Chips and Taiwan Are a New Cloud for Tech Earnings

Chip politics are no longer just the chip industry’s problem.

Investors got a sharp reminder last week of just how politicized the semiconductor industry has become—especially ahead of a U.S. presidential election. First came a report that the Biden administration is considering more severe trade restrictions to keep advanced chip manufacturing tools out of the hands of Chinese companies.

Then Bloomberg Businessweek ran an interview with Donald Trump in which the former president and current Republican nominee raised doubts about whether the U.S. under his administration would defend Taiwan from China unless the island democracy starts paying for U.S. protection.

The news poured more than a splash of cold water on what has been a red-hot sector. Chip stocks crashed Wednesday following the initial reports and kept falling. The PHLX Semiconductor Index closed Friday with a weekly loss of nearly 9%. The index had been up 40% for the year to date ahead of the damaging reports after having surged 65% this past year—its best annual performance since 2009.

Semiconductor investors have long been factoring in the growing risk of lost sales to China due to export restrictions. But Trump’s comments about Taiwan add a whole new element of risk: The island is a major hub for manufacturing the world’s most advanced semiconductors and less-advanced but vital ones that go into products such as thermostats, cars and medical devices.

This isn’t just about Taiwan Semiconductor Manufacturing , the chip-making giant better known as TSMC that produces key processors for companies such as Nvidia , AMD and Apple . The island is also home to many other suppliers of key components used in final chip products. During a speech at a conference in Taipei in June, Nvidia Chief Executive Officer Jensen Huang praised Taiwan as “the unsung hero” of the computer industry, showing a slide of more than 100 companies he described as “treasured partners” to the artificial-intelligence chip star .

Hence, Trump’s comments “threw gasoline on an already raging China restriction issue that had the chip stocks in turmoil already,” independent semiconductor analyst Robert Maire wrote in an email. Whatever the intent behind them, they may have raised the odds of an attempt at forced “reunification” by China by creating doubt about America’s response.

Military action against Taiwan wouldn’t just hit chip companies but also the many, many businesses that use those chips. It isn’t a small list: Chips sit at the heart of the cloud computing services offered by Microsoft , Google and Amazon as well as the iPhones sold by Apple and the EVs sold by Tesla , whose CEO is now one of Trump’s largest backers.

Armed conflict between mainland China and Taiwan is hardly a foregone conclusion, even if Trump wins in November. But investors who mostly have been trading on AI hype need to factor a new element of risk into their models—especially since political rhetoric will only grow louder ahead of the election. U.S. policy toward China is a major issue for both parties, and the question of defending Taiwan will very likely arise again.

This comes as investors are also grappling with how to value the AI opportunity, especially as coming tech-earnings reports will likely continue to feature more AI investments than actual revenue.

Risks there still aren’t fully baked in. The Nasdaq Composite Index has come down a bit from the record high it hit earlier this month, but is still up 18% for the year, which is more than double the Dow’s return. And the six megacap tech giants—Apple, Microsoft, Nvidia, Amazon, Google-parent Alphabet and Meta Platforms —have added a collective $3.7 trillion in market value in that time. That is an awfully big bet on a sector that no longer has the luxury of staying out of the political fray.

A 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