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Financial Statement Analysis with Large Language Models

papers.ssrn.com

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Re: Financial Statement Analysis with Large Language Models

#121

Post by repeekad »

nvy wrote: post #79
dangerwill wrote: post #69

I guess this makes sense. Because while there should be some noise from the text translation into the internal representation of the financial data once ingested into the model, the authors purposefully re-formatted all the reports to be formatted consistently. That then should allow the model to essentially do less of the LLM magic and more plain linear regression of the financial stats. And often past performance d…

You can scrape the filings from EDGAR, which presents the statements in standardized format.

fintool.com already has an LLM on top of EDGAR

Re: Financial Statement Analysis with Large Language Models

#122

Post by flourpower471 »

aniviacat wrote: post #115
flourpower471 wrote: post #107

Earlier quoted context omitted.

It is just a different (applied) discipline. It's like math v engineering - you can come up with some beautiful pde theory to describe this column in a building will bend under dynamic load and use it to figure out exactly the proportions. But engineering is about figuring out "just make its ratio of width to height greater than x" Because the goal is different - it's not about coming up with the most pleasing descri…

Claiming that being smart isn't required for trading is not the same as claiming that people doing trading aren't smart. (Note that I personally have no opinion on this topic, as I'm not sufficiently informed to have one.)

I was specifically addressing the "being smart isn't necessary for trading".

The op is making some implication across numerous posts that it's all basically a big con and it's all very simple.

It is like claiming you don't need to be rocket scientist to go to the moon because they just use metal and screws.

The individual parts might be simple in isolation. But it is the complexity of conducting large scale, large scope research in an environment that gives you limited feedback and will adapt to your own behaviour changes that is where the smarts are needed.

OP seems to not understand the inherent difficult of doing any research.

Almost anybody could be taught to make a simple circuit and battery from some basic raw materials. The fact it is simple and easy now we know the answer does not mean it was simple or easy to discover. Some of the greatest minds dedicated their entire lives to discovering things that now most 10 years olds understand. That doesn't imply you only need to have the intellect of a 10 year old to make fundamental breakthroughs in science.

Working in quant trading is almost pure research - and so it requires a certain level of intellect - probably at least the intellect required to pursue a quantitative PhD successfully (not that they need the PhD but they need the capacity to be able to do one).

Re: Financial Statement Analysis with Large Language Models

#123

Post by jasonfarnon »

flourpower471 wrote: post #112
Izkata wrote: post #89

Earlier quoted context omitted.

> but most "trading" isn't as complex as they'd like you/us to believe I know nothing about this world, but with things like "doctor rediscovers integration" I can't help but wonder if it's not deception but ignorance - that they think it really is where math complexity tops out at.

Drs rediscover integration is about people stepping far outside their field of expertise. It is neither deception or ignorance. It's the same reason some of the best physics students get PhD studentships where they are basically doing linear regression on some data. Being very good at most disciplines is about having the fundamentals absolutely nailed. In chess for example, you will probably need to get to a reasonab…

write bubble sort backward in assembly

you mean backporting a high-level implementation to assembly? Or is writing code "backward" some crazy challenge interviewees have to do now?

Re: Financial Statement Analysis with Large Language Models

#124

Post by flourpower471 »

chronic7202h wrote: post #120
flourpower471 wrote: post #112

Earlier quoted context omitted.

Drs rediscover integration is about people stepping far outside their field of expertise. It is neither deception or ignorance. It's the same reason some of the best physics students get PhD studentships where they are basically doing linear regression on some data. Being very good at most disciplines is about having the fundamentals absolutely nailed. In chess for example, you will probably need to get to a reasonab…

> Id say the industry average for somebody moving to a new firm and trying to replicate what they did at their old firm is about 5%. Because 95% of experienced candidates in trading were fired or are trying to scam their next employer. “Oh, yeah, my can do sharpe for million pnl per year. Trust me bro”. Fucking annoying

Obviously not true. The deals for most of these set ups are team founders/pms are paid mostly by profit share. So the only scam is scamming yourself into a low salary position for a couple years till they fire you.

Orders of magnitude more leave their jobs of their choosing than are fired.

Re: Financial Statement Analysis with Large Language Models

#125

Post by jasonfarnon »

SavageBeast wrote: post #36
bossyTeacher wrote: post #33

Earlier quoted context omitted.

>People didn't stop working on this in 1989 - they realised they can make lots of money doing it and do it privately. Mind elaborating?

Speaking for myself and likely others with similar motivations, yes we can "figure it out" and publish something to show our work and expand the field of endeavor with our findings - OR - we can figure something profitable out on our own and use our own funds to trade our strategies with our own accounts. Anyone who has figured out something relatively profitable isn't telling anyone how they did it.

Why not then publish the strategies once outmoded, or are they in fact published? Can I go see somewhere what strategies big funds used in the 90s to make bank, which presumably no longer offer a competitive advantage? The way I can go see what computer exploits/hacks used to work when they were still secret?

Maybe it's just what I know, but I can't help but think the "strategies" are a lot like security exploits--some cleverness, some technical facility, but mainly the result of staring at the system for a really long time and stumbling on things.

Re: Financial Statement Analysis with Large Language Models

#126

Post by worik »

I am disturbed to see so much enthusiasm here for "trading"

Markets matter, and some speculation is useful, but the purpose of markets is not speculation. Obviously.

If you want to make some money get trained and get a good salary. Save your money in safe assets

if you want to get supper rich be super creative, ensure going broke will only effect you (i.e. do not do this while supporting a family), and found a firm. You will likely fail, but there is a chance of super wealth and a bigger chance of a wild ride that will be good for you

Trading from the perspective of greed runs the risk of total destruction. Putting you in jail, maybe. Bankruptcy if not too unlucky. Many people out of work because of your misallocation, and if you do not care about that I'm not interested in you

The financial system is a zero sum game. (The economy in general is not) There is always someone cleverer and they likely do not care if they crush you. International finance is a snake pit

Friends, look after friends. Maximise happiness. Be honest, be ethical, be safe

Live long and prosper

Re: Financial Statement Analysis with Large Language Models

#127

Post by Terretta »

worik wrote: post #126

I am disturbed to see so much enthusiasm here for "trading" Markets matter, and some speculation is useful, but the purpose of markets is not speculation. Obviously. If you want to make some money get trained and get a good salary. Save your money in safe assets if you want to get supper rich be super creative, ensure going broke will only effect you (i.e. do not do this while supporting a family), and found a firm.…

> the purpose of markets is not speculation

Arguably, the purpose of markets is part price discovery, part liquidity, and arguably mostly to support economic growth and stability by channeling funds from savers to those who can invest them productively.

> If you want to make some money get trained and get a good salary. Save your money in safe assets

Sure, as long as you're not into dynamism.

Re: Financial Statement Analysis with Large Language Models

#128

Post by latency-guy2 »

worik wrote: post #126

I am disturbed to see so much enthusiasm here for "trading" Markets matter, and some speculation is useful, but the purpose of markets is not speculation. Obviously. If you want to make some money get trained and get a good salary. Save your money in safe assets if you want to get supper rich be super creative, ensure going broke will only effect you (i.e. do not do this while supporting a family), and found a firm.…

You assert a lot of personal opinions. On top of bad "characterizations" of people who are not you.

I don't think this is a signature of a person being honest, or trustworthy.

Re: Financial Statement Analysis with Large Language Models

#129

Post by richrichie »

antimatter15 wrote: post #9

Figure 3 on p.40 of the paper seems to show that their LLM based model does not statistically significantly outperform a 3 layer neural network using 59 variables from 1989. This figure compares the prediction performance of GPT and quantitative models based on machine learning. Stepwise Logistic follows Ou and Penman (1989)’s structure with their 59 financial predictors. ANN is a three-layer artificial neural networ…

The infamous 1/N portfolio comparison is missing. 1/N puts to shame many strategies.

Re: Financial Statement Analysis with Large Language Models

#130

Post by Fomite »

bossyTeacher wrote: post #33
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.

>People didn't stop working on this in 1989 - they realised they can make lots of money doing it and do it privately. Mind elaborating?

At a SciPy meeting where someone in finance was presenting an intro on some tools, someone asked if they ever contribute code to those open source projects. Their answer was "Yes, but only after we've stopped making money with them."
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