Live data from Hacker News

Financial Statement Analysis with Large Language Models

papers.ssrn.com

81–90 of 219 posts

Re: Financial Statement Analysis with Large Language Models

#81

Great. Humans no longer need to cook the books and can claim plausible deniability. The only problem is the hallucination errors could go against you as well as for you.

They may claim, but there is no such plausible deniability. Not for lawyers using AI hallucinations, not for Tesla drivers crashing into things with FSD, not for tax fraud. People are ultimately held responsible and accountable for the way they use AI.

Re: Financial Statement Analysis with Large Language Models

#82

The area where I see this making the most transformational change is by enabling average citizens to ask meaningful questions about the finances of their local government. In Cook County, Illinois, there are hundreds of local municipalities and elected authorities, all of which are producing monthly financial statements. There is not enough citizen oversight and rarely any media attention except in the most egregious…

I think this is in general one of the big wins with LLMs: Simple summarization. I first encountered it personally with medical lab reports. And as I noted in a past comment, GPT actually diagnosed an issue that the doctors and nurses missed in real-time as it was happening.

The ability to summarize and ask questions of arbitrarily complex texts is so far the best use case for LLMs -- and it's non-trivial. I'm ramping up a bunch of college intern devs and they're all using LLMs and the ramp up has been amazingly quick. The delta in ramp up speed between this and last summer is literally an order of magnitude difference and I think it is almost all LLM based.

Re: Financial Statement Analysis with Large Language Models

#83

Earlier quoted context omitted.

Let's say LLMs work exactly as advertised in this case: you go into the LLM, say "find corruption in these financial reports", and it comes back with some info about the mayor spending millions on overpriced contracts with a company run by his brother. What then? You can post on Twitter, but unless you already have a following it's shouting into the void. You can go to your local newspapers, they'll probably ignore y…

Are people supposed to be outraged that that is too little or too much money? That's still cheaper than sending them to prison!

> That's still cheaper than sending them to prison!

Literally:

> It costs an average of about $106,000 per year to incarcerate an inmate in prison in California.

https://www.lao.ca.gov/PolicyAreas/CJ/6_cj_inmatecost

Re: Financial Statement Analysis with Large Language Models

#84

Earlier quoted context omitted.

It’s impressive how incorrect so much of this information is. High frequency trading is about going fast. There is a huge mid and low freq quant industry. Also most quant strategies are absolutely not about being “super right”…that would be the province of concentrated discretionary strategies. Quant is almost always about being slightly more right than wrong but at large scale. What algos are you referring to derive…

Quantitative trading is simply the act of trading on data, fast or slowly, but I'll grant you for the more sophisticated audience there is a nuance between "HFT" and "Quant" trading. To be "super right" you just have to make money over a timeline, you set, according to your own models. If I choose a 5 year timeline for a portfolio, I just have to show my portfolio outperforming "your preferred index here" over that t…

> how fast you can calculate , forecast, and trade on that information has.

How you can calculate fast, forecast, and trade on that information has

There. Fixed it for you. ;)

Re: Financial Statement Analysis with Large Language Models

#86
if you want to see successful "machine learning based financial statement analysis", check out my paper & thesis. its from 2019 and ranks #1 for the term on google and gs because it is the first paper that applies a range of machine learning methods to all the quantitative data in them instead of just doing nlp on the text. happy to answer questions

paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3520684

thesis https://ora.ox.ac.uk/objects/uuid:a0aa6a5a-cfa4-40c0-a34c-08...

Re: Financial Statement Analysis with Large Language Models

#87
> In this section, we aim to understand the sources of GPT’s predictive ability.

Oh boy... I wonder how a neural net trained with unsupervised learning has a predictive ability. I wonder where that comes from... Unfortunately, the article doesn't seem to reach a conclusion.

> We implement the CoT prompt as follows. We instruct the model to take on the role of a financial analyst whose task is to perform financial statement analysis. The model is then instructed to (i) identify notable changes in certain financial statement items, and (ii) compute key financial ratios without explicitly limiting the set of ratios that need to be computed. When calculating the ratios, we prompt the model to state the formulae first, and then perform simple computations. The model is also instructed to (iii) provide economic interpretations of the computed ratios.

Who will tell them how an LLM works and that the neural net does not calculate anything? It only predicts the next token in a sentence of a calculation if it's been loss-minimized for that specific calculation.

It looks like these authors are discovering large language models as if they are some alien animal. When they are mathematically describable and really not so mysterious prediction machines.

At least the article is fairly benign. It's about the type of article that would pass as research in my MBA school as well... It doesn't reach any groundbreaking conclusions except to demonstrate that the guys have "probed" the model. Which I think is good. It's uninformed but not very misleading.

Re: Financial Statement Analysis with Large Language Models

#88

Earlier quoted context omitted.

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 - "eff…

It’s impressive how incorrect so much of this information is. High frequency trading is about going fast. There is a huge mid and low freq quant industry. Also most quant strategies are absolutely not about being “super right”…that would be the province of concentrated discretionary strategies. Quant is almost always about being slightly more right than wrong but at large scale. What algos are you referring to derive…

Leveraging "hidden" risk/reward asymmetries is another avenue completely that applies to both quant/HFT, adding a dimension that turns this into a pretty complex spectrum with plenty of opportunities.

The old joke of two economists ignoring a possible $100 bill on the sidewalk is an ironic adage. There are hundreds of bills on the sidewalk, the real problem is prioritizing which bills to pick up before the 50mph steamroller blindsides those courageous enough to dare play.

Re: Financial Statement Analysis with Large Language Models

#89

Earlier quoted context omitted.

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 - "eff…

> 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.

Re: Financial Statement Analysis with Large Language Models

#90

The area where I see this making the most transformational change is by enabling average citizens to ask meaningful questions about the finances of their local government. In Cook County, Illinois, there are hundreds of local municipalities and elected authorities, all of which are producing monthly financial statements. There is not enough citizen oversight and rarely any media attention except in the most egregious…

that's what I did with my town financial report. Asked chatGPT to find irregularities. The response was very concerning, with multiple expenses that looked truly very suspicious (like planting a tree - 2000$). I would have gone berserk at the town council meeting if I was an activist citizen.
Post reply on HN