AI Stocks Face Sharp Decline After US Midterms Spark Market Concerns

Stocks tied to artificial intelligence experienced a steep drop recently, triggered in part by the outcome of the US midterm elections where Democrats gained significant ground. This political shift has heightened worries about potential increased regulatory scrutiny on AI technologies and a possible slowdown in data center expansions, both critical factors supporting the AI sector's growth.

Before the elections, the AI trade was already facing challenges such as rising capital costs, skepticism over the vast capital expenditures without matching revenue growth, and declining cash flows among major cloud service providers who are key players in this space. The election results appear to have catalyzed the market's recognition of these risks, resulting in pronounced sell-offs.

On November 5, the tech-heavy Nasdaq-100 index saw a 6.4 percent drop, its most significant one-day decline since March 2020 when the COVID-19 pandemic first roiled markets. This single-day plunge erased $2.2 trillion in market value, the largest ever recorded for the index. Since reaching a peak on October 6, the Nasdaq-100 has surrendered over $5.2 trillion in gains, illustrating the sharp reversal in investor sentiment.

Market volatility surged as well. The CBOE Volatility Index, commonly known as the VIX, jumped by 70 percent on the same day, marking the third-highest spike in its history. This level of volatility is reminiscent of previous major market shocks like the 'Volmageddon' event in February 2018 and a December 2024 rise following an unexpectedly hawkish Federal Reserve meeting. These episodes are characterized by rapid increases in volatility leading to forced position adjustments among traders, accelerating market moves.

Unlike earlier market corrections, this downturn carries unique pressures. Elevated bond yields— with the 10-year US Treasury yield nearing 4.9 percent—imply a higher cost of capital than during the pandemic-era market crashes, where yields were near historic lows around 0.6 to 0.7 percent. This shift removes the low-rate environment that previously encouraged investors to buy dips aggressively.

The AI sector's capital intensity is also significant. Even large and cash-rich firms like Alphabet, Amazon, and Meta Platforms are seeking additional funds through debt and equity markets to finance their ambitious AI and data center projects. This increased demand for capital contributes to rising sovereign yields, which recently climbed to about 5.4 percent, squeezing investment returns and increasing financial risk.

Semiconductor companies, integral to AI hardware, were among the hardest hit. Stocks such as Sandisk, Micron, and Western Digital plunged between 17 and 22 percent on November 5 alone. Sandisk’s stock, notably, surged tenfold to $2,354 by June 2026 from just $237 at the end of 2025, only to fall back to $835 following the crash—a 66 percent decline in less than a year. This underscores the extreme volatility in this segment despite its large-cap status with a market value around $119 billion.

Other prominent chipmakers including Nvidia, SK hynix, TSMC, and Samsung Electronics have also seen their shares drop sharply, with declines ranging from 40 to 70 percent from their recent 52-week highs. The iShares Semiconductor ETF (SOXX), which tracks major semiconductor stocks, fell 12.1 percent on November 5. This was its second-worst day ever, surpassing most declines seen during the pandemic's onset.

The relative performance between semiconductor and software stocks has also shifted. The ratio comparing SOXX to the software-focused IGV ETF, which had reached a high of 250 in mid-June, retreated to about 145, reflecting a loss of semiconductor dominance in market gains. Regional benchmarks like South Korea’s KOSPI, heavily weighted by chip companies SK hynix and Samsung, also lost much of their advantage over indices like India’s Nifty.

Interestingly, despite the large declines, forward price-to-earnings ratios for memory chip manufacturers like Micron, SK hynix, Samsung, and Sandisk have dropped into single digits and are significantly lower than current P/E multiples. SK hynix’s forward multiple stands near 2 times earnings, highlighting the market’s skepticism about earnings forecasts despite expectations of strong results.

An illustrative deal during this turbulent period involved Marvell Technology, a $150 billion chip design firm, announcing the acquisition of Lumentum Holdings, a company specializing in laser and fiber-optic components, with an initial enterprise valuation of $115 billion. However, following the market downturn, Lumentum’s enterprise value fell 41 percent to $48 billion, while Marvell’s dropped 44 percent, reflecting market uncertainty over such large transactions in this environment.

Another departure from past crashes is how bond yields reacted. Typically, during equity sell-offs, investors seek safer assets like government bonds, pushing yields down. For example, in March 2020, when the Nasdaq-100 dropped over 12 percent, the 10-year Treasury yield fell by 24 basis points. On November 5, however, the yield dropped only 5 basis points, indicating less of a flight to safety and more cautious investor sentiment.

Credit markets for AI and cloud-related companies also display stress. Bonds issued by newer cloud firms such as CoreWeave and established companies like Oracle have seen their yield spreads widen compared to Treasury bonds, signaling increased concerns about their creditworthiness amid the market turmoil.

The broader economic impact of AI-related investment is substantial. In 2026’s first three quarters, real GDP growth was 2.5 percent, 2.2 percent, and 3.4 percent respectively. A large portion of this growth—between 32 and 65 percent depending on the quarter—came from private sector investments in information processing equipment and intellectual property, categories that include chips and software. Should this investment slow due to market or regulatory pressures, it could trigger an economic downturn, compounding the negative effects on market performance and consumer spending.

Political opposition to data center construction is intensifying as well. Some newly elected lawmakers advocate for halting new data center projects, which could further restrict AI infrastructure growth. Meta Platforms’ President Dina Powell McCormick has publicly commented on these challenges, emphasizing the complexities ahead.

This recent correction in AI stocks reflects deeper structural and regulatory challenges rather than a typical market pullback. Investors and market watchers are advised to approach the sector with caution, recognizing that the risks and uncertainties differ markedly from previous technology cycles.