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Reading SEC filings using LLMs

beatandraise.com

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Re: Reading SEC filings using LLMs

#61

Post by nnechm »

jatinshah wrote: post #60

The main use case highlighted here seems to be retrieving quantitative data from financial reports and then doing sophisticated analysis (trendlines, forecasting etc) using ChatGPT (basically what’s currently done in Excel). I doubt any finance professional would want to move from Excel to ChatGPT for these use cases. A secondary issue is that numbers in financial reports need to be standardized before they can be us…

I don't think excel can be defeated :) I certainly do not expect financial professionals to switch to a chat interface.

When you login into capitaliq or factset or look at a bloomberg screen, you access data, you can then do the same here. Excel plugins go on top which can then get this data into excel to build models. The api that powers this app, can also send data into excel for instance.

Data can be copied already directly from the chat box into excel, maintaining the table format for e.g

Regarding standardization, I think data was standardized not to enable comparison but simply to fit into the same schema for every industry. Most companies within the same industry report the same way. REITs do not report like SaaS, but the existing datasets put it all into one set. Raw data from source is always better as you can convert it to standardized but you can't go back...

Re: Reading SEC filings using LLMs

#62

Post by jatinshah »

nnechm wrote: post #61
jatinshah wrote: post #60

The main use case highlighted here seems to be retrieving quantitative data from financial reports and then doing sophisticated analysis (trendlines, forecasting etc) using ChatGPT (basically what’s currently done in Excel). I doubt any finance professional would want to move from Excel to ChatGPT for these use cases. A secondary issue is that numbers in financial reports need to be standardized before they can be us…

I don't think excel can be defeated :) I certainly do not expect financial professionals to switch to a chat interface. When you login into capitaliq or factset or look at a bloomberg screen, you access data, you can then do the same here. Excel plugins go on top which can then get this data into excel to build models. The api that powers this app, can also send data into excel for instance. Data can be copied alread…

If this product is not meant for finance professionals then who is the target customer?

Retrieving numbers via ChatGPT and then feeding it into Excel via APIs seems like a very odd thing to do. Especially when most of these numbers are already available on Yahoo finance for individual investors and CapitalIQ for professionals.

Re: Reading SEC filings using LLMs

#63

Post by provability »

dcsan wrote: post #22
anotherhue wrote: post #3

Earlier quoted context omitted.

I've been trying something similar with parliamentary debates. They're long winded, often full of empty speech, and a chore to read. The LLMs are able to hone in on the details and provide interesting responses like "What questions were asked of the minister that they failed to address" and "What should the opposition leader have mentioned in their response that the minister would have found difficult to answer" Cruc…

Could you ask an LLM if they were persuaded by a speaker of one side of a debate as a method of evaluation? Ie the bot's before and after opinion based on fine-tuning with the pro and con arguments? I was also thinking about a society of bots type application where you could have autonomous bot researchers, debaters, judges and audience. Would be interesting to feed in the topics and grab some popcorn

I like this question. I've always wanted to be able to compute, somehow, the "partial derivative of x with respect to y," where x is a proposition and y is an argument or a piece of evidence. It seems to me as though we're closer than ever before. The models are still fairly opaque, but I'm hoping the interpretability research will succeed and allow such introspection!

Re: Reading SEC filings using LLMs

#64

Post by blitzar »

DoingIsLearning wrote: post #38

I wonder if this will lead to fillings that use even more obfuscation in fillings with convoluted wording and obscure language whenever companies need to disclose bad news.

Almost certainly. Filings are written to communicate a specific message - if the Ai pass was to interpret a hidden meaning, filings would get rewritten to indicate the desired message.

Re: Reading SEC filings using LLMs

#65

Post by i_like_pie1 »

alxdrlitreev wrote: post #49

We've recently made COFIN AI — an AI based on ChatGPT that reads hundreds of pages of SEC filings such as 10Ks and 10Qs and checks investor calls to assist you with investment research and strategy evaluation. Pretty much similar (almost the same) to something you did. Check this out: https://cofinapp.com Let me know what you think!

asked 3 questions

1st question = got the ticker wrong. asked about company A - gave info on B 2nd question = please give info on A. it says sure 3rd question = please give info on A. pops a modal asking to pay

Re: Reading SEC filings using LLMs

#66

Post by nnechm »

jatinshah wrote: post #62
nnechm wrote: post #61

Earlier quoted context omitted.

I don't think excel can be defeated :) I certainly do not expect financial professionals to switch to a chat interface. When you login into capitaliq or factset or look at a bloomberg screen, you access data, you can then do the same here. Excel plugins go on top which can then get this data into excel to build models. The api that powers this app, can also send data into excel for instance. Data can be copied alread…

If this product is not meant for finance professionals then who is the target customer? Retrieving numbers via ChatGPT and then feeding it into Excel via APIs seems like a very odd thing to do. Especially when most of these numbers are already available on Yahoo finance for individual investors and CapitalIQ for professionals.

:) I guess its not very odd to say investment research is a lot of reading and LLMs are already very good at reading. So there is little doubt that LLMs will change the investment research process. Have you used CapitalIQ, do you use it on the browser or in excel. If you use it on the browser, the experience using beatandraise.com is already better for some cases. For instance, try getting Apple's Rest of Asia Pacific revenues which apple has been highlighting is their main growth region this year, you can pull that out easily. https://imgur.com/a/rRnrB4u Can you do that on capitaliq, you would have to hope their standardized tables include this...

Re: Reading SEC filings using LLMs

#67

Post by nnechm »

i_like_pie1 wrote: post #65
alxdrlitreev wrote: post #49

We've recently made COFIN AI — an AI based on ChatGPT that reads hundreds of pages of SEC filings such as 10Ks and 10Qs and checks investor calls to assist you with investment research and strategy evaluation. Pretty much similar (almost the same) to something you did. Check this out: https://cofinapp.com Let me know what you think!

asked 3 questions 1st question = got the ticker wrong. asked about company A - gave info on B 2nd question = please give info on A. it says sure 3rd question = please give info on A. pops a modal asking to pay

I am assuming this is on Cofin and not on beatandraise.com, if so, please let me know, I shall fix it. You have 20 chats etc.

Re: Reading SEC filings using LLMs

#68

Post by rtkwe »

notahacker wrote: post #39
dcsan wrote: post #22

Earlier quoted context omitted.

Could you ask an LLM if they were persuaded by a speaker of one side of a debate as a method of evaluation? Ie the bot's before and after opinion based on fine-tuning with the pro and con arguments? I was also thinking about a society of bots type application where you could have autonomous bot researchers, debaters, judges and audience. Would be interesting to feed in the topics and grab some popcorn

I think you could ask an LLM if they were persuaded, but I don't think you'd get meaningful data from it Leaving aside the bots that are trained to answer "as an LLM I do not have opinions..." it's going to be a very basic probabilistic yes or no based on tone and numbers of pros and cons rather than knowledge of the surrounding political context and higher order reasoning about the accuracy of the claimed pros and c…

Yeah the bot has both no initial position and no internal opinion on fact that an argument could operate on. It might write you a cogent response but it's fundamentally not a question an LLM can meaningfully answer.

Re: Reading SEC filings using LLMs

#69

Post by staticman2 »

dcsan wrote: post #22
anotherhue wrote: post #3

Earlier quoted context omitted.

I've been trying something similar with parliamentary debates. They're long winded, often full of empty speech, and a chore to read. The LLMs are able to hone in on the details and provide interesting responses like "What questions were asked of the minister that they failed to address" and "What should the opposition leader have mentioned in their response that the minister would have found difficult to answer" Cruc…

Could you ask an LLM if they were persuaded by a speaker of one side of a debate as a method of evaluation? Ie the bot's before and after opinion based on fine-tuning with the pro and con arguments? I was also thinking about a society of bots type application where you could have autonomous bot researchers, debaters, judges and audience. Would be interesting to feed in the topics and grab some popcorn

If you tell the LLM it is conservative it will report it was persuaded by the conservative speaker, if you tell it it is a liberal it will say it's persuaded by the liberal speaker. It will be happy to roleplay at being persuaded but I don't know why that would be useful?

Re: Reading SEC filings using LLMs

#70

Post by pbhjpbhj »

hef19898 wrote: post #15
nnechm wrote: post #2

I have been working on getting ChatGPT to answer questions that equity research analysts, investors would like to get from SEC filings. The application uses a combination of hybrid text search and LLMs for completion and does not rely much on embedding based distance searches. A core assumption underlying this is that LLMs are already pretty good and will continue to get better at reading texts. If provided with the…

I once had a collegue who used ChatGPT to sumarize our then employer's SEC filings. Results were, well, putting it mildly, mixed. Best case was a slightly less biased version of the "shareholder letters" (read: propaganda pieces) published around the same time. What ChatGPT completey missed was stuff like omissions (I'll kind of give it a pass here, how can software analyse the absence of something without having acc…

It seems like a system incorporating an LLM would be good at parsing a document to match all investors mentioned with the amounts invested and spot any major differences. That a generalized tool can't do that out of the gate doesn't seem surprising.
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