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Apollo's Slok says Magnificent Seven fall 13% as investors question AI capex returns

Apollo's Torsten Slok said on June 28 that Magnificent Seven stocks fell more than 13% since mid-May while the S&P 500 dropped about 2%, on AI spending doubts.

Dmytro Spodarets
Jun 29, 2026 · 1 min read

Apollo Global Management chief economist Torsten Slok said on June 28 that the Magnificent Seven have fallen more than 13% since mid-May while the S&P 500 dropped roughly 2% over the same stretch, as investors weigh returns on a wave of AI capital expenditure.

The gap matters because the seven stocks — Alphabet, Amazon, Apple, Meta, Microsoft, NVIDIA and Tesla — dominate the index, so when a group that large underperforms the S&P 500, money is rotating out of it. Slok’s Daily Spark report ties the move to skepticism about AI infrastructure payback.

The 32-slide note, titled “Mag 7 starting to underperform: Markets rotating toward quality and free cash flow,” frames the shift around cash generation, showing hyperscaler free cash flow coming down even as capital spending climbs as a share of operating cash flow. Hyperscaler AI infrastructure spending is separately reported to be heading toward roughly $725 billion for full-year 2026, more than $400 billion of it from the four largest spenders — outlays that, for now, are showing up as cost rather than return.

Slok describes the move as underperformance, not a crash, and the figures are projections rather than reported results. A 13% pullback over six weeks leaves the group well above where it traded a year ago, so the note reads as a rotation signal, not a market call.

This updates a storyline first flagged on June 27, when the same names were tracked for AI-driven market losses; Slok’s note is the first dated, first-party framing of the rotation. Whether the trend holds depends on what the hyperscalers report next earnings season, when investors get fresh numbers on whether the spending is converting to revenue.


Dmytro Spodarets
Dmytro Spodarets
Founder & Editor-in-Chief

Founder and Chief Editor of Data Phoenix — a San Francisco Bay Area media and education platform focused on AI and Data.

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