TradingAgents: An Open-Source Multi-Agent LLM Framework for Financial Trading
Multi-Agents LLM Financial Trading Framework
TradingAgents is an open-source framework that simulates a real trading firm using multiple LLM-powered agents. It employs specialized roles—fundamental, sentiment, news, and technical analysts—along with bullish/bearish researchers, a trader, and a risk management team. These agents collaborate through structured debates to evaluate market conditions and make trading decisions. Built with LangGraph, it supports multiple LLM providers and includes features like decision logging and checkpoint resume. The project, from TauricResearch, is fully open-sourced and available on GitHub.
TradingAgents is a multi-agent trading framework that mirrors the dynamics of real-world trading firms.
- alastairr
I'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.
- _pdp_
If 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/
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
- hacker_9
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 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.
- dsl
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 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
- SKYNET800
https://github.com/ConsciousGroupMind/SKYNET-800---Collectiv...