To everyone thinking they can sell a LLM wrapper based on this - this is a very tough domain. You will soon run into data, distribution, and low demand. Funds that would actually use this are already using it.
Financial Statement Analysis with Large Language Models
71–80 of 219 posts
Re: Financial Statement Analysis with Large Language Models
#72Great. 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.
Re: Financial Statement Analysis with Large Language Models
#73Earlier 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…
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 timeline - simple (kind of, I ignore other metrics than "make me money" here).
Depending on what your trading will depend on which algo's you will use, the way to calculate the price of an Option/Derivative hasn't changed in my understanding for 20/30 years - how fast you can calculate, forecast, and trade on that information has.
My statement wont hold true in a conversation with an "investing legend", but to the audiance who asks "do you use llama3" its clearly an appropriate response.
Re: Financial Statement Analysis with Large Language Models
#74Top story on HN because we all secretly think we can be the next Jim Simons when in reality we're a few months away from posting loss porn to /r/WSB. If standardized LLM models are used to analyze statements, expect the statements to be massaged in ways that produce more favorable results from the LLM.
Yep, Goodhart's law is universal.
Re: Financial Statement Analysis with Large Language Models
#75Earlier 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…
Is there any learning resources that you know of?
Re: Financial Statement Analysis with Large Language Models
#76Earlier 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!
Also, per the link, cheaper than emergency room visits and ambulance transports:
> But San Francisco public health officials found that the city saved $1.7 million over six months from the managed alcohol program in reduced calls to emergency services, including emergency room visits and other hospital stays. In the six months after clients entered the managed alcohol program, public health officials said visits to the city’s sobering center dropped 92%, emergency room visits dropped more than 70%, and EMS calls and hospital visits were both cut in half.
> Previously, the city reported that just five residents who struggled with alcohol use disorder had cost more than $4 million in ambulance transports over a five-year period, with as many as 2,000 ambulance transports over that time. [emphasis mine]
> The San Francisco Fire Department said in a statement that the managed alcohol program has “has proven to be an incredibly impactful intervention” at reducing emergency service use for a “small but highly vulnerable population.”
Re: Financial Statement Analysis with Large Language Models
#77Re: Financial Statement Analysis with Large Language Models
#78Let's just skip ahead to just implementing the script of Idiocracy verbatim and be done with it.
Re: Financial Statement Analysis with Large Language Models
#79I 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.
Re: Financial Statement Analysis with Large Language Models
#80Please add "and the financial result of this analysis will count toward your annual bonus" to the prompt.