In the AI-driven market environment, investors seek targeted exposure to high-growth technology themes. The MAGS and SMH ETFs provide alternative pathways within overlapping tech ecosystems. MAGS offers equal-weight access to the Magnificent Seven stocks—dominant innovators in cloud, software, social media, e-commerce, hardware, and AI—while SMH delivers precise semiconductor sector exposure critical to AI infrastructure. Though not direct competitors, they appeal to investors balancing concentrated mega-cap leadership against specialized chip industry dynamics. Comparing them reveals trade-offs in diversification, cost, and positioning amid surging AI demand and sector rotation.
The Roundhill Magnificent Seven ETF (MAGS) is an actively managed fund launched in April 2023, seeking capital growth through equal-weight exposure to Alphabet (GOOGL), Amazon (AMZN), Apple (AAPL), Meta Platforms (META), Microsoft (MSFT), NVIDIA (NVDA), and Tesla (TSLA). It rebalances quarterly to maintain roughly 14% per holding, using total return swaps alongside direct equities and Treasury collateral for Regulated Investment Company (RIC) diversification compliance.
Top holdings typically include each at ~14%, with recent weights around 14.3% for NVDA and similar for peers. Sector allocation spans information technology (~43%), communication services (~29%), and consumer discretionary (~29%). The gross expense ratio is 0.30%, with AUM near $4.8B. As a non-diversified, thematic ETF, MAGS emphasizes tax efficiency and liquidity for traders, distinguishing it via precise mega-cap tech purity without broader index dilution.
The VanEck Semiconductor ETF (SMH) is a passively managed fund inception December 2011, tracking the MVIS US Listed Semiconductor 25 Index of the largest, most liquid U.S.-listed semiconductor firms involved in production and equipment. It holds 26 companies in a market-cap-weighted structure, with top holdings like NVIDIA (NVDA) at ~17%, Taiwan Semiconductor (~10%), Broadcom (AVGO) (~8%), Intel (INTC) (~7%), and AMD (AMD) (~7%). Top 10 comprise ~72%.
Sector allocation is 100% technology (semiconductors). The expense ratio is 0.35%, AUM exceeds $65B, supporting exceptional liquidity. Non-diversified by design, SMH focuses on industry leaders, with turnover around 12%, capturing the full chip ecosystem from design to manufacturing equipment without leverage or active overlays.
The technology sector, particularly semiconductors, thrives amid an AI supercycle. Forecasts project global semiconductor revenues surpassing $1 trillion in 2026, up over 50% year-over-year, driven by AI infrastructure, high-bandwidth memory (HBM), and hyperscaler capital expenditures nearing $600B. Catalysts include generative AI chip demand (~30% of revenues), data center expansions, and advanced packaging innovations. Capital flows favor AI enablers, with memory and logic segments accelerating 30%+.
Macro drivers like sustained hyperscaler investments outweigh risks such as supply chain bottlenecks, geopolitical tensions over Taiwan, and cyclical downturns in autos/consumer electronics. Regulatory scrutiny on AI ethics and energy use adds caution, but sector momentum persists, benefiting pure-play chip exposure while mega-cap tech leverages ecosystem dominance.
In recent months, SMH has demonstrated stronger relative positioning, propelled by semiconductor momentum in AI accelerators and memory amid hyperscaler buildouts. Broader cycles favor SMH's concentrated exposure to chip leaders like NVDA and TSM, outpacing MAGS during sector rotations toward hardware infrastructure.
MAGS, balancing laggards like TSLA via quarterly rebalancing, exhibits lower volatility but trails in pure semi upswings, reflecting diversified tech drivers including software/cloud. Both correlate (~0.7), yet SMH's market-cap tilt amplifies leaders, while MAGS' equal-weight mitigates single-stock drawdowns. Interest rate stability and AI earnings cycles sustain semi outperformance, though MAGS offers resilience in broader tech rotations.
Tickeron’s AI Screener is an AI-powered stock and ETF discovery tool that helps traders and investors filter the market based on technical patterns, fundamentals, trends, volatility, and AI-driven signals. Users can scan thousands of stocks and ETFs using customizable filters such as industry, market capitalization (market cap), technical indicators, price patterns, and performance metrics. The screener identifies trade ideas, trending stocks, breakout candidates, and market opportunities more efficiently than manual screening, empowering data-driven decisions across asset classes. Explore it today to uncover hidden gems in tech and beyond.
Tickeron’s AI currently favors SMH with moderate conviction (~65% probability edge). Its structural purity in semiconductors aligns with AI infrastructure momentum, broader 26-holding diversification within the sector, and superior trend consistency amid hyperscaler flows. While MAGS excels in cost efficiency and mega-cap balance, SMH's focused exposure and liquidity better capture current sector tailwinds, albeit with elevated volatility from cap-weighting.
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| MAGS | SMH | MAGS / SMH | |
| Gain YTD | -4.275 | 72.729 | -6% |
| Net Assets | 3.37B | 78.4B | 4% |
| Total Expense Ratio | 0.30 | 0.35 | 86% |
| Turnover | 27.00 | 12.00 | 225% |
| Yield | 1.38 | 0.18 | 749% |
| Fund Existence | 3 years | 15 years | - |
| MAGS | SMH | |
|---|---|---|
| RSI ODDS (%) | 2 days ago 87% | 2 days ago 81% |
| Stochastic ODDS (%) | 2 days ago 90% | 2 days ago 85% |
| Momentum ODDS (%) | 2 days ago 78% | 2 days ago 89% |
| MACD ODDS (%) | 3 days ago 86% | 2 days ago 90% |
| TrendWeek ODDS (%) | 2 days ago 78% | 2 days ago 86% |
| TrendMonth ODDS (%) | 2 days ago 86% | 2 days ago 90% |
| Advances ODDS (%) | 28 days ago 90% | 3 days ago 90% |
| Declines ODDS (%) | 2 days ago 76% | 15 days ago 82% |
| BollingerBands ODDS (%) | 2 days ago 90% | 2 days ago 77% |
| Aroon ODDS (%) | 2 days ago 88% | 2 days ago 90% |
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A.I.dvisor indicates that over the last year, SMH has been closely correlated with LRCX. These tickers have moved in lockstep 86% of the time. This A.I.-generated data suggests there is a high statistical probability that if SMH jumps, then LRCX could also see price increases.
| Ticker / NAME | Correlation To SMH | 1D Price Change % | ||
|---|---|---|---|---|
| SMH | 100% | -7.01% | ||
| LRCX - SMH | 86% Closely correlated | -9.33% | ||
| KLAC - SMH | 83% Closely correlated | -9.17% | ||
| AMAT - SMH | 83% Closely correlated | -8.48% | ||
| TSM - SMH | 81% Closely correlated | -6.69% | ||
| ASML - SMH | 80% Closely correlated | -7.82% | ||
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