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Trading with PolyOracle AI

Learn how to execute trades based on your market analysis and manage your trading strategy effectively.

Trading Workflow​

1. Analysis to Trade Decision​

After completing market analysis, the agent provides a structured decision:

Decision: BUY YES tokens
Confidence: 0.82 (High)
Recommended Size: $250 USDC
Expected Price: $0.67
Rationale: Strong research consensus supports higher probability
Risk Assessment: Medium - liquid market, good fundamentals

2. Human Confirmation (Default)​

By default, all trades require human approval:

In Web Interface:

  • Review the analysis summary
  • Check the trade parameters
  • Click "Approve Trade" or "Reject Trade"
  • Monitor execution progress

Safety Features:

  • Clear display of trade size and direction
  • Summary of key analysis points
  • Risk warnings for large positions
  • Ability to modify trade size before approval

3. Trade Execution​

Once approved, the agent executes the trade:

  1. Pre-execution Checks:

    • Verify sufficient USDC balance
    • Check current market price
    • Validate order parameters
    • Confirm proxy contract is ready

  2. Order Placement:

    • Places market order on Polymarket CLOB
    • Monitors order status and fills
    • Updates position records
    • Logs execution details

  3. Post-execution:

    • Confirms token receipt
    • Updates portfolio balances
    • Records trade history
    • Calculates realized/unrealized P&L

Trade Types and Strategies​

Market Orders​

When to Use:

  • High-confidence signals
  • Time-sensitive opportunities
  • Liquid markets with tight spreads

Configuration:

market_order = {
    "type": "market",
    "side": "buy",  # or "sell"
    "size": 100,    # USDC amount
    "outcome": "yes" # or "no"
}

Position Sizing Strategies​

Fixed Dollar Amount​

fixed_size = {
    "method": "fixed_amount",
    "amount": 100,  # Always trade $100
    "max_position": 500  # Maximum total position
}

Confidence-Based Sizing​

confidence_sizing = {
    "method": "confidence_based",
    "base_amount": 50,
    "multiplier": 200,  # 200 * confidence
    # Confidence 0.8 = $160 trade
}

Kelly Criterion Sizing​

kelly_sizing = {
    "method": "kelly",
    "bankroll": 1000,
    "edge_estimate": "research_based",
    "max_fraction": 0.25  # Never risk over 25% of bankroll
}

Risk Management Rules​

Position Limits​

risk_limits = {
    "max_single_position": 500,    # Max $500 per market
    "max_total_exposure": 2000,    # Max $2000 total
    "max_positions": 10,           # Max 10 concurrent positions
    "max_correlation": 0.7         # Max 70% correlation between positions
}

Stop-Loss Rules​

stop_loss = {
    "enabled": True,
    "threshold": -0.3,             # Stop if down 30%
    "trailing_stop": True,         # Trail profits
    "min_hold_time": 3600          # Minimum 1 hour hold
}

Advanced Trading Features​

Portfolio Rebalancing​

Automatic Rebalancing:

  • Triggered by new high-confidence signals
  • Reduces overconcentrated positions
  • Maintains target allocation across markets

Manual Rebalancing:

# Via web interface
Click "Portfolio" → "Rebalance" → Review → Execute

# Via API
curl -X POST http://localhost:2024/rebalance \
  -H "Content-Type: application/json" \
  -d '{"target_allocation": "equal_weight"}'

Multi-Market Strategies​

Arbitrage Detection​

arbitrage_config = {
    "min_spread": 0.02,            # 2% minimum spread
    "max_execution_time": 60,      # 60 seconds max
    "related_markets_only": True,  # Only arb related markets
}

Correlation Trading​

correlation_strategy = {
    "base_market": "0x123...",
    "correlated_markets": ["0x456...", "0x789..."],
    "correlation_threshold": 0.8,
    "trade_on_divergence": True
}

Automated Trading (Advanced)​

⚠️ Warning: Automated trading involves significant risk. Start with small amounts and paper trading.

Enable Automated Trading​

# In backend configuration
auto_trading = {
    "enabled": False,  # Set to True when ready
    "min_confidence": 0.8,  # Only trade high-confidence signals
    "max_daily_trades": 5,   # Limit daily activity
    "position_limits": {...} # Include all risk limits
}

Paper Trading Mode​

paper_trading = {
    "enabled": True,
    "starting_balance": 1000,
    "track_performance": True,
    "log_would_be_trades": True
}

Monitoring Your Trades​

Real-Time Monitoring​

Web Interface Dashboard:

  • Current positions and P&L
  • Recent trade history
  • Portfolio allocation
  • Risk metrics

Key Metrics to Watch:

  • Total portfolio value
  • Unrealized P&L by position
  • Win/loss ratio
  • Average holding time
  • Risk-adjusted returns

Trade History Analysis​

Performance Metrics:

Trade Performance Summary:
Total Trades: 25
Win Rate: 68% (17 winners, 8 losers)
Average Win: +$45
Average Loss: -$23
Total P&L: +$321
Max Drawdown: -$78 (5.2%)
Sharpe Ratio: 1.34

Analysis by Market Category:

Politics Markets: 12 trades, +$234 P&L
Economics Markets: 8 trades, +$89 P&L  
Sports Markets: 5 trades, -$2 P&L

Trading Best Practices​

Entry Strategy​

  1. Wait for High Confidence (over 0.7)

    • Better to miss trades than make poor ones
    • Quality over quantity approach
    • Focus on your areas of expertise

  2. Check Market Conditions

    • Sufficient liquidity for your size
    • Reasonable bid-ask spreads (under 3%)
    • Not too close to expiration (under 24 hours)

  3. Position Sizing

    • Start smaller than you think
    • Scale up with experience and success
    • Never risk more than you can afford to lose

Exit Strategy​

  1. Profit Taking

    • Set profit targets (e.g., 20% gain)
    • Consider partial profit taking
    • Don't get greedy with winners

  2. Loss Management

    • Stick to stop-loss levels
    • Cut losses quickly on new negative information
    • Don't average down unless very confident

  3. Time-Based Exits

    • Consider position duration
    • Markets close to resolution may be less predictable
    • Rebalance periodically

Risk Management​

  1. Diversification

    • Don't put all funds in one market
    • Vary market categories and types
    • Consider correlation between positions

  2. Bankroll Management

    • Start with small percentage of total capital
    • Increase position sizes gradually with success
    • Keep some powder dry for opportunities

  3. Emotional Management

    • Let the AI handle analysis, you handle risk
    • Don't override the system based on emotions
    • Take breaks after significant losses

Troubleshooting Trading Issues​

Common Execution Problems​

"Insufficient Balance"

  • Check USDC balance in wallet
  • Account for gas fees (MATIC)
  • Verify funds are on Polygon network

"Order Rejected"

  • Market may have moved significantly
  • Check current bid/ask prices
  • Verify order size is within limits

"Proxy Contract Error"

  • Ensure proxy contract is properly configured
  • Check proxy address in environment variables
  • Verify proxy has necessary approvals

Performance Issues​

Poor Win Rate

  • Increase confidence threshold for trades
  • Focus on markets with better research quality
  • Analyze losing trades for patterns

High Transaction Costs

  • Batch trades when possible
  • Focus on larger position sizes
  • Monitor gas prices and trade timing

Market-Specific Issues​

Low Liquidity Markets

  • Reduce position sizes
  • Use limit orders instead of market orders
  • Consider impact on execution price

Volatile Markets

  • Use smaller position sizes
  • Set tighter stop-losses
  • Consider shorter holding periods

Advanced Features​

API Trading​

Direct API access for custom strategies:

import requests

# Place a trade via API
trade_request = {
    "market_id": "0x123...",
    "side": "buy",
    "outcome": "yes",
    "amount": 100,
    "confidence_required": 0.75
}

response = requests.post(
    "http://localhost:2024/trade",
    json=trade_request
)

Backtesting Strategies​

Test strategies on historical data:

backtest_config = {
    "start_date": "2024-01-01",
    "end_date": "2024-06-01",
    "initial_capital": 1000,
    "strategy": "confidence_based_sizing",
    "min_confidence": 0.7
}

Integration with External Tools​

TradingView Integration:

  • Export trade signals to TradingView
  • Use TradingView alerts for monitoring
  • Track performance against benchmarks

Spreadsheet Export:

  • Export trade history to CSV
  • Analyze performance in Excel/Google Sheets
  • Create custom reporting dashboards

Next Steps​

Once you're comfortable with trading:

  1. Portfolio Management - Use the Portfolio Status API to track positions
  2. Performance Monitoring - Monitor your trades using the dashboard features described in Monitoring Your Trades
  3. Advanced Strategies - Explore the Advanced Trading Features section above

Ready to improve your performance? Review the Trading Best Practices and Risk Management sections to optimize your strategy.