Some might argue that over the past decade there has never been a better time to buy the so-called Magnificent Seven stocks, the mega-cap companies at the top of the market today.
This may sound strange given all the talk about the AI bubble over the last year, after the launch of ChatGPT in November 2022, and after Mag 7 led to a parabolic rise in the S&P 500.
But Marta Norton, chief investment strategist at Empower Investments, said the basket of stocks that includes Nvidia (NVDA), Amazon (AMZN), Microsoft (MSFT), Meta (META), Alphabet (GOOG), Apple (AAPL) and Tesla (TSLA) is down 19% since October, and the valuations of these companies relative to the S&P 500 have rarely been this cheap.
In an interview with Business Insider last week, Norton specifically noted that the Bloomberg Magnificent Seven index is among the 10 cheapest since 2015.
“You’re essentially paying the same kind of valuations for these stocks as you would for a broader collection of U.S. stock markets,” Norton said.
Norton said he likes the five of the seven Mag stocks that are most closely tied to AI trade, which he sees as a long-term tailwind over the next few years. These include Nvidia, Amazon, Microsoft, Alphabet, and Meta.
Hyperscaler stocks in particular are advantageous because they play a role on both sides of the AI coin, he said. Only one of the five stocks mentioned above is not considered a hyperscaler, as Nvidia acts as a supplier to the tech giants that build their technology.
“They’re not only aggressively building infrastructure, they’re looking for ways to monetize it,” Norton said of hyperscaler stocks. “They’re kind of working on it from two different directions.”
Norton said the initial evaluation is especially important because major AI companies are spending a lot of money building AI. The more you spend on AI infrastructure, the greater the risk that future cash flows won’t justify the cost. Therefore, a lower valuation means that investors are taking on a lower amount of risk.
The four hyperscalers are expected to spend a total of about $600 billion in 2026 alone.
He emphasized that the stock looks attractive in the long term, but said it could fall further in the short term. With a clear path to monetizing its AI products, Norton will start to outperform expectations, she said.
“If I were to sleep for 10 years, I would want these names in my portfolio,” Norton said.