four days later 24/11 they are all in the negative with grok having lost nearly half of its starting sum
Exploring the limits of large language models as quant traders
101–103 of 103 posts
Re: Exploring the limits of large language models as quant traders
#102Earlier quoted context omitted.
I would argue that sentiment classification is where LLMs perform best. folks are already using it for precisely such purpose - have even built a public index out of it
what index ?
found one such index https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5763042 called Populism Index (POP) built from Wall Street Journal articles (not sure how publicly accessible it is)
Re: Exploring the limits of large language models as quant traders
#103Earlier quoted context omitted.
Yes, but LLM can barely cope with following the ordering of complex software tutorials linearly. Why would you reasonably expect them unprompted to understand time any better enough to trade and turn a profit?
My comment makes no such claim. I wrote about different timeframes that trading strategies operate on.
Exactly. If it can't distinguish between a basic repeat after me ordering how is it going to even get a simple output order correct? Let alone pull apart the strategies themselves