Asics Stock Catches Fire Along With Its Dad Sneakers

Asics , the 75-year-old Japanese sneaker brand, is having a moment. So are its shares.

The running-shoe maker’s stock price has quadrupled in total return terms over the past two years. Its financial performance is strong: Revenue in its last reported quarter grew 14% from a year earlier while its operating profit surged 53%.

Asics has long been a well-loved brand among the running community. Around a quarter of 54,000 runners who finished the Paris Marathon sported a pair of Asics, including both winners in the men’s and women’s races, according to the company.

In fact, even Nike can trace its roots back to the Japanese company. Nike began its business in the 1960s by importing and distributing shoes from Asics, then known as Onitsuka, in the U.S. Onitsuka Tiger remains a high-end fashion brand within Asics.

Asics has benefited from the Covid-19 pandemic: More people picked up running as a hobby when they had nothing else to do. At the same time, people working from home began giving priority to comfort in their footwear—discovering that lightweight shoes with cushioned soles designed for running are pretty comfortable for walking around in, too. Running-shoe upstarts such as Hoka and On Holding have also seen explosive growth in the past few years. Hoka’s sales in the quarter ended in March surged 34% from a year earlier, pushing shares of its owner , Deckers Outdoor , to record highs.

The performance running shoes segment is Asics’ largest by revenue, and it has tried to maintain a close-knit community of runners. Asics acquired Runkeeper, a popular fitness-tracking app among runners, in 2016. In recent years, it has been acquiring race-registration companies, including Njuko Sas in Europe and Register Now in Australia. Its loyalty program has nearly 15 million members globally.

But outside of runners and Onitsuka Tiger, Asics was perhaps best known for “dad sneakers” —a style of shoes that are picked more for practicality than aesthetics. Lately, however, some old Asics designs have become unlikely fashion symbols. Youngsters have apparently eschewed conventional beauty standards and embraced the uncool: Crocs and Hoka are some other examples of “ugly shoes” that have seen an explosion in popularity.

Asics has done its fair bit, too. Its collaboration with designers from Vivienne Westwood to Cecilie Bahnsen have generated lots of buzz on social media. For example, its redesign of its 2008 Gel-Kayano 14 sneaker with Canadian design studio JJJJound has been a smash hit . The shoe can sell for more than $1,000 on online marketplace StockX. Asics was the fifth most-traded brand on StockX last year, rising from No. 10 the year before. Revenue for the company’s more fashion-minded SportStyle division grew 52% year over year in the last reported quarter.

Even better news for investors is that the company has been more profitable, too. Operating margin in its quarter ended in March was 19.4%, compared with 9.5% two years earlier. Partly that is because the company has shifted its product mix to more premium products. It has also been selling more directly to customers than through wholesalers. Around 64% of its sales were through wholesale in the first quarter, down from 74% three years earlier. E-commerce sales have risen from 13% to 17% of sales.

Asics trades at 34 times forward earnings, according to S&P Global Market Intelligence. That is a similar multiple as Deckers Outdoor but higher than bigger peer Nike, which trades at 25 times. The premium could be justified if Asics could keep growing its sales with better margins.

Asics is sprinting ahead. It still has room to run.

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