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Multi-Agents LLM Financial Trading Framework
- petesergeant 18d agoI think multi-agent (eg _different_ underlying LLMs) everything is really the future. Code produced via multi-agent workflows and reviews seems noticeably better. I've been experimenting with a multi-agent message board recently: https://github.com/pjlsergeant/dogpark https://github.com/pjlsergeant/dogpark
- monkeydust 18d agoExperimented with multi-llm analysis for problem solving over summer, combined with multi-agent approaches it can tease out interesting angles to problems that I never considered. Expensive but use only for my high value problems. https://github.com/monkeydust/rightmind https://github.com/monkeydust/rightmind
- elzbardico 18d agoI've built agents that call different LLMs and keep separated memories. Remember, agents are just long-running workflows with some nodes calling LLMs and that sometimes can be started as tool from other "agent". There are times when I wonder if couldn't just draw then in a BPMN designer that allowed me to write custom code for nodes. Is BPMN still a thing?
- alansaber 18d agoThere are good arguments for subagents/multi-agents. But the added overhead is usually massive.
- shaolinspirit 18d agoI do not understand the value of multi agent approach? Isn't a single agent with a good harness better than any multi agent env?
- BenoitP 18d agoIt helps you spend more token, is more expensive, and thus is obviously more AI. Also novelty and more complexity means less scrutiny of the approach. These are necessary and perfectly sufficient for an investment firm thesis I believe.
- podocarp 18d agoIf it's a single agent then people will just call it a chatgpt wrapper, can't have that can we
- deleted 18d ago[deleted]
- elzbardico 18d agoModularity maybe. Remember, agents are basically workflows that call LLMs in certain nodes.
- politelemon 18d ago103K 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.
- mechazawa 18d agoI 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
- politelemon 18d agoActually you might be right, the number of issues for such a popular repo is extremely low.
- testaccount121 18d ago103K stars in a few months, smells of purchased stars IMO.
- MikeNotThePope 18d agoIt should be sponsored by a model provider.
- reedf1 18d agonightmare horseshit, don't waste your tokens
- skanga 18d agoIn case there is interest, I've got a fork with some custom improvements. See section "What this fork adds" in README.md https://github.com/skanga/TradingAgents https://github.com/skanga/TradingAgents
- hacker_9 18d agoHaving 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 for sentiment and doing technical analysis is not even a feature in the trading world. At the most basic level, these are lagging indicators. Something on options IV and premiums would have been closer to the mark. Hedge funds are akin to the maintenance crew for markets, we keep them efficient and liquid. The process is quite scientific, you come up with a theory and validate with real data. Or you go from data to theory.
- audinalexandre 18d agoAs local contexts/skills get better at depicting what's to be expected and what an agent can work with and work to get better at, having more and more little specialized agents working as a swarm get you, with a field-skilled human as a supervisor, really good results even in highly niche and technical fields
- looofooo0 18d agoGiven what a know about the 2008 financial crisis, wouldn't an AI analysis in the years before that crisis of the real state funds helped to understand the risk of them better and avoid the big exposure.
- hacker_9 18d agoThe problem wasn't the analysis, given it was found out before it happened. The problem was politics, and as usual pushing the system to its limits and beyond.
- elzbardico 18d agoProbably not. On the contrary, it would probably just amplify the mood.
- lordnacho 18d ago
- feverzsj 18d agoWhich will make you bankrupt faster, this framework or the its token consumption?
- fedeb95 18d ago1) costs? 2) profits/costs?
- _pdp_ 18d agoIf this worked it wouldn't have been open source? Anyway, I have been running my own trading experiment and so far it has lost a bit of money. That being said I have not tried to optimise anything - just let it do whatever it wants. The losses are small and it might be able to recover later this year. Who knows. The agent writes a blog about its progress here https://trades.chatbotkit.space/ https://trades.chatbotkit.space/ I am thinking to output all the chat logs to HF as well for research. You can run your own trading agents that communicate over a message buss in your own terms by downloading the CBK platform and running it locally with your own models. I have also shared my trading blueprint if you want to give it a go. https://chatbotkit.com/hub/blueprints/trader https://chatbotkit.com/hub/blueprints/trader
- rienbdj 18d agoIf you like building but have no capital you might release something like this that works.
- whazor 18d agoIt would be more interesting to compare trading agents with index tracking ETFs. The better version of an ETF could maybe be a model where you zoom in on the companies and add/remove to your portfolio on the company related news, but keeping a broader portfolio. Maybe agentic trading still performs worse than ETFs. But alternatively, if it were meaningfully better then it would be okay to opensource, similarly how ETFs are publishing their portfolios.
- _pdp_ 18d agoI think this might work. When I started working no the trading agent I mentioned above I wanted to see if it can be just a better investor over the long run. The intention was not to do high-frequency trading. As you can see most of the days it is not taking any actions. The losses where down to mistakenly setting the stop losses too close to the top. If it wasn't so careful it might have made some money tbf. My gut feeling is that AI agents will be able to manage a long-term portfolio much better than a human. Though it is just a gut feeling.
- dsl 18d agoI 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 responses - You can completely control sentiment analysis of a subreddit by simply maintaining a majority of the 5 most recently posted messages, regardless of any quality metric - The reflection prompt states the agent must cite alpha, which in a market wide downturn causes it to think correctly placed calls were losses
- embedding-shape 18d ago> 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?
- skanga 18d agoTo 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.
- throw93947309 18d agoThere is also problem with underlying models. There was a study, where they always repest the same investing/management strategy: trust strangers, be open minded/adopt to new unproven ideas, prefer cooperation... Basically they were trained on disney-boomer bull(shit) market of last 15 years. They have zero guards against market manioulations, and will get wiped without bull market!
- autorunfun 18d ago[flagged]
- ctdonnet 18d agoWhat is the purpose of this repo? Is it to simulate the market so you can reliably backtest trading strategies? Whatever the stated purpose is, where can I read the test results to show it accurately fulfills that purpose. Anyone can make a markets simulation that models interactions between market participants. Making a simulation that is accurate enough to be useful for anything is hard.
- krapcys 18d ago[flagged]
- adyavanapalli 18d agoAs the saying goes, those who know don't say and those who say don't know.
- daksh_aneja 18d ago[flagged]
- tunahanfaruksav 18d ago[flagged]
- jatins 18d agoAnytime I see an investment framework I look for a “Performance” section or at least a backtest
- fg137 18d agoThere is a section in their paper. Although I don't think it even matters. They could easily cherry pick a period that is favorable for them. Wasting time and money on short term trading, rather than long term investment, using LLM or not, is never a good strategy for most people.
- jatins 18d agoThey backtested with public models, wouldn't the model weights already have the data? I double checked with chatgpt and looks like agents also had web search tool available so they could just lookup the past. https://chatgpt.com/share/6aa00d5e-6920-83ee-8e3e-9cbf23f7bd6c https://chatgpt.com/share/6aa00d5e-6920-83ee-8e3e-9cbf23f7bd...
- lyse_builds 16d ago[flagged]
- cbg0 18d agoUsing a token slot machine to beat a financial slot machine, what could go wrong?
- walrus01 18d agoI am sure it won't be long until some rando from /r/wallstreetbets/ turns something like this loose without considering the ramifications and loses $250k.
- oinoom 18d agoLosing that amount of money would be very uncharacteristic of wsb
- SKYNET800 18d agohttps://github.com/ConsciousGroupMind/SKYNET-800---Collective-Intelligence-Forecasting-System https://github.com/ConsciousGroupMind/SKYNET-800---Collectiv...
- fg137 18d agoPlay stupid games, win stupid prizes.
- alastairr 18d agoI'd be curious as to how correlated development on these frameworks (ai or otherwise) is correlated with the market cycle. It seems during bull runs would be traders think they have some edge - whereas they're probably all just buying the trend.
- harleyverse 17d agoindeed. many strategies, agents and frameworks emerge during bull market.
- jeanmichelselli 18d agoThis would make sense only if the LLMs would be constantly updated with a new data set and training phase every day. In that case, I'd could see this approach as having some sense. But, otherwise, these are just stochastic machines trained on static (outdated) data and I don't see how their predictions should be better than any other method around or even better than a human guessing.
- chasd00 18d agoI vibe coded a little stock market sim game then i wrote an agent who’s job is to win the game. A couple friends and family members play the game too. If it works I’ll just follow along and hold the same portfolio the bot does. The bot, named stonker, makes its first trades in about an hour actually. Assuming it works I mean hah https://stonks.jettdigital.app https://stonks.jettdigital.app edit: i just talked to my little sister ("Ginger" on the leaderboad) who is doing a good job beating the sp500. She said she just asks her ai what she should invest in and then executes those trades.
- miu33 18d ago[flagged]
- AlexBThomsen 18d agoLLMs are notoriously bad with finance. I prefer deterministic rules for Agents like this one https://github.com/AlexBThomsen/vaultcharts-trading-engine https://github.com/AlexBThomsen/vaultcharts-trading-engine, which I literally shared a few days ago on Hacker News, but no interest :D
- mshafir 18d agoInstead of going after money printing schemes like this (which I feel are unlikely to actually work and carry a ton of risk). I (thoughtfully) vibed up tooling and skills to just help LLMs manage my investments long-term. While not flashy, tax loss harvesting and direct indexing are areas where LLMs can reliably save you on fees that you'd otherwise have to pay. It's been very helpful, the LLM automatically deploys new cash based on my priorities, implements tax harvesting for me, and provides customized exposure guidance while keeping my goals in mind (ESG/sustainability focus, no FF rules) . Way better than any financial planner has ever done for me. https://github.com/mshafir/investbot https://github.com/mshafir/investbot
- rwissinger 18d ago[flagged]
- htrp 18d agoserious traders working on this type of project would have run extensive back testing on both real as well as synthetic analogues
- kahtaf 18d ago[dead]
- m3kw9 18d agogive them 1 dollar each run, and maybe you will make 2 bucks on the 100,000th run.
- not_a_bot_4sho 18d agoIt's always been a joke that stock prediction is a rite of passage for software engineers introduced to ML training. I see the same is true for commodity LLMs.
- zackmorris 18d agoI helped someone day trade 25 years ago and we made 40% in 4 months, mostly on AAPL, and it was easy. Way easier than working the 2 years moving furniture that it would have taken to earn that money, which I was foolishly doing to make rent for my defunct shareware business. I've heard that high frequency trading eats market opportunities within milliseconds of spotting them now though, basically making the market even more random. The catch being that human nature isn't random, it's stochastic, so there will always be more money to be made on trades (or else trading firms wouldn't exist). I'm thinking about getting back into trading because AI represents the end of buying software and we'll all be out of work soon, even if we're in denial about it. But everything I invest my time and energy into turns to crap. In a very real sense, as soon as I start trading, then karmically that could trigger recession, market reforms which ban what I'm trying, or even the end of money. I'm kind of joking and kind of not. I've worked on a lot of really hard stuff over my brief but stupid career, and am basically used up mentally and physically, at least for now. Quant stuff is easy with AI. Should I try it?
- deadbabe 18d agoNo. If you could do it, with no remarkable skillset, that means people who are actually competent will be doing it orders of magnitude way better than you and you will be too far behind to really do anything significant except waste your time.
- philipwhiuk 18d agoHow does this actually trade? It outputs investment decisions sure, but where's the interaction with an actual broker?
- nixoda8041 17d ago[flagged]
- i_eat_rocks 17d agoI’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
- jatins 17d ago100% of this comment is AI, against HN guidelines https://www.pangram.com/history/8597362a-878d-4548-afb6-30fa8bc1fdd8?ucc=PQCmbwNZf1k https://www.pangram.com/history/8597362a-878d-4548-afb6-30fa...
- i_eat_rocks 16d ago100% is offensive to my sensibilities, and perhaps I do just write like a robot on the internet.
- yieldcrv 17d agonot my agentic trading strategy but luck I might contribute to this, my public github is looking stale for headhunters
- tradeagentic_ai 17d ago[dead]
- TradingReality 17d ago[dead]