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Yeah I mean if you generally believe the tech sector is going to do well because it has been doing well you will beat the overall market. The problem is that yo

Yeah I mean if you generally believe the tech sector is going to do well because it has been doing well you will beat the overall market. The problem is that you don’t know if and when there might be a correction. But since there is this one segment of the overall market that has this steady upwards trend and it hasn’t had a large crash, then yeah any pattern seeking system will identify “hey this line keeps going up!” Would it have the nuance to know when a crash is coming if none of the data you test it on has a crash? It would almost be more interesting to specifically train the model on half the available market data, then test it on another half. But here it’s like they added a big free loot box to the game and then said “oh wow the player found really good gear that is better than the rest!” Edit: from what I causally remember a hedge fund can beat the market for 2-4 years but at 10 years and up their chances of beating the market go to very close to zero. Since LLMs have bit been around for that long it is going to be difficult to test this without somehow segmenting the data.

tshaddox 10mo ago
> It would almost be more interesting to specifically train the model on half the available market data, then test it on another half. Yes, ideally you’d have a model trained only on data up to some date, say January 1, 2010, and then start running the agents in a simulation where you give them each day’s new data (news, stock prices, etc.) one day at a time.
- IgorPartola 10mo ago
  I mean ultimately this is an exercise in frustration because if you do that you will have trained your model on market patterns that might not be in place anymore. For example after the 2008 recession regulations changed. So do market dynamics actually work the same in 2025 as in 2005? I honestly don’t know but intuitively I would say that it is possible that they do not. I think a potentially better way would be to segment the market up to today but take half or 10% of all the stocks and make only those available to the LLM. Then run the test on the rest. This accounts for rules and external forces changing how markets operate over time. And you can do this over and over picking a different 10% market slice for training data each time. But then your problem is that if you exclude let’s say Intel from your training data and AMD from your testing data then there ups and downs don’t really make sense since they are direct competitors. If you separate by market segment then does training the model on software tech companies might not actually tell you accurately how it would do for commodities or currency training. Or maybe I am wrong and trading is trading no matter what you are trading.
  - chris_st 10mo ago
    > you will have trained your model on market patterns that might not be in place anymore My working definition of technical analysis [0] [0]: https://en.wikipedia.org/wiki/Technical_analysis https://en.wikipedia.org/wiki/Technical_analysis
    - IgorPartola 10mo ago
      It is always fun (in a broad sense of that word) when I make a comment on an industry I know nothing about and somehow stumble onto a thing that not only has a name but also research. I am sure there is a German word for that feel of discovering something that countless others have already discovered.
      - chris_st 10mo ago
        XKCD calls it the "Lucky 10,000" [0] [0]: https://xkcd.com/1053/ https://xkcd.com/1053/
        mewpmewp2 10mo ago
        That is referring to something completely else. This is referring to some common fact that the person didn't figure out by themself. OP is referring to something they came up with themselves in a field they have no experience with, realizing it is actually a thing in a way feeling validated and clever.
        gcr 10mo ago
        XKCD calls it "Engineering Syllogism" [0] [0]: https://xkcd.com/1570/ https://xkcd.com/1570/
      - taneq 10mo ago
        Any time I invent a cool thing, I go and try and find it online. Usually it's already an established product, which totally validates my feeling that the thing I invented is cool and would be a good product. :D Occasionally it's (as far as I can tell) a legitimately new 'wow that's obvious' style thing and I consider prototyping it. :)
- hxtk 10mo ago
  I suspect trading firms have already done this to the maximum extent that it's profitable to do so. I think if you were to integrate LLMs into a trading algorithm, you would need to incorporate more than just signals from the market itself. For example, I hazard a guess you could outperform a model that operates purely on market data with a model that also includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs.
  - giantg2 10mo ago
    "includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs." Not really. Sentiment analysis in social networks has been around for years. It's probably cheaper to by that analysis and feed it to LLMs than to have LLMs do it.
  - solotronics 10mo ago
    The part people are missing here is that if the trading firms are all doing something, that in itself influences the market. If they are all giving the LLMs money to invest and the AIs generally buy the same group of stocks, those stocks will go up. As more people attempt the strategy it infuses fresh capital and more importantly signaling to the trading firms there are inflows to these stocks. I think its probably a reflexive loop at this point.
    - brendoelfrendo 10mo ago
      They could have the AI perform paper trading: give it a simulated account but real data. This would make sense to me if it was just a research project. That said, I imagine the more high-tech trading firms started running this research a long time ago and wouldn't be surprised if there were already LLM-based trading bots that could be influencing the market.
calmbonsai 10mo ago
For a nice historic perspective on hedge funds and the industry as a whole, read Mallaby's "More Money Than God".
ainiriand 10mo ago
As an old friend investor I know always says: 'It is really easy to make money in the market when everyone is doing it, just try to not lose it when they lose it'.
- diamond559 10mo ago
  Everyone's a genius in a bull market is the phrase.
arisAlexis 10mo ago
You believe in the tech sector because technology always goes well and it's what humans strive to achieve, not because it has done well recently. It has always.
- knollimar 10mo ago
  When does the tech sector become the computer sector? Agriculture would have been considered tech 200 years ago.
  - arisAlexis 10mo ago
    full throttle until AGI is achieved, then we will see
    - d-lisp 10mo ago
      Maybe one day we will discover that a method exists for computing/displaying/exchanging arbitrary things through none other means than our own flesh and brains.
- DennisP 10mo ago
  Long term, yes. Short to medium term, we can get things like the 2001 crash.
Eddy_Viscosity2 10mo ago
> a hedge fund can beat the market for 2-4 years but at 10 years and up their chances of beating the market go to very close In that case the winning strategy would be to switch hedge funds every 3 years.
- perlgeek 10mo ago
  The problem is that you don't know in advance which will be doing well when.
- skeeter2020 10mo ago
  Except you don't know which fund is going to "go on a hot streak" or when the magic will end. The original statement only holds when looking at historical data; it's not predictive.
- ludwik 10mo ago
  > In that case the winning strategy would be to switch hedge funds every 3 years. When you flip a coin, you can easily get all heads for the first 2-4 flips, but over time it will average out to about 50% heads. It doesn’t follow from this that the winning strategy is to change the coin every 3 flips.
stonemetal12 10mo ago
Would that work for LLMs though? They hypothetically trained on news papers from the second half of the data so they have knowledge of "future" events.

tshaddox 10mo ago

> It would almost be more interesting to specifically train the model on half the available market data, then test it on another half. Yes, ideally you’d have a model trained only on data up to some date, say January 1, 2010, and then start running the agents in a simulation where you give them each day’s new data (news, stock prices, etc.) one day at a time.

IgorPartola 10mo ago
I mean ultimately this is an exercise in frustration because if you do that you will have trained your model on market patterns that might not be in place anymore. For example after the 2008 recession regulations changed. So do market dynamics actually work the same in 2025 as in 2005? I honestly don’t know but intuitively I would say that it is possible that they do not. I think a potentially better way would be to segment the market up to today but take half or 10% of all the stocks and make only those available to the LLM. Then run the test on the rest. This accounts for rules and external forces changing how markets operate over time. And you can do this over and over picking a different 10% market slice for training data each time. But then your problem is that if you exclude let’s say Intel from your training data and AMD from your testing data then there ups and downs don’t really make sense since they are direct competitors. If you separate by market segment then does training the model on software tech companies might not actually tell you accurately how it would do for commodities or currency training. Or maybe I am wrong and trading is trading no matter what you are trading.
- chris_st 10mo ago
  > you will have trained your model on market patterns that might not be in place anymore My working definition of technical analysis [0] [0]: https://en.wikipedia.org/wiki/Technical_analysis https://en.wikipedia.org/wiki/Technical_analysis
  - IgorPartola 10mo ago
    It is always fun (in a broad sense of that word) when I make a comment on an industry I know nothing about and somehow stumble onto a thing that not only has a name but also research. I am sure there is a German word for that feel of discovering something that countless others have already discovered.
    - chris_st 10mo ago
      XKCD calls it the "Lucky 10,000" [0] [0]: https://xkcd.com/1053/ https://xkcd.com/1053/
      - mewpmewp2 10mo ago
        That is referring to something completely else. This is referring to some common fact that the person didn't figure out by themself. OP is referring to something they came up with themselves in a field they have no experience with, realizing it is actually a thing in a way feeling validated and clever.
        gcr 10mo ago
        XKCD calls it "Engineering Syllogism" [0] [0]: https://xkcd.com/1570/ https://xkcd.com/1570/
    - taneq 10mo ago
      Any time I invent a cool thing, I go and try and find it online. Usually it's already an established product, which totally validates my feeling that the thing I invented is cool and would be a good product. :D Occasionally it's (as far as I can tell) a legitimately new 'wow that's obvious' style thing and I consider prototyping it. :)
hxtk 10mo ago
I suspect trading firms have already done this to the maximum extent that it's profitable to do so. I think if you were to integrate LLMs into a trading algorithm, you would need to incorporate more than just signals from the market itself. For example, I hazard a guess you could outperform a model that operates purely on market data with a model that also includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs.
- giantg2 10mo ago
  "includes a vector embedding of a selection of key social and news media accounts or other information sources that have historically been difficult to encode until LLMs." Not really. Sentiment analysis in social networks has been around for years. It's probably cheaper to by that analysis and feed it to LLMs than to have LLMs do it.
- solotronics 10mo ago
  The part people are missing here is that if the trading firms are all doing something, that in itself influences the market. If they are all giving the LLMs money to invest and the AIs generally buy the same group of stocks, those stocks will go up. As more people attempt the strategy it infuses fresh capital and more importantly signaling to the trading firms there are inflows to these stocks. I think its probably a reflexive loop at this point.
  - brendoelfrendo 10mo ago
    They could have the AI perform paper trading: give it a simulated account but real data. This would make sense to me if it was just a research project. That said, I imagine the more high-tech trading firms started running this research a long time ago and wouldn't be surprised if there were already LLM-based trading bots that could be influencing the market.

calmbonsai 10mo ago

For a nice historic perspective on hedge funds and the industry as a whole, read Mallaby's "More Money Than God".

ainiriand 10mo ago

As an old friend investor I know always says: 'It is really easy to make money in the market when everyone is doing it, just try to not lose it when they lose it'.

diamond559 10mo ago
Everyone's a genius in a bull market is the phrase.

arisAlexis 10mo ago

You believe in the tech sector because technology always goes well and it's what humans strive to achieve, not because it has done well recently. It has always.

knollimar 10mo ago
When does the tech sector become the computer sector? Agriculture would have been considered tech 200 years ago.
- arisAlexis 10mo ago
  full throttle until AGI is achieved, then we will see
  - d-lisp 10mo ago
    Maybe one day we will discover that a method exists for computing/displaying/exchanging arbitrary things through none other means than our own flesh and brains.
DennisP 10mo ago
Long term, yes. Short to medium term, we can get things like the 2001 crash.

Eddy_Viscosity2 10mo ago

> a hedge fund can beat the market for 2-4 years but at 10 years and up their chances of beating the market go to very close In that case the winning strategy would be to switch hedge funds every 3 years.

perlgeek 10mo ago
The problem is that you don't know in advance which will be doing well when.
skeeter2020 10mo ago
Except you don't know which fund is going to "go on a hot streak" or when the magic will end. The original statement only holds when looking at historical data; it's not predictive.
ludwik 10mo ago
> In that case the winning strategy would be to switch hedge funds every 3 years. When you flip a coin, you can easily get all heads for the first 2-4 flips, but over time it will average out to about 50% heads. It doesn’t follow from this that the winning strategy is to change the coin every 3 flips.

stonemetal12 10mo ago

Would that work for LLMs though? They hypothetically trained on news papers from the second half of the data so they have knowledge of "future" events.