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JPMorgan: Current Divergence in AI Trading Reminiscent of Pre-1999 Internet Bubble

AirdropBlackHole
On July 2, JPMorgan technology analyst Jason Hunter stated in a client report that the current divergence within AI trading is beginning to resemble the period leading up to the 1999 internet bubble. The issue lies in the fact that while the stock prices of semiconductor, storage, and AI hardware suppliers continue to rise, the performance of large-scale cloud providers, which bear the brunt of significant capital expenditures, has lagged noticeably. This type of divergence is critical in the market. The rise of AI hardware companies relies on large cloud providers like Microsoft, Meta, Alphabet, and Amazon continuing to make substantial purchases of chips, servers, storage, and data center equipment. If the stock prices of these 'buyers' remain under pressure while the 'sellers' continue to soar, investors will eventually question whether this round of capital expenditures can be sustained. JPMorgan pointed out that if the stocks of major cloud providers do not stabilize over the summer, the market may face greater pullback pressure in the fall. In other words, while the AI market can still rely on hardware profits and orders in the short term, it will need to see the cloud providers themselves regain market recognition in the medium term.
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