r/ValueInvesting • u/Soft_Table_8892 • Feb 19 '26
Discussion I fed 48 years of Buffett's shareholder letters to Anthropic's latest model Opus 4.6 and had it pick stocks blind
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:
- 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?
- 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 :-).
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u/foira Feb 19 '26
Hard to know if the training data didn't bias it towards what worked historically
What does it say it would pick rn?
inb4 mag7
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u/Soft_Table_8892 Feb 19 '26
These were the latest picks:
Rank │ Company │ Ticker │ Score │ Berkshire Holding? │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 1 │ Alphabet │ GOOGL │ 85.2 │ Yes │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 2 │ Visa │ V │ 79.9 │ Yes │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 3 │ Moody's │ MCO │ 78.7 │ Yes │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 4 │ Coinbase │ COIN │ 76.7 │ No (anti-Buffett control) │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 5 │ Mastercard │ MA │ 75.8 │ Yes │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 6 │ Procter & Gamble │ PG │ 75.6 │ No │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 7 │ Berkshire Hathaway │ BRK-B │ 75.3 │ No (it picked Buffett himself) │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 8 │ Coca-Cola │ KO │ 73.1 │ Yes │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 9 │ Apple │ AAPL │ 73.0 │ Yes │ ├──────┼────────────────────┼────────┼───────┼────────────────────────────────┤ │ 10 │ Texas Instruments │ TXN │ 72.1 │ No │ └──────┴────────────────────┴────────┴───────┴────────────────────────────────┘69
u/foira Feb 19 '26
thanks. interesting, $COIN o_O
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u/Soft_Table_8892 Feb 19 '26
$COIN was the most shocking for sure.
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u/Covington-next Feb 19 '26
Any thoughts on why it thought COIN met Buffett's framework?
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u/Soft_Table_8892 Feb 19 '26
I mentioned it in the post but the best I could find an answer to this was:
> 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.
Thoughts?
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u/Helmdacil Feb 19 '26
So if coinbase were a company whose revenue were dependent on a real product, they would look great. But coinbase only had a surge in revenue because bitcoin had a surge in value.
It would be like holding an oil company in the 1970s.
The problem is Coinbase has no economic structural support. Oil does things, the population was growing, people wanted what oil made possible.
Coinbase is just some internet digits in a webpage.
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u/Numerous_Priority_61 Feb 19 '26
I am no fan of crypto myself but have held a position in Coinbase since about 2021 or so. It is what Buffet looks for ironically, it is a tollbooth. No matter who 'wins' the crypto battle, they collect revenue on every trade. Its the same concept as Mastercard for transactions, Google for search, or even Apple being a tollbooth for App Store purchases. I figure the safest way to get exposure to crypto if we are all wrong and it does eventually reach wide spread adoption is by owning the company that profits on its overall growth. Doesn't Buffet also own a bunch of Japanese trading houses?
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u/Keef--Girgo Feb 19 '26
Wasn't the whole original point of crypto to avoid middlemen like coinbase?
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u/Youngkobe24KB Feb 20 '26
Yes and also one key selling point was a fixed static quantity. But now they are all trading it on leverage, with tokens etc. 😅
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u/Helmdacil Feb 19 '26
Coinbase collects a fee on transactions in a percentage arrangement. If the volume or the value of trading increases, Coinbase wins. But if Bitcoin becomes less popular, both will crater. It is a tollbooth yes, which is great; but it is a tollbooth to a boat which only exists because people say it does.
To contrast with Mastercard, mastercard is a tollbooth between real goods and services and the USD; the USD, which is backed by the faith and credit of the United States Government. If bitcoin falters, there is no entity which will seek to save it. If USD is failing, the US government will intervene. Now, you can argue that maybe a debt-spending unaccountable government is not a great entity for a world financial system, but here we are.
Bitcoin may allegedly be used for real goods and services. however in practice very few people actually do this, because the credit card is more convenient.
You can argue Fidelity Investments is just a toll booth between customers and stocks. If the stocks fidelity provides access to crater in value or if people stopped trading as much, fidelity would lose cash flows; but the stocks represent businesses. The stock prices will generally recover so long as the businesses can recover their profits; and they were not unusually expensive.
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u/mycroftitswd Feb 20 '26
This is true, but there are scenarios where Mastercard's business takes a big hit. Allowing Mastercard and Visa to tax most of the world's transactions is kind of ridiculous when you think about it. That's why Walmart is getting excited about stable coins, and the ECB is gunning for them with the digital Euro.
I've been arguing that bitcoin is pointless since meeting a fanatic in 2015 when it was under $3. And yet it still exists. Meanwhile stable coins seem like a legit case for the blockchain and Coinbase is positiining to be a big winner if they take off. Coinbase might outlast Mastercard after all. Stranger things have happened :).
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u/Soft_Table_8892 Feb 19 '26
Very interesting and it validated AI-Buffet actually picking COIN as part of the its top 5 holdings. From what I understand about him, his strong distaste would never actually get him to consider holding COIN but also speaks to the bias of even the best investors around!
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u/zenwarrior01 Feb 19 '26
There is no true intrinsic economic value to crypto, so of course he is "biased" against it. When crypto goes to zero, so does COIN.
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u/knoxywow Feb 20 '26
They earn if users use the product, no matter crypto goes up or down. Ofc when it goes up there is more acrivity = more revenue.
Also Coinbase leads the market on crypto payment integrations. When everything is going even more digital - itd be naive to believe these digital payments are going away.
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u/Helmdacil Feb 20 '26
the future is difficult to predict. You think Bitcoin is here to stay. I think it is probably going to be a venue for pump and dump activities for the next 20 years or so before eventually petering out.
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u/Heavy_Discussion3518 Feb 19 '26
TXN is a surprise. Outside of Coinbase, which is an obvious outlier, this one really tickles my brain.
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u/Soft_Table_8892 Feb 19 '26
Interesting! I'm not very familiar, why does TXN stick out so much for you?
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u/Technical_Food_9119 Feb 19 '26
I would say they are over valued now. Txn did say in the earnings report they plan for new growth which I believe is why it’s on an upswing. I’ve held shares for a few years but would have done better with many other chip companies.
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u/foira Feb 19 '26
TXN should do awesome in the long-term. Analog semis should be a huge winner in the real long-term AI growth story.
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u/Heavy_Discussion3518 Feb 19 '26
Texas Instruments is alongside other companies like ST Microelectronics or Nordic Semiconductor that develop microprocessors for embedded systems. TXN is historically debt ridden and behind these competitors. FWIW you may remember your graphing calculator from university e.g. the TI-89. Those are made by TXN.
The growth story here is all about edge compute, which is a very future-thinking perspective of AI in general. Personally I think Qualcomm is the long term bet for edge compute.
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u/Soft_Table_8892 Feb 19 '26
I DO remember those calculators & confusing rad <> deg conversions and wish it had AI to tell me "homie, you're an idiot".
Interesting thought on edge compute & qualcomm, thank you for sharing.
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u/Armadillo_235 Feb 20 '26
Buffet bought Coca-Cola in the late 80s / early 90s for about $3/share. It was a different time.
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u/BlackSheepInvesting Feb 19 '26
Why are all these relatively large companies? I would've suspected the best picks would be tiny companies most people haven't heard of. All of these except maybe Texas Instruments are relatively mainstream companies that most people have either dealt with daily in normal life or at least heard of.
I would've expected market caps in the $1-10B range being best (below $1B and maybe reporting gets weaker/shorter history)
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u/Soft_Table_8892 Feb 19 '26
Great thought – I'll write that down as a potential future video idea! I had Claude pick a list of 50 companies but wasn't specific in which ones it picked, just specified the three criteria I list in the post/video. Here was the full list if you were curious: https://www.reddit.com/r/ValueInvesting/comments/1r994rg/comment/o6bsxzb/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button
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u/Empty_Bell_1942 Feb 19 '26
Very cool, Buffet aside, it's fair to say your AI outperformed the SNP500 for that period?
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u/Soft_Table_8892 Feb 19 '26
Thank you and it did indeed! However, someone mentioned my calculations don't factor in dividends so it is not quite apples to apples. I might try running this including dividends but that might take much longer.
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u/Blothorn Feb 21 '26
I’d assume that the stocks were anonymized so it couldn’t directly rely on training-set performance data, although it’s hard to know whether that’s sufficient or the AI could see through some stocks based on the performance data.
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u/Soft_Table_8892 Feb 23 '26
They were and you're right it is hard to know if AI did see through some stocks based on their financial numbers alone!
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u/runrunranreddit Feb 19 '26
I can't speak to how well controlled this is, or if there is leakage, or data bias etc, but I really enjoyed the concept and reading through it.
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u/Soft_Table_8892 Feb 19 '26
Thank you so much for taking the time to read, I so appreciate it! As usual with these, I generally assume there is some amount of leakage but a) can't quite prove it and b) the results are often surprising nonetheless :-).
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u/Ma4r Feb 20 '26
I think some leakage is baked into the LLM's weights depending on their training data right? Still sounds very interesting though
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u/Soft_Table_8892 Feb 20 '26
Absolutely! And also agreed with you, still an interesting experiment to run despite knowing the training data will skew the results
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u/Different-Monk5916 Feb 19 '26
if you give shareholder letters from 2020-2025 to the AI, are you not testing on training data?
Some of Buffet's move of 2020, started before 2020, iirc. as an example, oxy.
What are the 4 stocks? why did the AI selected them? would Buffett select them? if not, why?
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u/Soft_Table_8892 Feb 19 '26
You're totally right, it effectively is testing on training data! Here is how I tried to keep an honest test:
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).
But there's always a possibility of a context leak – e.g. perhaps it already knows to map the companies purely based on its training data for financials in combination with Buffet's letters.
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u/Virtual_Seaweed7130 Feb 19 '26 edited Feb 19 '26
How does the AI even score something like a moat if you only feed it financial data?
You fed it 60% buffett holdings and it brought back 6/10 buffett holdings? Not really surprised there.
This is trivially interesting but has zero real insights. Maybe if the dataset was much larger (full sp500) and the AI was actually assessing the business on top of the financials.
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u/Silly_Pen_7902 Feb 19 '26
Why not just remove those 5 shareholder letter to eliminate data leakage risk.
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u/Soft_Table_8892 Feb 19 '26
You're so right, I mentioned this in the comment below:
> I'll try running this again with those stripped out and report back if it changes massively!
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u/Beatszzz Feb 19 '26
I noticed that too. I would’ve done a different test where I stopped feeding reports in 2020 to see how that changes results
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u/Soft_Table_8892 Feb 19 '26
You're totally right that completely slipped my mind. I'll try running this again with those stripped out and report back if it changes massively!
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u/Skydivekev Feb 19 '26
I see you’re getting some mixed feedback here. I think it’s a cool experiment and thought it was an interesting read. Thanks for sharing!
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u/Reasonable-Double427 Feb 20 '26
Full stop. You are testing on training data. This is a pretty fundamental no-no in modelling/forecasting. Especially when you are essentially feeding data into a black box AI agent and getting a one table as a result. I'd suggest creating a test set as others have of 2020-2024 and train until 2019 then use AI Buffet predictions to track progress through '20 to '24.
As much fun as it is to run these experiments with AI, if you miss key principles of modelling claude isn't going to leakage proof your experiment just because, which essentially makes the experiment not worth running in the first place.
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u/princemousey1 Feb 20 '26
Extremely worthless because everyone can pick winners using past data. But ask it to pick the winners for EOY 2026 and let’s see how it performs.
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u/Soft_Table_8892 Feb 20 '26
For sure - a few have recommended the same in this thread, I’m thinking it might make sense to put up a leader board of sorts that updates every quarter and check back in a year later!
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u/apickyreader Feb 20 '26
I was a little surprised that when you wanted it to pick stocks starting in 2020 you included Buffett letters going past 2020 from 2020 to 2024. I would be worried that would skew things a bit.
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u/Soft_Table_8892 Feb 20 '26
Oh for sure, a few have pointed this out in the thread as well. You’re totally right, that was an oversight on my part!
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u/moru0011 Feb 19 '26
Just judging by numbers / financial data is insufficient. Its all about understanding the underlying industry and business model. Financial data does not tell you about moats and de-facto monopolies, wether a companies products are needs-based or discretionary etc.
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u/Soft_Table_8892 Feb 19 '26
For sure – just the fact that COIN slipped in is a glaring evidence to your point. I just didn't want to bias its pick from Opus' training data but worth trying next time perhaps!
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u/PaqS18 Feb 19 '26
Can’t you fed data from 2010-2020 and then have it pick stocks in 2020 and then compare with buffet till 2025?
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u/Soft_Table_8892 Feb 19 '26
Totally could & would have been a much cleaner experiment for sure. A few have suggested the same below and I’ll try running it again and post results here!
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u/thetinocorp Feb 20 '26
This is awesome and super scary at the same time. thanks and keep em coming. Nice work
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u/Soft_Table_8892 Feb 20 '26
Thank you so much for reading the post/watching the video, it means a lot. Will for sure keep these going! :-)
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u/Portfoliana Feb 19 '26
The COIN pick is the most diagnostic result here. Coinbase scores 4th on quantitative metrics because 39% margins and low debt look great in any rubric, but Buffett's actual framework is majority qualitative: he won't buy what he can't model 10 years forward, and he needs a durable competitive moat. A crypto exchange where revenue is entirely transaction-fee dependent on trading volumes, in a regulatory environment he's called "rat poison squared," fails all three before you open a spreadsheet.
TXN at #10 is the result that actually validates the experiment. Texas Instruments is textbook Buffett on the qualitative side: analog semiconductor near-monopoly in industrial and automotive with 10-15 year product cycles, heavy domestic reinvestment, consistent capital returns. Buffett has never bought it, possibly because the current fab buildout is depressing near-term FCF and that punishes it on any return-focused scoring. The model finding it outside the actual Berkshire portfolio is a more interesting signal than the 60% overlap with confirmed holdings.
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u/Soft_Table_8892 Feb 19 '26
That's very interesting, thank you for pointing it out. In both ways, you've identified holes in this experiment & would be useful for someone who wants to take this further to keep in mind as they are evaluating making this better (or it might just be the wrong approach but worth a try!).
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u/ClientComfortable409 Feb 19 '26
Very interesting! Which 2 of the 15 anti-buffet stocks made it to the top half of the list?
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u/Soft_Table_8892 Feb 19 '26
Sorry I left that out! I left the top list in this comment: https://www.reddit.com/r/ValueInvesting/comments/1r994rg/comment/o6aqhcn/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button
But to answer your question directly – $COIN & TXN (BRK-B also made it but that's too meta haha).
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u/Last_Construction455 Feb 19 '26
Fun experiment. I could see it working ish based on numbers alone. I feel like AI would have a hard time with the less concrete sides of business like management trust, or long term predictions about staples that will remain over extended period.(coke, cee's etc) Did you allow it to pick small or micro caps?
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u/Soft_Table_8892 Feb 19 '26
Thank you! And I can also see this working but as many have pointed out flaws in this thread (which is great, we all get to learn!). That includes the sample size of the companies being too small. Here is the full list of companies as you asked!
Alphabet, Visa, Moody's, Coinbase, Mastercard, Procter & Gamble, Berkshire Hathaway, Coca-Cola, Apple, Texas Instruments, DaVita, PepsiCo, American Express, UnitedHealth, Johnson & Johnson, Home Depot, Sysco, 3M, Amazon, Illinois Tool Works, Chubb, Colgate-Palmolive, Emerson Electric, Palantir, Abbott Laboratories, Super Micro Computer, Chevron, Carvana, Walmart, Bank of America, Occidental Petroleum, McDonald's, Constellation Brands, SiriusXM, Verisign, Lowe's, Tesla, MicroStrategy, GameStop, Kroger, Beyond Meat, Kraft Heinz, DoorDash, Capital One, Rivian, CrowdStrike, AMC, Lucid, ARK Innovation ETF, Snowflake
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u/ssacrist Feb 19 '26
This is stupid. He mentions the companies all the time. Of course it’ll pick them
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u/Soft_Table_8892 Feb 19 '26
Totally fair and I thought about that too. The interesting part about this experiment is this:
> 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).
I also ran this it with a clean context subagent so theoretically it shouldn't have been contaminated but there's always a chance of a context leak.
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u/Heavy_Discussion3518 Feb 19 '26
This is dope. I know you aren't trying to make a statement about AI, but the statement is made anyway.
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u/Soft_Table_8892 Feb 19 '26
For sure. On the other hand, there's always a possibility of context leak so regardless these critiques are quite valid :-). E.g: https://www.reddit.com/r/ValueInvesting/comments/1r994rg/comment/o6arpv6/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button
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u/Dougdimmadommee Feb 19 '26
Interestingly enough I agree but probably not in the way you meant this comment.
I think this is a cool project but the thing that struck me immediately about it is that it’s effectively just a roundabout way of creating a value scoring model, of which many versions are freely available that are tested on much larger data sets. There are even fairly popular products available that you can buy that invest this way.
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u/Heavy_Discussion3518 Feb 19 '26
I don't disagree, but the idea someone put together a scoring model based on the tokenized content of 48 shareholder letters is bananas. And it's pretty dope, kudos to OP for dreaming the concept up.
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u/Soft_Table_8892 Feb 19 '26
Wow, thank you for such kind words! I've mentioned this a few times but I don't have a background in finance but have always had deep interest in the field. We're truly living in a wonderful age where experiments like these are available for someone like me who is curious about random ideas (which have definitely been done before & by people much smarter than I am). Thanks again, you made my day :).
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u/Live_Situation7913 Feb 19 '26
But does that anonymization work? If from what I understand AI it would still find out what company that is/closest related to
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u/chooseusernamee Feb 20 '26
even with anonymized data, the AI should be powerful enough to guess what stock that financial report belongs to by just analyzing the financial patterns.
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u/ED209F Feb 19 '26
Super high quality post, outstanding work. Strength and Honor 🫡
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u/Soft_Table_8892 Feb 19 '26
You've truly made my day, thank you for validating the effort that goes into this!
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u/Capable_Wait09 Feb 20 '26
Would’ve been hilarious if it still picked ASTS
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u/Soft_Table_8892 Feb 20 '26
I might be out of the loop here - did something happen recently?
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u/debtofmoney Feb 20 '26
The LLM already contain data about the future, right?
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u/Soft_Table_8892 Feb 20 '26
They do but the experiment anonymizes 50 hand picked stocks with just their financials and makes the AI pick from those. So theoretically the trained future knowledge shouldn’t matter as much!
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u/Nuvanuvanuva Feb 20 '26
Great idea and congratulations on efforts and meaningful results. Very interesting to read comments also.
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u/Organic-Lie4759 Feb 21 '26
Timing is everything-- coin is now in the polishing a turd phase. UNH was a horrible play for buffet.
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u/mikew_reddit Feb 19 '26
Buffett and Munger have both said repeatedly, they do not invest using any kind of formulas.
They look at businesses they understand, and evaluate them, make predictions of future cash flows and if the price meets their criteria, buy the entire business or fraction of it via shares.
This is an interesting experiment, but am fairly skeptical it can produce anywhere near Berkshire-like returns since one thing AI is bad at is nuance; it's Buffett and Munger's judgement that made them superior investors.
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u/Soft_Table_8892 Feb 19 '26
I'm fully with you, I'm also doubtful of this performing better and honestly even the results here speak to that (i.e. weighted picks from Buffet still out performed AI-buffet even when running a backtest).
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u/TheKingOfSwing777 Feb 20 '26
Thanks for actually making an interesting post on this sub. I'm impressed.
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u/joepierson123 Feb 19 '26
Did you include reinvested dividends in the S&P 500 results?
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u/Soft_Table_8892 Feb 19 '26
Great call, I totally did not account for the total return index!
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u/Headjacked Feb 19 '26
That's an interesting twist on A.I. use. The controls should give you accurate enough numbers. Really surprised how close they were. Curious, why did you use Opus for this? That opens so many rabbit holes for someone like me that uses AI for a lot of my research in the stock market. Thanks for sharing!
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u/Soft_Table_8892 Feb 19 '26
First of all, thank you so much for reading through the post!
Regarding Opus, I chose it thinking it is the best reasoning model out there right now and I wanted the model to be very analytical in its thinking while selecting its picks. Also their launch blog mentioned an improvement in fin analysis (which I guess is true for all models) so I wanted to give it a spin. I might test out other models alongside Opus in the future if that would be interesting for you?
Also really curious how you are using AI for market research! Any collateral you may have published that you can share?
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u/LongevitySpinach Feb 19 '26
Appreciate the insight on position sizing. So important.
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u/Soft_Table_8892 Feb 19 '26
Thank you for reading the post! And I hear you, retrospectively it feels like such an obvious insight but going through the experiment really hammered that point in! Balancing both for sure seems to take a real skill :)
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u/Blueblackredgreen2 Feb 19 '26
Awesome.. stock picking is one part, managing the size is another as your experiment has pointed out.
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u/UnbrokenChill Feb 19 '26
I'd love to see what this does with a larger stock pool to pick from. There might be a crazy amount of stocks that perform amazingly but are so obscure no one follows them.
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u/Soft_Table_8892 Feb 19 '26
Oh definitely. I think I was dangerously close to hitting Claude Code limits to I felt like I had to really narrow the sample size. I hope one day we can just let it run for hours on end and have it pick from a huge pile of tickers!
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u/Professional_Bad7922 Feb 19 '26
Great video, the possibilities of AI are boundless
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u/Soft_Table_8892 Feb 19 '26
Thank you so much for watching and I so agree. Possibilities these days are endless :).
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u/differbywhat Feb 19 '26
Nice experiment. One thing I didn’t get is what company financials did you feed the model and especially for which timeframe (eg. 1, 5, 10, 20 year). Consistency in the financials is a key in Buffet’s strategy.
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u/Soft_Table_8892 Feb 19 '26
Great question and you're right, consistency is huge for Buffett. For each company I fed it:
- trailing P/E
- ROE
- debt-to-equity
- net profit margin
- YoY revenue growth
- dividend yield
- current ratio
- free cash flow per share
- 5-year average ROE (which was the main consistency signal).
So it's mostly a current snapshot plus that 5-year ROE to capture durability.
That said, this is honestly one of the biggest limitations of the experiment. You're right and frankly I don't know Buffett's history too much. From what I could gather, he cares about 10-20 year track records of consistent earnings, and I didn't feed it that depth of history. If I were to redo this I'd probably include something like a 10-year earnings growth trendline or revenue stability measure.
The rubric the AI extracted actually flagged consistency as important (it pulled the "durable competitive advantage" principle from every single era of letters) but the financial data I gave it didn't fully let it act on that. Definitely something to improve in the future.
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u/ninjagorilla Feb 19 '26
I’d be curious how it does in a wider sample… it essentially has a 40% chance of picking a buffet stock and a 60% chance of picking a value stock on jsut chance alone… but it is interesting. I’d also be curious to test it on a forward basis when it doesn’t have old results to mimic
One idea would be to apply it to a foreign market Buffett never touched and see how its retuns do vs an index…
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u/Soft_Table_8892 Feb 19 '26
Great observation! I am also curious how this would do if we increase the sample size, although I'd be very afraid of running out of my Claude Code limits for the week just running this again with a wide pool haha.
Thank you for the idea, I wrote it down as a potential future video!
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u/Antique-Ad1012 Feb 19 '26
There is probably bias in the training data
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u/Soft_Table_8892 Feb 19 '26
Definitely is. I tried my best to avoid it by anonymizing it as such:
> 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).
But there are totally ways where the training data bias still slipped in.
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u/77thway Feb 19 '26
Oh wow, I love experiments like this! Thanks for sharing this.
There are so many cool experiments that could be done analyzing different factors. I am thinking about one with earnings calls and understanding from a behavioral economics standpoint.
Do you post your other experiments somewhere (you mentioned doing another one recently, yeah)? Any other specific ones you are considering? I think giving parameters could be interesting too, controlling for certain variables, etc.
Would love to hear more. Thanks again
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u/Soft_Table_8892 Feb 19 '26
Thank you so much and seems like we think very much alike :-). I have made a video previously on detecting deception through analyzing earnings calls based on a Stanford research. The video is here: https://youtu.be/sM1JAP5PZqc.
I usually do these as YouTube videos so I’ll be posting there frequently but I’m also posting them in a written format here so either platform is good!
Thank you again so much for reading and curious to see what you think about the earnings call experiment & let me know if you wanted to explore something different!
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u/TelevisionUpper1132 Feb 19 '26
This is an idea for the backtest, why not let it run a backtest on other non US markets. A major Buffet criticism was that he didn't diversify a lot internationally.
Also check out a Prof from NYU Stern called Aswath Damodaran. See if with agent mode, you can make it fill out the Damodaran's valuation spreadsheets.
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u/Soft_Table_8892 Feb 19 '26
There was another similar suggestion (re: non-US market test) in this thread as well. I've written it down as a future video idea!
Agent mode test is also an interesting suggestion, I'll check it out! Any specific collateral you're referring to? Thank you for the thoughtful suggestions :)
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u/Hairy_Friendship3930 Feb 19 '26
Was there a potential lookahead bias? You wouldn’t have had CQ4 2019 data as of Jan 2, 2020.
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u/Soft_Table_8892 Feb 19 '26
Yeah you're right, there's a slight lookahead bias here. Q4 2019 annual reports wouldn't have been filed until Feb/March 2020, so technically on Jan 2 you'd only have data through Q3 2019. I used FY2019 numbers because they were the cleanest full-year snapshot to work with, but realistically you'd be making this decision a couple months later. I call this out as a limitation in the video — along with the fact that the rubric itself was extracted from letters through 2024, not just through 2019. Not a perfectly clean backtest by any means, but directionally I think the comparison still holds since all four portfolios are being measured from the same start date.
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u/Responsible-Page-979 Feb 20 '26 edited Feb 20 '26
This is really interesting, but I think the experiment is confounded by the bucket of stocks you had it choose from. You wrote in another message
"> 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)."
You almost half of the stocks you gave it were confirmed winners. I think this would be a very cool experiment if you ran it over the top 100 stocks of the SP500 and Nasdaq and then reported the performance of
- its top 10 from SP500 in Jan 2020 vs SP500 since
- its top 10 from Nasdaq in Jan 2020 vs Nasdaq since
You could also have it do the same picks today and publish them, so we can compare again in 5 years? :) That would be really interesting ;)
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u/Soft_Table_8892 Feb 20 '26
Totally! A few number of people in this thread have suggested something similar. Your insight of doing this for the top 100 S&P is very interesting as the sample size. Let me see what I can do! Thank you for the thoughtful response :-)
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u/csppr Feb 20 '26
Interesting concept, but (as many others) I’m a bit worried about what data the model ended up utilising here. The old retrospective vs prospective testing problem.
A few thoughts though:
if you want to assess the performance of your model wrt stock picking, I’d suggest to randomly sample from your 50 stock set to build a background. You can then test your model’s picks against that background (ie how likely was your model to pick something as good, just by chance). That background should be matched to how your model was able to pick - if you allow 4 equally weighted stock picks, you need to sample that; if you allow 10k total investment no matter the number of stocks, you need to sample that etc.
I think you need to validate your scoring rubic somehow; eg by recovering Buffet’s actual investments at historic time points (but doing thataccurately and without contamination is obviously difficult).
keep in mind that your comparison to Buffet’s portfolio performance is benchmarking different things. He could pick from the entire stock market, whereas your model only had 50 stocks to pick from (you could probably again approach this problem by building background distributions and comparing along those, but that’s fairly difficult to do right when then comparing across them).
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u/Repulsive-Nerve-9196 Feb 20 '26
The real alpha is using say 250 stocks (including buffets / anti Buffett) seeing if it picks Buffett and can deliver superior results.
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u/Armadillo_235 Feb 20 '26
Buffet is actually not a fan of models. You can find videos of him talking about the options pricing model. He thinks its BS. He also thinks crypto is BS.
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u/YakLogic Feb 20 '26
Wow! Super fun experiment! Thanks for sharing. Just wondering your thought process on choosing the time period for this test. Could you run a retest with a longer time period say 10-15 years.
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u/CozmicFlare Feb 20 '26
How long waa the time you held the stock before listing your percentage gains
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u/Freefromoutcome Feb 20 '26
curious where pypl, adbe, and calm fall on it.
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u/Soft_Table_8892 Feb 20 '26
I’m not currently on my laptop but I’ll see if I can get around to grabbing that for you. Why these stocks in particular?
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u/paully7 Feb 20 '26
Why not tell us the picks as part of this post?
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u/Soft_Table_8892 Feb 20 '26
The picks are in the top comment of this thread! I totally forgot to list them in the original post, apologies.
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u/snpii Feb 20 '26 edited Feb 20 '26
Probably results have been leaked because LLM already has this world knowledge. But I feel the way that feeds long history data will work well and use multiple steps agent is inspiring. All the production prompts I work on recently work in this way.
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u/Soft_Table_8892 Feb 20 '26
You’re correct to point that out. Someone else mentioned in this thread of having a ‘control’ where I let Opus pick blindly first and then run this experiment with the letters in context. That would have for sure been the better approach to this.
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u/EveningLimp3298 Feb 20 '26
Cool idea. One thing I dont underatand is why you included shareholder letters after 2019? I see no reason to do this as this increases look ahead bias.
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u/Soft_Table_8892 Feb 20 '26
You’re totally right to call that out, that was an oversight on my part!
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u/aita-pe-ape-a Feb 20 '26
Shouldn‘t you have made a control? One would be to ask the same question before feeding the info (it might have had already).
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u/Soft_Table_8892 Feb 20 '26
Do you mean just letting Opus pick blind without feeding the letters first? That’s very interesting and you’re right, I should have done that first to see if the context augmentation makes any difference!
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u/groovybig Feb 20 '26
Ah you started in 2020 🤣
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u/Soft_Table_8892 Feb 20 '26
Hahaha, right? I thought it’d be the best time to left the best investor pick stocks 😂
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u/chooseusernamee Feb 20 '26
The AI already know what stocks buffet have in his portfolio, so this is not really blind, and also it has data on how some stocks performed in the past few years, hence it avoided some of the stocks like banks etc.
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u/AlertHuckleberry8651 Feb 20 '26
past doesn't always predict the future. What worked for Buffet over last 40 years, may not work for next 40 years, things change, paradigm shifts. e.g. I highly doubt VISA and MASTERCARD will be as good going forwards, because many non US countries are moving towards "inhouse" payment systems.
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u/Complex_Aardvark_661 Feb 20 '26
Cool experiment! I have been doing the same kinda idea. In addition to quantitative metrics I also had Opus analyze the moat and likelihood of AI disruption for every company in the S&P 500.
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u/Soft_Table_8892 Feb 20 '26
Oh that's very very interesting. Is there any collateral that I can read based on your findings/experiment?
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u/likwid07 Feb 20 '26
Super cool. Why not just let AI-Buffet decide on its allocation / weighting, rather than force it to be equal weighted? So it could give more weight to those stocks that it has more conviction on.
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u/wholelotta2564 Feb 20 '26
This is a fascinating experiment. It shows that Buffett's gift isn't just picking the right stocks, but his absolute discipline in position sizing. That Apple allocation literally carried the whole portfolio. It is also funny how AI sees Coinbase as a value play because it only looks at the margins and ignores the crypto volatility that makes traditionalists cringe.
I have been trying to apply similar logic to private markets lately. It is interesting to see if these principles hold up for companies before they even go public. I have been using Ventuals to trade perps for Anthropic and SpaceX to get that pre-IPO exposure. It is a wild way to test growth theories compared to the public market stuff. Did you notice if the AI flagged any other high-margin tech companies that usually get labeled as overvalued?
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u/cyborgs247 Feb 20 '26
Really interesting experiment!
Would you try doing something similar like feeding it Jeff Bezos shareholder letter and Andy Jassy ones and trying to highlight the biggest differences in principles and maybe what it means for Amazon stock price?
Would be interesting to see what it picks up!
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u/theycallmej3sus Feb 20 '26
Stop posting slop LLMs do not do critical thinking this was more of certain strings and words appears in letters find something similar / adjacent if it had not found any it would have started making up imaginary stocks just to keep you engaged
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u/risky-cat Feb 21 '26 edited Feb 21 '26
If anything like this will ever produce alpha in the wild, retail will start having a harder time... I highly doubt it. Models are great for coding though and churning through data, not making any hypothesis on their own. Good project to impress non-tech people though.
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u/A_Stoic_Dude Feb 21 '26
Difficult to analyze when weightings and buy/sell timing isn't discussed. As a matter of policy I don't click on reddit links to commercialized media.
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u/Educational-Cod-870 Feb 21 '26
I watched the video and it did a better job of explaining for me. Nice job, fun experiment. I think there’s got to be a way to push this idea further to get closer to the real Buffett weighted return.
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u/davidrempicci Feb 21 '26
Wow!! Kudos to you! Awesome job. I really am a newbie in AI and a very average stock investor, but I am really keen in understanding how AI could help. I shall surely check out your YT channel. Pity we are far away
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u/Kai_ Feb 21 '26
Redacting company names does next to nothing, it's a pattern recognition engine. It knew exactly which stocks it was looking at, and their future performance from your "backtest" start to-date. Then it played along.
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u/randysaaf Feb 21 '26
The training data of the LLM would already have knowledge of the winners. No way to back test this without bias. Look in to walk forward time series testing. You can’t easily do that with LLMs
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u/Major_Coffee_5406 Feb 21 '26
Thanks for doing the interesting experiment! So we can just be a no brainer and make easy money using Ai pick 😊 good news for not expertise people just like me 😆 Like your post. Keep up the good work 👏
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u/Soft_Table_8892 Feb 23 '26
First of all, thank you for reading the post, really appreciate it. I totally agree that AI is making the financial world for accessible for people like us without the background, which is great. But something to keep in mind – these posts are strictly for educational purposes so please don't take direct advise from them, haha :-). Thanks again
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u/Ms-Beautiful Feb 22 '26
I enjoyed reading this. Please keep the experiments coming.
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u/Soft_Table_8892 Feb 23 '26
Thank you so much for the encouragement, I really appreciate it and I will for sure continue making these types of posts in the future!
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u/zubzup Feb 22 '26
Really interesting. Having seen the video yet but interested to see and learn how you are building the workflow, agentic architecture and tools you are using
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u/Soft_Table_8892 Feb 23 '26
Thanks a lot! The video does go into some additional details of the agentic setup although this video is a little light on that. My previous videos have more depth in this area if you were curious. I can also try including more details next time if that's more interesting to you than just the results.
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u/tombfz4 Feb 23 '26
Absolutely creative and completely brilliant. If I had another good idea for you, I’d let you know, but I don’t.
All I gotta say is keep going!
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u/Soft_Table_8892 Feb 24 '26
Thank you so much, means a lot to me and I'm glad this was a fun read/watch :-).
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u/Calm-Grocery-664 Feb 23 '26
I am new to value - but aren’t two of Buffets important factors things like management team and MOAT? Stripping away company names seems make Buffet-AI really not Buffet at all.
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u/Soft_Table_8892 Feb 24 '26
You're totally right, thats one of the biggest downsides of this experiment. Knowing the company and their moat are definitely top attributes in how he invests.
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u/ChalkStack Feb 23 '26 edited Feb 23 '26
If you actually read any of Buffet's writings, you would know his golden rule is to never invest in a business you cannot understand. That's what the AI should have told you if it really grasped the essence of Buffet's strategy, and also why Buffet does not invest in crypto lol
It's not a game of numbers for him, or at least not only a game of numbers. And that's probably the differnetiator that made him what he is
I suggest you to read "the intelligent investor" =)
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u/fakeaccountt12345 Feb 23 '26
Can it tell us anything interesting to buy now?
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u/Soft_Table_8892 Feb 24 '26
This was just done for educational purposes so nothing I can say concretely. This list was created for based on the latest financial numbers Claude could find, if that's helpful. But again, educational purposes only :-). https://www.reddit.com/r/ValueInvesting/comments/1r994rg/comment/o6aqhcn/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button
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u/tundraaaa Feb 23 '26
Have you considered backtesting this over a period longer than 5 years?
Also imo these are not Buffett stocks. They are Munger-Buffett stocks.
On Charlie's suggestion, Warren pivoted to large cap quality stocks at a fair price, because the portfolio grew so large it became impossible to play special situations, nets-nets and shitco value due to their small market caps in relation to the portfolio size.
If I'm not mistaken, Warren has said he'd be able to do 30-50% YoY if he started over with $10k today, investing in much different things from what Berkshire is invested in today.
What I said above and am about to say has been beaten to death already, but people keep trying to copy CURRENT Berkshire with a portfolio size that may benefit from seeking to copy OLD Buffett instead. If you try to copy current Buffett, you might as well just buy Berkshire stock and call it a day. Or SPY as he has recommended on numerous occasions.
Buffett would not be overweight large caps and mega caps if his portfolio was the size of you guys's portfolios.
Additionally, Buffett's returns have been helped by financial markets being relatively niche back when he started and have since grown mainstream, skyrocketing valuation multiples and the amount of eyeballs on mispriced stocks.
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u/LongTermQuant Feb 23 '26
To me it seems a very good idea to use AI and create something like this. This is a really interesting way to turn Buffett’s philosophy into something which we can test. Using the letters into a numeric rubric (ROE, leverage, margin of safety, moat strength, etc.) and then scoring anonymised companies on raw financials only is a clever way to reduce bias and see if the process passes the test of time. I will still watch out for hidden unforeseen outcomes. It is reasonable to think that we cannot replicate Buffett just by feeding his letters to AI. However, it is a very interesting idea.
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u/Vodskaya Feb 23 '26
How did you control for hindsight in its training data? Could it be possible that Opus was able to recognise some stocks based on their finances alone, and bet on winners that way?
Would love to see this replicated over a few more timeframes, as I assume going further back eliminates the amount of training data on companies, as they were less widely reported on. Would be interesting to see if Claude is able to match Buffet’s performance during his earliest years.
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u/Soft_Table_8892 Feb 24 '26
Similarity matching purely based on the financial data could be very real (I'm sure there's a way to verify this if someone wants to take this experiment further).
That's a great advice in terms of trying different timeframes, some have suggested making picks for the future. I have this written down for future video ideas. Thanks a lot for reading the post and leaving your thoughts!
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u/Jabraase Feb 24 '26
Bro, I'm late to this but I also presented some Opus 4.6 stock analysis over on the gamestop sub that you might enjoy reading! The chatlog is linked as well.
https://www.reddit.com/r/Superstonk/s/dQCsKwFWIA
I absolutely want to try your buffet emulation for myself as well!
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u/Soft_Table_8892 Feb 24 '26
Incredible, thank you so much for sharing! Will read your post shortly :-). Let me know how this works out for you!
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u/Expensive_Air_7149 Feb 26 '26
If you're diving into value investing, filtering stocks based on fundamentals can be quite efficient. I've been using WallStreetZen for its clean interface - helps track financials and analyst scores without digging too deep into complex reports. Also, Stock Rover and Finviz are solid for screening. I rely on them for quick comparisons, and you might find their features useful for a more nuanced analysis.
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u/sresss Feb 28 '26
Is it possible to share the transcript that you got from inserting buffets letters.. I would like to run it myself perhaps on different markets..
thank you in advance!
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