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-...
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