橙子Joyce

US stocks’ semiconductor sector stages a super rebound! Is an opportunity being forged out of the “deleveraging wreckage” as the AI compute theme leads the charge?
Micron Technology (MU.US)
872.555
+18.07%
SanDisk (SNDK.US)
1265.455
+24.57%
The mutual fund wait-and-see approach, retail investor cooling, total leverage still at a five-year high, and potential CTA sell-side positioning are what constrain the S&P 500’s ability to break through as a whole. Meanwhile, semiconductors are getting industry tailwinds such as Lam Research’s order guidance, the continuation of AI capital expenditure, tightness in memory supply and demand, and extreme short-covering.
On Thursday before the US market open, semiconductor stocks closely tied to AI compute infrastructure collectively went on a wild surge, seemingly signaling a long-awaited “bullish sentiment in an irrational, blow-off style” super rebound for the semiconductor sector amid ongoing extreme deleveraging and crowded-position liquidation, as well as pessimism that AI capex has yet to deliver optimistic returns. At the same time, for strategists who remain cautious about global equity market conditions, over the past two months global investors have been trying but basically failed to find a major catalyst capable of breaking the newly formed, sharply volatile yet stuck-in-place state of the US stock market.

IBM said they have demonstrated the so-called “verifiable quantum supremacy,” claiming that a quantum computer can perform a computation beyond the capabilities of mainstream classical simulation methods, and they provided statistical evidence for the accuracy of the results.
According to IBM, this work, carried out in collaboration with researchers at the University of Chicago, is the company’s latest milestone in building fault-tolerant quantum computers. This experiment will not fundamentally change Bitcoin’s near-term security outlook. However, it adds new information to research aimed at overcoming one of the biggest obstacles in quantum computing—reliably correcting errors while scaling up to larger systems.