The semiconductor selloff is no longer just a weekly correction.
By the November 5 lows, Micron was 48% below its all-time high. Broadcom was down 41%, AMD and SK hynix 39%, TSMC 28%, and NVIDIA 26%.
The damage was even greater in equipment: Applied Materials was down 57% and Lam Research 58%.
These are very different businesses. Yet the market is repricing all of them.
I think the common question is changing.
For much of the AI buildout, investors focused on who would capture the most spending.
Now they're asking which earnings can survive a slower pace of investment.
Memory is particularly exposed to this shift. HBM shortages support today's pricing, but high margins also encourage capacity expansion. The market can discount a future pricing cycle before current orders weaken.
Equipment faces a different problem. Chip demand can remain strong while manufacturers postpone new fabs. Equipment revenue depends on the timing of capacity additions, not simply on how many chips customers need.
NVIDIA and TSMC have another advantage: their economics extend beyond a single memory pricing cycle. NVIDIA captures value through its computing platform; TSMC supplies competing chip architectures through advanced manufacturing.
That doesn't make either immune to weaker AI spending. It changes how the risk reaches their earnings.
Broadcom and AMD add another dimension: customer concentration, custom silicon adoption and competitive share shifts.
My hypothesis is that the market is no longer pricing AI demand alone. It's repricing the durability of each company's earnings if AI capex growth slows.
The next evidence won't be the stock charts. It will be memory pricing, qualified capacity additions, equipment orders, accelerator margins and hyperscaler deployment schedules.
Those will tell us whether this was mainly a valuation reset—or the beginning of a deeper earnings revision.
#AI芯片股重挫纳指周跌3.4%
$MU.US $NVDA.US
By the November 5 lows, Micron was 48% below its all-time high. Broadcom was down 41%, AMD and SK hynix 39%, TSMC 28%, and NVIDIA 26%.
The damage was even greater in equipment: Applied Materials was down 57% and Lam Research 58%.
These are very different businesses. Yet the market is repricing all of them.
I think the common question is changing.
For much of the AI buildout, investors focused on who would capture the most spending.
Now they're asking which earnings can survive a slower pace of investment.
Memory is particularly exposed to this shift. HBM shortages support today's pricing, but high margins also encourage capacity expansion. The market can discount a future pricing cycle before current orders weaken.
Equipment faces a different problem. Chip demand can remain strong while manufacturers postpone new fabs. Equipment revenue depends on the timing of capacity additions, not simply on how many chips customers need.
NVIDIA and TSMC have another advantage: their economics extend beyond a single memory pricing cycle. NVIDIA captures value through its computing platform; TSMC supplies competing chip architectures through advanced manufacturing.
That doesn't make either immune to weaker AI spending. It changes how the risk reaches their earnings.
Broadcom and AMD add another dimension: customer concentration, custom silicon adoption and competitive share shifts.
My hypothesis is that the market is no longer pricing AI demand alone. It's repricing the durability of each company's earnings if AI capex growth slows.
The next evidence won't be the stock charts. It will be memory pricing, qualified capacity additions, equipment orders, accelerator margins and hyperscaler deployment schedules.
Those will tell us whether this was mainly a valuation reset—or the beginning of a deeper earnings revision.
#AI芯片股重挫纳指周跌3.4%
$MU.US $NVDA.US