Slippage: Definition, Causes, and How to Minimise It in Crypto Trading

Definition

Slippage is the difference between the expected price of a trade and the actual price at which the trade executes. It occurs when market conditions change between the time a trade is initiated and the time it is filled, or when the trade is large enough relative to available liquidity that it moves through multiple price levels in the order book or significantly impacts the pricing curve of an automated market maker.

Slippage is a fundamental execution cost in digital asset trading, and managing it effectively is critical for both retail and institutional investors.

Types of Slippage

Price Slippage

Price slippage occurs when the market price moves between the time a trader views a price and the time their order is executed. In the fast-moving, 24/7 digital asset market, prices can change significantly in the seconds or milliseconds between order submission and execution.

Size Slippage

Size slippage — also called market impact — occurs when a trade is large enough to consume multiple price levels in the order book or significantly shift the pricing curve in a liquidity pool. The first units of the trade execute at favourable prices, but subsequent units execute at progressively worse prices as available liquidity is consumed.

Positive Slippage

While slippage is typically discussed as a cost, positive slippage can occur when the market moves favourably during order execution. A buy order that fills at a lower price than expected, or a sell order that fills at a higher price, benefits from positive slippage.

Causes of Slippage

Low Liquidity

Assets with thin order books or shallow liquidity pools are more susceptible to slippage. With limited liquidity at each price level, even moderate-sized orders can move through multiple price levels, resulting in significant slippage.

High Volatility

During periods of rapid price movement, the market price may change substantially between order submission and execution. Volatility-driven slippage is particularly acute during news events, market stress, and periods of extreme trading activity.

Large Order Size

The relationship between order size and slippage is non-linear. Doubling the order size may more than double the slippage, as liquidity tends to be concentrated near the current price and thins out at more distant price levels.

Network Congestion

In decentralised trading, blockchain network congestion can delay transaction confirmation, increasing the time between order submission and execution. During this delay, pool conditions may change significantly, resulting in greater slippage.

MEV (Maximal Extractable Value)

In DeFi trading, transactions in the public mempool can be observed and front-run by MEV extractors. These actors insert their own transactions ahead of the user’s trade, pushing the price unfavourably before the user’s order executes. This sandwich attack creates artificial slippage that benefits the MEV extractor at the trader’s expense.

Measuring Slippage

Absolute Slippage

Absolute slippage is the difference in price terms:

Absolute slippage = Execution price - Expected price

For a buy order, positive values indicate the trader paid more than expected. For a sell order, positive values indicate the trader received less than expected.

Percentage Slippage

Percentage slippage expresses the cost as a proportion of the expected price:

Percentage slippage = (Execution price - Expected price) / Expected price * 100

Percentage slippage allows comparison across assets with different price levels and facilitates transaction cost analysis.

Basis Points

In institutional contexts, slippage is often expressed in basis points (bps), where one basis point equals 0.01%. A trade with 50 basis points of slippage executed at a price 0.5% worse than the expected price.

Slippage Tolerance

DEX Slippage Settings

When trading on decentralised exchanges, users set a slippage tolerance — the maximum acceptable slippage before the transaction is automatically reverted. Common settings range from 0.1% to 1% for standard swaps, with higher tolerances sometimes needed for low-liquidity tokens.

Setting slippage tolerance involves a trade-off:

• Too low — Transactions may fail frequently, particularly during volatile markets, as the price moves beyond the tolerance before the transaction is confirmed
• Too high — Traders accept potentially significant execution costs, and high tolerance settings make transactions more vulnerable to sandwich attacks

Exchange Stop-Limit Orders

On centralised exchanges, stop-limit orders provide slippage control by setting a maximum price at which a triggered stop order will execute. If the market moves beyond the limit price, the order remains unfilled rather than executing at an unfavourable price.

Strategies to Minimise Slippage

Trade Sizing

Breaking large orders into smaller pieces reduces per-trade slippage by consuming less depth at each execution. OTC trading is often preferable for institutional-sized orders specifically because it avoids the slippage associated with large exchange or DEX orders.

Venue Selection

Different exchanges and liquidity pools offer different levels of liquidity for the same asset. Smart order routing systems analyse available liquidity across venues and route orders to minimise total slippage.

Limit Orders

Using limit orders on centralised exchanges guarantees a maximum execution price, eliminating slippage at the cost of execution certainty. The order may not fill if the market does not reach the limit price.

Timing

Avoiding trade execution during periods of extreme volatility, low liquidity (such as weekends for fiat-paired markets), or major news events can reduce slippage risk.

Aggregation

DEX aggregators split a single swap across multiple liquidity pools and protocols to find the path with the lowest total slippage. These tools are particularly valuable for larger DeFi trades.

Private Transactions

Some DeFi protocols offer private or protected transaction submission that shields trades from MEV extraction, reducing the artificial slippage caused by sandwich attacks.

Slippage in Institutional Context

For institutional investors, slippage is a major component of total transaction cost and directly impacts portfolio returns. OTC desks exist largely to mitigate slippage for institutional-sized orders, and sophisticated execution algorithms are designed to minimise market impact across fragmented venues.

Transaction cost analysis (TCA) — measuring and reporting execution quality including slippage — is increasingly expected by institutional investors and may be required by regulations such as best execution obligations for regulated fund managers.

Donovan Vanderbilt is a contributing editor at ZUG TRADING, a digital asset trading and exchanges intelligence publication by The Vanderbilt Portfolio AG, Zurich. His analysis covers institutional market structure, OTC liquidity, and regulatory developments across Swiss and global digital asset markets.