Multi-Agent AI Trading Swarm with Cross-Market Intelligence

Swarm Labs

Multi-Agent AI Trading Swarm with Cross-Market Intelligence

Overview

Swarm Labs is a sophisticated multi-agent trading system where specialized AI agents monitor cryptocurrency futures, forex, and stock futures markets simultaneously. Agents consult each other on optimal strategies, report intelligence to OpenClaw (the central orchestrator), and execute trades through integrated exchange APIs.

Architecture

┌─────────────────────────────────────────────────────────────────┐  
│                         OPENCLAW (CEO)                           │  
│              Central Decision Engine & Orchestrator              │  
└──────────────────────────┬──────────────────────────────────────┘  
                           │  
          ┌────────────────┼────────────────┐  
          │                │                │  
┌─────────▼─────────┐ ┌────▼─────┐ ┌───────▼────────┐  
│   CRYPTO AGENT    │ │  FOREX   │ │ FUTURES AGENT  │  
│  (Binance/Bybit)  │ │  (OANDA) │ │    (IBKR)      │  
└─────────┬─────────┘ └────┬─────┘ └───────┬────────┘  
          │                │                │  
          └────────────────┼────────────────┘  
                           │  
          ┌────────────────┼────────────────┐  
          │                │                │  
┌─────────▼─────────┐ ┌────▼─────┐ ┌───────▼────────┐  
│ STRATEGY EVALUATOR│ │   RISK   │ │  REDIS QUEUE   │  
│  (8 Strategies)   │ │ MANAGER  │ │  (Message Bus) │  
└───────────────────┘ └──────────┘ └────────────────┘  

Features

Multi-Market Coverage

• Crypto Futures: BTC, ETH perpetuals via Binance & Bybit
• Forex: Major and minor pairs via OANDA
• Stock Futures: ES, NQ, YM via Interactive Brokers

Swarm Intelligence

• 8 concurrent trading strategies evaluated in real-time
• Weighted consensus mechanism with confidence scoring
• Cross-market correlation detection
• Real-time strategy adaptation based on market conditions

Risk Management

• Position sizing based on volatility
• Dynamic stop-loss and take-profit
• Maximum drawdown protection
• Kill switches and circuit breakers
• Portfolio-level risk aggregation

Execution Layer

• Multi-exchange integration with unified API
• Order routing optimization
• Position tracking across all markets
• Error handling and retry logic

Communication

• Discord integration for real-time alerts
• GitHub logging for decision audit trail
• Redis pub/sub for agent coordination
• Structured JSON logging

Trading Strategies

1. Momentum/Trend Following - ATR and moving average confirmation
2. Mean Reversion - Fade overextended moves
3. Scalping - High-frequency during liquidity windows
4. News/Sentiment - Real-time news analysis
5. Volatility Breakout - Bollinger Band squeeze detection
6. Grid Trading - Range-bound market strategies
7. Arbitrage - Cross-exchange and cross-market opportunities
8. Session-Based - Asia/London/NY session optimizations

Quick Start

BASH
# Clone repository  
git clone https://github.com/HaroonPashaaa/swarm-labs.git  
cd swarm-labs

# Install dependencies  
pip install -r requirements.txt

# Configure environment  
cp .env.example .env  
# Edit .env with your API keys

# Start infrastructure  
docker-compose up -d

# Initialize database  
python scripts/init_db.py

# Run swarm  
python -m openclaw.core  

Documentation

• Architecture - System design and data flow
• API Reference - Exchange integrations and methods
• Strategies - Trading strategy implementations
• Risk Management - Risk controls and safety measures
• Deployment - Production deployment guide

Repository Structure

swarm-labs/  
├── openclaw/          # Central orchestrator  
├── agents/            # Market-specific agents  
├── strategies/        # Trading strategies  
├── exchanges/         # Exchange integrations  
├── core/              # Shared infrastructure  
├── data/              # Data handling  
├── tests/             # Test suite  
└── docs/              # Documentation  

Safety & Disclaimer

This system is designed for paper trading by default. Real money trading requires:

• Extensive backtesting
• Understanding of all risk parameters
• Acceptance of potential losses
• Compliance with local regulations

Never trade with money you cannot afford to lose.

License

MIT License - See LICENSE for details.

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Built with precision by the Swarm Labs team.

Source: https://github.com/HaroonPashaaa/swarm-labs