DeepSeek Deep Sixes the Stock Market. How Far the S&P 500 Could Fall

DeepSeek just might derail the stock market’s rally.

The S&P 500 hasn’t had a correction , a 10% pullback from a high, since October 2023. Investors kept buying throughout 2024 despite angst surrounding the Federal Reserve and interest rates, not to mention numerous international concerns.

But now, worries about cheaper artificial intelligence models from the Chinese-developed app named DeepSeek may be the excuse that investors were waiting for to finally sell shares in earnest. Stocks plunged Monday .

The declines were biggest in ing tech companies, such as Nvidia , Broadcom and Microsoft . But other sectors, namely manufacturing and the utility or energy stocks that have big ties to the AI theme, were hit hard as well

The S&P 500 and Nasdaq Composite tumbled 1.5% and more than 3% respectively. The Dow Jones Industrial Average , which is less exposed to tech, gained nearly 300 points, or 0.7% .

The market is now closer to correction territory than it has been since August , when worries about a surge in the value of the Japanese yen versus the dollar spooked investors and led to a spike in volatility. But the major stock indexes still have a way to go before the declines from their peaks reach 10%.

The S&P 500 ended Monday at around 6012 , putting it just 2% below its record high. The blue-chip index would need to fall another 8% to just above 5500 to reach correction status. The Nasdaq is closer: It has fallen more than 4% from its peak and is 6% above the correction- territory level of 18,156.50.

But even before Monday’s DeepSeek bombshell, there were growing concerns that stocks may head into a correction. Barry Bannister, chief equity strategist at Stifel, recently reiterated a July call for the S&P 500 to fall 10% from its peak. He thinks it will drop to about 5500 later this year.

Bannister has been fairly bearish for the better part of a year. He said in a report Sunday that there is too much optimism about fiscal stimulus from President Donald Trump; the notion of American exceptionalism, or that stocks here have better prospects because the U.S. economy is more innovative and entrepreneurial; and hype about the Magnificent Seven of tech.

Bannister worries that core inflation and longer-term bond yields will remain higher for longer, creating a “a mild case of stagflation”—the dreaded combination of stagnant growth and persistent inflation. That may mean fewer Fed rate interest-rate cuts until the economy actually weakens, “which itself is not bullish,” Bannister wrote.

Trump’s threat of tariffs and stricter immigration policies, which would boost the cost of imported goods and potentially drive wages higher by curtailing the supply of labor, may also stoke fear of more persistent inflation.

So what should investors do now?

Bannister argues that “defensive value” stocks, such as healthcare and consumer staples companies, should outperform. Investors seem to agree: Both the Health Care Select Sector SPDR and the Consumer Staples Select Sector SPDR exchange-traded funds were up more than 2% as the broader market fell on Monday.

Bannister likes utilities too, but that sector is trickier. The group as a whole sank Monday, led lower by significant drops in Vistra and Constellation Energy , the two utilities that have gotten the biggest boost from AI’s demand for energy. But shares of classic, less exciting, regulated utilities, such as Duke Energy, Dominion Energy, and Xcel Energy , rallied. All three stocks have big dividend yields.

Dividend payers across all sectors could hold up better in a suddenly more volatile market. Simeon Hyman, global investment strategist with ProShares , told Barron’s that companies that pay dividends tend to be more stable. Companies may pull back on plans to buy back more stock or invest in their future if conditions change, but with rare exceptions “once you commit to dividend growth, you stick with it,” he said.

The SPDR S&P Dividend ETF and ProShares S&P 500 Dividend Aristocrats ETF , which recently added FactSet Research System , Erie Indemnity , and Eversource Energy to the fund, were both up nearly 2% Monday.

Still, even investors in dividend stocks need to be wary. There could be more downside ahead for the broader market. Simply put, stocks are arguably long overdue for a correction.

“The last time the market entered an official correction was 309 trading days ago, spanning well beyond the average number of 173 trading days without a correction since 1928,” Adam Turnquist, chief technical strategist for LPL Financial , said in a report last week.

There is a case to be made that there was too much optimism on the part of investors. Katie Stockton, founder and managing partner of Fairlead Strategies, noted that the Cboe Volatility Index, known as Wall Street’s fear gauge, recently fell to levels in the midteens from a three-month high of nearly 28 in mid-December. She thinks a VIX reading that low was reflecting complacency. The VIX surged to just under 20 Monday.

Stockton now thinks that Monday’s market pullback could lead to more downside for the next few weeks. She said investors should keep an eye on two key technical support levels for the S&P 500: the closing level of about 5783 that it traded at on Election Day, and if stocks dip below that, the 200-day moving average of 5608.

Remember, the level that would bring the market into correction territory is just above 5500, in flirting distance from the 200-day average.

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