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🎯 Extraction Strategies: DEX Arbitrage

Master the techniques searchers use to profit from price differences

Discover how bots profit from transaction ordering

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Extraction Strategies

MEV extraction requires sophisticated strategies combining market monitoring, rapid execution, and gas optimization. Successful searchers run specialized bots that continuously scan for opportunities, calculate profitability accounting for gas costs, and compete in priority auctions to get transactions included first.

The three main strategies—arbitrage, liquidations, and sandwich attacks—each require different technical infrastructure and capital. Understanding how they work helps you both extract MEV yourself and protect against being exploited.

Interactive: Strategy Simulator

Watch how different MEV strategies execute step-by-step with real profit calculations.

1

Detect Price Gap

ETH is $2000 on Uniswap, $2010 on SushiSwap

2

Calculate Gas Cost

Swap costs ~150k gas at 30 gwei = $9

3

Execute Buy

Buy 10 ETH on Uniswap for $20,000

4

Execute Sell

Sell 10 ETH on SushiSwap for $20,100

$100
profit
5

Net Profit

$100 revenue - $9 gas = $91 profit

$91
profit

Strategy Requirements

DEX Arbitrage Requirements

Technical Requirements

  • ✓Flash loan or capital
  • ✓Low latency execution
  • ✓Gas optimization
  • ✓Multi-DEX monitoring

Risk Factors

  • ⚠Price slippage
  • ⚠Failed transactions
  • ⚠Gas wars
  • ⚠MEV competition

Advanced Techniques

⚡ Flash Loans

Borrow millions instantly with no collateral, execute arbitrage, repay in same transaction. Enables capital-free MEV extraction.

Example: Borrow $1M, arbitrage $10k profit, repay + 0.09% fee

🔗 Multi-Hop Arbitrage

Route through multiple DEXes and token pairs to find circular arbitrage opportunities: ETH → USDC → DAI → ETH (profit).

Example: Uniswap → Curve → Balancer → back to start

📦 Bundles

Group multiple transactions that must execute atomically. If one fails, all revert. No gas cost for failed bundles via Flashbots.

Example: Sandwich attack as bundle: front-run + victim tx + back-run

🎯 Statistical Arbitrage

Use machine learning to predict profitable trades based on historical patterns. Back-run trades without front-running (ethical MEV).

Example: Detect correlated price movements, trade ahead of trend

💡 Pro Tips

  • •Gas optimization is critical—optimize every opcode, use assembly when needed
  • •Use Flashbots Protect to submit bundles—failed txs don't cost gas
  • •Monitor multiple chains—arbitrage opportunities exist on L2s with less competition
  • •Build relationships with validators—private order flow = competitive advantage
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