you demand over and above the risk free rate for investing in equities as an asset class.
Both the default spread and the equity risk premium are market-set numbers and are driven by demand and supply. The default spread is a function of what investors believe is the likelihood that borrowers will fail to make their contractually obligated payments, and it will rise and fall with the economy. The equity risk premium is a more complex number and I think of it as the receptacle for everything from changes in investor risk aversion to perceptions of economic growth and stability to corporate choices on leverage and cash return to global flash points (war, health scares etc.).

The Default Spread
The default spread is the premium that investors demand on a bond to compensate for default risk, and not surprisingly, it varies across bond issuers, with safer (riskier) borrowers being charged less (more) to borrow money. One assessment of corporate default risk is a bond rating, a measure of default risk computed by ratings agencies. While ratings agencies have been criticized for bias and delay, these bond ratings are still widely used, and are a convenient proxy not only for measuring default risk, but also for estimating default spreads. In the graph below, I have listed the default spreads at the start of 2020 and compared them to default spreads that I had estimated at the start of 2019, by ratings class:
Source: Damodaran Online
The first conclusion, and a completely unsurprising one, is that companies that are lower rated (and thus perceived to have more default risk) have larger default spreads than companies that are highly rated; a BBB (Baa) rated bond, at the cusp of investment grade and junk bonds, for instance, saw its default spread drop from 2.00% at the start of 2019 to 1.56% at the start of 2020. To get some longer-term perspective on how much default spreads change over time, the default spread on the investment grade (BBB, Baa) rated bond is graphed below from 1980 to 2019:
Source: FRED (Federal Reserve St. Louis)
At the risk of stating the obvious, the default spreads on bonds change over time, decreasing when times are good and investors are sanguine, and increasing during economic downturns and market crises.

The US Equity Risk Premium
In my last data update post, where I looked at markets over the last decade, I also posted a table that reported historical equity risk premiums, i.e., the premiums earned by stocks over treasury bills and bonds over long periods, ranging from a decade to 92 years. 
Source: Damodaran Online
There are many practitioners, who use these historical equity risk premiums as the best estimates for what you will earn in the future, using mean reversion as their basic argument. I have already made clear my problems with using a backward-looking number with a large estimation error (see the standard errors in the table above) as an expectation for the future, but it cuts against the very essence of an equity risk premium as a number that should be dynamic and constantly changing, as new information comes into markets. For almost three decades, I have computed an implied equity risk premium, a forward-looking value computed by looking at what investors are paying for stocks today, and the expected cash flows on those stocks. Specifically, I take an approach that is used with bonds to compute a yield to maturity to stocks, computing an IRR for stocks and then subtracting out the risk free rate. At the start of 2020, the implied equity risk premium for the S&P 500 was 5.20% and the calculations are in the graph below:
Download spreadsheet

Since I have been computing this number at the start of each month, since September 2008, I can look at how this number moved in the twelve months of 2019:
Damodaran Online
During the course of the year, the implied equity risk premium has decreased from 5.96% to 5.20%, driven down by increasing stock prices and lower interest rates.

I am fascinated by the implied equity risk premium because it captures the market’s current standing in one number and frames debates about the overall market. A contention that markets are overvalued, or in a bubble, is equivalent to claiming that the equity risk premium is too low, relative to what you believe is a reasonable value. In contrast, a bullish assessment of the entire equity market can be viewed as a statement about equity risk premiums being too high, again relative to reasonable values. But what is a reasonable value? I have no idea, since I am not a market timer, but to help you make your own assessment, I have reproduced the implied equity risk premium for the S&P 500 going back to 1960:
Download spreadsheet
You could use the computed averages embedded in the graph as your basis for reasonable, and using that comparison, the market looks closer to under than overpriced, since the ERP on January 1, 2020 was 5.20%, higher than the average for the last 60 years (4.20%) or the last 20 years (4.86%). Even with a 10-year average, the market is only very mildly overpriced. It is true that the current implied ERP of 5.20% is being earned on a riskfree rate of 1.92%, low by historical standards, yielding an expected return of 7.12% and that may be too low for some. I will let you make your own assessment, but this is a healthier one that just looking at PE ratios (Shiller, trailing, forward) or other market metrics.

A Real Estate Risk Premium?
If default spreads measure the price of risk in bond markets and equity risk premiums measure the risk for investing in stocks, what is the price of risk of investing in other asset classes? It may be more difficult to assess what this value is in other risky markets, but it exists without a doubt, and one way of evaluating how much of your portfolio to allocate to these asset classes is to compare their risk premiums to the risk premiums of bonds and stocks. To get a sense of how this would play out, consider the real estate market, perhaps the biggest asset class outside of stocks and bonds. Investors in commercial real estate attach prices to properties, based upon their expectations of income from the properties and capitalization rates. Thus, a property with expected income of $10 million and a capitalization rate of 8% will be valued at $125 million = $10/.08. Since the capitalization rate is effectively a measure of expected return on real estate, subtracting out the risk free rate should yield a measure of the risk premium in real estate. 
Risk Premium for Real Estate = Cap Rate – Risk free rate
In the graph below, I have estimated the real estate risk premium and provided a comparison to the equity risk premium and default spread, over time:

Note that the real estate risk premium in the 1980s was not only well below the equity risk premium and the default spread, it was sometimes negative. While that may strike you as odd, it makes sense if you think of real estate as an asset class that is not only uncorrelated with financial asset returns but also provides insurance against inflation. As real estate was securitized in the 1990s and fears of inflation receded, the real estate risk premium has started behaving like the risk premiums in stock and bond markets, and the rising correlation between them reflects that co-movement. Put simply, we live in a world, where the real estate you own (often your house or apartment) will tend to move with, rather than against, your financial assets, and in the next market crisis, as the stocks and bonds that you own plummet in value, you should expect the value of your house to drop as well!

Conclusion
The debate about equity risk premiums is not an abstract one, since which side of the debate you come down upon (whether risk premiums today are too high or low) is going to drive your asset allocation judgments. If you are a bear, you believe that equity risk premiums should be higher, either for fundamental reasons or by instinct, and you should put less of your wealth into stocks than you normally would, given your age, liquidity needs and risk aversion. The challenge that you will face is in deciding where you will invest your money until you think that the ERP becomes more reasonable, since bonds are likely to also be overpriced (according to your view of the world) and real assets will often be no better. If you are a market bull, your story has to be one of equity risk premiums declining in the future, perhaps because you believe in your own version of mean reversion or because of continued economic growth. For both market bulls and bears, the perils with bringing these views into every valuation that they do is that every company they value will then jointly both their views about the company and the overall market. It is for this reason that I think it makes sense to revert back to a market neutral view, when valuing individual companies, even if you have strong market views. Since my market timing skills are non-existent, I prefer to stay market neutral, and stick to valuing companies using the prevailing equity risk premiums. 

YouTube Video

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Thursday, February 6, 2020

A Do-it-yourself (DIY) Valuation of Tesla: Of Investment Regrets and Disagreements!

I was hoping to move on from Tesla to my data update posts, but my last post on Tesla drew some attention, in good and bad ways, partly because of its timing. Right after I sold my shares for $640, last week (January 30), the stock took off, climbing to more than $900/share in the matter of days. As always, there were people on both sides of the great Tesla divide commenting on my valuation, with bears accusing me of wearing rose-colored glasses and making unrealistically optimistic assumptions, and bulls pointing to inputs that they felt under estimated the company’s potential. I wish that I had been clearer in my writing that the numbers that I was using did not represent “the” valuation of Tesla but that this was “my” valuation of the company, and that I not only expect disagreement, but I think it is part and parcel of a healthy market. Rather than leave that view as an abstraction, I thought I would revisit the valuation and present it in a different format, one in which you can choose your story for Tesla and estimate the value for yourself.

The Key Levers of Value
In my earlier post, I valued Tesla and presented my valuation in a picture, where I connected the story that I was telling about the company to my estimated value per share of roughly $427 per share:
Download spreadsheet
If you find the numbers off putting or overwhelming, the value is determined by four key levers:
  1. The Growth Lever: The revenue growth rate controls how much and how quickly the firm will be able to grow its revenues from autos, software, solar panels and anything else that you believe the company will be selling. Rather than focus on the growth rate, I would suggest looking at the estimated revenues in 2030 (ten years out). In my Tesla story (valuation), I have estimated revenues of $125 billion in 2030, a five-fold increase over the 2019 revenues.
  2. The Profitability Lever: The target (pre-tax) operating margin determines how profitable you think the company will be, once its growth days start to scale down. Since these are operating margins, not gross or net margins, they are after all operating expenses (cost of goods sold, SG&A etc.) but before any financial expenses (interest expenses). In keeping with my view that R&D is really a capital expense, I capitalize R&D, which improves Tesla’s profitability, and target an operating margin of 12% by 2025.
  3. The Investment Efficiency Lever: To grow, companies have to invest in production capacity and the sales to invested capital drives how efficiently investment is done, with higher sales to capital ratios reflecting more efficiency. With Tesla, I assume that every dollar of investment (in new factories, technology and new R&D) in the first 5 years generates $3 in revenues, as it utilizes excess capacity in the early years, and that this efficiency drops back by a third, as capacity constraints hit.
  4. The Risk lever: There are two inputs in this valuation that incorporate risk. The first is the cost of capital that I start the valuation with, a reflection of risk as seen through the eyes of a diversified investor in the company. The second is the likelihood of failure (or distress), where the company has to liquidate assets and lose the additional value that it could have generated as a going concern. With Tesla, I set this cost of capital at 7% and assume that given its marginal profitability and significant debt load, the chance of failure is 10%.
The value per share of $427 comes out of these assumptions and is driving my investment decisions. Since this is my story and valuation, I expect and welcome disagreement on any and all of these inputs. After all, I don’t have a crystal ball to forecast the future or a monopoly on the right estimates

A DIY Valuation of Tesla
In the rest of this post, rather than force my story on your, I would like you to make your choices on the growth, profitability, investment and risk dimensions future for Tesla, and just in case you need some help, I will offer data perspective, on each of those choices. 

The Growth Lever
To make your judgment on how much revenue Tesla will have in a decade, it may help to take a look at the overall auto business. In 2019, the collective revenues of all publicly traded auto companies in the world was about $2.46 trillion and the the compounded average growth rate in those revenues over the last decade has been about 3.5%:
Source data: S&P Capital IQ
Put simply, this is a big market, but the overall market is in slow growth. To provide some perspective on what the bigger auto companies generate in revenues, I have listed the 20 largest auto companies, in terms of revenues in the table below:
Source data: S&P Capital IQ
Tesla does make the list, coming in at the very bottom of the list, and its compounded annual growth rate between 2010 and 2019 stands out, partly the base revenues for the company, in 2010, were tiny. Since one of the Tesla stories told by optimistic is that it is a tech company, It may help in your estimation to see what large tech companies look like, and to make this assessment, I decided to focus on the giants on top of the tech heap in the FAANG stocks, with Microsoft thrown in for full measure:
Note that while the tech companies are substantially more profitable than the auto companies, in terms of margins and dollar operating income, their revenues tend to be more muted, reflecting the pricing of their products and services. Apple, the largest market cap company in the world, had revenues of $ 260 billion in 2019, and Microsoft, the largest software company in the world, by far, had revenues of $129 billion, and both companies lagged Toyota and Volkswagen, on total revenues.

With this background, I think that you have the ammunition you need to make your own revenue judgments for Tesla in a decade, differentiating your story from mine, where revenues in 2030 for Tesla are roughly $125 billion. So, with no further ado, here are your choices (pick one):
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Since Tesla’s revenue stream includes not just autos but also software, batteries and solar panels, your story may augment revenues to reflect these, but remember that these streams cannot deliver the same revenue heft as selling cars, though they may be more profitable. In addition, be cautious about growth rates, since it is almost impossible to grasp the compounding effect, without looking at the dollar values. For instance, there are some who take Elon Musk at his word that he plans to grow Tesla at 50%-100% a year; applying a 50% growth rate to Tesla's revenues would give it $470 billion in revenues, which would make it second only to Walmart on a global basis. With 100% growth, Tesla's revenues would be around $4 trillion in 2030, and if you can find a way to get there, good luck to you!

The Profitability Lever
To make your judgment on operating profitability, take a look at both the largest auto company tables and the one for FAANG stocks in the last section. There is not a single large auto company with double digit margins, and across all auto companies listed publicly, the profit picture is even more bleak:
Source: S&P Capital IQ
The picture is brighter for the FAANG stocks, where the aggregate operating margin across all five stocks is 19.87%, well above auto industry averages. That margin, though, is delivered on smaller revenues and with business models where production costs are a smaller fraction of selling prices. The marginal cost of producing an extra unit for Microsoft is close to zero on both its Office and Cloud business, and even for Apple, which derives a large chunk of its revenues from the iPhone, the cost of making the iPhone is about about 40% of the price it charges. 

This information should provide a basis for you to make a choice on a target operating margin for Tesla in the future, keeping in mind that its current operating margin is miniscule and barely positive. 
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As you make this choice, it is important that you tie it back to your earlier growth story. While Tesla sales of software/tech will have higher margins, it the auto sales that are responsible for the bulking up of revenues over time. Thus, if your argument is that Tesla will become predominantly a soft services company, you can give it higher margins, but your revenue expectations may have to be reduced. If you buy the argument of some that the costs of manufacturing will continue to drop (by about 15%), as production increases (doubles), you may think you have the basis for exploding margins, but the flaws in this argument should be obvious. First, there has to be a floor on cost savings or Volkswagen, which sells close to 10 million a year right now, should be making cars for close to nothing and generating margins of closer to 100% on the marginal car it sells (and it does not). Second, even if there are revolutionary changes in technology that allow the costs of production to decrease, unless you can show that Tesla and Tesla alone can reap these benefits, you have a business that will see the prices drop, as costs drop. Put simply, if Wright's law applies to all competitors, you and I will be able to buy electric cars at $3000/car and none of the manufacturers will be making sky high margins.

The Investment Efficiency Lever
The investment efficiency lever is one of the trickiest to navigate. Again, the place to start is with automobile companies, and the table below presents the distribution of sales to invested capital across all auto firms, at the start of 2020.

Looking across global auto companies, the median company generates $1.37 in sales for every dollar of capital invested, and at the 75th percentile, the more capital-efficient auto companies generate $2.42 in revenues for every dollar of capital invested. In fact, my estimate of $3 in revenues for every dollar of capital invested reflects an optimistic view of Tesla’s capacity to bring technological innovation to its production processes, and reduce the capital needed to fund those processes. Since Tesla, in 2019, generates $1.32 in revenue for every dollar of capital invested, my estimate is more aspirational than based on observable efficiencies, right now. Tesla bulls will counter with the tech company story, and to help the estimation process, I estimated the sales to invested capital at tech firms generally, just software firms and finally at just the FAANG stocks. None of these groups had sales to invested capital that were higher than my estimate. With that data to provide perspective, it is time to make your own judgment on investment efficiency:
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This choice will drive not only how much Tesla will have to reinvest to grow, but the extent to which it will be dependent on external capital for that growth.

The Risk Lever
The first component in the risk lever is the cost of capital, and to provide a sense of what costs of capital look like around the world at the start of 2020, let me start with a cost of capital distribution for all publicly traded companies:
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Note that the median cost of capital across all firms globally is 7.58%, and that 50% of all publicly traded firms have costs of capital that fall between 6.27% and 8.71%. It is true that costs of capital vary across different industries, and while you can get the entire list on my website, the median cost of capital for auto firms is 6.94% and for tech firms, it is 8.86%. While I used 7% as my cost of capital, you may disagree and here are your choices:
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The other component of risk is failure, where the company faces the risk of having its life truncated, either because it runs out of cash or because of debt payments coming due. While the rise in stock price has reduced its vulnerability for the moment, those who see more losses in the future and continued borrowing to fund investment may attach a higher probability of default than the 10% that I use, whereas those who believe Elon’s claims that Tesla has entered an era of positive earnings and cash flows, may decide that Tesla has no risk of failure any more:

The Valuation
I have created a front end for my Tesla valuation spreadsheet that allows the choices you made to drive the valuation. Running through the different combinations for the four variables, I have too many to list individually, but consider a subset in this table:
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Broadly speaking, there are four broad stories that I have valued here:
  1. The Big Auto Story: If your story is that Tesla will emerge from its growth period as one of the largest auto companies in the world (revenues of $100- $300 billion in year 10), with top-tier auto company margins (7.42%), investment efficiency (2.42) and cost of capital (6.94%), the value per share ranges from $106/share (with BMW like revenues) to $227/share (with Daimler-like revenues) to $333/share (with VW/Toyota like revenues).
  2. The Techy Auto Company Story: An alternate story is that Tesla is an auto/software/services company with tech company characteristics, giving it higher margins (10.25%) and a higher cost of capital (8.86%). With this story, the value per share ranges from $111/share (with BMW like revenues) to $212/share (with Daimler-like revenues) to $298/share (with VW/Toyota like revenues). Put simply, the higher risk nullifies the benefits of higher profitability.
  3. The FAANGy Auto Company: In this variant of the tech story, Tesla not only develops a tech twist, but becomes as successful as the most successful tech companies (I use the FAANG stocks + Microsoft).  In this story, the margins approach 18.97% and with a tech cost of capital, the value per share ranges from $459/share (with BMW like revenues) to $855/share (with Daimler-like revenues) to $2,106/share (with VW/Toyota like revenues).
  4. The Make-your-best Company: In this variant, I give Tesla the best possible outcomes on each variable, revenues like VW/Toyota, margins like pure software companies (21.24%), a sales to capital ratio that is higher than any of the sector averages (4.00) and a cost of capital of an auto company (6.94%), and arrive at a value per share of $2106.
For some of you, the fact that there is a value here that justifies whatever your Tesla status is right now (long, short or just watching) should not be the end of your analysis. Each of these stories may be possible, but the tests you have to run, and I will prejudge your conclusions, is whether they are plausible. With each story, there are key questions that need answering:

  • With the big auto stories, the key question will be whether Tesla can climb to the very top of the heap in terms of revenues, generally reserved for mass market companies, while earning operating margins that are usually reserved for smaller luxury auto companies?
  • With the techy auto stories, the key question becomes whether a company that derives the bulk of its revenues from selling cars be profitable and reinvest like a tech company? 
  • With the FAANGy stories, the investment question becomes whether you should up front for a company on the expectation that it will be an exceptional company. It very well might make it to the top of the heap, but if it does not, you are set up for disappointment.
  • With the MYB story, you are approaching the most dangerous place in valuation, where you pick and choose each assumption, without considering the ones you have already made. Put simply, is it even possible to build a company that generates revenues like Toyota, earns margins like Microsoft and invests more efficiently than any manufacturing company in history has ever done, while still preserving the low cost of capital of an auto company?
Conclusion
In the week since I sold Tesla at $640, the stock has gone on a wild ride, rising above $900 in two trading days. Not surprisingly, quite a few of you have asked me whether I have any regrets about selling too early. You may not believe me, but I don't. I made my decision to buy, based on my story and valuation for Tesla, and my decision to sell, for the same reason, because I am an investor who believes in value, and acting on it. If I abandon that philosophy to play the momentum game, a game that I am not good at and don’t really play well, I may make a bit more money, but at what cost?   On a different note, I have to confess that one reason that I write about Tesla reluctantly is the vitriol that seems to be part of any discussion of the stock. In a world where we face unbridgeable divides on politics, religion and culture, do we need to add investing to the mix?  If you stayed with your Tesla investment, I wish you the best, and I hope that you are holding on for the right reasons, either because you believe that its value is much higher or because you are playing the pricing game. If you sold short and lost money, I get no joy out of your losses and no inclination to do a celebratory dance. For the moment, you may have lost, but having watched this stock for as long as I have, that can change in a minute. As far as I am concerned, Tesla is a fascinating company, but it is just an investment, not a matter of life or death, and definitely not worth losing sleep, and friends, over.

YouTube Video


Spreadsheet

  1. A Do-it-Yourself Valuation of Tesla
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