We just released an open source project for agent swarm based stock trading simulations built and tested by heyneo.so - Fully autonomous ML engineering agent.
The agent swarm self coordinates with each other via an asynchronous message bus.
There are around 10 agents with distinct roles:
- 3 Analyst Agents → Generate BUY/SELL signals (SMA crossovers, volume trends)
- 4 Trader Agents → Execute trades, manage $250K portfolios each
- 2 Risk Managers → Validate orders, enforce stop-loss rules
- 1 Reporter Agent → Aggregate P&L and generate reports
The simulation consists of capital allocation, risk checks like stop-losses and order blocking, and reporting baked into the flow. The system backtests over ~250 trading days, starts with a fixed $1M capital, and logs things like drawdown, blocked orders, and approval rates.
The agent swarm self coordinates with each other via an asynchronous message bus.
There are around 10 agents with distinct roles: - 3 Analyst Agents → Generate BUY/SELL signals (SMA crossovers, volume trends) - 4 Trader Agents → Execute trades, manage $250K portfolios each - 2 Risk Managers → Validate orders, enforce stop-loss rules - 1 Reporter Agent → Aggregate P&L and generate reports
The simulation consists of capital allocation, risk checks like stop-losses and order blocking, and reporting baked into the flow. The system backtests over ~250 trading days, starts with a fixed $1M capital, and logs things like drawdown, blocked orders, and approval rates.
Repo here if anyone wants to dig into the implementation or poke holes in the design: https://github.com/dakshjain-1616/Stock-trading-Agent-Swarm-...
Extend the project in your VS Code IDE with Neo: https://marketplace.visualstudio.com/items?itemName=NeoResea...