PDD Holdings reported a 12% decline in net profits in the three months ended June 30, surpassing Wall Street consensus.
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Vanguard’s VOO may be quietly exposing your portfolio
The Vanguard S&P 500 exchange-traded fund has drawn investors with its industry-low costs, a strategy that has delivered strong results so far.
At a 0.03% expense ratio, VOO costs about $3 per year on a $10,000 investment, matching iShares’ IVV and undercut only by State Street’s SPLG/SPYM at 0.02%.
The fund has delivered a 20.69% gain over the last 12 months, and its total net assets sit near $997 billion as of mid-August 2026.
But the fee comparison that drew millions of investors into VOO says nothing about what the fund holds beneath the ticker symbol.
What VOO holds beneath the S&P 500 label
Technology stocks make up approximately 37% of VOO’s portfolio, with Nvidia, Apple, and Microsoft leading the lineup, Vanguard confirmed.
Depending on the data cut and whether Alphabet’s dual-class share structure is combined, VOO’s 10 largest positions control roughly 36–41% of total assets, meaning about 2% of the names carry more than a third of the weight.
For every $100 invested in VOO, roughly $36 flows into those 10 companies, while the remaining $64 gets divided among more than 500 other names.
That concentration extends beyond stock prices into the earnings that drive them.
Liz Ann Sonders, Chief Investment Strategist at Charles Schwab, noted on the firm’s On Investing podcast in May 2026 that the upward revision in full-year S&P 500 earnings is being powered by just a handful of names.
Just three companies alone, just Alphabet, Amazon, and Meta, explain about 70%, in dollar terms, of the increased earnings expectation for calendar year 2026
A decade ago, the S&P 500’s top 10 stocks held about 19% of the index, meaning concentration has nearly doubled over roughly 10 years, RBC Wealth Management reported in January 2026.
The mismatch between VOO’s sector weight and U.S. economic output
That technology tilt looks dramatically different from the economy the index is supposed to mirror, and the gap keeps widening each quarter.
The Bureau of Economic Analysis (BEA) reported that the Information sector generated just 5.6% of the U.S. gross domestic product in the first quarter of 2026.
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Real estate, the economy’s largest industry by value added, contributed 13.6% of GDP in that same period, and finance and insurance added 8.0%.
Information sector corporate profits jumped from $271 billion in the first quarter of 2025 to $352.5 billion one year later, BEA data showed.
That growth pushed the sector’s share of total domestic corporate earnings from 7.9% to 9.1%, fueling a significant portion of VOO’s recent gain.
But strong earnings and outsized index representation are two distinct things, because cap-weighted positions reflect expectations about future growth, not current economic output.
VOO’s tech-heavy portfolio looks little like the U.S. economy, highlighting how market value reflects future growth expectations rather than current economic output.Bloomberg / Getty Images
How the S&P 500’s concentration compares to dot-com-era peaks
Meera Pandit, Executive Director and Global Market Strategist, and Corey Hill, Managing Director and Global Head of Portfolio Insights at J.P. Morgan Asset Management, reported that the S&P 500’s top 10 stocks now account for 40.8% of the index.
That figure surpasses the 26.6% concentration peak reached during the late-1990s technology bubble, the firm noted.
“When valuations are priced to perfection, they are prone to correction,” Pandit and Hill wrote, adding that elevated concentration amplifies the impact on portfolios.
During a 28-session rally from late March to early May 2026, just 10 stocks drove 69% of the S&P 500’s total gains, according to a Nomura return-attribution analysis reported by Investing.com.
The math cuts both ways: the same concentration that amplifies gains on the way up amplifies losses if those names reverse, because a 10% decline in a stock that represents 7% of the index moves the portfolio seven times more than the same decline in a stock weighted at 1%.
Goldman Sachs projects lower S&P 500 returns driven by concentration
David Kostin, Advisory Director at Goldman Sachs, and his team projected in an October 2024 note that the S&P 500 would deliver just 3% annualized returns over the next decade.
That figure would rank in the 7th percentile of 10-year returns since 1930, a steep drop from the 13% average posted over the prior decade.
“If the historical pattern persists, high concentration today portends much lower S&P 500 returns over the next decade,” Kostin’s team wrote.
Goldman’s analysis also indicated that the equal-weight S&P 500 could outperform the cap-weighted version by two to eight percentage points per year.
An equal-weight fund holds the same 500 companies but caps each position near 0.2% of the portfolio, which structurally limits any single sector’s dominance, RBC Wealth Management reported.
The trade-off VOO investors haven’t priced in
VOO’s 0.03% expense ratio still represents a genuine cost advantage, and the fund’s 87.50% five-year total return has rewarded investors who chose low-cost indexing.
But those returns increasingly depend on a narrow cluster of stocks, and online investors have started noticing, with Reddit threads questioning whether the “VOO and chill” strategy carries hidden sector-concentration risk, 24/7 Wall St. reported.
VOO’s 0.03% fee sits within one basis point of the lowest available S&P 500 tracker, so the cost side of the equation is essentially settled.
What’s not settled is whether a roughly 37% technology tilt matches the level of sector risk long-only index investors have typically expected the fund to carry.
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BofA finds AI is creating a credit divide that could reach consumers
The artificial-intelligence boom is most often seen as a Wall Street story.
Nvidia (NVDA) rallies. Big Tech spends billions. Data centers multiply. Investors debate which company will become the next major AI winner.
But Bank of America says something more substantial is starting to unfold under the surface.
AI is splitting firms into two paths: those turning the technology into tangible growth and those being disrupted by it.
The BofA research note of Aug. 20, shared with TheStreet, paints a stark picture of this gap in the leveraged-finance sector.
And although bond spreads and leveraged loans may seem distant from everyday life, the companies borrowing in these markets employ workers, buy equipment, and supply products and services that consumers use.
If one group can develop and invest and the other faces slower revenue growth and more expensive financing, the implications can ultimately reach Main Street through hiring, wages, company investment, and corporate cutbacks.
BofA finds a widening gap between AI winners and losers
BofA separated issuers of high-yield and leveraged loans into those benefiting from AI (the “tailwind” group) and those facing AI-related disruption (the “AI-risk” or “headwind” group).
The data reveal a shocking gap.
Among high-yield borrowers, BofA’s AI-tailwind group posted 16.2% year-over-year revenue growth in the second quarter and 15.2% growth in adjusted EBITDA.
The AI headwinds companies grew their revenue by only 4.1% and EBITDA by 7.6%.
The disparity was considerably more pronounced for leveraged-loan debtors.
AI beneficiaries saw a 26.8% revenue increase compared with a 3.6% gain for enterprises vulnerable to AI disruption, according to BofA.
The AI-tailwind cohort’s EBITDA growth was 23.4% vs. 3% for the AI-risk cohort.
BofA describes the emerging pattern as a “Credit-K,” basically two groups going in significantly divergent ways.
That’s important because companies that make more money tend to have more room to hire, invest, and service their debt.
Companies on the weaker side of that split may have to make some tough decisions.
AI hardware is where the money is showing up first
The tech sector was again one of the best-performing sectors in leveraged finance during the second quarter.
But not all companies shared equally in the spoils.
Hardware companies in the leveraged-loan market recorded nearly 48% revenue growth and more than 50% EBITDA growth.
Hardware sales among high-yield issuers climbed 32.1%, and EBITDA jumped 85.6%.
Software and services were much softer.
Revenue rose just 4.5% among loan borrowers and 5.8% in high yield. That gap helps explain where the AI boom now stands.
The first to benefit are the companies that sell servers, data center gear, and other physical infrastructure, as huge sums of money are being invested to build out AI capability.
The advantage for firms only now rolling out AI is less clear.
BofA’s investigation identified substantial AI benefits at 31% of S&P 500 companies, compared with just 18% of leveraged-finance issuers.
Thus, the AI cash bonanza is still concentrated in the companies closest to building the technology.
BofA says AI is creating a new economic split beyond Wall StreetRon Jenkins / Getty Images
Big Tech is borrowing billions to build the AI economy
In the debt market, the scale of the investment becomes evident.
Companies have sold over $335.7 billion in AI-linked U.S. dollar debt year-to-date, according to BofA.
Investment-grade debt accounts for some $255 billion of that.
High-yield borrowing is adding another $40 billion. Loans and direct lending each are contributing about $20 billion.
Some of America’s most known corporations are in the middle of that funding tsunami.
Alphabet (GOOGL) alone sold almost $25 billion of investment-grade debt focused on AI on Aug. 6, according to BofA’s transaction tracker, after raising nearly another $20 billion in February.
Amazon (AMZN) sold $25 billion of debt in July, following an even larger debt sale in March.
Nvidia (NVDA) raised around $25 billion in June.
And Meta Platforms (META) sold almost $25 billion of bonds in April.
Those numbers are another way to think about AI.
Big Tech isn’t only hooking up chatbots to current products.
Companies are pouring unprecedented amounts of capital into data centers, semiconductors, electricity, and infrastructure.
AI borrowing comes with a price
And bond investors aren’t perceiving that expenditure as risk-free.
Investment-grade AI debt now trades at spreads of roughly 119 basis points, or around 46 basis points wider than comparable non-AI debt, says BofA.
High-yield AI spreads are around 320 basis points, a premium of about 147 basis points over similar non-AI debt.
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That suggests lenders understand the tension at the heart of the AI boom.
If built, the infrastructure could generate huge long-term profits.
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But someone has to pay for it first.
And those costs of financing weigh more for weaker borrowers than they do for cash-rich technological companies.
The AI boom is still leaving many companies behind
The underlying fundamentals in leveraged finance remain pretty solid overall.
High-yield revenue increased 7.5% year over year in the second quarter, with adjusted EBITDA up 9%.
Leveraged-loan borrowers delivered 8.6% revenue growth and 9.5% EBITDA growth. BofA expects the broader market to maintain solid momentum in the third quarter. But the headline numbers hide increasingly different realities.
Technology and energy are performing strongly. Real estate remains pressured by elevated rates and housing affordability. Retail high-yield revenue increased only 1%, while earnings declined 2%.
Food producers had a modest 2% increase in revenue and an 11% fall in earnings as rising commodity and freight prices squeezed margins.
That’s why BofA’s AI gap matters more than traders monitoring bond displays.
If the businesses that can do AI keep pushing away, cash could progressively flow into areas that are already benefiting from the technology.
That might decide which companies expand, whose factories and data centers are built, and eventually where new employment is produced.
The first stage of the AI boom was about exhilaration.
The following stage is getting a lot more tangible.
Now firms have to prove that standard artificial intelligence can deliver real revenue, improved margins, and enough cash flow to justify hundreds of billions of dollars of investment.
And Bank of America’s most recent data reveals that the winners are starting to separate from the rest of the pack.
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These Tiny Stocks Are Quietly Outperforming the Market
The mice have roared in the past year.It may have escaped your notice as the broad market this year has climbed despite worries over war, inflation, interest rates, artificial intelligence spending, and mega-initial public offerings, but very small stocks and funds that own them have had a very big run.Micro-caps started outperforming the broad market and its large-, mid-, and small-cap strata about a year ago. In the trailing year through Aug. 17, 2026—roughly the middle of the month, the Morningstar US Micro Cap Index, which includes the smallest 3% of domestic equities—walloped the Morningstar US Market Index 45.7% to 22.8%. Morningstar’s broad small-, mid-, and large-cap benchmarks also ate micro-cap dust.Naturally, this trend has been great for mutual and exchange-traded funds that own a lot of micro-cap stocks. Sorting small-cap funds and ETFs at least a year old with more than $100 million in total assets into five buckets by their stakes in what Morningstar considers micro-caps shows smaller has been better in the past year. Over the past 12 months, the first bucket, or quintile, which included funds that had between 51% and 100% of their money in micro-caps, gained an average of more than 33% and beat two-thirds of their respective category peers in the year ending Aug. 17. Meanwhile funds in the fifth quintile, which had less than 19.6% in smallest of the small-cap stocks, gained about 26.0%, but lagged more than 61.0% of their respective peers.Many small-cap managers use a different definition of micro-cap than Morningstar, often setting absolute market-cap levels, such as $300 million or $1 billion, as a cutoff. Slicing the small-cap funds into quintiles by their average market cap, rather than by amount of assets in the US market’s bottom 3% of market cap, produced similar results, though. The smallest average market-cap quintile still posted better average returns and category ranks than the fifth of small-cap funds with the largest average market caps.With a few exceptions, the same factors that have been driving the rest of the market up—exuberance for and extravagant spending on all things AI—have propelled micro-caps and funds and ETFs with generous portions of them. Dividing small-cap funds with more than $100 million in assets and more than half their assets in micro-caps into five groups by their technology sector weightings and looking at their performance over the past year shows that micro-cap heavy strategies with more than 18% of assets in tech stocks posted much better returns and achieved much better category rankings.The iShares Micro-Cap ETF IWC is a good proxy for the universe, and an assortment of tech and biotech stocks helped it beat the Morningstar US Small Cap Market Index. Those include Applied Optoelectronics AAOI, a supplier of fiber-optic components to data centers, semiconductor chip material supplier AXT AXTI, and Applied Digital APLD, TeraWulf WULF, and Cipher Digital CIFR, a clutch of former cryptocurrency miners that have morphed into AI data center landlords. Expectations for the commercial prospects of essential tremor and childhood epilepsy treatments also fueled Praxis Precision Medicines’ PRAX high triple-digit trailing-year returns.Many of the hottest micro-cap stocks, however, are also lower on the quality scale. They often rely on one or a few big customers or products and must spend gouts of money to keep growing revenue. In the case of the former crypto miners, they’re changing their entire business models in midflight. It’s fair to call them speculative.Indeed, sorting small-cap funds with big micro-cap stakes by their portfolios’ quality factor exposure—a measure of firm profitability and debt—shows that the fifth of funds with bigger helpings of low-quality stocks have done better and ranked higher in their peer groups than those with relatively better-quality holdings. Other stocks besides tech-flavored ones worked for micro-cap-leaning managers in the recent rally. Semiconductor holdings helped Royce Small-Cap Opportunity ROFIX, which had more than 60% of its assets in micro-caps, but so did some industrial stocks like machinery-maker Mayville Engineering MEC and construction company Orion Group Holdings ORN, and oil- and gas-services provider Tetra Technologies TTI. Some of those stocks, such as Mayville, build or supply materials and services to data centers, so AI buildout tailwinds have filled their sails, too. Yet, there have been more idiosyncratic winners. Royce Small-Cap Special Equity RSEIX, had watchmaker Movado Group MOV, retailer Macy’s M, and cat litter maker Oil-Dri Corporation of America ODC among its top performing and contributing holdings. Diamond Hill Small Cap DHSIX also owned Oil-Dri and has had good experiences with packaged food supplier Mama’s Creations MAMA and medical and scientific tool company Mesa Laboratories MLAB. Both funds had more than two-thirds of their equity assets in Morningstar’s definition of micro-caps. Micro-cap-leaning funds have been in outflows for years, but, on average, they’ve turned slightly positive on average in the last year. Perhaps the micro-cap rally has not escaped everyone’s attention.If you’ve noticed and are considering jumping in, look before you do. The same trends that have propelled the rest of the market have contributed to many micro-cap-heavy funds’ recent results. A lot of the tiny stocks these funds own face the same worries about the sustainability of AI-related spending and valuations as their larger-cap brethren. And if you already own a small-cap fund, you may already have all the micro-cap exposure you need.
IBM’s next-gen mainframe chip is the first to run Arm and Z workloads on the same cores
IBM is announcing today at the annual Hot Chips conference what may be the most consequential change to mainframe architecture in decades: a processor whose cores can natively execute both IBM’s own instruction set and Arm’s — switching between the two in nanoseconds.The chip, which will power the next generation of IBM Z and LinuxONE systems, is the first dual-architecture mainframe processor ever built. It is designed to let enterprises run the vast and fast-growing ecosystem of Arm-native Linux software — including the AI frameworks that increasingly define modern infrastructure — directly alongside the z/OS transaction-processing workloads that anchor the world’s banks, insurers, and governments.”As technology enthusiasts on both sides, we’re really excited about being what I would consider one of the most powerful commercially available processors that’ll be dual architecture,” Tina Tarquinio, chief product officer for IBM Z and LinuxONE, told VentureBeat in an exclusive interview ahead of the announcement.The announcement marks the first hardware milestone from the strategic collaboration IBM and Arm unveiled in April, and it offers an unusually direct answer to a question that has shadowed the mainframe for years: can the machine that processes most of the world’s regulated financial transactions remain a first-class citizen in an AI era built largely on other people’s silicon?How IBM engineered a processor core that speaks two instruction setsThe most striking engineering decision is what IBM chose not to do. The company could have bolted a handful of standalone Arm cores onto the side of its processor — a simpler design that other chipmakers have used for heterogeneous computing. Instead, IBM built every core on the chip to be bilingual.”On this chip are 11 cores, and each core can dynamically switch back and forth between Arm software mode and traditional Z software mode,” Jacobi explained in an exclusive interview with VentureBeat. “That enables us to run the mission-critical enterprise software right next, on the same chip, to the much broader software ecosystem of Arm applications.”The mechanism relies on the open-source KVM hypervisor. Enterprises can run Arm64 Linux virtual machines and Linux on Z virtual machines side by side, and as the hypervisor dispatches each virtual machine onto a physical core, the core flips into the corresponding mode. The performance penalty, Jacobi said, is effectively zero. “That switch takes about the nanosecond scale,” he said. “Because you’re running for many milliseconds in the virtual image, this switching overhead sort of amortizes to zero — pretty much no impact at all.”Traditional z/OS workloads run in a separate partition on the same chip, outside KVM — meaning a bank’s core ledger, its fraud models, and a modern Arm-native monitoring stack can all share the same silicon, the same memory fabric, and the same reliability guarantees. Jacobi was candid that IBM debated the easier path and rejected it. “We’re really not addressing their need if we just have a few, I’d say, loosely Arm cores in the corner of the chip,” he said. “It really needed to be deeply integrated into the entire system design for it to have the same qualities of service that clients are used to.”The specifications underscore that this is no compromise design. Built on a leading-edge 2-nanometer process node, the chip runs its 11 high-performance cores at a base frequency above 5.7 GHz — extraordinarily fast by industry standards — with on-chip AI inference accelerators for in-transaction fraud detection, a dedicated data processing unit for I/O acceleration, and a large cache architecture. Full systems will scale to hundreds of cores and tens of terabytes of memory. “That’s really, really fast compared to what you otherwise get in the industry,” Jacobi said. “It’s just another example of how mainframe technology is not old technology. It’s very modern, leading-edge technology.”Why the mainframe needed Arm’s 22 million developersThe strategic logic behind the chip is about software, not hardware. IBM’s s390x architecture runs an enormous share of the world’s mission-critical transactions, but the broader universe of enterprise software — monitoring tools, security agents, cloud-native middleware, and above all the AI stack of PyTorch, ONNX Runtime, and container workloads — was built for x86 and, increasingly, for Arm. By Arm’s own estimates, close to half of the compute shipped to major hyperscalers in 2025 was Arm-based, driven by AWS Graviton, Google Axion, and Microsoft’s Arm silicon. Arm counts more than 22 million developers worldwide.Porting each application to s390x has been a grinding, one-ISV-at-a-time effort, and Tina Tarquinio, chief product officer for IBM Z and LinuxONE, described the calculus bluntly. “No matter how great our ecosystem team is, we would never be able to work with all of them and port them all,” she told VentureBeat. “There’s a lot of ISVs out there, and so we wanted to make a fundamental, big step-function forward. We took a swing from a technology point of view.”Notably, she said customers weren’t asking for a dual-architecture chip per se — they were asking for outcomes. “I wouldn’t say our clients were saying, ‘Can you please make me a dual-architecture environment?’ But they were saying, ‘Help me get these surround workloads, or different types of workloads, to run in a quicker-to-market fashion.'”The compatibility promise is ambitious: Arm Linux binaries should run unmodified. “The new Arm capabilities are designed to be 100% binary compatible,” Jacobi said. “Once you have, for example, Red Hat Linux for Arm, and you have applications that run on Red Hat Linux for Arm, they will run on the system without modifications.” Arm defines the instruction set architecture and supplies validation tooling to guarantee that IBM’s implementation behaves identically to every other Arm chip — while IBM designs and builds the silicon entirely in-house. “Very good partnership. Very solid engineering partnership as well,” Jacobi said of the collaboration.What a next-generation Spyre accelerator means for enterprise AI on the mainframeIBM is also previewing the next generation of its Spyre AI accelerator at Hot Chips, and the pairing is not coincidental. The current architecture already offers two tiers of AI: an on-processor accelerator, introduced with the Telum chip in 2022, that handles ultra-low-latency inference such as fraud scoring inside a payment transaction, and the Spyre accelerator card sitting in the I/O subsystem for heavier models.The new Spyre raises the ceiling considerably. “We’re also bringing a much higher performance chip that is capable of running large language models for agentic workflows,” Jacobi said — both AI-ops workflows that administer the system itself and business workflows “for things like document understanding and insurance adjudication.” The new accelerator will ship with high-bandwidth memory to feed those models.Here the dual-architecture bet and the AI bet converge. Enterprises want to run inference next to their data; the data lives on the mainframe; and the AI tooling is overwhelmingly Arm-native. Mohamed Awad, Arm’s executive vice president for cloud AI, framed the announcement in exactly those terms: “As AI scales, more of the computing landscape is converging on Arm. Bringing Arm compute and its software ecosystem to these platforms will extend that momentum into mission-critical enterprise infrastructure to give organizations greater choice in how they deploy AI.”The timing tracks with where enterprise AI actually stands. McKinsey’s most recent State of AI survey found that while 88% of organizations now use AI in at least one business function, nearly two-thirds have not yet scaled it across the enterprise — and the companies capturing the most value are those redesigning core workflows rather than running detached pilots. For regulated industries whose systems of record sit on IBM Z, running AI where the transactions happen is arguably the most direct route to that kind of integration.When the dual-architecture IBM Z system will ship — and why existing customers shouldn’t worryBuyers will need patience. The chip will debut in the successor to the z17, which shipped in the second quarter of 2025, and IBM holds to a roughly three-year product cadence — pointing to a launch around 2028. But Tarquinio insisted the program is well past the concept stage. “It’s more than being on the drawing board. We’re full steam ahead on the whole system,” she said, adding that IBM will release more details in the run-up to launch.For IBM’s installed base, the reflexive question is whether embracing Arm signals a slow sunset for the traditional architecture. Both executives pushed back hard. “This is a big and. It is not an or,” Tarquinio said. “I have a roadmap that goes out 10 or 15 years of hardware systems. Many of our teams are working on this next system; many are also working on the one after that, and the one after that.”Jacobi cast the move as continuity rather than rupture. “The traditional mainframe that we have today as a z17 system is not just a faster version of what we built 25 years ago,” he said. “We didn’t have pervasive encryption capabilities. We didn’t have on-processor AI capabilities. Adding the Arm capability is the next big iteration in this continuous evolution.”The competitive subtext is the cloud. Asked why an enterprise would run Arm workloads on a mainframe instead of a hyperscaler, Tarquinio pointed to the platform’s availability numbers: “We’re talking eight nines of availability — that’s 0.3 seconds of downtime a year. If you’re running your ledger, if you’re running your fraud detection, any of these mission-critical apps, you want that.” The pitch, she said, is fit for purpose: match the infrastructure to the SLA, not the fashion.There are real caveats. IBM’s own press release notes that statements of future direction “represent goals and objectives only.” The Arm support is Linux-only for now, and the hardest engineering — running a foreign instruction set at production performance, with mainframe-grade fault detection and recovery, under real customer workloads — remains to be proven over the next two years.But the ambition is unmistakable. For sixty years, the mainframe has survived every wave of technology that was supposed to kill it — minicomputers, client-server, the cloud — by absorbing what it needed from each. Now IBM is attempting its boldest act of absorption yet: teaching the machine that runs the world’s money to speak the language of the AI era, fluently and natively, on the same silicon. “Bringing something that’ll really be first of its kind in production,” Tarquinio said, “showcases again what IBM is capable of from a technology point of view.” The mainframe, it turns out, isn’t being left behind by the future. It’s learning to run it.
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A cancer vaccine years in the making just proved itself
On August 19, Merck (MRK) said its personalized cancer vaccine had proved effective in a large, late-stage melanoma study, and Wall Street responded fast.
Merck shares closed up about 12.5% that day, one of the biggest single-day moves the stock has ever posted.
The rally added roughly $43 billion to Merck’s market value in hours.
The reason the market cared so much goes beyond one skin-cancer result.
Merck faces a problem in 2028, when its top-selling drug loses patent protection. This new vaccine gives the company a way to replace some of that revenue.
For investors, the question now is whether the jump reflects real long-term value or a one-day reaction that fades.
What Merck’s Phase 3 melanoma result actually showed
Merck and Moderna Announce Phase 3 INTerpath-001 Trial of Intismeran Autogene Plus KEYTRUDA® Met Endpoints of Recurrence-Free Survival (RFS) and Distant Metastasis-Free Survival (DMFS) in Patients With Completely Resected Stage IIB-IV Melanoma – Merck.com↗
Merck and partner Moderna (MRNA) said their Phase 3 INTerpath-001 trial hit its main goal.
The study tested a vaccine called Intismeran alongside Merck’s blockbuster immunotherapy Keytruda in patients whose melanoma had been surgically removed.
Intismeran is a personalized treatment. It reads the specific mutations in each patient’s tumor, then trains the immune system to recognize and attack cancer cells that carry them.
The trial enrolled 1,137 people with high-risk, stage 2B to stage 4 melanoma, according to Moderna‘s release.
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The combination of the two drugs beat Keytruda alone on two measures: how long patients went without their cancer returning, and how long before it spread to distant parts of the body.
The companies called it the first positive Phase 3 result for an individualized mRNA cancer therapy.
Why the $43 billion jump surprised even Wall Street
The rally looks big compared to the actual melanoma sales at stake.
Goldman Sachs analysts, in a research note shared with TheStreet, estimated global peak sales for Intismeran for treatment of melanoma at about $4.3 billion a year.
Merck and Moderna will split the profits 50/50, though Merck books all the global sales.
So why did Merck add roughly $43 billion in market value over a program worth a few billion in annual sales?
Investors were pricing in more than melanoma.
The result validated the underlying technology, opening the door to using the same approach against other cancers.
Goldman noted that Merck shares carried lower expectations for this program going in, which left more room for the stock to move once the data landed.
Merck and Moderna’s personalized mRNA vaccine trains each patient’s immune system using mutations found in their own tumors.Cheng Xin / Getty Images
The Keytruda cliff that makes this vaccine matter
Keytruda is Merck’s best-selling drug and made up close to half of the company’s 2025 sales.
That drug loses key U.S. patent protection in 2028, which means cheaper competition can enter, and revenue could drop sharply.
Investors have worried for years about what replaces that income. Intismeran gives Merck a credible answer.
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A vaccine like Intismeran, tailored to each patient, is hard to copy, so it faces limited generic competition and could produce a longer, steadier revenue stream than a typical drug.
That durability is what strengthened Wall Street confidence in Merck’s future progress, after 2028, when Keytruda loses exclusivity.
How analysts reset their Merck price targets
The data triggered a wave of higher price targets across Wall Street.
Goldman Sachs raised its 12-month target on Merck to $160 from $140 and applied a higher earnings multiple, of 16 times, up from 14 times.
Other firms moved in the same direction:
UBS lifted its target to $175 from $145 and kept a Buy rating.
Bank of America raised its target to $166 from $141.
JPMorgan moved to $150.
Not every analyst turned more bullish.
RBC Capital downgraded Merck to Sector Perform, even while raising its target to $150, a reminder that a strong result can still leave a stock fully valued after a double-digit jump.
What still has to happen for Merck
The melanoma win is one indication. The bigger prize depends on results in other cancers, and those are still pending.
For example, Merck is focusing the vaccine on tumors that respond well to immune-based treatment, such as melanoma and non-small cell lung cancer.
Here is the near-term timeline investors are watching:
Renal cell carcinoma (a kidney cancer): Phase 2 data expected in 2026 or early 2027
Muscle-invasive bladder cancer: Phase 2 data in 2027
Non-small cell lung cancer: Phase 3 data in 2027
A win in kidney cancer would suggest the approach can work in the same settings where Keytruda already helps patients.
The companies also plan to present full melanoma data at an international medical meeting and file submissions with regulators, according to Merck.
Who else moved on the news
The result lifted a group of related health care stocks in what traders call a sympathy move.
BioNTech (BNTX), which runs its own personalized cancer vaccine programs, rose about 24% as investors saw the data as broad support for the approach.
Companies tied to manufacturing and cancer diagnostics also jumped, including Maravai LifeSciences (MRVI), up about 28%, and Tempus AI (TEM), up about 24%.
Investors watched Bristol-Myers Squibb (BMY), a major player in melanoma treatment, for risk.
Goldman estimated a long-term risk of up to $1 billion to Bristol’s melanoma franchise, but expects the impact to be limited and gradual.
This is because Intismeran targets earlier-stage patients, while much of Bristol’s melanoma revenue comes from later-stage, metastatic cases.
What Merck’s move means for your portfolio
Merck’s rally reflects a real change in the company’s long-term outlook.
For investors, a few things are worth keeping in mind:
The stock already climbed sharply, so much of the good news is now in the price.
The melanoma result is strong, but survival data is still early, and full results have not been published.
The larger payoff depends on kidney, bladder, and lung cancer trials that report in 2026 and 2027.
If those readouts succeed, Merck’s case for replacing Keytruda revenue gets much stronger.
If they disappoint, the stock could give back some of this gain, which is why the coming trial dates matter more than the one-day rally.
For long-term investors, Merck now offers a clearer story beyond its patent cliff, backed by a technology that just proved it can work.
Related: Goldman Sachs sees writing on the wall for Eli Lilly stock
Stock Market Today (Aug. 24, 2026): : Dow futures slide on Iran sanctions, U.S.-Canada tariff threats
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Happy Monday. Stock futures were falling as investors weighed new U.S. economic sanctions against Iran, failed U.S.-Canada trade talks and reciprocal tariff threats, along with earnings from chipmaking giant Nvidia (NVDA) and the Federal Reserve’s annual symposium in Jackson Hole, Wyoming.
Treasury Secretary Scott Bessent is expected to reveal details of the administration’s sanctions plans against Iran later today after President Donald Trump threatened the country with “economic D-Day.”
The Federal Reserve will hold its annual symposium beginning Thursday, with Chairman Kevin Warsh expected to deliver a speech on Friday.
“Warsh is scheduled to deliver keynote remarks on Friday, and markets will be looking for greater clarity on both his assessment of inflation and the broader ‘regime change’ he has advocated at the Fed,” said Daniela Hathorn, senior market analyst at Capital.com.
“He has been reluctant to provide conventional forward guidance, meaning the speech may focus more heavily on the Fed’s reaction function and longer-term philosophy than explicitly signaling what policymakers will do in September.”
In addition to Nvidia, Intuit (INTU), Salesforce (CRM) and Marvell Technology (MRVL) are also slated to report earnings this week.
Stocks closed higher on Friday, rebounding from earlier losses, but the major indexes still finished the week lower amid volatile Treasury yields and heightened Middle East tensions.