In a post at the end of August 2026, I talked about interest rates in 2026 and marveled at the capacity of equities to keep rising in the face of rising rates. I argued that the resilience of stocks during the year could be traced to higher-than-expected earnings being reported by companies in 2026, and a concurrent increase in expected earnings in 2027 and 2028. Now that September 2026 is one for the record books, it is time to take stock and dig a little deeper, especially since the month brought about one of the largest increase in treasury yield rates in recent memory, and stock prices still held their own. In particular, I want to examine the earnings at US companies, in the aggregate and by sector, trying to trace out where the earnings increase is coming from, and how that increased earnings is playing out on corporate balance sheets and cash flows.
Stock Prices and Rates
In my earlier post on interest rates, I had looked at treasury rates by day through the end of August, and I will begin this section by updating that chart to include a tumultuous September:
I had described the rise in rates between January and August as gradual, but the rise in rates in September was anything but, as the ten-year rate rose from 4.75% at the start of the month to 5.29% at the end. In fact, to put the 54 basis point rise in the ten-year rate in context, take a look at the distribution of monthly rate changes in the ten-year treasury in the chart below:
The September rise in rates would put in the top ten percent of 770 monthly rate changes that we have seen between 1962 and 2026. In the face of the mark up in rates, stocks held their own in September, at least in the aggregate, and you can see that in the chart below, where I look at aggregate market values, by month, and by sector:
=
The market added $2.5 trillion in market capitalization across all stocks in September 2026, but almost $1.5 trillion of that came from technology As you look across the entire year, broken down by quarters, here is what you see in the aggregate market caps:
Only companies listed at the start of 2026 included
I excluded firms that were not listed at the start of 2026 from the list since including them will give a misleading sense of returns to investors; adding SpaceX, for instance, which was listed in June 2026, will increase the value of communication service companies by more than $2 trillion, but it was listed at roughly that value. There are many who have pointed to the fact that US equities, while up for the year, have seen divergence in performance, and you can see that phenomenon play out in two statistics. The first is that three sectors - technology, energy and materials have carried the market, with technology being the biggest contributor to market gains. The second is that the percent of companies within each sector that are up for the year is about 50% across the market, and in the third quarter, about 65% of all listed stocks saw dropping stock prices.
It is often difficult to make sense of what is moving stock prices because there are so many factors from growth to interest rates to cash payout that are pulling in different directions. It is to counter this confusion that I have resorted to estimating an implied equity risk premium, where I estimate the internal rate of return you can earn by buying equities, given how they are priced, and their expected earnings growth and cash flows, as well as interest rates. That calculation, which I have done at the start of each month since September 2008, yields an expected return of 8.99% for equities and an equity risk premium of 3.70% (3.92%) over the ten-year treasury rate (dollar riskfree rate) of 5.29% (5.07%) at the start of October 2026:
Note that this estimation is model-agnostic and is an internal rate of return for investing in stocks, given expectations of the cash flows from investing in equities. If you are a market timer, and I am not one, you could use this implied equity risk premium as a barometer of market priciness, with a lower number indicating overpricing and a higher number indicating underpricing.
The jump in US treasury rates in September 2026 has had an effect, with the equity risk premium dropping below 4% for the first time this year. In fact, even as the ten-year treasury rate has climbed this year from 4.18% to 5.29%, the expected return on stocks has also gone up from 8.41% at the start of 2026 to 8.99% on September 30, 2026.
The AI Cap Ex Boom: Accounting and Corporate Finance Consequences
The focus on stock prices and interest rates can sometimes distract us from paying attention to corporate investing, financing and cash return policies that drive value. It should not surprise you, given the times we live in, that AI is at the heart of the business story that is driving corporate behavior, and in the process, providing the fodder for market resistance to higher rates. I will begin with an assessment of how the trillions of dollars in AI cap ex will show up in financial statements:
As you can see, the AI cap ex story is a complicated one, if you are looking at market aggregates, because the market includes both the companies that are spending the money building the AI architecture, which includes data centers and other infrastructure, as well as the companies that are supplying the ingredients for that infrastructure.
The builders of the architecture are the hyperscalers (Meta, Alphabet, Amazon, Microsoft et al.), and the money they spend on cap ex will cause lower earnings, at least until the cap ex starts paying off, in the form of amortization of the AI cap ex, as well as a hit to their free cash flows, which are after cap ex.
The money spent on AI cap ex though becomes revenues to the chip makers (Nvidia and TSMC leading the way), network equipment manufacturers (Broadcom, Micron and Marvel, to name just three), power plant builders (Constellation Energy et al.) and even real estate developers focused on data centers (Equinix, Digital Realty), and ultimately net profits (with net margins driving the bottom line).
It is true that there are gray zones here, with some AI builders also benefiting from being suppliers (Amazon is spending money on AI cap ex but is also benefiting from the usage of its cloud space for data storage, and Nvidia, while selling the chips that go into the architecture, is also investing directly or indirectly into data centers).
As we trace through the aggregated effects of the AI cap ex boom on accounting statements, there are two caveats that need to be stated up front. The first is that the data that is accessible to the public, and which I will be using, will be data from publicly traded companies. To the extent that some of AI's big players (builders and suppliers) are private, I will be missing the revenues, earnings, cash flows and invested capital at these large private players (which include at least two companies in Anthropic and OpenAI that are expected to command trillion dollar plus market caps. The second is that some of the AI cap ex is taking the form of joint ventures and off-balance sheet entities, and the accounting for these (especially on the debt side) may not fully reflect the consequences for firms. As a result, the numbers you see in the public company financials will understate the full effect across all businesses.
With those caveats in place, the business story for US equities starts with massive capital expenditures in AI, with trillions being invested into data centers and AI architecture. It is true that this cap ex is top heavy, with the top ten hyper-scalers accounting for more than $2 trillion of the AI cap ex, but in the table below, I look at the aggregate cap ex reported in corporate financial statements at all publicly traded companies in the United States:
Even with the caveats about understatement, but you can still see that cap ex in the second quarter of 2026, which is our last completed quarter of reported financials, was up $133.4 billion from the cap ex in the second quarter of 2025, an increase of almost 36%. Again, the surge in cap ex is concentrated, with technology, communication services and consumer discretionary all registering growth of more than 50% in the quarter-to-quarter comparison.
Accounting incorporates capital expenditures into the balance sheet as assets, and reflects how this cap ex is funded (debt or equity) by increasing the book values of the funding used in the investment. A surge in cap ex, such as the one that we have seen in 2026, will show up as higher book values for equity, debt and invested capital, and we capture this effect, by sector, in the table below:
Across all US stocks, the book equity has increased almost 13%, between the second quarter of 2025 and the second quarter of 2026, and total debt is up almost 8%. In dollar terms, the book equity at US companies increased by $1.8 trillion between the second quarter of 2025 and the second quarter of 2026, and book debt by $1.9 trillion, over the same period. Technology, being the most active player in AI cap ex, has seen much bigger increases in both numbers, with book equity rising almost 30% and total debt up about 18.8%.
From an earnings perspective, the focus on cap ex and book values may seem misplaced, since the former can only decrease cash flows and the latter impacts accounting returns. In 2026, though, the increased capital expenditures on AI are affecting earnings for a simple reason. The money spent on cap ex by a company building AI architecture will become revenues (and earnings) for other companies that supply the building blocks for the architecture. There is a reason why Nvidia has been the biggest beneficiary from the AI cap ex boom so far, since its chips, marked up massively, power the data centers, and there others, from electrical equipment makers to power companies to real estate developers who have also reaped the benefits. It is true that there should be increased amortization expenses at the AI builders, but the longer amortization schedules being used by many of them is reducing the current hit to earnings at these companies. The earnings effect of the AI story can be seen in the table below, where I look at aggregate net income at US companies, broken down by sector:
Note that in both the first and second quarters of 2026, US companies have seen earnings surge over the corresponding quarters in 2025, with aggregate earnings increasing from $511 billion to $692 billion (translating into an earnings growth rate of 35%, quarter-to-quarter) in the first quarter of 2026 and from $576 billion to $904 billion (translating into an earnings growth rate of 57%, quarter-to-quarter) in the second quarter of 2026. As with stock prices, the earnings benefits are not broad-based, with more than half of all companies in the market reporting declines in net income, and there are wide differences in earnings growth across sectors. Technology, financials and communication services have seen the biggest increases in earnings, and health care, utilities and real estate have lagged.
A cap-ex driven surge in aggregate earnings comes with an asterisk, since the higher earnings across firms will be partially or even fully offset by capital expenditures across firms, leading to free cashflows to firms often growing at much lower rates than earnings. Since these free cash flows are what fund dividend payments and stock buybacks, I looked at cash returned to shareholders in both forms in 2026:
In the aggregate, dividends in the last twelve months are up about $43.3 billion (about 5%) from dividends in the 2025 calendar year, and stock buybacks are up about $106.7 billion (about 9%). In fact, if you net out stock issuances, which spiked in the second quarter of 2026, from buybacks, net buybacks have grown bout 7% between the last calendar year and now. Those numbers represent reasonable step ups from the last year's numbers, but they clearly have not kept up with the earnings growth in 2026. One way to see the disconnect that is occurring between earnings and cash flows is to look at the cash returned as a percent of earnings for the S&P 500 companies over time:
For much of the last two decades, US companies have returned 80% or more, and sometimes more than 100% of their earnings, to shareholders in dividends and buybacks. Starting in about 2024, you can see a divergence with earnings rising much faster than cash returns, and in the last twelve months leading into 2026, the companies in the S&P 500 returned 63% of their earnings to shareholders, a low not seen since 2004. Many of those who were criticizing US companies for buying back too much stock and not investing enough back into businesses are now finding fault with those same companies scaling back buybacks and investing more into AI cap ex, leading to the conclusion that these critics will find fault no matter what companies do.
The AI Business Resolution: Accounting and Market Consequences
It is true that the massive investments in AI cap ex are being driven by expectations that AI as a business will enjoy not only a large market, but one that where the winners can sustain huge profits for the long term. As I noted in my post on AI as a business, this is a plausible path, but there are vast disagreements on whether this is the expected one, given uncertainties about all three layers of the business story - the size of the total addressable market, the unit economics/operating margins of companies in the business and the moats and competitive advantages that will allow for sustainability in profits. So, what will the accounting and market consequences be, if the AI pathway diverges from expectations? In the table below, I trace out the accounting and market consequences of the AI business working better than expected at delivering growth and profits, as well as if i does much worse than expected:
In the best case scenarios for AI, the companies that have invested in AI, at least collectively, will be able to deliver not just earnings growth from the cap ex, but enough incremental earnings to generate returns on the AI cap ex that exceed their cost of capital for those investments. Their lenders will be made whole, with interest and principal payments, and the AI builders will see their cashflows become more positive, but the companies, while successful, will emerge as very different businesses than when they entered the space, more capital intensive than they used to be.
In the worst case scenarios for AI, there will be both accounting and market carnage, as accountants write off large portions of the AI cap ex, because of its failure to deliver promised profits, and while cash flows may recover, markets will correct the pricing of these companies to reflect a lack of trust in management. For companies that were excessively dependent on debt for their AI cap ex, there will be defaults and increased distress, with lenders feeling the pain as well.
There are also intermediate scenarios, ranging from AI being a moderate success, where the companies investing AI may be able to extract some earnings from their investment, but not enough to cover the cost of capital, to a moderate failure, where some companies may be able to justify their investments and most will not.
Given that AI business surprises will have both market and accounting consequences, I will hazard a guess that the market will lead in this process and accounting will follow. In short, if AI is working better (worse) than expected, you should see stock prices at AI-centered businesses rise (fall) before you see accountants respond. Put simply, in the event that AI does not deliver on its promise, waiting to act until accountants write off AI cap ex to sell your AI company implies that you waited too long.
An Investor Perspective: Taking Stock and Taking Action
In my post on AI as a business, I zeroed in on the debate between AI optimists, pointing to huge (albeit unspecified) markets for AI products and services, and AI skeptics, drawing attention to the outsized capital expenditures. While that debate plays out, financial markets and businesses cannot afford to wait for resolution, and are acting now, with companies making investments in cap ex and markets building in their expectations of what that will mean for future earnings into stock prices. That has made not just the market but also the economy a giant bet on AI, with success vindicating the companies and investors who have bet on it, and failure manifesting in massive write offs at companies (feeding into losses) and stock price markdowns. As investors, there are four choices that you can make, and unfortunately, none of these choices give you the luxury of sitting out the AI debate:
Go all in on the AI story winning (and doing it soon): The first betis that AI is an unstoppable force, destined to change the way we live and work, with AI businesses reaping the benefits of the disruption. It is a plausible story, albeit one that raises significant questions about the economic and social costs of disruption, with disagreements about the speed and extent of the disruption. It was the story that Leo Aschenbrenner built Situational Awareness around, and while excessive leverage, driven by hubris and over-conviction, brought him down, it is possible that you could mimic his strategy, of buying the AI disruptors and/or selling the AI disrupted, albeit with far less leverage, and win in the long term.
Go with the market consensus: In an age where we worship at the altar of crowd wisdom in almost everything we do, you could examine what the market is pricing in, as its AI story, and go along. At the moment, at least, the market seems to be building in the expectation that AI will be a major disruption that will give rise to large and valuable businesses and it is picking its winners among the AI architecture companies (with Nvidia the biggest so far) and among the LLMs (SpaceX in the public markets and OpenAI and Anthropic in the private markets). For better or worse, you may have already chosen this path implicitly, if your pension funds and savings are invested passively, getting partial exposure to this story with an S&P 500 fund, and more complete exposure if you buy a total market fund for US equities.
Be an AI skeptic: There are many reasons to be skeptical about the AI story, and for some, that skepticism may lead to the belief that AI will not make it as a viable business, or at least one large enough to sustain the pricing and investment you are seeing for it. While that belief may not be strong enough to lead you to act on it, you can steer your new investing away from the AI space, investing in businesses that are least likely to be altered by AI (food processing and leisure) and in geographies where AI is less likely to be a threat, such as the EU (perhaps because of regulation) and parts of Asia (because AI is too expensive to replace human labor in many businesses).
Crash out on the AI story: If your belief that AI will fail hardens into a conviction that failure is imminent, you can try to actively cash in on your story. You should, at the minimum, reduce your exposure to equities, especially in the US, by selling your holdings and putting that money into cash,. If you are more risk taking, you can sell short on the companies that have seen their pricing surge on the AI story and perhaps buy the companies that AI was meant to disrupt, flipping Leo Aschenbrenner's story. This has not been a winning strategy for many of the traders and investors who have tried it out for the last two years, and it is worth remembering the adage hat markets can stay irrational longer than you can stay solvent
I am personally going with the "market consensus' choice for the bulk of my portfolio, since I do hold five of the Mag Seven (all except Tesla and Nvidia) and four of my holdings in this group (Amazon, Alphabet, Meta and Microsoft) are heavy investors in AI cap ex, but the new money added to my portfolio in the last year or two has gone mostly into cash (short term treasuries, yielding 4%) for much of the last year, leaving my portfolios more cash-laden than usual. I have left money on the table undoubtedly by doing so, but it has helped me sleep better at night, and my advice to you is that you find a pathway in the AI jungle that helps you pass the sleep test as well.
There is one final piece of this puzzle that bears watching, and that is a portion of your portfolio that does not show up (yet) in your holdings. The income you will earn in your occupation, over the rest of your working life, is human capital, and to the extent that you believe that AI disruption is coming for your profession, it behooves you to direct your financial capital away from the businesses most exposed to AI disruption to balance your portfolio. I am old enough not to care much about this component, since I have fewer working years left, but if you are much younger than me, this could change your investment game.
The war in Iran, oil prices and worries about a recession have all taken turns driving stock prices in 2026 but talk about interest rates and where they are going has been a constant concern all year. In the last few weeks, interest rate worries have come to the surface again, for three reasons, all related. The first is the rise in long-term US treasury rates to levels not seen in twenty years. The second is US debt exceeding $40 trillion for the first time, bringing attention to a long-standing worry that this debt burden may be hitting a tipping point for bond buyers. The third is a that the Federal Reserve has a new chair in Kevin Warsh, and for the many Fed Watchers, who are uncertain about where he plans to lead the Fed, the Federal Open Market Committee (FOMC) meeting coming up in mid-September looms larger than ever.
In this post, I hope to step back from the day-to-day coverage of US treasury yields and look at their performance in 2026, not only with a longer term perspective, but also in the context of movements in long terms yields in government bonds in other currencies. I also intend to revisit a discussion that I initiated in 2022, when interest rates were the central act in markets, about the relationship between interest rates and stock prices, and why higher rates do not always translate into lower stock prices, and why that effect will vary across sectors and companies.
Government Borrowing Rates
Governments borrow money and often do so by issuing bonds in financial markets. The rates on these bonds reflect the concerns that lenders have about the purchasing power of the currencies that they are issued in, and government bond rates, for better or worse, become indicators that drive day-to-day market movements in almost all asset classes. In this section, I will begin with an examination of US treasury rates before expanding the discussion to government bond rates in other currencies.
The 2026 Interest Rate Experience
Coming into 2026, US treasury rates had mostly moved sideways for a couple of years, but during the course of 2026, rates have risen steadily across the maturity spectrum with long term treasury rates showing more movement than rates at the short end. Both the 20-year and 30-year treasuries rose above 5% during the course of the year, and the 10-year rate, which started the year at 4.18% reached 4.75% at the end of August. The graph below looks at US treasury rates across maturities in 2026:
I know that there are some who attribute almost everything related to interest rates to the Fed, and while I think that is simplistic and wrong-headed to do so, I show the four FOMC meetings that have occurred in 2026, as well as the date of Kevin Warsh’s ascension to the chairmanship of the Fed. While there is little in this graph to indicate that the meetings or the changing of the guard at the top had a material impact on treasury rates, the divergence in rate movement across maturities has removed the kink (at the 2-year maturity) at the start of the year and made the yield curve more upward sloping:
To put the increase in rates, especially long term, during 2026 in context, I looked at movements in 3-month, 10-year and 30-year rates between 1962 and the start of September 2026, with the caveat that the 30-year rate series is available only since the mid-1970s.
Federal Reserve Data (FRED)
As you look at the entire time period, you can see the trauma of the 1970s, a decade where interest rates rose to levels not seen in the US in a century, and peaking in 1981, as the Fed struggled to put the inflation bogeyman back into the closet. While rates did come down from those highs, they stayed in the 8-9% range in the second half of the 1980s, and in the 6-8% range in the 1990s with the dot-com boom operating as a ballast. In the first decade of this century, ten-year rates declined below 5% in 2002, but stayed in the 4-5% range until 2008, when the financial crises drove rates below 4%. In the last decade (2011-2020), rates trended down, dropping below 3% in 2011 and staying in the 2-3% range for most of the period, with the Fed lending a helping hand. The economic shutdown in 2020, after COVID, pushed long term rates below 1% for the first time in history, and rates stayed low in 2021. The extended stretch of low interest rates from 2009 to 2021 was broken in 2022, when the ten year rate more than doubled, from 1.52% to 3.88%, and rates since have largely stayed in the 4-4.5% range, with the 4.75% rate in September 2026 representing a breakout. The graph also includes the 3-month treasury bill rate, and it moves largely with the 10-year rate, albeit with bigger swings, and rates close to zero for much of the last decade, and the 30-year treasury rate, which has generally traded at slightly above the 10-year rate, with the difference widening in September 2026.
The Drivers of US Interest Rates
In my prior posts on interest rates, I have argued that the focus among many investors and market-watchers on the Federal Reserve as the all-powerful force moving interest rates has diverted attention from the fundamentals that move rates over time. The first of these fundamentals is inflation, with higher expected inflation manifesting as higher rates, and the second is a real interest rate, which at least in the long term, you can proxy with real growth in the economy. One of the indicators that I track is what term an "intrinsic riskfree rate", which I obtain by summing up the inflation rate and real GDP growth in the US economy each year. Financial markets have minds of their own, and the observed rates are a function of demand and supply:
If your pushback is that actual inflation is a noisy estimate, and that expected inflation is anyone's guess, you are right, but for much of this century, we have had market estimates of expected inflation, that can be obtained from the US treasury market, by comparing the 10-year US treasury yield to the yield on a ten-year US TIPs (inflation-protected rate):
Federal Reserve Data (FRED)
The expected inflation numbers embedded in the US treasury market show a market that is less swayed by year-to-year changes in inflation than more by long term expectations, with a dip in expected inflation between 2008 and 2021, and an increase in expected inflation estimates, starting in 2022. It is interesting that notwithstanding the surge in oil prices this year, and the increased talk of inflation, there has been only a very mild increase in the long-term expected inflation rate, as calculated using yields on treasuries at the start of September 2026.
In the graph below, I use the actual inflation rates and real GDP growth rates for the US, going back to 1962, and compute the intrinsic 10-year treasury rate (the cumulative column) and actual 10-year treasury rate each year:
Federal Reserve Data (FRED)
The graph tells the interest rate story well, as the surge in inflation in the 1970s played out as higher rates (intrinsic and real) for much of that decade and the next, and the decline in inflation and anemic real growth translated into the lower rates that we observed from 2009 and 2021. When inflation surged in 2022, interest rates went up, but since the rates that I am tracking are long term rates, the intrinsic risk free rate vastly exceeded the actual rate that year, but the difference has narrowed over time, and almost dissipated by September 2026 (when the US 10-year treasury bond rate was 4.75% and and the intrinsic ten-year rates yielded 5.41%).
Government Bond Rates in Other Currencies (Countries)
As investors focus on movements in US treasuries, interest rates have been on the move across the globe since 2021. In the graph below, I start with a look at government bond rates in five other currencies: the Euro (with the German 10-year bond rate), the Japanese Yen, the Australian and Canadian dollar and the British pound:
You will notice that the rise in rates from COVID lows (which pushed the Euro ten-year rate into negative territory) has been across the board, with rates surging in 2022. Focusing just on 2026, you see the same pattern, with rates rising across all of the currencies tracked in this graph. What about the currencies of other economies? I track ten-year government rates in four currencies - the Chinese Yuan, the Indian rupee, the Brazilian Real and the South African Rand - in the graph below:
Here, the results are more nuanced, with no or a muted 2022 effect, and ups and downs since; rates are lower in September 2026 than they were in 2021 in three of the four currencies.
The convergence of government bond rates across currencies in the last few years has laid waste to the carry trade, where you borrow money in a low-rate currency and lend it out at a higher-rate currency, and the punishment meted out to its practitioners is, in my view, well deserved. The carry trade is the laziest of investment strategies, with its successes due entirely to lags in how exchange rates respond to fundamentals, and calling it an investment strategy does a disservice to investing, in general.
Interest Rate Ripple Effects
Changes in government bond rates clearly play out in the pricing of government bonds, and returns you will earn on them, but the ripple effects play out across the rest of the market (financial and real). In this section, I will start with the corporate bond market, where the interest rate effect is dominant, before looking at equities, where interest rate effects are more nuanced.
Corporate Bonds
Just as governments need to borrow money to fund their expenditures, businesses also borrow money, either through bank loans or if they are positioned to do so, by issuing bonds. The rates at which businesses can borrow start with a riskfree rate in the currency as a base, with a credit spread reflecting the business borrower's default risk added on. If governments are perceived to be riskfree, the government bond rate stands in as the riskfree rate, but if they are not, the riskfree rate can be extracted from the government bond rate, by netting out the default spread for the government. That makes working with US dollars tricky, since the US lost its Aaa rating (Moody's) in May 2025, and I wrote about the consequences for computing dollar riskfree rates at the time.
In the graph below, I look at the day-to-day movements in default spreads over the ten-year US treasury rate, across seven bond ratings classes - AAA, AA, A, BBB, BB, B and CCC & lower - in 2026:
Federal Reserve Data (FRED)
Since default spreads are added to the US treasury rate, and the ten-year rate has risen in 2026 from 4.18% at the start to 4.75% on August 31, 2026, corporate bond rates are all higher than they were at the beginning of the year. For all of the ratings classes, other than high yield (CCC & below), spreads are largely unchanged or lower. The only ratings class where you see a surge in spreads is in the lowest rated bonds, where the default spread has increased by 1.57% during the course of the year.
The implications for corporate borrowing and costs of capital are direct. Debt is now costlier than it was at the start of the year, for business borrowers across the world, with almost all of the increase coming from rising riskfree rates, in different currencies, with an added cost for the borrowers with the highest default risk. For bond investors, with money in long-term corporate bonds, the year has played out in lower bond prices, in both the treasury and corporate bond markets.
Note that while the returns have been low or even negative, across bond categories, the effect is nowhere near the carnage that we saw in 2022, partly because the rate change has been more muted and partly because the price effect of a rate change is much greater when rates are very low, as they were at the start of 2022.
Stock Prices
The essence of intrinsic value is that the value of an asset is the present value of the expected cashflows from that asset. As you take your first steps through discounted cashflow valuation, the question of what should happen to value, as interest rates increase, seems obvious. After all, as interest rates rise, discount rates should go up, and as they go up, the present value should decrease. That is, in fact, the process that I used to estimate the changes in bond value during 2026, in both US treasuries and corporate bonds. The reason that the effect of higher rates on value is direct, with bonds, is because the cash flow on a bond is the coupon and the coupon is set at the time the bond is issued, and does not change as interest rates change. With stocks, the effect of higher interest rates is not as direct for a simple reason. The expected cash flows on stocks are the residual cashflows from operations at businesses, and these residual cash flows reflect the revenues, earnings and reinvestment at these businesses.
If, as interest rates rise, both cash flows and discount rates change, the effect of interest rates changes on equity prices requires grappling with how these interest rates changes play out in operating metrics:
With revenues, the key determinants of how higher interest rates play out in value will depend first on why interest rates rose in the first place (higher inflation or higher real rates), and if it is higher inflation, how much pricing power a business has to pass through that inflation to its customers.
With earnings, the question is how higher interest rates play out in profit margins, through their effects on costs of goods sold (gross), other operating expenses (operating) and interest expenses (net).
When interest rates rise, and that rise is due more to real rates rising rather than inflation going up, businesses can scale back reinvestment, since fewer investments will generate the returns needed to pass muster. This reduction in reinvestment can increase near-term cashflows, at the expense of future growth.
The effects of higher interest rates will therefore vary across companies, with some companies seeing decreases in value (as the discount rate effect dominates any cash flow effects), some seeing no impact (as the discount rate and cash flow effects cancel out), and some benefiting with higher value, because their cash flows rise more than enough to compensate for higher discount rates:
The effect on equities, in the aggregate, will depend on the composition of the market, and which of the three groups (companies hurt by. not affected by or helped by) dominates. There is the added complication of risk premiums (equity risk premium and bond default spread) being affected by higher rates, adding to the discount rate effect.
As you can see, the question of how higher interest rates will play out in stock prices, will vary across different equity markets, and with any given market, it will vary across time. As US treasuries have risen in 2026, US equity indices have, for the most part, taken that increase in stride, with the S&P 500 and NASDAQ both rising strongly over the first eight months of the year:
To zero in on the interest rate effect, I looked at the yield on the 10-year US treasury bond, by day, during 2026. Of the 169 trading days of the year, from January 1 through August 31, 2026, there have been 84 days when yields increased, 73 days that they decreased and 12 days where they remained unchanged, and I looked at S&P 500 average daily returns for each group:
Were stock prices affected by changes in treasury rates during the trading day in 2026? The answer is yes, but only for larger movements in the yield (>3 basis points), with the S&P 500 down almost half a percent on days when the 10-year rate increased by more than 3 basis points and up about half a percent on days when the rate decreased by more than 3 basis points. Thus, at the risk of sounding contradictory, while stocks have held their own during 2026, in the face of rising rates, they have done much worse on days when the 10-year treasury rate went up than they did on days that rate decreased. The secret to equity resilience in the face of higher oil prices, interest rates and political turmoil has been in equity earnings, which have surged over the course of 2026. In the graph below, you can see the analyst consensus estimates of earnings for the S&P 500 for 2026 and 2027 over the course of 2026:
Ed Yardeni
Over the first eight months of 2026, analysts who track the S&P 500 companies have raised their estimates for corporate earnings by more than 11% for both 2026 and 2027, indicating that companies are finding ways to get more to the bottom line, in the face of macro concerns and higher rates. I know that you have questions about these earnings, and I do as well, especially in the context of how companies are reporting the effects of AI on their earnings, but at least on the surface, the numbers are impressive. I plan to revisit these earnings numbers in a future post, and take a deeper look at what's driving these numbers, but for the moment, they are the reason that stocks have held their own in 2026.
Equities: Cross Company Comparisons
While equities, at least in the aggregate, have held their value, how have higher interest rates played out across sectors? In the table below, I break down all US companies, broken down into sectors, and look at the change in aggregate market capitalization for the sector, as well as statistics on individual companies within each sector (lower quartile, median, upper quartile and percent up and down):
Source Data: S&P Capital IQ
During 2026, energy was the best performing sector, not surprising given the spike in oil prices, followed by technology, at least based upon aggregated market cap returns. The divergence between the at measure of return and the returns on the median company in the sector is a measure of how top-heavy a sector's returns are, and with technology, it is clearly the largest tech companies that are driving the returns; the median tech company had returns of only 7.75%, well below the aggregate tech sector returns of 25.22%. The worst performing sectors in 2026, at least through August, are the consumer sectors (discretionary and staple), utilities and communications, with lower pricing power and higher input costs to blame.
Since the rise in interest rates is not restricted to the United States, I looked at the performance of equities across the globe, based upon aggregated market capitalization (in dollar terms) and looking at individual company metrics on returns:
Source Data: S&P Capital IQ
While global equity value has increased about $17 trillion (11.28%) in 2026 (through August 31, 2026), there are wide differences across regions, with Indian and Chinese equities struggling with low single digit returns, and far more stocks down than up. Some of the performance that you see in this table comes from movements in exchange rates, since regions with currencies that have appreciated (depreciated) against the US dollar will see increases (decreases) in US dollar returns.
Conclusion
As we get closer to the FOMC meeting date, it is likely that there will more talk about interest rates, and what the Fed can or cannot do to change their course. Much of that debate, in my view, is pointless, since the pathway of rates is and will continue to be set by fundamentals. In fact, the ten-year US treasury rate has been stuck in a fairly tight range, between 4% and 5%, since 2022, and that is largely because expected inflation has settled in at about 2.5%, even as actual inflation has remained volatile. For rates to change significantly, up or down, there has to be a break in inflation expectations, to the up or downside, and there is little that Kevin Warsh or Scott Bessent can do to alter that trajectory. As to how equity markets and businesses are dealing with higher rates, the pain from moving from a low-rate to a high-rate world was most acutely felt in 2022, and both have adapted quickly to the new environment, with businesses finding ways to deliver higher earnings in the face of higher rates, and markets pricing in these earnings to deliver solid returns.
It is undeniable technology companies have found their most hospitable setting in the United States and while there are many reasons for the US dominance of technology, easier access to capital for young businesses has been a key ingredient. Venture capital in the US, in its institutional and organized form, can trace its roots back to the 1950s, and over the last few decades, it has generated its share of legendary investors. Vinod Khosla is one of those legends, and it is for that reason that I was surprised to see him tweet the following:
I understand that utterances on social media, often in response to comments by others or made in anger, are often quickly regretted, and I believe (though I am not certain) that Mr. Khosla did not quite mean what he said here, confusing profitability with cash flows, and arguing that every business should put scaling ahead of profitability. That said, his view that scaling should be given priority over profitability is more the norm, than the exception, among many venture capitalists, and while it probably always has been the case, I believe the tilt towards scaling has become pronounced in the last two decades. In this post, I want to zero in on the scaling and profitability trade off, how the emphasis on the former over the latter plays out at start-ups and very young companies, and why we live with the consequences, whether they want to or not.
Scaling versus Business Building
To put the choices you will face on scaling up versus business building into perspective, let's assume that you are a founder, and that your start-up has a tested product and that you believe there is a market for that product. You can stay with what you have built and build a business to take advantage of the immediate market, focusing on financial health and profitability. The fact that you will stay small, and perhaps unrecognized in markets other than your own, is a minus, but there are pluses. You will have little need for external capital, and you will own much or all of the business, facing little pressure from outside to change the way you do things. Alternatively, you can take a more ambitious route, where you seek out a bigger market, augmenting existing or adding new products, and while that path will deliver larger revenues, you may have to work harder to get it to deliver profits and cash flows, and perhaps have to give up more of your ownership and control of that business.
The Scaling Choice
Before starting on the determinants of scaling, it make ssense to begin with the metric being scaled. For most businesses, it is revenues that is the chosen metric, with scale capturing how big revenues can become over time. With some earlier-stage businesses, many of which are pre-revenue, the metric can become a variable that these businesses hope to convert to revenues; with tech intermediaries and social media companies, it can be users or subscribers.
Focusing on scale, though, there are factors that come into play that allow scaling to have a higher likelihood of success in some businesses than others:
Market size: It is easier to scale up a company, if it is small player in a big market, than if if the market is small, and scaling up will quickly give you a dominant market share. That said, the way you describe your business, and then run it, can play a role in how big a market you will have for your products. In my posts on valuing Uber, for instance, I noted that describing it as a logistics company (car service, moving, delivery) rather than just a car service company could triple its potential market.
Market growth: It is also easier to scale up a company if the overall market that it is targeting is also growing, since growth does not require going after competitors' customers. A smartphone company (Apple or Samsung, for instance) in 2010 had a growing market to work with, as customers switched from flip phones and smartphones made inroads into large emerging markets. In 2026, that advantage had largely dissipated, as the smartphone market has matured.
Industry Structure: There is a natural structure to industries, driven by economics and business type, with some industries splintered across many players, and some concentrated in a few big players or even in a winner-take-all. You can scale up more in the latter, but you will have to confront the odds favoring you being one of the winners in the industry.
Capital intensity: It is easier to scale up a business that does not require large capital investments to be able to generate more in revenues. Using Uber as an example again, scaling up was made easier in the early years, since it did not own the cars or hire the drivers that comprised its car service, and growth came quickly and with little added investment.
Customer inertia: Businesses can grow faster and get bigger if there is less inertia among customers and more willingness to try out new products or services. At the risk of generalizing, this may explain why scaling up can happen more quickly in younger industries (like technology) than in older ones (health care, education).
Key person(s): There are some businesses that are built around the specific skill sets of a person (usually a founder or business owner) and these skill sets are not easily transferred or taught to others. A master craftsperson, say a furniture-maker, will have a more difficult time scaling up that business, because without being able to pass his skills on to his or her apprentices (which can take time and require intense oversight), he or she is constrained in how much new business he can take on. If that craftsperson has a recognizable name, it is possible that you could build a scalable franchise model, as has been tried by some master chefs (Wolfgang Puck, Gordon Ramsey etc.)
The graph below captures the scaling choices that companies make as a function of these factors:
As you can see, some businesses can scale up quickly, some take more time to scale up and some never scale up, and the businesses that scale up quickly often scale down just as fast. Thus, the decision of whether to scale and how quickly to do so is as much driven by the nature of the business (capital intensity, industry structure, competition) and the characteristics of the market that it is targeting (size and growth, customer inertia).
Business Building
While having access to a big, growing market can allow you to scale up more quickly, your capacity to generate profits and build a business will ultimately come from other forces:
Unit economics: Unit economics measures the profitability of the marginal unit sold by a business, and is thus determined by the price charged for that unit and what it costs the business to produce that unit. Businesses like software, where the marginal unit costs very little to produce and can still be priced highly, have superior unit economics and will find it easier to convert growing revenues into profits, since much of the increase in revenue will flow into profits. Conversely, businesses like electric cars, where each additional car sold costs money to make, will struggle to convert scaled up revenues to profits.
Economies of scale: Businesses with large fixed costs, whether they be associated with maintaining platforms and infrastructure, or sales and marketing, face obstacles to profitability. While growing can provide scaling benefits, that works only if the fixed costs don't grow with revenues and if they are not so onerous, that you still have losses after scaling up.
Competition: & Competitive Edges (moats): Large and growing markets provide businesses with opportunities to grow, but for that growth to translate into sustainable profits, these businesses will need pricing power and that power comes from barriers to entry that keeps new entrants out and gives existing players advantages.
It is true that the operating choices that businesses make play out on both the scaling and profit dimensions, sometimes pitting them against each other. A decision to lower product prices may increase revenues at the expense of unit economic profits, and a decision to spend more on advertising and promotion may expand markets, but the higher marketing costs will impose a drag on profitability.
One way to illustrate the combination of forces that go into business building is to to go back to basics, and to look at what lies under each one:
As you can see, scaling up is not a mantra that automatically translates in profitability, and the pathway to profits will be determined by variables that are often out of the control of a business.
Scale & Profitability Mixes
With the multitude of factors determining both scaling potential and business model viability, it should come as no surprise that the outcomes that we observe can range the spectrum, starting with extraordinary companies that scale up quickly, while delivering huge profits, to companies that never scale up, either by choice or because they could not, and some of which never make money.
Lightning in a Bottle: Are scaling and profitability mutually exclusive? Put differently, can a company scale up, while delivering profits and perhaps positive cash flows as it grows? The answer is yes, but it does require a fairly unusual combination of circumstances - a big and growing market, being an early entrant into the market with few competitors, low capital intensity and excellent unit economics. There are a few companies that meet these conditions, and we will call them "Lightning in a Bottle" firms, partly because they are rare, and partly because success can come from being at the right place at the right time. Google and Facebook, in their early years, were good examples, with revenues growing exponentially and profitability in place.
Field of Dreams (Shoeless Joe Jackson version): As a baseball fan, I have always had a soft spot for the movie, Field of Dreams, where a farmer (Kevin Costner) builds a baseball field in the cornfields, and when asked why, responds with "if you build it, they will come". There are companies that seem to be built around this motto, where scaling up comes first, often accompanied by large losses, but with the promise that "if they build (revenues), they (the profits) will come. During Amazon's first decade and a half of existence, I described their business model as a Field of Dreams model, and gave credit for Jeff Bezos for being steadfast in not only telling this story, but also acting consistently with it, and carrying investors along. (If you are wondering what Shoeless Joe is doing in this story, I am afraid you have to watch the movie all the way to the end.)
Field of Nightmares: Amazon was not the first successful Field of Dreams company, but as one of its highest profile winners, it gave rise to a legion of young companies, all labeling themselves the "next Amazon". Needless to say, Amazon's success came from being a disruptor of a huge business (retail), which had atrophied and weakened over time, and many of the Amazon wannabes that tried to imitate it managed to do so on the growth dimension, with immense amounts of capital invested in scaling up, but never turned the corner on profitability, partly because they had neither the unit economics nor the economies of scale to pull it off.
Niche Star: Scaling is not always the optimal choice, and there are some companies that recognize this reality early, choosing to stay small and focusing on a portion of the market where they have decided advantages. To that extent that they can convert those advantages into premium pricing and niche market dominance, they can have values that are disproportionately large relative to their operating metrics, i.e., trade at high multiples of revenues and earnings. Ferrari, for instance, sells only a few thousand cars every year, but with an operating profit margin in excess of 20%, it trades at a market capitalization comparable to that of auto companies that sell hundreds of thousands of cars each year.
Big and Broken: It is no secret that there are some businesses that start with business models with a fatal flaw, i.e,, a broken business model, and rather than being shut down, they are fed increasing amounts of capital and allowed to scale up. A real-estate based business that leases properties long term, and then sub-leases them short term, has a duration mismatch born in hell, and expanding it geographically and allowing it to lease hundreds of properties, as WeWork did, just makes it a really big, bad business. If you are puzzled as to why investors would supply capital to these businesses, you may want to read on.
Small winner & Small losers: If you look at all businesses, private and public, most remain small, some due to business and industry structure and some because of owner constraints on capital and control. These small businesses, though, over time, bifurcate into good small businesses, earning more than their cost of capital and delivering value, and bad ones, earning less than the cost of capital, but still worth more as going concerns, than liquidated.
Cut your losses: Finally, there are businesses that start up with dreams aplenty, and over time discover that they can neither scale up, nor make money. In the absence of capital infusions, these businesses fail early, but if capital providers keep funneling resources into these companies, they still fail, but do so later and with a much higher price tag.
In the matrix below, with scaling on one axis and profitability on the other, I plot all eight of my scale/profit combinations:
Any investor or founder who blindly follows the pathway of scaling first and profiting later for every business is using a cookbook approach to business building, and runs the risk of making small failures into big ones.
The Tradeoff between Scaling and Profitability: Determinants
As you review the factors that govern the trade off between scaling and profitability, it is clear that the right choice (on how much to scale) will depend on the firm, and that not every small firm is destined to become or be more valuable as a larger firm, and that not all large firms have the same profitability characteristics, once scaled up. That said, is it possible for firms to adopt scaling pathways that look, at least from a business standpoint, to be suboptimal? Of course! There are small firms that have viable pathways to scaling up that choose to stay small, and at the same time, there are small firms that are designed to be small, niche businesses embark on scaling that is value destructive, and the reasons are a mix of human frailties on the part of founders, system constraints (from governments and regulators), access to capital (too little or too much) and exit options (sell, liquidate or go public).
1. Founder Characteristics
The founder or founders of a business not only play a key role in guiding the business through its early days, when most start-ups fail, but they also make key choices that can determine in its end game. In making these choices, they may be guided by the fundamentals we outlined in the last section, that affect scalability, but they are also a function of their personal make-up, on at least a couple of dimensions:
Control versus Ambition: There is a natural tension between wanting to control the levers of decision-making in a business and scaling that business, since the latter almost always requires raising capital from providers who will either constrain your choices (if borrowed money is used) or demand a share of ownership rights (if equity). With the latter, founders will find their control diluted over time, and with enough scaling up, it is possible that founders end up with less than controlling stakes. For some founders, that fear of dilution and losing power over their business creations runs deep enough to stop them from embarking on growth plans, even though these plans make economic and financial sense.The flip side of control is ambition, and for some founders, the desire to build big businesses that are not restricted geographically or in product offerings can drive the decision to scale up, even though the fundamentals may not support that expansion. This works only if they can convince investors that their ambitions In fact, this tension between a founder’s need to be in control and that same founder’s desire to build big plays out in what Noam Wasserman called the Founder’s Dilemma, where to make a business bigger, its founder has to step down or at least compromise on control.
Longevity versus Scale: There is an argument to be made that if your intent as a founder is to build a business that is long-lived, your odds of success improve if you keep your business smaller and more focused on what it does well. While there are many exceptions to this generalized rule, it is worth noting that some of the longest lived firms in the world are family owned small businesses, that serve a niche market, and are passed down generation to generation in the same family. It is also true that firms that see a sudden surge in revenues, usually as the result of an external factors or happenstance, often live to regret their good fortune, as they scale up overnight. In the aftermath of the Covid shutdown, for instance, firms like Moderna and Peloton boomed, but they also overreached, and did long-term damage to their business models.
In summary, the choice between scaling and profitability will play out differently across businesses, depending upon what founders value most, thought it is healthy for an economy to a have a mix of founders, since it creates a mix of businesses.
II. Access to capital
It is true that businesses need access to capital, to varying degrees, to scale up, and the easier it is to raise that capital, the easier it is to make a business bigger. Capital can come from different sources, ranging from family wealth to venture capital to public equity, with each one carrying its pluses and minuses.
Family (or friend) wealth: Every business, through human history, having lived through its early days (when failure risk is high and its products and services are still untested) has faced a choice of whether to stay small, serving a market that it knows and understands, or whether to get bigger, going after a bigger market. For much of that history, though, with businesses funded with family funds and access to capital was limited, most businesses chose the first path and remained small businesses, focusing on building business models that delivered profits, with wide differences in success rates. For a few, owned by wealthier families, access to a much larger pool of capital (from family savings and bankers willing to lend to these families) created family groups that dominated economies, and continue to do so in some parts of the world.
Venture capital: The growth of public equity markets in the late 1800s and much of the last century did little to change the family control dynamic, since investors in those markets were primarily interested in funding larger companies with established business models. Recognizing this gap between capital need and capital access at younger businesses, and the opportunities that the gap presented, allowed for the rise of venture capital in the 1950s, primarily in the United States. These venture capitalists provided seed capital for start-ups, using winners to cover their failures, and got the bulk of their winnings when they exited these investments, either by going public or selling to another entity. Over the last few decades, venture capital has grown, and in the last 12 years, that growth has not let up:
Source: NCVA 2026 Yearbook
In this century, venture capital has also become more global, growing in Asia and Europe, but it is still true that it is easier for a small business to raise capital to scale up in the United States than it is in much of the rest of the world.
Public equity: There are some growth businesses that bypass venture capital and go after public equity, a much bigger pool of capital and one that may give founders better terms. In some cases, this access to capital might be enabled by going public, even with unformed business models and little to show in terms of existing operations (revenues or earnings), but in most others, it takes the form of capital invested by larger, more mature public companies in return for a share of ownership. These investments may be labeled as strategic, but the motives for making these investments vary across companies. Some invest to get access to a promising technology or product. some to pre-empt competitors and some for the same reason that venture capitalists do.
The bottom line is that businesses that seek out capital, whether from family, venture capital or public equity, have to accept that the capital providers will demand and usually get a say in business decisions, and the more capital you seek, the more sway they will have.
III. Investor Preferences
Businesses get their cues on whether to scale up or build business models from the investors who fund them, and much as founders want to map their own path, investor preferences matter, as do their end games. Put simply, a family that invests in a business with no plans for exit will choose a very different path for that business than a VC that invests in the same business with the intent of exiting that investment by selling it to another investor or company, or taking it public.
Venture capitalists are often viewed as the sherpas who guided young businesses to success, both operationally and in markets, the mythology about venture capitalists and what they do has also built up. Since that mythology extends to almost every aspect of venture capitalist activity, perhaps the best way to dispel myths and bring in reality checks is to look at what venture capitalists are "assumed" to do in each phase, and contrast it with what they actually do:
If you are reading this as a critique of venture capitalists, you are misreading it. My intent is not to paint a picture of venture capitalists as lazy and greedy, but to bring home the reality that given how venture capitalists invest, act and are judged, it is unrealistic to expect them to do the heavy lifting of building businesses for the long term and to even make business sense, when they talk about companies.
There are two parts of the venture capital rulebook that you should focus on, to understand why many VCs prioritize scale over profitability. The first is that they price companies, rather than value them, and in a post from a few years ago, I made the argument in more depth. VC pricing based on what other venture capitalists are paying for similar businesses, often scaled to simplistic metrics, users and subscribers for pre-revenue companies and forward revenues or earnings in what passes for VC valuation:
The second is that VC success is measured based on price at entry and price at exit on an investment, rather than the quality of the business built, and using that metric, the median venture capitalist has not been much better at harvesting alpha than the median mutual fund manager or PE investor:
Source: Cambridge Associates
There are, of course, standouts in each of these categories, fund managers who have delivered well above the market, but in mutual funds and to an increasing extent, hedge funds, that success is fleeting. There are two aspects on delivering returns where venture capital stands out, relative to other active investing classes.
The first is that failure, always a concern in investing, is much more a part and parcel of investing in venture capital than in other investing grouping. Put simply, not only are there more VC funds that go out of existence every year, but even the most successful VC funds lose on many or even most of the investments that they make, especially in angel financing deals.
The second is that venture capital investing, when it works, can generate outsized returns on winners that (hopefully) cover the cost of failures.
You can see both of these at play in the graph below, which looks at returns that VCs book when they exit investments:
Source: CF Private Equity, from Pitchbook data
As you can see, across all the time periods, it is the top 10% of VC investments that deliver the bulk of returns to VC investors, and over time, that concentration has increased: in the 2023-2026 period, 80% of all returns to VC investors came from their top 1% of investments. The combination of these two forces (losses on most investments and outsized winners), i.e., the power law in venture capital, has two consequences. The first is that only about a quarter of venture capitalists in each year deliver above-average returns, making the average VC returns in the table above more palatable. The second is that success in venture capital, unlike in other areas of active investing (including mutual funds, hedge funds and even private equity), has been more enduring. The power law characteristic also feeds into VC incentives, leading venture capitalists to direct their capital more into chasing the biggest winners than in building businesses. In fact, the more top-heavy VC returns become, i.e., dependent on big payoffs, the more pressure venture capitalists feel (and pass on to their portfolio companies) to find the next big winner, pushing the ecosystem dangerously close to gambling.
A Changing Game
With the discussion of the scale versus profitability at the business level leading in, and the assessment of the incentives of capital providers following, I think that we are well positioned to examine how changes in public and private markets have increased business incentives to scale, as opposed to building business models. There are two developments, in particular, that have taken the tilt towards scaling in venture capital and made it even more pronounced - the entry of public equity into the funding of private businesses and the fading of reversal, as an antidote to momentum, in public markets.
The Gray Market Effect
For much of the last half of the last century, after venture capital established a presence in the United States, it remained the only or primary source of capital for young firms. That has changed especially int the last decade, as public equity investors have increased their investments in young, private businesses, supplementing venture capital in some and even displacing it in others. An early measure of this trend is captured in the charts below:
While this graph looks at only the number of mutual funds investing in private businesses, and stops in 2016, there was a corresponding surge in capital invested by mutual funds in young, growth companies, with T.Rowe Price and Fidelity investing billions in high profile tech companies like Uber. They were joined by sovereign funds, who invested heavily in these companies either directly or indirectly, through stakes in entities like Softbank's Vision fund.
We can debate the reasons for why we saw this surge, with fear over missing out (FOMO) and wanting to partake in tech playing roles, but whatever the reasons, capital access surged for young companies, especially in tech, during the period. In effect, rather than two mostly separated markets - one for young, smaller, private business dominated by VCS and one for larger companies more advanced in the life cycle, where public equity suppled the funds, a gray market was created where VC and public equity fund access allowed private businesses to stay private for longer.
Public Markets: Momentum, Fundamentals and Reversals
Public equity markets have always been momentum-driven, allowing traders who ride that momentum to prosperity, before bringing them down when the momentum shifts. At the same time, fundamentals act as an anchor, operating as a counter to momentum, leading to reversals and allowing investors to hold their own over time. While the congruence is not always perfect, scaling feeds into momentum and profitability is the most critical fundamental, and in markets with balance, when one gets out of sync, the other restores harmony.
Over the history of stock markets, value investors have often claimed dominance, and pointed to the returns you could have earned by buying companies that look cheap on a value basis (low price earnings or low price to book) and waiting for price reversals. Traders push back by noting that over the same history, momentum has had a decisive effect on returns, especially over shorter time intervals. While the momentum effect shows up across the decades, there is evidence that the reversal effect has weakened over time, leaving investors who bet on mean reversion and a return to fundamentals in the lurch:
Source: Ken French's datasets
The reasons given for this shift vary, and are often reflective of the biases of the investors giving the reasons.
The Fed did it: For those who view central banks as all-powerful, and believe that the low interest rates of the last decade were their doing, those low rates have also become the proximate reason for market pricing behavior and reckless risk taking. Their argument is that interest rates that are close to zero induce investors to shift from bonds to stocks, and within stocks, to move from low growth, high earnings stocks to high-growth companies with little or negative earnings.
The rise of passive investing: In the battle between active investing and passive investing, with ETFs supplementing index funds, the latter has had a decisive edge in terms of returns over the last two decades, and its share of the market now stands are well above 50%. There are some who argue that the flow of funds to passive investing vehicles has contributed to the increased power of momentum, since more new funds flow to the largest market cap companies than to the smaller ones. In addition, it is argued as the number of active investing declines, there are fewer investors looking at business models and profitability, reducing the pull of fundamentals on price.
Public market composition: It is noteworthy that the reversal effect started weakening in the 1990s, a decade when young dot.com companies with unformed business models flooded the market, bypassing the more traditional route of using venture capital to grow. With these companies, where value is almost entirely driven by potential and not by operating metrics today, the catalysts needed for reversal may take longer to manifest.
Information sources and access: It is undeniable that investors and traders get information from a wider ranges of sources now than two or three decades ago, with social media and online sources supplying information that used to come from newspapers and financial news channels. In additional to being less curated and controlled, that information is also instantaneously accessible to the public, and price reactions tend to follow.
While I take issue with parts of each of these arguments, there is some truth to all of them, and they have contributed to making pushing back against momentum a more hazardous exercise for investors.
The Consequences
With larger amounts of capital being deployed by VCs at young, growth companies, substantial capital infusions from public equity funds into private capital markets, and public equity markets that are more used to and receptive to young company listings, it should not be surprising that it is changing how private companies behave. In the graph below, I look at the characteristics of companies going public in the United States, using the data that is generously made available by Jay Ritter:
Source: Jay Ritter's IPO data
There are three clear changes over time that are visible in this graph:
1. Private businesses are waiting longer before going public: As you can see, the average age of a company going public has risen over time, with the median age rising about 11 years in the last 15 years.
2. Private businesses are scaling up (revenues) more, while waiting: While private businesses wait longer to go public, they are spending that time scaling up more than they used to. The inflation-adjusted revenues at the median IPO have tripled or even quadrupled, relative to IPOs in the 1980s.
3. Private businesses are deferring building business models & profitability: The most striking feature of the data, to me, is that while private businesses are waiting longer and scaling up more before going public, they also seem to be deferring business building for much longer as well. While it was routine for companies going public in the 1980s to be profitable (>80% were), less that a quarter of the companies that have gone public in the last decade have been profitable.
While companies that are going public are bigger (in revenue terms) and less likely to be profitable, markets are attaching large market capitalizations to these newly minted companies, as you can see in this graph which zeros in on tech IPOs:
Source: Jay Ritter's IPO data
You will also notice that companies going public are issuing smaller portions of their shares to the public, at least in the initial offering, suggesting that the need for capital that drove companies to go public has become less pressing over time, perhaps because of more capital access as private businesses. While the median market cap of a company going public in the last six years has exceeded a billion, the largest IPOs command market capitalizations that would have been unimaginable a few decades ago. From Facebook, with a pricing of $104 billion, in 2012 to SpaceX, going public in June 2026 at $1.8 trillion, the trend lines are pointing upwards, especially if Anthropic and OpenAI deliver on their trillion-dollar plus pricing promise.
Implications
By itself, the trend towards private companies scaling up more, while public, and going public at eye-popping market capitalizations may be understandable and explainable, but there are implications that we need to consider both from an investing and governance standpoint.
Corporate governance: One of the reasons that private companies often delay going public is because governance requirements, from board composition to top management compensation, are more stringent at public than private businesses. While Sarbanes-Oxley, which wrote into law many of the current governance rules for public companies, is often toothless and ineffective, it still forces disclosures about governance (on conflicts of interest and board member relationships) at public companies. In addition, public market investors can pressure public companies to change governance practices or top management, if companies underperform in the market place. One of the perils of letting companies scale up more before these governance questions get raised is that the top management in these companies may have few checks on their actions. It is true that venture capitalists could operate as a disciplinary mechanism, but in an age of founder worship and where VCs can be divided and conquered, you can have companies with market pricing of a billion, hundreds of billions or even trillions run by people who are ill-suited for the task.
Delayed business model building: If the first imperative for a private business is to scale up, because scaling pushed up pricing both in private and public markets, the challenge of business building will get deferred to a later stage. The problem with scaling up first, and building a business model later, is that it may be too late, since the choices made to allow for scaling up may impede the pathway to profitability. Again, if your response is that VCs will work on fixing this problem, they have little incentive to do so, since they benefit from scaling up and exiting these businesses, before the business problems become too big to ignore.
Scaling stories: If you believe, as I do, that valuation is a bridge between stories and numbers, and that the balance between the two shifts over the life cycle, with stories dominating early in the life cycle and the numbers taking center stage in the later stages, it is understandable that VCs and founders, when marketing their companies are primarily story tellers. I don't have a problem with that, but as I noted in my last post on AI as a business, the stories that are being told for these companies are often incomplete, and almost entirely focused on the scaling question. Thus, in the Anthropic sales pitch it is the growth in the annualized revenue run rate (ARR) and the size of the AI market (huge, but with no specifics) that comprises the bulk of the story, with little or no mention of business models or profitability.
Disruption without replacement: Disruption has been a key component of the stories that underlie many of the largest companies that have gone public in this century. Accepting the premise that a healthy economy needs a shaking up of the status quo, and that disruption can lead to economic growth and better practices, it is still legitimate to look at disruption's debris. One of the perils of supplying capital in almost endless quantities to private businesses that aim to disrupt, without challenging them on business models, is that you may succeed at disrupting the status quo (driving existing players out of business) but your disruptor may not be able to build a business that can be self-sustaining in the long term.
Conclusion
I am sure that you are already aware of the core message of this post, which is that notwithstanding the current emphasis on scaling up businesses, not all businesses are meant to scale up, and that scaling up comes with challenges that founders may be ill-equipped to meet. That said, ambitious founders will feel the urge to make their businesses bigger, and if they raise capital (from venture capitalists) to make this happen, the incentives to scale up will increase, even if it makes little or no business sense to do so, with all parties hoping to exit by selling to others (public or private) who will price based on scale. While this has always been the case, changes in private and public capital markets have tilted the scale even further in favor of scaling, and it is possible that companies, both public and private, with sky-high pricing have been built on bad business models that are irredeemable.
