MEV Strategy Evaluation Guide

Who This Guide Is For

This guide is for operators, developers, and reviewers who need a reproducible way to evaluate MEV automation before any controlled live execution.

• Traders who want to automate MEV strategies with guardrails
• Developers building or optimizing MEV bots
• Security and risk reviewers checking assumptions, limits, and evidence

MEV Strategies Overview

MEV describes value associated with transaction inclusion, exclusion, or ordering. A strategy may identify a candidate, but only settled transactions and a complete cost ledger can establish an outcome.

How FRB Supports MEV Strategies

FRB is a local Windows execution assistant. The operator configures data sources, strategies, providers, and risk controls:

• User-selected RPC and WebSocket endpoints
• Configurable observation and candidate filters
• Simulation and bounded execution controls
• Separate EVM and Solana workflows with local signing

1. Arbitrage Trading Strategy

An arbitrage hypothesis compares executable quotes across venues after accounting for fees, price impact, state changes, and transaction failure. A displayed price difference alone is not an outcome.

How It Works

1. FRB monitors prices across multiple DEXs (Uniswap, Sushiswap, Curve, etc.)
2. When a price difference is detected that exceeds gas + slippage costs, it flags the opportunity
3. A transaction bundle is created to buy on the cheaper DEX and sell on the more expensive one
4. The configured route is submitted only after simulation and cost limits pass

Best Practices

• Set realistic profit thresholds accounting for gas costs and slippage
• Use FRB's gas calculator to optimize transaction costs
• Start with liquid pairs (ETH/USDC, BTC/ETH) before moving to smaller tokens
• Enable simulation mode to test strategies without risking real funds
• Measure end-to-end timing from defined events in your own environment

Example (Pseudo-code)

// Pseudo-code example
if (priceDEX1 < priceDEX2 && profit > gasCost + slippage) {
  buyOnDEX1(amount);
  sellOnDEX2(amount);
  profit = (priceDEX2 - priceDEX1) * amount - gasCost;
}

2. Liquidation Strategy

Liquidation automation monitors documented protocol health conditions and constructs a permitted liquidation transaction when the current contract state allows it.

How It Works

1. Continuously scan lending protocols for positions approaching liquidation threshold
2. Calculate liquidation bonus vs. gas costs to determine profitability
3. Execute liquidation transactions with high gas priority
4. Confirm the settled transaction and reconcile repayment, fees, inventory, and any protocol incentive

Best Practices

• Use each protocol's current liquidation conditions and oracle documentation
• Pre-approve tokens to save gas on execution
• Use flash loans for capital-efficient liquidations
• Set up monitoring for multiple protocols simultaneously
• Keep adequate collateral in your wallet to execute liquidations quickly

3. Back-Running Strategy

A backrun is ordered after another transaction and reacts to the resulting state. Its effect and permissibility depend on the route, protocol, and order-flow policy.

How It Works

1. Identify large transactions that will create significant price impact
2. Calculate the expected price change after the target transaction
3. Submit a transaction immediately after the target with slightly higher gas
4. Confirm the resulting state and reconcile all costs on-chain

Best Practices

• Define candidate thresholds from measured liquidity and cost data
• Use private mempool channels to avoid competition
• Calculate precise entry and exit points using real-time liquidity data
• Set tight profit thresholds to avoid false signals
• Monitor multiple DEXs for the best execution price

4. Sandwich-Risk Analysis

Sandwiching worsens another user's execution by placing transactions around the target swap. This section treats it as a risk to detect and mitigate, not an implementation strategy.

How It Works

1. Identify swaps whose slippage and public visibility create exposure
2. Compare public and documented private submission behavior
3. Model price impact and ordering risk in simulation
4. Apply slippage, route, and cancellation controls without targeting another user

Ethical Considerations

Warning: Sandwich attacks directly harm users by worsening execution. FRB documentation does not recommend deploying them. Use simulations to understand exposure and validate defensive routing.

5. Token-Launch Automation Review

Token-launch automation observes new on-chain state and may construct a bounded transaction. It cannot establish token quality, future liquidity, or profit.

How It Works

1. Monitor blockchain events for new token deployments and liquidity additions
2. Analyze token contract for honeypot patterns and rug pull indicators
3. Simulate the exact transaction against a declared state reference
4. Enforce explicit size, slippage, fee, tip, and retry caps
5. Verify the resulting signature and balance changes on-chain

Best Practices

• Use a dedicated wallet with a deliberately limited balance
• Treat filters as rejection controls, not proof that a token is safe
• Stop when state, provider, simulation, or confirmation evidence is incomplete
• Avoid tokens with suspicious contract patterns or anonymous teams
• Remain in simulation until the workflow and stop conditions are reproducible

Implementation Guide: Getting Started with FRB

Risk Management for MEV Strategies

MEV strategies carry significant risks. Implement these controls:

• Gas cost risk: Always calculate gas costs before executing. Failed transactions still cost gas.
• Slippage risk: Set appropriate slippage limits. Too tight = failed transactions. Too loose = poor execution.
• Competition risk: Other bots compete for the same opportunities. Use private mempool channels to reduce competition.
• Smart contract risk: Interacting with DeFi protocols carries smart contract risk. Only use audited protocols.
• Capital risk: Start with small amounts. Never risk more than you can afford to lose.
• Regulatory risk: MEV strategies may face increased regulatory scrutiny. Stay informed about regulatory developments in your jurisdiction.

Optimization Tips

• Use FRB's WSS latency test to find the fastest RPC endpoint for your region
• Implement dynamic gas pricing based on network congestion
• Use batch transactions where possible to reduce per-trade gas costs
• Report submitted, included, rejected, expired, and failed attempts separately
• Regularly update your strategy parameters based on changing market conditions
• Keep adequate ETH reserves for gas costs during high-activity periods

Useful FRB Tools for MEV

• Gas Calculator - Document a bounded fee policy for a declared transaction
• Profitability Calculator Guide - Understand how to use FRB's profit calculation tools
• WSS Latency Test - Find the lowest-latency RPC endpoint for your location
• System Status - Monitor FRB infrastructure health before starting a session

Next Steps

Ready to implement these strategies? Here's where to start:

• Flashbots Tutorial - Learn how to use private mempools to protect your transactions
• MEV 101 - Get the foundational knowledge before diving into strategies
• FRB App - Access the live bot interface and start in simulation mode
• Ethereum MEV Ecosystem - Understand the broader MEV landscape on Ethereum

Applying This Guide

Before executing any live trades, complete the MEV 101 curriculum and run a declared simulation window. Understanding why a candidate passes or fails is as important as the strategy hypothesis.

1. Pick one narrowly defined strategy and document its invalidation rules
2. Run FRB in simulation for a declared observation window
3. Review your simulation results, then install FRB to move to live execution with conservative risk controls