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There has been much discussion in the financial media recently about whether another bubble is forming in the publicly traded stocks of companies involved in the development and use of artificial intelligence.
While it’s true that a handful of stocks, from Nvidia, Microsoft and Google parent Alphabet to Oracle and Adobe, have enjoyed strong rallies, the intense interest in Generative AI has yet to create a bubble in said stocks.
Let us recall the elements of bubbles, as identified by many market historians (myself included) who write about such financial market phenomena.
Historians and economists such as Charles McKay (“Some Extraordinary Dreams and the Madness of the Crowd”), John Kenneth Galbraith (“The Great Crash, 1929”), Edward Chancellor (“The Devil’s Back”), and Charles Kindleberger (“Manias,”). Panics and Crashes”) has written extraordinary books about the tendency of investors to go crazy for stocks.
Bubbly books describe everything from the Dutch tulip mania in the 17th century, to the South Sea and Mississippi bubbles in 18th century England and France, to the jazz age for roaring stocks in the 20s.
They also include the Japanese stock and property bubbles of the 1980s, the internet craze of the 1990s, and most recently the global real estate and credit bubble that led to the Great Financial Crisis in 2008.
In each case, there were several common features that defined the bubbles, from early disbelief that a particular asset or technology had transformative potential to wider adoption, rapid advances in asset prices, and widespread public participation in the mania that accompanied massive stock issuance. by any company even marginally related to fashion.
Lessons from the dotcom bubble
Yes, we’ve all been quick to believe in the transformative potential of AI, but only a few companies have taken a bid in anticipation of this generative potential. Artificial intelligence will fundamentally change the way we work and live.
The public is increasingly buying related tech stocks and related ETFs, but we have yet to see the single-minded focus of the entire stock trading world affect AI stocks.
With greater interest comes greater issuance until the supply of stocks involved in a bubble exceeds even the excessive demand among traders and investors.
In 1999 alone, 456 stocks went public at the height of Internet mania. 77% of them had no profit. Indeed, in 1999, the five largest stocks excluded Nasdaq 100the P/E of the rest exceeded 3000%.
In my personal book, TrendWatching, I noted that in 1998 and 1999, “first-day returns of IPOs exceeded 50%,” and in 1999, a quarter of all IPOs doubled on their first day of trading.
As my colleague David Faber pointed out on CNBC earlier this week, K-Tel, which sells music in late-night TV commercials, has soared from $5 to $30 a share just by announcing that it was becoming an Internet-based telecommunications technology company. strategy.
Like most other stocks, price/earnings ratios are endless, many have crashed, cratered and simply gone out of business.
The Nasdaq Composite gained 85% in 1999, a record annual gain for any US-based index in a calendar year. By 2003, it had declined by about 75%.
If there is going to be a bubble in AI, it’s early days.
Also, the Federal Reserve’s “easy money,” a key component of the financial frenzy, does not drive speculation in publicly traded AI stocks or any other asset class.
The public is not yet complete. In other words, we’re not there yet.
Bubbles are easy to spot
The gains, as we have seen, are concentrated in five or six stocks. Granted, they’ve boosted the Nasdaq 100 by 33% year-to-date, impressive to be sure, but it’s more like the performance of the so-called “Nifty 50” of early 1970s pioneer companies than the internet itself. The bubble of the late 1990s.
Some experts say that it is impossible to identify a bubble while it is swelling.
I’d argue that once you’ve covered a few topics, they’re pretty easy to find. And more importantly, there is a huge difference between a small bubble and a massive bubble.
Big bubbles that have burst in the past have brought down markets and in some cases entire economies, such as the real estate and credit crises in Japan in the 1990s or here in the United States that destroyed almost the entire financial system.
Currently, AI is attracting a lot of attention and a fair amount of investment dollars, but not all of the funds available in finance.
The day may come when smart investors speculate on AI without regard for revenue or profit, but only for potential.
When that day comes, the really smart money will be separated from the dumb money, because bets on exploration are extremely unwise.
Commentary by Ron Insana, contributor to CNBC and MSNBC and author of four books on Wall Street. Follow him on Twitter @rinsana.