Multiple Wall Street Firms Recommend Buying the Mag 7 Dip
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Morgan Stanley, Goldman Sachs, and Empower Investments have each urged clients to buy the Mag7 tech megacaps on the dip, arguing valuations have compressed to historic relative lows — but the thesis hinges on whether AI capital spending ultimately converts into profit.
Why have the Mag7 lagged this year?
The Roundhill Magnificent Seven ETF (MAGS) is roughly flat year-to-date, while the S&P 500 is up double digits and semiconductor stocks have outperformed further.
This means → the group that once led the market higher has become this year's most visible underperformer.
The dominant concern: hyperscalers — giant cloud platforms such as Amazon AWS and Microsoft Azure — are pouring money into AI, and investors doubt whether the spending will pay off.
What divergence is Morgan Stanley flagging?
Chief U.S. equity strategist Mike Wilson wrote that the wide gap between chip stocks and hyperscaler stocks "is unlikely to persist, because the latter's earnings depend on the former."
In plain terms = the buyers of chips (hyperscalers) are flat while the sellers of chips (semis) are rallying — that mismatch has to resolve one way or the other.
Wilson argues that if hyperscalers trim some spending plans, capital could rotate back from semis into the cloud names.
Why does Goldman say valuations look attractive now?
Chief U.S. equity strategist Ben Snider said hyperscaler P/E ratios have fallen to levels near the March 2020 Covid bottom and the October 2022 rate-hike trough.
This means → the last two times these stocks were this "cheap," markets were at peak pandemic fear and peak rate-hike pain — both were followed by sharp rallies.
Goldman is actively discussing strategies with clients to increase exposure to the group.
Why does Empower say "hold for ten years with your eyes closed"?
Chief investment strategist Marta Norton named Nvidia, Amazon, Microsoft, Alphabet, and Meta as her highest-conviction picks right now.
Her core argument: these stocks' valuations relative to the S&P 500 sit at historic lows — "What you're paying for these companies is basically the same as buying a basket of the U.S. stock market."
In plain terms = investors used to pay a steep premium for these leaders; that premium has nearly vanished — you're getting "the best companies" at "ordinary stock" prices.
What will prove or break this consensus?
The common denominator across all three firms: valuations have compressed enough, and relative premiums are at multi-year lows.
The shared risk is equally clear: whether AI capex converts into profit growth is the critical validation point for this thesis.
This means → if hyperscaler AI revenue starts beating expectations over the next few quarters, the buy case holds; if not, "cheap" may just mean "not cheap enough yet."
Content is for reference only, not financial advice.