Wells Fargo’s top market strategist says it is keeping a close watch on one equity play that’s offering a solid opportunity following the market correction over the last few months.
In a new CNBC interview, Wells Fargo chief equity strategist Ohsung Kwon says it is now bullish on mega-cap tech names, despite concerns that the hyperscalers are draining their cash flow in favor of AI CapEx.
According to Kwon, analysts at Wells Fargo have crunched the numbers and believe that hyperscaler cash flow will come in better than expected as Wall Street underestimates the revenue-generation potential of AI.
“So we started to like tech. So we have been almost like outright bearish hyperscalers for the past few months. And I think hyperscalers are starting to look a lot more interesting…
Yeah, so the reason why we were bearish was because of their weakening free cash flow. And their free cash flow estimates for 2026 came down by about two-thirds over the past year. And our analysts think that we are actually at an inflection point where free cash flow could actually come in above where consensus is. They’re actually forecasting a higher CapEx number than consensus, but it’s really the sales estimates, the top-line growth that people are underestimating.
And if you listen to hyperscalers, they’re all saying that demand still outpaces supply, and there’s a lot of supply coming online. So I think I think the street is still underestimating their potential top -line growth story. And if AI is truly that transformative, then hyperscalers are probably not overinvesting either.”
Kwon adds that the equity markets have already priced in the risks tied to a potential overinvestment cycle, considering that the Nasdaq has been on a decline since Q4 of 2025.
“So if you look at the Nasdaq, since October, the Nasdaq derated by 25% already. It’s actually been one of the most extreme deratings that we have seen in history. So I think equities are already pricing in the downside risk of a potential overinvestment cycle.
And I don’t think hyperscalers are necessarily overinvesting. It’s just there might be a little bit of delay on the return on investment. But if AI is really that good and we’re just going to need more compute power too.”
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