Could the bubble in AI megacaps pop?

Megacaps may be entering a new phase of the business cycle where they have historically underperformed

Would this cause the AI megacap bubble to burst?

On Tuesday, August 19, the SandP 500 fell 0.6 percent, with tech stocks leading the US stock market's retreat. The largest declines were seen in artificial intelligence (AI) megacap stocks such as Nvidia and Meta, whose shares dropped 3 and 5% and 2 and 1%, respectively. Palantir, the AI bull's favorite, dropped 9 points to 0.4 percent.

In recent years, investors have grown accustomed to the tech megacaps being the best stocks to buy, with the Magnificent Seven appearing to be the only factors influencing stock market returns. However, the market is beginning to show signs of trepidation due to stretched valuations.

The head of equity funds at Hargreaves Lansdown, Steve Clayton, stated, "Tech stocks came under real selling pressure last night, August 19."

The drop came after it was reported that OpenAI CEO Sam Altman believes the AI market is in a bubble.

According to reports, Altman told reporters at a dinner on Friday, August 15, "When bubbles happen, smart people get overexcited about a kernel of truth." I believe that we are in a time when investors are overly enthusiastic about artificial intelligence.

In addition, Altman stated that he thinks AI is "the most important thing to happen in a very long time". Yet, remarks like these from one of the key players in the AI boom have only heightened worries about how expensive the AI industry is.

Could the US economy's recovery put an end to megacap dominance?

The release of a report by Bank of America analysts that indicated a shift in the market narrative might be imminent preceded the sell-off, in addition to Altman's remarks.

The US economy is exiting its downturn phase and entering a recovery, according to a number of key economic indicators, according to the Bank of America report.

That an improvement in the US economy's health would be detrimental to its largest stocks may seem counterintuitive. However, the Bank of Americas model, which divides the market cycle into four stagesrecovery, mid-cycle, late-cycle, and recoverydemonstrates that megacaps with strong market positions and superior earnings power typically benefit from downturn phases.

However, businesses such as these tend to lag behind the overall market during the recovery phase.

According to Savita Subramanian, head of US equity and quantitative strategy at Bank of America, weaker monetary policy from the Fed "has been accompanied by Mega caps lagging more than leading, and higher inflation should support a broadening of the S&P 500 beyond defensives/secular growth."

The belief that the US economy has transitioned from a downturn to a recovery would be reinforced if the Fed were to lower interest rates at its next meeting.

Does artificial intelligence exist in a bubble?

According to the Bank of America report, over the past ten years, the nifty fifty, which consists of the fifty largest stocks in the S&P 500, has outperformed the rest of the index by 73 percentage points.

According to Subramanian, "the 1990s lead-up to the Tech Bubble was the last memorable nifty fifty run." "It lasted for roughly six years, and the outperformance against... There were 71 percentage points in the S&P 500 index.

In spite of near-record valuations, she added, "sports average long-term growth expectations" and "today's nifty fifty is lower quality than most of the 1990s."

This isn't unique to technology. "Tech is not the culprit," Subramanian emphasized, adding that sector-neutral analyses revealed that the similarities are emphasized by large market caps rather than sector alignment in general. Nevertheless, "the run may be done" in terms of megacap profits.

Naturally, this draws attention to the enormous multiples at which tech and AI megacaps are present at the moment. Only if these stocks continue to perform significantly better than the market would these valuations make sense.

According to a recent analysis by financial author Bill Bonner, who writes for the substack Bonner Private Research, the combined market capitalization of the Magnificent Seven is worth more than China's GDP. These businesses may not see enough revenue increases from AI projects to make the investment worthwhile.

AI's protracted path to financial success.

We witnessed the same thing in the late 1990s, so if excessive investment in a technological trend that doesn't yield the expected profits sounds familiar, it is.

When the AI boom and the .com bubble are compared, it is countered that the former is driven by extremely profitable firms like Nvidia and Microsoft, while the latter was marked by a proliferation of unprofitable business models.

This ignores the fact that Microsoft's hardware and cloud businesses account for the majority of its earnings. Nvidia is fueled by AI investment, just like Microsoft's cloud division. But in both cases, the money is being spent by AI development companies. It's not that selling the kit to build AI won't generate a lot of revenue; rather, the profitability of this buildout's products is in doubt.

Looking past the AI megacaps reveals a landscape that resembles the 1990s quite a bit. Though they are common, AI-powered start-ups are essentially nothing more than money-burning machines.

"Neither Anthropic nor OpenAI is even close to being profitable," Morningstar principal Kenneth Lamont says. Growth has become the top priority, and even though both companies make good money, the enormous expenses of leasing or constructing state-of-the-art infrastructure far outweigh their earnings.

In order for OpenAI to become profitable by 2029, Altman anticipates that top-line revenue will tenfold over the next four years, and that enterprise sales will rise even more quickly (ChatGPT's consumer uses are, and likely always will be, loss-making).

Even though AI is a bubble, that doesn't mean there won't be any long-term benefits. Lamont claims that it is "missing the point" to frame the discussion as either a bubble about to burst or the beginning of a long-lasting change. Both can be true, as history demonstrates: the .-com boom produced both the tech behemoths that still rule today and a number of failures.

There is no question that artificial intelligence will become more and more important to the economy. The businesses that will benefit from the gains are less certain.

Preventing the AI bubble from popping.

You are probably more vulnerable than you realize to any possible burst of the AI megacap bubble. Index funds that follow the world stock market will probably make up the majority of your portfolio, whether it includes pension funds or investments in stocks and shares through an ISA. At least temporarily, your portfolio may suffer if sentiment toward these stocks declines.

Concentration risk is a disadvantage of passive investing with index funds. These funds naturally allocate your money primarily to megacap stocks with the highest weighting in global indices, following the broader market's movements. However, that exposes you to stretched valuations by default. Every index fund for a particular market must purchase the stocks that increase the most, which drives up prices even more. This has a circular effect.

Purchasing equal-weight funds, which will cap each holding at a specific weighting of the portfolio, can help you lower your concentration risk. Lamont uses the Xtrackers S&P 500 Equal Weight UCITS ETF (LON:XDWE) as an illustration.

Alternatively, you could purchase a fund like Amundi MSCI USA Ex Mega Cap UCITS ETF (LON:XMGA) that completely excludes megacaps.

Value opportunities in AI and its wider ecosystem, such as suppliers to firms like Nvidia and TSMC, may be of interest to investors who wish to maintain some exposure to AI without being overexposed to the stretched valuations of the megacaps.

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