JPMorgan: The current internal divergence in AI trading is reminiscent of the eve of the 1999 internet bubble.

BlockBeats News, July 2 — JPMorgan technical analyst Jason Hunter said in a client report that the current divergence within AI trading is beginning to resemble the period before the 1999 internet bubble. The issue is that semiconductor, memory, and AI hardware suppliers' stock prices continue to rise, but the performance of hyperscale cloud companies that bear massive capital expenditures is clearly lagging.

This kind of divergence is critical in the market. The rise of AI hardware companies relies on cloud giants like Microsoft, Meta, Alphabet, and Amazon continuing to purchase large volumes of chips, servers, storage, and data center equipment. If the stock prices of these "buyers" remain under pressure while the "sellers'" stocks keep soaring, investors will sooner or later question whether this round of capital spending can be sustained.

JPMorgan pointed out that if the stocks of major cloud companies cannot stabilize in the summer, the market could face greater downside pressure in the fall. In other words, the AI rally can be supported in the short term by hardware profits and orders, but in the medium term, it will need to see that the cloud companies themselves are re-recognized by the market.