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.

There has rarely, if ever, been so much tech talent available in the job market. Yet many tech companies say good help is hard to find.

What gives?

U.S. colleges more than doubled the number of computer-science degrees awarded from 2013 to 2022, according to federal data. Then came round after round of layoffs at Google, Meta, Amazon, and others.

The Bureau of Labor Statistics predicts businesses will employ 6% fewer computer programmers in 2034 than they did last year.

All of this should, in theory, mean there is an ample supply of eager, capable engineers ready for hire.

But in their feverish pursuit of artificial-intelligence supremacy, employers say there aren’t enough people with the most in-demand skills. The few perceived as AI savants can command multimillion-dollar pay packages. On a second tier of AI savvy, workers can rake in close to $1 million a year .

Landing a job is tough for most everyone else.

Frustrated job seekers contend businesses could expand the AI talent pipeline with a little imagination. The argument is companies should accept that relatively few people have AI-specific experience because the technology is so new. They ought to focus on identifying candidates with transferable skills and let those people learn on the job.

Often, though, companies seem to hold out for dream candidates with deep backgrounds in machine learning. Many AI-related roles go unfilled for weeks or months—or get taken off job boards only to be reposted soon after.

Playing a different game

It is difficult to define what makes an AI all-star, but I’m sorry to report that it’s probably not whatever you’re doing.

Maybe you’re learning how to work more efficiently with the aid of ChatGPT and its robotic brethren. Perhaps you’re taking one of those innumerable AI certificate courses.

You might as well be playing pickup basketball at your local YMCA in hopes of being signed by the Los Angeles Lakers. The AI minds that companies truly covet are almost as rare as professional athletes.

“We’re talking about hundreds of people in the world, at the most,” says Cristóbal Valenzuela, chief executive of Runway, which makes AI image and video tools.

He describes it like this: Picture an AI model as a machine with 1,000 dials. The goal is to train the machine to detect patterns and predict outcomes. To do this, you have to feed it reams of data and know which dials to adjust—and by how much.

The universe of people with the right touch is confined to those with uncanny intuition, genius-level smarts or the foresight (possibly luck) to go into AI many years ago, before it was all the rage.

As a venture-backed startup with about 120 employees, Runway doesn’t necessarily vie with Silicon Valley giants for the AI job market’s version of LeBron James. But when I spoke with Valenzuela recently, his company was advertising base salaries of up to $440,000 for an engineering manager and $490,000 for a director of machine learning.

A job listing like one of these might attract 2,000 applicants in a week, Valenzuela says, and there is a decent chance he won’t pick any of them. A lot of people who claim to be AI literate merely produce “workslop”—generic, low-quality material. He spends a lot of time reading academic journals and browsing GitHub portfolios, and recruiting people whose work impresses him.

In addition to an uncommon skill set, companies trying to win in the hypercompetitive AI arena are scouting for commitment bordering on fanaticism .

Daniel Park is seeking three new members for his nine-person startup. He says he will wait a year or longer if that’s what it takes to fill roles with advertised base salaries of up to $500,000.

He’s looking for “prodigies” willing to work seven days a week. Much of the team lives together in a six-bedroom house in San Francisco.

If this sounds like a lonely existence, Park’s team members may be able to solve their own problem. His company, Pickle, aims to develop personalised AI companions akin to Tony Stark’s Jarvis in “Iron Man.”

Overlooked

James Strawn wasn’t an AI early adopter, and the father of two teenagers doesn’t want to sacrifice his personal life for a job. He is beginning to wonder whether there is still a place for people like him in the tech sector.

He was laid off over the summer after 25 years at Adobe , where he was a senior software quality-assurance engineer. Strawn, 55, started as a contractor and recalls his hiring as a leap of faith by the company.

He had been an artist and graphic designer. The managers who interviewed him figured he could use that background to help make Illustrator and other Adobe software more user-friendly.

Looking for work now, he doesn’t see the same willingness by companies to take a chance on someone whose résumé isn’t a perfect match to the job description. He’s had one interview since his layoff.

“I always thought my years of experience at a high-profile company would at least be enough to get me interviews where I could explain how I could contribute,” says Strawn, who is taking foundational AI courses. “It’s just not like that.”

The trouble for people starting out in AI—whether recent grads or job switchers like Strawn—is that companies see them as a dime a dozen.

“There’s this AI arms race, and the fact of the matter is entry-level people aren’t going to help you win it,” says Matt Massucci, CEO of the tech recruiting firm Hirewell. “There’s this concept of the 10x engineer—the one engineer who can do the work of 10. That’s what companies are really leaning into and paying for.”

He adds that companies can automate some low-level engineering tasks, which frees up more money to throw at high-end talent.

It’s a dynamic that creates a few handsomely paid haves and a lot more have-nots.

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

A divide has opened in the tech job market between those with artificial-intelligence skills and everyone else.

Playing a different game

Overlooked