Data Update 5 for 2026: Risk and Hurdle Rates

    In my first four posts, I looked at markets - equity, debt and collectibles - in the aggregate performed in 2025. In this post, I turn my attention to divergences in risk across companies, looking at alternative measures of risk, some based on prices and others at earnings, and how these differences play out in hurdle rates, a necessary ingredient for businesses trying to determine whether and how much to invest in individual projects and for investors making that same judgment, when looking at companies.

Risk: Definition and Measures

    For a concept tas central to investing and corporate finance as risk is, it is astonishing how much divergence there is across even finance experts and academics on what it is, and consequently on how to measure it. I have heard some describe risk as uncertainty, essentially substituting one fuzzy word for another, others as the threat of grevious loss and still and still others as the possibility of negative outcomes. If you have taken a finance class, and I confess to having a part in this, you may define risk as volatility or standard deviation, or even bring Greek alphabets into play. My favorite definition of risk and one that I start my corporate finance class with is that Chinese symbol for crisis or big risk (and I am sure that I have mangled the symbols, since I have been corrected a dozen times in the past):

As someone who can neither read nor speak Chinese, I am reliant on friends who know the language, and I have been told that the first of the two symbols is the one for danger and the second is a symbol for opportunity. In effect, by bunding together danger and opportunity, the risk measure captures how risk both attracts (to get to opportunity) and repels (with the threat of danger). That duality explains why an investment or business strategy generally cannot be built around the objective of just minimizing risk, since that effectively will remove access to opportunities or recklessly chasing after opportunities, ignoring dangers 

    With that definition of risk in place, I will start the discussion of risk measures by examining the choices that we face in making the measurement:

1. Upside versus Downside: If you start with a generic definition of risk as receiving an outcome that is different from what your expectation, it is worth recognizing that some of these outcomes will be positive (better than expected) and some will be negative (worse than expected), and that it is the latter than investors and businesses dislike. Thus, there are some who argue that risk measures should focus on just downside outcomes, not all unexpected outcome.
2. Price-based versus accounting-based: Risk measures that are based upon data can be built on market prices, for publicly traded firms, or on accounting data, especially earnings. Price-based measures have the advantage of constant updating, giving you more data, but are sometimes contaminated by the noise and volatility that come from trading. Accounting measures yield more stability, but since they are updated infrequently, and accounting smooths changes over time, they can offer stale or distorted values.
3. Total versus Non-diversifiable: The risk in an investment, whether a project or a business, can come from many different sources, but some of the risks are more investment-specific whereas others are market-wide:

To the question of why we should care, the presence of many investments in a portfolio implies that risks that are investment-specific will average out, decreasing or even disappearing as portfolios get larger, whereas market risks remain intact. This insight, which earned Harry Markowitz a Nobel prize, gave birth to modern portfolio theory and is at the heart of most risk and return models in finance.

    I have my preferences on how best to measure risk, I would like to keep an open mind and start by laying out the choices we face on risk-measures:

As you can see, the risk measure you choose will be a function of whether you (as an investor or business) believe that the marginal investors, i.e., the investors who own the most shares in your business and trade those share, are diversified or not, and what you believe about financial markets and accounting data.

Risk across Companies in 2025

    My sample includes 48,156 publicly traded firms and given that these companies trade across different geographies and are in different businesses, it should come as no surprise that there are wide variations in risk across these companies. In this section, I will start with accounting-based measures, with the caveat that accounting standards vary across the world, though IFRS and GAAP have created significant convergence. 

Accounting Measures

    While there are a variety of accounting metrics that you can use to measure risk, the most logical one to focus on is earnings, but you have many choices. You could use net income or earnings per share, which will reflect not only the riskiness of the business operate in, but also the amount of debt you have chosen to take on, or you can used operating income, more reflective of just market risk. Within each of these metrics, you can measure risk as volatility (in earnings) or in more simplistic terms, on whether you have positive or negative income. For those investors and businesses to whom, it is debt that is the risk trigger, you can look at measures of that debt burden:

Let’s start with volatility in earnings, where we have two estimation choices that we must make, before we get started. The first is history, and I compute the standard deviations in operating and net income using ten years of earnings data, for each firm, a compromise between a number too high (where I lose too many firms in my sample) and too low (where I lack enough data). The second is that earnings standard deviations in earnings will reflect the level of earnings, with higher earnings companies having higher standard deviations. To control for this, I divide the standard deviation of earnings by the average earnings over the ten years, yielding coefficients of variation in earnings. The following table summarizes the distributional values for this metric, across sectors:

It should come as no surprise that utilities have the least volatile operating earnings and have the lowest coefficient of variation on that metric, and that energy and technology haver the most volatile operating income. On a net income basis, financials and utilities have the lowest volatility in earnings, , and energy and communication services have the highest net income volatility.

    If you use the frequency of loss-making, as a risk proxy, the table below captures differences on that metric across sectors on this dimension:

Utilities are again the least risky sector, with a lower percentage of money losers than any other sector, and health care and technology firms have a higher percent of money losers than other sectors.

    While there are some who use debt loads as proxies for company risk, and we will come back and look at differences across sectors and industries in a later post, it is a narrow measure, since a young, risky, high growth company with no debt would be classified as low-risk, if it is not debt-laden.

 
Price-based Measures

    All of the stocks in our sample are publicly traded, and consequently, you can use market prices to measure risk. That said, liquidity is a wild card, high in some markets and low in others, and that can cause distortions in the comparison.

1. High and Low Prices: One of the simplest measures of price volatility is the range of prices, with wider divergences between high and low prices at more risky companies and smaller ones at safer companies:

HiLo Risk Measure = (High Price – Low Price)/ (High Price + Low Price)

I computed this statistic for each company in my sample, and then the averages across companies in each industry, and it should be lower (higher) for safer (riskier) stocks.  Using my global data, this is what this statistic looks like, across sectors:

Utilities again come in as safest, using this risk metric, tied with real estate, and health care has the widest price ranges of the companies in my sample.

2. Standard deviation in price changes: This is a standard statistical construct, and measures volatility in a stock, though it does not distinguish between upside and downside volatility. Based upon the company-specific standard deviations, again averaged out across sectors, here is what the numbers looked like in 2025:

Financials and utilities are the two safest sectors, and technology and health care are the riskiest, if you measure risk with standard deviation.

3. Betas: If you buy into the notion that the investors setting prices are diversified, and thus care only about risk that cannot be diversified away, you will focus only on the portion of the standard deviation in a stock that comes from the market, and betas, notwithstanding the misinterpretations and misreading, are trying to measure that non-diversifiable portion of standard deviation and scale around one. Again, looking across industries, I look at the distribution of betas, by sector:

If you are interested in a less broad categorization, you can check out betas by industry at the end of this post.

As you review the sector rankings using the varied risk measures, you can see why the heated debates about which risk measure to use is often overdone, since they, for the most part, rank the sectors similarly, with the sectors having less earnings volatility and fewer money-losers also having less volatility in stock price, smaller price ranges and lower betas.

Hurdle Rates
    Even as we wrestle with choosing between price and accounting-based measures, it is worth remembering that the end game here is not the risk measure itself, and that risk measures are a means to an end, which is estimating hurdle rates. Hurdle rates come into play for both businesses and investors, setting thresholds that they can use to determine whether to invest or not:

There are some investors and businesses who believe that hurdle rates come from their guts, numbers that reflect personal risk aversion and past experiences, but hurdle rates are opportunity costs, reflecting returns that investors (businesses) can earn in the market on investments of equivalent risk. 

    In the context of a business, which raises money from debt and equity, you can look at hurdle rates through the eyes of the capital providers – a cost of equity, capturing what equity investor believers expect to make on other equity investments of equivalent risk, and a cost of debt, looking at what lenders can earn on lending to others with similar default risk:

That is what all risk and return models try to do, albeit with different degrees of fidelity to the principle. In fact, my use of an implied equity risk premium in the estimation of the cost of equity is designed to advance this cause, since it is model-agnostic and reflects what investors are pricing stocks to earn, on an annual basis. Thus, when you use the beta in the capital asset pricing model to derive the cost of equity, you should be computing the return you can earn elsewhere in the market on other investments with the same beta, making the cost of equity the hurdle rate for equity investments in a project or company. The cost of capital, which incorporate the cost of borrowing into its construct, is also a hurdle rate, albeit to both debt and equity providers:

As to the question of which of these hurdle rates you should use as a business, the answer lies in consistence. If you are looking at equity returns (return on equity or an internal rate of return based on equity cash flows alone), you should be measuring up against just the cost of equity. Alternatively, with returns on invested capital or an internal rate of return based upon cashflows to the business (pre-debt), it is the cost of capital that comes into play.

I compute the costs of equity and capital for all 48,156 firms in my sample, and in doing so, and in the interests of consistency and ease, I make some simplifying assumptions:

Once I have the costs of equity and capital for each firm, I compute industry averages, both for global firms, and by region (US, Japan, Europe, Emerging Markets, with India and China as sub-categories). You can find the links to the data at the end of this post, but there is another perspective that you can bring to the cost of capital discussion, based upon where a company falls in the company life cycle:

Intuitively, you would expect more uncertainty about business prospects with younger firms, than older ones, especially on the estimation front. That said, it is an open question of whether this uncertainty will translate into higher costs of equity and capital, since it depends on who the marginal investors in these firms are, and whether the risk is diversifiable (and not affect cost of equity) or non-diversifiable. To answer these questions, I classify firms into ten deciles, based on their corporate age, and compute costs of capital:

As you can see, there is no discernible pattern on costs of equity, as you go across the age classes. However, as firms age, they do borrow more, partly because their capacity to generate earnings increase, and that does have some impact on the cost of capital, especially with the oldest firms in the market.
    In corporate finance and valuation, an undervalued skill is having perspective, a sense of what comprises typical, and what is a high or a low value. It is for that reason that I also compute a histogram of costs of capital of all publicly traded firms at the start of 2026:

This table is one on my most-used, for many reasons. First, when doing my own valuations, especially for young firms or for firms where the cost of capital is in flux, it gives me the input to us. Thus, if I am valuing a small, AI firm that has just gone public and has global operations, in US dollars, I will start the valuation with a cost of capital of 11.66% and move that cost of capital over time towards 8.65%, as its gets larger and more established. Second, I do see (and must review or grade) other people’s valuations more than I do my own, and this table operates as a plausibility check; a valuation of a publicly traded US company that has a dollar cost of capital of 14% goes on my suspect list, since that is well above the 90th percentile for US firms. Third, the table operates as a reminder that any analysts where the bulk of the time is spent estimating and finessing the cost of capital is time ill-spent, since the 80% of all US (global) companies have costs of capital between 5.26% (6.28%) and 9.88% (11.66%).

    For those working in different currencies, the inflation differential approach that I described and used in the last post can be used to convert the entire table. Thus, if you use the expected inflation rates of 2.24% and 4.00% for the United States and India, from the IMF forecasts, you can 1.76% to each of the numbers to each dollar cost of capital that you see in the table or as an industry average.

Conclusion

    To run a business or invest in one, you need hurdle rates, and that is what costs of equi6y and debt measure. While models and equations may be how you get these numbers, it is always worth going back to first principles, whenever you face questions on what to do. Thus, recognizing that the cost of capital is an opportunity cost, i.e., the rate of return you can earn elsewhere in the market, on investments of equivalent risk, should be a prompt to use betas that reflect the risk in investments, rather than the entities making the investment, and updated costs of borrowing for the cost of debt. As we enter 2026, we are now in our fourth year with US dollar riskfree rates around 4%, and companies and investors seem to have become acclimatized to the resulting costs of capital, and the shock of seeing dollar riskfree rates surge in 2022, pushing up costs of capital across the board seem to have faded.

YouTube


Datasets

1. Earnings variability, by industry (Global in 2025)
2. Money making and losing percentages, by industry (Global in 2025)
3. Pricing risk measures, by industry (Global in 2025)
4. Betas by industry group (US, Global, Japan, Europe, Emerging Markets, India & China)
5. Cost of capital by industry group (US, Global, Japan, Europe, Emerging Markets, India & China)

Data Update Posts for 2026

1. Data Update 1 for 2026: The Push and Pull of Data
2. Data Update 2 for 2026: Equities get tested and pass again!
3. Data Update 3 for 2026: The Trust Deficit - Bonds, Currencies, Gold and Bitcoin!
4. Data Update 4 for 2026: The Global Perspective
5. Data Update 5 for 2026: Risk and Hurdle Rates

Data Update 4 for 2026: The Global Perspective!

    If you have read my first three data updates in 2026, I won’t blame you if you skip this one, because you found them long and boring. I won't take issue with you either if you viewed them as too US-focused, because I did spend my second data update, looking at US equities, and my third, examining US treasuries and the US dollar. In this post, I widen my data analysis to look at the rest of the world, starting with a journey through global equity markets in 2025, moving on to creating a snapshot of country risk at the start of 2025 and finishing by looking at interest rate differences across currencies. Along the way, I will argue for a larger narrative, underlying this global perspective. I am not a political or a macroeconomic analyst, but I attribute much of what we have seen in terms of global politics and economics in the last four decades, first to the rise of globalization as an almost unstoppable force, shaping immigration and economic policies in much of the world, and then, in most recent years, to a backlash against the same forces. That backlash has not only upended the political order in the developed world, with both Europe and the United States seeing changes in power structure, but also brought nationalist parties to power in many emerging market countries. From investing and business perspectives, we saw the effects play out strongly in 2025, and I don't think that this genie is going back into the bottle.

Global Equties in 2025

    In my second data update, I noted that US equities had a good year in 2025, delivering a return of 17.72% for the year, but the US dollar weakened in 2025, down a bit more than 7% during the year. I started my exploration of global equities by looking at the returns in local currency terms of equity indices in different parts of the world:

 

In each region, I have highlighted the best performing index (in green) and worst performing one (in red), and you can see the disparities in market performance, even within regions. One of the problems with comparing returns across currencies is that they are distorted by the effects of inflation that also vary widely across currencies. While I will look at inflation differences in more detail later in this post, one way to make the returns comparable is to recompute them in a common currency. To this end, I compute the dollar returns, in aggregate dollar market capitalization terms, in 2025:

As I mentioned in my second data update, India was the worst performing sub-region of the world, up only 3.31% in 2025, and those returns reflect not just a relatively below-average year in local currency terms, with the Sensex up 8.55% for the year, but a weaker currency, with the rupee depreciating against the dollar. It is only one year and while I will need read too much into it, my argument earlier last year that the India story has legs, but that the path to delivering it will be rockier than many of its advocates seem to thing. For much of the rest of the world, the dollar returns are higher than local currency returns, because of currency appreciation against the dollar.

    Zeroing in on the aggregate market capitalization across the world at the start of 2026, I first created a pie chart (on the left)  breaking market capitalization by region, and as you can see, US equities, in spite of a weaker dollar, accounted for 47% of global market capitalization.

Evaluating just the change in market capitalization during 2025, in the second pie (not he right), you can see the reason for the slippage in the US hare, with the US punching in below its weight (38% of the change) and Europe and China weighing in, with larger shares. 

  To close this section, I will unwrite an epitaph for international diversification that many US investors, wealth advisors and market experts were starting to etch in stone even a year ago. For much of the twenty first century, an investor invested entirely in US stocks would have outperformed one who followed the textbook advice to diversify globally. While that may look sound conclusive, the truth is that two decades is not a long time period in stock market history and that you can have extended market runs that look permanent, even when they are not. It is true that as multinationals displace domestic companies, the payoff to international diversification has become smaller over time; buying the S&P 500 would have bought your exposure to the global economy, since the companies in the index, while incorporated in the US, get almost 60% of their revenues in the rest of the world. However, the underperformance of the US, relative to the rest of the world, in 2025 should be a reminder that international diversification still belongs in the toolkit for a prudent investor. That lesson cuts across the globe, and suggests that much as politicians and countries may want to delink from each others, investors don't have that choice.

Country risk in 2025

    If you have been a reader of my posts, I do have a bit of an obsession with country risk,, i.e., why the risk of investing and doing business varies across countries, and what causes that risk to change. My defense for that is that I teach corporate finance and valuation, and to do either, I need answers to these country risk questions, and while you may not like the short cuts and approximations I use along the way, I will take you along on my January 2026 journey:

    The place to start any discussion of country risk is with an examination of the factors that feed into that risk, and I will use a matrix that you may have seen in my prior posts on country risk:

While I do take a deeper and more detailed look at these factors in a mid-year update that I do every year (links to paper and my July 2025 blog post), the forces that cause differences in country risk span politics and economics, and include:

1. Political Structure: From an investing and business standpoint, the choice between democracy and autocracy is nuanced, with the former creating more continuous uncertainty, as changes in government bring more policy change , and the latter creating more policy stability in the near term, albeit with a greater likelihood for wrenching and potentially catastrophic uncertainties over time.
2. War and Violence: Investing and business become more hazardous, both physically and economically, if you invest in a more violent setting, and war, terrorism and access to weapons can create differences across countries.
3. Corruption: Corruption affects businesses directly, operating as implicit taxes on businesses that are exposed to it, and indirectly, by undercutting trust and the willingness to follow rules. While differences in corruption across countries are often attributed to cultural factors, a significant component of corruption comes from structures that are designed to encourage and reward it.
4. Legal and Property rights: Investors and businesses are dependent on contracts and legal agreements to operate, but protection for property rights. Legal systems that are capricious in how they enforce contractual and ownership rights, or delay judgments to make them effectively useless, create risks for businesses and investors.

There are many reasons to expect differences across countries, on these dimensions, there is a different perspective that can also help. As some of you may know, I look at businesses through the lens of a corporate life cycle, where as businesses age, their characteristics and challenges change as well. That life cycle structure can be used to explain differences across countries, where the age is less tied to how long a country has been in being and more to do with its economy.

Young economies have higher growth potential, but that higher economic growth comes with more risk (more volatile economies) and require more robust governance to deliver on their promise. As economies age, they face a period of lower growth, albeit with more economic stability, and governance matters less, effectively become mature (middle aged) economies. There is a final phase, where a country’s economy hits walls, and growth can stagnate or even become negative, driven partly by a loss of competitive edge and partly by aging populations. In each of these phases, countries often overreach, with young countries aspiring for the stability of middle age, while trying to grow at double-digit rates, and mature companies, seeking to rediscover high growth. Without treading too much on political terrain, it may be worth thinking about the Trump actions in 2025 as driven, at least partially, by nostalgia for a different time, when the United States was the dominant economic power, with a combination of solid economic growth and stability that few economies, almost unmatched in history.

    With that philosophical discourse in country risk out of the way, let’s turn to the brass tacks of measuring country risk, starting with one of the most accessible and widely available one, which are ratings that agencies such as S&P, Moody’s and Fitch (among others) attach to sovereigns. The following is the heatmap of sovereign ratings (from Moody’s) at the start of 2026:

While Moody’s rates more than 140 countries, there remain a few (called frontier markets) that have no ratings, but in terms of the color map, I have included those countries with the lowest rated, because they share many of the same risk characteristics. There are three key features of these ratings that are worth emphasizing:

1. The sovereign ratings are focused almost entirely on default risk, and while the chance that a country will default is correlated with the core risks (violence, political structure, legal system and corruption) that I mentioned up front, there are countries on this list where they diverge. I believe that this is especially the case in the Middle East, where there are countries, like Saudi Arabia, that have low or no default risk, but remain exposed to large political risks.
2. The sovereign ratings have their share of biases, for or against regions, but their bigger sin is that they are slow to react. If you look at the list, you will see countries like Argentina and Venezuela that have seen significant changes in governance and politics in the last year, but where the ratings have not changed or barely changed. That will probably change in 2026, but this delayed response will mean that the sovereign ratings for some countries, at least, will not be good reflections of country risk, at the moment.
3. There were a few ratings changes in 2025, mostly at the margin, but the one that got the most attention was the ratings downgrade for the US that I highlighted at the time it happened. While markets, for the most part, took that ratings downgrade in stride, it did create waves in the process that I use to estimate riskfree rates and equity risk premiums, by country, as you will see later in this post.

The reason that so much of how we deal with country risk rests on sovereign ratings is not because ratings agencies have special insights, but because sovereign ratings, unlike other (often more comprehensive) measures of country risk, like country risk scores (from PRS or the Economist, to name two), can be converted into default spreads that conveniently feed into financial analysis. At the start of 2026, here are my estimates of default spreads for each sovereign rating:

As I noted earlier though, using sovereign ratings to get default spreads comes with the limitations that these ratings may not reflect current conditions, when change is rapid, and that is where the sovereign CDS market has created an alternative. For the 80 countries where sovereign CDS exist, you can get a market-determined number for the default spread, and here are the numbers at the start of 2026:

Note that these spreads, while noisy and reflective of market mood, reflect the world we live in, and both Argentina and Venezuela, which used to be uninsurable, have both seen improvement on these market-driven numbers, albeit from impossible to insure to really costly to insure.

    As a final step in my country risk exploration, I repeat a process that I have used to estimate equity risk premiums, by country, every six months for close to three decades. That process starts with estimating an equity risk premium for the S&P 500, and then uses the country default spreads (based upon the ratings) to estimate equity risk premiums for countries:

It is undeniable that the ratings downgrade for the US has created some change in this process. Instead of using the S&P 500’s implied equity risk premium as my estimate of the mature market premium, which was my pathway until May 2025, I now remove the default spread (0.23%) for the US from that premium to get to a mature market equity risk premium (4.23%). To get to country risk premiums for individual countries, I scale up the ratings-based default spreads for the relative riskiness of equities, and add these country risk premiums to the mature market premium:

Download equity risk premiums, by country

Note that I bring the frontier countries into the mix, by using country risk scores for these countries to estimate country and equity risk premiums. 

The Currency Effect

    While it remains true that country risk and currency volatility/devaluation often go together, one of my concerns with mixing up the two up is that you end up double counting or miscounting risk. To understand the divide between country and currency risk, I start with a look at government bond rates in different currencies, with the caveat that there only about forty governments that issue bonds in their local currencies and that some or many of these government bonds are lightly traded, making their rates unreliable.

In many finance classes and textbooks, you are often taught (as I was) to use the government bond rate as the riskfree rate, on the facile assumption that governments should not default on these bonds, since they can print more currency and cover their debt obligations. The problem with that logic is that it is at odds with the reality that governments can, and often do, default on local currency bonds, choosing that option over devaluation. That also means that the government bond rates can include a default risk component, and to get to a riskfree rate, that default risk needs to be removed from the government bond rate. In the picture above, that is what I do, using the ratings-based default spread). After this clean-up, you can see that riskfree rates vary widely across currencies, from very low in some currencies (Swiss Franc, Japanese yen and the Thai Baht), slightly higher for others (US dollar, Euros) and very high on a few (Turkish Lira, Zambian kwacha). 

    In my third data update, I estimated an intrinsic riskfree rate for the US dollar, by adding inflation and real GDP growth. Extending that lesson to other currencies, the primary reason for differences in these riskfree rates, across currencies, is expected inflation, with higher(lower) interest rates in higher (lower) inflation currencies. While inflation measures are imperfect and expected inflation estimates are often flawed, I use the IMF’s estimates of inflation to build a global inflation heat map:

The logic that I used to argue that it is unlikely that you will see US treasury bond rates drop much below 4%, at least as long as inflation runs hot (2.5-3%), not only applies for other currencies, but yields a roadmap for estimating riskfree rates in those currencies (including those without a government bond in the local currency). To illustrate, I will try to estimate an Egyptian pound riskfree rate at the start of 2026:

Riskfree rate in local currency = Riskfree rate in US dollars + (Expected inflation rate in local currency – Expected inflation in US $)

Thus, the riskfree rate in Egyptian pounds, using the expected inflation rates of 7.78% for Egypt and 2.24% for the United States is 9.49%:

          Riskfree rate in US dollars = US T.Bond rate - US default spread = 4.18% -0.23% = 3.95%

Riskfree rate in EGP (1/1/26) = Riskfree rate in US $ + (Expected inflation in Egypt – Expected inflation in US) = 3.95% + (7.78% - 2.24%) = 9.49%

Note that the riskfree rate in US $ is 3.95%, obtained by cleansing the US 10-year treasury rate on January 1, 2026 (4.18%) of US default risk (0.23%). The estimate for a riskfree rate is an approximation is an approximation, since inflation rates compound, and that compounded version is below:

Riskfree rate in EGP = (1+ US $ Riskfree Rate) × (1 + Expected inflation rate in EGP)/ (1+ Expected inflation rate in US $) -1 = 1.0395 × (1.0778/ 1.0224) -1 = .0958 or 9.58%

I have used IMF inflation rates to get riskfree rates in almost all global currencies in this link, but I don’t blame you, if you are skeptical about the expected inflation numbers. From a financial analysis and valuation perspective, I have good news and it is that it does not matter if you are wrong on inflation, if you are consistently so (in both your earnings and cash flows as well as your discount rates).

Put simply, the effects of expected inflation in valuation cancel out, and that is that the basis of what I would term “the currency invariance theorem”, where the value of a project or company should not change, if you change the currency in which you do your analysis. A project that has a positive NPV, when the analysis is done in US $, should continue to have the same positive NPV, if you redo the analysis in EGP, and a company that is overvalued, when the valuation is in US $, will remain overvalued, if you revalue it in EGP. The currency you chose to do an analysis is cannot alter the underlying value but that does not mean that changes in inflation cannot change the values of businesses, since that effect will depend on how well a company can pass inflation through to its customers (with pricing power), and I examined that relationship in 2022, after inflation had a resurgence in the United States after a decade of being low and boring. 

Thus, high inflation in Turkish lira has undoubtedly wreaked havoc the value of some Turkish companies, but given that damage, my point is that revaluing these companies in Euros will not undo that damage.

The Bottom Line

   As globalization gets a blowback, and in the midst of turmoil from tariffs, we got a reminder of how, much as we may want to go back to simpler times where the rest of the world did not intrude into our lives, we are all connected in good and bad ways. Thus, you may disagree with me on how to measure country risk and to bring into your analysis and investments, but it is undeniable that risk varies across countries and that we must incorporate that risk into our decision making. I hope that this post expose the layers in the process from the drivers of country risk to how these drivers play out as differences in country ratings, default spreads and equity risk premiums, while illustrating th how country risk can change over time, and sometimes in short periods.

YouTube Video

Datasets

1. Equity risk premiums by country at the start of 2026
2. Differential-inflation riskfree rates, by currency, at the start of 2026

Data Update Posts for 2026

1. Data Update 1 for 2026: The Push and Pull of Data
2. Data Update 2 for 2026: Equities get tested and pass again!
3. Data Update 3 for 2026: The Trust Deficit - Bonds, Currencies, Gold and Bitcoin!
4. Data Update 4 for 2026: The Global Perspective