How to Lose Money on the World’s Most Popular Investment Theme
Pity the investors in the three artificial-intelligence-themed ETFs that managed to lose money this year
4 min
There are lots of embarrassing ways to lose money, but it is particularly galling to lose when you correctly identify the theme that will dominate the market and manage to buy into it at a good moment.
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.
This problem hit the three losers of the year. First Trust’s $457 million AI-and-robotics fund has only 0.8% in Nvidia, a bit over half what it holds in cybersecurity firm BlackBerry .
WisdomTree ’s $213 million AI-and-innovation fund holds the same amount of each stock, giving it only 3% in Nvidia.
BlackRock ’s $610 million iShares Future AI & Tech fund was also equal weighted until three weeks ago, when it altered its purpose from being a robotics-and-AI fund, changed ticker and switched to a market-value-based index that gives it a larger exposure to Nvidia.
The result has been a 20-percentage-point gap between the best and worst AI ETFs this year. There is a more than 60-point gap since the launch of ChatGPT in November 2022 lit a rocket under AI stocks—although the ETFs are at least all up since then.
The market has penalized being equal weighted recently, instead rewarding big holdings in the largest stocks.
Jay Jacobs , U.S. head of thematic and active ETFs at BlackRock, says it is best to be market-value weighted when a theme has winner-takes-all characteristics, which he says generative AI has. When the firm’s AI fund included robotics it was spread across a lot more stocks that didn’t compete with each other, so equal weighted made more sense.
For investors, it isn’t so simple. Global X takes the opposite approach with its two $2 billion-plus AI funds, AIQ and BOTZ. BOTZ only buys stocks that focus on AI and robotics, but takes larger positions. AIQ spreads its bets on AI and tech more widely, and its 3% cap on its biggest holdings each time it rebalances means it has far less in Nvidia than BOTZ, with a cap of 8%. AIQ still managed to beat BOTZ this year, though.
So far, so confusing. The basic lesson: Picking among funds within a theme is hard, and depends on luck as well as close reading of the fund’s documents. A more advanced lesson is that it is hard to pick a theme in the first place, or to stick with it. The three problems:
1. Defining the theme is hard . Nvidia features in the anti-woke YALL ETF, which pitches itself as for “God-fearing, flag-waving conservatives.” The chip maker is also held by vegan, gender-diverse and climate-action ETFs. Its shares are clearly driven by the prospects for AI, but it is still big in computer-game and bitcoin ETFs, where its chips were originally used.
2. Timing the theme is even harder. Get in too early, and there aren’t any companies to buy. Get in when the funds are being launched, and the chances are the theme is already widely known and overpriced, as there are typically large numbers of launches during bubbles and late-stage bull markets.
“They are trendy by design,” says Kenneth Lamont, a senior researcher at Morningstar. “They play to our worst instincts, because we’re narrative-driven creatures.”
A recent example was the race to launch clean-energy and early-stage-tech ETFs during the bubble of late 2020 and early 2021. Performance since then has been miserable as prices corrected, with many of the ETFs halving or worse.
Dire timing is common across themes: According to a paper last year by Prof. Itzhak Ben-David of Ohio State University and three fellow academics, what they call “specialized” ETFs lose 6% a year on average over their first five years due to poor launch timing.
3. Long-term investing is pitched by fund managers as the goal for thematic investing, to hang on until the theme bears fruit. But even investors who really want to commit to a theme for the long run often find it hard, as so many funds are wound up, merged or change strategy when they go out of fashion.
The boom in internet funds of the late 1990s vanished after the dot-com bubble burst, with few surviving to see the internet theme blossom a decade later, while six of the 50 “metaverse” funds launched after Facebook switched to Meta Platforms in 2021 have already shut, according to Lamont.
The oldest thematic fund, the DWS Science and Technology mutual fund, started as the Television Fund in 1948 before adding electronics, and has gone through at least four other names. I only have data back to 1973, but it has lagged far behind the wider market since then, despite golden ages for television, electronics, science and now tech. (Yes, it has a lot of Nvidia.)
So what to do? At a very minimum, don’t buy based on the name of a fund. Look at the holdings, look at the index it follows and how it is structured, and consider whether it does what it says. Then think about just how expensive the idea has already become. Watch for the theme coming into fashion and getting overpriced, as that is a good time to sell (or to launch a fund).
But mostly, look at the fees: They will be many times higher than a broad market index fund, and the dismal history of poor timing suggests that for most people they aren’t worth paying.
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Quantum computing is moving from theory to real-world investment. Professor David Reilly says it could reshape finance, security and global technology infrastructure.
3 min
For decades, the world’s computing power has quietly expanded at an astonishing pace.
From the first transistor developed at Bell Labs in 1947 to modern processors containing billions and even trillions of transistors, each generation of technology has been faster, smaller and more powerful than the last.
But according to quantum physicist and technology entrepreneur David Reilly, that era of effortless progress is beginning to slow.
Reilly, CEO of Sydney-based Emergence Quantum and Professor of Physics at the University of Sydney, says the computing infrastructure underpinning modern economies is approaching fundamental physical limits.
And that could have enormous implications for finance, artificial intelligence and global investment.
Speaking at an industry event organised by Kanebridge International, Reilly said many critical parts of modern society depend on computing and the infrastructure used to process information.
The slowdown behind the tech boom
For years, the technology industry relied on a steady improvement known as Moore’s Law, where the number of transistors on a chip doubled roughly every two years.
More transistors meant more computing power, allowing faster software, smarter devices and ever-larger data systems.
Today, however, those gains are slowing.
“It feels to me very innate that I’m going to just find that next year there’s going to be another breakthrough,” Reilly said.
“But if you look at the data…there’s a slowing down, a roll off in performance that started some 10, 20 years ago.”
Rather than making chips dramatically faster, manufacturers are now largely increasing computing capacity by packing more transistors onto each processor.
The approach works, but it comes with growing complexity, higher costs and increasing energy demands.
The brute-force race for AI
That challenge is already visible in the massive data centres being built to support artificial intelligence.
In the race to dominate AI, companies are constructing vast computing facilities that consume huge amounts of electricity and water. Reilly described this expansion as a “brute force” approach driven by the global competition to develop advanced AI systems.
Yet the demand for computing power continues to accelerate.
Artificial intelligence, advanced robotics, healthcare research, pharmaceuticals and cybersecurity all require far more processing capacity than today’s systems can easily deliver.
The question now facing the technology sector is whether traditional computing can keep up.
Enter quantum computing
That is where quantum computing enters the conversation.
Unlike conventional computers, which process information using binary switches that represent ones and zeros, quantum computers exploit the unusual behaviour of particles at the atomic scale.
Reilly describes them as a fundamentally different type of machine.
“So a quantum computer is a wave computer,” he said.
Instead of processing information through simple on-off switches, quantum systems can use wave-like properties of particles to process many possible outcomes simultaneously.
Those waves can interact in complex ways, reinforcing correct solutions while cancelling out incorrect ones. In theory, this allows quantum systems to tackle certain types of problems dramatically faster than classical computers.
What it could mean for finance
The concept may sound abstract, but its potential applications are significant.
Quantum computers are expected to transform areas such as materials science, chemical modelling and pharmaceutical development.
They could also help solve complex optimisation problems in logistics, finance and risk management.
For financial institutions in particular, the technology could offer new tools for detecting fraud, analysing market behaviour and optimising portfolios.
But the shift will not happen overnight.
“One message to take away is that quantum is not going to suddenly solve all of your problems,” Reilly said.
Instead, he said quantum systems will likely complement existing computing technologies as part of a broader and more diverse computing ecosystem.
Why data centres may soon “go cold”
One key change already emerging is how computing systems are physically designed.
Many next-generation technologies, including quantum processors, operate far more efficiently at extremely low temperatures. As a result, future data centres may rely heavily on cryogenic cooling systems to manage heat and energy consumption.
Reilly believes that the shift will gradually reshape the computing industry.
“Over the next five years, you’re going to see data centres go cold,” he said.
“And as that happens, they almost drag with them new compute paradigms.”
Emergence Quantum, the company he co-founded, is focused on developing technologies to support that transition, including cryogenic electronics and integrated hardware platforms designed for quantum computing and energy-efficient systems.
A new technological era
For investors and businesses, the technology remains in its early stages. But the scale of global interest is growing rapidly.
Governments, research institutions and technology companies are investing heavily in quantum research, betting it could become a foundational technology for the next generation of computing.
For Reilly, the moment feels similar to earlier technological turning points.
In the 19th century, new discoveries in thermodynamics helped drive the development of steam engines and the Industrial Revolution. In the 20th century, advances in electromagnetism led to radio, television and eventually the internet.
Quantum physics, he suggests, could represent the next chapter in that story.
“Today we have, as a society, in our hands new physics that we’re just beginning to figure out what to do with,” Reilly said.
“But I think it’s an exciting time to be alive and watch what happens over the coming decades.”
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