TheChek News Flow

The next crash: why this time might not be different

Stock markets are not only ignoring the obvious threats, but seem imbued with extreme optimism

In the autumn of 1929, Irving Fisher, one of the greatest American economists, stated: “Stock prices have reached what looks like a permanently high plateau.” This turned out to be one of the most incorrect forecasts ever made: in short order, US and global stock markets were hit by the Great Crash, which was followed by the Great Depression.

Some scholars argue that Fisher was analytically right: markets were indeed valuing the US capital stock correctly in 1929. But his “permanently” proved unambiguously mistaken. Maybe markets were in some sense “right” before the crash and wrong after it. But who cared? For investors and the hundreds of millions of people across the world whose lives were upended by the disaster, the gods of the stock market had failed for a generation.

Why might this story be relevant today? The answer is that the valuation of US stocks is even higher today than in September 1929. In only one other period since 1881 has there been a higher valuation of the US market than today’s. That was in 1999-2000, immediately before the bursting of the “dotcom” bubble. (See charts.)

We know what followed that peak: a fall in valuations that was as steep, though not as deep, as the one after 1929. The first global financial crisis after the disaster of the 1930s followed a little over six years after the bursting of the 1999 bubble, in 2007-09. This was not just a coincidence: the easy monetary — and relaxed regulatory — policies adopted after the stock market bubble burst contributed to the financial crisis.

How can one best judge the valuation of stocks? The best-known metric is the cyclically adjusted price/earnings ratio developed by Robert Shiller, the Nobel laureate and Yale economist. Cape is defined as today’s value of the stock market divided by the average of the previous 10 years of earnings per share, both in real terms. Shiller also provides a “total return Cape”, which adjusts for changes over time in the payout policies of companies. There is a difference between the two calculations, but it is not large.

The intuition underlying this measure is simple: if people are paying more than has been historically normal for the underlying earnings of companies, the stock market can be judged to be relatively highly valued, and vice versa. Data for the US market, measured in the S&P 500, goes back to 1881. Over that period, the mean Cape has been 17.8, which indicates a healthy average real return of 5.6 per cent. There have also been three huge peaks: September 1929, at 32.6, December 1999, at 44.2 and, crucially, July 2026, at 41.4.

The Cape is a simple and effective measure of value. But Shiller also offers a more sophisticated one: “the excess Cape yield”. This measures the difference between the inverted Cape ratio — or cyclically adjusted aggregate earnings per share — and inflation-adjusted yields on Treasury bonds.

When stocks are expensive, the excess yield is low. When stocks are cheap, the excess yield is high. Crucially, when the excess yield is low, the subsequent 10-year excess returns on stocks have normally been poor. The excess yield is a mere 1.4 per cent in July 2026, far below its long-run average of 4.7 per cent. With stocks this expensive, the chances of healthy future returns must, again, be relatively low.

How does today’s US situation compare with those of comparable markets elsewhere? One way of addressing this question is to examine the ratio of the total value of the stock market to GDP, also known as the “Buffett indicator” (after Warren Buffett). At over 200 per cent in the US in early 2026, this was extraordinarily high by US historical standards and more than double UK levels.

High valuations of US shares add to the size and relative dynamism of the overall US economy and so of its corporate sector to make its stock market far and away the world’s most important: in June 2026, it accounted for 55 per cent of the global value of stock markets (at current prices). The US market is a titan.

Historically, when US valuations have come close to this sort of level, a crash has followed. Stocks almost always fall much more quickly than they rise. Will things be different this time?

We do know that the Cape is far from a perfect predictor of an imminent crash: if it were, it would not be; well-informed investors would then not allow markets to reach extreme positions in the first place and so crashes would be far less likely.

This time, boosters always say, is different. One justification for such optimism is the scale of the AI-related boom. Its impact includes expectations of huge profits for the “hyperscalers” (Amazon, Google, Meta, Microsoft and SpaceX) and also the suppliers of microprocessors (notably Nvidia) and memory chips. Although not yet floated, OpenAI and Anthropic are also expected to be highly rewarding, even at eye-popping valuations.

As the most recent annual economic report of the Bank for International Settlements notes, these buoyant expectations are fuelling an enormous surge in US investment, which itself raises economic optimism.

The view that artificial intelligence is a transformative technology is quite reasonable. But the history of investment surges underpinned by profound innovations does not show that the latter guarantee huge profits.

Over-investment, destructive competition, waves of bankruptcies and then painful consolidation are standard features of such episodes, from the railway booms of the 19th century to the internet boom of the 1990s. This is the classic capitalist story of booms and busts.

This matters very much for the future of today’s markets. As Chris Watling, chief executive at Longview Economics, noted in June, “a handful of AI-linked stocks accounts for roughly 40 per cent of the S&P 500’s market capitalisation, according to Bank of America data”. Thus, the current extraordinary valuations of the market depend on the continuation of the AI boom.

Given the scale of what is happening, the latter, in turn, depends on the materialisation of one (or both) of two hoped-for outcomes — faster productivity growth and/or a big shift in income from labour to capital. Neither is guaranteed. But if the former happened, real interest rates would rise, lowering the present value of the higher future earnings. If the latter happened, it would tend to create political and social upheaval — hardly the ideal environment for peaceful enjoyment of enhanced earnings.

Without such huge transformations in economic growth and the distribution of income, today’s Cape suggests prospective real returns of a mere 2.4 per cent, less than half the historic average. At some point people will realise this, and the market will crash.

One argument against such a pessimistic conclusion is that the US market has been more expensive on average since, say, 1960 than it was in the previous 80 years, perhaps because both economic management and access to index funds have improved. Thus, since 1960, Cape has averaged 21.7. This is indeed above the average of 17.8 since 1880. But that is still just about half of what it is today.

Current valuations look to be a huge stretch. Moreover, as Joachim Klement, a strategist at Panmure Liberum, wrote in the FT, not just the valuations but even the earnings themselves look to be in a bubble.

Nobody knows for certain what might trigger the corrections. But we can see plenty of opportunities for destabilising shocks in which a stock market plunge is just one part of a bigger story.

First, we have definitively lost the stabilising and benevolent US hegemon of old. Under today’s irrational and unpredictable management, anything is possible. The on-again-off-again war on Iran is the perfect example. The unpredictable trade war is another. Uncertainty has costs. Moreover, for the first time since its emergence as a superpower in the early 20th century, the US has, in China, a peer competitor.

Second, the ratio of public debt to GDP in the advanced economies is back to where it was at the end of the second world war, even though there has been no war, but a financial crisis, a pandemic and fiscal profligacy, notably that of Donald Trump, instead. According to the IMF, the US now has general government fiscal deficits of over 7 per cent of GDP. The public debt of emerging economies, though lower than that of advanced economies, is also at an all-time high.

Private debt is also worrying. Data from the Institute of International Finance shows private gross indebtedness is close to where it was on the eve of the global financial crisis. Worse, there is procyclical financial deregulation, which is precisely what tends to occur some decades after the crisis that justified the earlier tightening. This inevitably exacerbates the perils of periods of “irrational exuberance” such as today’s.

Third, high and rising debt generates financial fragility. The BIS report focuses rightly on the interaction of the rising government debt with the increasing role of hedge funds in funding that debt. The strategy of the latter depends on leverage. That increases the risks of a panic in which trades unwind at high speed. We have already seen such disruptions early in the pandemic and again in the UK’s “Truss shock” of September 2022.

Yet this is far from the only form of financial fragility. Another is the lack of transparency created by the growing role of non-bank financial intermediation, especially in the US. Another, again, is the rapid pace of financial innovation, notably the rising role of weakly regulated stablecoins. Would these be as reliable as money needs to be in a crisis? If not, flight could heap panic on panic.

Fourth, the underpinnings of dynamic market economies — the rule of law, support for science, orderly government — are under attack, notably in the US. This links with the disarray of global economic governance, notably the trading system on which our economies continue to depend.

Finally, as Manoj Pradhan and Charles Goodhart argue in The Unanchored Central Banker, the combination of de-globalisation with ageing will, in the longer term, generate still higher interest rates and rising fiscal pressures. As a result, they argue that central banks will lose their ability to “anchor” inflationary expectations.

My best guess on what might trigger the correction? Fiscal pressures, higher long-term interest rates, forced monetisation, inflation, financial shocks and panics. But war and accelerated de-globalisation are also possibilities.

The markets, above all US markets, are not only ignoring all such threats, but also embracing a highly optimistic view of the prospects even of what is going well. Stocks are, as a result, extremely expensive.

So, what are investors to do? This depends, as always, on both their time horizons and capacity for bearing losses. If the former are long and the latter are large, they can stay fully invested. Those without the luxury of time or robust financial security need to hedge. Options are a possibility; cash (and not just dollars) and precious metals are others. In today’s world, remember the downside risks.

Findings raise questions over the quality of the FCA’s information

New regulatory data released this week on short sellers’ bets against UK-listed companies contained several apparent errors, raising questions over the quality of the information being provided to the market under the new disclosure regime.

The Financial Conduct Authority published the data after new rules ended the practice of publicly naming hedge funds and investors holding significant short positions — bets that a company’s share price will fall. Instead, the regulator will now disclose the total short positions in a company on an aggregate basis.

But the new information published by the FCA contained several apparent errors, with positions subsequently removed or changed without a record, according to an analysis by data provider Breakout Point that was reviewed and confirmed by the FT.

The data also included years-old positions which are highly unlikely to still exist.

The findings raise questions over the quality of the FCA’s data, which is based on private submissions by investors about their short positions and is an important source of information for traders and regulators.

“The information that flows into the FCA is essential for market oversight and to identify misconduct,” said Chris Brennan, partner at law firm Dentons. “Market users have a reasonable expectation that what they see published is correct.”

Short positions against FTSE 250 IT infrastructure company Softcat were disclosed in an FCA report on Monday but were not included in an updated report on Tuesday. However, the change was not noted in a section setting out historic positions that have since been closed.

Tuesday’s report also listed different dates and sizes for short positions in four companies, including student accommodation provider Unite, without noting that these details differed from the information published on Monday.

One of the adjustments was made because a short seller’s position had been duplicated in the data, said a person familiar with the matter.

“Early-days issues are perhaps forgivable and things are already improving, but invisible corrections in an official market record should not become a habit,” said Ivan Cosovic, founder of Breakout Point.

The regulator’s reports on Monday and Tuesday contained other errors, with one of the documents being wrongly dated. They also appeared to omit some short positions which had been disclosed as active in the final report under the old disclosure regime, including shorts held by Saba Capital and Lombard Odier Asset Management.

Those positions had been disclosed as active last Friday but a person familiar with the matter said these positions had not been carried over in the latest disclosures as they were historic.

However, the regulator did publish details of some short bets that are more than five years old and are therefore unlikely to still be active or to be the same size as when they were previously disclosed.

For example, a short position in miner Critical Mineral Resources disclosed in April 2021 appeared to have been included on an anonymised basis in the FCA’s new report despite the company suffering an 87 per cent fall in its share price since the bet was first made public. Short sellers normally close their positions to secure a profit after a company’s share price drops sharply.

It is not known whether the potential errors were introduced by the FCA or stemmed from inaccuracies in data submitted to it by investors.

The FCA said it had considered the examples of potential errors raised by the Breakout Point analysis and concluded “there is no need for any revisions [to the data] at this point”.

It added: “The FCA monitors reported positions and engages with position holders where necessary to verify information and maintain the accuracy of published disclosures. We are also monitoring how the regime is operating and will consider whether changes are necessary.”

A person close to the FCA noted that its reports rely on the timeliness and accuracy of the information provided to it, and that it approaches firms to understand whether older reported positions remain valid.

The FCA has long published daily reports on hedge funds’ and asset managers’ short positions in UK companies.

Under the new rules, the regulator reports the total short interest in each company but it no longer discloses the size of each investor’s individual position or their identities.

The FCA will make a public disclosure when aggregate short interests exceed 0.2 per cent of a company’s share capital. It previously only published details of short positions of more than 0.5 per cent.

The spot rate for a 40-foot container from Shanghai to Los Angeles rose to $6,482 last week, the highest since 2024.

This marks the 10th consecutive weekly increase.

Spot rates for this route have nearly TRIPLED since the Iran War began in February.

Still, the Port of Los Angeles processed more than 530,500 loaded inbound containers in June, up +13% YoY, the highest volume in any June on record.

The surge has been driven by importers rushing goods into the US ahead of the expiration of temporary tariffs on July 24th and expected new import taxes, while the Iran War continues to disrupt shipping patterns.

Supply chain stress is surging again.

In the age of intelligence, how should firms protect their core IP?

Nobel Prize winning economist Kenneth Arrow famously described a paradox in the market for information. “Its value for the purchaser is not known until he has the information, but then he has in effect acquired it without cost.” In Arrow’s “Information Paradox,” the seller risks giving away knowledge in order to sell it.

AI creates the reverse problem. In the AI age, the buyer risks giving away knowledge, just in order to use what they bought.

You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more of that knowledge you have to feed it!

Over time, the information asymmetry becomes increasingly skewed. The seller learns more and more about you as you use what you purchased, while you learn very little about what the seller is learning in return.

That is what I think of as the Reverse Information Paradox.

Patents solve one aspect of Arrow’s paradox. They let an inventor disclose an idea without simply giving it away. The Reverse Information Paradox needs its own equivalent.

This requires more than data protection. Models learn from "exhaust," the prompts people write, the tools agents use, and especially the corrections people make when the model is wrong. Every correction is distilled into institutional know-how. It's the kind of knowledge a competitor could never buy, and the kind that leaks almost imperceptibly: trace by trace, correction by correction, eval by eval.

In consuming intelligence, you are creating intelligence. And what you create should belong to you. This is your particular intelligence, in Hayek's sense: the knowledge of time, place, and circumstance that no one else can hold. It knows what you think, what you value, and how you measure success.

While the great innovation that comes from model providers having fair use rights to train models on public data is needed, I find it ironic that the status quo is to then turn around and impose restrictive terms on distillation, and to reserve the right to learn from customer usage and interaction data. If learning flows in only one direction, economic value converges toward the owners of the learning infrastructure rather than the creators of the knowledge itself. Therefore, it's imperative that we distribute the learning infrastructure to every firm so that they can control their own learning loop.

As Alex Karp put it: "What the technical customers want is control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it's not being transferred to someone else." The current regime does precisely the transfer Karp and companies fear.

That is why enterprises need a real trust boundary for their human capital and token capital to compound. It is where an organization’s data, traces, evals, adapted weights, and memory accumulate and improve together. And it is a hard boundary across which nothing crosses, not even the intelligence exhaust, without consent. Enterprises will demand the rights to use model outputs to fine tune and/or train their own models. I think of this as every firm’s right to align models to their enterprise accountability obligations.

In the cloud era, enterprises accumulated data. In the AI era, they accumulate learning. The trust boundary must evolve accordingly, from protecting information to protecting the mechanisms through which organizations learn, adapt, and compound intelligence. There are a few things every enterprise must do to ensure this:

Control: Create your private evals, because evals define what “good” looks like inside the organization. Also, retain ownership of your organization’s memory, traces, feedbacks, decisions, and institutional context, and ability to use outputs of models from your own tasks and queries.

Capability: Build your own proprietary learning environments within the tenant boundary to train or tune models, where models learn against real workflows without exposing the company’s knowledge.

Choice: Ensure the orchestration layer is decoupled from any single model. Ask yourself: If any one model you are using is taken away, do you still have the ability to operate and optimize for your evals using other models? Does your company “veteran” capability remain with you even if a given “generalist” model is taken away?

Cost: By decoupling the orchestration layer, you are also able to bring together context, models, and tasks in the most efficient and cost-effective way without sacrificing quality.

Compound: Bring these four together and you create your own continuous learning loop (i.e. hill climbing machine) that will allow your AI investments to compound the value of your firm.

In other words, a company should be able to use a model without giving up the knowledge that makes it unique. That is the reverse information paradox we need to confront.

Frost Investment Advisors isn’t a household name like fellow bond fund managers Pimco or BlackRock. But perhaps it should be.

The firm’s $4.2 billion Frost Total Return Bond fund has completely dominated its Morningstar intermediate core-plus bond fund category over the past three, five, 10, and 15 years, beating over 95% of its peers in each period. In a weak time for bonds overall, the fund has delivered a 6% three-year annualized return and 3.1% over five years. By comparison, the average fund in the group has produced a measly 0.3% annualized return over the past five years, and the $398 billion Vanguard Total Bond Market Index exchange-traded fund has notched an even worse minus 0.1%.

The key to the Frost fund’s success has been lead manager Jeffery Elswick’s astute application of a flexible strategy. “If our view is that the bond market is going to deliver negative returns over the next 12 months, we give ourselves large latitude to minimize that downside in whatever way we can,” he says.

Elswick’s 12-month outlook on interest rates and the economy affects how much duration risk—a measure of bond interest-rate sensitivity—he will take, as well as the kinds of bonds he will own. Although the fund can hold any U.S. bond, he limits its exposure to high-yield bonds with low credit qualities to no more than 25% of the portfolio, since junk bonds increase a fund’s correlation with the stock market. As of March 31, the fund was only 4.9% invested in high-yield bonds, as Elswick doesn’t find their yields justify the additional credit risks.

The 2022 bond downturn and the 2023 recovery show the advantages of such flexibility. At the start of 2022, the U.S. Treasury market was poor from a risk/reward perspective because of low rates, Elswick says. He shortened the duration of his portfolio to a range between 2.5 to three years while that of the typical fund in his category was five to six years. Bond prices move inversely to interest rates, and the longer a bond’s duration, the more sensitive it is to rate moves. As inflation and rates spiked in 2022, the average core-plus bond fund fell 13.3%. Frost fell only 5.5%.

“I describe 2022 to our clients as our best year in 20 years and our worst year in 20 years,” because the fund isn’t supposed to lose money, Elswick says. Yet in 2023 the fund also outperformed its peers and benchmark, rising 8.4% because of astute individual security selection and the manager having increased the duration to four years.

Currently, the fund’s duration is 5.4 years, which, “versus the prior 10 years, is on the very high end and much closer to our benchmark duration,” Elswick says, referring to the Bloomberg U.S. Aggregate Bond Index. “We’re of the view that the U.S. economy is slowly normalizing and that money-market rates are not going to change appreciably over the course of the next year.” He expects the yield on the 10-year Treasury note will largely be range-bound between 4.4% and 4.6%.

Although the Iran war is a continuing concern vis a vis inflation, which drives interest rates, oil and other commodities “are actually lower than where they were a couple of months ago,” he says. “Also, U.S. tariffs on trade peaked around October of last year, and that is a tailwind for lower inflation.” For this reason, Elswick expects the Federal Reserve either not to change interest rates in the next year or to make one small cut by year-end.

In such a range-bound environment, Elswick wants to collect the coupon yield on high-quality bonds. But instead of Treasuries, he’s favoring higher-yielding securitized debt, primarily mortgage-backed bonds guaranteed by government agencies such as Ginnie Mae. A stable-rate environment is good for mortgage bonds as declining rates lead to more homeowners prepaying their mortgages and refinancing them with newer ones at lower rates—good for homeowners but less so for investors. Meanwhile, higher rates hurt all fixed-rate bonds.

Currently, 53% of the fund is in securitized debt, versus 34% for the average fund in its category and only 21% for the Vanguard index fund, according to Morningstar. The highest-quality agency debt yields about 1.2 percentage points above comparable Treasuries.

Elswick will also hunt for value in lower-quality corporate debt—recently 17% of his portfolio. He holds beleaguered aircraft-maker Boeing’s bonds, for example, which mature in 2064 and have a coupon rate of 7.1%. But Elswick purchased the issue at a significant discount to its face value, so it yields even more.

“We’re always searching for ideas that a lot of folks just don’t want to touch,” he says. “Boeing is the perfect example of that. We started to add to Boeing when they were having problems with their new Dreamliner [aircraft]. The market really beat the name up more than what we thought was justified.”

He also recently purchased bonds from software company Oracle, which has suffered from leveraging up its balance sheet to build data centers. S&P Global gives Oracle bonds a BBB- rating —investment-grade, but only one notch above junk bonds. Yet the bonds have been trading at a discount, with higher yields equivalent to BB-rated credits.

“This is still one of the premier companies in its industry,” he says. “The management team has said pretty firmly that they want to continue to keep the company at investment-grade-rated levels.”

The fund generally doesn’t invest in derivatives, such as swaps or index futures, which larger competitors like Pimco do for liquidity purposes. Elswick doesn’t like the leverage and counterparty risks derivatives add. “If we were running a trillion dollars like a Pimco, we almost certainly would have to do something different,” he notes.

Instead, Elswick employs a team of 10 analysts and traders to scour the market for individual bonds. For this, the fund charges a 0.71% expense ratio, which is higher than the Vanguard ETF’s 0.03%. If you have a Charles Schwab account, you can buy the institutional share class, FIJEX, which has a more attractive 0.46% fee, for a $1 minimum. Elswick also says a low-fee ETF share class of the fund may be forthcoming.

Maybe that will attract more investors’ attention.

Investors typically look to emerging markets for diversification from their U.S. holdings. But these days, holding the most popular emerging market investments amounts to doubling down on the artificial-intelligence themes driving U.S. markets.

The Magnificent Seven have nothing on emerging markets’ semiconductor trio. Taiwan Semiconductor, Samsung Electronics, and SK Hynix account for 30% of the MSCI Emerging Markets index, which is up 22% this year—double the gain of the S&P 500.

The broad emerging markets index is an even bigger bet on the wider tech scene, with information technology accounting for half the allocation. There’s also country concentration: Some 70% of the index is invested in China, Korea, and Taiwan.

Investors looking for diversification in the event AI doesn’t live up to its promises can find hedges within emerging markets, but they need to go beyond the index.

While Rory Green, head of China research at TS Lombard, sees emerging markets as well positioned for geopolitical and technology trends and likes their growth potential over the longer term, he warns that the backdrop for the rest of the year is trickier, given the run-up in South Korea’s and Taiwan’s stock markets and the strong growth coming out of the U.S.

South Korea is especially vulnerable, due to leveraged exchange-traded funds and a retail investor base that has been driving up to 60% of the market’s moves—an uncomfortably high level, says Charles de Boissezon, global head of equity strategy at Société Générale.

Another risk: Some Chinese chip makers are going public soon, with ChangXin Memory Technologies beginning to take orders for what is expected to be a $4 billion-plus offering on China’s domestic Shanghai Stock Exchange. Their debuts could poke holes in the idea of a memory shortage, a theme that has driven South Korean stocks higher, Green says.

As fund managers trim some of their tech winners, many are taking a closer look at laggards. Young Jae Lee, an emerging markets fund manager at Pictet, sees the 30% of the index outside of Taiwan, South Korea, or China as more representative of the diversification opportunity that has drawn investors to emerging markets. Countries like Brazil, India, and even parts of Africa are home to growing working populations that drive increased income and consumption.

A burgeoning middle class buying cars, financial products, and other services is a good way to hedge against AI overconcentration, says Lee, who is also a co-manager on Pictet’s recently launched Emerging Markets Rising Economies ETF.

Valuations in Brazil are sitting near historic trough levels even as its banks, telecoms, and other companies churn out stable earnings and high dividend yields, Lee says. The country’s fall presidential election looms, but he sees a status quo situation if populist President Luiz Inácio Lula da Silva is re-elected.

In China, the domestic A-shares market and the CSI 300 index have outperformed the broader MSCI China index, which has fewer of the AI, industrial, and other companies getting the bulk of Beijing’s support. Any pullback in the A-shares market is likely a buying opportunity, with Green expecting Beijing to come in and buy stocks if the market falls 10% or more.

But over the next couple months, he sees a better opportunity in the lagging MSCI China index, which is dominated by internet giants and consumer-oriented companies. Valuations on internet giants and some of the country’s biggest consumer businesses are sitting near Covid-era lows. That is drawing the likes of Tom Harvey, senior equity specialist at Aberdeen Investments, who has taken some gains from AI-related stocks and put them in consumer companies—including in China, where he thinks the worst is behind these companies.

Green also sees a possible catalyst ahead: Tencent Holdings is expected to launch an AI-embedded version of its ubiquitous WeChat app—used by some one billion people—possibly appealing to investors who had dismissed such companies as too slow on AI.

AI fatigue may make what was old hot again in emerging markets. If so, looking beyond the iShares MSCI Emerging Markets ETF or the Vanguard Emerging Markets Stock Index fund, which track the broad index, may be the way to go.

SpaceX shares fell back to Earth following their blockbuster initial public offering. But Elon Musk’s rocket company is also dragging down T-Mobile US and its wireless and broadband rivals due to worries that SpaceX’s Starlink will be a formidable foe in the high-speed internet business. Those fears are overdone—and T-Mobile’s stock is now looking like a good bargain.

T-Mobile has fallen slightly since SpaceX’s IPO in mid-June and is down 8% this year, partly due to worries about competition from Starlink. Shares of Verizon Communications and AT&T, as well as cable companies Comcast and Charter Communications, have all slid since SpaceX went public. But T-Mobile has the best chance of bouncing back.

Morgan Stanley’s Sean Diffley said in a report in early July that “the perceived risk of Starlink Mobile disrupting the U.S. wireless industry is greater than the actual risk in the next one to two years.” He said the big three wireless carriers have improved their speeds and customer satisfaction rates over the past several years. He added that T-Mobile is his best idea in telecom/cable, arguing that the company “offers the fastest growth” along with the “strongest spectrum position.”

Diffley thinks concerns about SpaceX are a classic case of Wall Street overreacting. “The market is increasingly concerned that Starlink is going to make a more aggressive push in mobile,” he wrote, adding that “the fear of the unknown has led many to shoot first and ask questions later in telecom.”

BofA Securities’ Michael Funk also dismissed fears about SpaceX, writing in a recent report that “T-Mobile is least exposed to the competitive threat” from low Earth orbit internet services like Starlink. “T-Mobile wireless has 50% share of households in urban markets such as LA and NYC and only 24% share in rural markets,” he wrote, adding that a service like Starlink “seems to work best in rural and underserved environments.”

Funk has a $220 price target on T-Mobile while Diffley has a $230 price target. That actually makes them a little less bullish than many of their peers. The average price target according to FactSet is just over $251, 33% higher than T-Mobile’s current price.

That seems reasonable given the stock’s valuation. T-Mobile is trading for 14 times earnings estimates for 2026, a price-to-earnings ratio that’s barely above its five-year low of 13 and well below its five-year average forward multiple of nearly 20.

While that’s a premium to the multiples of eight and 8.5 for Verizon and AT&T, T-Mobile is worth it given that its long-term projected earnings growth rate is nearly 16% a year on average compared with long-term growth forecasts of just 7.4% for Verizon and 8.8% for AT&T.

T-Mobile even pays a decent dividend that yields 2.2%. Sure, that’s a lot lower than the yields of 5.2% for Ma Bell and 6.7% for Verizon, two income stalwarts. But T-Mobile’s dividend, in conjunction with its above average earnings growth and overdone fears about SpaceX, makes the stock, with its signature magenta logo, look pretty in pink.

An FDA hearing in late July may lead to a peptides boom. What consumers and investors need to know.

An FDA advisory panel will hold hearings in late July on whether to let compounding pharmacies produce and sell more peptides.

FDA staff scientists said in a recent report that the bulk of criteria weigh against placing the substances on a list for permitted use.

Health Secretary Robert F. Kennedy Jr. supports regulating more peptide production to shift demand away from the black market.

Many Americans would love a drug that makes them fitter, sharper, and more attractive. The peptides industry aims to oblige, and sales may soon be off to the races, courtesy of the Trump Administration and its chief peptides backer, Health Secretary Robert F. Kennedy Jr.

Peptides are short-chain amino acids that are formulated into drugs. Insulin is a peptide. So are GLP-1s like Ozempic. Legions of other peptides are on the market in the “wellness” industry, promoted for everything from athletic performance to skin care, mental focus, and “romantic connection”—the latter pitched by a startup called Feel Peptides.

Compounding pharmacies make some peptides, but many are manufactured without much oversight with ingredients mainly sourced from China. They’ve soared in popularity online, often sold to consumers without a prescription, designated for “research use.”

The FDA may soon step into that gray market, allowing compounding pharmacies to produce and sell more peptides. An FDA advisory panel is scheduled to hold hearings in late July on whether to recommend seven substances for inclusion on a list of approved bulk ingredients that compounders may use to create peptide drugs.

Several popular peptides are under review. BPC-157, for instance, is the poster child for muscle and tissue repair. Others include TB-500, popularly paired with BPC-157 in a “wolverine stack” to recover from workout injuries, and MOTs-C, marketed for metabolism benefits.

Five more peptides are up for review by early next year. The FDA panel is evaluating each peptide for uses—like BPC-157 for ulcerative colitis—that don’t necessarily match up with what they’re known for online.

Kennedy has has said he’s a “big fan” of peptides and indicated he wants the FDA to regulate more of their production. The advisory panel review “begins to restore regulated access and will immediately begin shifting demand away from the black market,” he said on X.

The advisory panel includes several physicians involved in peptides. At least six doctors on the panel are involved in peptides therapy and some have posted content about the drugs, according to their disclosures and websites.

The FDA isn’t obligated to take the panel’s recommendations, an FDA spokesperson said. “All committee members underwent the same ethics review and vetting process required of all FDA advisory committee members,” the spokesperson added.

Peptides are contentious in the medical community. A dearth of clinical trial data in humans has long raised concerns. The FDA restricted compounders from selling certain peptides in 2023, citing safety risks. In a report made public in the past week, FDA staff scientists said the bulk of criteria “weigh against” placing the substances on a list for permitted use in compounded drugs.

Wall Street, for its part, sees a potentially large growth market. Needham analysts estimate an addressable market for non-GLP-1 peptides of $34 billion, up from around $3 billion in annual sales now, assuming FDA permission and other factors fall into place. Investment bank Leerink Partners sees a $2.2 billion market for telehealth companies, based on sales projections of the first seven peptides under review.

The biggest publicly traded beneficiary could be Hims & Hers Health. The telehealth company bought a peptides manufacturing facility last year. Leerink analyst Michael Cherny estimates Hims could capture 20% of the $2.2 billion market. “The Hims chassis should be well-positioned to maximize peptide sales,” Cherny says.

Hims says over half the questions it received before its recent earnings call were on peptides. The company doesn’t have to be “first to market,” CEO Andrew Dudum told investors, but it aims to be “the best.”

For now, Hims remains a play on GLP-1s. The stock started taking off in March after the company struck a deal with Novo Nordisk to sell its branded GLP-1s like Ozempic and Wegovy. Shares got another boost Wednesday after Canaccord Genuity and Bank of America raised price targets, citing an improving outlook for branded GLP-1s.

Most analysts see the stock fully valued. Its average rating is a Hold with a target of $29, below recent prices around $38.

Needham analyst Ryan MacDonald has a rare Buy on Hims, but he pegs the fair value at $35. He views recent updates from FDA as mixed, but thinks it’s “more likely than not” the agency will permit the peptides, he told Barron’s.

Wall Street’s caution on Hims reflects another unknown: whether peptides sold for unapproved uses will make the leap from the medical fringes to mainstream consumer adoption.

While there’s some clinical evidence for peptides, claimed health benefits tend to rely on preclinical or animal studies and research conducted outside the U.S.—lacking the kind of rigorous studies the FDA requires to approve a drug. Unlike FDA-approved medications, compounded drugs don’t go through the same process in which clinical data is reviewed for safety and efficacy.

The peptides up for FDA review “are in general lacking most or all of that information,” says Peter Lurie, a former FDA official and head of the Center for Science in the Public Interest. The FDA’s move on peptides could undermine the clinical trial process, he adds, while consumers waste money on products that are ineffective.

While the science is unsettled, scores of companies are gearing up to sell peptides. Privately-held telehealth company Noom recently bought a compounding pharmacy and plans to expand into peptides. “Noom believes that peptide-based therapies should move out of the unregulated gray market and into a legitimate, clinically responsible framework,” the company said in a statement.

Gyms may also add peptides to their menus of massages and other add-ons. A gym charging $100 for a monthly membership, for example, could make an additional $100 a month from the same customer with peptides, says Jon Lensing, co-founder and CEO of OpenLoop Health, a telehealth infrastructure company. “It’s a significant revenue bump with an already existing audience they control,” he says.

Several physicians on the FDA’s peptides committee work at longevity clinics and have posted content about peptides. Gabriel Alizaidy describes himself as a “peptide and hormone” educator on LinkedIn and offers consultations for peptide protocols. Asare Christian, another panel member, has posted content called Unlocking Your Potential with Peptide Therapy.

Haleem Mohammed, also on the panel, is chief medical officer for a network of clinics called Gameday Men’s Health, which markets peptide and vitamin injections on its website.

The three panel members didn’t reply to a request for comment.

Proponents argue there’s ample evidence for taking certain peptides. Lee Rosebush, an attorney and co-founder of a nonprofit, the American Academy of Peptide Medicine, has challenged FDA restrictions on peptide compounding. He plans to present at the advisory meeting, telling Barron’s, he looks forward “to providing additional clinical information…that shows that safe access to these peptides is possible.”

Some investors, after taking peptides themselves, are betting on them financially.

Venture capitalist Brian Sugar started taking GLP-1s for weight loss and then tried BPC-157 tablets. The experience was eye-opening, he says, and he saw mass-market potential in peptides more broadly. He’s since invested $1.5 million in Feel Peptides through his firm, Sugar Capital.

“It was very clear to me, after this experience that I went through, that GLP-1 was, as I call it, the amuse-bouche of what’s going to be happening,” he says.

Other investors say they’d like to see more clinical data before investing in wellness peptides. Joe Horsman, a Ph.D. biochemist and investor at venture capital firm Madrona, has backed biotech companies developing peptide therapies. But Horsman says low clinical evidence for many peptides in the wellness space remains a challenge. “I’d love to see some safety data before we say, ‘Go nuts, people.’ ”