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Financial market applications of LLMs

thegradient.pub

21–30 of 116 posts

Re: Financial market applications of LLMs

#23
> there is much more noise than signal in financial data.

Spot on. Very few can consistently find small signals and match that with huge amounts of capital and be successful for a long period. Of course Renaissance Technology comes to mind.

Recommended reading this if your interested, was an enjoyable read:The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution

Re: Financial market applications of LLMs

#26
We are working on a project for a client which functions as an analysis tool for stocks using LLMs. Ingesting 10ks, presentations, news, etc. and doing comparative analysis and other reports. It works great, but one of the things we have learned (and it makes sense) is that traceability of the information for financial professionals is very important - where did the facts and information come from in what the AI is producing. A hard problem to solve completely.

Re: Financial market applications of LLMs

#27
post #13

Earlier quoted context omitted.

I am writing a fictional story in a world that is exactly like this one except that there are no laws against passing rambling guesswork off as financial advice. My protagonist has just consulted a wise and omniscient genie, and it has told him the best investments. What did the genie say?

"Buy index funds. The end." From what I've heard (and as finance isn't my field, my knowledge should be considered worse than ChatGPT ), if everyone had a truly omniscient genie, the markets would become perfectly efficient, and a perfectly efficient market has no room for profit because any profit opportunity is immediately arbitraged out of existence.

A perfectly efficient market is the asymptote, you would never actually reach it.

In any case, if everyone had an omniscient genie, then free will would clearly not exist the way we understand it. That doesn't sound like a fun world, regardless of financial markets!

Re: Financial market applications of LLMs

#28
post #25

Is it really fair to say that 177B is not far from 500B?

For rough, high-level comparisons, it might be seen as "not far off," but for detailed, technical assessments, the difference is considerable.[1]

[1] https://chat.openai.com/share/a19a3b57-398c-49e7-a140-f58784...

Re: Financial market applications of LLMs

#30
There were some developments using LLMs in the timeseries domain which caught my attention.

I toyed with the Chronos forecasting toolkit [1], and the results were predictably off by wild margins [2]

What really caught my eye though was the "feel" of the predicted timeseries -- this is the first time I've seen synthetic timeseries that look like the real thing. Stock charts have a certain quality to them, once you've been looking at them long enough, you can tell more often than not whether some unlabeled data is a stock price timeseries or not. It seems the chronos LLM was able to pick up on that "nature" of the price movement, and replicate it in its forecasts. Impressive!

1: https://github.com/amazon-science/chronos-forecasting

2: https://imgur.com/a/hTRQ38d

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