A fresh round of U.S. export restrictions on China’s AI capabilities has caught NVIDIA Corp. (NASDAQ:NVDA) off guard, with ETFs with high exposure to the chip giant are feeling the pain (or gain, in some cases). While Nvidia plummeted 6.87% by market close Wednesday, some semiconductor-themed ETFs moved sharply.
The unexpected regulatory shock, preventing Nvidia from sending its high-margin H20 AI chips to China, has triggered a broader selloff in the tech-heavy sector, rekindling arguments on geopolitical risk, earnings visibility, and the role of ETFs in escalating such shocks.
Advanced Micro Devices Inc.’s (NASDAQ:AMD) MI308 chips also come under the new licensing regime and fell 6%, adding to the broader pressure across chipmakers.
ETF Reaction: Bloodbath For Some, Jackpot For Others
The ripple effects were most apparent in semiconductor and Nvidia-focused ETFs, many of which took deep intraday losses -- while inverse products registered explosive gains.
GraniteShares 2x Short NVDA Daily ETF (NASDAQ:NVD) skyrocketed more than 13% on Wednesday, with short selling in Nvidia paying off during the rout. The fund, providing 2x inverse daily leverage on Nvidia’s stock, has been a most significant volatility trade during earnings and regulatory events.
Strive U.S. Semiconductor ETF (NYSE:SHOC) fell over 4%. SHOC, with its heavy weighting in fabless semiconductor companies such as Nvidia (23% weightage) and AMD (4.74% weightage), is especially susceptible to revenue shock from export policy shifts.
VanEck Fabless Semiconductor ETF (NASDAQ:SMHX) fell more than 3%, following the general market jitters. Nvidia is one of the key holdings in SMHX, with the biggest weightage of 21.4%, making it extremely sensitive to any slowdown in AI chip sales.
These movements represent how closely ETFs have become tied to a few megacap tech narratives -- rendering them both effective and vulnerable vehicles for sector bets.
What Happened?
Markets soured on Wednesday following the U.S. government’s decision to tighten AI chip exports to China and arms-embargoed countries. Nvidia, whose H20 chips were specifically designed to meet prior export controls, announced that it will incur a $5.5 billion charge for excess inventory, purchase commitments, and reserves -- essentially discounting the failure of its China-facing H20 strategy.
Crafted specifically to meet previous export regulations under the Biden administration, the H20 chip was made China-sale-specific and had enabled Nvidia to keep a firm grip on the market despite continued tensions. In 2024 alone, the chips were estimated to have brought in $12 billion to $15 billion in revenue.
The new measures now make the old playbook dated. AMD also conceded the blow in a Wednesday report, cautioning that restrictions on its MI308 chips could generate an $800 million revenue blow.
The new regulations -- universally regarded as a crackdown on loopholes -- will likely impact Nvidia’s fiscal 2026 revenue by 6%–10%, Bank of America analyst Vivek Arya estimated. While Arya labeled the risks “manageable” and reaffirmed a Buy rating with a $160 price target, the market reaction was swift and severe.
Also Read: Chip Shock: 3 Hot Semiconductor ETFs To Watch As Trump’s Tariff Bomb Ticks
What’s Next For Nvidia-Focused Funds?
In spite of the carnage on the day, some analysts are of the view that the sell-off can provide a tactical entry. Bank of America’s Arya noted Nvidia is currently trading at about 20 times estimated 2025 earnings -- less than its historical valuation range of 23x–25x -- and that its future GB300 Blackwell Ultra chips have the potential to re-spark the growth story by the second half of 2025.
Yet, near-term volatility is unlikely to fade, especially with geopolitics now a key driver of chipmaker valuations.
ETF investors, meanwhile, face a tough balancing act: whether to double down on U.S. AI chip dominance or hedge against further policy shocks that could derail near-term earnings.
One thing is clear -- Nvidia's dominance may still be intact, but its ETF exposure just made a lot more complicated.
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