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The most concentrated semiconductor ETFs

Two funds on one theme can hold ten names or two hundred. That is the choice this list is about, and it is not visible in either fund’s name.

The most concentrated semiconductor ETFs, ranked by the share of the fund held in its ten largest positions, as of Sep 18, 2026. Source: ETFIQ.
#TickerFundTop ten weightHoldingsNet assetsTotal return, 1Y
1SHOCStrive U.S. Semiconductor ETF77.3%30$278m+72.0%
2SMHXVanEck Fabless Semiconductor ETF74.8%22$267m+48.5%
3SMHVanEck Semiconductor ETF72.3%26$72.5bn+81.3%
4SOXQInvesco PHLX Semiconductor ETF62.9%33$3.1bn+90.6%
5SOXXiShares Semiconductor ETF62.3%34$45.4bn+99.9%
6SMHCVanEck China Semiconductor ETF60.7%30$21mtoo new
7FTXLFirst Trust Nasdaq Semiconductor ETF59.5%38$1.5bn+116.0%
8EUVCorgi Lithography & Semiconductor Photon58.2%40$419mtoo new
9CHPSXtrackers Semiconductor Select Equity ET49.5%52$118m+115.8%
10PSIInvesco Semiconductors ETF47.5%33$2.7bn+96.1%
11XSDState Street(R) SPDR(R) S&P(R) Semicondu31.4%48$3.0bn+58.2%

Method

The 11 of 11 ETFs in the semiconductors theme with a filed book, most concentrated first. Across the funds listed here the weight in the ten largest runs from 31.4% to 77.3%. Concentration is not a fault. It is how much of the fund rides on ten decisions. The ranking is the published field sorted, nothing else: no scoring, no weighting and no view on any fund. Every fund ETFIQ covers in this category is eligible, including funds that have closed, because leaving them out would flatter the category.

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Where these figures came from

ETFIQ links to the documents behind every figure. It is not affiliated with any issuer, and a link is not an endorsement.

A ranking is not a recommendation and no order on this site is an opinion. ETFIQ is an independent publisher, not an adviser. Standards and sources

Cite this page. ETFIQ, The most concentrated semiconductor ETFs, ranked by the share of the fund held in its ten largest positions, data as of Sep 18, 2026. https://etfiq.com/rankings/themes-concentrated-semis Free to use with attribution; the underlying files are at Open data.