Luxury Brands Are in a Winner-Takes-All Phase

Louis Vuitton’s owner designed the medals for the Paris Olympic Games. It can’t be easy to see rival Hermès make off with gold in the second-quarter sales heat.

France’s three most powerful luxury-goods companies reported very mixed second-quarter results last week. On Tuesday, LVMH Moët Hennessy Louis Vuitton said sales in the three months through June rose by a disappointing 1% compared with the same period last year. Gucci owner Kering followed with an 11% fall for the quarter and issued a profit warning. Hermès left its competitors in the dust with a 13% increase in sales over the same period.

Hermès captured more than 100% of the incremental growth in the industry in the latest quarter. Luxury shoppers spent €440 million—equivalent to $477.6 million at current exchange rates—more in the French brand’s stores than they did in the same period of last year. They spent €400 million less on all other luxury brands combined, based on analysis by Bank of America.

This points to a double whammy for high-end brands, which face challenges at both ends of the consumer spectrum they serve.

It has been clear for months that middle-class shoppers in the U.S. and China, the luxury industry’s two most important markets, have reined in their purchasing.

Chinese consumers are saving rather than spending because the value of their homes is falling. Lower-income and middle-income Americans who developed a taste for luxury during the pandemic have pulled back sharply as they have burned through excess savings.

Now, wealthy consumers, too, seem to be getting choosier about which brands they will and won’t buy. Hermès Chief Executive Axel Dumas said there is a “flight to quality” under way in the luxury industry. This shift is benefiting the Birkin handbag maker , which has a reputation for timeless designs.

Chinese buyers in particular are avoiding flashy and logo-heavy brands as worries about the country’s economy and real-estate challenges grow.

Jewellery sales are also holding up as shoppers look for goods that are more likely to hold their value than clothing or handbags. Cartier’s owner Richemont said its jewellery sales rose 4% in the quarter, although the company’s overall sales were weighed down by weak demand for its watch and fashion brands. Kering jewellery labels Boucheron and Pomellato were rare bright spots in its portfolio.

The outlook is harsh for brands such as Gucci and Burberry that are in turnaround mode. The latter issued a profit warning earlier this month and replaced its CEO in an admission that a years-long push to make the British trench-coat maker more exclusive had failed. Its shares have fallen to levels not seen since 2010.

Both brands face an uphill battle to lure shoppers. Neither Gucci nor Burberry is known for the classic designs now in vogue. The labels might also have exacerbated the slump, as the sharp price increases that luxury brands implemented in recent years have sidelined aspirational shoppers.

Luxury stocks are diverging. Shares in Richemont and Hermès have gained 15% and 8% respectively so far this year, with everyone else in the red.

Investors are taking their cue from wealthy shoppers: In troubled times, the most exclusive brands are the safest bet.

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