zhound420

zhound420 / swarm-trader

Public

Multi-agent AI trading system using LLM-powered analyst agents (Buffett, Munger, Burry, etc.) with free data sources (SEC EDGAR + yfinance) and Alpaca integration.

15
4
89% credibility
Found Mar 14, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

Swarm Trader is a web-based AI hedge fund simulator where multiple expert investor agents analyze stocks and make paper trades with built-in safety rules.

How It Works

1
🔍 Discover Swarm Trader

You hear about this free AI tool that runs like a hedge fund with expert investor brains making stock picks.

2
📱 Set up your accounts

Sign up for a free paper trading account and connect an AI thinking service so agents can analyze stocks.

3
🚀 Open the web app

Launch the friendly web dashboard where everything is ready with one click.

4
Pick your trading style
📈
Swing trading

Let agents study company stories over days or weeks.

⚡
Day trading

Scan hot stocks for quick moves during market hours.

5
🧠 Watch 20 experts analyze

Famous investors like Buffett and Burry plus data wizards team up to study your stocks and vote on trades.

6
✅ Review safe decisions

See buy/sell ideas with automatic risk limits like stop losses and daily caps.

💰 Your AI fund trades

Watch paper profits build safely while you learn from expert reasoning.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 15 to 15 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is swarm-trader?

Swarm-trader is a Python-based multi-agent AI trading system that deploys 20 LLM-powered analyst agents—modeled after investors like Buffett, Munger, and Burry—to analyze stocks using free data from SEC EDGAR and yfinance, then executes trades via Alpaca paper trading. It supports swing and intraday day-trading modes, with dynamic market scanners spotting movers and a portfolio manager aggregating signals into bracket orders with enforced risk limits like daily loss caps and end-of-day flattening. Users get a ready-to-run multi agent llm trading bot that handles everything from data gathering to autonomous execution.

Why is it gaining traction?

Unlike single-model trading bots, this multi-agent trading framework leverages 13 LLM providers (OpenAI, Anthropic, Ollama, etc.) for diverse perspectives, plus zero-cost data fallbacks and overnight AutoResearch that evolves strategies via backtests. Day traders appreciate the 5-min bar analysis, VWAP/RSI signals, and cron automation for 5 daily runs, while swing users get fundamentals and insider trade insights. It's a practical multi agent stock trading platform github devs fork for custom agents without API bills.

Who should use this?

Quant hobbyists scripting automated stock portfolios will find it ideal for testing multi agent llm financial trading workflows on paper accounts. Day traders needing a multi agent trading bot for intraday scans and bracket orders can pipe scanner output directly into analysis pipelines. Python devs exploring langgraph multi agent github setups for ai powered multi agent trading should start here for its Alpaca integration and risk rails.

Verdict

Grab it if you're prototyping multi-agent trading systems—15 stars show it's early, but solid docs and free data make it playable out-of-box despite the 0.8999999761581421% credibility score. Add tests for production; great for rogue trader swarm experiments.

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.