Web3 Beginner Series: Understand MEV Bots in Five Minutes - You Can Write One Too

This article is solely for technical sharing and does not constitute any investment advice.

In the context of the increasing popularity of blockchain technology, the cryptocurrency trading ecosystem is expanding rapidly. Decentralized exchanges (DEX) have become significant platforms for digital asset trading due to their advantages of decentralization and transparency. As the market matures, various automated trading tools have emerged. MEV (Maximal Extractable Value) bots are automated programs used to execute strategies and other trading tactics on blockchain networks. They extract maximum value by rearranging, inserting, or delaying blockchain transactions. This article will delve into the definition, principles, implementation methods, key factors, and optimization directions of sandwich bots.

As technology progresses and market demands evolve, sandwich bots have also diversified into various types to adapt to different trading environments and strategy needs. Here are a few common types of sandwich bots:

1. Sandwich Bots
   These bots listen to large orders in the transaction pool and submit transactions with higher gas fees before these orders are officially on-chain, allowing them to execute trades before the target user. This strategy involves inserting transactions before and after the target transaction (front-running and back-running) to manipulate prices and profit from the difference.
2. Arbitrage Bots
   This type of sandwich bot focuses on profiting from price discrepancies between different DEXs. The bot buys an asset at a low price on one exchange and then sells it at a higher price on another exchange, thus securing a profit. This strategy often requires the bot to quickly identify price movements between different exchanges and execute trades rapidly.
3. New Token Release Bots
   These bots focus on price fluctuations during new token launches. In the initial stages of a new token listing on a DEX, prices tend to be unstable and highly volatile. The sandwich bot quickly buys when the token is first listed and sells after the price increases to capture the difference. This type of bot requires close attention to the release dynamics of new projects and the ability to place orders quickly.
4. Liquidity Pool Arbitrage Bots
   These bots conduct arbitrage by moving assets between different liquidity pools. They look for price discrepancies in different pools and perform liquidity addition and withdrawal operations to achieve profits. This requires the bot to efficiently manage liquidity and respond rapidly to price changes within the pools.
5. Flash Loan Arbitrage Bots
   Flash loan arbitrage bots utilize the features of flash loans to trade. Flash loans allow users to borrow large amounts of funds in one transaction without collateral. Bots can use these funds to manipulate market prices in a short time for arbitrage. For example, they might use a flash loan to drive up prices in one pool and profit from another.
6. Triangle Arbitrage Bots
   Triangle arbitrage involves trading among three different token pairs to take advantage of exchange rate discrepancies and generate profits. For example, trading A/B, B/C, and then C/A in a loop. This type of bot requires complex calculations and rapid trade execution capabilities.

This article will primarily analyze sandwich bots Sangwich Bots .

I. Sandwich Bots

A sandwich bot is an automated trading tool designed for profiting through front-running transactions on decentralized exchanges. It captures on-chain trading opportunities swiftly, executing trades before or after the target transaction to earn a spread. The core of sandwich bots lies in effectively and quickly securing a trading edge.

II. Principles of Sandwich Bots

The profit operations of sandwich bots are based on the following fundamental principles:

1. Front-Running: Before other users submit buy orders that have not yet been packed into a block by miners, the bot buys the target token at a lower price. When the user's order is executed and drives up the price, the bot quickly sells to capture the price difference.
2. Back-Running: Before other users sell their tokens, the bot sells at a higher price first. When the user's sell order drives down the price, the bot repurchases at a lower price, thus realizing profits.

The so-called "sandwich" refers to sandwiching other trading users to earn the price difference. The success of sandwich bots relies on the precise timing of trades and the high priority of trade execution.

III. Implementation Approach

1. Real-Time Trade Monitoring:

• Use WebSocket to connect to blockchain nodes for real-time monitoring of unconfirmed transactions.
• Trade Filtering: Filter target transactions by matching the transaction.to or transaction.from fields to identify those related to the target DEX.

2. Filtering and Exclusion:

• Filter out trades unrelated to the strategy and transactions from the bot’s own address to prevent self-trade loops.

3. Dynamic Gas Price Adjustment:

• Manually set a high gas price so that miners prioritize the bot's transactions to execute before regular users.

4. Transaction Data Decoding:

• Use smart contract interfaces (like the Interface in ethers.js) to decode transaction data and determine the tokens and amounts involved.
• Based on the decoded information, choose the appropriate contract call methods, such as swapExactETHForTokens or swapTokensForExactTokens.

IV. Code Approach

Utilize the websocket service provided by ZAN Node service, and you can find a complete tutorial in this document (https://docs.zan.top/docs/quick-start-guide). The script will be implemented using ethers.js.

1. Create a listening websocket service.

const ZAN_WSS_URL = `wss://api.zan.top/node/ws/v1/eth/mainnet/${YOUR_KEY}`
const ZANWssProvider = new ethers.providers.WebSocketProvider(ZAN_WSS_URL);
ZANWssProvider.on("pending", (tx) => {
  // TODO
})

2. Filter those transactions.

ZANWssProvider.on("pending", (tx) => { 
  if (transaction && transaction.to && transaction.to.toLowerCase() === ROUTER.toLowerCase() && transaction.from !== blackAddress) {
		// TODO
	}
})

3. Implement a method to determine transaction direction and manually set gas price.

function calculate_gas_price(action, amount) {
  if (action === "buy") {
    return amount.add(100000000) // 0.1 Gwei
  } else {
    return amount.sub(100000000) // 0.1 Gwei
  }
}

4. Decode transaction methods and call functions.

const iface = new ethers.utils.Interface(abi)
const result = iface.decodeFunctionData('swapExactETHForTokens', transaction.data)

V. Key Determinants

The effectiveness and success of sandwich bots are closely related to various factors:

1. Transaction Speed:

• Network latency and node response time directly impact the bot’s reaction speed. Using high-performance node services (like ZAN, Infura, Alchemy) can reduce delays; ZAN also offers support for dedicated nodes.

2. Gas Fees:

• Gas fees are an important consideration when seizing transaction priority. Excessively high gas fees can eat into profits, so a balance between speed and cost must be found.

3. Market Liquidity:

• High liquidity helps facilitate the quick execution of large trades without significantly affecting market prices. Insufficient liquidity may lead to increased slippage or trade failures.

4. Contract Security:

• The security of the target contract directly relates to the operational risks of the strategy. The bot must have basic verification capabilities of the contract code to avoid being exploited by malicious contracts. ZAN’s audit capabilities can be used for risk assessment of target contracts (https://zan.top/home/ai-scan).

5. Competitive Environment:

• There may be multiple sandwich bots in the market competing for profitable opportunities. Intense competition may affect the success rate and profits of trades.

Conclusion

MEV bots provide an efficient solution for arbitrage in decentralized exchanges. Through real-time analysis and rapid execution, they can gain an edge in the market. However, sandwich bots also face challenges of high competition and substantial risks. Investors must comprehensively consider technical implementation, risk control, and market strategy to remain competitive in the ever-changing cryptocurrency markets. In the future, with the advancement of technology and the expansion of the DeFi ecosystem, sandwich bots are expected to leverage their potential in more areas, creating more value for users.