Polymarket Arbitrage Cn

Polymarket 套利 | Polymarket Arbitrage. 预测市场套利机会 | Prediction market arbitrage opportunities. 自动发现价格差异 | Auto discover price differences. 触发词：Polymarket、预测市场、套利、arbitrage.

Guohongbin@guohongbin-git

Install

openclaw skills install @guohongbin-git/polymarket-arbitrage-cn

Polymarket Arbitrage

Find and execute arbitrage opportunities on Polymarket prediction markets.

Quick Start

1. Paper Trading (Recommended First Step)

Run a single scan to see current opportunities:

bash

cd skills/polymarket-arbitrage
pip install requests beautifulsoup4
python scripts/monitor.py --once --min-edge 3.0

View results in polymarket_data/arbs.json

2. Continuous Monitoring

Monitor every 5 minutes and alert on new opportunities:

bash

python scripts/monitor.py --interval 300 --min-edge 3.0

Stop with Ctrl+C

3. Understanding Results

Each detected arbitrage includes:

net_profit_pct: Edge after 2% fees
risk_score: 0-100, lower is better
volume: Market liquidity
action: What to do (buy/sell all outcomes)

Good opportunities:

Net profit: 3-5%+
Risk score: <50
Volume: $1M+
Type: math_arb_buy (safer)

Arbitrage Types Detected

Math Arbitrage (Primary Focus)

Type A: Buy All Outcomes (prob sum < 100%)

Safest type
Guaranteed profit if executable
Example: 48% + 45% = 93% → 7% edge, ~5% net after fees

Type B: Sell All Outcomes (prob sum > 100%)

Riskier (requires liquidity)
Need capital to collateralize
Avoid until experienced

See references/arbitrage_types.md for detailed examples and strategies.

Cross-Market Arbitrage

Same event priced differently across markets (not yet implemented - requires semantic matching).

Orderbook Arbitrage

Requires real-time orderbook data (homepage shows midpoints, not executable prices).

Scripts

fetch_markets.py

Scrape Polymarket homepage for active markets.

bash

python scripts/fetch_markets.py --output markets.json --min-volume 50000

Returns JSON with market probabilities, volumes, and metadata.

detect_arbitrage.py

Analyze markets for arbitrage opportunities.

bash

python scripts/detect_arbitrage.py markets.json --min-edge 3.0 --output arbs.json

Accounts for:

2% taker fees (per leg)
Multi-outcome fee multiplication
Risk scoring

monitor.py

Continuous monitoring with alerting.

bash

python scripts/monitor.py --interval 300 --min-edge 3.0 [--alert-webhook URL]

Features:

Fetches markets every interval
Detects arbitrage
Alerts on NEW opportunities only (deduplicates)
Saves state to polymarket_data/

Workflow Phases

Phase 1: Paper Trading (1-2 weeks)

Goal: Understand opportunity frequency and quality

Run monitor 2-3x per day
Log opportunities in spreadsheet
Check if they're still available when you look
Calculate what profit would have been

Decision point: If seeing 3-5 good opportunities per week, proceed to Phase 2.

Phase 2: Micro Testing ($50-100 CAD)

Goal: Learn platform mechanics

Create Polymarket account
Deposit $50-100 in USDC
Manual trades only (no automation)
Max $5-10 per opportunity
Track every trade in spreadsheet

Decision point: If profitable after 20+ trades, proceed to Phase 3.

Phase 3: Scale Up ($500 CAD)

Goal: Increase position sizes

Increase bankroll to $500
Max 5% per trade ($25)
Still manual execution
Implement strict risk management

Phase 4: Automation (Future)

Requires:

Wallet integration (private key management)
Polymarket API or browser automation
Execution logic
Monitoring infrastructure

Only consider after consistently profitable manual trading.

See references/getting_started.md for detailed setup instructions.

Risk Management

Critical Rules

Maximum position size: 5% of bankroll per opportunity
Minimum edge: 3% net (after fees)
Daily loss limit: 10% of bankroll
Focus on buy arbs: Avoid sell-side until experienced

Red Flags

Edge >10% (likely stale data)
Volume <$100k (liquidity risk)
Probabilities recently updated (arb might close)
Sell-side arbs (capital + liquidity requirements)

Fee Structure

Polymarket charges:

Maker fee: 0%
Taker fee: 2%

Conservative assumption: 2% per leg (assume taker)

Breakeven calculation:

2-outcome market: 2% × 2 = 4% gross edge needed
3-outcome market: 2% × 3 = 6% gross edge needed
N-outcome market: 2% × N gross edge needed

Target: 3-5% NET profit (after fees)

Common Issues

"High edge but disappeared"

Homepage probabilities are stale or represent midpoints, not executable prices. This is normal. Real arbs disappear in seconds.

"Can't execute at displayed price"

Liquidity issue. Low-volume markets show misleading probabilities. Stick to $1M+ volume markets.

"Edge is too small after fees"

Increase --min-edge threshold. Try 4-5% for more conservative filtering.

Files and Data

All monitoring data stored in ./polymarket_data/:

markets.json - Latest market scan
arbs.json - Detected opportunities
alert_state.json - Deduplication state (which arbs already alerted)

Advanced Topics

Telegram Integration (Future)

Pass webhook URL to monitor script for alerts:

bash

python scripts/monitor.py --alert-webhook "https://api.telegram.org/bot<token>/sendMessage?chat_id=<id>"

Position Sizing

For a 2-outcome math arb with probabilities p₁ and p₂ where p₁ + p₂ < 100%:

Optimal allocation:

Bet on outcome 1: (100% / p₁) / [(100%/p₁) + (100%/p₂)] of capital
Bet on outcome 2: (100% / p₂) / [(100%/p₁) + (100%/p₂)] of capital

This ensures equal profit regardless of which outcome wins.

Simplified rule: For small edges, split capital evenly across outcomes.

Execution Speed

Arbs disappear fast. If planning automation:

Use websocket connections (not polling)
Place limit orders simultaneously
Have capital pre-deposited
Monitor gas fees on Polygon

Resources

Polymarket: https://polymarket.com
Documentation: https://docs.polymarket.com
API (if available): Check Polymarket docs
Community: Polymarket Discord

Support

For skill issues:

Check references/arbitrage_types.md for strategy details
Check references/getting_started.md for setup help
Review output files in polymarket_data/
Ensure dependencies installed: pip install requests beautifulsoup4