Wall Street Is Counting on Nvidia to Keep the AI Party Going
Nvidia’s earnings will test Wall Street’s confidence in the AI boom.
3 min
Chip makers are fighting to assure investors that the artificial-intelligence boom is racing forward. Wall Street might not believe it until Nvidia’s NVDA -0.98%decrease; down pointing triangle Jensen Huang says so.
When Huang steps up to the mic for his company’s earnings call Wednesday, he will have the world’s attention. What he says about Nvidia’s present will preview the future of AI, dictate the path forward for a tech-crazed stock market and influence an American economy increasingly tethered to hopes that the boom won’t go bust.
The $5 trillion chip maker has provided the key building blocks for AI since the launch of ChatGPT in 2022 set off a race for dominance among OpenAI, Anthropic and established Silicon Valley giants. Now, as Nvidia backstops sprawling data-center projects and an exotic money pipeline to boost chip demand, the company’s influence is arguably bigger than ever.
But there are signs of trouble ahead. Political pushback to AI is growing. A bond selloff propelled borrowing costs to their highest levels in years. The hyperscalers that include some of Nvidia’s key customers—once cash-printing machines—are relying more on debt. OpenAI recently told investors its revenue rose by a tepid 18% in the second quarter while its losses deepened.
Nvidia is increasingly stepping in to shore up potential weak points across the market. Earlier this month, the company teamed up with six of Wall Street’s biggest firms on a $500 billion AI-financing plan, pledging to backstop lending to customers that can’t afford its chips otherwise. The chip maker last week also took a stake in Cloverleaf Infrastructure, which arranges power for data centers, and struck a $6 billion deal with startup Poolside aimed at developing a powerful open-weight AI model.
After watching shares in other chip makers and the so-called Magnificent Seven tech companies swing wildly in recent months, Wall Street is hoping Nvidia can beat expectations—again. The countdown is on.
“It’s kind of becoming more and more like the World Cup final than the Super Bowl at this point,” said Brian Mulberry, chief market strategist at Zacks Investment Management. “It’s just gotten to be that big.”
The company has smashed analysts’ earnings estimates for each of the 14 quarters since the AI boom kicked into high gear. Nvidia posted 210% annual growth in net income in its last three-month period, according to FactSet, making Wall Street’s 126% projection look pedestrian.
Expectations for a blowout second quarter have risen rapidly over the course of this year. All Nvidia will have to do to beat this target: outrun 95% annual earnings growth to more than $51.5 billion. Analysts project the chip maker will report record sales of $92 billion for the period, up from a forecast of $78 billion at the start of this year.
In July, big-tech earnings sparked volatility. Concerns about runaway capital spending spread across the sector after Alphabet’s and Tesla’s results, driving a $890 billion wipeout that contributed to the unwind of hedge fund Situational Awareness. Microsoft posted the largest one-day gain in market capitalization by any company, ever, after a quarter proving that it could still show investors the money. SpaceX rocketed higher after a record-breaking initial public offering, only to see $1 trillion in value evaporate.
Surging memory prices and borrowing costs have fueled fears that those and other companies will be unable to keep plowing more money into supplies including Nvidia chips. Shaia Hosseinzadeh, founder of OnyxPoint Global Management, has recently bought dips in AI-infrastructure stocks when Wall Street has strained to absorb massive debt issued by Silicon Valley.
“The macro data is really quite robust,” he said. “Of course, there’s a level at which everything breaks.”
Investors have kept pumping money into the AI trade despite concerns around chip consumers—and to the benefit of chip producers. That is why Nvidia’s outlook for semiconductor demand could send ripples through counterparts such as Micron Technology and Sandisk, developers of the data centers in which their chips reside, and a supply chain of power producers, contractors and other specialists that underpin the globe-spanning AI build-out.
“We joke internally that we’re all Nvidia analysts now,” said David Lefkowitz, head of U.S. equities at UBS Global Wealth Management.
The irony is that investors have tended to sell Nvidia stock immediately after blockbuster earnings, with shares falling each trading session after its four past quarterly reports. Some are betting that will be the case this time around, too.
The options market is pricing in a 5.3% swing, higher or lower, in Nvidia shares during the session following earnings, according to Option Research & Technology Services. That is higher than the 4.8% average move in Nvidia’s stock over the last 12 months after the company reports quarterly results.
In recent days, some of the most actively traded Nvidia options have been put contracts tied to the stock falling from its Friday value of $214.75 to $205 and $210 apiece, according to Cboe Global Markets data. Put options give the right to sell a stock by a set price and typically represent a bearish wager.
Many analysts remain optimistic. Frank Lee, global head of tech hardware and semiconductor research at HSBC Global Investment Research, recently raised his price target for Nvidia shares to $360 from $325, citing, among other things, Nvidia’s strategic partnerships with suppliers and its role as a top contributor to open-source AI.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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