A bruising tech sell-off may be nearing exhaustion, even as earnings remain intact, according to banking giant Citi.
In a new CNBC interview, Citi managing director Tyler Radke says the scale of recent selling has been unusual given the strength of fourth-quarter results.
He notes that the disconnect between fundamentals and price action is particularly jarring for investors.
“But look, I think this has been painful, really unprecedented, the volume of selling. And I think what’s been particularly disorienting for investors is that Q4 earnings have been pretty solid. You’ve seen beats and raises, new business trends have accelerated, yet pretty indiscriminate selling.”
Radke points to early signs that selective names may be stabilizing after the broad-based decline.
“And this AI trade, this concern on AI, is actually broadened out beyond software. So it feels like we’re getting close to the bottom.”
Across Wall Street, strategists are now trying to separate temporary panic from structural opportunity.
In a new Bloomberg interview, Morgan Stanley global director of research Katy Huberty says the investment cycle in AI is rooted in a long-term productivity shift that spans industries.
“That investment cycle is underwritten by a productivity story. As the technology diffuses into the market, there is real productivity acceleration, which is important because the last two decades we’ve been running at labor productivity that is half of normal levels.”
Huberty says her team has taken a granular approach to identifying where AI exposure truly matters.
“Because we knew this adoption story was going to be critical, and it was going to touch all sectors of the market. We have now five times over mapped the 3,600 stocks that we cover to understand the rate of change, exposure, materiality [and] pricing power. And it’s on the back of that data that, yes, we’ve been able to identify where there are companies that have been sold indiscriminately, and there’s a real opportunity. We see that in software and services.”
She adds that within software and services, firms with strong data moats may be the best positioned for growth as AI tools are integrated more deeply into enterprise workflows.
“And the conversations we’re having right now with large language models are how do we connect those models to the applications and data that we use every day to unlock the real potential. And so you can see that the list that we published last week, the thread across the software and services companies is where there is a data moat, whether that’s credit, or it’s market data, or it’s systems of record in financials or customer care.”
If both strategists are right, the recent wave of selling may be less about broken fundamentals and more about investors resetting expectations as AI enthusiasm shifts from blanket buying to selective positioning.
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