In my last three posts, I looked at the macro (equity risk premiums, default spreads, risk free rates) and micro (company risk measures) that feed into the expected returns we demand on investments, and argued that these expected returns become hurdle rates for businesses, in the form of costs of equity and capital. Since businesses invest that capital in their operations, generally, and in individual projects (or assets), specifically, the big question is whether they generate enough in profits to meet these hurdle rate requirements. In this post, I start by looking at the end game for businesses, and how that choice plays out in investment rules for these businesses, and then examine how much businesses generated in profits in 2023, scaled to both revenues and invested capital.
The End Game in Business
If you start a business, what is your end game? Your answer to that question will determine not just how you approach running the business, but also the details of how you pick investments, choose a financing mix and decide how much to return to shareholders, as dividend or buybacks. While private businesses are often described as profit maximizers, the truth is that if they should be value maximizers. In fact, that objective of value maximization drives every aspect of the business, as can be seen in this big picture perspective in corporate finance:
For some companies, especially mature ones, value and profit maximization may converge, but for most, they will not. Thus, a company with growth potential may be willing to generate less in profits now, or even make losses, to advance its growth prospects. In fact, the biggest critique of the companies that have emerged in this century, many in social media, tech and green energy, is that they have prioritized scaling up and growth so much that they have failed to pay enough attention to their business models and profitability.
For decades, the notion of maximizing value has been central to corporate finance, though there have been disagreements about whether maximizing stock prices would get you the same outcome, since that latter requires assumptions about market efficiency. In the last two decades, though, there are many who have argued that maximizing value and stockholder wealth is far too narrow an objective, for businesses, because it puts shareholders ahead of the other stakeholders in enterprises:
It is the belief that stockholder wealth maximization shortchanges other stakeholders that has given rise to stakeholder wealth maximization, a misguided concept where the end game for businesses is redefined to maximize the interests of all stakeholders. In addition to being impractical, it misses the fact that shareholders are given primacy in businesses because they are the only claim holders that have no contractual claims against the business, accepting residual cash flows, If stakeholder wealth maximization is allowed to play out, it will result in confused corporatism, good for top managers who use stakeholder interests to become accountable to none of the stakeholders:
As you can see, I am not a fan of confused corporatism, arguing that giving a business multiple objectives will mangle decision making, leaving businesses looking like government companies and universities, wasteful entities unsure about their missions. In fact, it is that skepticism that has made me a critic of ESG and sustainability, offshoots of stakeholder wealth maximization, suffering from all of its faults, with greed and messy scoring making them worse.
It may seem odd to you that I am spending so much time defending the centrality of profitability to a business, but it is a sign of how distorted this discussion has become that it is even necessary. In fact, you may find my full-throated defense of generating profits and creating value to be distasteful, but if you are an advocate for the point of view that businesses have broader social purposes, the reality is that for businesses to do good, they have to be financial healthy and profitable. Consequently, you should be just as interested, as I am, in the profitability of companies around the world, albeit for different reasons. My interest is in judging them on their capacity to generate value, and yours would be to see if they are generating enough as surplus so that they can do good for the world.
Profitability: Measures and Scalars
Measuring profitability at a business is messier than you may think, since it is not just enough for a business to make money, but it has to make enough money to justify the capital invested in it. The first step is understanding profitability is recognizing that there are multiple measures of profit, and that each measure they captures a different aspect of a business:
It is worth emphasizing that these profit numbers reflect two influences, both of which can skew the numbers. The first is the explicit role of accountants in measuring profits implies that inconsistent accounting rules will lead to profits being systematically mis-measured, a point I have made in my posts on how R&D is routinely mis-categorized by accountants. The other is the implicit effect of tax laws, since taxes are based upon earnings, creating an incentive to understate earnings or even report losses, on the part of some businesses. That said, global (US) companies collectively generated $5.3 trillion ($1.8 trillion) in net income in 2023, and the pie charts below provide the sector breakdowns for global and US companies:
Notwithstanding their trials and tribulations since 2008, financial service firms (banks, insurance companies, investment banks and brokerage firms) account for the largest slice of the income pie, for both US and global companies, with energy and technology next on the list.
Profit Margins
While aggregate income earned is an important number, it is an inadequate measure of profitability, especially when comparisons across firms, when it is not scaled to something that companies share. As as a first scalar, I look at profits, relative to revenues, which yields margins, with multiple measures, depending upon the profit measure used:
Looking across US and global companies, broken down by sector, I look at profit margins in 2023:
Note that financial service companies are conspicuously absent from the margin list, for a simple reason. Most financial service firms have no revenues, though they have their analogs - loans for banks, insurance premiums for insurance companies etc. Among the sectors, energy stands out, generating the highest margins globally, and the second highest, after technology firms in the United States. Before the sector gets targeted as being excessively profitable, it is also one that is subject to volatility, caused by swings in oil prices; in 2020, the sector was the worst performing on profitability, as oil prices plummeted that year.
Does profitability vary across the globe? To answer that question, I look at differences in margins across sub-regions of the world:
You may be surprised to see Eastern European and Russian companies with the highest margins in the world, but that can be explained by two phenomena. The first is the preponderance of natural resource companies in this region, and energy companies had a profitable year in 2023. The second is that the sanctions imposed after 2021 on doing business in Russia drove foreign competitors out of the market, leaving the market almost entirely to domestic companies. At the other end of the spectrum, Chinese and Southeast Asian companies have the lowest net margins, highlighting the reality that big markets are not always profitable ones.
Finally, there is a relationship between corporate age and profitability, with younger companies often struggling more to deliver profits, with business models still in flux and no economies of scale. In the fact, the pathway of a company through the life cycle can be seen through the lens of profit margins:
Early in the life cycle, the focus will be on gross margins, partly because there are losses on almost every other earnings measure. As companies enter growth, the focus will shift to operating margins, albeit before taxes, as companies still are sheltered from paying taxes by past losses. In maturity, with debt entering the financing mix, net margins become good measures of profitability, and in decline, as earnings decline and capital expenditures ease, EBITDA margins dominate. In the table below, I look at global companies, broken down into decals, based upon corporate age, and compute profit margins across the deciles:
The youngest companies hold their own on gross and EBITDA margins, but they drop off as you move to operating nnd net margins.
In summary, profit margins are a useful measure of profitability, but they vary across sectors for many reasons, and you can have great companies with low margins and below-average companies that have higher margins. Costco has sub-par operating margins, barely hitting 5%, but makes up for it with high sales volume, whereas there are luxury retailers with two or three times higher margins that struggle to create value.
Return on Investment
The second scalar for profits is the capital invested in the assets that generate these profits. Here again, there are two paths to measuring returns on investment, and the best way to differentiate them is to think of them in the context of a financial balance sheet:
The accounting return on equity is computed by dividing the net income, the equity investor's income measure, by the book value of equity and the return on invested capital is computed, relative to the book value of invested capital, the cumulative values of book values of equity and debt, with cash netted out. Looking at accounting returns, broken down by sector, for US and global companies, here is what 2023 delivered:
In both the US and globally, technology companies deliver the highest accounting returns, but these returns are skewed by the accounting inconsistencies in capitalizing R&D expenses. While I partially correct for this by capitalizing R&D expenses, it is only a partial correction, and the returns are still overstated. The worst accounting returns are delivered by real estate companies, though they too are skewed by tax considerations, with expensing to reduce taxes paid, rather than getting earnings right.
Excess Returns
In the final assessment, I bring together the costs of equity and capital estimated in the last post and the accounting returns in this one, to answer a critical question that every business faces, i.e,, whether the returns earned on its investment exceed its hurdle rate. As with the measurement of returns, excess returns require consistent comparisons, with accounting returns on equity compared to costs of equity, and returns on capital to costs of capital:
These excess returns are not perfect or precise, by any stretch of the imagination, with mistakes made in assessing risk parameters (betas and ratings) causing errors in the cost of capital and accounting choices and inconsistencies affecting accounting returns. That said, they remain noisy estimates of a company's competitive advantages and moats, with strong moats going with positive excess returns, no moats translating into excess returns close to zero and bad businesses generating negative excess returns.
I start again by looking at the sector breakdown, both US and global, of excess returns in 2023, in the table below:
In computing excess returns, I did add a qualifier, which is that I would do the comparison only among money making companies; after all, money losing companies will have accounting returns that are negative and less than hurdle rates. With each sector, to assess profitability, you have to look at the percentage of companies that make money and then at the percent of these money making firms that earn more than the hurdle rate. With financial service firms, where only the return on equity is meaningful, 57% (64%) of US (global) firms have positive net income, and of these firms, 82% (60%) generated returns on equity that exceeded their cost of equity. In contrast, with health care firms, only 13% (35%) of US (global) firms have positive net income, and about 68% (53%) of these firms earn returns on equity that exceed the cost of equity.
In a final cut, I looked at excess returns by region of the world, again looking at only money-making companies in each region:
To assess the profitability of companies in each region, I again look at t the percent of companies that are money-making, and then at the percent of these money-making companies that generate accounting returns that exceed the cost of capital. To provide an example, 82% of Japanese companies make money, the highest percentage of money-makers in the world, but only 40% of these money-making companies earn returns that exceed the hurdle rate, second only to China on that statistic. The US has the highest percentage (73%) of money-making companies that generate returns on equity that exceed their hurdle rates, but only 37% of US companies have positive net income. Australian and Canadian companies stand out again, in terms of percentages of companies that are money losers, and out of curiosity, I did take a closer look at the individual companies in these markets. It turns out that the money-losing is endemic among smaller publicly traded companies in these markets, with many operating in materials and mining, and the losses reflect both company health and life cycle, as well as the tax code (which allows generous depreciation of assets). In fact, the largest companies in Australia and Canada deliver enough profits to carry the aggregated accounting returns (estimated by dividing the total earnings across all companies by the total invested capital) to respectable levels.
In the most sobering statistic, if you aggregate money-losers with the companies that earn less than their hurdle rates, as you should, there is not a single sector or region of the world, where a majority of firms earn more than their hurdle rates.
In 2023, close to 80% of all firms globally earned returns on capital that lagged their costs of capital. Creating value is clearly far more difficult in practice than on paper or in case studies!
A Wrap!
I started this post by talking about the end game in business, arguing for profitability as a starting point and value as the end goal. The critics of that view, who want to expand the end game to include more stakeholders and a broader mission (ESG, Sustainability) seem to be operating on the presumption that shareholders are getting a much larger slice of the pie than they deserve. That may be true, if you look at the biggest winners in the economy and markets, but in the aggregate, the game of business has only become harder to play over time, as globalization has left companies scrabbling to earn their costs of capital. In fact, a decade of low interest rates and inflation have only made things worse, by making risk capital accessible to young companies, eager to disrupt the status quo.
In my last data updates for this year, I looked first at how equity markets rebounded in 2023, driven by a stronger-than-expected economy and inflation coming down, and then at how interest rates mirrored this rebound. In this post, I look at risk, a central theme in finance and investing, but one that is surprisingly misunderstood and misconstrued. In particular, there are wide variations in how risk is measured, and once measured, across companies and countries, and those variations can lead to differences in expected returns and hurdle rates, central to both corporate finance and investing judgments.
Risk Measures
There is almost no conversation or discussion that you can have about business or investing, where risk is not a part of that discussion. That said, and notwithstanding decades of research and debate on the topic, there are still wide differences in how risk is defined and measured.
What is risk?
I do believe that, in finance, we have significant advances in understanding what risk, I also think that as a discipline, finance has missed the mark on risk, in three ways. First, it has put too much emphasis on market-price driven measures of risk, where price volatility has become the default measure of risk, in spite of evidence indicating that a great deal of this volatility has nothing to do with fundamentals. Second, in our zeal to measure risk with numbers, we have lost sight of the reality that the effects of risk are as much on human psyche, as they are on economics. Third, by making investing a choice between good (higher returns) and bad (higher risk), a message is sent, perhaps unwittingly, that risk is something to be avoided or hedged. It is perhaps to counter all of these that I start my session on risk with the Chinese symbol for crisis:
Chinese symbol for crisis = 危機 = Danger + Opportunity
I have been taken to task for using this symbol by native Chinese speakers pointing out mistakes in my symbols (and I have corrected them multiple times in response), but thinking of risk as a combination of danger and opportunity is, in my view, a perfect pairing, and this perspective offers two benefits. First, by linking the two at the hip, it sends the clear and very important signal that you cannot have one (opportunity), without exposing yourself to the other (danger), and that understanding alone would immunize individuals from financial scams that offer the best of both worlds - high returns with no risk. Second, it removes the negativity associated to risk, and brings home the truth that you build a great business, not by avoiding danger (risk), but by seeking out the right risks (where you have an advantage), and getting more than your share of opportunities.
Breaking down risk
One reason that we have trouble wrapping our heads around risk is that it has so many sources, and our capacity to deal with varies, as a consequence. When assessing risk in a project or a company, I find it useful to make a list of every risk that I see in the investment, big and small, but I then classify these risks into buckets, based upon type, with very different ways of dealing with and incorporating that risk into investment analysis. The table below provides a breakdown of those buckets, with economic uncertainty contrasted with estimation uncertainty, micro risk separated from macro risks and discrete risks distinguished from continuous risks:
While risk breakdowns may seem like an abstraction, they do open the door to healthier practices in risk analysis, including the following:
Know when to stop: In a world, where data is plentiful and analytical tools are accessible, it is easy to put off a decision or a final analysis, with the excuse that you need to collect more information. That is understandable, but digger deeper into the data and doing more analysis will lead to better estimates, only if the risk that you are looking at is estimation risk. In my experience, much of the risk that we face when valuing companies or analyzing investments is economic uncertainty, impervious to more data and analysis. It is therefore healthy to know when to stop researching, accepting that your analysis is always a work-in-progress and that decisions have to be made in the face of uncertainty.
Don't overthink the discount rate: One of my contentions of discount rates is that they cannot become receptacles for all your hopes and fears. Analysts often try to bring company-specific components, i.e, micro uncertainties, into discount rates, and in the process, they end up incorporating risk that investors can eliminate, often at no cost. Separating the risks that do affect discount rates from the risks that do not, make the discount rate estimation simpler and more precise.
Use more probabilistic & statistical tools: The best tools for bringing in discrete risk are probabilistic, i.e., decision trees and scenario analysis, and using them in that context may open the door to other statistical tools, many of which are tailor-made for the problems that we face routinely in finance, and are underutilized.
Measuring risk
The financial thinking on risk, at least in its current form, had its origins in the 1950s, when Harry Markowitz uncovered the simple truth that the risk of an investment is not the risk of it standing alone, but the risk it adds to an investor's portfolio. He followed up by showing that holding diversified portfolios can deliver much higher returns, for given levels of risk, for all investors. That insight gave rise not only to modern portfolio theory, but it also laid the foundations for how we measure and deal with risk in finance. In fact, almost every risk and return model in finance is built on pairing two assumptions, the first being that the marginal investors in a company or business are diversified and the second being that investors convey their risk concerns through market prices:
By building on the assumptions that the investors pricing a business are diversified, and make prices capture that risk, modern portfolio theory has exposed itself to criticism from those who disagree with one or both of these assumptions. Thus, there are value investors, whose primary disagreement is on the use of pricing measures for risk, arguing that risk has to come from numbers that drive intrinsic value - earnings and cash flows. There are other investors who are at peace with price-based risk measures , but disagree with the "diversified marginal investor" assumption, and they are more intent on finding risk measures that incorporate total risk, not just risk that cannot be diversified away. I do believe that the critiques of both groups have legitimate basis, and while I don't feel as strongly as they do, I can offer modifications of risk measures to counter the critiques;
For investors who do not trust market prices, you can create risk analogs that look at accounting earnings or cash flows, and for those who believe that the diversified investor assumption is an overreach, you can adapt risk measures to capture all risk, not just market risk. In short, if you don't like betas and have disdain for modern portfolio theory, your choice should not be to abandon risk measurement all together, but to come up with an alternative risk measure that is more in sync with your view of the world.
Risk Differences across Companies
With that long lead-in on risk, we are positioned to take a look at how risk played out, at the company level, in 2024. Using the construct from the last section, I will start by looking at price-based risk measures and then move on to intrinsic risk measures in the second section.
a. Price-based Risk Measures
My data universe includes all publicly traded companies, and since they are publicly traded, computing price-based risk measures is straight forward. That said, it should be noted that liquidity varies widely across these companies, with some located in markets where trading is rare and others in markets, with huge trading volumes. With that caveat in mind, I computed three risk-based measures - a simplistic measure of range, where I look at the distance between the high and low prices, and scale it to the mid-point, the standard deviation in stock prices, a conventional measure of volatility and beta, a measure of that portion of a company's risk that is market-driven.
I use the data through the end of 2023 to compute all three measures for every company, and in my first breakdown, I look at these risk measures, by sector (globally):
Utilities are the safest or close to the safest , on all three price-based measures, but there are divergences on the other risk measures. Technology companies have the highest betas, but health care has the riskiest companies, on standard deviation and the price range measure. Looking across geographies, you can see the variations in price-based risk measures across the world:
There are two effects at play here. The first is liquidity, with markets with less trading and liquidity exhibiting low price-based risk scores across the board. The second is that some geographies have sector concentrations that affect their pricing risk scores; the preponderance of natural resource and mining companies in Australia and Canada, for instance, explain the high standard deviations in 2023.
Finally, I brought in my corporate life cycle perspective to the risk question, and looked at price-based risk measures by corporate age, with the youngest companies in the first decile and the oldest ones in the top decile (with a separate grouping for companies that don't have a founding year in the database):
On both the price range and standard deviation measures, not surprisingly, younger firms are riskier than older ones, but on the beta measure, there is no relationship. That may sound like a contradiction, but it does reflect the divide between measures of total risk (like the price range and standard deviation) and measures of just market risk (like the beta). Much of the risk in young companies is company-specific, and for those investors who hold concentrated portfolios of these companies, that risk will translate into higher risk-adjusted required returns, but for investors who hold broader and more diversified portfolios, younger companies are similar to older companies, in terms of risk.
b. Intrinsic Risk Measures
As you can see in the last section, price-based risk measures have their advantages, including being constantly updated, but they do have their limits, especially when liquidity is low or when market prices are not trustworthy. In this section, I will look at three measures of intrinsic risk - whether a company is making or losing money, with the latter being riskier, the variability in earnings, with less stable earnings translating to higher risk, and the debt load of companies, with more debt and debt charges conferring more risk on companies.
I begin by computing these intrinsic risk measures across sectors, with the coefficient of variation on both net income and operating income standing in for earnings variability; the coefficient of variation is computed by dividing the standard deviation in earnings over the last ten years, divided by the average earnings over those ten years.
Globally, health care has the highest percentage of money-losing companies and utilities have the lowest. In 2023, energy companies have the most volatile earnings (net income and operating income) and real estate companies have the most onerous debt loads. Looking at the intrinsic risk measures for sub-regions across the world, here is what I see:
Again, Australia and Canada have the highest percentage of money losing companies in the world and Japan has the lowest, Indian companies have the highest earnings variability and Chinese companies carry the largest debt load, in terms of debt as a multiple of EBITDA. In the last table, I look at the intrinsic risk measures, broken down by company age:
Not surprisingly, there are more money losing young companies than older ones, and these young companies also have more volatile earnings. On debt load, though, there is no discernible pattern in debt load across age deciles, though the youngest companies do have the lowest interest coverage ratios (and thus are exposed to the most danger, if earnings drop).
Risk Differences across Countries
In this final section, I will look risk differences across countries, both in terms of why risk varies across, as well as how these variations play out as equity risk premiums. There are many reasons why risk exposures vary across countries, but I have tried to capture them all in the picture below (which I have used before in my country risk posts and in my paper on country risk):
Put simply, there are four broad groups of risks that lead to divergent country risk exposures; political structure, which can cause public policy volatility, corruption, which operates as an unofficial tax on income, war and violence, which can create physical risks that have economic consequences and protections for legal and property rights, without which businesses quickly lose value.
While it is easy to understand why risk varies across countries, it is more difficult to measure that risk, and even more so, to convert those risk differences into risk premiums. Ratings agencies like Moody's and S&P provide a measure of the default risk in countries with sovereign ratings, and I build on those ratings to estimate country and equity risk premiums, by country. The figure below summarizes the numbers used to compute these numbers at the start of 2024:
The starting point for estimating equity risk premiums, for all of the countries, is the implied equity risk premium of 4.60% that I computed at the start of 2024, and talked about in my second data post this year. All countries that are rated Aaa (Moody's) are assigned 4.60% as equity risk premiums, but for lower-rated countries, there is an additional premium, reflecting their higher risk:
You will notice that there are countries, like North Korea, Russia and Syria, that are unrated but still have equity risk premiums, and for these countries, the equity risk premiums estimate is based upon a country risk score from Political Risk Services. If you are interested, you can review the process that I use in far more detail in this paper that I update every year on country risk.
Risk and Investing
The discussion in the last few posts, starting with equity risk premium in my second data update, and interest rates and default spreads in my third data update, leading into risk measures that differrentiate across companies and countries in this one, all lead in to a final computation of the costs of equity and capital for companies. That may sound like a corporate finance abstraction, but the cost of capital is a pivotal number that can alter whether and how much companies invest, as well as in what they invest, how they fund their investments (debt or equity) and how much they return to owners as dividends or buybacks. For investors looking at these companies, it becomes a number that they use to estimate intrinsic values and make judgments on whether to buy or sell stocks:
The multiple uses for the cost of capital are what led me to label it "the Swiss Army knife of finance" and if you are interested, you can keep a get a deeper assessment by reading this paper.
Using the updated numbers for the risk free rate (in US dollars), the equity risk premiums (for the US and the rest of the world) and the default spreads for debt in different ratings classes, I computed the cost of capital for the 47,698 companies in my data universe, at the start of 2024. In the graph below, I provide a distribution of corporate costs of capital, for US and global companies, in US dollars:
If your frame of reference is another currency, be it the Euro or the Indian rupee, adding the differential inflation to these numbers will give you the ranges in that currency. At the start of 2024, the median cost of capital, in US dollars, is 7.9% (8.7%) for a US (global) company, lower than the 9.6 (10.6%) at the start of 2023, for US (global) stocks, entirely because of declines in the price of risk (equity risk premiums and default spreads), but the 2024 costs of capital are higher than the historic lows of 5.8% (6.3%) for US (Global) stocks at the start of 2022. In short, if you are a company or an investor who works with fixed hurdle rates over time, you may be using a rationale that you are just normalizing, but you have about as much chance of being right as a broken clock.
What's coming?
Since this post has been about risk, it is a given that things will change over the course of the year. If your question is how you prepare for that change, one answer is to be dynamic and adaptable, not only reworking hurdle rates as you go through the year, but also building in escape hatches and reversibility even into long term decisions. In case things don't go the way you expected them to, and you feel the urge to complain about uncertainty, I urge you to revisit the Chinese symbol for risk. We live in dangerous times, but embedded in those dangers are opportunities. If you can gain an edge on the rest of the market in assessing and dealing with some of these dangers, you have a pathway to success. I am not suggesting that this is easy to do, or that success is guaranteed, but if investment is a game of odds, this can help tilt them in your favor.
In my last post, I looked at equities in 2023, and argued that while they did well during 2023, the bounce back were uneven, with a few big winning companies and sectors, and a significant number of companies not partaking in the recovery. In this post, I look at interest rates, both in the government and corporate markets, and note that while there was little change in levels, especially at the long end of the maturity spectrum, that lack of change called into question conventional market wisdom about interest rates, and in particular, the notions that the Fed sets interest rates and that an inverted yield curve is a surefire predictor of a recession. As we start 2024, the interest rate prognosticators who misread the bond markets so badly in 2023 are back to making their 2024 forecasts, and they show no evidence of having learned any lessons from the last year.
Government Bond/Bill Rates in 2023
I will start by looking at government bond rates across the world, with the emphasis on US treasuries, which suffered their worst year in history in 2022, down close to 20% for the year, as interest rates surged. That same phenomenon played out in other currencies, as government bond rates rose in Europe and Asia during the year, ravaging bond markets globally.
US Treasuries
Investors in US treasuries, especially in the longer maturities, came into 2023, bruised and beaten rising inflation and interest rates. The consensus view at the start of the year was that US treasury rates would continue to rise, with the rationale being that the Federal Reserve was still focused on knocking inflation down, and would raise rates during the yearl. Implicit in this view was the belief that it was the Fed that had created bond market carnage in 2022, and in my post on interest rates at the start of 2023, I took issue with this contention, arguing that it was inflation that was the culprit.
1. A Ride to Nowhere - US Treasury Rates in 2023
It was undoubtedly a relief for bond market investors to see US treasury markets settle down in 2023, though there were bouts of volatility, during the course of the year. The graph below looks at US treasury rates, for maturities ranging from 3 months to 30 years, during the course of 2022 and 2023:
As you can see, while treasury rates, across maturities, jumped dramatically in 2022, their behavior diverged in 2023. At the short end of the spectrum, the three-month treasury bill rate rose from 4.42% to 5.40% during the year, but the 2-year rate decreased slightly from 4.41% to 4.23%, the ten-year rate stayed unchanged at 3.88% and the thirty-year rate barely budged, going from 3.76% to 4.03%. The fact that the treasury bond rate was 3.88% at both the start and the end of the year effectively also meant that the return on a ten-year treasury bond during 2023 was just the coupon rate of 3.88% (and no price change).
2. The Fed Effect: Where's the beef?
I noted at the start of this post that the stock answer than most analysts and investors, when asked why treasury rates rose or fell during much of the last decade has been "The Fed did it". Not only is that lazy rationalization, but it is just not true, and for many reasons. First, the only rate that the Fed actually controls is the Fed funds rate, and it is true that the Fed has been actively raising that rate in the last two years, as you can see in the graph below:
In 2022, the Fed raised the Fed funds rate seven times, with the rate rising from close to zero (lower limit of zero and an upper limit of 0.25%) to 4.25-4.50%, by the end of the year. During 2023, the Fed continued to raise rates, albeit at a slower rate, with four 0.25% raises.
Second, the argument that the Fed's Fed Funds rate actions have triggered increases in interest rates in the last two years becomes shaky, when you take a closer look at the data. In the table below, I look at all of the Fed Fund hikes in the last two years, looking at the changes in 3-month, 2-year and 10-year rates leading into the Fed actions. Thus, the Fed raised the Fed Funds rate on June 16, 2022 by 0.75%, to 1.75%, but the 3-month treasury bill rate had already risen by 0.74% in the weeks prior to the Fed hike, to 1.59%.
In fact, treasury bill rates consistently rise ahead of the Fed's actions over the two years. This may be my biases talking, but to me, it looks like it is the market that is leading the Fed, rather than the other way around.
Third, even if you are a believer that the Fed has a strong influence on rates, that effect is strongest on the shortest term rates and decays as you get to longer maturities. In 2023, for instance, for all of the stories about FOMC meeting snd the Fed raising rates, the two-year treasury declined and the ten-year did not budge. To understand what causes long term interest rates to move, I went back to my interest rate basics, and in particular, the Fisher equation breakdown of a nominal interest rate (like the US ten-year treasury rate) into expected inflation and an expected real interest rate:
If you are willing to assume that the expected real interest rate should converge on the growth rate in the real economy in the long term, you can estimate what I call an intrinsic riskfree rate:
Intrinsic Riskfree Rate = Expected Inflation + Expected real growth rate in economy
In the graph below, I take first shot at estimating this intrinsic riskfree rate, by adding the actual inflation rate each year to the real GDP growth rate in that year, for the US:
I will not oversell this graph, since my assumption about real growth equating to real interest rates is up for debate, and I am using actual inflation and growth, rather than expectations. That said, it is remarkable how well the equation does at explaining the movements in the ten-year US treasury bond rate over time. The rise treasury bond rates in the 1970s can be clearly traced to higher inflation, and the low treasury bond rates of the last decade had far more to do with low inflation and growth, than with the Fed. In 2023, the story of the year was that inflation tapered off during the course of the year, setting to rest fears that it would stay at the elevated levels of 2022. That explains why US treasury rates stayed unchanged, even when the Fed raised the Fed Funds rate, though the 3-month rate remains a testimonial to the Fed's power to affect short term rates.
3. Yield Curves and Economic Growth
It is undeniable that the slope of the yield curve, in the US, has been correlated with economic growth, with more upward sloping yield curves presaging higher real growth, for much of the last century. In an extension of this empirical reality, an inversion of the yield curve, with short term rates exceed long term rates, has become a sign of an impending recession. In a post a few years ago, I argued that if the slope of the yield curve is a signal, it is one with a great deal of noise (error in prediction). If you are a skeptic about the inverted yield curves as a recession-predictor, that skepticism was strengthened in 2022 and 2023:
As you can see, the yield curve has been inverted for all of 2023, in all of its variations (the difference between the ten-year and two-year rates, the difference between the two-year rate and the 3-month rate and the difference between the ten-year rate and the 3-month T.Bill rate). At the same time, not only has a recession not made its presence felt, but the economy showed signs of strengthening towards the end of the year. It is entirely possible that there will be a recession in 2024 or even in 2025, but what good is a signal that is two or three years ahead of what it is signaling?
Other Currencies
The rise in interest rates that I chronicled for the United States played out in other currencies, as well. While not all governments issue local-currency bonds, and only a subset of these are widely traded, there is information nevertheless in a comparison of these traded government bond rates across time:
Note that these are all local-currency ten-year bonds issued by the governments in question, with the German Euro bond rate standing in as the Euro government bond rate. Note also that during 2022 and 2023, the movements in these government bond rates mimic the US treasuries, rising strongly in 2022 and declining or staying stable in 2023.
These government bond rates become the basis for estimating risk-free rates in these currencies, essential inputs if you are valuing your company or doing a local-currency project analysis; to value a company in Indian rupees, you need a rupee riskfree rate, and to do a project analysis in Japanese yen, a riskfree rate in yen is necessary. While there are some who use these government bond rates as riskfree rates, it is worth remembering that governments can and sometimes do default, even on local currency bonds, and that these government bond rates contain a spread for default risk. I use the sovereign ratings for countries to estimate and clean up for that default risk, and estimate the riskfree rates in different currencies at the start of 2024:
Unlike the start of 2022, when five currencies (including the Euro) had negative riskfree rates, there are only two currencies in that column at the start of 2024; the Japanese yen, a habitual member of the low or negative interest rate club, and the Vietnamese Dong, where the result may be an artifact of an artificially low government bond rate (lightly traded). Understanding that riskfree rates vary across currencies primarily because of difference in inflation expectations is the first step to sanity in dealing with currencies in corporate finance and valuation.
Corporate Borrowing
As riskfree rates fluctuate, they affect the rates at which private businesses can borrow money. Since no company or business can print money to pay off its debt, there is always default risk, when you lend to a company, and to protect yourself as a lender, it behooves you to charge a default or credit spread to cover that risk:
Cost of borrowing for a company = Risk free Rate + Default Spread
The question, when faced with estimating the cost of debt or borrowing for a company, is working out what that spread should be for the company in question. Many US companies have their default risk assessed by ratings agencies (Moody's, S&P, Fitch), and this practice is spreading to other markets as well. The bond rating for a company then becomes a proxy for its default risk, and the default spread then becomes the typical spread that investors are charging for bonds with that rating. In the graph below, I look at the path followed by bonds in different ratings classes - AAA, AA, A, BBB, BB, B and CCC & below - in 2022 and 2023:
As with US treasuries, the default spread behaved very differently in 2023, as opposed to 2022. In 2022, the spreads rose strongly across ratings classes, and more so for the lowest ratings, over the course of the year. During 2023, default spreads reversed course, declining across the ratings classes, with larger drops again in the lowest ratings classes.
One perspective that may help make sense of default spread changes over time is to think of the default spread as the price of risk in the bond market, with changes reflecting the ebbs and flows in fear in the market. In my last data update, I measured the price of risk in the equity market in the form on an implied equity risk premium, and chronicled how it rose sharply in 2022 and dropped in 2023, paralleling the movements in default spreads. The fact that fear and risk premiums in equity and bond markets move in tandem should come as no surprise, and the graph below looks at the equity risk premiums and default spreads on one rating (Baa) between 1928 and 2023:
For the most part, equity risk premiums and default spreads move together, but there have been periods where the two have diverged; the late 1990s, where equity risk premiums plummeted while default spreads stayed high, preceding the dot-com crash in 2001, and the the 2003-2007 time periods, where default spreads dropped but equity risk premiums stayed elevated, ahead of the 2008 market crisis. Consequently, it is comforting that the relationship between the equity risk premium and the default spread at the start of 2024 is close to historic norms and that they have moved largely together for the last two years.
Looking to 2024
If there are lessons that can be learned from interest rate movements in 2022 and 2023, it is that notwithstanding all of the happy talk of the Fed cutting rates in the year to come, it is inflation that will again determine what will happen to interest rates, especially at the longer maturities, in 2024. If inflation continues its downward path, it is likely that we will see longer-term rates drift downwards, though it would have to be accompanied by significant weakening in the economy for rates to approach levels that we became used to, during the last decade. If inflation persists or rises, interest rates will rise, no matter what the Fed does.
Heading into 2023, US equities looked like they were heading into a sea of troubles, with inflation out of control and a recession on the horizon. While stocks had their ups and downs during the year, they ended the year strong, and recouped, at least in the aggregate, most of the losses from 2022. That positive result notwithstanding, the recovery was uneven, with a big chunk of the increase in market capitalization coming from seven companies (Facebook, Amazon, Apple, Microsoft, Alphabet, NVidia and Tesla) and wide divergences in performance across stocks, in performance. As we move into 2024, it looks like expectations have been reset, with most forecasters now expecting the economy to glide in for a soft landing and interest rates to decline, and while that may seem like good news, it will represent a challenge for equity market investors.
Looking Back
Almost a year ago, I wrote a post about what 2023 held for stocks, and it reflected the dark mood in markets, and in the face of investor gloom, looked at how the expectations game would play out for equities. In that post, I noted that if inflation subsided quickly, and the economy stayed out of a recession, stocks had upside, and that is the scenario that played out in 2023. Stocks ended the year well, with November and December both delivering strong up movements, and while this left investors feeling good about the year, it was a rocky year. In the graph below, I look at the monthly levels on the index and price returns, by month:
On a month-to-month basis, stocks started the year well and had a good first half, before entering a tough third quarter where they gave back most of those gains. Over the course of the year, the S&P 500 rose from 3840 to 4770, an increase of 24.23% for the year, which when added to the dividend yield of 1.83% translated into a return of 26.06% for the year:
To get historical context, I compared the returns in 2023 to annual returns on the S&P 500 going back to 1928:
It was a good year, ranking 24th out of the 95 years of data that I have in my dataset, a relief after the -18.04% return in 2022.
The solid comeback in stocks, though, came with caveats. The first is that it was an uneven recovery, if you break stocks down be sector, which I have, for both US and global stocks, in the table below:
As you can see, technology was the biggest winner of the year, up almost 58% (44%) for US (global) stocks, with communication services and consumer discretionary as the next best performers. Energy, one of the few survivors of the 2022 market sell-off, had a bad year, as did utilities and consumer staples. Breaking equities down by sub-region, and looking across the globe, I computed the change in aggregate market capitalization, by region:
While US stocks accounted for about $9.5 trillion of the $14 trillion increase in equity market capitalization across the world, two regions did even better, at least on a percentage basis. The first was Eastern Europe and Russia, coming back from a massive sell-off in the prior two years and the other was India, which saw an increase of $1 trillion in market cap, and a 31.3% increase in market capitalization.
Looking forward
While there is comfort in looking backwards, slicing and dicing data in the hope of getting clues for the future, investing is about the future. Much as we like to believe that history repeats itself, and find patterns even when they do not exist, the nature of markets makes them difficult to forecast, precisely because they are driven not by what actually happens to the economy, inflation and other fundamentals, but by how these results compare to expectations. Going into 2024, investors are clearly in a better mood about what is to come this year, than they were a year ago, but they are pricing in that better mood. To capture the market's mood, I back out the expected return (and equity risk premium) that investors are pricing in, through an implied equity risk premium:
Put simply, the expected return is an internal rate of return derived from the pricing of stocks, and the expected cash flows from holding them, and is akin to a yield to maturity on bonds.
To see how expectations and pricing have changed over the course of the year, I compare the implied equity risk premium (ERP) from the start of 2023 with the same number at the start of 2024
At the start of 2023, in the midst of the market's pessimism of what the coming years would deliver, stocks were priced to earn a 9.82% annual return and a 5.94% equity risk premium. In contrast, at the start of 2024, the lifting of fear has led to higher prices, a more upbeat forecast of earnings and an expected return of 8.48% and an equity risk premium of 4.60%. I do compute this expected return and the equity risk premium at the start of each month, and the last 24 months have been a roller coaster ride:
While equity risk premiums and expected returns rose strongly in 2022, registering the largest single-year increase in history, they declined over 2023, as hope has gained an upper hand over fear.
To the question of whether 8.48% is a reasonable expectation for an annual return for US stocks, and 4.60% a sufficient equity risk premium, I looked at the historical estimates for these numbers going back to 1960:
While stocks had expected returns exceeding 10% for much of the 1970s and 1980s, the culprit was high interest rates, and as interest rates have declined in this century, expected returns have come down as well. The post-2008 time period also was a period of historically low interest rates, and expected returns bottomed out in 2021, before rising again in 2022. In the table below, I look at the expected returns and equity risk premiums at the start of 2022, 2023 and 2024 against the distribution of the corresponding variables between 1960 and 2024:
It is comforting, if you are an equity investor, to see that the expected returns are only slightly lower than the median value over the longer period, and the equity risk premium is above historical norms.
Needless to say, there are other metrics, measuring the cheapness or expensiveness of equities, that investors may find more troubling. In particular, the earnings yield (the inverse of the PE ratio) for US equities will give investors pause:
Note that the EP ratio, after a surge last year, has dropped back towards 2022 levels, with the caveat being that treasury bond rates are much higher now than they were then, an attractive alternative to equities that did not exist two years ago.
Taking a Stand
I am not a market timer, but I do value the market at regular intervals, more to get a measure of what the market is pricing in, than to forecast future movements. In valuing the index, I follow the intrinsic value rulebook, where the value is determined by expectations of cash flows in the future, discounted back to adjust their risk.
To get expected cash flows, I start with expectations of earnings from the equities that comprise the index. For the S&P 500, the most widely followed equity index, I use the consensus estimates of aggregate earnings for 2024 and 2025, from analysts. I know that mistrust of analysts runs high, and the perception that they are cheerleaders for individual companies is often well founded, but I will stick with these forecasts for a simple reason. Having tracked analyst forecasts for four decades,I have found that analyst estimates of aggregated earnings for the index are unbiased, with analysts under estimating earnings in almost as many years as they over estimate them.
The cash flows to equity investors, especially in the United States, have increasingly taken the form of buybacks, not just supplementing but supplanting dividends. In 2023, dividends and buybacks on the S&P 500 index amounted to $1.367 trillion, 164.25 in index units, with 57.6% of these cash flows coming from buybacks. As a percent of earnings, the cumulative cash returned represented 74.8% of earnings in that year, representing a decline from payout ratios during this century (2000-2022); the median payout ratio for this period was 83%.
With these earnings and cash flows as starting points, and assuming that the treasury bond rate of 3.88% is a fair interest rate, I value the S&P 500:
Note that I forecast earnings beyond 2025, by assuming that growth scales down to the growth rate of the economy, estimated to be roughly equal to the riskfree rate. Unlike early in 2023, when stocks looked slightly under valued, with consensus earnings numbers and prevailing rates, stocks look over valued by about 9.2%, with a similar structure today.
As with any market valuation, there are risks embedded in this value. First, the consensus view that the economy will come in for a soft landing may be wrong, with a recession or a stronger recovery both in the cards; the earnings numbers will be lower than analyst estimates in a recession and higher with a stronger economy. Second, while the market is building in expectations of interest rates declining in 2024, a significant portion of that optimism comes from a delusion that the Fed can raise or lower rates at well. After all, the treasury bond rate, a much stronger driver of equity values than short term treasury rates, remained unchanged in 2023, even as the Fed repeatedly raised the Fed Fund rates, and it is very likely that the future path of the treasury bond rate will depend more on the vagaries of inflation than on the whims of Jerome Powell. In the graph below, I look at the fair index level as a function of assumptions about earnings surprises and interest rates:
Note that I report the fair index values currently, and to convert them into target levels for the index a year from now, you have to take the future value of the index, using the expected return on stocks (net of dividend yield). For instance, to get the expected index level at the end of 2024, if rates stay at around 4% and earnings come in 10% above expectations, is as follows:
Expected index level on 12/31/2024 (r =4%, Earnings 10% above expected) = 5202 (1.075) = 5592
As you can see, you would need earnings to come in above expectations, for the current index level (4750 on January 16) to be justified, with lower interest rates providing an assist. While what-if tables like the one above are useful tools for dealing with uncertainties, a more complete assessment of uncertainty requires that I be explicit about the uncertainties I face on each input, resulting in a simulation:
Not surprisingly, with uncertainties built in, the fair value of the index has a wide range, but using the first and ninth decile, a reasonable range for the fair value would 3670 - 5200, and at the January 16 closing level of 4750, there is about a 70% chance that the market is over valued.
I am sure that you will disagree with one or more of the inputs that I have used to value the index, and I welcome that disagreement. Rather than point out to me the error of my ways, please download the spreadsheet containing the intrinsic valuation, and you should be able to replace my assumptions about earnings, cash payout and interest rates, and arrive at your own estimates of index value.
Caveat emptor!
Before you take my market prognostications at face value, please consider my open disclosure that I am a terrible market timer and try to avoid it in my investing. In short, I do not plan to act on my market valuation by buying puts on the index, or scaling down by portfolio's equity exposure. If you are wondering why I bother valuing the index, there are two reasons. First, there are times in the past, when the overvaluation of the market is so large that it operates as a red flag on investing in equities, as an asset class, in general. That signal worked in early 2000 but did not in early 2008, and it is thus a noisy one. Second, and more generally, though, valuing the market allows you to make sense of, and tolerance for, bullish and bearish views on the market that may diverge from your own views. Thus, investors and analysts who believe that rates will continue to decline, with a strong economy delivering higher-than-expected earnings, will see significant upside in this market, just as investors and analysts who believe that stubbornly higher inflation will cause rates to rise, and that earnings will come in well below expectations will be more likely to be part of the doomsday crowd. Just as in 2023, there will be times in 2024 when one side or the other will think that it has decisively won the argument, just to see a reversal in the next period.
