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Financial Statement Analysis with Large Language Models

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Re: Financial Statement Analysis with Large Language Models

#51

Post by HanayamaTriplet »

foota wrote: post #37
_se wrote: post #17

Earlier quoted context omitted.

That is not a benefit. If you use a tool like this to try to compete with sophisticated actors (e.g. all major firms in the capital markets space) you will lose every time.

We come up with all sorts of things that are initially a step backwards, but that lead to eventual improvement. The first cars were slower than horses. That's not to suggest that Renaissance is going to start using Chat GPT tomorrow, but maybe in a few years they'll be using fine tuned versions of LLMs in addition to whatever they're doing today. Even if it's not going to compete with the state of the art models for…

It seems to me that LLMs the metaphorical horse and specialized algorithms are the metaphorical car in this situation. A horse is a an extremely complex biological system that we barely understand and which has evolved many functions over countless iterations, one of which happening to be the ability to run quickly. We can selectively breed horses to try to get them to run faster, but we lack the capability to directly engineer a horse for optimal speed. On the other hand, cars have been engineered from the ground-up for the specific purpose of moving quickly. We can study and understand all of the systems in a car perfectly, so it's easy to develop new technology specialized for making cars go faster.

Re: Financial Statement Analysis with Large Language Models

#52

Post by z7 »

ecjhdnc2025 wrote: post #48
foota wrote: post #37

Earlier quoted context omitted.

We come up with all sorts of things that are initially a step backwards, but that lead to eventual improvement. The first cars were slower than horses. That's not to suggest that Renaissance is going to start using Chat GPT tomorrow, but maybe in a few years they'll be using fine tuned versions of LLMs in addition to whatever they're doing today. Even if it's not going to compete with the state of the art models for…

Far too much in the way of "maybe in a few years" LLM prediction relies on the unspoken assumption that there will not be any gains in the state of the art in the existing, non-LLM tools. "In a few years" you'd have the benefit of the current, bespoke tools, plus all the work you've put into improving them in the meantime. And the LLM would still be behind, unless you believe that at some point in the future, a radic…

>Why is it that we wouldn't trust a generalist over a specialist in any walk of life, but in AI we expect one day to be able to?

The specialist is a result of his general intelligence though.

Re: Financial Statement Analysis with Large Language Models

#53

Post by nebula8804 »

chollida1 wrote: post #19

So the history of this type of research as I know it was that we - started to diff the executives statements from one quarter to another. Like engineering projects alot of this is pretty standard so the starting point is the last doc. Diffing allowed us to see what the executives added and thought was important and also showed what they removed. This worked well and for some things still does, this is what a warrant…

I have no window into this world but I am curious if you know anything about the techniques that investors used to short or just analyze Tesla stock during the production hell of 2017-2020? It was an interesting window in ways that firms use to measure as much of the company as they can from the outside. In fact was there any other stock that was as heaving watched during that time?

Looking back at that era it seemed investors were too focused on the numbers and fundamentals, even setting up live feeds of the factories to count the number of cars coming out and thats the same feeling I get from your post. It seems like dumb analysis ie. analysis without much context.

We now know from the recent Isaacson biography what was happening on the other side. The shorts failed to measure the clever unorthodox ways that Musk and co would take to get the delivery numbers up. For example: The famous Tent. Musk used a loophole in CA laws to set up a giant tent in the parking lot and allowed him to boost the production by eliminating entire bottlenecks from the factory design. There is also just the religious like fervor with which the employees wanted to beat the shorts. I dont think this can be measured no? It helped to get them past the finish line.

Re: Financial Statement Analysis with Large Language Models

#55

Post by infecto »

nicce wrote: post #47
infecto wrote: post #27

Earlier quoted context omitted.

This has already been a thing since the late 80s.

It hasn't been accurate enough to be meaningful, nor enough data.

There has been plenty of work behind the scenes over the decades that has been meaningful.

Re: Financial Statement Analysis with Large Language Models

#56

Post by SavageBeast »

BobaFloutist wrote: post #50
andsoitis wrote: post #44

Earlier quoted context omitted.

> Anyone who has figured out something relatively profitable isn't telling anyone how they did it. Corollary: someone who is selling you tools or strategies on how to make tons and tons of money, is probably not making tons and tons of money employing said tools and strategies, but instead making their money by having you buy their advice.

I think I could probably make more money selling a tool or strategy that consistently, reliably makes ~2% more than government bonds than I could make off it myself, with my current capital.

Seems like the money here would be building a shiny, public facing version of the tool behind a robust paywall and build a relationship with a few Broker Dealer firms who can make this product available to the Financial Advisors in their network.

If you were running this yourself with $1M input capital, that'd be $20k/year per 1M of input - so $20K is a nice number to try and beat selling a product that promulgates a strategy.

But you're going to run into the question from people using the product: "Yeah - but HOW DOES IT WORK??!!!" and once you tell them does your ability to get paid disappear? Do they simply re-package your strategy as their own and cease to pay you (and worse start charging for your work)? Is your strategy so complicated that the value of the tool itself doing the heavy lifting makes it sticky?

Getting people to put their money into some Black Box kind of strategy would probably be challenging - but Ive never tried it - it may be easier than giving away free beer for all I know. Sounds like a fun MVP effort really. Give it a try - who knows what might happen.

Re: Financial Statement Analysis with Large Language Models

#58

Post by bongodongobob »

BobaFloutist wrote: post #50
andsoitis wrote: post #44

Earlier quoted context omitted.

> Anyone who has figured out something relatively profitable isn't telling anyone how they did it. Corollary: someone who is selling you tools or strategies on how to make tons and tons of money, is probably not making tons and tons of money employing said tools and strategies, but instead making their money by having you buy their advice.

I think I could probably make more money selling a tool or strategy that consistently, reliably makes ~2% more than government bonds than I could make off it myself, with my current capital.

Lol try it and get back to us.

Re: Financial Statement Analysis with Large Language Models

#59

Post by jimbokun »

BobaFloutist wrote: post #50
andsoitis wrote: post #44

Earlier quoted context omitted.

> Anyone who has figured out something relatively profitable isn't telling anyone how they did it. Corollary: someone who is selling you tools or strategies on how to make tons and tons of money, is probably not making tons and tons of money employing said tools and strategies, but instead making their money by having you buy their advice.

I think I could probably make more money selling a tool or strategy that consistently, reliably makes ~2% more than government bonds than I could make off it myself, with my current capital.

Or just sell it to exactly one buyer with a lot of capital to invest.

Re: Financial Statement Analysis with Large Language Models

#60

Post by posting_mess »

bethekind wrote: post #24
flourpower471 wrote: post #15

Earlier quoted context omitted.

Not to mention, as somebody who works in quant trading doing ml all day on this kind of data. That ann benchmark is nowhere near state of the art. People didn't stop working on this in 1989 - they realised they can make lots of money doing it and do it privately.

Do you use llama 3 for your work?

No hedge fund registered before the last 2 weeks will use Llama3 for their "prod work" beyond "experiments".

Quant trading is about "going fast" or "being super right", so either you'd need to be sitting on some huge llama.cpp/transformer improvement (possible but unlikely) or its more likely just some boring math applied faster than others.

Even if they are using a "LLM", they wont tell you or even hint at it - "efficient market" n all that.

Remember all quants need to be "the smartest in the world" or their whole industry falls apart, wait till you find out its all "high school math" based on algo's largely derived 30/40 years ago (okay not as true for "quants" but most "trading" isn't as complex as they'd like you/us to believe).

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