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Halfway through 2023, it’s evident that the artificial intelligence (AI) investing theme is reach hysteria-type levels and that’s evident on multiple fronts.
Several members of the “magnificent seven” – the cohort of stocks contributing the bulk of this year’s broader market gains – have direct AI ties. Likewise, the Nasdaq CTA Artificial Intelligence and Robotics Index is higher by more than 26% year-to-date. That’s impressive, but it’s not alarmingly “bonkers” for a six-month stretch in which growth stocks were in favor. Still, fears persist that AI equities are entering bubble territory.
Amid a recent selloff in some AI equities, concerns linger that this is another disruptive tech bubble primed for bursting. Memories of the internet bubble of 2000 and, to a lesser extent, the more recent repudiation of once beloved cloud computing stocks, linger to this day. Those are among the reasons some advisors and many of their AI-enthused clients may be getting pensive about an AI bubble.
The intent here isn’t to predict the arrival of a bubble or to predict that one won’t afflict AI. Rather, the point of emphasis is that history lessons are meaningful when it comes to tech bubbles and the related prognostications.
What History Says Could Await AI Equities
I’m very fond of mentioning in this space that past performance isn’t a guarantee of future returns. And I also frequently note that while history doesn’t always repeat, it often rhymes. No, I’m not taking credit for those market maxims. They’re ancient. However, they remain useful in discussing potential AI equity retrenchment.
“So how does the downside play out for stocks perceived to be by investors more at risk from these types of technology disruption? The market typically de-rates and waits,” notes Ed Stanley, Morgan Stanley's Head of Thematic Research in Europe. “So valuations fall somewhere between 50 to 60% in the years 1 to 3 post-a-disruptive-event with consensus sales and profit downgrades taking anywhere around 5 to 7 years to materialize. This process is shorter for business to consumer, B2B and longer for business to business contracts, B2B.”
That’s instructive regarding what could await potential losers, but astute clients will want to know strategies for capitalizing on an AI rebound, assuming a downturn materializes in earnest. Good news: Clients need not rush in at the first signs of a rebound.
“For perceived winners, upgrades need to arrive within 6 to 12 months post the initial re-rating. However, we find that missing the first year of upside tends to have little impact on long term compound returns for investors,” adds Stanley.
AI Bubble Clues
Assessing whether or not an asset class is in bubble territory isn’t a taxing endeavor and doesn’t always boil down to market price action. As one example of something advisors can put in their tool boxes, Stanley mentions internet searches for AI images. They’re down 50% from recent highs.
One reason why AI could encounter a bubble is the sheer number of publicly traded companies relevant to this theme remains small today. On the other hand, that’s a point that could work in investors’ favor when the second phase of AI upside comes to pass.
“History suggests that diffusion of technologies that are transformational like this have tended to lead to changes in stock market leadership over the last hundred years, with ultimately 2.3% of all companies generating all $75 trillion of net shareholder returns since 1990,” concludes Stanley.
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