Data Update 5: Relative Risk and Hurdle Rates

In my last four posts, I focused on the macro variables that we draw on, in both corporate finance and valuation, to estimate required returns or hurdle rates. In data post 3, I looked at how the prices of risk in both the bond market (default spreads) and the equity market (equity risk premiums) dropped in 2019, in the US. In data post 4, I extended the discussion to cover country and currency risk. In this one, I will bring in the micro variables that cause differences in risk across firms, and how to convert them into risk measure.

Relative Risk Measures

To get from the macro risk measures to company-level hurdle rates, you need to make judgments on relative risk. Put simply, if you buy into the proposition, like I do, that some companies/investments are riskier than others, you need a measure of relative risk that captures this variation.  It is in this context that I think of betas, a loaded concept that carries with it the baggage of modern portfolio theory and efficient markets. If you add to this the standard approach to estimating betas, built on looking at past prices and running regressions against market indices, you have the makings of a perfect storm, designed to drive value investors to apoplexy. I have no desire to re-litigate these arguments, partly because those for and opposed to betas are set in their ways, but let me suggest some compromise propositions.

Relative Risk Proposition 1: You do not need to believe in betas to do financial analysis and valuation. 

While there are many who seem to tie discounted cash flow valuations to the use of beta or betas, there is nothing inherently in  a DCF that requires that you make this leap:

While the discount rate in a DCF is a risk-adjusted number, the approach is agnostic about how you measure risk and adjust discount rates for that risk.

Relative Risk Proposition 2: If you don't like to or want to measure relative risk with betas, you can come up with alternate measures that better reflect your view of how risk should be measured. 

While I do use beta as my proxy for risk, I do so with open eyes, recognizing its many limitations as a risk measure, and I have been always willing to consider competing risk measures. In fact, I have presented alternate measures of risk, drawing on the two building blocks of betas that draw the most pushback. The first is the assumption that marginal investors are diversified, and that the only risk that needs to be measured is the risk that cannot be diversified away. The second is its use of prices (stock and market) to estimate risk, seemingly contradicting intrinsic value's basic precept that market prices are not trustworthy. Since a picture is worth a thousand words, here a few alternative risk measures to consider, if you don't trust betas;

Put simply, if your primary problem with betas is the assumption that marginal investors are diversified, there are total risk measures that are built around measuring the total risk in a company or investment, by looking at either the standard deviation or adding premiums (small cap, company-specific risk) to the traditional risk and return model. If your concern is that past prices are being used to estimate betas, you can switch to using accounting earnings and computing risk measures either from the perspective of diversified investors (accounting beta) or undiversified ones (earnings variability).

Relative Risk Proposition 3: The margin of safety is not a competitor to any of the risk measures above, since it is a post-value adjustment for risk.

Rather than repeat what I said in a much longer post that I had on the topic, let me summarize the points that I made there. When value investors talk about protecting themselves from risk by using a margin of safety, they are talking about building a buffer between value and price, but to use the margin of safety, you need to value a stock first. To get that value, you need a risk measure, and that brings us back full circle to how you adjust for risk, when valuing companies.

Relative Risk in 2020

With that long lead-in, let's take a look at how companies measured up on relative risk measures, at the start of 2020. In keeping with my argument in the last section that you can use alternative risk measures, I will report on three alternative risk measures:

• Betas: I start with betas, estimated with conventional regressions of returns on the stock against a market index, for each of the companies in my sample. To get a measure of how these betas vary across companies, I have a distribution of betas, broken down globally and for regions of the world:
  
  It is worth noting that, at least for public companies, half of all companies have betas between 0.85 and 1.45, globally. If you are wondering why the betas are not higher for companies in riskier parts of the word, it is worth emphasizing that betas are scaled around one, no matter of the world you are in, and are not designed to convey country risk. (The equity risk premiums that I wrote about in my last post carry that weight.)
• Relative Standard Deviation: For those who do not buy into the notion that the marginal investors are diversified and that the only risk that matters is market risk, I report on the standard deviation in stock prices (using the last two years of data):
  
  Note that you can convert these numbers into relative measures, resembling betas, by dividing by the average standard deviation of all stocks. Thus, if you have a US stock with an annualized standard deviation of 35.00% in stock returns, you would divide that number by the average for US equities of 42.36% to arrive a relative standard deviation of 0.826 (=35.00%/42.36%).
• High-Low Risk: For those who prefer a non-parametric and more intuitive measure of risk, I compute a risk measure by looking at the difference between high and low prices in the most recent year, and dividing by the sum of the two numbers. Thus, for a stock that has a high price of 20 and a low price of 12, during the course of a year, this measure would yield 0.25 ((20-12)/ (20+12)). Note that the bigger the range in prices, the more risky a stock looks on this measure, and this too is broken down globally and by region:
  
  As with the other risk measures, this too can be converted into a relative risk measure, by dividing by the average.
• Earnings Variability: Finally, for those who trust accountants more than markets (even though I am not one of them), I have computed a risk measure that is built around earnings variability, computed by looking at the standard deviation in net income over the last 10 years for each firm, and converted into a standardized measure, by dividing by the average net income over the ten years (a coefficient of variation in net income), The global and regional breakdown is below:
  
  The earnings variability number has a bigger selection bias than the other measures, because it requires a longer history (10 years of data) and positive earnings, cutting the sample size down significantly. Here again, dividing a company's coefficient of variation in net income by the average value across all companies will give you a relative risk measure.

I follow up by looking at median values for each of the risk measures by industry grouping. Since I have 94 industry groupings, I will not report them all here, but you can download the data on all of the industry groupings, by clicking here.

Hurdle Rates in 2020

The relative risk measures are a means to an end, since the only reason for computing them is to use them to get to required returns. In this section, I begin by looking at the cost of equity, then bring in the cost of debt and close of by looking at the cost of capital.

a. Cost of Equity

There are three ingredients that go into the cost of equity and the last few posts have laid the foundations for the three inputs:

• The risk free rate is a function of the currency you choose to compute your hurdle rates in, and will be higher for high-inflation currencies than low-inflations ones. Since I will be comparing and aggregating costs of equity across more than 40,000 firms spread across the world, I will compute their costs of equity in US dollars, using the US T.Bond rate as of January 1, 2020, as the risk free rate. You can convert these into any other currency, using the differential inflation approach that I described in my earlier post from a couple of weeks ago.
• The equity risk premium for a company is a function of where it does business, and in my last data update post, I described my approach to estimating equity risk premiums for individual countries, and the process of weighting these (using either revenues or production) to get equity risk premiums for companies.
• For the relative risk measure, I will use betas but as I argued in the last section, I am agnostic about what you prefer to use instead. Thus, if you prefer earnings variabliity as a measure, you can use relative earnings variability as your risk measure.

With these inputs, I estimate the costs of equity for all of the companies in my database, and report the distribution in the table below:

Comparing this distribution to the one for betas, earlier in this post, you will notice a wider spread in the numbers across regions, as we bring in equity risk premium differences into the calculation.

b. Cost of Debt

The cost of debt is a simpler exercise, since it is a measure of the rate at which companies can borrow money today, not a reflection of the rates at which they have borrowed in the past. It is a function of the risk free rate and the default spread:

As with the cost of equity, the risk free rate is a function of the currency in which you estimate the cost of debt in, and I will estimate the costs of debt for all companies in US dollars, again to make comparisons across companies. For the default spread, I have little choice but to use bludgeon measures, since I cannot assess credit risk for 40,000 plus companies. For companies that have an S&P bond rating (about 15% of the sample), I use the rating to estimate a default spread. For the rest, I estimate synthetic bond ratings based on financial ratios (interest coverage and debt ratios). The US $ pre-tax cost of debt distribution is below:

Since these costs are all in US dollars, the differences across regions reflect difference in country default risk and reflect wide divergences. It is worth noting that the tax law tilt towards debt, represented in the fact that interest expenses are tax deductible and cash flows to equity (dividends and buybacks) have to come from after-tax cash flows, is not just a phenomenon for the US, but true over much of the world, with the Middle East representing the holdout. This tax benefit shows up in the cost of capital, through the conversion of the pre-tax cost of debt into an after-tax cost, using the marginal tax rate to make the adjustment:

After-tax cost of debt = Pre-tax cost of debt (1 - Marginal Tax Rate)

In my sample, I use the marginal tax rate of the country in which a company is incorporated. You can find these marginal tax rates, which KPMG should be credited for collecting, also on my website for download.

c. Debt Ratios and Costs of Capital

The final piece of the puzzle in computing the cost of capital is the mix of debt and equity that companies use in funding their operations. In keeping with the cost of capital being a measure of what companies have to pay for their debt and equity today, I use the market values of equity and debt, with leases converted into debt and included in the latter, to compute the cost of capital. While I will talk in more detail about debt loads and choices in a future post, you can sense of the debt load at companies, as a percent of capital (in market value terms) in the table below below:

With these debt ratios, and using the costs of equity and debt also shown above, I compute costs of capital, in US dollar terms, for all publicly traded companies and the resulting distribution is below:

This is a table that I will use, and have already put to use, in valuing companies since it provides a quick and effective way to estimate discount rates for companies, without losing yourself in the details. Thus, when valuing a young, money-losing public company in the US (like Casper, the only mattress-maker that went public last week), I will use a cost of capital of 9.15%, representing the 90th percentile of US firms, whereas to value a slow-growing European company in a stable business,  like Heineken, my cost of capital will be 6.02%, the 25th percentile of European companies. For all companies, the median cost of capital of 7.58% is a good proxy for the number that all companies will converge towards, as they approach maturity. If all of these numbers look low to you, that is because they reflect a risk free rate, in US dollars, that is low, and if it does rise, it will carry these numbers upwards.  As with the risk measures, I have estimated costs of equity, debt and capital, by industry group and you can download them for all companies globally, as well as regionally (US, Emerging Markets, Europe, Japan and Australia/Canada) and for India and China, separately.

YouTube Video


Downloadable Data

1. Industry Average Risk Measures at start of 2020
2. Betas, by industry (Global, US, Emerging Markets, Europe, Japan,  Australia/Canada, India, China)
3. Costs of Debt, Equity and Capital, by industry (Global, US, Emerging Markets, Europe, Japan,  Australia/Canada, India, China)
4. Marginal tax rates, by country, for 2020

A Viral Market Meltdown: Fear or Fundamentals?

It has become almost a rite of passage for investors, at least since 2008, that they will be tested by a market crisis precipitated sometimes by political developments (Brexit), sometimes by governments (trade wars), sometimes by war and terrorism (the US/Iran standoff) and sometimes by economics (Greek default). With each one, the question that you face about whether this is the “big one”, a market meltdown that you have to respond to by selling everything and fleeing for safety (or the closest thing you can find to it) or just another bump in the road, where markets claw back what they gave up, and then gain more. After yesterday’s global meltdown in equity markets, I think it is safe to say that we are back in crisis mode, with old questions returning about the global economic strength and market valuations. I have neither the stomach nor the expertise to play market guru, but I will go through my playbook for coping.

Start at the source
This crisis has an uncommon source, insofar as it is one of the few that is not man-made (at least based upon what we know now) and is thus more difficult to predict, in terms of how it will play out. As a novice in infectious diseases, here is what I know at the moment:

1. The virus (COVID-19) had its origins in China, though what caused it to spread into the human population is still unclear and rife with conspiracy theories. In an attempt to keep the populace from panicking and to give the impress of being in control, the Chinese government initially went into crisis mode, trying to control the information that is being made public and that has created both confusion and skepticism about official claims.
2. Within China, the virus has had its biggest impact in the Wuhan province, but it has affected other parts, though there is still not clear by how much or how many. The count, which is obviously a moving target, is that there are more than 80,000 cases of the virus, with more than 2700 fatalities so far. The latest reports from China is that new infections are falling, and if true, this would suggest that the spread is being controlled. 
3. The most immediate spread has been to the neighboring Asian countries, with Singapore being an early casualty and South Korea a recent-add on. It has jumped borders and is showing up in more distant parts of the world, mostly in occasional cases. Over the weekend, though, the Italian government set alarm bells ringing with an announcement of a large cluster of cases in the country, which suggests that earlier assessments that the virus was not easily communicable may need to be rethought, and it was this news that seems to have precipitated this week’s sell off. On February 25, the CDC warned Americans that the disease could make significant inroads in the United States and suggested that states prepare cautionary measures.
4. There is no cure or vaccine yet for the virus, but the mortality rate from the virus seems to vary across the population, with the very young and the very old being the most likely to die from it, and across geographies, with more deaths in Asia than in Europe or the United States. The overall mortality rate is low ( about 3%), but it is higher for people who are hospitalized with complications. 

In short, there is a lot more that we do not know about COVID-19, than we do, at least at the moment. While it has not been labeled a pandemic yet, it seems to have the potential to become one, and we do not yet have a clear idea of how quickly it will spread, how many people will be affected and what will push it into dormancy. It is also clear that much of this uncertainty will get resolved by real-time developments, not by collecting data or by listening to experts to tell us what will happen.

Get perspective
There is no denying that the last week has been a rocky one for investors, and a 1800-point drop for the Dow over two days (February 24 &25) is bound to add to the sense of foreboding. Since the first casualty of a crisis is perspective, it may be worth stepping back and looking at the market through wider lens. After the drop yesterday (February 24), the S&P 500 was at 3225.89, slightly above where it started this month (February 2020) at. In short, investors in the index were back where they were 18 trading days ago. Bringing in February 25 into the picture does put you below that level, but it still way above what it was a year ago:

In fact, extending the comparison to longer time periods only makes the hand wringing over the last week’s losses look even more absurd. This is both good and bad news. The good news is that, if you are a diversified investor, your portfolio should not look dramatically different from what it looked like at the start of the year and much, much healthier than it looked a year ago, five years ago or ten years ago. The bad news is that the big run-up in stocks over the last decade has left you exposed to more and bigger losses to come. The bottom line is that your concern should not be about the damage to your portfolio from the last week’s developments, but the damage that is yet to come.

Have a framework

With perspective in place, I am now in a position to look to the future, since that should govern how we react to last week’s developments. Given my investment philosophy of trusting fundamentals and value, I have to go back to my basic framework for valuation, which is to tie the value of an investment to its cashflows, growth and risk. When valuing the overall market, here is what it looks like:

With my value framework, the effects of the Corona Virus will play out in my forward-looking numbers in the following inputs:

1. Earnings Growth: Even at this early stage in this crisis, it is clear that the virus is having an effect on corporate operations. With some companies like hotels and airlines, the effect that the virus has had on global travel has clearly had an effect on revenues and operations, and it should come as no surprise that United Airlines announced, after close of trading on February 24, 2020, that it was withdrawing its guidance for revenues this year, as it was waiting for more information. With others, it is concern about supply chain disruptions, especially with Chinese facilities, and how this will affect operations in the rest of the world. The follow up question then becomes one of specifics:

• Drop in 2020 Earnings: This is the number that will reflect how you see Corona Virus affect the collective earnings on stocks in 2020. This will include not only earnings declines caused by lower revenues growth at companies like United Airlines, but also the earnings decline caused by higher costs faced by companies due to virus related problems (supply chain breakdowns). The wider the swath of companies that are affected, the bigger will be the earnings effect. As to how big this effect will be on overall earnings, we can only guess, given where we are in this process. To provide some perspective, the 2008 banking crisis caused an earnings implosion, with earnings dropping almost 40% in 2008, from 2007, but the World Trade Center attacks in September 2001 barely made an impact on overall S&P 500 earnings in the last quarter of 2001.
• Drop in long term Earnings: In previous crises, where consumers and workers stayed home, either for health reasons or because of fear, the business that was lost as a result of the peril was made up for, when it passed. If consumption is just deferred or delayed, the growth in subsequent quarters will be higher, to compensate for the lost business in the crisis quarter. If consumption is lost, the drop in earnings in the crisis quarter will never be made up. 

To illustrate the point, I look at how three different perspectives on growth will play out in growth rates, based upon how much of the drop in earnings this year is recovered over the following years:

Note that the first series is the unadjusted earnings, prior to the corona virus scare and that in all three of the scenarios, there is a drop in earnings of 5% in 2020, putting earnings well below expected values for 2020, but the difference arises in how earnings recover after that. If none of the drop in earnings in 2020 is recouped in the following years, the earnings in 2025 is 179.22, well below the pre-virus estimate of 199.28. If only half of the earnings drop is recouped, the earnings in 2025 is 189.41 and if all of the earnings drop is recouped, the earnings in 2025, even with the virus effect, matches up to the original estimates.

2. Cash Returned: In 2019, US companies returned 92.33% of earnings as cash to stockholders, with a big chunk (about 60%) coming from buybacks. That high number reflects not only the cash that many US companies had on hand, but a confidence that they could maintain earnings and continue to pay out cash flows. To the extent that this confidence is shaken by the virus, you may see a pull back in this number to perhaps something closer to the 85.24% that is the average for the last decade.

3. Risk and Discount Rates: Finally, the required return on stocks will be impacted, with one of the effects being explicit and visible in markets, in the form of the US treasury bond rate and the other being implicit, taking the form of an equity risk premium. If investors become more risk averse, they will demand a higher ERP, though as the fear factor fades, this number will fall back as well, but perhaps not to what it was prior to the crisis. The fact that the equity risk premium is already at the higher end of the historical norms, at about 5.50% on February 25, 2020, does indicate limits, but there could be a short-term jump in the number, at least until there is less uncertainty.

Using this framework on the S&P 500, you can see how each of these variables play out in value.

Download spreadsheet

I am not an expert on infectious diseases, and the health and economic impacts of this virus are likely to play out as developments in real time, requiring that I revisit this framework frequently. Based upon my estimates of how this virus will affect the numbers, the value that I get for the index is 3003, about 4.14% less than the index level of 3128.21 at the close of trading on February 25, 2020, which, in turn, represents a significant drop from the level of the index a week ago. To the question of whether a virus can cause this much damage to the markets, the answer is yes, though whether it is an overreaction or not will depend on how it plays out in the numbers. For the moment, though, if you are tempted to buy on what looks like a dip, I would suggest caution just as I would argue for slowing down to someone who wants to do the opposite and sell. As you look at my assumptions about how the virus will play out in earnings (both short term and long term), cash flows and risk premiums, some of you may disagree (and perhaps even strongly) and you can use this spreadsheet to arrive at your own valuation of the index, and use it to drive your actions. 

To thine own self, be true...

It is entirely possible that I am underestimating the impact of this virus on economic growth and earnings and that I should be panicking more, but it is also plausible that I am over adjusting my numbers too much. The bottom line with my calculations is that I am inclined to do very little, at the moment. I don’t feel the urge to buy the market, because there is a plausible case to be made that the adjustment in value, steep and sudden, was merited. I feel little need to sell either, because I don’t see an over valuation large enough to trigger action. As for whether I should be reducing my exposure to companies that are directly affected by the virus (hotels and airlines) and increasing my exposure to companies that are more insulated, I don’t believe there will be any segment of the market that is fully protected from the consequences, no matter how far you get from China and from travel-oriented companies. In fact, if there is a segment of the market where you are likely to see over reaction, it is likely to be in airline, travel and energy stocks, precisely because they are in the center of the storm. Do I now wish that I had bought Zoom before this crisis reached full blown status? Yes, but I am not sure buying it now will do much for me. I am loath to offer advice, but my only suggestion is that rather than listen to the experts on either side of this debate tell you what to do, you should make your own best judgments, recognizing that they can and will change as more facts emerge, and act accordingly.

YouTube Video


Spreadsheets

1. Spreadsheet to value Corona Virus Effects on S&P 500 (February 25, 2020)

Viral Market Update Posts

1. A Viral Market Meltdown: Fear or Fundamentals?
2. A Viral Market Meltdown II: Pricing or Valuing? Investing or Trading?
3. A Viral Market Meltdown III: Clues in the Market Debris
4. A Viral Market Meltdown IV: Investing for a post-virus Economy
5. A Viral Market Meltdown V: Back to Basics
6. A Viral Market Meltdown VI: The Price of Risk
7. A Viral Market Update VII: Market Multiples
8. A Viral Market Update VIII: Value vs Growth, Active vs Passive, Small Cap vs Large!
9. A Viral Market Update IX: A Do-it-Yourself S&P 500 Valuation
10. A Viral Market Update X: A Corporate Life Cycle Perspective
11. A Viral Market Update XI: The Flexibility Premium
12. A Viral Market Update XII: The Resilience of Private Risk Capital
13. A Viral Market Update XIII: The Strong (FANGAM) get Stronger!

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:

Download spreadsheet

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

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

Spreadsheets

1. Implied Equity Risk Premium on January 1, 2020

Datasets

1. Historical Equity Risk Premiums for the US - 1960 to 2019
2. Historical Default Spreads on Baa Rated Bond - 1980 to 2019
3. Default Spreads on Bond Ratings Classes (my estimates) in January 2020

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!

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