The End of Japan’s Negative Rates Will Be a Slow-Moving Tsunami

Japan’s stocks have reached levels that haven’t been seen for 34 years . The country is likely to hit another milestone soon: Its central bank could raise interest rates for the first time in 17 years as soon as Tuesday.

Higher, and positive, Japanese rates won’t reshape markets overnight. But the long-term effects could be profound, particularly if U.S. growth heads structurally lower for any reason, further narrowing the yield advantage of many U.S. assets. Japan is the single largest overseas holder of U.S. Treasurys, a major overseas lender, and an export heavyweight whose corporate earnings—and stocks—have been significantly supported by the ultra cheap Japanese yen. More Japanese capital staying at home could eventually impact the price of everything from U.S. mortgages to infrastructure finance in the developing world.

For much of the past two years, Japan has swum against global monetary tides, maintaining its ultra low interest-rate regime. But now, as most other major central banks are about to cut rates, the Bank of Japan is poised to break the trend again. Domestic media reported over the weekend that Japan’s central bank will end its negative interest rates, which have been in place since 2016, during its policy board meeting on Monday and Tuesday.

The decision would come after mounting evidence that the job market is on an increasingly strong footing , after years of stagnant wage growth. Unions secured an average salary increase of 5.28% , according to the first-round results of Japan’s annual spring wage negotiations, the Japanese Trade Union Confederation said last week. For the entire decade ending in 2022, the final annual increase never exceeded 2.4%.

Much likely won’t change in the short term. The Bank of Japan will probably pace its rate increases slowly: The past couple of years have, if anything, reaffirmed its reputation for moving slowly and deliberately. Moreover, while inflation is still high by Japanese standards—2.2% in January—it has already cooled from the peaks of last year.

Japanese bond yields have picked up, but they are still substantially lower than in the U.S. The rate differential between 10-year government bonds in the U.S. and Japan stands at 3.5 percentage points. That is significantly lower than the 4.2-percentage-point gap of a few months ago, but still way higher than the 1.5 percentage points of three years ago.

Even so, a narrowing rate gap—especially if the Fed cuts rates later this year, as seems likely—will support the Japanese yen . That could damp enthusiasm for rip-roaring Japanese stocks . They would become more expensive in dollar terms for foreign investors, who have been significant drivers of the rally. A stronger yen would also hit profits at some Japanese companies , especially big exporters.

Likewise, gradual interest-rate increases in Japan probably won’t change investment flows much in the short term. But it could be a different story down the road if the shift back to positive rates proves sustainable.

Japanese individuals and companies have been big investors abroad in search of higher yield for decades. The country’s foreign-portfolio investments stood at the equivalent of $4.2 trillion at the end of last year. A big chunk of that comes from Japanese pension funds and insurers, who would suddenly have more attractive options at home. Japanese investors, for example, hold around $1.1 trillion of Treasury bonds, making them the largest foreign owner.

Japanese investors have been scouring the globe for better returns for as long as most investors can remember. If that starts to change, the effects will be felt nearly everywhere—sooner or later.

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