Key Points
The VanEck Semiconductor ETF (NASDAQ: SMH) soared by 82.1% in the first half of 2026, according to the data from S&P Global Market Intelligence. It’s a fantastic performance. Still, it’s not just a story of a rising tide in semiconductors lifting all boats. There’s a lot of nuance to the sterling performance, and here’s a look at a few of them to help investors decide what to do in the second half of 2026.
The VanEck Semiconductor ETF
The passively managed ETF aims to track the performance of the MarketVector U.S. Listed Semiconductor 10% Capped Screened Index (MVIS). The MVIS tracks the performance of the top 25% of U.S.-listed semiconductor industry stocks (including equipment companies), subject to a 10% cap. The companies must derive 50% of their revenue from semiconductors or semiconductor equipment.
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It’s an interesting approach that gives the MVIS and, in turn, the VanEck ETF, broader-based exposure than a market-cap-weighted index would. That’s been a good thing for the ETF investors this year, as it means the position in Nvidia is capped at 10% and is rebalanced every quarter.
Given that Nvidia significantly underperformed the ETF in the first half, it’s a good thing that its massive market cap weighting (its current market cap is 3.7 times and 5.1 times the market cap of the top two holdings in the ETF as of 30 June, namely Micron Technology and Advanced Micro Devices) is mirrored in the MVIS, and in turn the ETF.
What Nvidia’s underperformance means to VanEck ETF investors
This fact underscores some of the dynamics in the semiconductor market this year, in which equipment makers (the ETF holds the ones shown below) have massively outperformed.
Two investing themes for 2026
Semiconductor equipment companies have outperformed due to two defining characteristics of the market in 2026. The first is that artificial intelligence (AI) spending has outpaced expectations going into the year. Since AI spending is the major driver of semiconductor demand, semiconductor companies have had to ramp up their capital spending plans in line with hyperscalers’ AI spending.
Image source: Getty Images.
Second, the nature of spending is likely to shift over time as AI-related spending does. As previously discussed, Intel has massively outperformed as demand for central processing units (CPUs) has increased relative to that for graphics processing units (GPUs). The former is used more for inference (agents running models), while the latter is used for AI model training and building. Moreover, after the initial rush to build out AI infrastructure, inference spending is likely to take over.
These kinds of insights demonstrate the benefits of diversifying across the sector, unless you are confident or knowledgeable enough to pick winners within it.
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Lee Samaha has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Advanced Micro Devices, Intel, Micron Technology, and Nvidia. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
