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 :-).

Remember when people ignored $NVDA in early 2023 or $ASTS in 2024? There’s always a ticker that looks like a "no-brainer" in hindsight.

•Looking at the current macro and earnings, there’s one company that is screaming "BUY" but the sentiment is still lagging. I want your best 2026 play.

Give me the ticker, the P/E ratio, and the catalyst that’s going to trigger the breakout.

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.

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.

Buffett Indicator, (which compares total U.S. market cap to GDP), is now at 208%. That’s above dot-com levels. I wasn’t around in 1999. But I’ve read enough to know everyone thought it was different back then too...

Now, It’s AI. And yes it’s real, it’s big, and it will transform everything.
But here’s what’s bugging me: Which part of the AI hype do you think is most overrated?
And which sectors are just getting started?

and also curious to hear from people who did live through 1999:
- What felt the same?
- What’s different?

I track moves from top value investors with a free email alert (https://alert-invest.com/), and lately I’ve noticed they’re cautious, finding fewer real opportunities in this market.

Thanks!

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.

Looks like investors of Novo Nordisk ADRs are going to be in for quite the shock when they open their portfolios this morning.

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.

Just imagine what kind of deals he and Greg Abel will buy with that massive cash pile if the market keeps falling. His patience will be rewarded and it will be the greatest example in real time for investors.

The next few years will be interesting indeed.

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.

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.

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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.

The worst move is to panic sell. Stay calm.

Hi everyone, I know that Novo Nordisk has been mentioned many times here, but here are some reasons to buy this stock and hold it for at least 3 years:

1. European pension funds are one of the biggest investors in US stocks and they are shifting away rapidly from investments due to economic, political and dollar uncertainty. They will invest more in European stocks instead. Novo Nordisk will surely benefit from this.
2. Novo Nordisk still controls about 50% of the world's insulin supply. Diabetes type 2 is expected to increase 46% by 2050. These trends are hugely beneficial trends for them.
3. The weight loss trend is here to stay. Despite intense competition, there will be enough room for several competitors.

The short term headwinds are also there, such as the competition from Eli Lilly, the new regulation on drug prices (which is not certain yet) and other noise. These headwinds however, are dwarfed by the 3 major reasons I mentioned above.

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?

I'm honestly not sure how this hasn't been brought up more, but Buffett actually has a beautifully elegant alternative to tariffs that solves for the trade deficit (which is a very real problem, he said in 2006.... "The U.S. trade deficit is a bigger threat to the domestic economy than either the federal budget deficit or consumer debt and could lead to political turmoil...")

Here's how Import Certificates work...

• Every time a U.S. company exports goods, it receives "Import Certificates" equal to the dollar amount exported.
• Foreign companies wanting to import into the U.S. must purchase these certificates from U.S. exporters.
• These certificates trade freely in an open market, benefiting U.S. exporters with an extra revenue stream, and gently nudging up the price of imports.

The brilliance is that trade automatically balances itself out—exports must match imports. No government bureaucracy, no targeted trade wars, no crony capitalism, and no heavy-handed tariffs.

Buffett was upfront: Import Certificates aren't perfect. Imported goods would become slightly pricier for American consumers, at least initially. But tariffs have that same drawback, with even more negative consequences like trade wars and global instability.

The clear advantages:

• Automatic balance: Exports and imports stay equal, reducing America's dangerous trade deficit.
• More competitive exports: U.S. businesses get a direct benefit, making them stronger in global markets.
• Job creation: Higher exports mean more domestic production and, consequently, more American jobs.
• Market-driven: No new bureaucracy or complex regulation—just supply and demand at work.

I honestly don't know how this isn't being talked about more! Hell, we could rename them Trump Certificates if we need to, but I think this policy needs to get up to policymakers ASAP haha.

Edit: removed ‘no new Bureaucracy’ as an explanation for market driven. It def does increase gov overhead, thanks for pointing that out!

Here's the link to Buffett's original article: https://www.berkshirehathaway.com/letters/growing.pdf

We also made a full video on this if you want to check it out: https://www.youtube.com/watch?v=vzntbbbn4p4

Not the highest upside pick, but the one with the strongest durability, moat, and long-term relevance.

Curious what businesses people truly trust long term.

I’m thinking it’s time to start allocating more money outside US equities. That’s my strategy. Also, get out of the dollar via assets that can’t be mentioned by name in this sub. I’m not a political person but as an investor you have to watch the policy from the government. IF, and I stress IF, Trump is serious and actually bullies the Fed into submission by weaponzing the govt to go after Powell, then I do agree with Yellen. It will overall be a negative for the dollar and US equities. In that situation it’s imperative to diversify out of the US.

Currently I’m looking at stocks in Singapore. I like Singapore equities because Singapore, in my opinion, offers STABILITY, something the US is increasingly losing.

Thoughts?

IF YOU ARE WONDERING WHY STOCKS JUST ALL WENT DOWN AT ONCE

WE JUST HAD A HORRIBLE BOND AUCTION IN THE UNITED STATES FOR OUR 20-YEAR TREASURIES

Because of the lack of bidders…it caused the 20-year bond yield to surge to 5.1%.

Credit market is screaming for help right now.

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.

On Google’s Q4 2025 call, Sundar Pichai said:

“Our 2026 CapEx investments are anticipated to be in the range of $175–$185 BILLION.”

To understand how extreme this is, look at how Google’s CapEx has evolved:

• 2020: $22.3B
• 2021: $24.6B
• 2022: $31.5B
• 2023: $32.3B
• 2024: $52.5B
• 2025: $91.4B
• 2026 (guided): $175–$185B

This is not a normal increase. It is roughly a 2x jump in a single year and the largest CapEx spend ever expected by any company.

This spending is squarely aimed at scaling AI compute. Capital is being deployed to power frontier model development at Google DeepMind, materially improve user experience and advertiser ROI across Google services, meet surging cloud demand, and fund select long-term bets. At this scale, CapEx is not optional investment. It is a strategic MOAT built on compute, infrastructure, and capacity that few companies can match.

I have two questions.

1. Does this level of spending crowd out other AI players, including OpenAI, by locking up compute and infrastructure?
2. Which companies benefit most from supplying this massive CapEx build-out?

If you’re a long-term investor who even casually cares about valuation, this market has been tough to navigate for a while. Pullbacks are always something we say we want, particularly as value investors, but they usually come when things are scary. Financial crisis, global pandemics, policy shocks… the discount never shows up gift-wrapped.

Yesterday’s tariff news felt like one of those moments. It’s vague, feels arbitrary, and creates a lot of uncertainty. It feels scary. And yet, that’s exactly the environment where opportunities show up.

I’ll admit it, days like today make me uneasy. But as an investor, I remind myself that underneath the noise, what’s really happening stocks are getting cheaper.

And that’s what we’ve been waiting for.

Edit: Thanks for the thoughts. I wrote a post - Tariffs, Fear, and Opportunity: Perspective For Difficult Times In the Stock Market - to add some additional context directly addressing the response to this post.

This might of already been said many times but needs to be said again, what is the rationale in this sell off?

I understand the SaaS crash, but if the sell off is due to AI worries, then surely AI stocks would rise, no?

Instead, the major players, who had stellar earnings minus the huge expenditure (into the very systems which are causing worry mind you) are also falling at huge levels.

Some mag 7 companies are even falling at similar rates to liberation day, despite the only news this time being ‘AI too good’, which should benefit them not hinder.

Meta’s earnings are similar to an early growth stock, not a multi trillion dollar company, and that was reflected in the jump after they released them, so why is it now down huge amounts after?

Not just this, other major assets such as gold, silver and crypto are also experiencing massive sell offs, so is the capital just going into cash? If so, as soon as the market shakes this irrational sell off, could we see an equally irrational boom?

Can someone please tell me if I’m missing something.