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Discussion (100 Comments)Read Original on HackerNews
> […] Since 1926, the median ten-year return on individual U.S. stocks relative to the broad equity market is –7.9%, underperforming by 0.82% per year. For stocks that have been among the top 20% performers over the previous five years, the median ten-year market-adjusted return falls to –17.8%, underperforming by 1.94% per year. Since the end of World War II, the median ten-year market-adjusted return of recent winners has been negative for 93% of the time. The case for diversifying concentrated positions in individual stocks, particularly in recent market winners, is even stronger than most investors realize.
* https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4541122
Every time.
I look forward to your weather report too: "It's always sunny outside until one day it starts raining. Every time."
This is more of a mathematical axiom than a financial effect, because you're defining "underperform/overperform" with respect to an average that contains them.
I am really struggling to see what's the investment thesis behind Google valuation increasing 2x in response to AI, though. Assuming no magical AGI singularity, by the end of the day, they're still selling the same services, but the services have gotten more expensive for them to provide. Everyone was already using Google Search, but now, provisioning AI summaries on top of requires more compute. Everyone was already using Google Docs and Meet, but now, AI features cost Google more. Etc, etc.
The only place where they stand to make money is selling AI compute to enterprises. But with the current supply-chain challenges, the margins there are probably getting thinner.
Google is basically Nvdia (TPUs), Tesla (Waymo Self-Driving), Hyperscaler, Netflix (YouTube) and a massive VC (Anthropic, Databricks, SpaceX, etc.) all rolled into one.
Their valuation isn't really a 2x'ing so much as a reversion from halving.
Focus on cash/cashflow.
* Index investing raises in popularity, with index funds that automatically reinvest dividends being often preferred due to their tax efficiency.
* Large caps prefer to repurchase stocks, stock repurchases contribute fully towards a given company share price increase.
* Smaller caps still pay dividends, these dividends are then reinvested by index funds and the reinvestment is weighted by capitalization, so large caps share price benefits more from repurchases done with dividend cash paid by smaller caps. When dividend is paid, share price of a company that paid it is reduced, which further widens the performance gap between large and smaller caps.
The market is both happy that Apple didn’t spend all its cash on AI build-out, but also at the same time angry that Apple is “missing AI”.
Not to mention the grumblings that Apple has peaked.
Page 25 "The number of data centers in the US" gives an interesting insight as to the magnitude of the data center boom. 60% more data centers are being planned or are under construction. This might actually be underselling it in dollar amount, as I believe the average data center size under construction is larger than the average data center already constructed.
Page 27 "Cyclically adjusted P/E ratio near all-time highs" is certainly concerning and points to a near term correction.
I agree with the headline, but this really feels like analysis-slop. It's only remarkable in terms of who is publicizing it.
It makes sense to focus all effort into building a time machine.
But what gives me pause is that a some of the mag 7 (think Meta) could change their mind on AI build-out tomorrow, and 1-year from now have the same amazing free cash flow they always did.
I would naively expect Microsoft’s to be the highest since they are probably mainly just selling access to their capex through cloud since they aren’t seriously pursuing frontier AI, I’d imagine Google to be in the middle (selling TPUs, general cloud GPUs, Gemini, revenue lift on ads from better AI) but also spending heavily on infra to compete with OAI/ Anthropic, and then Meta to be on the low end since they are likely getting serious revenue lift from AI but not monetizing their models by API.
That is the slide that is likely to pop the economy.
Page 8 for Oracle's free cash flow trending negative is really quite impactful. The Bloomberg AI bubble diagram [1] shows how this could really blow up. If Oracle falls they could take the whole market with them. We're just waiting on the mag 7 or any closely linked companies to fail to raise investment.
Page 16 really outlines how insane these evaluations are. I think most countries see it, hence aggressive selloffs of US bonds [2]. But everybody is just too insanely heavily exposed to it all now, it's going to wipe out everything. It's going to be a very awful time when heavily debt strapped countries can't issue debt anymore.
I think what we're going to see is some insane moves to keep these companies afloat longer in some desperate attempt to delay the pop, which will just make a bigger bubble. I could see Nvidia for example issuing bonds in excess of $100bn soon if the market has appetite for it [3].
[1] https://archive.is/0bYLS
[2] https://sg.finance.yahoo.com/news/china-japan-uae-india-sell...
[3] https://uk.finance.yahoo.com/news/nvidia-raises-over-21-5bn-...
OK, I guess it _would_ be pretty hard to have an _unrecoverable_ crash...
Mag7 is just an arbitrary list of companies that were coined at a specific time with no rigor.
If you must do rigorous analysis, then just like S&P 500 you need to add drop BigTech / High Growth companies continuously to this Mag7 (or Mag10) and then do analysis
“Do they make money? I don’t know but I know they’re magnificent!”
https://finance.yahoo.com/markets/article/magnificent-7-stoc...
> The once high-flying "Magnificent Seven" are looking more like the Dreadful Seven.
> The why: Wall Street is growing increasingly impatient with Big Tech's astronomical capital expenditures on artificial intelligence, projected to balloon 70% to exceed $700 billion this year.
Amazon $200B
MS $190B
Alphabet $175B-$185B
Meta $115B-135B
https://finance.yahoo.com/news/apple-lazy-ai-strategy-could-...
If a good enough model can be swapped in every few months, the value moves away from the model and toward cheap inference. That is great for users, but not always great for returns on huge capex.
-signed a bitter somebody that had to buy a new SD card for my camera last week.
One major part of the investment thesis in these companies were their constant stock buy backs. Now their gargantuan Capex that sees no end but acceleration is back at diluting investors.
I think the companies will keep doing fine, but the financial outlooks are no longer as rosy.
This is why we are seeing a correction at those companies, perks and free food going away with constant layoffs and all time low morale.
Now the party is at Nvidia. But I will tell you that that will not last forever either.
Maybe even the state of unprecedented relative peace we had enjoyed.
Waiting for next game, bets are open, any new names? O A S I S? upcoming IPOs and new names needed so they can exit scam
And the bar chart for token costs, really? As if that’s information? Their sources are the API docs ffs. If they had at least modeled something to estimate token costs that would be interesting, but showing the public prices and calling it research is dumb.
I'm not sure what was said during what looks like a deck of a presentation? I'm hoping it wasn't this, because that's an obvious misfire.
That's more than their combined FCF, and they're borrowing to bridge the gap.
https://finance.yahoo.com/sectors/technology/articles/mark-z...
https://www.nytimes.com/2026/03/19/technology/mark-zuckerber... | https://archive.today/iEGAj
Ah, the old _argumentum ad giletum Patagoniae_
If only that's a measure of if they know how to time the stock market. The real measure is how much they earn not if their sales or marketing department manages to get more customers.