As AI continues to dominate the markets, advisors are trying hard not to burst anyone’s bubble.
Sure, the S&P 500 Index is up a respectable 14% so far this year, but nearly half of all U.S. stocks are in negative territory, and 70% of those stocks are lagging the index, which is leaving some advisors increasingly worried about a pullback. These gloomy data are being overshadowed and offset by the strength of a small group of AI infrastructure and related semiconductor stocks that are driving a run on the market. All of this is sparking a debate about whether it should be described as a bubble.
For example, Nvidia, which is often considered the poster child for the rise of AI, is up almost 40% this year. But even that performance lags behind AI infrastructure names like Broadcom, up 54%; Palantir Technologies, up 123%; and Micron Technologies, an increase of 177%. Then there are data storage-only plays, like Seagate Technology, up 203%; and Western Digital, an increase of 243%.
“If it looks like a bubble, it barks like a bubble, it sounds like a bubble, it is a bubble, and you have to be naïve not to think that this whole AI thing is in its euphoria phase,” said Kashif Ahmed, president of American Private Wealth. “This is the dotcom of 2025, and I’ve been warning people for most of the year and positioning portfolios. This is not going to end well for those who are succumbing to FOMO.”
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One way to show the imbalanced nature of today’s stock market is to compare the composition of the S&P 500 with that of the Nasdaq Composite Index.
According to Nick Kalivas, head of equity and factor ETF strategy at Invesco, the market cap-weighted S&P and Nasdaq are currently at a 53% overlap, compared to just an 18.5% overlap in 2010. “This shows that the S&P 500 has become very growing and very concentrated,” he said.
In terms of valuation risk, Kalivas compares the relative price of the Russell 1000 Growth Index to that of the Russell 1000 Value Index: the ratio between the two now stands at 1.65. This compares to a historical average spread dating back to January 1987 of 0.92. That spread fell to 0.57 in 2006 as the market adjusted in the wake of the dot-com bubble, raising it to 1.54. “Right now, the gap between growth and value is historically large,” Kalivas said.
But when it comes to investing, identifying a bubble is usually the easy part, according to Rick Wedell, chief investment officer at RFG Advisory. “The hard part about trying to create a bubble is timing,” he said. “You can be right about something being overvalued, but if you’re not right by the time that value comes back to reality, you’re still wrong.”
Wedell reinforces his point by referencing the famous “irrational exuberance” comment made in a December 1996 speech by Alan Greenspan, who was chairman of the Federal Reserve for nearly two decades. “If you had sold the market and gone on the defensive the day he gave the speech, and then bought back at the bottom of the subsequent crisis when it hit, you would have been 15% worse off than if you had simply done nothing,” Wedell said. “Put another way, just because something looks stupid doesn’t mean it can’t get stupider.”
Tom Graff, chief investment officer at Facet, is less comfortable using the term “bubble” because it implies the possibility of catastrophic losses. “We don’t think it’s likely that stocks like Nvidia, Microsoft, etc., are in bubble territory, where losses of 60% or 70% could occur,” he said. “AI is too powerful a tailwind for that.” However, based on current valuation levels, Graff believes “there is a risk of a significant correction in tech stocks.”
Will Rocket, senior director of investment strategy at Mercer Advisors, sees the growth behind the performance and believes the foundation of AI is structurally sound.
“AI-related stocks have contributed to most of the S&P 500’s earnings growth and market profitability over the past five years, but there is also the intrinsic value of the emerging AI sector to consider,” he said.
As for comparisons to the dot-com bubble that boosted valuations of virtually every internet-related company, Rocket said the AI model is much more set for future cash flows. “What is similar is exciting new technology, market rumors and rising stock prices,” he said. “What’s different is that the search engines of 25 years ago were dependent on the growth of online advertising, which was a very new business at the time.”
Open the hood. One of the biggest problems for advisors is managing clients’ fear of missing out. Thomas Van Spankeren, wealth advisor at RISE Investments, said the best thing to do is emphasize the importance of disciplined portfolio diversification. “My concern is that investors have too much portfolio in the technology or technology-related sector,” he said. “Omitting rebalancing concentrated and highly valued sectors can be detrimental to achieving long-term financial objectives.”
The good news, according to Invesco’s Kalivas, is that financial advisors don’t have to make massive moves out of the market or expose themselves to AI investments to weather rising and risky valuations. He recommends moving from traditional cap-weighted index allocations to equally weighted indexes that reduce exposure to the most expensive stocks and increase exposure to the least expensive names in the indexes.
Traditionally, capitalization-weighted and equal-weighted indices have traded at nearly equal valuations. “You need to know what’s in your portfolio and feel comfortable with the exposure levels you have,” Kalivas said. “Right now, investors might have more exposure to AI trading than they realize.”
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