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If the title of this post sounds familiar, it is because is one of Disney’s most iconic rides, one that I have taken hundreds of times, first with my own children and more recently, with my grandchildren. It is a mainstay of every Disney theme park, from the original Disneyland in Anaheim to the newer theme parks in Paris, Hong Kong and Shanghai. For those of who have never been on it, it is the favored ride for anyone who is younger than five in your group, since you spend ten minutes in a boat going through the world as Disney would like you to see it, full of peace, happiness, and goodwill. In this post, I will expand my analysis of data in 2024, which has a been mostly US-centric in the first four of my posts, and use that data to take you on my version of the Disney ride, but on this trip, I have no choice but to face the world as is, with all of the chaos it includes, with tariffs and trade wars looming.Ìý
Returns in 2024Ìý Ìý Clearly, the most obvious place to start this post is with market performance, and in the table below, I report the percentage change in index level, for a subset of indices, in 2024:


The best performing index in 2024, at least for the subset of indices that I looked at, was the Merval, up more than 170% in 2024, and that European indices lagged the US in 2024. The Indian and Chinese markets cooled off in 2024, posting single digit gains in price appreciation.ÌýÌý ÌýThere are three problems with comparing returns in indices. First, they are indices and reflect a subset of stocks in each market, with different criteria determining how each index is constructed, and varying numbers of constituents. Second, they are in local currencies, and in nominal terms. Thus, the 172.52% return in the Merval becomes less impressive when inflation in Argentina is taken into account. It is for this reason that I chose to compute returns differently, using the following constructs:I included all publicly traded stocks in each market, or at least those with a market capitalization available for them.I converted all of the market capitalizations into US dollars, just to make them comparable.I aggregated the market capitalizations of all stocks at the end of 2023 and the end of 2024, and computed the percentage change.The results, broken down broadly by geography are in the table below:
As you can see, the aggregate market cap globally was up 12.17%, but much of that was the result of a strong US equity market.ÌýContinuing a trend that has stretched over the last two decades, investors who tried to globally diversify in 2024 underperformed investors who stayed invested only in the United States.ÌýÌýÌý ÌýI do have the percentage changes in market cap, by country, but you should take those results with a grain of salt, since there are countries with just a handful of listings, where the returns are distorted. Looking at countries with at least ten company listings, I have a list of the ten best and worst performing countries in 2024:
Argentina's returns in US dollar terms is still high enough to put it on top of the list of best-performing countries in the world in 2024 and Brazil is at the top of the list of worst performing countries, at least in US dollar terms.
The Currency Effect Ìý Ìý As you can see comparing the local index and dollar returns, the two diverge in some parts of the world, and the reason for the divergence is movements in exchange rates. To cast light on this divergence, I looked at the US dollar's movements against other currencies, using three variants of US dollar indices against emerging market currencies, developed market currencies and broadly against all currencies:
The dollar strengthened during 2024, more (10.31%) against emerging market currencies than against developed market currencies (7.66%), and it was up broadly (9.03%).ÌýÌý ÌýI am no expert on exchange rates, but learning to deal with different currencies in valuation is a prerequisite to valuing companies. Since I value companies in local currencies, I am faced with the task of estimating risk free rates in dozens of currencies, and the difficulty you face in estimating these rates can vary widely (and be close to impossible in some) across currencies. In general, you can break down risk free estimation, in different currencies, in three groupings, from easiest to most difficult:

My process for estimating riskfree rates in a currency starts with a government issuing a long term bond in that currency, and if the government in question has no default risk, it stops there. Thus, the current market interest rate on a long term Swiss government bond, in Swiss Francs, is the risfree rate in that currency. The process gets messier, when there is a long-term, local currency bond that is traded, but the government issuing the bond has default risk. In that case, the default spread on the bond will have to be netted out to get to a riskfree rate in the currency. ÌýThere are two key estimation questions that are embedded in this approach to estimating riskfree rates. The first is the assessment of whether there is default risk in a government, and I use a simplistic (and flawed) approach, letting the local currency sovereign rating for the government stand in as the measure; I assume that AAA rated government bonds are default-free, and that any rating below is a indication of default risk. The second is the estimation of the default spread, and in my simplistic approach, I use one of two approaches - a default spread based upon the sovereign rating or a sovereign credit default swap spread. At the start of 2025, there were just about three dozen currencies, where I was able to find local-currency government bonds, and I estimated the riskfree rates in these currencies;

At the risk of stating the obvious (and repeating what I have said in earlier posts), there is no such thing as a global riskfree rate, since riskfree rates go with currencies, and riskfree rates vary across currencies, with all or most of the difference attributable to differences in expected inflation. High inflation currencies will have high riskfree rates, low inflation currencies low riskfree rates and deflationary currencies can negative riskfree rates.Ìý Ìý It is the recognition that differences in riskfree rates are primarily due to differences in expected inflation that gives us an opening to estimate riskfree rates in currencies without a government bond rate, or even to run a sanity check on the riskfree rates that you get from government bonds. If you start with a riskfree rate in a currency where you can estimate it (say US dollars, Swiss Francs or Euros), all you need to estimate a riskfree rate in another currency is the differential inflation between the two currencies. Thus, if the US treasury bond rate (4.5%) is the riskfree rate in US dollars, and the expected inflation rates in US dollars and Brazilian reals are 2.5% and 7.5% respectively, the riskier rate in BrazilianÌýreals:

Riskfree rate in $R = (1+ US 10-year T.Bond Rate) * (1 + Expected inflation rate in $R)/ (1+ Expected inflation rate in US $) - 1 = 1.045 *(1.075/1.025) -1 = 9.60%

In approximate terms, this can be written as

Riskfree rate in $R = US 10-year T.Bond Rate + (Expected inflation rate in $R) - Expected inflation rate in US $) - 1 = 4.5% - (7.5% - 2.5%) = 9.50%

While obtaining an expected inflation rate for the US dollar is easy (you can use the difference between the ten-year US treasury bond rate and the ten-year US TIPs rate), it can be more difficult to obtain this number in Egyptian pounds or in Zimbabwean dollars, but you can get estimates from the IMF or the World Bank.Ìý
The Risk Effect
Ìý Ìý There are emerging markets that have delivered higher returns than developed markets, but in keeping with a core truth in investing and business, these higher returns often go hand-in-hand with higher risk. The logical step in looking across countries is measuring risk in countries, and bringing that risk into your analysis, by incorporating that risk by demanding higher expected returns in riskier countries.ÌýÌý ÌýThat process of risk analysis and estimating risk premiums starts by understanding why some countries are riskier than others. The answers, to you, may seem obvious, but I find it useful to organize the obvious into buckets for analysis. I will use a picture in posts on country risk before to capture the multitude of factors that go into making some countries riskier than others:
To get from these abstractions to country risk measures, I make a lot of compromises, putting pragmatism over purity. While I take a deeper look at the different components of country risk in my annual updates on country risk (with ), I will cut to the chase and focus explicitly on my approach to estimating equity risk premiums, using my 2025 data update to illustrate:


With this approach, I estimated equity risk premiums, by country, and organized by region, here is what the world looked like, at the start of 2025:

Note that I attach theÌýof 4.33%Ìý(see my data update 3 from a couple of weeks ago) to all Aaa rated countries (Australia, Canada, Germany etc.) and an augmented premium for countries that do not have Aaa ratings, with the additional country risk premium determined by local currency sovereign ratings.ÌýÌý Ìý I am aware of all of the possible flaws in this approach. First, treating the US as default-free is questionable, now that it has threatened default multiple times in the last decade and has lost its Aaa rating with every ratings agency, other than Moody's. That is an easily fixable problem, though, since if you decide to use S&P'sÌýAA+ rating for the US, all it would require is that you net out the default spread of 0.40% (for a AA+ rating at the start of 2025) from the US ERP to get a mature market premium of 3.93% (4.33% minus 0.40%). Second, ratings agencies are not always the , especially when there are dramatic changes in a country, or when they are biased (towards or against a region). That too has a fix, at least for the , and those sovereign CDS spreads can be used instead of the ratings-based spreads for those countries.
The Pricing Effect
Ìý ÌýAs an investor, the discussions about past returns and risk may miss the key question in investing, which is pricing.ÌýAt the right price, you should be willing to buy stocks even in the riskiest countries, and especially so after turbulent (down) years. At the wrong price, even the safest market with great historical returns are bad investments. To assess pricing in markets, you have to scale the market cap to operating metrics, i.e., estimate a multiple, and while easy enough to do, there are some simple rules to follow in pricing.ÌýÌýÌý ÌýThe first is recognizing that every multiple has a market estimate of value in the numerator, capturing either just equity value (market cap of equity), total firm value (market cap of equity + total debt) or operating asset (enterprise) value (market cap of equity + total debt - cash):
Depending on the scalar (revenues, earnings, book value or cash flow), you can compute a variety of multiples, and if you add on the choices on timing for the scaling variables (trailing, current, forward), the choices multiply. To the question of which multiple is best, a much debated topic among analysts, my answer is ambivalent, since you can use any of them in pricing, as long as you ask the right follow-up questions.ÌýÌý Ìý To compare how stocks are priced globally, I will use three of these multiples. The first is the price earnings ratio, partly because in spite of all of its faults, it remains the most widely used pricing metric in the world. The second is the polar opposite on the pricing spectrum, which is the enterprise value to sales multiple, where rather than focus on just equity value, I look at operating asset value, and scale it to the broadest of operating metrics, which is revenue. While it takes a lot to get from revenues to earnings, the advantage of using revenues is that it is number least susceptible to accounting gaming, and also the one where you are least likely to lose companies from your sample. (Thousands and thousands of companies in my sample have negative net income, making trailing PE not meaningful, but very few (usually financial service firms) have missing revenues). The third pricing metric I look at is the enterprise value to EBITDA, a multiple that has gone from being lightly used four decades ago to a banking punchline today, where EBITDA represents a rough measure of operating cash flow). With each of these multiples, I make two estimation choices:I stay with trailing values for net income, revenues and EBITDA, because too many of the firms in my 48,000 firm sample have no analysts following them, and hence no forward numbers.I compute two values for each country (region), an aggregated version and the median value. While the latter is simple, i.e., it is the median number across all companies in a country or region, the former is calculated across all companies, by aggregating the values across companies. Thus, the aggregated PE ratio for the United States is 20.51, and it computed by adding up the market capitalizations of all traded US stocks and dividing by the sum of the net income earned by all traded firms, including money losers. Think of it a weighted-average PE, with no sampling bias.With these rules in place, here is what the pricing metrics looked like, by region, at the start of 2025:
The perils of investing based just upon pricing ratios should be visible from this table. Two of the cheapest regions of the world to invest in are Latin America and Eastern Europe, but both carry significant risk with them, and the third, Japan, has an aging population and is a low-growth market. The most expensive market in the world is India, and no amount of handwaving about the India story can justify paying 31 times earnings, 3 times revenue and 20 times EBITDA, in the aggregate, for Indian companies. The US and China also fall into the expensive category, trading at much higher levels than the rest of the world, on all three pricing metrics.Ìý Ìý Within each of these regions, there are differences across countries, with some priced more richly than others. In the table below, I look at the ten countries, with at least 5 companies listed on their exchanges, that trade at the lowest median trailing PE ratios, and the ten countries that are more expensive using that same metric:


Many of the markets are in the world that trade at the lowest multiples of trailing earnings are in Africa. With Latin America, it is a split decisions, where you have two countries (Colombia and Brazil) on the lowest PE list and one (Argentina) on the highest PE list. In some of the countries, there is a divergence between the aggregated version and the trailing PE, with the aggregated PE higher (lower) than the median value, reflecting larger companies that trade at lower (higher) PE ratios than the rest of the market.Ìý Ìý Replacing market cap with enterprise value, and net income with revenues, gives you a pricing multiple that lies at the other end of the spectrum, and ranking countries again, based on median EV to sales multiples, here is the list of the ten most expensive and cheapest markets:

On an enterprise value to sales basis, you see a couple of Asian countries (Japan and South Korea) make the ten lowest list, but the preponderance of Middle Eastern countries on ten highest lists may just be a reflection of quirks in sample composition (more financial service firms, which have no revenues, in the sample).
The Year to come
Ìý Ìý This week has been a rocky one for global equities, and the trigger for the chaos has come from the United States. The announcements, from the Trump administration, of the intent to impose 25% tariffs on Canada and Mexico may have been delayed, and perhaps may not even come into effect, but it seems, at least to me, a signal that globalization, unstoppable for much of the last four decades, has crested, and that nationalism, in politics and economics, is reemerging.ÌýÌýÌý ÌýAs macroeconomists are quick to point out, using the Great Depression and Smoot-Hawley's tariffs in the 1930 to illustrate, tariffs are generally not conducive to global economic health, but it is time that they took some responsibility for the backlash against free global trade and commerce. After all, the notion that globalization was good for everyone was sold shamelessly, even though globalization created winners (cities, financial service firms) and losers (urban areas, developed market manufacturing) , and much of what we have seen transpired over the last decade (from Brexit to Trump) can be viewed as part of the backlash. In spite of the purse clutching at the mention of tariffs, they have been part of global trade as long as there has been trade, and they did not go away after the experiences with the depression. I agree that the end game, if tariffs and trade wars become commonplace, will be a less vibrant global economy, but as with any major macroeconomic shocky, there will be winners and losers.ÌýÌý Ìý There is, I am sure, a sense of schadenfreude among many in emerging markets, as they watch developed markets start to exhibit the behavior (unpredictable government policy, subservient central banks, breaking of legal and political norms) that emerging markets were critiqued for decades ago, but the truth is that the line between developed and emerging markets has become a hazy one. After the fall of the Iron Curtain, George H.W. Bush (theÌýsenior) declared a "new world order", a proclamation turned out to be premature, since the old world order quickly reasserted itself. The political and economic developments of the last decade may signal the arrival of a new world order, though no one in quite sure whether it will be better or worse than the old one.Ìý
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Data Updates for 2025
Data Links

Ìý Ìý I am going to start this post with a confession that my knowledge of the architecture and mechanics of AI are pedestrian and that there will be things that I don't get right in this post. That said, DeepSeek's abrupt entry into the AI conversation has the potential to change the AI narrative, and as it does, it may also change the storylines for the many companies that have spent the last two years benefiting from the AI hype. I first posted about AI in the context of valuing Nvidia, in June 2023, when there was still uncertainty about whether AI had legs. A little over a year later, in September 2024, that question about AI seemed to have been answered in the affirmative, for most investors, and I posted again after Nvidia had a disappointing earnings report, arguing that it reflected a healthy scaling down of expectations. As talk of AI disrupting jobs and careers also picked up, I also posted a piece on the threat that AI poses for all of us, with its capacity to do our jobs, at low or no cost, and what I saw as the edges I could use to keep my bot at bay. For those of you who have been tracking the market, the AI segment in the market has held its own since September, but even before the last weekend, there were signs that investors were sobering up on not only how big the payoff to AI would be, but how long they would have to wait to get there.Ìý
The AI story, before DeepSeek
Ìý Ìý The AI story has been building for a while, reflecting the convergence of two forces in technology - more computing power, often in smaller and smaller packages, and the accumulation of data, on technology platforms and elsewhere. That said, the AI story broke out to the public on November 30, 2022, when OpenAI launched ChatGPT, and it made its presence felt in homes, schools and businesses almost instantaneously. It is that wide presence in our daily lives that laid the foundations for the AI story, where evangelists sold us on the notion that AI solutions would make our lives easier and take away the portions of our work that we found most burdensome, and that the businesses that provided these solutions would be worth trillions of dollars.Ìý Ìý As the number of potential applications of AI proliferated, thus increasing the market for AI products and services, another part of the story was also being put into play. AI was framed as being made possible by the marriage of incredibly powerful computers and deep troves of data, effectively setting the stage for the winners, losers, and wannabes in the story. The first set of companies were perceived as benefiting from building the AI architecture, with the advance spending on this architecture coming from the companies that hoped to be players in the AI product and service markets:Computing Power: In the AI story that was told, the computers that were needed were so powerful that they needed customized chips, more powerful and compact than any made before, and one company (Nvidia), by virtue of its early start and superior chip design capabilities, stood well above the rest. Not only did Nvidia have an 80% market share of the AI chip market, as assessed in 2024, the lead and first-mover advantage that the company possessed would give it a dominant market share, in the much larger AI chip market of the future. Along the way, the the AI story picked up supercomputing companies, as passengers, again on the belief that Ai systems would find a use for them.Power: In the AI story, the coupling of powerful computing and immense data happens in data centers that are power hogs, requiring immense amounts of energy to keep going. Not surprisingly, a whole host of power companies have stepped into the breach, with some increasing capacity entirely to service these data centers. Some of them were new entrants (like Constellation Energy), whereas others were more traditional power companies (Siemens Energy) who saw an opening for growth and profitability in the AI space.ÌýData: A third beneficiary from the architecture part of the AI story were the cloud businesses, where the big data, collected for the AI systems would get stored. The big tech companies with cloud arms, particularly Microsoft (Azure) and Amazon (AWS) have benefited from that demand, as have other cloud businesses.Since the companies involved in building the AI infrastructure are the ones that are most tangibly (and immediately) benefiting from the AI boom, they are also the companies that have seen the biggest boost in market cap, as the AI story heated up. In the graph, I have picked on a subset of high-profile companies that were part of the AI market euphoria and looked at the consequent increase in their market capitalizations:

Using the ChatGPT introduction on November 30, 2022, as the starting point for the AI buzz, in public consciousness and markets, the returns in 2023 and 2024 are a composite (albeit a rough) measure of the benefits that AI has generated for these companies. Note that the biggest percentage winner, at least in this group was Palantir, up 1285% in the last two years, but the biggest winner in absolute terms was Nvidia, which gained almost $ 3 trillion in value in 2023 and 2024.Ìý Ìý The investments in that AI architecture were being made, with the expectation that companies that invested in the architecture would be able to eventually profit from developing and selling AI products and services. Since the AI storyline required immense upfront investing in computing power and access to big data, the biggest investors in AI architecture were big tech companies, with Microsoft and Meta being the largest customers for Nvidia chips in 2024. In the table below, I look at the Mag Seven, not inclusive of Nvidia, and examine the returns that they have made in 2023 and 2024:

As you can see, the Mag Seven carried the market in the two years, each adding a trillion (or close, in the case of Tesla) dollars in value in the last two years, with some portion of that value attributable to the AI story. With requirements for large investment up front acting as entry barriers, the expectation was these big tech companies would eventually not only be able to develop AI products and services that their customers would want, but charge premium prices (and earn higher margins).ÌýÌý ÌýIn the picture below, I have tried to capture the essence of AI story, with the potential winners and losers at each stage:

There are parts to this story where there is much to be proved, especially on the AI product and service part, and while investors can be accused of becoming excessively exuberant about the story, it is a plausible one. In fact, my most recent (in September 2024) valuation of Nvidia bought into core elements of the story, though I still found it overvalued:

Note that the big AI story plays out in these inputs in multiple places:AI chip market: My September 2024 estimate for the size of the AI chip market was $500 billion, which in turn was justifiable only because the AI product and service market was expected to huge ($3 trillion and beyond).Nvidia market share: In my valuation, I assumed that Nvidia's lead in the AI chip business would give the company a head start, as the business grew, and to the extent that demand is sticky (i.e., once companies start build data centers with Nvidia chips, it would be difficult for them to switch to a competitor), Nvidia would maintain a dominant market share (60%) of the expanded AI chip market.Nvidia margins: Nvidia has had immense pricing power, posting nosebleed-level gross and operating margins, while TSMC (its chip maker) has generated only a fraction of the benefits, and its biggest customers (the big tech companies) have been willing to pay premium prices to get a head start in building their AI architecture. Over time, I assumed that Nvidia would see its margins drop, but even with the drop, their target margin (60%) would resemble those of very successful, software companies, not chip making companies.My concern in September 2024, and in fact for the bulk of the last two years, was not that I had doubts about the core AI story, but that investors were overpaying for the story. That is partly why, I have shed portions of my holdings in Nvidia, selling half my holdings in the summer of 2023 and another quarter in the summer of 2024.
The AI Story, after DeepSeek
Ìý Ìý I teach valuation, and have done so for close to forty years. One reason I enjoy the class is that you are never quite done with a valuation, because life keeps throwing surprises at you. The first session of my undergraduate valuation class was last Wednesday (January 22), and during the course of the class, I talked about how a good valuation connects narrative to numbers, and followed up by noting that even the most well thought through narratives will change over time. I am not sure how much of that message got through to my studentls, but the message was delivered much more effectively by DeepSeek's entry into the AI story over the weekend, and the market shakeup that followed when markets opened on Monday (January 27).
A DeepSeek Primer
Ìý Ìý The DeepSeek story is still being told, and there is much we do not know. For the moment, though, here is what we know. In 2010, Liang Wenfeng, a software engineer, founded DeepSeek as a hedge fund in China, with the intent of using artificial intelligence to make money. Unable to get traction in that endeavor, and facing government hostility on speculative trading, he pivoted in 2023 into AI, putting together a team to create a Chinese competitor to OpenAI. Since the intent was to come up with a product that could be sold at bargain prices, DeepSeek did what disruptors have always done, which is look for an alternate path to the same destination (providing AI products that work). Rather than invest in expensive infrastructure (supercomputers and data centers), DeepSeek used much cheaper, less powerful chips, and instead of using immense amounts of data, created an AI prototype that could work with less data, using rule-based logic to fill in the gap. While there has been chatter about DeepSeek for weeks, it became publicly accessible at the end of last week (ending January 24), and within hours, was drawing rave reviews from people well versed in tech, as it matched beat ChatGPT at many tasks, and even performed better on scientific and math queries.ÌýÌý Ìý There are parts of this story that are clearly for public consumption, more side stories than main story,, and it is best to get them out of the way, before looking at the DeepSeek effect.Cost of development: The notion that DeepSeek was developed for just a few million dollars is fantasy, and while there may have been a portion of the development that cost little, the total was probably in the hundreds of millions of dollars and required a lot more resources (including perhaps even Nvidia chips) than the developers are letting on. No matter what the true cost of development is finally revealed to be, it will be a fraction of the money spent by the existing players in building their systems.Performance tests: The tests of DeepSeek versus OpenAI (or Claude and Gemini) suggests that DeepSeek not only holds it own against the establishment, but even outperforms them on some tasks. That is impressive, but the leap that some are making to concede the entire AI product and service market to DeepSeek is unwarranted. There are clearly aspects of the AI products and service business, where the DeepSeek approach (of using less powerful computing and data) will be good enough, but there will be other aspects of the AI business, where the old paradigm of super computing power and vast data will still hold.A Chinese company: The fact that DeepSeek was developed in China throws a political twist into the story that will undoubtedly play a role in how it develops, but the genie is out of the bottle, even if other governments try to stop its adoption. Adding to the noise is the decision by the company to make DeepSeek open-source, effectively allowing others to adapt and build their own versions.Fair or foul: Finally, there has been some news on the legal front, where OpenAI has argued that DeepSeek unlawfully used data that was generated by OpenAI in building their offering, and while part of that lawsuit may just be showboating, it is possible that portions of the story are true and that legal consequences will follow.While we can debate the what's and why's in this story, the market reaction this week to the story has been swift and decisive. I graph the performance of the five AI stocks highlighted in the earlier section, throwing in the Meta and Microsoft for good measure, on a daily basis in 2025.
As you can see in this chart, Nvidia Broadcom, Constellation and Vistra have had terrible weeks, losing more than 10% in the last week, but just for perspective, also note that Constellation and Vistra are still up strongly for the year. Meta and Microsoft were unaffected, and so was Palantir, Clearly, the DeepSeek story is playing out differently for different companies in the AI space, but its overall market impact has been substantial, and for the most part, negative.ÌýÌý ÌýWhat is it that makes the DeepSeek story so compelling? First, is the technological aspect of coming up with a product, with far less in resources that the establishment, and I have nothing but admiration for the DeepSeek creators, but the part of the story that stands out is that the they chose not to go with the prevailing narrative (the one where Nvidia chips and huge data bases are a necessity) and instead asked the question of what the end products and services would look like, and whether there was an easier, quicker and cheaper way of getting there. In hindsight, there are probably others who are looking at DeepSeek and wondering why they did not choose the same path, and the answer is that it takes courage to go against the conventional wisdom, especially when, as AI did over the last two years, it sweeps everyone (from tech titans to individual investors) along with its force.Ìý Ìý The truth is that even if DeepSeek is stopped through legal or government action or fails to deliver on its promises, what its entry has done to the AI story cannot be undone, since it has broken the prevailing narrative. I would not be surprised if there are a dozen other start-ups, right now, using the DeepSeek playbook to come up with their own lower-cost competitors to prevailing players. Put simply, the AI story's weakest links have been exposed, and if this were the tale about the Emperor's new clothes, the AI emperor is, if not naked, is having a wardrobe malfunction, for all to see.
The Story Effect
Ìý Ìý In this first week, as is to be expected, the response has been anything but reasoned. If you are a voracious reader of financial news (I am not), you have probably seen dozens of “thought piecesâ€� from both technology and market experts claiming to foretell the future, and even among the few that I have read, the views range the spectrum on how DeepSeek changes the AI story.ÌýÌý Ìý In my writings on narrative and numbers, where I talk about how every valuation tells a story, I also talk about how stories are dynamic, with a story break representing radical change (where a great story can crash and burn or a small story can break out to become a big one), a story change can be a significant narrative alteration (where a story adds or loses a dimension with big value effects) or a story shift (where the core story remains unchanged, but the parameters can change). Using the pre-DeepSeek story as a starting point, you can classify the narratives on what is coming on the story break/story change/story shift continuum:



With all the caveats, including the fact that I am an AI novice, with a deeper understanding of potato chips than computer chips, and that it is early in the game, I am going to take a stand on where in this continuum I see the DeepSeek effect falling. I believe that DeepSeek does change the AI story, by creating two pathways to the AI product and service endgame. On one path that will lead to what I will term the “low intensityâ€� AI market, it has opened the door to lower cost alternatives, in terms of investments in computing power and data, and competitors will flock in. That said, there will remain a segment of the AI market, where the old story will prevail, and the path of massive investments in computer chips and data centers leading to premium AI products and services will be the one that has to be taken.Ìý Ìý Note that the entry characteristics for the two paths will also determine the profitability and payoffs from their respective AI product and service markets (that will eventually exist). The “low entry costâ€� pathway is more likely to lead to commoditization, with lots of competitors and low pricing power, whereas the “high entry costâ€� path with its requirements for large upfront investment and access to data will create a more restrictive market, with higher priced and more profitable AI products and services. This story leaves me with a judgment call to make about the relative sizes of the markets for the two pathways. I am generalizing, but much of what consumers have seen so far as AI offerings fall into the low cost pathway and I would not be surprised, if that remains true for the most part. The DeepSeek entry has now made it more likely that you and I (as consumers) will see more AI products and services offered to us, at low cost or even for free. There is another segment of the AI products and services market, though, with businesses (or governments) as customers, where significant investments made and refinements will lead to AI products and services, with much higher price points. In this market, I would not be surprised to see networking benefits manifest, where the largest players acquire advantages, leading to winner-take-all markets.ÌýÌý Ìý In telling this story, I understand that not only am I going to be wrong, perhaps decisively, but also that it could unravel in record time. I make this leap, not out of arrogance or a misplaced desire to change how you think, but because I own a slice of Nvidia (one quarter of the holding that I had two years ago, but still large enough to make a difference in my portfolio), and I cannot value the company without an AI story in place. That said, the feedback loop remains open, and I will listen not only to alternate opinions but also follow real world developments, in the interests of telling a better story.
The Value Effect
ÌýÌý ÌýNow that my AI story is in the open, I will use it to revisit my valuation of Nvidia, and incorporate my new AI story in that valuation. Even without working through the numbers, it is very difficult to see a scenario where the entry of DeepSeek makes Nvidia a more valuable company, with the biggest change being in the expected size of the AI chip market: table.tableizer-table { font-size: 12px; border: 1px solid #CCC; font-family: Arial, Helvetica, sans-serif; } .tableizer-table td { padding: 4px; margin: 3px; border: 1px solid #CCC; } .tableizer-table th { background-color: #104E8B; color: #FFF; font-weight: bold; }In September 2024 (pre DeepSeek)In January 2025 (post DeepSeek) AI chip market size in 2035$500 billion$300 billion Nvidia's market share60%60% Nvidia's operating margin60%60% Nvidia's risk (cost of capital)10.52% _> 8.49%11.79% -> 8.50% (Higher riskfree rate + higher ERP)
With the changes made, and updating the financials to reflect an additional quarter of data, Ìýyou can see my Nvidia valuation in the picture below:

There are two (unsurprising) results in this valuation. The value per share that I estimate for Nvidia dropped from $87 in September 2024 to $78 in January 2025, much of that change driven by the smaller AI chip market that comes out of the DeepSeek disruption (with the rest of the decline arising for higher riskfree rates and the equity risk premiums). The other is that the stock is overvalued, at its current price of $123 per share, even after the markdown this week. Since I found Nvidia overvalued in September 2024, when the big AI story was still in place, and Nvidia was trading at $109, $14 lower than todays price, estimating a lower value and comparing to a higher price makes it even more over valued..Ìý ÌýÌýMore generally, the value effect of the DeepSeek disruption will be disparate, more negative for some companies in the AI space than others, and perhaps even positive for a few and I have attempted to capture those effects in the picture below, comparing DeepSeek to a bomb, and looking at the damage zones from the blast:
In my view, the damage, in the near and long term, from DeepSeek will be to the businesses that have been the lead players in building the AI architecture. In addition to Nvidia (and its AI chip business), this includes the energy and gas businesses that have benefited from the tens of billions spent on building AI data centers. It is not that they will currently contracts, but that it is likely that you will see a slowing down of commitments to spend money on AI, as companies examine whether they need them. More companies are therefore likely to follow Apple's path of cautious entry than Meta and Microsoft's headfirst dive into the AI businesses. As for the businesses that are aiming for the AI products and services market, the effect will depend upon how much these products and services need data and computing power. If the proposed AI products and services are low-grade, i.e., they are more rule-based and mechanical and less dependent on incorporating intuition and human behavior, the effect of DeepSeek will be significant, with lower costs to entry and a commoditized marketplace, with lower margins and intense competition, If on the other hand, the AI products and services are high grade, i.e,, trying to imitate human decision making in the face of uncertainty, the effects of the DeepSeek entry are likely to be minimal and perhaps even non-existent. Thus, I would expect a business that is working on an AI product for financial accounting to find its business landscape changed more than Palantir, working on complex AI products for the defense department or commercial businesses. There is a grouping of companies, primarily big tech firms with large platforms, like Meta and Microsoft, where there may be buyer’s remorse about money already spent on AI (buying Nvidia chips and building data centers) but the DeepSea disruption may make it easier to develop low-cost, low-tech AI products and services that they can offer their platform users (either for free or at low costs) to keep them in their ecosystems.ÌýÌý ÌýWhen faced with a development that could change the way we live and work, it is natural, especially in the early phases, to give that development a catchy name, and use it as a rationale for investing large amounts (if you are a business) or pushing up what you would pay for the businesses in the space (if you are an investor). In my early piece on AI, I talked about four developments in my lifetime that I would classify as revolutionary â€� personal computers in the 1980s, the internet in the 1990s, the smartphone in the first decade of the twenty first century and social media in the last decade, and how each of these started as catchall buzzwords, before investors and businesses learned to discriminate. Cisco, AOL and Amazon were all born in the internet era, but they had very different business models, and as the internet matured, faced very different end games. I hope that the DeepSeek entry into the AI narrative, and its disparate effects on different businesses in this space, will lead us to be more focused in our AI conversations. Thus, rather than describe a company as an AI company or describe the AI market as “hugeâ€�, we should be more explicit about what part of the AI business a company fits into (architecture, software, data or products/services) and apply the same degree of discrimination when talking about AI markets. If you also buy into my reasoning, you may want to follow up by asking whether the AI offering is more likely to fall into the premium or commoditized grouping.
The Bottom Line
Ìý Ìý My early entry into Nvidia and my holdings of many of the other Mag Seven stocks have allowed me to ride the AI boom, I have remained a skeptic about the product and service side of AI, for much of the last two years. I can attribute that wariness partly to my age, since I cannot think of a single AI offering that has been made to me in the last two years that I would pay a significant additional amount for. I see AI icons on almost everything that I use, from Zoom to Microsoft Word/Powerpoint/Excel to Apple mail. I must admit that they do neat things, including reword emails to not only clean up for mistakes but change the tone, but I can live without those neat add-ons. Since I work in valuation and corporate finance, not a day goes by without someone contacting me about a new AI product or service in the space. Having tried a few out, my response to many of these products and services is that, at least for me, they don’t do enough for me to bother. In many ways, DeepSeek confirms a long-standing suspicion on my part that most AI products and services that we will see, as consumers and even as businesses, fall into the “that’s cuteâ€� or “how neatâ€� category, rather than into the “that would change my lifeâ€�, If that is the case, it has also struck me as overkill to expend tens of billions of dollars building data centers to develop these products, akin to using a sledgehammer to tap a nail into the wall. Every major innovation of the last few decades, has had its reality check, and has emerged the stronger for it, and this may the first of many such reality checks for AI.ÌýÌý ÌýI know that much of what I have said here goes against the "happy talk" narrative about AI, emanating from tech titans and business visionaries.ÌýI know that and Sam Altman believe that AI will be world-changing, in a good way, relieving us of the pain of tasks that are boring and time consuming, and even replacing flawed "human" decisions with be more reasoned AI decisions. They are smart men, but I have two reasons for being cautions. The first is that I have had exposure to smart people in almost every walk of life - smart academics, smart bankers, smart software engineers, smart venture capitalists and yes, even smart regulators - but most of them have had blind spots, perhaps because they hang out with people who think like them. The second, and this perhaps follows from the first, is that I am old enough to have heard this evangelist pitch for a revolutionary change before. In the 1980s, I remember being told that personal computers would eliminate the drudgery of working through ledger sheets with calculators and pencils, but as young financial analysts will tell you today, it has just created a fresh and Ìýperhaps even more soul-sucking drudgery, where monstrously large spreadsheets govern their workdays. In the 1990s, the advocates for the internet painted a picture of the world where access to online information would make us all more informed and wiser, but in hindsight, all it has done is weaken our reasoning muscles (by letting us look up answers online) and made us misinformed. In this century, social media too was born on the promise that it would keep us connected with friends, even if they were thousands of miles away, and happier, because of those connections, but as my good friend, and others have chronicled, it has left many in its orbit more isolated and less happy than before.Ìý
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Nvidia Valuations

It was an interesting year for interest rates in the United States, one in which we got more evidence on the limited power that central banks have to alter the trajectory of market interest rates. We started 2024 with the consensus wisdom that rates would drop during the year, driven by expectations of rate cuts from the Fed. The Fed did keep its end of the bargain, cutting the Fed Funds rate three times during the course of 2024, but the bond markets did not stick with the script, and market interest rates rose during the course of the year. In this post, I will begin by looking at movements in treasury rates, across maturities, during 2024, and the resultant shifts in yield curves. I will follow up by examining changes in corporate bond rates, across the default ratings spectrum, trying to get a measure of how the price of risk in bond markets changed during 2024.

Treasury Rates in 2024

Ìý Ìý Coming into 2024, interest rates had taken a rollicking ride, surging in 2022, as inflation made its come back, before settling in 2023. At the start of 2024, the ten-year treasury rate stood at 3.88%, unchanged from its level a year prior, but the 3-month treasury bill rate had climbed to 5.40%. In the chart below, we look the movement of treasury rates (across maturities) during the course of 2024:

During the course of 2024, long term treasury rates climbed in the first half of the year, and dropped in the third quarter, before reversing course and increasing in the fourth quarter, with the 10-year rate ending Ìýthe year at 4.58%, 0.70% higher than at the start of the year. The 3-month treasury barely budged in the first half of 2024, declined in the third quarter, and diverged from long term rates and continued its decline in the last quarter, to end the year at 4.37%, down 1.03% from the start of the year. I have highlighted the three Fed rate actions, all cuts to the Fed Funds rate, on the chart, and while I will come back to this later in this post, market rates rose after all three.

Ìý Ìý The divergence between short term and long term rates played out in the yield curve, which started 2024, with a downward slope, but flattened out over the course of the year:

Writing last year about the yield curve, which was then downward sloping, I argued that notwithstanding prognostications of doom, Ìýit was a poor prediction of recessions. This year, my caution would be to not read too much, at least in terms of forecasted economic growth, into the flattening or even mildly upward sloping yield curve.ÌýÌý Ìý The increase in long term Ìýtreasury rates during the course of the year was bad news for treasury bond investors, and the increase in the 10-year treasury bond rate during the course of the year translated into an annual return of -1.64% for 2024:
With the inflation of 2.75% in 2024 factored in, the real return on the 10-year bond is -4.27%. With the 20-year and 30-year bonds, the losses become larger, as time value works its magic. It is one reason that I argue that any discussion of riskfree rates that does not mention a time horizon is devoid of a key element. Even assuming away default risk, a ten-year treasury is not risk free, with a one time horizon, and a 3-month treasury is definitely not riskfree, if you have a 10-year time horizon.

The Drivers of Interest Rates

Ìý Ìý Over the last two decades, for better or worse, we (as investors, consumers and even economics) seem to have come to accept as a truism the notion that central banks set interest rates. Thus, the answer to questions about past interest rate movements (the low rates between 2008 and 2021, the spike in rates in 2022) as well as to where interest rates will go in the future has been to look to central banking smoke signals and guidance. In this section, I will argue that the interest rates ultimately are driven by macro fundamentals, and that the power of central banks comes from preferential access to data about these fundamentals, their capacity to alter those fundamentals (in good and bad ways) and the credibility that they have to stay the course.

Inflation, Real Growth and Intrinsic Riskfree Rates

Ìý Ìý It is worth noting at the outset that interest rates on borrowing pre-date central banks (the Fed came into being in 1913, whereas bond markets trace their history back to the 1600s), and that lenders and borrowers set rates based upon fundamentals that relate specifically to what the former need to earn to cover Ìýexpected inflation and default risk, while earning a rate of return for deferring current consumption (a real interest rate). If you set the abstractions aside, and remove default risk from consideration (because the borrower is default-free), a riskfree interest rate in nominal terms can be viewed, in its simplified form, as the sum of the expected inflation rate and an expected real interest rate:

Nominal interest rate = Expected inflation + Expected real interest rate

This equation, titled the Fisher Equation, is often part of an introductory economics class, and is often quickly forgotten as you get introduced to more complex (and seemingly powerful) monetary economics lessons. That is a pity, since so much of misunderstanding of interest rates stems from forgetting this equation. I use this equation to derive what I call an "intrinsic riskfree rate", with two simplifying assumptions:

Expected inflation: I use the current year's inflation rate as a proxy for expected inflation. Clearly, this is simplistic, since you can have unusual events during a year that cause inflation in that year to spike. (In an alternate calculation, I use an average inflation rate over the last ten years as the expected inflation rate.)Expected real interest rate: In the last two decades, we have been able to observe a real interest rate, at least in the US, using inflation-protected treasury bonds(TIPs). Since I am trying to estimate an intrinsic real interest rate, I use the growth rate in real GDP as my proxy for the real interest rate. That is clearly a stretch when it comes to year-to-year movements, but in the long term, the two should converge.With those simplistic proxies in place, my intrinsic riskfree rate can be computed as follows:Intrinsic riskfree rate = Inflation rate in period t + Real GDP growth rate in period tIn the chart below, I compare my estimates of the intrinsic riskfree rate to the observed ten-year treasury bond rate each year:

While the match is not perfect, the link between the two is undeniable, and the intrinsic riskfree rate calculations yield results that help counter the stories about how it is the Fed that kept rates low between 2008 and 2021, and caused them to spike in 2022.Ìý

While it is true that the Fed became more active (in terms of bond buying, in their quantitative easing phase) in the bond market in the last decade, the low treasury rates between 2009 and 2020 were driven primarily by low inflation and anemic real growth. Put simply, with or without the Fed, rates would have been low during the period.In 2022, the rise in rates was almost entirely driven by rising inflation expectations, with the Fed racing to keep up with that market sentiment. In fact, since 2022, it is the market that seems to be leading the Fed, not the other way around.
Entering 2025, the gap between intrinsic and treasury rates has narrowed, as the market consensus settles in on expectations that inflation will stay about the Fed-targeted 2% and that economic activity will be boosted by tax cuts and a business-friendly administration.

The Fed Effect

Ìý ÌýÌýI am not suggesting that central banks don't matter or that they do not affect interest rates, because that would be an overreach, but the questions that I would like to address are about how much of an impact central banks have, and through what channels. To the first question of how much of an impact, I started by looking at the one rate that the Fed does control, the Fed Funds rate, an overnight interbank borrowing rate that nevertheless has resonance for the rest of the market. To get a measure of how the Fed Funds rate has evolved over time, take a look at what the rate has done between 1954 and 2024:

As you can see the Fed Funds was effectively zero for a long stretch in the last decade, but has clearly spiked in the last two years. If the Fed sets rates story is right, changes in these rates should cause market set rates to change in the aftermath, and in the graph below, I look at monthly movements in the Fed Funds rate and two treasury rates - the 3-month T.Bill rate and the 10-year T.Bond rate.

The good news for the "Fed did it" story is that the Fed rates and treasury rates clearly move in unison, but all this chart shows is that Fed Funds rate move with treasury rates contemporaneously, with no clear indication of whether market rates lead to Fed Funds rates changing, or vice versa. To look at whether the Fed funds leads the rest of the market, I look at the correlation between changes in the Fed Funds rate and changes in treasury rates in subsequent months.Ìý

As you can see from this table, the effects of changes in the Fed Funds rate on short term treasuries is positive, and statistically significant, but the relationship between the Fed Funds rate and 10-year treasuries is only 0.08, and barely meets the statistical significance test. In summary, if there is a case to be made that Fed actions move rates, it is far stronger at the short end of the treasury spectrum than at the long end, and with substantial noise in predictive effects. Just as an add on, I reversed the process and looked to see if the change in treasury rates is a good predictor of change in the Fed Funds rate and obtained correlations that look very similar.Ìý
In short, the evidence is just as strong for the hypothesis that market interest rates lead the Fed to act, as they are for "Fed as a leader" hypothesis.Ìý Ìý As to why the Fed's actions affect market interest rates, it has less to do with the level of the Fed Funds rate and more to do with the market reads into the Fed's actions. Ultimately, a central bank's effect on market interest rates stems from three factors:
Information: It is true that the Fed collects substantial data on consumer and business behavior that it can use to make more reasoned judgments about where inflation and real growth are headed than the rest of the market, and its actions often are viewed as a signal of that information. Thus, an unexpected increase in the Fed Funds rate may signal that the Fed sees higher inflation Ìýthan the market perceives at the moment, and a big drop in the Fed Funds rates may indicate that it sees the economy weakening at a time when the market may be unaware.Central bank credibility: Implicit in the signaling argument is the belief that the central bank is serious in its intent to keep inflation in check, and that is has enough independence from the government to be able to act accordingly. A central bank that is viewed as a tool for the government will very quickly lose its capacity to affect interest rates, since the market will tend to assume other motives (than fighting inflation) for rate cuts or raises. In fact, a central bank that lowers rates, in the face of high and rising inflation, because it is the politically expedient thing to do may find that market interest move up in response, rather than down.Interest rate level: If the primary mechanism for central banks signaling intent remains the Fed Funds rate (or its equivalent in other markets), with rate rises indicating that the economy/inflation is overheating and rate cuts suggesting the opposite, there is an inherent problem that central banks face, if interest rates fall towards zero. The signaling becomes one sided i.e., rates can be raised to put the economy in check, but there is not much room to cut rates. This, of course, is exactly what the Japanese central bank has faced for three decades, and European and US banks in the last decade, reducing their signal power.The most credible central banks in history, from the Bundesbank in Deutsche Mark Germany to the Fed, after the Volcker years, earned their credibility by sticking with their choices, even in the face of economic disruption and political pushback. That said, in both these instances, central bankers chose to stay in the background, and let their actions speak for themselves. Since 2008, central bankers, perhaps egged on by investors and governments, have become more visible, more active and, in my view, more arrogant, and that, in a strange way, has made their actions less consequential. Put simply, the more the investing world revolves around FOMC meetings and the smoke signals that come out of them, the less these meetings matter to markets.Ìý
Forecasting RatesÌý ÌýÌýI am wary of Fed watchers and interest rate savants, who claim to be able to sense movements in rates before they happen for two reasons. First, their track records are so awful that they make soothsayers and tarot card readers look good. Second, unlike a company's earnings or risk, where you can claim to have a differential advantage in estimating it, it is unclear to me what any expert, no matter how credentialed, can bring to the table that gives them an edge in forecasting interest rates. In my valuations, this skepticism about interest rate forecasting plays out in an assumption where I do not try to second guess the bond market and replace current treasury bond rates with fanciful estimates of normalized or forecasted rates. If you look back at my S&P 500 valuation in my second data post for this year, you will see that I left the treasury bond rate at 4.58% (its level at the start of 2025) unchanged through time.ÌýÌý ÌýÌýIf you feel the urge to play interest forecaster, I do think that it is good practice to make sure that your views on the direction of interest rates are are consistent with the views of inflation and growth you are building into your cash flows. If you buy into my thesis that it is changes in expected inflation and real growth that causes rates to change in interest rates, any forecast of interest rates has be backed up by a story about changing inflation or real growth. Thus, if you forecast that the ten-year treasury rate will rise to 6% over the next two years, you have to follow through and explain whether rising inflation or higher real growth (or both) that is triggering this surge, since that diagnosis have different consequences for value. Higher interest rates driven by higher inflation will generally have neutral effects on value, for companies with pricing power, and negative effects for companies that do not. Higher interest rates precipitated by stronger real growth is more likely to be neutral for the market, since higher earnings (from the stronger economy) can offset the higher rates. The most empty forecasts of interest rates are the ones where the forecaster's only reason for predicting higher or lower rates is central banks, and I am afraid that the discussion of interest rates has become vacuous over the last two decades, as the delusion that the Fed sets interest rates becomes deeply engrained.

Corporate Bond Rates in 2024

Ìý Ìý The corporate bond market gets less attention that the treasury bond market, partly because rates in that market are very much driven by what happens in the treasury market. Last year, as the treasury bond rate rose from 3.88% to 4.58%, it should come as no surprise that corporate bond rates rose as well, but there isÌýinformation in the rate differences between the two markets. That rate difference, of course, is the default spread, and it will vary across different corporate bonds, based almost entirely on perceived default risk.Ìý

Default spread = Corporate bond rate - Treasury bond rate on bond of equalÌýmaturity

Using bond ratings as measures of default risk, and computing the default spreads for each ratings class, I captured the journey of default spreads during 2024:

During 2024, default spreads decreased over the course of the year, for all ratings classes, albeit more for the lowest rated bonds. Using a different lexicon, the price of risk in the bond market decreased during the course of the year, and if you relate that back to my second data update, where I computed a price of risk for equity markets (the equity risk premium), you can see the parallels. In fact, in the graph below, I compare the price of risk in both the equity and bond markets across time:

In most years, equity risk premiums and bond default spreads move in the same direction, as was the case in 2024. That should come as little surprise, since the forces that cause investors to spike up premiums (fear) or bid them down (hope and greed) cut across both markets. In fact, lookin a the ratio of the equity risk premium to the default spread, you could argue that equity risk premiums are too high, relative to bond default spreads, and that you should see a narrowing of the difference, either with a lower equity premium (higher stock prices) or a higher default spread on bonds.

Ìý Ìý The decline of fear in corporate bond markets can be captured on another dimension as well, which is in bond issuances, especially by companies that face high default risk. In the graph below, I look at corporate bond issuance in 2024, broken down into investment grade (BBB or higher) and high yield (less than BBB).Ìý

Note that high yield issuances which spiked in 2020 and 2021, peak greed years, almost disappeared in 2022. They made a mild comeback in 2023 and that recovery continued in 2024.Ìý

Ìý Ìý Finally, as companies adjust to a new interest rate environment, where short terms rates are no longer close to zero and long term rates have moved up significantly from the lows they hit before 2022, there are two other big shifts that have occurred, and the table below captures those shifts:

First, you will note that after a long stretch, where the percent of bond that were callable declined, they have spiked again. That should come as no surprise, since the option, for a company, to call back a bond is most valuable, when you believe that there is a healthy chance that rates will go down in the future. When corporates could borrow money at 3%, long term, they clearly attached a lower likelihood to a rate decline, but as rates have risen, companies are rediscovering the value of having a Ìýcalculability option. Second, the percent of bond issuances with floating rate debt has also surged over the last three years, again indicating that when rates are low, companies were inclined to lock them in for the long term with fixed rate issuances, but at the higher rates of today, Ìýthey are more willing to let those rates float, hoping for lower rates in future years.
In ConclusionÌý Ìý I spend much of my time in the equity market, valuing companies and assessing risk. I must confess that I find the bond market far less interesting, since so much of the focus is on the downside, and while I am glad that there are other people who care about that, I prefer to operate in a space where there there is more uncertainty. That said, though, I dabble in bond markets because what happens in those markets, unlike what happens in Las Vegas, does not stay in bond markets. TheÌýspillover effects into equity markets can be substantial, and in some cases, devastating. In my posts looking back at 2022, I noted how a record bad year for bond markets, as both treasury and corporate bonds took a beating for the ages, very quickly found its ways into stocks, dragging the market down. On that count, bond markets had a quiet year in 2024, but they may be overdue for a clean up.

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Data Updates for 2025

Data Links

In my first two data posts for 2025, I looked at the strong year that US equities had in 2024, but a very good year for the overall market does not always translate into equivalent returns across segments of the market. In this post, I will remain focused on US equities, but I will break them into groupings, looking for differences. I first classify US stocks by sector, to see return variations across different industry groupings. I follow up by looking at companies broken down by market capitalization, Ìýwith an eye on whether the much-vaunted small cap premium has made a comeback. In the process, I also look how much the market owes its winnings to its biggest companies, with the Mag Seven coming under the microscope. In the next section, I Ìýlook at stock returns for companies in different price to book deciles, in a simplistic assessment of the value premium. With both the size and value premiums, I will extend my assessment over time to see how (and why) these premiums have changed, with lessons for analysts and investors. In the final section, I look at companies categorized by price momentum coming into 2024, to track whether winning stocks in 2023 were more likely to be winners or losers in 2024.

US Stocks, by Sector (and Industry)

Ìý ÌýÌý Ìý It is true that you very seldom see a market advance that is balanced across sectors and industries. This market (US stocks in 2024) spread its winnings across sectors disproportionately, with four sectors - technology, communication services, consumer discretionary and financials - delivering returns in excess of 20% in 2024, and three sectors - health care, materials and real estate delivering returns close to zero:

Sector Returns - Historical (with $ changes in millions)

The performance of technology stocks collectively becomes even more impressive, when you look at the fact that they added almost $4.63 trillion in market cap just in 2024, and that over the last five (ten) years, the sector has added $11.3 trillion ($13.6 trillion) in market cap.Ìý

Ìý ÌýI Ìýbreak the sectors down into 93Ìýindustries, to get a finer layer of detail, and there again there are vast differences between winning and losing industry groups, based upon stock price performance in 2024:

$ changes in millions

While most of the industries on the worst-performing list represent old economy companies (steel, chemicals, rubber & tires), green energy finds itself on the list as well, perhaps because the "virtue trade" (where impact and socially conscious investors bought these companies for their greenness, rather than business models) lost its heft. The top two performers, in 2024, on the best performing industry list, semiconductors and auto & truck, owe much of their overall performance to super-performers in each one (Nvidia with semiconductors and Tesla with auto & truck), but airline companies also had a good year, though it may be premature to conclude that they have finally found working business models that can deliver profitability on a continuous basis.

US Stocks, by Market Cap

Ìý Ìý For much of the last century, the conventional wisdom has been that small companies, with size measured by market cap, deliver higher returns than larger companies, on a risk-adjusted basis, with the debate being about whether that was because the risk measures were flawed or because small cap stocks were superior investments. That "small cap premium" has found its way into valuation practitioners playbooks, manifesting as an augmentation (of between 3-5%) on the cost of equity of small companies. ÌýTo get a sense of how market capitalization was related to returns, I classified all publicly traded US companies, by market cap, and looked at their returns in 2024.

The returns across deciles are volatile, and while the lowest deciles in terms of market cap deliver higher percent returns, looking at the top and bottom halves of the market, in terms of market cap, you can see that there is not much setting apart the two groups.ÌýÌý Ìý To make an assessment of how the performance of small cap stocks in 2024 falls in the historical spectrum, I drew on Ken French's research return data, one of my favorite data sources, and looked at the small cap premium as the difference in compounded annual returns between the lowest and highest deciles of companies, in terms of market cap:

In this graph, you can see the basis for the small cap premium, but only if go back all the way to 1927, and even with that extended time period, it is far stronger with equally weighted than with value weighted returns; the 1927-2024 small cap premium is 2.07% with value-weighted returns and 6.69% in Ìýequally weighted terms. It should be noted that even its heyday, the small cap premium had some disconcerting features including the facts that almost of it was earned in one month (January) of each year, and that it was sensitive to starting and end points for annual data, with smaller premium in mid-year starting points. To see how dependent this premium is on the front end of the time period, I estimated the small cap premium with different starting years in the graph (and the table), and as you can see the small cap premium drops to zero with any time period that starts in 1970 and beyond. In fact, the small cap premium has become a large cap premium for much of this century, with small cap returns lagging large cap returns by about 4-4.5% in the last 20 years.

Ìý Ìý The market skew towards large cap companies can be seen even more dramatically, if you break stocks down by percentile, based upon market cap, and look at how much of the increase in market cap in US equities is accounted for by different percentile groupings:

US Stocks: Market Cap Change Breakdown

Looking across 6000 publicly traded stocks in 2024, the top percentile (about 60 stocks) accounted for 74% of the increase in market cap, and the top ten percent of all stocks delivered 94% of the change in total market capitalization.

Ìý Ìý Zeroing in even further and looking at the biggest companies in the top percentile, the Mag Seven, the concentration of winners at the very top is clear:

$ changes in millions
In 2024, seven companies (Apple, Amazon, Meta, Alphabet, Microsoft, Nvidia and Tesla) increased in market cap by $5.6 trillion, almost of the entire market's gain for the year. While it is not uncommon for stock market returns to be delivered by a few winners at the top, Ìýwith the Mag Seven, the domination extends over a decade, and in the last ten years (2014-2024), these seven companies have added $15.8 trillion in market cap, about 40% of the increase in market capitalization across all US stocks over the decade.Ìý ÌýÌýFor years now, some investors have bet on a reversal in this trend line, with small cap stocks coming back in favor, and these investors have lagged the market badly. To get a better handle on why large cap stocks have acquired a dominant role, in markets, I look at three explanations that I have seen offered for the phenomenon:

Momentum story: Momentum has always been a strong force in markets, in both directions, with price increases in stocks (decreases) followed by more price increases (decreases). In effect, winning stocks continue to win, drawing in new funds and investors, but when these same stocks start losing, the same process plays out in reverse. A reasonable argument can be made that increasing access to information and easing trading, for both individual and institutional investing, with a boost from social media, has increased momentum, and thus the stock prices of large cap stocks. The dark side of this story, though, is that if the momentum ever shifted, these large cap stocks could lose trillions in value.Passive investing: Over the last two decades, passive investing (in the form of index funds and ETFs) has taken market share from active investors, accounting for close to Ìý50% of all invested funds in 2024. That shift has been driven by active investing underperformance and a surge in passive investing vehicles that are accessible to all investors. Since many passive investing vehicles hold all of the stocks in the index in proportion to their market cap, there presence and growth creates fund flows into large cap stocks and keeps their prices elevated.ÌýHere again, the dark side is that if fund flows reverse and became negative, i.e., investors start pulling money out of markets, large cap stocks will be disproportionately hurt.Industry economics: In writing about the disruption unleashed by tech start-ups, especially in the last two decades, I have noted the these disruptors have changed industry economics in many established businesses, replacing splintered, dispersed competition with consolidation. Thus, Meta and Alphabet now have dominant market shares of the advertising business, just as Uber, Lyft and Grab have consolidated the car service business. As industries consolidate, we are likely to see them dominated by a few, big winners, which will play out in the stock market as well. It is possible that antitrust laws and regulatory authorities will try to put constraints on these biggest winners, but as I on the topic, it will not be easy.In my view, the small cap premium is not coming back, and given that it has been invisible for five decades now, the only explanation for why appraisers and analysts hold on to it is inertia. That said, the large cap premium that we have seen in the last two decades, was businesses have transitioned from splintered to consolidated structure, will also fade. Where does that leave us? Picking a company to invest in, based upon its market capitalization, will be, at best, a neutral strategy, and that should surprise no one.

The Value Premium?

Ìý Ìý Just as the small cap premium acquired standing as conventional wisdom in the twentieth century, the data and research also indicated that stocks that trade at low price to book ratios earned higher returns that stocks that trade at high price to book ratios, in what was labeled as the value premium. As with the size premium, low price to book (value) stocks have struggled to deliver in the twenty first century, and as with the small size premium, investors have waited for it to return. To see how stocks in different price to book classes performed in 2024, I looked at returns in 2024, for all US stocks, broken down into price to book deciles:

Deciles created based on price to book ratios at start of 2024
In 2024, at least, it was the companies in the top decile (highest price to book ratios) that delivered the best returns in 2024, and stocks in the lowest decile lagged the market.ÌýÌý Ìý Here again, Ken French's data is indispensable in gaining historical perspective, as I looked the difference in annual returns between the top decile and bottom decile of stocks, classified by price to book, going back to 1927:

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In this graph, I am computing the premium earned by low price to book stocks, in the US, with different starting points. Thus, if you go back to 1927 and look at returns on the lowest and highest deciles, the lowest decile earned an annual premium of 2.43%. That premium remains positive until you get to about 1990, when it switches signs; the lowest price to book stocks have earned 0.87% less annually between 1990 and 2024, than the highest price to book stocks. As was the case with the small cap premium, the premium earned by low price to book stocks over high price to book stocks has faded over time, spending more time in negative territory in the last 20 years, than positive.ÌýÌý Ìý Value investors, or at least the ones that use the conventional proxies for cheapness (low price to book or low PE ratios), have felt the effects, significantly under performing the market for much of the last two decades. While some of them still hold on to the hope that this is just a phase that will reverse, there are three fundamentals at play that may indicate that the low price to book premium will not be back, at least on a sustained basis:Price to book â‰� Value: It is true that using low price to book as an indicator of value is simplistic, and that there are multiple other factors (good management, earnings quality, moats) to consider before making a value judgment. It is also true that as the market's center of gravity has shifted towards companies with intangible assets, the troubles that accountants have had in putting a number on intangible asset investments has made book value less and less meaningful at companies, making it a poorer and poorer indicator of what a company's assets are worth.Momentum: In markets, the returns to value investing has generally moved inversely with the strength of momentum. Thus, the same forces that have strengthened the power of momentum, that we noted in the context of the fading of the small cap premium, have diluted the power Ìýof value investing.Structural Shifts: At the heart of the premium earned by low price to book ratios is mean reversion, with much of the high returns earned by these stocks coming from moving towards the average (price to book) over time. While that worked in the twentieth century, when the US was the most mean-reverting and predictable market/economy of all time, it as disruption and globalization have weakened mean reversion.So, what does this mean for the future? I see no payoff in investing in low price to book stocks and waiting for the value premium to return. As with market cap, I believe that the value effect will become volatile, with low price to book stocks winning in some years and high price to book stocks in others, and investing in one or another of these groups, just on the basis of their price to book ratios, will no longer deliver excess returns.

Ìý Ìý Since the fading of the small cap and value premiums can be traced at least partially to the strengthening of momentum, as a market force, I looked at the interplay between momentum and stock returns, by breaking companies into deciles, based upon stock price performance in the previous year (2023), and looking at returns in 2024:

Deciles formed on percentage returns in 2023

As you can see, barring the bottom decile, which includes the biggest losers of 2023, where there was a strong bounce back (albeit less in dollar terms, than in percent), there was a strong momentum effect in 2024, with the biggest winners from last year (2023) continuing to win in 2024. In short, momentum continued its dominance in 2024, good news for traders who make money in its tailwinds, with the caveat that momentum is a fickle force, and that 2025 may be the year where it reverses.

Implications

Ìý Ìý The US equity market in 2024 followed a pathway that has become familiar to investor in the last decade, with large companies, many with a tech focus, carried the market, and traditional strategies that delivered higher returns, such as investing in small cap or low price to book stocks, faltered. This is not a passing phase, and reflects the market coming to terms with a changed economic order and investor behavior. There are lessons from the year for almost everyone in the process, from investors to traders to corporate executive and regulators:

For investors: I have said some harsh things about active investing, as practiced today, since much of it is based upon history and mean reversion. A mutual fund manager who screens stocks for low PE ratios and high growth, while demanding a hefty management fee, deserves to be replaced by an ETF or index fund, and that displacement will continue, pruning the active management population. For active investors who hold on to the hope that quant strategies or AI will let them rediscover their mojo, I am afraid that disappointment is awaiting them.For traders: Traders live and die on momentum, and as market momentum continues to get stronger, making money will look easy, until momentum shifts. Coming off a year like 2024, where chasing momentum would have delivered market-beating returns, the market may be setting up traders for a takedown. It may be time for traders to revisit and refine their skills at detecting market momentum shifts.For companies:ÌýCompanies that measure their success through stock market returns may find that the market price has become a noisier judge of their actions.ÌýThus, a company that takes a value destructive path that feeds into momentum may find the market rewarding it with a higher price, but it is playing a dangerous game that could turn against it.ÌýFor regulators: With momentum comes volatility and corrections, as momentum shifts, and those corrections will cause many to lose money, and for some, perhaps even their life savings. Regulators will feel the pressure to step in and protect these investors from their own mistakes, but in my view, it will be futile. In the markets that we inhabit, literally any investment can be an instrument for speculation. After all, Gamestop and AMC were fairly stolid stocks until they attracted the meme crowd, and Microstrategy, once a technology firm, has become almost entirely a Bitcoin play.Ìý

I recently watched Timothy Chalamet play Bob Dylan in the movie, A Complete Unknown, Ìýand I was reminded of one of my favorite Dylan tunes, "". ÌýI started my investing in the 1980s, in a very different market and time, and while I have not changed my investing principles, I have had to modify and adapt them to reflect a changed market environment. You may not agree with my view that both the small cap and value premiums are in our past, but it behooves you to question their existence.Ìý

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Data Updates for 2025

Datasets

In , I noted that the US has extended its dominance of global equities in recent years, increasing its share of market capitalization from 42% in at the start of 2023 to 44% at the start of 2024 to 49% at the start of 2025. That rise was driven by a surge in US equity values during 2024, with the S&P 500 delivering returns of close to 25%, all the more impressive, given that the index delivered returns in excess of 26% in 2023. In this post, I will zero in on US equities, in the aggregate, first by looking at month-by-month returns during 2024, and then putting their performance in the last two years in a historical context. I will follow up by trying to judge where markets stand at the start of 2025, starting with PE ratios, moving on to earnings yields and ending with a valuation of the index.

US Equities in 2024

Ìý Ìý Entering 2024, there was trepidation about where stocks would go during the year especially coming off a a strong bounce back year in 2023, and there remained real concerns about inflation and a recession. The hopeful note was that the Fed would lower the Fed Funds rate during the course of the year, triggering (at least in the minds of Fed watchers) lower interest rates across the yield curve, Clearly, the market not only fought through those concerns, but did so in the face of rising treasury rates, especially at the long end of the spectrum.Ìý

ÌýÌý ÌýWhile the market was up strongly for the year, it is worth remembering that the there were months during 2024, where the market looked shaky, as can be seen in the month to month returns on the S&P 500 during the course of 2024:

The market’s weakest month was April 2024, and it ended the year or a weak note, down 2.50% in December. Overall, though the index was up 23.31% for the year, and adding the dividend yield of 1.57% (based upon the expected dividends for 2025 and the index at the start of the years) yields a total return 24.88% for the year:

As is almost always the case, the bulk of the returns from equity came from price appreciation, with the caveat that the dividend yield portion has shrunk over the last few decades in the United States.
Historical ContextÌý Ìý To assess stock returns in 2024, it makes sense to step back and put the year's performance into historical perspective. In the graph below, I look at returns (inclusive of dividends) on the S&P 500 every year from 1928 to 2024.Ìý

Across the 97 years that I have estimated annual returns, stocks have had their ups and downs, delivering positive returns in 71 years and negative returns in the other 26 years. The worst year in history was 1931, with stocks returning -43.84%, and the best year was 1954, when the annual return was 52.56%. If you wanted to pick a benchmark to compare annual returns to pass judgment on whether a year was above or below average, you can can go with either the annual return (11.79%) or the median return (14.82%) across the entire time period.ÌýÌý ÌýLooking at the 24.88% return in 2024 in terms of rankings, it ranks as the 27th best year across the last 97 years, indicating that while it was a good year, there have been far better years for US stocks. Combining 2023 and 2024 returns yield a cumulative a two-year return for the S&P 500 of 57.42%, making it one the ten best two-year periods in US market history.ÌýÌý Ìý The riskless alternative to investing in US stocks during this period, in US dollar terms, are US treasuries, and in 2024, that contest was won, hands down, by US equities:Equity risk premium earned in 2024, over 3-month Ìýtreasury billsÌý= Return on stocks - Return on 3-month treasuries (averaged over 2024)Ìý= 24.88% -4.97% = 19.91%Equity risk premium earned in 2024, over 10-year treasuries= Return on stocks - Return on 10-year treasury= 24.88% -(-1.64%) = 26.52%The ten-year treasury return was negative, because treasury bond rates rose during 2024.ÌýÌýÌý ÌýEquity risk premiums are volatile over time, and averaging them makes sense, and in the table below, I look at the premium that stocks have earned over treasury bills and treasury bonds, going back to 1928, using both simple averages (of the returns each year) and geometric averages (reflecting the compounding effect):
These returns are nominal returns, and inflation would have taken a bite out of returns each year. Computing the returns in real terms, by taking out inflation in each year from that year's returns, and recomputing the equity risk premiums:

Note that the equity risk premiums move only slightly, because inflation finds its way into both stock and treasury returns.ÌýÌý ÌýMany valuation practitioners use these historical averages, when forecasting equity risk premiums in the future, but it is a practice that deserves scrutiny, partly because it is backward looking (with the expectation that things will revert back to the way they used to be), but mostly because the estimates that you get for the equity risk premium have significant error terms (see standard errors listed below the estimates in the table). Thus, if are using the average equity risk premium for the last 97 years of 5.44% (7.00%), i.e., the arithmetic or geometric averages, it behooves you to also inform users that the standard error of 2.12% will create a range of about 4% on either side of the estimate.

Pricing Questions

Ìý Ìý Coming into 2025, investors are right to be trepidatious, for many reasons, but mostly because we are coming off two extraordinarily good years for the market, and a correction seems due. That is, however, a poor basis for market timing, because stock market history is full of examples to the contrary. There are other metrics, though, which are signaling danger, and in this section, I will wrestle with what they tell us about stocks in 2025.

PE ratios and Earnings Yields

Ìý Ìý Even as we get new and updated pricing metrics, it is undeniable that the most widely used metric of stock market cheapness or expensiveness is the price earnings ratio, albeit with variations in the earning number that goes into the denominator on timing (current, last 12 months or trailing or next 12 month of forward), share count (diluted, primary) and measurement (ordinary or extraordinary). In the graph below, I focus on trailing earnings for all companies in the S&P 500 and compute the aggregated PE ratio for the index to be 24.16 at the start of 2025, higher than the average value for that ratio in every decade going back to 1970.Ìý

Just for completeness, I compute two other variants of the PE, the first using average earnings over the previous ten years (normalized) and the second using the average earnings over the last ten years, adjusted for inflation (CAPE or Shiller PE). At the start of 2025, the normalized PE and CAPE also come in at well above historical norms.Ìý Ìý If I have terrified youÌýwith the PE story, and you have undoubtedly heard variants of this story from market experts and strategists for much of the last decade, I would hasten to add that investing on that basis would have kept you out of stocks for much of the last ten years, with catastrophic consequences for your portfolio. For some of this period, at least, you could justify the higher PE ratios with much lower treasury rates than historic norms,, and one way to see this is to compare the earnings yield, i.e., the inverse of the PE ratio, with the treasury yields, which is what I have done in the graph below:

If you compare the earnings yield to the ten-year treasury rate, you can see that for much of the last decade, going into 2022, the earnings yield, while low, was in excess of the ten-year rate. As rates have risen, though, the difference has narrowed, and at the start of 2025, the earnings yield exceeded the treasury rate. If you see market strategists or journalists talking about negative equity risk premiums, this (the difference between the earnings yield and the treasury rate) is the number that they are referencing.Ìý Ìý At this stage, you may be ready to bail on stocks, but I have one final card to play. In a , I talked about equity risk premiums, and the implicit assumptions that you make when you use the earning to price ratio as your measure of the expected return on stocks.ÌýIt works only if you make one of two assumptions:That there will be no growth in earnings in the future, i.e., you will earn last year's earnings every year in perpetuity, making stocks into glorified bonds.ÌýIn a more subtle variants, there will be growth, but that growth will come from investments that earn returns equal to the cost of equity.The problem with both assumptions is that they are in conflict with the data. First, the earnings on the S&P 500 companies has increased 6.58% a year between 2000 and 2024, making the no-growth assumption a non-started. Second, the return on equity for the S&P 500 companies was 20.61% in 2023, and has averaged 16.38% since 2000, both numbers well in excess of the cost of equity.Ìý Ìý So, what is the alternative? Starting 30 years ago, I began estimating a more complete expected return on stocks, using the S&P 500, with the level of the index standing in for the price you pay for stocks, and expected earnings and cash flows, based upon consensus estimates of earnings and cash payout ratios. I solve for an internal rate of return for stocks, based upon these expected cash flows:

The expected return from this approach will be different from the earnings to price ratio because it incorporate expected growth and changes in cash flow patterns. The critique that this approach requires assumptions about the future (growth and cash flows) is disingenuous, since the earnings yield approach makes assumptions about both as well (no growth or no excess returns), and I will wager that the full ERP approach is on more defensible ground than the earning yield approach.ÌýÌý Ìý Using this approach at the start of 2025 to the S&P 500, I back out an i³¾±è±ô¾±±ð»åÌýexpect return of 8.91% for the index, and an implied equity risk premium of 4.33% (obtained by netting out the ten-year bond rate on Jan 1, 2025, of 4.58%):

You are welcome to take issue with the number that I use there, lowering the growth rates for the future or changing the assumptions about payout. That is a healthy debate, and one that provides far more room for nuance that looking at the earnings yield.ÌýÌý ÌýÌý Ìý How does an implied equity risk premium play out in market level arguments? Every argument about markets (from them being in a bubble to basement level bargains) can be restated in terms of the equity risk premium. If you believe that the equity risk premium today (4.33%) is too low, you are, in effect, stating that stocks are overvalued, and if you view it as too high, you are taking the opposite position. If you are not in the market timing business, you take the current premium as a fair premium, and move on. To provide perspective on the ERP at the start of 2025, take a look at thisÌýgraph, that lists implied ERP at the start of each year going back to 1960:

There is something here for almost point of view. If you are sanguine about stock market levels, you could point to the current premium (4.33%) being close to the historical average across the entire time period (4.25%). If you believe that stocks are over priced, you may base that on the current premium being lower than the average since 2005. I will not hide behind the "one hand, other hand" dance that so many strategists do. I think that we face significant volatility (inflation, tariffs, war) in the year to come, and I would be more comfortable with a higher ERP. At the same time, I don't fall into the bubble crowd, since the ERP is not 2%, as it was at the end of 1999.Ìý

Valuation Questions

Ìý Ìý Pulling together the disparate strands that are part of this post, I valued the index at the start of 2025, using the earnings expectations from analysts as the forecasted earnings for 2025 and 2026, before lowering growth rates to match the risk free rate in 2029. As the growth rates changes, I also adjust the payout ratios, given the return on equity for the S&P 500 companies:

With the assumption that the equity risk premium will climb back to 4.5%, higher than the average for the 1960-2024 period, but lower than the post-2008 average, the value that I get for the index is about 5260, about 12% lower than the index at the start of the year. Note that this is a value for the index today, and if you wanted to adopt the market strategist approach of forecasting where the index will be a year from now, you would have to grow the value at the price appreciation portion (about 7.5%) of the expected return (which is 9.08%).ÌýÌý ÌýAs I see it, there are two major dangers that lurk, with the first being higher inflation (translating into higher treasury rates) and the second being a market crisis that will push up the equity risk premium, since with those pieces in play, the index becomes much more significantly over valued. From an earnings perspective, the risk is that future earnings will come in well below expectations, either because the economy slows or because of trade frictions. Rather than wring my hands about these uncertainties, I fell back on a tool that I use when confronted with change, which is a simulation:Crystal Ball used for simulations
While the base case conclusion that the market is overvalued stays intact, not surprising since my distributions for the input variables were centered on my base assumptions, there is a far richer set of output. Put simply, at today's price levels, there is an 80% chance that stocks are overvalued and only a 20% chance that they are undervalued. That said, though, if you are bullish, I can see a pathway to getting to a higher value, with higher earnings, lower interest rates and a continued decline in the equity risk premium. Conversely, you are bearish, I understand your point of view, especially if you see earnings shocks (from a recession or a tariff war), rising inflation or a market crisis coming up.Ìý Ìý I don't dish out market advice, and as one whose market timing skills are questionable, you should not take my (or anyone else's) assessments at face value, especially heading into a year, where change will be the byword. It is possible that lower taxes and less regulation may cause to come in higher than expected, and that global investment fund flows will keep interest rates and equity risk premiums low. My advice is that you download the , change the inputs to reflect your views of the world, and value the index yourself. Good investing requires taking ownership of the decisions and judgments you make, and I am glad to provide tools that help you in that process.

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Data Updates for 2025
Data Update 2 for 2025: The Party continued for US EquitiesDatasetsHistorical returns on stocks: Historical implied ERP: ÌýPE ratios for the S&P 500:ÌýSpreadsheetsÌýImplied ERP at the start of 2025: Valuation of the index on Jan 1, 2025:

For the last four decades, I have spent the first week of each year collecting and analyzing data on publicly traded companies and sharing what I find with anyone who is interested. It is the end of the first full week in 2025, and is now up and running, and I plan to use this post to describe my data sample, my processes for computing industry statistics and the links to finding them. I will also repeat the caveats about how and where the data is best used, that I have always added to my updates.
The Draw (and Dangers) of DataÌý ÌýIt is the age of data, as both companies and investors claim to have tamed it to serve their commercial Ìýinterests. While I believe that data can lead to better decisions, I am wary about the claims made about what it can and cannot do in terms of optimizing decision making. I find its greatest use is on two dimensions:Fact-checking assertions: It has always been true that human beings assert beliefs as facts, but with social media at play, they can now make these assertion to much bigger audiences. In corporate finance and investing, which are areas that I work in, I find myself doing double takes as I listen to politicians, market experts and economists making statements about company and market behavior that are fairy tales, and data is often my weapon for discerning the truth.ÌýNoise in predictions: One reason that the expert class is increasingly mistrusted is because of the unwillingness on the part of many in this class to admit to uncertainty in their forecasts for the future. Hiding behind their academic or professional credentials, they ask people to trust them to be right, but that trust has eroded. If these predictions are based upon data, as they claim they are, it is almost always the case that they come with error (noise) and that admitting to this is not a sign of weakness. In some cases, it is true that the size of that errors may be so large that those listening to the predictions may not act on them, but that is a healthy response.As I listen to many fall under the spell of data, with AI and analytics add to its allure, I am uncomfortable with the notion that data has all of the answers, and there two reasons why:Data can be biased: There is a widely held belief that data is objective, at least if it takes numerical form. In the hands of analysts who are biased or have agendas, data can be molded to fit pre-conceptions. I would like to claim to have no bias, but that would be a lie, since biases are often engrained and unconscious, but I have tried, as best as I can, to be transparent about the sample that I use, the data that I work with and how I compute my statistics. In some cases, that may frustrate you, if you are looking for precision, since I offer a range of values, based upon different sampling and estimation choices. ÌýTaking a look at my tax rate calculations, by industry, for US companies, int the start of 2025, I report the following tax rates across companies. Note, that the tax rates for US companies range from 6.75% to 26.43%, depending on how I compute the rate, and which companies I use to arrive at that estimate. If you start with the pre-conception that US companies do not pay their fair share in taxes, you will latch on to the 6.75% as your estimated tax rate, whereas if you are in the camp that believes that US companies pay their fair share (or more), you may find 26.43% to be your preferred estimate.ÌýPast versus Future: Investors and companies often base their future predictions on the past, and while that is entirely understandable, there is a reason why every investment pitch comes with the disclaimer thatÌý“past performance is not a reliable indicator of future performanceâ€�. I have , and why assuming that history will repeat can be a mistake. Thus, as you peruse my historical data on implied equity risk premiums or PE ratios for the S&P 500 over time, you may be tempted to compute averages and use them in your investment strategies, or use my industry averages for debt ratios and pricing multiples as the target for every company in the peer group, but you should hold back.ÌýThe SampleÌýÌý ÌýIt is undeniable that data is more accessible and available than ever before, and I am a beneficiary. I draw my data from many raw data sources, some of which are freely available to everyone, some of which I pay for and some of which I have access to, because I work at a business school in a university. For company data, my primary source is S&P Capital IQ, augmented with data from a Bloomberg terminal. For the segment of my data that is macroeconomic, my primary source is , but I supplement with other data that I found online, including for bond spread data and for country risk scores.ÌýÌýÌý ÌýMy dataset includes all publicly traded companies listed at the start of the year, with a market price available, and there were 47810 firms in my sample, roughly in line with the sample sizes in the last few years. Not surprisingly, the company listings are across the world, and I look at the breakdown of companies, by number and market cap, by geography:
As you can see, the market cap of US companies at the start of 2025 accounted for roughly 49% of the market cap of global stocks, up from 44% at the start of 2024 and 42% at the start of 2023. In the table below, we compare the changes in regional market capitalizations (in $ millions) over time.
Breaking down companies by (S&P) sector, Ìýagain both in numbers and market cap, here is what I get:
While industrials the most listed stocks, technology accounts for 21% of the market cap of all listed stocks, globally, making it the most valuable sector. Thee are wide differences across regions, though, in sector breakdown:
Much of the increase in market capitalization for US equities has come from a surging technology sector, and it is striking that Europe has the lowest percent of value from tech companies of any of the broad subgroups in this table.ÌýÌý ÌýI also create a more detailed breakdown of companies into 94 industry groups, loosely structured to stay with industry groupings that I originally created in the 1990s from Value Line data, to allow for comparisons across time. I know that this classification is at odds with the industry classifications based upon SIC or NAICS codes, but it works well enough for me, at least in the context of corporate finance and valuation. For some of you, my industry classifications may be overly broad, but if you want to use a more focused peer group, I am afraid that you will have to look elsewhere. The industry averages that I report are also provided using the regional breakdown above. If you want to check out which industry group a company falls into, please (a very large one that may take a while to download) for that detail.
The Variables
ÌýÌý ÌýThe variables that I report industry-average statistics for reflect my interests, and they range the spectrum, with risk, profitability, leverage, and dividend metrics thrown into the mix. Since I teach corporate finance and valuation, I find it useful to break down the data that I report based upon these groupings. The corporate finance grouping includes variables that help in the decisions that businesses need to make on investing, financing and dividends (with links to the US data for 2025, but you can find .)
table.tableizer-table { font-size: 12px; border: 1px solid #CCC; font-family: Arial, Helvetica, sans-serif; } .tableizer-table td { padding: 4px; margin: 3px; border: 1px solid #CCC; } .tableizer-table th { background-color: #104E8B; color: #FFF; font-weight: bold; }ÌýCorporate Governance & DescriptiveÌýÌýÌýÌýÌý1.ÌýÌýÌýÌýÌý2.ÌýÌýÌýÌýÌý3.ÌýÌýÌýÌýÌýÌýÌýÌýÌýÌý±õnvesting PrincipleÌýFinancing PrincipleÌýDividend PrincipleÌýHurdle RateProject ReturnsFinancing MixFinancing TypeCash ReturnDividends/Buybacks1.Ìý1.Ìý1.Ìý1.1.Ìý1.2.Ìý2.Ìý2.Ìý2.2.ÌýÌý3.Ìý3.Ìý3ÌýÌýÌý4.Ìý4.ÌýÌý4.ÌýÌýÌýÌýÌý5.ÌýÌýÌýÌý(If you have trouble with the links, please try a different browser)Many of these corporate finance variables, such as the costs of equity and capital, debt ratios and accounting returns also find their way into my valuations, but I add a few variables that are more attuned to my valuation and pricing data needs as well.
table.tableizer-table { font-size: 12px; border: 1px solid #CCC; font-family: Arial, Helvetica, sans-serif; } .tableizer-table td { padding: 4px; margin: 3px; border: 1px solid #CCC; } .tableizer-table th { background-color: #104E8B; color: #FFF; font-weight: bold; }ValuationÌýPricingÌýGrowth & ReinvestmentProfitabilityRiskMultiples1.1.Ìý1.Ìý1.Ìý2.Ìý2.Ìý2.Ìý2.Ìý3.Ìý
Ìý3.4.ÌýÌý4.Ìýs5.ÌýÌýÌýÌý6.ÌýÌýÌý(If you have trouble with the links, please try a different browser)Not that while much of this data comes from drawn from financial statements, some of it is market-price driven (betas, standard deviations, trading data), some relates to asset classes (returns on stocks, bonds, real estate) and some are macroeconomic (interest rates, inflation and risk premiums). ÌýWhile some of the variables are obvious, others are subject to interpretation, and I have a , where you can see the definitions that I use for the accounting variables. In addition, within each of the datasets (in excel format), you will find a page defining the variables used in that dataset.Ìý
The TimingÌý Ìý These datasets were all compiled in the last four days and reflect data available at the start of 2025. For market numbers, like market capitalization, interest rates and risk premiums, these numbers are current, reflecting the market's judgments at the start of 2025. For company financial numbers, I am reliant on accounting information, which gets updated on a quarterly basis.ÌýAs a consequence, the accounting numbers reflect the most recent financial filings (usually September 30, 2024), and I use the trailing 12-month numbers through the most recent filing for flow numbers (income statement and cash flow statements) and the most recent balance sheet for stock numbers (balance sheet values).ÌýÌý Ìý While this practice may seem inconsistent, it reflects what investors in the market have available to them, to price stocks. After all, no investor has access to calendar year 2024 accounting numbers at the start of 2025, and it seems entirely consistent to me that the trailing PE ratio at the start of 2025 be computed using the price at the start of 2025 divided by the trailing income in the twelve months ending in September 2024.ÌýIn the same vein, the expected growth rates for the future and earnings in forward years are obtained by looking at theÌýmost updated forecasts from analysts at the start of 2025.ÌýÌý Ìý Since I update the data only once a year, it will age as we go through 2025, but that aging will be most felt, if you use my pricing multiples (PE, PBV, EV to EBITDA etc.) and not so much with the accounting ratios (accounting returns). To the extent that interest rates and risk premiums will change over the course of the year, the data sets that use them (cost of capital, excess returns) allow for updating these macro numbers. In short, if the ten-year treasury rate climbs to 5% and equity risk premiums surge, you can update those numbers in the , and get updated values.

The Estimation Process ÌýÌý ÌýWhile I compute the data variables by company, I am restricted from sharing company-specific data by my raw data providers, and most of the data I report is at the industry level. That said, I have wrestled with how best to estimate and report industry statistics, since almost every statistical measure comes with caveats. For a metric like price earnings ratios, computing an average across companies will result in sampling bias (from eliminating money-losing firms) and be skewed by outliers in one direction (mostly positive, since PE ratios cannot be negative). Since this problem occurs across almost all the variables, I use an aggregated variant, where with PE, for instance, I aggregate the market capitalization of all the companies (including money losing firms) in an industry grouping and divide by the aggregated net income of all the companies, including money losers.ÌýÌýÌý ÌýSince I include all publicly traded firms in my sample, with disclosure requirements varying across firms, there are variables where the data is missing or not disclosed. Rather than throw out these firms from the sample entirely, I keep them in my universe, but report values for only the firms with non-missing data. One example is my , a dataset that I added two years ago, where I report statistics like revenue per employee and compensation statistics. Since this is not a data item that is disclosed voluntarily only by some firms, the statistics are less reliable than on where there is universal disclosure.ÌýÌýÌý ÌýOn an upbeat note, Ìýand speaking from the perspective of someone who has been doing this for a few decades, accounting standards around the world are less divergent now than in the past, and the data, even in small emerging markets, has far fewer missing items than ten or twenty years ago.Ìý
Accessing and Using the Data ÌýÌý ÌýThe data that you will find on my website is for public consumption, and I have tried to organize it to make it easily accessible on my webpage. Note that the current year’s data can be accessed here:If you click on a link and it does not work, please try a different browser, since Google Chrome, in particular, has had issues with downloads on my server.ÌýÌý ÌýIf you are interested in getting the data from previous years, it should be available in the archived data section on my webpage:This data goes back more than twenty years, for some data items and for US data, but only a decade or so for global markets.ÌýÌý ÌýÌýÌý Finally, the data is intended primarily for practitioners in corporate finance and valuation, and I hope that I can save you some time and help in valuations in real time. It is worth emphasizing that every data item on my page comes from public sources, and that anyone with time and access to data can recreate it. ÌýFor a complete reading of data usage, try this link:If you are in a regulatory or legal dispute, and you are using my data to make your case, you are welcome to do so, but please do not drag me into the fight. ÌýAs for acknowledgements when using the data, I will repeat that I said in prior years. If you use my data and want to acknowledge that usage, I thank you, but if you skip that acknowledgement, I will not view it as a slight, and I certainly am not going to threaten you with legal consequences.Ìý Ìý As a final note, please recognize that this I don't have a team working for me, and while that gives me the benefit of controlling the process, unlike the pope, I am extremely fallible. If you find mistakes or missing links, please let me know and I will fix them as quickly as I can. Finally, I have no desire to become a data service, and I cannot meet requests for customized data, no matter how reasonable they may be. I am sorry!

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LinksData Updates for 2025Data Update 2 for 2025: The Resilience of US Equities

I am a teacher at heart, and every year, for more than two decades, I have invited people to join me in the classes that I teach at the Stern School of Business at New York University. Since I teach these classes only in the spring, and the first sessions for each of the classes will be in late January, I think this is a good time to provide some details on the classes, including content and structure. If you have read these missives in prior years, much of what I say will sound familiar, but I have added new content and updated the links you will need to partake in the classes.Ìý
My Motives for Teaching
Ìý Ìý I was in the second year of my MBA program at UCLA, when I had my moment on grace. I had taken a job as a teaching assistant, almost entirely because I needed the money to pay my tuition and living expenses, and in a subject (accounting) that did not excite me in the least. A few minutes after I walked in to teach my first class, I realized that I had found what I wanted to do for the rest of my life, and I have been a teacher ever since. Since that was 1983, this will be my forty first year teaching, and I have never once regretted my choice. Ìý Ìý I know that teaching is not a profession held in high esteem anymore, for good and bad reasons, and I will not try to defend it here. It is possible that some of the critics are right, and I teach because I cannot do, but I like to think that there is more to my career choice than ineptitude. My motivations for teaching are manifold, and let me list some of them:I like the stage: I believe that every teacher, to some extent, has a little bit of a repressed actor in him or her, and I do enjoy being in front of an audience, with the added benefit that I get to review the audience, with the grades that I given them, rather than the other way around.I like to make a difference: I do not expect my students to agree with all or even much of what I have to say, but I would like to think that I sometimes change the way they think about finance, and perhaps even affect their choice of professions. I am lucky enough to hear from students who were in my classes decades ago, and to find out that my teaching made a difference in their lives.ÌýI like not having a boss: I would be a terrible employee, since I am headstrong, opinionated and awfully lazy, especially when I must do things I don’t like to do. As a teacher, I am my own boss and find my foibles completely understandable and forgivable.I know that teaching may not be your cup of tea, but I do hope that you enjoy whatever you do, as much as I do teaching, and I would like to think that some of that joy comes through.
My Teaching Process
Ìý Ìý I do a for business school faculty, and I emphasize that there is no one template for a good teacher. I am an old-fashioned lecturer, a control freak when it comes to what happens in my classroom. In forty years of teaching, I have never once had a guest lecturer in my classroom or turned my class over to a free-for-all discussion.Class narrative: This may be a quirk of mine, but I stay away from teaching classes that are collections of topics. In my view, having a unifying narrative not only makes a class more fun to teach, but also more memorable. As you look at my class list in the next section, you will note that each of the classes is built around a story line, with the sessions building up to what is hopefully a climax.Bulking up the reasoning muscle: When asked a question in class, even if I know the answer, I try to not only reason my way to an answer, but to also be open about doubts that I may have about that answer. In keeping with the old saying that it is better to teach someone to fish, than to give them fish, I believe it is my job to equip my students with the capacity to come up with answers to questions that they may face in the future. In , I argued that one advantage we have over AI is the capacity to reason, but that the ease of looking up answers online, i.e., the Google search curse, is eating away at that capacity.Make it real: I know that, and especially so in business schools, students feel that what they are learning will not work in the real world. I like to think that my classes are firmly grounded in reality, with my examples being real companies in real time. I am aware of the risks that when you work with companies in real time, your mistakes will also play out in real time, but I am okay with being wrong.ÌýStraight answers: When I was a student, I remember being frustrated by teachers, who so thoroughly hedged themselves, with the one hand and the other hand playing out, that they left me unclear about what they were saying. I would like to think that I do not hold back, and that I stay true to the motto that I would rather be transparently wrong than opaquely right. It has sometimes got me some blowback, when I expressed my views about value investing being rigid, ritualistic and righteous and the absolute emptiness of virtue concepts like ESG and sustainability, but so be it.I am aware of things that I need to work on. My ego sometimes still gets in the way of admitting when I am wrong, I often do not let students finish their questions before answering them, I am sometimes more abrupt (and less kind) than I should be, especially when I am trying to get through material and my jokes can be off color and corny (as my kids point out to me). I do keep working on my teaching, though, and if you are a teacher, no matter what level you teach at, I think of you as a kindred spirit.Ìý
My Class Content

Ìý Ìý In my first two years of teaching, from 1984 to 1986, I was a visiting professor at the University of California at Berkeley, and like many visiting faculty around the world, I was asked to plug in holes in the teaching schedule. I taught six different classes ranging from a corporate finance class to undergraduates to a central banking for executive MBAs, and while I spent almost all of my time struggling to stay ahead of my students, with the material, it set me on a pathway to being a generalist. Once I came to NYU in 1986, I continued to teach classes across the finance spectrum, from corporate finance to valuation to investing, and I am glad that I did so. I am a natural dabbler, and I enjoy looking at big financial questions and ideas from multiple perspectives. ÌýÌý ÌýÌý Ìý There are two core classes that I have taught to the MBAs at Stern, almost every year since 1986. The first is corporate finance, a class about the first principles that should govern how to run a business, and thus a required class (in my biased view) for everyone in business.Ìý

If you are a business owner or operator, this class should give you the tools to use to make business choices that make the most financial sense. If you work in a business, whether it be in marketing, strategy or HR, this class is designed to provide perspective on how what you do fits into value creation at your business. If you are just interested in business, just as an observer, you may find this class useful in examining why companies do what they do, from acquisitions to buybacks, and when corporate actions violate common sense.
ÌýÌý ÌýThe second is valuation, a class about how to value or price almost anything, with a tool set for those who need to put numbers on assets.Ìý
Again, I teach this class to a broad audience, from appraisers/analysts whose jobs revolve around valuation/pricing to portfolio managers who are often users of analyst valuations to business owners, whose interests in valuation can range from curiosity (how much is my business worth?) to the transactional (how much of my business should I give up for a capital infusion?)Ìý
ÌýÌý ÌýWhile my class schedule has been filled with these two courses, I developed a third course, investment philosophies, a class about how to approach investing, trying to explain why investors with very different market views and investment strategies can co-exist in a market, and why there is no one philosophy that dominates.Ìý

My endgame for this class is to provide as unbiased a perspective as I can for a range of philosophies from trading on price patterns to market timing, with stops along the way from value investing, growth investing and information trading. It is my hope that this class will allow you to find the investment philosophy that best fits you, given your financial profile and psychological makeup.
ÌýÌý ÌýIn 2024, I added a fourth course to the mix, one centered around my view that businesses age like human beings do, i.e., there is a corporate life cycle, and that how businesses operate and how investors value them, changes as they move from youth to demise.

I have used the corporate life cycle perspective to structure my thinking on almost every class that I teach, and in this class, I isolate it to examine how businesses age and how they respond to to aging, sometimes in destructive ways.
Ìý Ìý In my corporate finance and valuation classes, the raw material comes from financial statements, and I realized early on that my students, despite having had a class or two on accounting, still struggled with reading and using financial statements, and I created a short accounting class, specifically designed with financial analysis and valuation in mind. The class is structured around the three financial statements that embody financial reporting - the income statement, balance sheet and statement of cash flows - and how the categorization (and miscategorization) of expenses into operating, financing and capital expenses plays out in these statements.As many of you who may have read my work know, I think that fair value accounting is not just an oxymoron but one that has done serious damage to the informativeness of financial statements, and I use this class to explain why.
Ìý Ìý Since so much of finance is built around the time value of money (present value) and an understanding of financial markets and securities, I also have a short online foundational class in finance:
As you can see, this class covers the bare basics of macroeconomics, since that is all I am capable to teaching, but in my experience, it is all that I have needed in finance.
Ìý Ìý As our access to financial data and tools has improved, I added a short course on statistics, again with the narrow objective of providing the basic tools of data analysis.Ìý

A statistics purist would probably blanch at my treatment of regressions, correlations and descriptive statistics, but as a pragmatist, I am willing to compromise and move along.ÌýÌý ÌýÌý Ìý As you browse through the content of these classes, and consider whether you want to take one, it is worth noting that they are taught in different formats. The corporate finance and valuation classes will be taught in the spring, starting in late January and ending in mid-May, with two eighty-minute sessions each week that will be recorded and accessible shorts after they are delivered in the classroom. There are online versions of both classes, and the investment philosophies class, that take the form of shorter recorded online classes (about twenty minutes), that you can either take for free on my webpage or for a certificate from NYU, for a fee.Ìý

The accounting, statistics and foundations classes are only in online format, on my webpage, and they are free. All in all, I know that some of you are budget-constrained, and others of you are time-constrained, and I hope that there is an offering that meeting your constraints.
Ìý Ìý If you are interested, the table below lists the gateways to each of the classes listed above. Note that the links for the spring 2025 classes will lead you to webcast pages, where there are no sessions listed yet, since the classes start in late January 2025. The links to the NYU certificateÌýclasses will take you to the NYU page that will allow you to enroll if you are interested, but for a price. The links to the free online classes will take you to pages that list the course sessions, with post-class tests and material to go with each session: table.tableizer-table { font-size: 12px; border: 1px solid #CCC; font-family: Arial, Helvetica, sans-serif; } .tableizer-table td { padding: 4px; margin: 3px; border: 1px solid #CCC; } .tableizer-table th { background-color: #104E8B; color: #FFF; font-weight: bold; }ClassNYU Spring 2025ÌýOnline (free)NYU CertificateWhatsApp Discussion Group Corporate FinanceÌý(Fall) ValuationÌý(Spring & Fall) Investment PhilosophiesNAÌý(Spring) Corporate Life CycleNANA AccountingNANAÌý Foundations of FinanceNANAÌý StatisticsNANA
The last column represents WhatsApp groups that I have set up for each class, where you can raise and answer questions from others taking the class.
My Book (and Written) Content Ìý ÌýÌýLet me begin by emphasizing that you do not need any of my books to take my classes. In fact, I don't even require them, when I teach my MBA and undergraduate classes at NYU. The classes are self contained, with the material you need in the slides that I use for each class, and these slides will be accessible at no cost, either as a packet for the entire class or as a link to the session (on YouTube). To the extent that I use other material, spreadsheets or data in each session, the links to those as well will be accessible as well.Ìý
Ìý Ìý If you prefer to have a book, I do have a few that cover the classes that I teach, though some of them are obscenely overpriced (in my view, and there is little that I can do about the publishing business and its desire for self immolation.) You can find my books, and the webpages that support these books, and a description of the books is below:
table.tableizer-table { font-size: 12px; border: 1px solid #CCC; font-family: Arial, Helvetica, sans-serif; } .tableizer-table td { padding: 4px; margin: 3px; border: 1px solid #CCC; } .tableizer-table th { background-color: #104E8B; color: #FFF; font-weight: bold; }Corporate FinanceÌýValuationÌýInvestment PhilosophiesÌýCorporate Life Cycle : This is the book that is most closely tied to this class and represents my views of what should be in a corporate finance class most closely.Ìý, ): This is my only valuation textbook, designed for classroom teaching. At almost 1000 pages, it is overkill but it is also the most comprehensive of the books in terms of coverage.Ìý): This is the best book for this class, and provides background and evidence for each investment philosophy, with a listing of the personal characteristics that you need to make that philosophy work for you.Ìý This is the most recent of my books and it introduces the phases of the corporate life cycle and why business, management, valuation and investment challenges change with each phase. ): This is a more conventional corporate finance book, but it has not seen a new edition in almost 20 years.Ìý: This is the shortest of the books, but it provides the essentials of valuation, and at a reasonable price.Ìý: This is a very old book, and one that I co-edited with the redoubtable Peter Bernstein, focused on writings on different parts of the investment process. It is dated but it still has relevance (in my view).ÌýÌý : This is a book specifically about measuring risk, dealing with risk and how risk taking/avoidance affect value.Ìý: This is a book about valuing difficult-to-value companies, from young businesses to cyclical/commodity companies. It is a good add-on to the valuation class.Ìý: This book is also old and badly in need of a second edition, which I may turn to next year, but it covers stories that we hear about how to beat the market and get rich quickly, the flaws in these stories, and why it pays to be a skeptic.ÌýÌý ÌýÌý): This was my very first book, and it is practitioner-oriented, with the second half of the book dedicated to loose ends in vlauation (control, illiquidity etc.)ÌýÌýÌýÌý ÌýÌý: This was the book I most enjoyed writing, and it ties storytelling to numbers in valuation, providing a basis for my argument that every good valuation is a bridge between stories and numbers.ÌýÌýÌý
Ìý Ìý Finally, I discovered early on how frustrating it is to be dependent on outsiders for data that you need for corporate financial analysis and valuation, and I decided to become self sufficient and , where I report industry averages on almost every statistic that we track and estimate in finance. These data tables should be accessible and downloadable (in excel), and if you find yourself stymied, when doing so, trying another browser often helps. The data is updated once a year, at the start of the year, and the 2025 data update will be available around January 10, 2025.
A Class GuideÌý Ìý I would be delighted, if you decide to take one or more of my classes, but I understand that your lives are busy, with jobs, family and friends all competing for your time. You may start with the intent of taking a course, but you may not be able to finish for any number of reasons, and if that happens, I completely understand. In addition, the courses that you find useful will depend on your end game.If you own a business, work in the finance department of a company, or are a consultant, you may find the corporate finance course alone will suffice, providing most of what you need.If you are in the appraisal or valuation business, either as an appraiser or as an equity research analyst (buy or sell side), valuation is the class that will be most directly tied to what you will do. I do believe that to value businesses, you need to understand how to run them, making corporate finance a good lead in.If you plan to be in active investment, working at a mutual fund, wealth management or hedge fund, Ìýor are an individual investor trying to find your way in investing, I think that starting with a valuation class, and following up with investment philosophy will yield the biggest payoff.Finally, the corporate life cycle class, which spans corporate finance, valuation and investing, with doses of management and strategy, will be a good add on to any of the other pathways, or as a standalone for someone who has little patience for finance classes but wants a framework for understanding businesses.As a lead-in to any of these paths, I will leave it to you to decide whether you need to take the accounting, statistics, and foundations classes, to either refresh content you have not seen in a long time or because you find yourself confused about basics:If you find yourself overwhelmed with any or all of these paths, you always have the option of watching a session or two of any class of your choice. As you look at the choices, you have to consider three realities.ÌýThe first is that, unless you happen to be a NYU Stern student, you will be taking these classes online and asynchronously (not in real time). As someone who has been teaching online for close to two decades now, I have learned that watching a class on a computer or display screen is far more draining than being in a Ìýphysical class, which is one reason that I have created the online versions of the classes with much shorter session lengths.ÌýThe second is that the biggest impediment to finishing classes online, explaining why completion rates are often 5% or lower, even for the best structured online classes, is maintaining the discipline to continue with a class, when you fall behind. While my regular classes follow a time line, you don't have to stick with that calendar constraint, and can finish the class over a longer period, if you want, but you will have to work at it.ÌýThe third is that learning, especially in my subject area, requires doing, and if all you do is watch the lecture videos, without following through (by trying out what you have learned on real companies of your choosing), the material will not stick.Ìý Ìý I will be teaching close to 800 students across my three NYU classes, in the spring, and they will get the bulk of my attention, in terms of grading and responding to emails and questions. With my limited bandwidth and time, I am afraid that I will not be able to answer most of your questions, if you are taking the free classes online; with the certificate classes, there will be zoom office hours once every two weeks for a live Q&A. I have created WhatsApp forums (see class list above) for you, if you are interested, to be able to interact with other students who are in the same position that you are in, and hopefully, there will be someone in the forum who can address your doubts. Since I have never done this before, it is an experiment, and I will shut them down, if the trolls take over.

In Closing�
ÌýÌý ÌýI hope to see you (in person or virtually) in one of my classes, and that you find the content useful. If you are taking one of my free classes, please recognize that I share my content, not out of altruism, but because like most teachers, I like a big audience. If you are taking the NYU certificate classes, and you find the price tag daunting, I am afraid that I cannot do much more than commiserate, since the university has its own imperatives. If you do feel that you want to thank me, the best way you can do this is to pass it on, perhaps by teaching someone around you.Ìý
YouTube Video
Class list with linksCorporate Finance (NYU MBA): Valuation (NYU MBA): ÌýCorporate Finance (Free Online): ÌýValuation (Free Online): ÌýCorporate Finance (NYU Certificate): ÌýValuation (NYU Certificate): ÌýInvestment Philosophies (Free Online): ÌýInvestment Philosophies (NYU Certificate): ÌýCorporate Life Cycle (Free Online): ÌýAccounting 101 (Free Online): ÌýFoundations of Finance (Free Online): ÌýStatistics 101 (Free Online): WhatsApp Groups for Classes
Corporate Finance: Valuation: Investment Philosophies: Corporate Life Cycle:

ÌýÌýÌý You might know, by now, of my views on ESG, which I have described as an empty acronym, born in sanctimony, nurtured in hypocrisy and sold with sophistry. My voyage with ESG began with curiosity in of what it purported to measure, turned to cynicism as the answers to the became clear and has curdled into something close to contempt, as ESG advocates and retroactively changed their measurements in recent years. Late last year, I , as a subset of ESG investing, and chronicled the trillions put into fighting climate change, and the absence of impact from that spending. Sometime before these assessments, I also looked at the notion of Ìýas an idea that only corporate lawyers and strategists would love, and argued that there is a reason, in conventional businesses to stay focused on shareholders. With each of these topics (ESG, impact investing, stakeholder wealth maximization), the response that I got from some of the strongest defenders was that "sustainability" is the ultimate end game, and that the fault has been in execution (in ESG and impact investing), and not in the core idea. Ìý

ÌýÌý ÌýI was curious about what sets sustainability apart from the critiqued ideas, as well as skeptical, since the cast of characters (individual and entities) in the sustainability sales pitch seems much the same as for the ESG and impact investing sales pitches. ÌýIn critiquing sustainability, I may be swimming against the tide, but less so than I was five years ago, when I first wrote about these issues. In fact, in my first post on ESG, I confessed that I risked being labeled as a "moral troglodyte" for my views, and I am sure that my subsequent posts have made that a reality, but I have a thick skin. This post on sustainability will, if it is read, draw withering scorn from the righteous, and take me off their party invite list, but I don't like parties anyway.

Sustainability: The What, the Why and the Who?

Ìý ÌýÌýI have been in business and markets for more than four decades, and while sustainability as anÌýend game has existed through that period, but much of that time, it was in the context of the planet, not for businesses. It is in the last two decades that corporate sustainability has become a term that you see in academic and business circles, albeit with definitions that vary across users. Before we look at how those definitions have evolved, it is instructive to start with three measures of sustainability, measuring (in my view) very different things:

Planet sustainability, measuring how our actions, as consumers and businesses, affect the planet, and our collective welfare and well being. This, of course, covers everything from climate change to health care to income inequality.Product sustainability, measuring how long a product or service from a business can be used effectively, before becoming useless or waste. In a throw-away world, where planned obsolescence seems to be built into every product or service, there are consumers and governments who care about product sustainability, albeit for different reasons.Business or corporate sustainability, measuring the life of a business or company, and actions that can extend or constrict that life.ÌýThere are corporate sustainability advocates who will argue that it covers all of the above, and that a business that wants to increase its sustainability has to make more sustainable products, and that doing so will improve planet sustainability. That may be true, in some cases, but in many, there will be conflicts. A company that makes shaving razors may be able to create razor blades that stay sharp forever, and need no replacement, but that increased product sustainability may crimp corporate sustainability. In the same vein, there may be some companies (and you can let your priors guide you in naming them), whose very existence puts the planet at risk, and if planet sustainability is the end game, the best thing that can happen is for these companies to cease to exist.ÌýÌý ÌýÌý
Ìý Ìý Which of these measures of sustainability lies at the heart of corporate sustainability, as practiced today? To get the answers, I looked at a variety of players in the sustainability game, and will use their own words in the description, lest I be accused of taking them out of context:
Business schools around the world have discovered that sustainability classes not only draw well, and improve their rankings (especially , which seems to have a fetish with the concept), but are also money makers when constructed as executive classes. NYU, the institution that I teach at, has an course, with certification costing $2,200, but I will quote the Vanderbilt University instead, where for a $3,000 price tag, you can get a certificate in corporate sustainability, which is described as "Ìýa holistic approach to conducting business while achieving long-term environmental, social, and economic sustainability."ÌýAcademia: I read through seminal and impactful (as academics, we are fond of both words, with the latter measured in citations) papers on corporate sustainability, to examine how they defined and measured sustainability. A describes it as recognizing thatÌý"corporate growth and profitability are important, it also requires the corporation to pursue societal goals, specifically those relating to sustainable development â€� environmental protection, social justice and equity, and economic development." In the last two decades, it is estimated that there have been more than twelve thousand articles published on corporate sustainability, and while the definition has remained resilient, it has developed offshoots and variants.Corporate/Business: Companies, around the world, were quick to jump onto the sustainability bandwagon, and sustainability (or something to that effect) is part of many corporate mission statements. , a US insurance company, describes corporate sustainability as centered "around developing business strategies and solutions to serve the needs of our stakeholders, while embracing the necessary innovation and foresight to ensure we are able to meet those needs in the decades to come."Governments: Governments have also joined the party, and the EU has been the frontrunner, and its definition of corporate sustainability as "integrating social, environmental, ethical, consumer, and human rights concerns into their business strategy and operations" has become the basis for both disclosure and regulatory actions. The Canadian government has used to EU model to create a corporate sustainability reporting directive, requiring companies to report on and spend more on a host on environmental, social and governance indicators.ÌýI am willing to be convinced otherwise, but all of these definitions seem to be centered around planet sustainability, with varying motivations for why businesses should act on that front, from clean consciences (it is the right thing to do) to being "good for business" (if you do it, you will become more profitable and valuable).
Ìý Ìý While corporate sustainability has taken center stage in the last two decades, it is part of a discussion about the social responsibilities of businesses that has been around for centuries. From Adam Smith's description of economics as the "gospel of mammon" in the 1700s to Milton Friedman's full-throated defense of business in the 1970s, it can be argued that almost every debate about businesses has included discussions of what they should do for society, beyond just following the law. That said, corporate sustainability (and its offshoots) have clearly taken a more central role in business Ìýthan ever before, and one manifestation is in the rise of "corporate sustainability officers" (CSOs) at many large companies. A in 62 countries, in 2022, found that the number of companies with CSOs tripled in 2021, with about 30% of all companies having someone in that position. A Conference Board survey of hundred sustainability leaders (take the sample bias into account) of the state of corporate sustainability pointed to the expectation that sustainability teams at companies would continue to grow over time.ÌýFinally, going back to academia, an indicator of the buzz in buzzwords, a survey paper in 2022 noted the rise in the number of corporate-sustainability related articles in recent years, as well as documenting their focus:
Note that much of the surge in articles came from ESG, which at least for the bulk of this period marched in lockstep with sustainability. Reflecting that twinning, many of the papers on corporate sustainability, just like the papers on ESG, were f.Ìý
Ìý Ìý I will admit that I have no idea what a CSO is or does, but I did get a chance to find out for myself, when I was invited to give a talk to the CSOs of fifty large companies. I startedÌýthat session with a Ìýquestion, born entirely out of curiosity, to the audience of what they did, at their respective organizations. After about twenty minutes of discussion, it was very clear that there was no consensus answer. In fact, some were as in the dark, as I was, about a CSO's responsibilities and role, and among the many and sometimes convoluted and contradictory answers I heard, here was my categorization of potential CSO roles:CSO as : Some of the CSOs described their role as providing vision and guidance to the companies they worked at, about the societal effects of their actions, and doing so with a long term perspective. In short, even though they did not make this explicit, they were projecting that they had the training and foresight on how the company and society would evolve over time, and advice the company on the actions that it would need to take to match that evolution. I was tempted, though I restrained myself, to ask what training they had to be such receptacles of wisdom, since a degree or certification in sustainability clearly would not do the trick. I did dig into Star Wars lore, where it is estimated that it takes a decade or two of intense training to become a Jedi, and left open the possibility that there may be an institution somewhere that is turning out sustainability jedis.CSO as Jiminy Cricket: I am a fan of Disney movies, and Pinocchio, while not one of the best known, remains one of my favorites. If you have watched the movie, is the character that sits on Pinocchio's shoulder and acts as his conscience, and for some of the CSOs in the audience, that seemed to be the template, i.e., to act as corporate consciences, reminding the companies that they work for, of the social effects of their actions. The problem, of course, is that like the Jiminy Cricket in the movie, they get tagged as relentless scolds, usually get ignored, and get little glory, even when proved right.ÌýCSO as PR Genius: There were a few CSOs who were open about the fact that they were effectively marketing fronts for companies, with the job of taking actions that could not remotely be argued as being good for the planet and selling them as such. I am not sure whether Unilever's CSO was involved in the process, but the company's push to have each of its four hundred brands have a social or environmental purpose would have fallen into this realm.ÌýCSO as Embalmer: Finally, there were some CSOs who argued that it was their job to ensure that the company would live longer, perhaps even forever. Like the embalmers who promised the Egyptian pharaohs everlasting life, if they wrapped themselves in bandages and buried themselves in crypts, these CSOs view longer corporate lives as the end game, and act accordingly. If you are familiar with my work on corporate life cycles, I believe that not much good comes from companies surviving as “walking deadâ€� entities, but in a world where survival at any cost is viewed as success, it is a by product.ÌýHere are the roles in table form, with the training that would prepare you best for each one:
I am sure that I am missing some of the nuance in sustainability, but if so, remember that nuance does not survive well in business contexts, where a version of Gresham's law is at work, with the worst motives driving out the best.
Sustainability and ESGÌý Ìý In the last two or three years, corporate sustainability advocates have tried to separate themselves from ESG, arguing that the faults of ESG are of its own doing, and came from ignoring sustainability lessons. I am sorry, but I don't buy it. If ESG did not exist, sustainability would have had to invent it, because much of the growth in sustainability as a concept and in practice has come from its ESG arm. As I see it, ESG took the noble sounding words of corporate sustainability and converted them into a score, and it was that much maligned scoring mechanism that caused a surge of adoptions both in corporate boardrooms and in investment funds. To complete the linkage, both ESG and sustainability draw on stakeholder wealth maximization, with the core thesis that businesses should be run for the benefit of all stakeholders, rather than “justâ€� for shareholders.ÌýIt is in this context that I used the "theocratic trifecta" to describe how ESG, sustainability and stakeholder wealth are linked, and have been marketed.Ìý
I use of the word “theocratâ€� deliberately, since like the theocrats of yore, some in these spaces believe that they own the high ground on virtue, and view dissent as almost sacrilegious.Ìý

Ìý Ìý While the ESG scoring mechanism, by itself, can be viewed as having a good purpose, i.e., to create a measure of how much a company is moving towards it sustainability goals, and to hold it accountable, it creates the natural consequences that come with all scoringÌýmechanisms:MeasurersÌýclaiming to be objective arbiters, when the truth is that all scores require subjective judgments about what comprises goodness, and the consequences for business profitability and value.BusinessesÌýthat start to understand the scoring process and factors, and then game the scoring systems to improve their scores. Greenwashing is a feature of these scoring systems, not a bug, and the more you try to refine the scoring, the more sophisticated the gaming will become.Advocates wringing their hands about the gaming, and arguing that the answer is more detailed definitions of things that defy definition, not recognizing (or perhaps not caring) that this just feeds the cycle and creates even more gaming.With ESG, we have seen this process play out in destructive ways, with scores varying across services for the same companies, significant gaming around ESG scoring and more disclosure, but with little to show in tangible benefits for society. ÌýIn fact, taking a step back and looking at ESG and sustainability as concepts, they share many of the same characteristics:They are opaque: Both ESG and sustainability are opaque to the point of obfuscation, perhaps because it serves the interests of advocates, who can then market them in whatever form they want to. To the pushback from defenders that the details are being nailed down or that there are new standards in place or coming, the argument runs hollow because the end game seems to keep changing. With ESG, for instance, the end game when it was initiated was ), which evolved to generating alpha (excess returns for investors), on to being a risk measure before converting on a disclosure requirement. Defenders argue that there will be convergence driven by tighter definitions from regulators and rule makers, and the EU, in particular, has been in the lead on this front, putting out a Corporate Sustainability Reporting Directive (CSRD) in 2022, ÌýoutliningÌýeconomic activities that contribute to meeting the EU’s environmental objectives. While ESG advocates may be right about convergence, looking to the the bureaucracy in Brussels to have the good sense (on economics and sustainability) to get this right is analogous to asking a long-time vegan where you can get the best steak in town.ÌýThey are rooted in virtue: While some of the advocates for ESG and sustainability have now steered away from goodness as an argument for their use, almost every debate about the two topics eventually ends up with advocates claiming to own the high ground on virtue, with critics consigned to the other side.ÌýDisclosures, over actions:ÌýÌýThe path for purpose-driven concepts (sustainability, ESG) seems to follow a familiar arc. They start with the endgame of making the world a better place, Ìýare marketed with the pitch that purpose and profits go together (the original sin) and when the the lie is exposed, are repackaged as being about disclosures that can be used by consumers and investors to make informed judgments. Both ESG and sustainability have traversed this path, and both seem to be approaching the "it's all about disclosure" component. While that seems like a reasonable outcome, since almost everyone is in favor of more information, there are two downsides to this disclosure drive. The first is that disclosure can become not just a substitute for acting, but an impediment to the change that makes a difference. ÌýThe second is that as disclosures become more extensive,, especially as the consequential disclosures are mixed in with minor ones, where users start ignoring the disclosure, effectively removing their information value.ÌýUnderplay or ignore sacrifice: Of all the mistakes, the biggest one made in the sales pitch for ESG and sustainability was that you could eat your cake, and have it too. Companies were told that being sustainable would make them more profitable and valuable, investors were sold on the notion that investing in good companies would deliver higher or extra returns and consumers were informed that they could make sustainable choices, with little or no additional cost. The truth is that sustainability will be costly to businesses, investors, and consumers, and why should that surprise us? Through history, being good has always required sacrifice, and it was always hubris to argue that you could upend that history, with ESG and sustainability.Notwithstanding the money, time and resources that have been poured into ESG and sustainability, there is little in terms of real change on any of the social or climate problems that they purport to want to change.Ìý
Can sustainability be saved?ÌýÌý Ìý
Ìý Ìý I may be a moral troglodyte, because of my views on ESG, sustainability and all things good, but I want my children and grandchildren to live in a better world than the one that I lived in. Put simply, we have a shared interest in making the world a better place, and that leads to Ìýthe question of whether corporate sustainability, or at least the mission that it espouses, can be saved. I believe that there is a path forward, but it requires steps that many sustainability purists may find anathema:

Be clear eyed about what can be achieved at the business level: There is truth to the Milton Friedman adage that the business of business is business, not filling in for social needs or catering to non-business interests. It is true that there are actions that businesses take that can create costs to society, and even if the law does not require it, it behooves us all to get businesses to behave better. That said, the danger of overreaching here, and asking businesses to do what governments and regulators should be doing, is that it is not just ineffective but counter-production. ÌýFor business sustainability to deliver results, it has to make that line (between business and government action) clearer.Open about the costs to businesses of meeting sustainability goals: Start being real about the sacrifices in profitability and value that will be needed for a company to do what's good for society. To the extent that in a publicly traded company, it is not the managers, but one of the stakeholders (shareholders, bondholders, employees or customer), who bear this cost, you need buy in from them, of the sustainability actions are voluntary. For companies that are well managed and have delivered success for their owners, the sacrifice may be easier to sell, but for badly managed businesses, it will be and should be a steep hill to climb. To the extent that corporate executives and fund managers have chosen the path of virtue, at a cost to their shareholders and investors, without their buy in, there is clearly a violation of fiduciary duty that will and should leave them exposed to legal consequences.Clear about who bears these costs: I was recently asked to give testimony to a Canadian parliamentary committee that was considering ways of getting banks to contribute to fighting climate change (by lending less to fossil fuel companies and more to green energy firms), and much of what I heard from committee members and the other experts was about how banks would bear the costs. The truth is that when a bank is either restricted from a Ìýprofit-making activity or forced to subsidize a money-losing activity, the costs are borne by either the bank's shareholders or depositors, or, in some cases, by taxpayers. In fact, given that bank equity is such a small slice of overall capital, I argued that it bank depositors who will be burdened the most by bank lending mandates.ÌýAnd honest about cost sharing: One of the benefits of recognizing that being good (for the planet or society) creates costs is that we can then also follow up by looking at who bears the costs. It is my view that for much of the past few decades, we (as academics, policy makers and regulators) been far too quick to decide what works for the "greater good", at least as we see it, and much too blind to the reality that the costs of delivering that greater good are borne by the people who can least afford it.ÌýAbove all, Ìýdrain the gravy train: Drawing on a biblical theme, both ESG and sustainability have been contaminated by the many people and entities that have benefited monetarily from their existence. The path to making sustainability matter has to start by removing the grifters, many masquerading as academics and experts, from the space. I won’t name names, but if you want to see who you should be putting on that grifter list, many of them will be at the annual extravaganza called , where the useful idiots and feckless knaves who inhabit this space will fly in from distant places to Azerbaijan, to lecture the rest of us on how to minimize our carbon footprint. If you are a business that cares about the planet, fire your sustainability consultants, stop listening to sustainability advisors or bending business models to meet CSRD needs, and fall back on common sense, and while you are at it, you may want to get rid of your CSO (if you have one), unless you have Yoda on your payroll.ÌýIn all of this discussion, there is a real problem that no one in the space seems to be willing to accept or admit to, and that is much as we (as consumers, investors and voters) claim to care about social good, we are unwilling to burden ourselves, even slightly (by paying higher prices or taxes), to deliver that good. It could be because we are callous, or have become so, but I think the true reason is that we have lost trust in governments and institutions, and who can blame us? ÌýWhether it is the city of San Diego, where I live, trying to increase sales taxes by half a percent or a government imposing a carbon tax, taxpayers seem disinclined to given governments the benefit of doubt, given their history of inefficiencies and broken promises.ÌýÌýÌý ÌýOne argument that I have heard from many advocates for ESG and sustainability is that the pushback against these ideas is coming primarily from the United States, and that much of the rest of the world has bought in their necessity and utility. That is nonsense! I would suggest that these people leave the ivory towers and echo chambers that they inhabit, and talk to people in their own environs. There are many reasons that incumbent governments in Canada and France (both "leaders" in the climate change fight) are facing the political abyss in upcoming elections, but one reason is the "we know best" arrogance embedded in their climate change strictures and laws, combined with the insulting pitch that the people most affected by these laws will not feel the pain.ÌýÌýÌý ÌýHow do we get trust in institutions back? It will not come from lecturing people on their moral shortcomings (as many will undoubtedly do to me, after reading this) or by gaslighting them (telling them that they are better off when they are clearly and materially not). It will require humility, where the agents of change (academics, governments, regulators) are transparent about what they hope to accomplish, and the costs of and uncertainties about reaching those objectives, and patience, where incremental change takes precedence over seismic or revolutionary change.Ìý
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My posts on ESG, impact investing and stakeholder wealth(August 2019) (September 2020) (September 2021) (March 2022) (October 2023)

Ìý Ìý In this, the first full week in November 2024, the big news stories of this week are political, as the US presidential election reached its climactic moment on Tuesday, but I don't write about politics, not because I do not have political views, but because I reserve those views are for my friends and family. The focus of my writing has always been on markets and companies, more micro than macro, and I am sure that you will find my spouting off about who I voted for, and why, off-putting, much as I did in his cycle, when celebrities and sports stars told me their voting plans. This post, though, does have a political angle, albeit with a market twist. During the just-concluded presidential election, we saw Ìýelection markets, allowing you to predict almost every subset of the election, not only open up and grow, but also insert themselves into the political discourse. I would like to use this post to examine how these markets did during the lead in to the election, and then expand the discussion to a more general one of what markets do well, what they do badly, i.e., revisit an age-old divide between those who believe in the wisdom of crowds and and those that point to their madness.

Election Forecasts: From polls to political markets

Ìý Ìý I watched the movie "Conclave"just a couple of days ago, and it is about the death of a pope, and the meeting to pick a replacement. (It is based on a , one of my favorite authors.) In the movie, as the hundred-plus Catholic cardinals gathered in the Sistine chapel, to pick a pope, ÌýI was struck by how the leading candidates gauged support and jockeyed ahead of the election, essentially informally polling their brethren. I know that the movie (and book) is fiction, but I am sure that the actual conclaves that have characterized papal succession for centuries have used Ìýinformal polling as a way of forecasting election winners for centuries. In fact, going back to the very first democracies in and times, where notwithstanding the restrictions on who could vote, there were attempts to assess election winners and losers, ahead of the event.Ìý

Ìý Ìý The first reported example of formal polling occurred ahead of the 1824 presidential election, when the Raleigh Star and North Carolina Gazette polled 504 voters to determine (rightly) that Andrew Jackson would beat John Quincy Adams. Starting in 1916, The Literary Digest started a political survey, asking its readers, and after correctly predicting the next four elections, failed badly in 1936 (predicting that Alf Landon would beat FDR in the election that year, when, in fact, he lost in a landslide). While polling found its statistical roots after that, it had one of its early dark moments, in 1948, when pollsters predictions that Thomas Dewey would beat Harry Truman were upended onÌýElection Day, leading to one of the (in the Chicago Tribune). In the decades after, polling did learn valuable lessons about sampling bias and with an assist from technological advancements, and the number of pollsters has proliferated. Coming into this century, pollsters were convinced that they had largely ironed out their big problems, but even at it peak, polls came with noise (standard errors), though pollsters were not always transparent about it, and the public took polling estimates as facts.Ìý

Ìý Ìý The fact that individual polls, even if not biased, are noisy (with ranges around estimates) led to a Ìýpoll aggregators, which collected individual polls and averaged them out to yield presumably a more precise estimate. Here, for example, is the aggregated value from Real Clear Politics (RCP), which has been doing this for at least four presidential election cycles now, leading into election days in the US (November 5):

While the original reason for aggregation was removing bias, aggregators can still induce bias by deciding which polls to include (and exclude) in their averages, and sometimes in how they weight these polls. While RCP computes simple averages, there are other aggregators who weight polls, based generally on their accuracy in prior elections, but bias enters in insidious ways.

Ìý Ìý The pushback in poll-based forecasting (whether individual or aggregated) is that it may miss fundamentals on voter history and predilections, and in the last three cycles, there have been a few polling pundits who have used polling aggregates and their presumably deeper understanding of fundamentals to make judgments on who will win the election. Two are the best known are , a site that used to be part of the New York Times but is now owned by ABC, and , and leading into the election, here were their assessments for the election:

Both arrive at their estimates using Monte Carlo simulations, based upon data fed into the system. Note that polls, aggregated polls and poll judgment calls have run into problems in the last decade, some of which may be insurmountable. The first is the advent of smartphones (replacing land lines) and call screening allows callers to not answer some call, and polls have had to struggle with the consequences for sampling bias. The second is that a segment of the population has become tough, if not impossible, to poll, sometimes lying to pollsters, and to the extent that they are more likely to be for one side of the political divide, there will be systematic error in polls that will not average out, and those errors feed into polling judgments.

Ìý Ìý With poll-based forecasts being less reliable and trusted, a vacuum opened up leading into the 2024 elections, and political markets have stepped into the gap. While it has always been possible to bet on elections, either in Las Vegas or through UK-based betting sites like Betfair, they are odd-driven, opaque and restricted. In contrast, opened markets on US election outcomes (president, senate, by state, etc.), and through much of 2024, it has given watchers a measure of what investors in that market thought about who would win the election. In the graph below, you can see the Polymarket prices for a "Trump win" and a "Harris win" in the months leading into the election:

Note that until July, it was Joe Biden who was the democratic nominee for president, and the only portion of the graph that is relevant is the section starting in late July, when Kamala Harris became the nominee.ÌýÌýÌý ÌýMid-year, Polymarket was joined by , structured very similarly, with slightly different rules on trading and transactions costs, and that market's assessment of who would win the market is below:

Since both markets existed in tandem for the months leading into the election, there were intriguing questions that emerged.ÌýThe first is that at almost every point in time, in the months that they have co-existed, the prices for a Trump or Harris win on the two pricing platforms were different, with the prices on Kalshi generally running a little lower than on Polymarket for a Trump win.Ìý

In theory, this looks like an arbitrage opportunity, where you could buy the Trump win on the cheaper market and sell it on the more expensive one, but the transactions costs (1-2% in both markets) would have made them tough to pull off.Ìý

The second is that within each market, there were a proliferation of contracts covering the same outcome, trading at different prices. For instance, on Polymarket, you could buy a Trump win contract for one price, a a Republican win contract at a slightly higher price, leading into just last week, but that difference could just reflect concerns on mortality.Do the actual results vindicate political markets? At least on this election, the answer is nominally yes, since the political markets attached a higher probability for a decisive victory for Trump in the electoral college than did the poll aggregators or judgments. However, political markets did notÌýexpect Trump to win the popular vote, which he may end up doing (some states are still counting), and that can be taken as evidence that markets can be surprised sometimes. ÌýIn the weeks leading into the election, there were two dimensions on which political markets varied from the polls and aggregators. On the plus side, the political markets were more dynamic, reflecting in real time, responses to events like the debates, interviews and endorsements; Polymarket's odds of a Trump win dropped by almost 10% after the debate. On the minus side, political markets were much more volatile than the polls, with swings driven sometimes by large trades; the highlighted one trader who put almost $30 million into the market on the Trump win, pushing up the price.

The Wisdom of Crowds

Ìý ÌýÌýThat trust in crowd judgments in guiding our actions is not restricted to politics. In an earlier part of this post, I talked about going to the movies, and it is indicative of the times we live in that my movie choice was made, not by reading movie reviews on the newspaper, but by . Once the movie was done, the restaurant choice I made was determined by Yelp reviews, and without boring you further, you can see this pattern unfold as you think about how you choose the products you buy on Amazon or even the services (plumbing, electrical, landscaping) that you go with, as a consumer. On a less personal and larger scale, Ìýthe block chains that underlie Bitcoin transactions represent a crowd sourcing of the checking process (performed by institutions like banks conventionally), and you can argue that trusting social media to deliver you information is essentially crowd-sourcing your news.

Ìý ÌýWith these examples, you can see one of the dangers of crowd judgments, and that is that in all the crowds described above (Rotten Tomatoes, Yelp, Amazon product reviews and social media), there is no cost to entry, or to offer an opinion, and that can dilute the power of the judgments. In every one of these sites, you can game the system to give high ratings to awful movies and terrible restaurants, and social media news can be filled with distortions. With markets, we introduce an entry fee to those who want to join the crowd in the form of price, and demand more money to amplify those views.ÌýÌýIn the , opinionated people with no skin in the game can make outlandish predictions, often with no accountability. If you don't believe me, watch the parade of experts and market gurus on any financial television channel, and notice how they are allowed to conveniently gloss over their own forecasts and predictions from earlier periods. In contrast, no matter what you think about the experience or motivations of traders on a market, they have to put money behind their views.

ÌýÌý ÌýWhen you use the price in a market as an assessment of the likelihood of an event, which is what you are implicitly doing when you trust Polymarket or Kashi prices as predictors of election winners, you are, in effect, trusting the crowd (albeit a selective one of those who trade on these markets) to be closer to the right outcome than polling experts or opinion leaders. When market price based forecasts are offered as alternatives to expert forecasts, the push back that you get is that experts have a deeper knowledge of what is being predicted. So, why do we trust and attach weight to the prices that investors assess for something? There are three reasons:

Information aggregation: One of the almost magical aspects of well-functioning markets is how pieces of information possessed by individual traders about whatever is being traded get aggregated, delivering a composite price that is effectively a reflection of all of the information.ÌýReal time adjustments to news: While experts (rightfully) take their time to absorb new information and reflect that information in their assessments, markets do not have the luxury of waiting. Consequently, markets react in real time, often in the moment, to events as they unfold, and studies that look at that reaction find that they often not only beat experts to the punch but deliver better assessments.ÌýLaw of large numbers: It is true that individual traders in a markets can make mistakes, often big ones, in their assessments of value, and can sometimes also let their preconceptions and biases drive their trading. To the extent that these mistakes and biases can lie on both sides, they will average out, allowing the "right' price to emerge from several wrong judgments.

There is also a strand of research that is developing on the forecasting abilities of experts versus amateurs and it is not favorable for the former. Phil Tetlock, co-author of the , chronicles the dismal record of expert forecasts, and argues that the best forecasts come from foxes (knows many things, but not in depth) and not hedgehogs (with deep expertise in the discipline). To the extent that a market is filled with amateurs, with very different knowledge and skill sets, Tetlock's work can be viewed as being supportive of market-based forecasts.

The Madness of Crowds

Ìý ÌýÌýÌýWell before we had Rotten Tomatoes and Twitter were conceived, we had financial markets, and not surprisingly, much of the most interesting research on crowd behavior has come from looking at those markets.. Our experience there is that while markets allow for information aggregation and consensus judgments that are almost magical in their timeliness and assessment quality, they are also capable of making mistakes, sometimes monumental ones. One of my favorite books isÌý, published in 1841, and it chronicles how market mistakes form and grow, using the South Sea Bubble and the Tulip Bulb Craze as illustrative examples. To those who believe that markets have somehow evolved since then to avoid these mistakes, behavioral finance provides the counter, which is that the behavioral quirks that gave rise to those bubble are still present, and may actually be amplified by technology and large platforms. The falsehood that was born in a pub in the South Sea bubble often looks weeks to work its way into market prices, but the same falsehood on a large social media platform today could affect prices almost instantaneously.Ìý

Ìý Ìý Without making this a treatise on behavioral finance, here are some of the problems that can lead markets off course, and make prices poor predictors of outcomes:Ìý ÌýÌý

Noise drowns out information: In finance, we use noise as a term to capture all of the stories and influences that should have no effect on value, but that can still affect prices. While noise exists in even the best-functioning markets, there is enough information in those markets to offset the noise effect, and bring prices back into sync with value. However, if noise is the dominant force in a market, it can drown out information, causing prices to delink from information.ÌýMomentum versus Fundamentals: On a related note, it is worth remembering that the strongest force in markets is momentum, where price movements are driven more by price movements in past periods, than by fundamentals. While in a well-functioning market, that momentum will Ìýbe checked by bargain hunters (if the price is pushed too low) or short sellers (if it is pushed too high), a market where one or the other of these players is either rare or non-existent can see momentum run rampant. It is one reason that I think that markets that restrict short selling, often labeling it as speculation, are creating the condition for market madness.Participant bias: While markets require skin in the game from traders, that requires money, and that biases markets against people with little or no money. In political markets, for instance, it could be argued that the traders on Polymarket and Kalshi represent a subset of the population (younger, better off) that may differ from the voting population.ÌýMarket Manipulation: The history of financial markets also includes clear cases where markets have been manipulated, to deliver profits to the manipulators. That problem becomes worse in markets with limited liquidity, where big trades can move prices, and where market insiders have access to data that outsiders do not.ÌýIlliquidity: All of the problems listed above become greater in a market where liquidity is light, since a large trade, whether motivated by noise, momentum or manipulation, will move prices more.ÌýFeedback loop: There are times where market prices can affect the fundamentals, and through them, the value of what is being traded. With publicly traded companies, a higher stock price, for instance, may allow the companies to issue shares at these higher prices, to finance investments and acquisitions. With the political markets, this feedback loop manifested itself in my social media feeds, where I often saw the Polymarket or Kashi charts being used by candidates to convince potential voters that they were winning (to get them to jump on the bandwagon) or losing (to get people to give them money).Political markets are young, attract a subset of participants, and have limited liquidity (though it did improve over the course of the months), and there were clearly times in the weeks leading in to the election, where crowd madness overwhelmed crowd wisdom. On a optimistic note, these markets are not going away, and it is almost certain that there will be more traders in these markets in the next go-around and that some of the frictions will decrease.Ìý

To "crowd" or not to "crowd"

Ìý Ìý I am convinced that in making our choices as consumers and citizens, we will be facing the choice between market-based assessments and expert assessment on more and more dimensions of our life. Thus, our weather forecasts may no longer come from meteorologists, but from a weather market where weather traders will tell us what tomorrow's temperature will be or how much snow will be delivered by a snow storm. As we face these choices, there will be two camps about whether market prices should be trusted. One, rooted in the wisdom of markets, will push us to accept more crowd-sourcing and crowd-judgments, and the other, building on market madness, will point to all the things that markets can get wrong.Ìý

ÌýÌý ÌýWhile I do believe that, in balance, the wisdom will offset the madness in most markets, there are places where I will stay wary, as a user of market prices. Put simply, rather than view this as an either/or choice, consider using both a Ìýmarket pricing, if available, and a professional assessment. In the context of my discipline, which is valuation, I use both market assessment of country default risk, in the form of sovereign CDS spreads, and sovereign ratings, from the ratings agencies. The latter have more knowledge and expertise, but they are also slow to react to changes on the ground, and I am glad that I have market prices to fill in that gap. ÌýIf you are planning to trade on these markets, I would hope you will heed , where I argued that if you are buying or selling something that has no cash flows, you can only trade, not value, it. In the context of political markets, the price that you are paying is a function of probabilities of outcomes and your capacity to make money in the market will come from you being able to assess those probabilities better than the rest of the market.Ìý

Ìý Ìý There is another use for these political market securities that you may want to consider. To the extent that you feel emotionally invested in one candidate winning, and you don't have much faith in your probability assessments, you may want to consider buying shares in the other candidate. That way, no matter what the outcome, you will have a partially offsetting benefit; a win for your candidate will make you happy, but you will lose some money on your political market bet, and a loss for yourÌýcandidate may be emotionally devastating, but you may be able to soothe your pain with a financial windfall.

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ÌýÌý Ìý I have spent the last week reading "", Phil Knight's memoir of how Ìýa runner on the Oregon University track team built one of the great shoe companies in the world, in Nike. In addition to its entertainment value, and it is a fun book to read, I read it for two storylines. The first is the time, effort and grit that it took to build a business, in a world where risk capital was more difficult to access than it has been in this century, and in a business where scaling up posed significant challenges. The second is the building of a brand name, with a mix of happy accidents (from the naming of the company to the creation of the swoosh as the company's symbol to its choice of slogan), good timing and great merchandising all playing a role in creating one of the great brand names in apparel and footwear. The latter assessment led a more general consideration of what constitutes a brand name, what makes a brand name valuable and what causes brand name values to deplete and disappear. Of course, since my attention was drawn to Nike in the first place, because of and talk of brand name malaise, I tried my hand at valuing Nike in 2024, along the way.

Brand Name - What is it?

Ìý Ìý The broadest definition of a brand name is that it is recognized (by employees, consumers and the market) and remembered, either because of familiarity (because of brand name longevity) or association (with advertising or a celebrity). That definition, though, is not particularly useful since remembering or recognizing a brand, by itself, tells you nothing about its value. After all, almost everyone has heard or recognizes AT&T as a brand/corporate name, but as someone who is a cell service and internet customer of AT&T, I can assure you that neither of those choices were driven by brand name.ÌýÌýThe essence of brand name value is that the recognition or remembrance of a brand name changes how people behave in its presence. With customers, brand name recognition can manifest itself in buying choices (affecting revenues and revenue growth) or willingness to pay a higher price (higher profit margins). With capital providers, it may allow for lower funding costs, with equity investors pricing equity higher and lenders accepting lower interest rates and/or fewer lending covenants. For the moment, this may seem abstract and subjective, but in the next section, we will flesh out brand name effects on operating metrics and value more explicitly.

Corporate, Product and Personal Brand Names

Ìý Ìý Brand names can attach to entireÌýcompanies, to particular products or brands, or even to personnel and people. With a company like Coca Cola, it is the corporate brand name that has the most power, but the soft drink beverages marketed by the company (Coca Cola, Fanta, Sprite, Dasani etc.) each have their own brand names. With companies like Unilever, the corporate brand name takes a back seat to the brands names of the dozens of products controlled by the company, which include Dove (soap), Axe (deodorant), Hellman's (mayonnaise) and Close-up (toothpaste), just to name a few. There are clearly cases of people with significant brand name value, in sports (Ohtani in baseball, Messi in soccer, Kohli in cricket) and entertainment (Taylor Swift, Beyonce), with a spill over to the entities that attach themselves to these people. In fact, a critical component of Nike's brand name was put in place in 1984, when the company signed on Michael Jordan, in his rookie season as a basketball player, and reaped benefits as he became the sport's biggest star over the next decade.

Brand names and other Competitive Advantages

Ìý Ìý One reason that brand name discussions often lose their focus is that companies are quick to bundle a Ìýhost of competitive advantages, each of which may be valuable, in the brand name grouping. The table below, where I have loosely borrowed from Morningstar and Michael Porter is one way to think about both the types and sustainability of competitive advantages:

Companies like Walmart and Aramco have significant competitive advantages, but I don't think brand name is on the top five list. Walmart's strengths come from immense economies of scale and bargaining power with suppliers, and Aramco's value derives from massive oil reserves, with far lower costs of extraction, than any of its competitors. Google and Facebook control the advertising business, because they have huge networking benefits, i.e., they become more attractive destinations for advertisers as they get bigger, explaining why they were so quick to change their corporate names, and why it has had so little effect on value. The pharmaceutical companies have some brand name value, but a bigger portion of their value added comes from the protection against competition they get from owning patents. While this may seem like splitting hairs, since all competitive advantages find their way into the bottom line (higher earnings or lower risk), a company that mistakes where its competitive advantages come from risks losing those advantages.

Brand Name Value

Ìý Ìý At the risk of drawing backlash from marketing experts and brand name consultants, I will start with my "narrow" definition of brand name. In arriving at this definition, I will fall back on a structure where I connect the value of a business to key drivers, and look at how brand name will affect these drivers:

Put simply, brand name value can show up in almost every input, with a more recognizable (and respected) brand name leading to more sales (higher revenues and revenue growth), more pricing power (higher margins), and perhaps even less reinvestment and less risk (lower costs of capital and failure risk). That said, the strongest impact of brand name is on pricing power, with brand name in its purest form allowing it's owner to charge a higher price for a product or service than Ìýa competitor could charge for an identical offering. To illustrate, I walked over to my neighborhood pharmacy, and compared the prices of an over-the-counter pain killer (acetaminophen), in its branded form (Tylenol) and its generic version (CVS) :

The ingredients, in case you are wondering, are exactly the same, leading to the interesting question, more psychological than financial, of why anyone would pay an extra $2.50 for a product with no differentiating features. If you are wondering how this plays out at the business level, the operating margins of pharmaceutical companies that own the "brand names" are significantly higher than the brand names of companies that make just the generic substitutes.

Ìý Ìý The Tylenol example also serves to illustrate when it is easiest to value brand name, i.e., when it is the only competitive advantage, and when it will become difficult to do, i.e., when it has many competitive advantages. It is for that reason that valuing brand name is easier to do at a beverage or cereal company, such as Coca Cola or Kellogg's, where there is little to differentiate across products other than brand name, and you can attribute the higher margins almost entirely to brand name. It is at the basis for my valuation of Coca Cola's brand name in the picture below, where I value the company with its current operating margin:

Note that while the company comes in as slightly overvalued, it is still given a value of $281.15 billion, with much of that value coming from its pre-tax operating margin of 29.73%. We estimate the value of Coca Cola's brand name in two steps, first comparing to a weighted average margin off 16.75% for soft-drink beverage companies, where many of the largest companies are themselves branded (Pepsi, Dr.ÌýPepper etc.), albeit with less pricing power than Coca Coal and then comparing to the median operating margin of 6.92%, skewed towards smaller and generic beverage companies listed globally:

This is undoubtedly simplistic, since it assumes that the brand name value shows up entirely in the margin, and it likely understates the value of Coca Cola's brand name. That said, valuing Coca Cola at the median beverage company margin yields a value of $51 billion, suggesting that 82% of the company's intrinsic value comes from its brand name. Comparing to other beverage company and valuing at the weighted average operating margin still yields a differential brand value of $131.4 billion for Coca Cola, indicating that having a premium brand name has significant value.

Ìý Ìý Brand names become more difficult to isolate and value, when a company has multiple competitive advantages, since the higher margins or growth or returns on capital will reflect the composite effect of all of the advantages.ÌýWith companies like Apple, where brand name is a factor, as is a proprietary operating system, a superior styling and a unique app ecosystem, the higher margin can be attributed to a multitude of factors, making it more difficult, perhaps even impossible, to isolate the brand name value. When valuing Birkenstock, at the time of its IPO, I wrestled with this problem, and with the help of a series of assumptions along the way, did find a way to break the value of the four intangibles that I saw in the company: a world-recognized brand name, a quality management team, free celebrity advertising and the buzz created by Margot Robbie wearing pink Birkenstock in the Barbie movie.

The pricing premium effect of brand name also becomes an effective device to strip companies that hold on to the delusion that their brand name values have value, long afterÌýthey have lost their shine. If a company has margins that trail that of other companies in its industry grouping, it has lost brand name bragging rights (and value), and it is time to either accept that reality or rebrand to acquire pricing power again. Applying this test, you will find that nine out of ten companies that claim to have brand values have really nothing to show for that claim.

Ìý Ìý Nike, in my view, falls somewhere between the two extremes. It is not as pure a brand play as Coca Cola, since athletic footwear, in particular, has physical differentiation that may lead some to prefer one brand over another. At the same time, it is not as complex as Apple, insofar as even a Nike aficionado can find a relatively close substitute in another brand. To measure how Nike's brand name has played out in its operating metrics, we compared the company's operating margins to the weighted operating margin of the two businesses (two thirds footwear and one third apparel) that Nike has operated in for much of the last two decades:

Other than 2023, Nike has consistently earned a higher operating margin (1.5% to 3% higher) than the rest of the industry, and since much of this industry is composed of brand name companies, it would suggest that Nike has a premium brand name, not surprisingly. If you are a Nike-pessimist, though, the drop off in the margin differential in the last five years is troubling, but almost all of that drop can be attributed to the company's troubles in 2023. Clearly, the company is taking the decline seriously, bringing back a Nike employee of long standing in Elliott Hill to replace John Donahoe, who cut his teeth in tech companies (ServiceNow, eBay and PayPal).ÌýÌýÌý ÌýI valued Nike, using its compounded annual growth rate and average operating margin over three period - 2014-2108, 2019-2023 and just the last twelve months: You can see why Nike acted swiftly to change its CEO, since its value will dip substantially, if its growth stays down and margins do not bounce back. At the $71 stock price that the stock was trading at, just six weeks ago, the investing odds would have been in your favor, but the bounce back in the stock price to $88, after the new CEO hire, suggests that the market is pricing in the expectation that the company will bounce back to higher growth and better margins.

Brand Name Creation

Ìý ÌýÌýBrand name does add value, if it gives the company that owns it pricing power, but how does a company end up with a valuable brand name? There are facile answers and they include longevity, with long-lived companies having more recognizable brand names, and advertising, where more spending is assumed to result in a more valuable brand name. To see why I attach the "facile" prefix to these answers, consider again the example of AT&T, a company that has been around for more than a century and remains one of the ten largest spenders on advertising in the United States. None of that spending has translated into a significant brand name value, thought there may other benefits that the company accrues.Ìý

Ìý ÌýI am sure that someone who immerses themselves in in this topic, perhaps in marketing and advertising, may be able to provide a deeper answer, but here is what I see as ingredients that go into developing a valuable brand name:

Attachment to an emotional factor/need: As marketing has recognized through the ages, the key to a powerful brand name is a tie to a human emotion. Rational or not, consumers may reach for a branded product, because they associate the product with , , , or , if that association exists in their minds. The challenge, of course, is to find an emotion that attaches well to your product, either because of its history or its make-up, but the association, once made, can be powerful and long-lasting.Celebrity connection: Earlier, we talked about personal brand names, and argued that Nike benefited from its association with Michael Jordan, in building its brand name. In fact, Apple (in its streaming service) and Major League Soccer benefited mightily from Lionel Messi playing Inter Miami, with the former adding hundreds of thousands of subscribers to it soccer streaming service, and the latter increasing attendance in stadiums around the country. Here again, there are perils, since attaching a brand name to a person also exposes the company to the failings and foibles of that person, as Nike found out in its associations with both Tiger Woods and Colin Kaepernick.Fortuitous events/ choices: There is a third factor that is not covered in most brand name management classes, and for good reason, and that is the effect of luck. In an alternate universe, Phil Knight might have stayed with Dimension Six, his initial choice for the company name, picked a different symbol than the swoosh (for which Nike paid $35 to the designer) and even a different slogan ( than the "Just do it" picked by the advertising team), and the end result could have been very different.Advertising: While there may be little or no link between overall advertising spending and brand name, it is undeniable that there are ads that catch people's attention and alter perceptions of a product. I was an Apple user already in 1984, when it ran its famous 1984 ad during the Super Bowl, setting itself apart from the PC makers, and while that ad yielded little monetary benefit to Apple in the immediate aftermath, it contributed to creating the brand name that now allows the company to charge $1600 for a new smart phone. Nike has had its share of iconic commercials, and I still remember , with Michael Jordan, from 1997, showing how long the shelf life can be for a great ad.

If asked to advice a company that was intent on creating a brand name, my suggestion would be to start with a product or service that is differentiated from the competition, and to give the brand name time to build around that differentiation. That may require sacrifices on scaling up (accepting less growth to preserve the product differential), a higher cost structure (if it is a quality difference) and perhaps even more reinvestment, but trade offs are inherent to almost everything of value in business. If the expected costs of building a brand name exceed its benefits, though, it may be worth asking whether brand name is the competitive advantage that the company should be aspiring for, since there are other competitive advantages that can add as much or much more value in the business the company operates in.

Brand Name Destruction

Ìý Ìý The benefit of building a strong brand name is that it remains one of the most sustainable competitive advantages in business, with the advantages often lasting decades. However, even brand names eventually lose their luster, but the reasons they do so vary:

Aging brand/consumer base: In my posts and book on corporate life cycle, I talk about how and why companies age, and how aging is inevitable. The same can be said of brand names, since even the most highly regarded brand names eventually age, and no matter how much managers try to resurrect them, they never recover their mojo. When valuing Kraft Heinz in 2015, when the most venerable name in value investing (Warren Buffett) teamed up with one of the shrewdest players in private equity (3G Capital) to buy the company because it was under valued, I wondered whether the reason the market was turning down on the company was because the portion of the population that were drawn to the company's products (fifty seven types of ketchup, all of which taste bad, and cheese that stays liquid through a nuclear winter) to be tasty was getting smaller and older. In hindsight, it is clear that Kraft Heinz will not reclaim its former glory, because its products and customer base have aged.Benign neglect: Brand names may provide sustainable competitive advantages, but only if they are cared for and maintained. There are legendary brand names that have been neglected, treated as cash cows with no new investment or sprucing up needed, and have faded in value. Quaker Oats, a longstanding mainstay of the US cereal business, not only allowed itself to pushed to the sidelines by aggressive cereal companies, but failed to take advantage of the rise in demand for oatmeal as a heart-healthy substitute.ÌýCultural changes: There are products and services that have lost their allure over time, because the cultural mores or social norms of the consumers have changed. If you binge watch Mad Men, the television series about advertising in the 1960s, you should not be surprised to see ads for products and services that you would now view in a very different light.ÌýChanging tastes: There are some businesses, where the demand for products is transient and fad-driven, and new brands replace old ones, as tastes shift. This has generally been the case with Ìýapparel retail in the United States, with the Gap's reign at the top lasting about a decade, with newer and cooler retail brands like Abercrombie and Fitch and Tommy Hilfiger replacing them, and then were themselves being displaced by H&M and Uniqlo.ÌýToxic connections: A brand name that is built up over time can sometimes very quickly fall back to earth, if the company or its personnel bring toxic connections. Abercrombie and Fitch, for instance, which became a hot destination for the young in the first decade of this century, found its brand name devastated by accusations of racism and sexism in its ranks.ÌýBrand overreach: There are cases where a company with a valuable brand name may dilute or even destroy that brand name by overreaching, and putting it on products that cut agains the brand name narrative. A good argument can be made that Disney, usually masterful at managing its brands, diluted the value of both its Avengers and Star Wars franchises by rushing headlong into the streaming business, with new series.While all of these forces can cause a once valuable brand name to lose its value, it is worth noting that there are companies that have redeemed brand name value, sometimes by remaking the product or service, sometimes by repackaging it and sometimes by repositioning it. Crocs, whose brand name soared in the 2000s, but crashed by the end of the decade, repackaged itself around celebrity endorsements to become a successful brand again. Lego, a venerable brand name in the toy business, sold off its theme parks, and refocused attention on its core product, while redirecting its offerings to adults. In general, though, reincarnating a brand becomes easier for niche brands than for mass market ones, for product brands than for company brands, and for younger brands than for older ones.Ìý Ìý I believe that 2023 was a wake up call for Nike, as it awoke multiple disruptions. First, in the post-COVID years, Nike moved from store sales to digital sales, with Nike Digital, accounting for almost 43% of revenues in 2022. While that shift does reflect a change in consumer preferences towards shopping online, there is a question of whether bypassing shoe stores, which over the decades have contributed to the Nike brand, by highlighting their most iconic shoes, has undercut the brand. Second, while the footwear business has been more resistant to fads than the apparel business, Nike;'s mass market strategy of being all things to all people is exposing it to disruption. The company is losing market share, especially among younger customers, to newcomers in the space like Ìýand , and among runners (Nike's original core market) to older companies like New Balance that have rediscovered their mojo. Third, in an age where celebrities come with problems, and politics divides us on even the most trivial of issues, Nike's celebrity-driven advertising campaigns may hurt more than help the company. In short, Nike's new CEO has his work cut out for him!
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