Slippage

What Is Slippage?

Slippage occurs when the price you see when initiating a trade differs from the price you actually receive. In decentralized finance, this happens for two main reasons: the AMM's pricing curve causes price impact proportional to trade size, and other transactions may execute before yours, shifting the pool's reserves and therefore the price.

For example, if you attempt to buy a token at $1.00 but receive it at $1.03, you experienced 3% slippage. On highly liquid pairs like ETH/USDC on Uniswap, slippage on a $10,000 trade is typically under 0.1%. On low-liquidity memecoin pairs, even a $500 trade might produce 5% or more slippage.

How Slippage Works

On AMMs, slippage comes from two sources. First, price impact is the deterministic slippage caused by the AMM formula. In a constant product pool, buying token X reduces its supply in the pool, raising its price. The larger the trade relative to the pool, the greater the price impact. A trade representing 1% of pool reserves produces roughly 2% price impact.

Second, price movement occurs when other trades execute between the time you submit your transaction and when it is confirmed (typically 12 seconds on Ethereum, 400 milliseconds on Solana). If another large buy executes before yours, the token price rises, and your trade executes at the new, higher price.

Traders protect against slippage by setting a slippage tolerance — the maximum acceptable difference from the quoted price. If actual slippage exceeds this threshold, the transaction automatically reverts. Common settings range from 0.5% for stable pairs to 5-15% for volatile memecoins.

Why Slippage Matters

Slippage directly affects trading profitability. A trader buying $1,000 of a token with 5% slippage effectively pays $1,050 for $1,000 worth of tokens — a $50 loss before any price appreciation. For active traders making dozens of trades per day, cumulative slippage costs can exceed hundreds or thousands of dollars.

High slippage tolerance also makes traders vulnerable to sandwich attacks, where MEV bots exploit the gap between the quoted price and the maximum acceptable price to extract profit.

Managing Slippage in Volume Generation

Volume bots must carefully manage slippage to avoid eroding the session budget. OpenLiquid calculates the optimal trade size for each swap based on the current pool depth, ensuring that individual trades produce less than 0.5% price impact. The bot also monitors pool reserves in real time and adjusts trade parameters if liquidity changes during a session. On low-liquidity tokens, the bot uses smaller, more frequent trades to generate target volume without significant slippage costs.