JPMorgan Chase: Current AI Trading Internal Fragmentation Reminiscent of the Eve of the 1999 Internet Bubble

BlockBeats News, July 2nd. Morgan Stanley's technical analyst Jason Hunter stated in a client report that the current internal divergence in AI trading is starting to resemble the period just before the 1999 Internet bubble. The issue lies in the fact that semiconductor, storage, and AI hardware vendor stocks have been continuously rising, while the truly massive-scale cloud players that bear the brunt of capital expenditure show a noticeably lagging performance.

This kind of divergence is crucial in the market. The AI hardware companies surge on the back of continued large-scale chip, server, storage, and data center equipment purchases by Microsoft, Meta, Alphabet, Amazon, and other cloud players. If the stocks of these "buyers" continue to be under pressure while the stocks of the "sellers" keep skyrocketing, investors will sooner or later question the sustainability of this capital expenditure cycle.

Morgan Stanley pointed out that if the stocks of large cloud players fail to stabilize during the summer, the market may face even greater retreat pressure in the fall. In other words, while the AI market can rely on hardware profits and orders in the short term, it needs to see a market revalidation of the cloud players themselves in the medium term.