Catch pre-market movers with AI signals.
A few months back, I dug into Micron’s financials and realized how crucial High Bandwidth Memory (HBM) is for their earnings. Some folks even say this memory isn't a typical cyclical product, leading me to wonder, "Who's buying this memory?"
One name that jumps out is Nvidia, and the data suggests it's getting less attention than it should. Micron forecasts a $100B market for HBM, with about 60% going into GPUs and accelerators. That makes sense with Nvidia's $40B revenue for Q3 2026.
This means $60B of HBM is used just for GPUs. If about 10% of a GPU’s cost is HBM, then the demand for $60B of HBM suggests a potential $600B market for those GPUs. Compared to Morgan Stanley's $400B GPU forecast from their $1.1T AI spending estimate, that brings the total market to over $1.3T.
Nvidia currently takes about 35% to 40% of AI spending, so maintaining that pace could mean $465B in data center revenue, already surpassing Wall Street's $390B consensus. Adding $15B–$30B for edge and retail GPUs, the total could hit $495B.
Right now, Nvidia converts about 66% of its revenue into EBITDA, with some estimates up to 70% by 2027. Even on the lower end, that's around $325B EBITDA, with an enterprise value of $4.5T, giving a 14x forward EV/EBITDA multiple or $192 per share. That's half of today’s multiple and about three times less than AMD’s 46x.
With 35% of hyperscaler spending, and today’s multiple, Nvidia appears to be the cheapest large-cap AI stock. Even if the multiple drops to 14x–30x and they trade at 25x compared to peers, it’s still around $336 per share. It's like the market has almost forgotten about it. AMD and Intel are trading at multiples much higher than Nvidia, and even Micron at about 30x.
Thoughts? Just my take while doing some research. Not investment advice.AMD--
As an allocator, I’m watching NVDA’s multiple compress relative to AMD and Intel, but I’m sizing cautiously. I’d prefer a 15–20% core position, with a sleeve to Micron on HBM visibility, and keep cash for any AI-capex surprises.
From a sector lens, HBM is the real bottleneck. If hyperscalers keep scaling GPUs, Micron’s DRAM share and revenue trajectory look solid, while AMD’s architecture wins depend on software adoption. NVDA’s 66% conversion is hard to beat.
If NVDA dips, I’m nibbling on the pullback.
QCOM dip looks like a scalp setup; watching AAL.
I’m leaning into the volatility: selling QCOM dips with tight stops, buying strength in AAPL rallies. If it keeps oscillating, I’ll rotate back and forth, small sizes, until the trend reclaims.
Not adding QCOM until the dip stops.
Watching U from the sidelines; if it actually moves, I’ll consider a starter, but I want confirmation on funding and timelines.
U could disrupt if it scales, but incumbents like AVGO aren’t backing down.
Feels like everyone’s rushing to the U stock pump, but I’m not buying it. If the catalysts are as strong as claimed, why isn’t it showing up in volume? I’d rather fade a quick pop than chase.
