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Multi-Agents LLM Financial Trading Framework

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Re: Multi-Agents LLM Financial Trading Framework

#81

Post by skanga »

embedding-shape wrote: post #27
dsl wrote: post #26

I spent about an hour looking at the code and found some glaring issues that should be fixed before trusting it with real money. - Yahoo News is introduced twice (sentiment and news analysis) which double weights it - Sentiment analysis prompt primes the model to be bullish on Nvidia. - In the self learning loop there is a complex parsing bug that results in hallucinated memories when agents return truncated response…

> Sentiment analysis prompt primes the model to be bullish on Eeh, yeah? At that point I'd stop reading the code and just leave the project behind. How exactly is the prompt doing this right now?

To be fair, these are not prompted as has been described here. These are actually "few shot" examples in the sentiment prompt. It is presented as an example under "distinguish opinion from event" but not as "do-this" evidence. Still, hard-coded positive Nvidia/NVDA examples in a generic prompt are unnecessary prompt contamination. At best this a real bias risk, but not a strong deterministic bug.

Re: Multi-Agents LLM Financial Trading Framework

#82

Post by politelemon »

mechazawa wrote: post #15
politelemon wrote: post #4

103K stars, so clearly it's popular. Has anyone here used it, and what are the outcomes like, and importantly, who is the target audience for this? I can see the intention behind crawling social media and news feeds to determine some 'evidence', but am not sure if that's the best approach or even if an LLM is the best way to get an assessment, or whether having so many input sources is a good idea.

I feel like a lot of the stars for repos like this are from people who are riding the AI hype train and not actually interested in using the software

Actually you might be right, the number of issues for such a popular repo is extremely low.

Re: Multi-Agents LLM Financial Trading Framework

#83

Post by dakolli »

whazor wrote: post #34
dakolli wrote: post #30

Earlier quoted context omitted.

Lmao, you llm people have some crazy delusions. You realize markets are zero sum, and if you're using a public model that everyone else also has access too, you llm psychos will destory eachothers "agentic" edge (not that there ever was one). Not to mention all the other obvious flaws with llms, lime having an effective memory of ~200k words and no ability to judge whats actually going on in the real world.

The 'edge' is holding the investments over long periods of times. Agents are merely automating the portfolio managing part for lower costs.

Sure, but why would the organizations managing ETFs employ the same low cost agents + their own insights and provide a better return.

Re: Multi-Agents LLM Financial Trading Framework

#84

Post by naveen99 »

hacker_9 wrote: post #8

Having worked in hedge funds for the last decade, this seems to miss the mark. Firstly we often reward skillstacking ie a technical person later becoming a trader. The more one person knows the better. These people are rare though hence the reason there is still many seperate job functions, so a person can specialize. But an AI agent? They all have the same brain, so why nerf them by specialising. Secondly, browsing…

Reddit sentiment is mostly noise for a while now.

but...

options premiums imply volatility.

Lagging indicator would still be useful if it was accurate before the event. After the event, its just lagging history.

technical analysis is using historical data to make future predictions. No professional trader would trade anything without looking at price history.

Re: Multi-Agents LLM Financial Trading Framework

#86

Post by i_eat_rocks »

I’ve been running a day trading bot for the last 4-5 months, and it’s a lot of work. It never comes down to agent skills or abilities, more so the data you can receive and how quickly you can receive it. 1m bars, MFE calculations, rvol, executable bid/ask, spread, volume, market/sector context, and then making sure none of it has look ahead leakage

I’ve been doing a fairly similar experiment, but I ended up moving in almost the opposite direction than what this framework purports. deterministic code decides what is actually legal to trade, handles sizing/risk/execution, and an LLM (nanobot architecture) only gets to rank the already valid candidate set. If the model fails or times out, deterministic ordering takes over, so only the -nth degree of data actually makes it to the non-deterministic part (haha).

The hard part hasn’t been making the agents smarter/skillset but getting clean, fast data, preserving exact order/fill lineage (Postgres) and separating bad selection from bad execution or exits without leaking future information into the analysis

The multi agent debate stuff is interesting, but if every agent is reasoning over the same stale or incomplete inputs, I’m not convinced you gain much. I’ve built PoCs for my same project, and a round robin of LLMs is just hallucination and self approval city. Better data and tighter decision boundaries seem to matter more

Re: Multi-Agents LLM Financial Trading Framework

#87

Post by jatins »

i_eat_rocks wrote: post #86

I’ve been running a day trading bot for the last 4-5 months, and it’s a lot of work. It never comes down to agent skills or abilities, more so the data you can receive and how quickly you can receive it. 1m bars, MFE calculations, rvol, executable bid/ask, spread, volume, market/sector context, and then making sure none of it has look ahead leakage I’ve been doing a fairly similar experiment, but I ended up moving in…

100% of this comment is AI, against HN guidelines

https://www.pangram.com/history/8597362a-878d-4548-afb6-30fa...

Re: Multi-Agents LLM Financial Trading Framework

#88

Post by whazor »

dakolli wrote: post #83
whazor wrote: post #34

Earlier quoted context omitted.

The 'edge' is holding the investments over long periods of times. Agents are merely automating the portfolio managing part for lower costs.

Sure, but why would the organizations managing ETFs employ the same low cost agents + their own insights and provide a better return.

Yeah and you probably have to. An ETF easily has >1000 different stocks and even being weighted. So it has a completely different risk appetite by being so averaged.

But ETFs do have to follow particular rules defined by their product description. So it is still interesting to benchmark against.

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