In June 2026, global technology stocks underwent a notable divergence. The semiconductor sector, represented by the VanEck Semiconductor ETF (SMH), faced intense selling pressure, while the Invesco QQQ Trust (QQQ), which tracks the Nasdaq 100, also declined but to a much lesser extent. For the week ending June 24, SMH posted a cumulative drop of over 5%, while the Nasdaq 100 Index fell less than 3% during the same period. On June 23 alone, SMH plunged 7%, marking its largest single-day loss of the year, while QQQ closed down about 3%. This underperformance by semiconductor ETFs relative to the Nasdaq wasn’t just a broad market correction—it was the concentrated release of structural risks within the semiconductor sector.
Both SMH and QQQ are exposed to macro risks in the technology sector, so why did SMH fall so much more sharply? Is this outsized decline a temporary phenomenon, or is it an inherent, independent downside risk for semiconductor ETFs under certain macro conditions? By analyzing SMH’s concentration of holdings, marginal changes in AI spending expectations, and valuation levels, we can build a framework for understanding the unique risk factors and allocation value of semiconductor ETFs.
Where Does SMH’s Independent Downside Risk Come From?
The fundamental difference between SMH and QQQ lies in the concentration of their underlying assets. QQQ tracks the Nasdaq 100 Index, covering 100 large-cap, non-financial tech companies across various industries—semiconductors, software, internet services, consumer electronics, and more. SMH, by contrast, is a pure-play semiconductor ETF, with its holdings highly concentrated in global chip leaders like NVIDIA, TSMC, Broadcom, AMD, and Micron. This concentration drives excess returns during bull cycles but amplifies risk during downturns.
The recent underperformance of semiconductor ETFs in June 2026 was driven by multiple semiconductor-specific risk factors acting in concert.
First, a marginal downward revision in AI infrastructure spending expectations. In early June, Broadcom released its fiscal Q2 2026 earnings report, guiding AI semiconductor revenue for Q3 at $16 billion—below Wall Street’s consensus estimate of $17.2 billion, a gap of about $1.2 billion (roughly 7%). Broadcom also projected full-year AI chip sales at $56 billion, again below the previous analyst average of $57.6 billion. As the second most important player in AI chips after NVIDIA, Broadcom’s guidance cut was interpreted by the market as a signal that the pace of AI infrastructure investment might be slowing. This expectation gap triggered a chain reaction in the semiconductor sector: NVIDIA dropped about 6%, wiping out more than $300 billion in market cap in a single day; AMD fell nearly 11%; Micron plunged over 13%. Broadcom’s own stock fell 11% to 13% in after-hours trading.
Second, cross-market contagion from the collapse in Korean tech stocks. On June 23, Korea’s KOSPI Index suffered a sharp selloff, with foreign institutional investors dumping about $2.5 billion in KOSPI stocks. Samsung Electronics and SK Hynix—two global leaders in memory chips—saw steep declines. This selloff quickly spread to US semiconductor ETFs, with SMH plunging 7% that day. The volatility in Korea reflected global investor concerns about the cyclical peak in semiconductors, and SMH, as a collection of global semiconductor leaders, had virtually no immunity to this cross-market risk.
Third, the amplifying effect of leveraged products. As SMH fell, the Direxion Daily Semiconductor Bull 3x ETF (SOXL) tumbled about 23% in a single day, highlighting the magnifying effect of daily-reset leverage. Forced liquidations in leveraged ETFs further intensified selling pressure in the semiconductor sector, creating a downward spiral. This derivative-driven downside pressure was much milder in the broader tech sector represented by QQQ.
The combination of these three risk factors explains why SMH’s single-day drop of 7% on June 23 was more than double QQQ’s roughly 3% decline.
How QQQ’s Diversification Acts as a Cushion
In contrast to SMH’s high concentration, QQQ’s diversified industry exposure provided a significant buffer during this selloff.
QQQ tracks the Nasdaq 100 Index, and although the weight of semiconductor companies in its holdings has increased in recent years due to the AI boom, it remains diluted by software services, internet platforms, consumer electronics, biotech, and other sectors. When the semiconductor sector faces systemic selling, QQQ’s non-semiconductor components—like Microsoft, Apple, Amazon, and Google—are also affected by market sentiment, but their fundamentals are less tied to AI chip spending expectations, making their declines more manageable.
On June 23, the Nasdaq 100 Index fell 3.3%, while SMH plunged 7%. This means SMH’s excess decline was about 3.7 percentage points. Given SMH’s weighting within QQQ, this excess drop directly reflects the independent downside risk of the semiconductor sector relative to the broader Nasdaq 100.
Additionally, QQQ’s options market also saw a surge in put volume—of QQQ’s $3.7 billion in options trading volume, about $2.5 billion was in puts—but the absolute scale, relative to QQQ’s market cap, was much less impactful than SMH’s options market was to SMH itself. In SMH’s hundreds of millions in options premium, puts accounted for an unusually high proportion. This structural difference in the derivatives market further amplified SMH’s vulnerability during declines.
The Allocation Value of Semiconductor ETFs: Balancing Independent Risk and Long-Term Trends
SMH’s independent downside risk doesn’t mean it lacks allocation value. On the contrary, understanding these risk factors is essential for developing a sound allocation strategy.
From a long-term perspective, the structural drivers of the semiconductor industry haven’t disappeared following June’s selloff. The AI supercycle remains intact—core demand drivers like GPUs for model training and inference, HBM memory, advanced packaging and wafer foundry expansion (led by TSMC), and fiber network growth are all still strong. SMH represents the infrastructure layer of the AI economy. As AI transitions from the infrastructure phase to the deployment phase, growth may slow, but the absolute scale continues to expand.
Fundstrat’s Head of Research, Tom Lee, noted on June 24 that historically, when SMH and SOXX experience such large single-day drops, the probability of positive returns in the following month is as high as 88%. This statistical pattern is validated across multiple market cycles, including the 35% drop in semiconductors in 2022 followed by a rebound, and the sector’s more than doubling in the 18 months after the 2020 pandemic. Lee argues that an 88% win rate suggests that sharp selloffs often attract buyers—markets view these declines as overreactions and buying opportunities.
However, historical patterns don’t guarantee future performance. Currently, SMH’s valuation remains elevated. According to GuruFocus’s GF Value model, SMH’s current price is around $622.68, while its estimated intrinsic value is about $372.81—a premium of roughly 67%. SMH’s trailing P/E ratio (TTM) is about 15.2x, while its forward P/E is as high as 40.71x. This huge gap in P/E ratios means the market has priced in extremely aggressive growth expectations—any signal falling short could trigger a valuation contraction.
Therefore, SMH’s allocation value requires balancing two dimensions: long-term structural growth driven by AI, and the independent downside risk from high valuations and concentration. For investors seeking tech sector exposure, SMH offers the purest semiconductor beta, but at the cost of much higher sector-specific volatility than QQQ.
Conclusion
The divergence between SMH and QQQ in June 2026 wasn’t random market sentiment—it was a concentrated reflection of unique risk factors in the semiconductor industry. Broadcom’s disappointing AI revenue guidance triggered a reassessment of the sustainability of AI infrastructure spending; the collapse in Korean tech stocks exposed the global interconnectedness and fragility of the semiconductor supply chain; leveraged products amplified the severity of the decline. Together, these factors form SMH’s independent downside risk relative to QQQ—a type of volatility that can’t be eliminated through diversification at the sector level.
For investors, understanding the differences in risk-return characteristics between SMH and QQQ is fundamental to allocation decisions. SMH is the purest beta tool for the semiconductor sector, capable of delivering significant excess returns during the AI supercycle’s upswing—from early 2026 to June 3, SMH surged from $360 to $638, a gain of 77%. But during downturns, its concentration and high valuation make it the focal point for risk release. QQQ, meanwhile, offers broader tech sector exposure, sacrificing some upside for relative downside protection.
The two aren’t substitutes—they serve different roles in a portfolio. SMH is best used as a satellite allocation, playing an aggressive role whose weighting should match the investor’s tolerance for semiconductor-specific risk. QQQ is better suited as a core allocation, providing more stable tech sector beta and balanced risk exposure across market environments. As the AI supercycle continues but valuations remain elevated, this distinction in allocation logic is more relevant than ever.
FAQ
Q1: What are the main differences between SMH and QQQ?
SMH (VanEck Semiconductor ETF) is a pure-play semiconductor ETF, with holdings concentrated in global chip leaders like NVIDIA, TSMC, Broadcom, and AMD—making it highly sector-focused. QQQ (Invesco QQQ Trust) tracks the Nasdaq 100 Index, covering 100 large-cap, non-financial tech companies across a broader range of industries, including software, internet, consumer electronics, and more, with significantly greater diversification.
Q2: Why did SMH underperform QQQ so sharply in June 2026?
On June 23, SMH plunged 7% in a single day, while QQQ fell about 3%. Key reasons include: Broadcom’s AI revenue guidance falling short of expectations, triggering a sector revaluation; the collapse in Korean tech stocks spreading to US chip stocks; and the amplifying effect of leveraged ETFs increasing selling pressure. These factors hit the highly concentrated SMH much harder than the more diversified QQQ.
Q3: Is SMH currently overvalued?
According to GuruFocus’s GF Value model, SMH’s current price is about $622.68, while its estimated intrinsic value is $372.81—a premium of roughly 67%. Its trailing P/E is about 15.2x, and its forward P/E is as high as 40.71x, indicating the market has priced in very aggressive future growth expectations, creating risk of valuation contraction.
Q4: Does the long-term growth thesis for semiconductors still hold?
The core drivers of the AI supercycle remain intact—GPU demand, HBM memory, advanced packaging and wafer foundry expansion, and other long-term trends are unchanged. The market is transitioning from the AI infrastructure phase to the deployment phase, with growth expectations normalizing from extremely high levels. The long-term structural growth thesis is intact, but short-term volatility and valuation resets are inevitable.
Q5: How should investors allocate between SMH and QQQ?
SMH is best used as a satellite allocation, playing an aggressive role whose weighting should match the investor’s tolerance for semiconductor-specific risk. QQQ is better suited as a core allocation, providing more stable tech sector beta. The two aren’t substitutes—they serve different portfolio functions. As the AI supercycle continues but valuations remain elevated, distinguishing between these roles is especially important.
