Jewels Created for Princess Diana Going up for Auction in New York

A diamond and South Sea pearl necklace and pair of matching earrings created for the late Princess Diana—and worn by her just once, at a 1997 English National Ballet performance—will go up for auction in June and could fetch as much as US$15 million.

The auction will take place not long after the coronation of Diana’s ex-husband, Charles, who will become king in a ceremony on Saturday at Westminster Abbey in London.

The necklace has clusters of pearls and 178 diamonds. Courtesy of Guernsey’s

New York-based auctioneers Guernsey’s will oversee the sale at Manhattan’s Pierre Hotel on June 27, according to a news release. The jewels were speculated to have been commissioned by Dodi Fayed, Diana’s paramour, before the couple perished in an August 1997 car crash, a Guernsey spokesperson said.

Along with its clusters of pearls and 178 diamonds, the necklace is significant because of Diana’s mystique—and the scarcity of her possessions on the market, according to Arlan Ettinger, president and founder of Guernsey’s.

“This is the only major jewellery of Diana’s that will ever be sold,” Ettinger says. “The family is not about to start parting with treasured items from their late mother.”

The prized jewels are being sold by Mark Ginzburg, a Ukrainian real-estate developer who bought them in 2009 at Guernsey’s and now is being forced to sell because of the war against Russia

Guernsey’s declined to disclose how much Ginzburg for the set.

One report, however, said Ginzburg paid US$632,000, which Penta couldn’t independently confirm.

“The family’s success in Ukraine enabled them to buy the jewels, but their business has been largely devastated by the war,” Ettinger says. “This is a motivated sale.”

The Crown Jeweller, which has created baubles for the Royal Family for centuries and at the time was the venerable British jeweler Garrard, designed the necklace for Diana after meeting with her in early 1997, according to Guernsey’s. Two years after Diana’s death, her family authorised the Crown Jeweller to sell the necklace.

Diana “didn’t have much in the way of jewelry while she was princess,” Ettinger says. “Most of what she wore was jewellery owned by the crown, given for an occasion, but not permanently.” Once Diana divorced then-Prince Charles, “she emerged as her own woman, and the fact that the Crown Jeweller created this for her is a big deal.”

Once the necklace was completed, Diana wore it to a June 3, 1997, premiere of Swan Lake by the English National Ballet. She returned the necklace to the jeweller after the ballet so he could complete a set of matching earrings, although Diana never had a chance to wear them, Guernsey said.

“It has been said that the Princess of Wales—who was also England’s Patron of Dance—was photographed more often on that occasion than at any other time of her life, with the exception of her wedding day,” according to Guernsey’s.

Next month’s sale will mark the third time the necklace has changed hands. Ettinger handled the first sale in 1999; the buyer was Houston furniture magnate James McIngvale. Ten years later, McIngvale put the necklace up for auction with Ettinger and Guernsey’s, which is when Ginzburg bought it.

The diamonds and pearls on their own “are intrinsically worth at least US$1 million to US$1.5 million,” Ettinger says. “But what they’re worth on the market is hard to predict.”

He estimated the necklace may sell for anywhere from US$5 million to US$15 million, though there was no official range provided by the auction house.

“This is connected to someone who was one of the most admired and accomplished women in the world,” Ettinger says.

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