Louis Vuitton Owner LVMH Closes Year-End Quarter With Weak Sales Growth
French luxury-goods giant’s results are a sign that shoppers weren’t splurging on its collections of high-end garments in the run-up to the holiday season.
French luxury-goods giant’s results are a sign that shoppers weren’t splurging on its collections of high-end garments in the run-up to the holiday season.
LVMH Moët Hennessy Louis Vuitton wrapped up last year’s final quarter with sluggish sales growth, a sign that shoppers weren’t splurging on its collections of high-end garments and handbags in the run-up to the holiday season.
The French luxury-goods giant posted fourth-quarter sales of 22.72 billion euros ($27 billion), up 1% organically. Analysts had forecast €22.59 billion in sales and an organic decline of 0.3%, according to Visible Alpha.
LVMH’s fashion and leather goods division, which houses brands like Louis Vuitton and Dior, contributed €10.16 billion in sales, down 3% organically.
Sales at perfumes and cosmetics declined 1%, while the wines and spirits division reported a 9% contraction in sales. Selective retailing, the unit behind Sephora, fared better, with a 7% increase in sales, while watches and jewelry logged 8% growth.
For LVMH and the wider luxury-goods sector, the final quarter represents a key test of customers’ willingness to indulge on nonessential items in the run-up to Black Friday, Thanksgiving and Christmas.
Earlier this month, British trench-coat maker Burberry Group , Italian luxury-fashion house Brunello Cucinelli and Cartier owner Cie. Financière Richemont all reported higher sales for the quarter, raising the bar for industry bellwether LVMH.
Weak sales growth shows that LVMH’s collections aren’t appealing to clients and that the group is still contending with a slowdown in spending for luxury goods that has plagued the industry for years.
Demand weakened considerably after a postpandemic boom, especially among less affluent shoppers. The downturn has been particularly acute in China—a key market for LVMH and its rivals—as shoppers there have been holding back spending.
Last year brought a dose of uncertainty for LVMH and the sector as it took several months for the European Union to reach a trade deal with the U.S. after President Trump announced his Liberation Day tariffs.
Luxury goods are particularly sensitive to trans-Atlantic trade frictions and the specter of tariffs has never fully disappeared despite that trade deal.
Last week, LVMH and other luxury stocks slumped after Trump threatened 10% levies on various European countries he said were opposed to a U.S. takeover of Greenland. He subsequently called off those tariffs.
LVMH closed 2025 with €80.81 billion in annual sales, down 1% organically. Analysts had forecast €80.65 billion in 2025 sales with a 1.8% organic decline, according to Visible Alpha.
The group said revenue declined in Europe in the second half of the year, while the U.S. benefited from solid demand.
Sales in Japan were down from 2024, but the company said it had seen a noticeable improvement in trends in the rest of Asia, citing a return to growth in the second half of the year.
In an earnings call, executives expressed confidence for 2026 despite an uncertain geopolitical and macroeconomic environment, saying the positive trends they started to see in the second half were still there.
Net profit slid 13% on year to €10.88 billion, while profit from recurring operations fell 9% to nearly €17.76 billion. Analysts had forecast net profit of 10.55 billion euros and profit from recurring operations of €17.15 billion, according to Visible Alpha.
The group said it would propose a dividend of €13 a share at its shareholders’ meeting on April 23, the same as the previous year.
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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.
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.
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.
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.
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.
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.
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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