Christie’s Restructures Classical Asian Sales to Focus on the Arts of India
4 min
Christie’s will feature classical Indian art created from the third century through the beginning of the 20th century in a standalone sale for the first time this September.
The online auction is a break with the traditional approach of including Indian, Himalayan, and Southeast Asian art in one sale and responds to collectors of modern and contemporary Indian art who are “interested in following art history backwards,” finding links in the art of recent time to the faraway past, says Tristan Bruck, head of sale.
The previous model better suited “an old-fashioned collector who was buying works in all three sub-niches,” Bruck says. “A collector who bought Indian paintings, for instance, was likely to also go out and buy a Tibetan thangka (or tapestry).”
The Arts of India sale, open from 10 a.m. Sept. 13 to 9 a.m. Sept. 27, is paying particular attention to works that transition Indian art from the classical to the modern era, a period that until now hadn’t received close attention, he says.
Christie’s Images Ltd. 2023
In the midst of the online offering, on the morning of Sept. 20, Christie’s also will hold a live sale in New York of mostly modern but also contemporary South Asian art, which is predominately from India in addition to Pakistan, Bangladesh, and Sri Lanka.
Christie’s expectation is that collectors who attend, or dial into the modern and contemporary sale via phone or online, might be intrigued to also take a look at the online sale, where earlier Indian works provide inspiration for colours, style, and themes by 20th-and 21st-century artists. The auction house will also display the works together in its Rockefeller Center galleries in New York.
Collectors “realize that this art wasn’t created in a vacuum,” says Nishad Avari, Christie’s head of South Asian modern and contemporary art. “There’s thousands of years of tradition that modern and contemporary artists in the region drew on and continue to draw from.”
Consider Maqbook Fida Husain’s Untitled (Naga), a massive work of five female figures and a serpent (or naga) painted around 1971. The painting portrays four of the women with breaks at the neck, hips, and knees, alluding to physical forms expressed in temple sculpture of the Gupta Empire from the fourth- to early sixth century, Avari says.
The painting, expected to achieve between US$700,000 and US$1 million, likely was created to commemorate the launch of a monograph of Husain’s work that was published by Harry N. Abrams, who acquired the painting, Christie’s said in a catalog note. Abrams, a vast collector who also published art and illustrated books about Old Masters through artists such as Robert Rauschenberg, had displayed the work in his offices and later in his family’s home for more than 50 years.
Courtesy of Christie’s Images Ltd. 2023
Going further back in time within the Arts of India sale is a Pichvai painting of Vishvarupa—a form of the god Krishna—painted in the 18th to 19th century. The work, originally a temple banner, is a traditional Indian form and concept, “but by the 19th century you can see artists are working with different types of perspective,” Bruck says. They are also using a more modern color palette, with vibrant pinks and blues, and the canvas is large—about six by eight feet.
“This could go in a gallery with the modern works, which are on these large canvases,” Bruck says. The painting “tells a great story alongside 20th-century work, being able to see the origin of a lot of these concepts.”
The Pichvai—a term that refers to devotional folk art paintings—is estimated to achieve at least US$120,000.
Another popular category are so-called company-school paintings that came out of India’s princely courts beginning with the imperial Mughal around 1600 through to the 19th century, when they were commissioned by British administrators, Bruck says.
Each court had its own style that may have been influenced by other courts and changed over time, he says. The works, often called miniature paintings because of the small, precise figures and scenes they depicted, were typically created in albums, or series, making them highly collectible.
Until recently, a group of collectors had focused solely on this sector somewhat in isolation, but Bruck says, Christie’s is seeing an “explosion of interest” in court painting albums, such as an illustration from the “Bharany” Ramayan series that is being offered in the upcoming sale.
A collector “can see what the other pages from that album have sold for and sort of put them together as an album in [their] mind and ideally collect more than one or try to get a few from the set,” Bruck says. The fact they exist within series also gives collectors confidence in what to pay, he adds.
Christie’s Images Ltd. 2023
The Bharany Ramayan work in the sale, titled The Monkey Army Intruding Upon a Demon’s Cave, from “Punjab Hills, Kangra or Guler, first generation after Nainsukh or Manaku,” from 1775-1780, is being offered for a minimum of US$80,000. A Patna court painting of a marriage procession at night, from around 1810 and painted in a more European style, is being offered for a minimum of US$10,000.
For many collectors, those price points are more accessible than, for example, the estimated US$250,000 they would pay for a work by Sayed Haider Raza, whose Rajasthan, 1983, is included in the modern and contemporary sale. The structure and primary-colour palette of Rajasthan, in fact, is intentionally drawn from court paintings, Avari says.
“The way in which their discrete sections, cells, in which he paints and the way in which he surrounds it with the red border is a direct reference to Pahari or Rajasthani (court) painting,” he says.
When collectors can see the court paintings that inspired a modern work they own, and they can acquire them for far less, “why not hang them side-by-side?” Avari says.
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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.
4 minA 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
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