r/valueinvesting
英伟达看起来像是一个价值投资标的，其TAM预测被低估了
HBM需求暗示1.3万亿美元GPU TAM，基于预测营收支撑英伟达仅14倍的EV/EBITDA，使其成为价值标的。
- HBM需求暗示了高达1.3万亿美元的GPU总TAM，远高于华尔街共识。
- 预计总收入约4950亿美元和EBITDA约3250亿美元，支撑其仅为14倍的前瞻EV/EBITDA倍数。
- 基于保守的AI资本开支市场份额假设，当前股价较其内在价值存在显著折价。
Not long ago, I did a deep dive into Micron’s fundamentals and it became apparent how important High Bandwidth Memory (HBM) has become for its revenue. Some even argue that this new type of memory is not a traditional cyclical, which led me down the rabbit hole of “Who’s buying this memory?”.
One of the names that stands out is Nvidia, and the numbers indicate that this is something that is not receiving as much attention as it deserves. Using Micron’s $100B TAM forecast for HBM, multiple sources claim around 60% of this memory ends up in GPUs and accelerators. Which seems realistics after their $40B revenue for Q3 2026.
This leaves us with $60B of memory going into GPUs. Using Nvidia’s numbers, around 10% of GPU cost is HBM, so… if there’s demand for $60B of HBM just for GPUs and accelerators, that’s around $600B of reasonable TAM for the same GPUs containing this memory. If we compare this to Morgan Stanley’s forecast, who puts GPU TAM at $400B out of their $1.1T total AI CapEx forecast, and we adjust it to these numbers results a total over $1.3T.
Nvidia currently captures around 35% to 40% of AI CapEx, so simply sustaining that pace would put their Data Center revenue at \~$465B between compute and networking. Already over the $390B Wall Street total consensus. This is before adding $15B–$30B for their edge/retail GPUs and compute, which would put that number on the high end at \~$495B in revenue.
As of today, Nvidia can convert 66% of that revenue into EBITDA, with estimates going as high as 70% for 2027. Even on the low end of those numbers, it would put the company at \~$325B EBITDA, which at today’s enterprise value of \~$4.5T gives us a 14x forward EV/EBITDA multiple, or $192 per share, for the company currently leading the compute market. That’s half of today’s multiple and around three times less than AMD’s forward multiple of x46.
[](https://substackcdn.com/image/fetch/$s_!AFkE!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fda3f52a0-141c-4731-b5c5-55b999daabb5_1556x467.png)
With that in mind after capturing 35% of total hyperscaler CapEx, with current enterprise value, the multiple of 14x would leave us with the cheapest large-cap AI name in the market. Considering their large footprint in the sector, I would consider that to be grossly undervalued. Even if their multiple were to contract somewhere between 14x and today’s \~30x, and they traded at a discount to peers at 25x, we land at $336 a share. Putting it in an odd situation where it seems like the market has almost forgotten it’s even there. With AMD (\~110x) and Intel (\~50x) trading at multiples well above the leader of the segment, and even its own supplier Micron trading at \~30x.
Let me know what you think, and do not take anything in this piece as investment advice. Just my observation while doing research.
It was like at some point in 24, when people were pondering in a post here at what price will nvidia’s stock start going down. And I said: when forward pe is like 10.
I guess we’re getting there.
I think you're overstating the TAM. Nvidia has dominated because there were no alternatives. The Nvidia tax was too high and the value of custom chips have become too important. We can see how desperate the hyperscalers are to convert to XPUs. Google has demonstrated the importance of the XPU market with their TPU and Broadcom's business (Google and Meta) is set to explode in 2027. The other hyperscalers are still limited by TSM production (Microsoft and Amazon) but Marvell has still shown a big increase in XPU revenue in 2027 and it doubling in 2028. This timeline could accelerate if Intel provides a reasonable alternative to TSM.
Nvidia is still the king and will always have a place for frontier models. However, I think their bet on Marvell and the NV Fusion is a sign that they know the GPU gravy train won't last forever. Also, I don't think we can expect a massive capex increase in 2027 as balance sheets are getting weaker and just maintaining 2026 numbers might be difficult for everyone not named Google and Microsoft.
Nvidia's goal is to remain the leader and pivot into physical AI. If they can't do that, I think their TAM is a lot smaller than you think.
There is some serious cognitive dissonance with nvda and HBM numbers, and the associated bullishness. You cannot be bullish MU, and bearish any other part of the AI trade. Really nvda is just a better buisness all around. Another thing, if saas were really about to be disrupted I would expect intel/amd to be the ones getting annihilated because x86 disruption would be guaranteed
Funnily enough I was just looking into NVDA this morning and thought I might start a position for a swing trade around here.
Understated TAM is the comfiest bull thesis there is. It's like standing on the beach arguing the ocean is bigger than people realize. Probably true and almost entirely beside the point, because your revenue is the bucket you can actually fill and keep refilling, and at the moment about five guys are doing all the pouring.
NVDA on a downward dog trajectory.
how? can you elaborate on the math for that?
The recent drop was due to hyperscaler ROI capex fear. + Open ai leaked financials that are not looking good at all.
That's all
AI Clouds, Industrials and Enterprise (ACIE) is where Nvidia expects the largest growth.
You wrote the correct word. FEAR. FEAR FEAR FEAR. Let me tell you something, on Friday, I woke up 5:30 AM PST. and got 6 notifications from Barron's. 4 had "Fear" in the title.
I sure as hell didn't go to bed in fear the night before. I'm on X all the time now, I have a good grasp on what's going on.
I'm extremely bullish on Nvidia right now, mostly because Collette Kress said they saw what was coming and pre-purchased memory quarters in advance.
You can also take away, that memory is still a good investment but so is Nvidia, which is cheaper now based on multiples than it's ever been in the past 10 yrs.
Open AI is only one of Nvidia's clients and dont even have a substantial share of CapEx
|Hyperscalers|Capex|||Non-Circular Capex|
|:-|:-|:-|:-|:-|
|Amazon|$200,000.00|||$200,000.00|
|Microsoft|$190,000.00|||$190,000.00|
|Google|$180,000.00|||$180,000.00|
|Meta|$130,000.00|||$130,000.00|
|Oracle|$50,000.00|||$50,000.00|
|Open AI|$50,000.00|||$10,000.00|
|Anthropic|$20,000.00|||$5,000.00|
|Space X|$30,000.00|||$30,000.00|
|Total|$850,000.00|||$795,000.00|
I’m not necessarily disagreeing with your substantive points—just underscoring certain market mechanics at play.
I mean there are risk, of course, AMD could take some of the market share from Nvidia, Hyperscaler capex could substantially slow down, but as we sit, this is the best priced semiconductor in the market.