The best AI fund of 2024? The S&P 500.
High-fee AI ETFs are great for asset managers, but not so good for investors.
If I asked you to name the defining technological trend of the past two years, you would probably say, “artificial intelligence,” and if I asked you how artificial intelligence stocks had performed over the last two years, you would probably say, “Pretty well!” Even after its recent sell-off, Nvidia is up ~900% since Fall 2022, SMCI is up ~700%, Meta has tripled, and Microsoft has gained roughly 80%. And yet, according to The Wall Street Journal’s James Mackintosh, every AI-themed ETF has underperformed the S&P 500:
Pity the investors in the three artificial-intelligence-themed exchange-traded funds that managed to lose money this year. Every other AI-flavored ETF I can find has trailed both the S&P 500 and MSCI World. That is before the AI theme itself was seriously questioned last week, when investor doubts about the price of leading AI stocks Nvidia and Super Micro Computer became obvious.
The AI fund disaster should be a cautionary tale for buyers of thematic ETFs, which now cover virtually anything you can think of, including Californian carbon permits (down 15% this year), Chinese cloud computing (down 21%) and pet care (up 10%). Put simply: You probably won’t get what you want, you’ll likely buy at the wrong time and it will be hard to hold for the long term.
Ironically enough, Nvidia’s success has made it harder for some of the AI funds to beat the wider market. Part of the point of using a fund is to diversify, so many funds weight their holdings equally or cap the maximum size of any one stock. With Nvidia making up more than 6% of the S&P 500, that led some AI funds to have less exposure to the biggest AI stock than you would get in a broad index fund.
How have so many artificial intelligence funds underperformed the S&P 500? Well, for starters, the S&P is top-heavy with some of the biggest current winners of the AI boom: its six largest components, which make up 28% of the index, are Apple, Microsoft, Nvidia, Amazon, Meta, and Alphabet. Meanwhile, the six largest positions in BlackRock’s iShares Future AI & Tech ETF are Broadcom, Nvidia, AMD, Palantir, Fortinet, and Accenture. While I do appreciate BlackRock including Accenture, a management consulting firm with $3.6 billion in annualized generative AI bookings, in its AI ETF, it’s surprising that the asset manager weighted it heavier than Amazon, Microsoft, Alphabet, and Taiwan Semiconductor.
The issue at hand is that betting on market trends and betting on individual companies are two very, very different endeavors. An association with “AI” doesn’t guarantee that a company’s stock will benefit from AI, at least not in the long-run. AI has to, at some point, translate to cash flow for the business. Compounding this issue is the fact that “trend” winners might be concentrated, but ETFs tend to be diversified. Nvidia’s market cap may have increased by 900% since Fall 2022, but if a fund has a max position size mandate, it will be forced to diversify into worse-performing companies (such as, you know, Accenture and Intel).
Imagine, for example, that you invested in an “electric vehicle” ETF in 2022 that was equal-weighted to Tesla, Fisker, Nio, Nikola, Canoo, Lucid Motors, and Rivian. While Tesla has been roughly flat over that time, the other companies are down significantly. Increasing electric vehicle adoption did not necessarily mean that all electric vehicle stocks would do well. The businesses themselves matter.
So why, given the underperformance, do so many asset managers issue thematic ETFs? Because they can charge hefty fees and expenses. BlackRock’s iShares Future AI & Tech ETF charges 0.47%, while the expense ratio on its S&P 500 ETF is just 0.03%. Thematic ETFs are lucrative for asset managers, regardless of how their investors fare. If you want to play the AI trend (or any market trend, for that matter), it’s probably best to either do your own due diligence on winners and losers or simply stick with index funds.
