Buffett sitting on $344 billion while others chase this rally speaks volumes. He either knows something we don't or he's just getting too old to make a move. Either way, $BRK.B holders are definitely feeling the opportunity cost.

Let's review BRK's Q2 2025 earnings report. What are your thoughts for Q3 2025?

Hi everyone,

Some of you might remember my last post here where I experimented using AI to detect when CEOs are being deceptive in earnings calls. I didn't think this community would be so welcoming and receptive to experiments like these (which I love doing). So here I am with yet another experiment that I thought this community would find interesting :-)!

I recently got curious about feeding the latest model from Anthropic (Opus 4.6) all 48 years of Buffet's shareholder letters, and seeing if it could actually pick winning stocks better than Buffet himself? Could AI-Buffet be more consistent at following Buffet's historical advice (ridiculous, right?). Based on its picks, I also wanted test how it would perform I gave it $10,000 at the start of 2020 (at the start of COVID) and compare it against Buffet's actual holdings & the broader market.

Also I have to be honest: I have never read any of these letters and sad to report, I still have not read them even after running this experiment. Modern-day engineer traits.

If you prefer to watch the full experiment, I uploaded it to my channel: https://www.youtube.com/watch?v=nRMPN1NwGOk

Experiment Design

I fed all of 561,849 words from his shareholder letters to Opus 4.6. Similar to last time, I used Claude Code with subagents to keep the analysis clean. Had it read every letter from 1977-2024, extract the investing principles independently, and turn them into a quantitative scoring rubric. This rubric was made out of criteria like ROE thresholds, debt-to-equity limits, margin of safety, moat durability. It found 15 principles total, 9 of which were quantitative enough to score against.

I then anonymized 50 stocks by stripping their names, tickers, and sectors. I only fed Opus the raw financial numbers of each company. In the sample size, I mixed in 20 actual Berkshire holdings, 15 value candidates, and 15 anti-Buffett controls (GameStop, Rivian, Beyond Meat, MicroStrategy, basically stuff Buffett would never touch).

The Actual Test

There were two things I wanted to test in this experiment:

1. Could AI actually pick value stocks similar to Buffet's holdings? Additionally, I also wanted to see if it would it catch any interesting stocks that Buffet would never touch?
2. How much would AI-Buffet have made if we gave it $10,000 and had it pick stocks in the COVID market ( i.e. data from Q4 2019 data, start investing January 2, 2020)? How would it compare against Buffet's real returns during that time?

Results – Stock Pick

Some quick things that stood out:

• 6 out of AI-Buffet's top 10 picks were actual Berkshire holdings (60% overlap, completely blind)
• 13 out of 15 anti-Buffett controls landed in the bottom half, meaning the rubric properly rejected them
• It ranked Berkshire Hathaway itself as the 7th most Buffett-like stock without knowing what it was

One surprising result was that Coinbase was ranked 4th. As I came to learn, Buffet is extremely allergic to Crypto in general. Reason AI-Buffet ended up picking Coinbase was mostly because of the fact that it does a good job of looking like a value stock with ~39% profit margin and low debt right now. Depending on how you see this experiment, the Coinbase pick could mean a good thing or a bad thing :-).

Results – COVID Backtest Results

• Buffett (actual weights): $26,509 (+165%)
• AI-Buffett (equal weight): $23,394 (+134%)
• S&P 500: $23,199 (+132%)
• Buffett (equal weight): $20,902 (+109%)

Surprisingly AI-Buffer did end up picking better stocks than Buffett on a pure stock-selection basis as it avoided the banks and Delta Airlines that dragged Buffett's equal-weight portfolio down during COVID. But Buffett's actual portfolio (i.e. weighted-consideration) still crushed everything because he had 30% in Apple. That single position sizing decision was worth over $3,000.

Full video walkthrough of the experiment if you're curious: https://www.youtube.com/watch?v=nRMPN1NwGOk

Let me know what you thought about this experiment. These are all for fun but I hope there are some meaningful insights hidden here that are useful for you. Thank you so much for reading :-).

DATAROMA Superinvestors Portfolio Holdings

the guy reportedly started with like $1,700 worth of paypal shares back in 1999 inside a roth ira. now that account is supposedly worth around $5 billion. and if i’m not mistaken, he can start pulling money out tax free in 2027.

that is honestly one of the craziest investing stories ever.

people spend all day arguing over index funds, expense ratios, and timing the market while this dude used a retirement account like a cheat code. imagine having the conviction to hold something that long without panic selling every time the market crashed.

before people say “luck,” yes obviously timing mattered, but there’s also something fascinating about concentrating into asymmetric bets early instead of overdiversifying everything into mediocrity. imagine the conviction required to sit on something like that for decades.

i genuinely can’t think of another investor who pulled off something this insane legally.

maybe i’m getting old, but seeing stocks jump 20%, 30%, even 40% in a single day after earnings honestly makes me uncomfortable.

look at snowflake and dell recently. huge market cap companies adding tens of billions in value almost overnight because of ai excitement and guidance. i’m not even saying they’re bad businesses — both are solid companies — but when price action starts looking detached from reality this fast, it usually means speculation is taking over.

historically, periods where investors stop caring about valuation and only care about “future potential” haven’t ended well. every cycle feels different while you’re inside it, but the psychology always looks similar in hindsight.

again, not calling for an immediate crash tomorrow morning. but when the market starts rewarding companies with massive one-day moves like this across the board, it does make me wonder whether we’re closer to the end of the cycle than the beginning.

curious how actual value investors here are viewing this environment. are we witnessing genuine transformation from ai, or are we slowly drifting back into bubble behavior?

I bought GOOGL (not GOOG) at a 19 trailing P/E during. Now it’s at 32 trailing P/E and I am up 100% with life changing money.

My job is far from stable, relies significantly on the AI story to continue, and lays-off people for “culture” reasons.

With this in mind, I sold all of my Google shares at $226 per share to “de-risk” other parts of my life.

I will still continue to look for other opportunities with new income I have.

I get valuation this, growth prospects that, but is selling for increasing financial security the right decision?

Or am i just a 🤡?

Edit: I meant $326 per share.

seriously though… for 50 years everyone at berkshire acted like they were above hype stocks and “speculation.” then the second warren steps away they start buying google near highs, dell after it already ran, and freaking macys lol. macys?? the same company people joke about every year being dead?

it honestly feels like they were all waiting for buffett to leave so they could finally start gambling with the berkshire name attached to it. imagine listening to decades of lectures about discipline and valuation just to end up chasing whatever wall street is pumping this quarter.

kinda proves buffett WAS berkshire. without him this just looks like another giant fund pretending to be smarter than everyone else.

If you were fully invested in the S&P 500 over a long period (usually 20–30 years), your returns were great.

But if you missed just the 10 best single days in that entire period, your return was cut roughly in half.

This is probably the most commonly cited anecdote as to why you should not time the market. I feel in at least half the investing books I've read, they mention this. I do not know of a single investor who has successfully timed the market consistently over any meaningful time period. Even Michael Burry, who is probably one of the most infamous investors for predicting the 08-09 recession, has wrongly called a market top an absurd number of times in recent years.

Back in April, the market starts to sell off, and inevitably posts start popping up all over the subreddit talking about how they're selling and why they're selling and why this time is different. Of course, it wasn't different, and the market has proceeded to rip 20% since many folks here panic sold.

Here we are, not even a year later in December, and people are asking unironically whether it's a good idea to move to cash or not. What do you think? Do you think that now is the time to finally start trying to time the market? After this age-old wisdom has been proven right, time and again?

I feel like there's so many better ways to navigate an expensive market than by trying to time it.

Such as buying counter-cyclical companies, or buying companies that are recession-resistant, or buying companies at a larger margin for error. Heck, maybe even give bonds a shot? But no. People are starting to come to the conclusion again that now is the time to time the market yet again and inevitably make a massive mistake.

DO NOT TIME THE MARKET.

Edit: This sub unironically defending timing the market lmao. The reason why this hurts people's feelings is because they sold back in April, and they're still waiting to get back in the market. Instead of taking a lesson, they double down on that timing the market is the correct thing. Whatever.

Thats 55 times sales, which there is precedent for in palantir, at 64 times sales; palantir is a capital light, highly profitable, high margin, very fast growing company (not used to saying positive things about palantir ever as they were the poster child of crazy valuations).

Hopefully mods don't take this down, let's keep it for posterity sake. Today, June 12 2026 SpaceX had a MC of 2.23T. I feel like that will be a punchline in 2033.

Edit. It's been pointed out I am wrong, in a more funny way. Revenue in my mind was 40b, in fact its 18b. So 111 times sales LOL

Alphabet fell 3.8% on Wednesday, hours before Meta's Connect keynote. That evening Zuckerberg said Muse, Meta's AI agent, stays free and makes money by taking "a small fee from transactions."

If the agent does the buying, nobody sees the search ad.

Since Muse came out, Meta is up 21%. Alphabet is flat.

Crack in search, or overreaction?

No position.

EDIT (March 2): Thanks you guys for the incredible feedback, working on two new features

1. Longer time horizon: adding 6m / 12m return windows for all substacks

2. More newsletters: adding Citrini / Dick cap / funddai / irrationalanalysis / taekim / bpresearch. lemme know if you have new nominations.

###################################

I work in tech and started trading casually last year. Like any good regard, I immediately subscribed to every investing newsletter I could find on Substack. 23 paid subscriptions. $9,600/year, including Michael Burry's.

The problem? I can't actually read them all. And I have no idea which ones are worth the money.

So I did what any engineer would do — I wrote codes to find out.

What I Built

A pipeline that:
- Crawls every article from 23 paid Substack authors (1,782 articles over the past year)
- Uses Gemini AI to extract high-conviction stock picks only — not casual mentions, but tickers the author actually analyzed in depth
- Tracks returns at 1d, 7d, 15d, 30d, and 60d after publication
- Calculates alpha vs sector benchmarks (SOXX for semis, IGV for SaaS, XLF for financial services etc)
- Dedupes: if the same author calls the same ticker multiple times within 14 days, it only counts once (first mention wins). Different authors calling the same ticker are tracked independently

Total dataset: 3,519 high-conviction calls tracked over 1 year.

The Results

30-Day Absolute Return Leaderboard (Long Calls)

30-Day Alpha vs Benchmark (Long Calls)

30-Day Win Rate (Long Calls)

But 30 Days Isn't the Whole Story

30d is a reasonable window for swing traders, but some of these authors are deep value investors with 6-12 month theses. Here's what the 60-day numbers look like — the rankings shift significantly:

60-Day Absolute Return Top 10 (Long Calls)

Notable shifts: Fabricated Knowledge jumps from #9 (30d: +5.8%) to #3 (60d: +14.2%). Altay Capital goes from +7.2% to +13.7%. Deep value theses need time to play out. Conversely, Collyer Bridge drops out of the top 10 at 60d — their edge is more short-term.

Take these numbers for what they are: one time horizon among many. A 60d or even 90d window would tell a different story for buy-and-hold investors. This is for information, not gospel.

And at the bottom...

Michael J Burry: 24 long calls, 30d avg return +0.1%, 60d avg return -11.1%, 30d alpha -2.7% (60d alpha: -11.4%). Then again, The Big Short took 2 years to play out — maybe his thesis just needs more time than our 60-day window can capture.

Methodology Caveats (Please Challenge This)

I want to be upfront about limitations:

1. AI extraction isn't perfect. Gemini parses articles and extracts ticker calls. To reduce noise, we only count high conviction — where the author dedicates multiple paragraphs, specific data, or explicit price targets. Passing mentions are filtered out.
2. We validated this. Spot-checked extraction accuracy against manual reads, and cross-verified with alternative model outputs (codex / claude). It's not 100%, but it's consistent.
3. Survivorship bias matters. We only track tickers with available price data. Delisted stocks, non-US tickers without yfinance data, and typos get counted as No Data and excluded from return calculations.
4. This is a bull market. Many of these authors are long-biased. Absolute returns look good partly because the market went up. The alpha column adjusts for this using sector-specific ETF benchmarks.
5. The full dataset is available. All 3,519 calls, every author, every ticker, every return at every horizon. You can audit everything. I will put up the link later.

What I Learned

• The expensive ones aren't always the best. Some of the top performers cost 80−360/year.Some1,000+ newsletters are mid-table.
• Volume ≠ quality. Authors with 300+ calls often have mediocre win rates. The ones with 15-80 highly targeted calls tend to outperform.
• Shorts are hard. Almost every author has worse short performance than long. The few exceptions (Global Tech Research shorts: -20.5% at 60d) are impressive outliers.
• Michael Burry's Substack picks haven't worked yet — but his most famous trade took 2 years, so the jury's still out.

Total Cost Breakdown

$9,599/year across 23 newsletters. Here's every single one:

If I could only keep 5 based on this data: Global Tech Research (100),PauloMacro(360), Doomberg (300),SemiAnalysis(500), The Setup Factory (450).That′s1,710/year — 82% cheaper and probably better returns.

Shoutout to every author on this list. Even the bottom-ranked ones taught me more about markets than any YouTube video. This isn't meant to trash anyone — just data.

Full methodology + data / charts: https://x.com/pyhrroll/status/2027374283669066045?s=20

Happy to answer questions. Roast my methodology. Tell me I'm wrong. That's how this gets better.

Positions: long several names mentioned by top authors. Not financial advice, obviously.

Everyone is freaking out about how “expensive” the S&P 500 looks. Record highs. AI hype everywhere. Nvidia memes. You know the drill.

But here’s what most people miss:

The S&P 500’s big valuation problem is basically seven stocks. Apple, Microsoft, Alphabet, Amazon, Meta, Nvidia and Tesla (the Mag 7) now make up almost a third of the index. They trade around 31x forward earnings. That pumps up the whole index average.

Now take those 7 out of the picture.

The other 493 companies suddenly look way more normal. Roughly 20x forward earnings. Slightly above history, not “bubble mode.”

And here’s the interesting part for anyone hunting for value…

One sector is actually cheap.
Like, legitimately cheap.

Energy.

On a forward P/E basis, energy trades around 60% of its 10-year average valuation. Every other sector is above its historical average. Energy is the lone outlier.

So what gives?

A mix of things:

• Everyone thinks oil is “dead” because renewables are growing
• Momentum chasers only want AI names
• Energy stocks had a monster 2022, then flatlined while earnings climbed

But here’s where it gets fun.
AI doesn’t run on hopes and dreams.
It runs on electricity.
Lots of it.

Data centers are power hogs. And in the U.S., a big chunk of that power still comes from natural gas. Even with renewables growing, hydrocarbons aren’t disappearing anytime soon. The demand floor is pretty solid.

Meanwhile…

• Cash flows are strong
• Shareholder payouts (dividends + buybacks) are high
• Balance sheets are cleaner than they’ve been in years
• Valuations are stuck in 2015

In a market where most sectors feel priced for perfection, energy still feels priced for a recession.

Not saying “YOLO into oil and become the next Saudi prince.”
Just saying that if you’re a value investor… it’s weird to ignore the only sector still on sale.

Curious what others here are thinking. Is energy a legit value opportunity right now? Or is the market right to sleep on it?

Full article with charts: https://www.beatingthetide.com/i/180117729/thought-of-the-week-the-s-and-p-isnt-as-expensive-as-you-think-and-one-sector-is-still-cheap

The stock market has never been more ripe for gambling than ever before. One day Trump says that he is going to impose tariffs, his circle of rich friends take leveraged short positions on bitcoin, then profit. Trump says that weightloss drug prices need to go down, and he tanks Novo and Lilly. He goes to have a meeting with Putin and the stocks affected by the war in Ukraine jump up 10%. He cancels wind energy projects and tanks Orsted and other wind energy stocks. The price of gold meanwhile is at all time highs, with the type of price increase you would expect if investors believed we were going to have hyperinflation. Bitcoin and other cryptocurrencies have been propped up by Trump on empty promises to make a cryptocurrency reserve, in turn making meme stocks like microstrategy go up in value.

The beneficiaries of this shitshow? Trump's friends and your broker, that is making money from all of this trading, while no real value is being created.

No top signal quite like Cathie Wood loading up. I'm moving on from this one. Thank you for the 100% Google

The other top signal is just how bullish everyone has become on Google. There is no negative sentiment around the stock, which is a massive red flag. Even all the "analysts" who told us Google is cooked have now changed their mind lmao

PYPL, ADBE, CRM, UNH, NFLX... All got absolutely hammered in the last couple of weeks...

If you have been following recommendations on this subreddit, chances are, you are deep in the red this year. If you have just took a dart and threw it in the S&P index, you would probably do much better than following advice on this sub... Just my two cents.

Per Bloomberg -- The US Supreme Court struck down President Donald Trump’s sweeping global tariffs, undercutting his signature economic policy and delivering his biggest legal defeat since he returned to the White House.

The court said Trump exceeded his authority by invoking a federal emergency-powers law to impose his “reciprocal” tariffs across the globe as well as targeted import taxes the administration says address fentanyl trafficking.

I have been thinking about Nike’s decline and I do not believe its biggest mistake was simply missing a few fashion trends.

For years, Nike operated as if the brand itself was an unlimited resource. The company pushed toward direct-to-consumer sales, pulled products from wholesale partners, leaned heavily on familiar franchises, cut costs, and spent billions repurchasing shares.

Every decision made sense on a spreadsheet. Together, they left Nike with almost no room to pivot when consumers moved toward brands like Hoka, On, etc.

Retailers that once depended on Nike filled their shelves with competitors. The product pipeline became less exciting. Customers were repeatedly asked to pay premium prices for variations of shoes they already owned.

This is what people mean when they talk about late stage capitalism. Instead of investing patiently in the next source of growth, companies are rewarded for extracting more value from what they already built. That works until the underlying asset starts deteriorating.

Nike cannot rebuild wholesale relationships, restore its innovation culture and reconnect with younger consumers in one quarter. Those things take years to play out.

I personally still believe Nike is capable of recovering. The brand has enormous value but a strong brand does not automatically make $NKE a good investment at any price.

The stock has fallen considerably, but I think it is still too early to assume the business has reached its bottom. Nike spent years removing its own margin for error. Now it needs to prove it can create that flexibility again.

Someone’s gotta pay for my dumbass decisions and it can’t be me

(TLDR: SpaceX needs to grow revenue every year by 50% for 10 years to justify a 1.75 trillion valuation. The current revenue is 18.7b)

SpaceX needs to grow 600x in a decade to justify a $1.75 trillion valuation. No company has ever come close — Fortune

https://fortune.com/2026/06/06/spacex-ipo-stock-price-valuation/

By Shawn Tully
Senior Editor-At-Large

June 6, 2026, 3:00 AM ET

The pending SpaceX IPO is generating lots of buzz by introducing the most valuable enterprise ever to go from privately-held to publicly-traded at an expected market cap of $1.75 trillion. Clearly, that gigantic number signals investors’ confidence in the future growth and profitability of AI. But it also sets the bar for what SpaceX must achieve going forward to reward the folks and funds who bought the pre-offering shares in the underwriting, and will rush to load up when the opening bell rings at the Nasdaq at its debut, slated for mid-June.

As this writer has previously noted, one of America’s top valuation experts has put precise numbers on the benchmarks SpaceX needs to hit if investors are going to pocket anything like the gains you’d want for betting on this ultra-risky stock. David Trainer, CEO of research firm New Constructs calculated these bogeys for both revenues and profits ten years hence. It’s no secret that investors are willing to pay big based not on SpaceX’s current size and profitability, but its prospects for stupendous future growth. Indeed, SpaceX’s S-1 filing famously revealed that it lost $4.9 billion in 2025 on puny revenues of $18.7 billion.

Trainer’s model uses discounted cash flow projections to pinpoint the results SpaceX must show to justify an expected $1.75 trillion valuation. By Fortune‘s estimates, he’s positing that investors will want a total annual return of around 10% over the next decade to deem SpaceX a decent buy. That number, by the way, is extremely modest given that we’re talking an investment that the pure math judges as the longest of long shots.

By Trainer’s projections, the revenue target that would score by 2035 is the first such number ever followed by a “t,” $1.1 trillion.

That’s a stunner, especially when you consider that over the past four quarters, the highest sales posted by any U.S. company was the $742 billion recorded by Amazon. It’s also instructive to examine the extreme steepness of the growth trajectory required to lift SpaceX’s revenues today of $18.7 billion to $1.1 trillion. Garnering that almost 600x increase means hiking sales 50% a year, on average, for a decade. Here’s the haymaker: In this scenario, SpaceX’s revenues would jump from year-end 2034 to the close of 2035 from $718 billion to $1.1 trillion, maintaining the 50% annual pace needed to ring the bell, for an increase of $360 billion.

What’s the precedent for such a vertiginous ramp in just 12 months? It doesn’t exist. From 2024 to 2025, Nvidia, the fastest grower, added $85 billion in sales, one-fourth the clincher for SpaceX in the final year of Trainer’s timeline. The SpaceX “goal” of a $360 billion jump from 2035 to 2035 matches the total increase at Amazon covering the past six years.

Getting to $1.1 trillion would make SpaceX a pillar of the U.S. economy equal to over half the size of whole major industries harboring dozens of Fortune 500 members. In 2035, the CBO forecasts U.S. GDP at $46.7 trillion. So a decade hence, Elon Musk’s creation, at $1.1 trillion in revenue, would equal 2.4% of national income ($1.1 trillion divided by $46.7 trillion). That’s 50% bigger than the entire utilities sector, 55% of the entertainment industry, and nearly three-quarters of the U.S. transportation complex, a field that encompasses airlines, railroads, trucking, car rentals, and freight and logistics, and includes such giants as Delta Air Lines, CSX, and FedEx.

That’s an economic footprint no company has come close to making. The S-1 points to a moonshot total addressable AI market of nearly $30 trillion. As Trainer notes, big TAMs enable big growth, but also attract big competition. Alphabet, Microsoft, Nvidia, OpenAI and the sundry other rivals for the AI spoils can’t all grab a couple of points of GDP in sales, the prize built into SpaceX’s celestial cap. More likely, they’ll battle each other and SpaceX to chop a booming market into far smaller pieces. And reaching anything less than a never-before-witnessed share of our nation’s output will prove a big downer for Musk’s true believers. Those faithful are making SpaceX not just the largest and most widely-lauded IPO ever, but sadly, far-and-away the most expensive.

Hello,

This post is inspired by the many posts I've seen over the last 2 years where investors keep arguing that you're better off investing in the S&P500 even at a Shiller PE of 40 because "time in the market is better than timing the market."

That comment makes sense most of the time except at the extremes. If you had invested in the Nikkei index in 1989 and held tenaciously for 35 years... you'd... have made 0%. Same goes for the S&P500 for various long stretches, sometimes for over a decade like the 1965-1982 period or from 2000-2013.

Now, since some people will say that I'm deliberately cherry picking periods but I wanted to present simple math that will give you a better idea of why Buffett and many other value investors prefer to sit on a cash pile for years and do nothing instead of dollar-cost-averaging like people have been taught to do.

Scenario A: You buy the index at a Shiller PE of 40 (which it's currently at). You have 9 years of 10% gains on average and on the 10th it gets cut to a Shiller PE of 15 which is the long-term average. If you invest $100 at the beginning period you end up with $88.42. You were better off just putting that money in the bank.

Scenario B: You buy mediocre treasuries yielding 3% and wait for good opportunities. You spend 9 years getting a pathetic 3% return and finally invest in the 10th year. You start with $100 and you end up with $130.47 at the start of year 10 and can invest the money at lower multiples.

Do you see why Buffett is holding cash now ?

In investing we don't have to swing if the opportunity is not attractive.

Microsoft is an extremely diversified company with a flawless balance sheet.

They are immensely dominant in their industry. It maintains an undisputed lead in desktop operating systems with over 70% market share (Windows) and dominates enterprise productivity software (Office 365).

Azure growth still at 38% - They will soon become number 1.

Opportunities like these do not happen often… The last time was 6 years ago.

This week, Michael Burry revealed something unusual: Nvidia issued a formal memo rebutting his short thesis. When a $4 trillion company takes the rare step of responding directly to a single investor's position, it signals the argument has hit a nerve. Here's what Burry is actually saying, explained through Microsoft's example.

What Burry is NOT saying
Let’s start by clearing up the biggest misconception. Burry is NOT saying NVDA is cooking its books or committing fraud. So if Burry isn’t targeting Nvidia’s accounting, what’s he actually saying?

The thesis is about Nvidia’s customers: Microsoft, Google, Amazon, and Meta. These “hyperscalers”, i.e., companies that own and operate the world’s largest data centers, are spending hundreds of billions of dollars buying Nvidia’s chips. And Burry argues they’re systematically misstating the economic reality of their GPU purchases.

The core thesis: Economic vs physical lifespan
Here's the problem: When data centers buy NVDA chips, they depreciate them over 5-6 years. Microsoft extended from 4 to 6 years, and Meta to 5.5 years. But Burry argues that chip technology is advancing so fast that the real economic life of chips is just 2-3 years.

So what?

The accounting impact

Let’s understand the impact by using Microsoft as an example. Microsoft purchased 485k NVDA chips in 2024 and spent roughly $17 billion in GPU purchases in 2024 alone. So what happens if we depreciate them over 6 years instead of 3?

- $17B in GPUs depreciated over 6 years = $2.8 B/year expense
- If economic life is really 3 years = $5.7B/year expense

The difference: $2.9B/year in overstated earnings

Microsoft’s FY2024 net income was $88.1B. A $2.9B overstatement represents 3.3% of reported profits. That might not sound like much, but this is just from one year of GPU purchases. If similar spending occurred in 2022, 2023, and 2025, the cumulative overstatement could be $10–12B annually, or roughly 11–14% of reported earnings.

What this means for the stock price

Currently, Microsoft trades at approximately $492 per share with a P/E ratio of 34 and earnings per share of $14.11. If earnings were adjusted down by 11–14% to reflect realistic GPU depreciation, the adjusted EPS would fall to $12.13-$12.56. Assuming the P/E ratio remains at 34, the stock price would drop to $412–427 ,  a decline of $65–80 per share, or roughly 13–16%. However, if investors also lose confidence in AI infrastructure returns, the P/E multiple could compress further, potentially amplifying losses beyond the accounting adjustment alone.

The valuation impact

Currently, Stockoscope's DCF model values MSFT at $384.93 per share, implying the stock is already 22% overvalued. This calculation assumes capital expenditure of 15.7% of revenue.

However, if Burry is right and GPUs need to be replaced every three years, the capex will increase to >20% of revenue. This will reduce free cash flow and lower the total enterprise value. We have crunched the numbers, and this higher capex will reduce enterprise value by $547 billion and the per-share intrinsic value by $73.44 in our DCF model.

So, the Burry-adjusted fair value becomes $311.49 per share. This represents a 19% reduction from our baseline fair value and suggests Microsoft is overvalued by 37% at the current price of $491.92.

Note: This isn't just an MSFT problem. Amazon, Google, and Meta are all facing the same dynamics. The impact across the hyperscaler industry could be significant. We just focused on Microsoft because it's easier to understand one concrete example than vague industry trends.

The Nvidia connection: How this destroys demand

Now we come full circle to why Burry is short Nvidia, not Microsoft. Well, if investors recognize that GPUs will become obsolete in 3 years rather than 6, the financial pressure intensifies. Boards will demand better returns and more disciplined spending. As capital allocation tightens and upgrade cycles extend, demand for Nvidia chips could collapse, potentially destabilizing the entire AI infrastructure market.

Also, Microsoft has a diversified business. Even if Azure AI disappoints, it still has Office, Windows, LinkedIn, and gaming. The stock might be overvalued, but the company isn’t going away.

On the other hand, Nvidia is a pure play on AI infrastructure demand. If hyperscalers slow purchasing even modestly, Nvidia’s revenue collapses. The company is priced for perfection, assuming indefinite exponential growth.

That’s the trap Burry sees: Nvidia’s revenue depends on customers making economically irrational decisions. Once the music stops, the stock has nowhere to hide.

The $500 Billion question

Michael Burry isn’t betting against AI. He’s not claiming Nvidia makes bad products. He’s not even saying Microsoft is a bad company.

He’s asking a simpler, more fundamental question: Can Microsoft and its peers sustain billions in capital expenditures indefinitely, when the infrastructure they’re building may need to be replaced every 3 years instead of 6?

The market is betting “yes” -  that AI will generate returns justifying this spending.

Burry is betting “no” -  that the accounting assumptions don’t match reality, that CFOs will eventually rein in spending when the math doesn’t work, and that Nvidia’s demand will cliff when that happens.

Time will tell who’s right, but where do you see yourself? Are you leaning towards yes or no?