Tech Valuations Slip Below Broader Market for First Time Since 2017 as AI Selloff Reshapes Stock Pricing

By the numbers, technology stocks have become cheaper than the market they were long expected to outrun. The forward price-to-earnings ratio for the S&P 500's tech sector has dropped to about 17 times, below the broader index's 18 times. It is the first time that has happened since 2017, and it follows a sharp selloff tied to artificial intelligence.

Keith Lerner, chief investment officer at Truist Wealth, flagged the reversal in a report published this week. At its peak in October 2025, the sector's forward multiple had reached as high as 32. "The 32x multiple last year meant the market had already priced in a lot of good news," Lerner wrote. With the multiple now nearly halved, he said, "you could argue the market has also priced in a lot of bad news."

The drop came fast. Wall Street was still enjoying a rally the day after the midterm elections when Thursday brought the heaviest single-day decline in tech stocks since the 2020 COVID crash. The damage was uneven, though. Outside AI-related names, most individual stocks held up fairly well. The equal-weighted S&P 500 hit a record high on Wednesday and finished the week within about 1% of where it began. The cap-weighted benchmarks, which lean heavily on the biggest tech companies, fared worse: the S&P 500 and the Nasdaq Composite each fell about 3% for the week, their fourth straight weekly decline.

Chipmakers took the worst of it. The Philadelphia Semiconductor Index has fallen five weeks in a row, losing nearly 30% over the stretch. Micron and Sandisk each dropped more than 20% in this week alone. Lerner described "a bit of a buyer's strike" in tech and noted that chips are the area most exposed to any slowdown in data-center construction, a worry that has hung over the market through the election period. He also offered a counterpoint. A slower buildout could relieve the cash drain on a handful of the largest AI spenders. "If this forces a bit of a slower pace and potentially has some positive impact on cash flow, I think it could actually extend the cycle," he said.

Truist Wealth recommends staying overweight U.S. large caps while adding small caps, partly as a hedge against a sharp rotation away from mega-cap tech. The firm also pointed out that the stock market has risen in every year following a midterm election since 1946. Other history is mixed in a more useful way. Since 1990, the S&P 500 has had four or more consecutive weekly declines 33 times. By industry calculations, the index was higher three months later about 80% of the time, with a median gain of 6%, against roughly 3% after a typical week. The exceptions were the dot-com bust and the 2008 financial crisis, when stocks kept falling over the following year.

Not everyone is buying. Michael Martin, founder of TraderMindset.com, says it is time to cash out. "I don't see these as buying opportunities — everything is in a downtrend," he said, adding that falling share prices "don't mean better investment value." He would make only small, tentative call-option purchases if the S&P 500 holds its 200-day moving average. Lerner sees the setup differently: "We're moving toward a situation where a little bit of good news could have an outsized impact."

Friday brought some relief. The S&P 500 rose 23.13 points, or 0.31%, to 7,376.86, and the Nasdaq Composite gained 264.43 points, or 1.09%, to 24,579.42. The Philadelphia Semiconductor Index jumped 379.11 points, or 4.21%, to 9,390.25. The Dow Jones Industrial Average slipped 237.33 points, or 0.46%, to 51,285.73.

Sentiment remains fragile. Reports say Microsoft is trimming its list of "neocloud" partners, concentrating on a few key suppliers and building out its own data centers, which feeds concern that U.S. AI infrastructure spending is slowing. Some Democratic lawmakers and governors-elect have also taken a more cautious line on data-center construction, and the newly elected officials do not take office until January. What happens next depends on the pace of AI capital spending and on how clear the policy picture becomes.