Whether you’re a seasoned trader or a beginner, slippage can quietly change your fill price, which affects risk, costs, and outcomes.
In crypto, slippage occurs when your expected price is different from the price your order executes at, often due to fast market moves or limited liquidity.
In this article, you'll learn what causes slippage, how it differs across platforms, how to calculate it, and how to reduce it with practical settings and strategies.
Key Takeaways
Slippage is the gap between the expected price and the executed price, and it can be positive or negative.
Volatility, liquidity, order size, and transaction delays are the most common drivers of slippage.
You can reduce slippage with limit orders, better timing, smaller trade sizing, and thoughtful slippage tolerance settings.
Types of Slippage
Positive Slippage – When It Works in Your Favor
Positive slippage means you execute at a better price than you expected at the time you submitted the trade. You receive more tokens than quoted or pay less than anticipated because the market moved in your favor.
This can happen on both centralized exchanges (CEXs) and decentralized exchanges (DEXs), especially when prices are changing quickly. It is still slippage, even if it benefits you, because the execution differs from the initial quote.
Negative Slippage – Risks to Your Trades
Negative slippage means you execute at a worse price than expected, such as paying more for a buy or receiving less on a sale. This is the slippage most traders notice because it directly reduces the value of the trade.
Negative slippage is most visible when you use market orders, trade illiquid pairs, or trade during sharp moves. The delay between click and fill can be enough for prices to change.
Price vs Liquidity Slippage – Different Impacts
Price slippage is driven by the market price moving while your order is being executed. Fast volatility can move the quote before the exchange or the network finalizes your fill.
Liquidity slippage is driven by limited depth at the current price, so the trade “walks the book” or shifts a pool price. You consume available liquidity tiers and end up filling across multiple prices instead of one.
Causes of Slippage in Cryptocurrency Trading
Market Volatility and Rapid Price Fluctuations
When prices move quickly, the quoted price you see may already be stale by the time your order reaches the matching engine (CEX) or the network’s transaction queue/validator pipeline (DEX). Volatility creates timing risk between submission and execution.
This is why slippage often spikes around major news, macro events, or sudden liquidations. A “normal” market can change in seconds, even for large-cap assets.
Low Market Liquidity and Order Book Depth
Liquidity is the ability to buy or sell without moving the price too much. Shallow order books amplify slippage because there are fewer resting orders near the current price.
On a DEX, the same idea appears as “thin” liquidity pools, where a swap meaningfully changes the pool ratio. Limited pool reserves increase price impact, which shows up as slippage for the trader.
Large Order Sizes and Their Effects
A large order can cause slippage even in calm conditions because it consumes liquidity at multiple price levels. Trade size relative to liquidity matters more than the absolute size of the trade.
On AMM-based DEXs, the pricing rule means bigger trades push the pool price further along the curve. Large swaps move the price because the pool must maintain its invariant, meaning reserves update to keep the AMM’s formula balanced (for example, keeping the product of the two token reserves constant).
Network Congestion and Transaction Delays
Even if you submit a trade instantly, settlement can still take time, especially for onchain swaps. Transaction delays widen the window in which prices can move before your trade finalizes.
For example, on Proof of Stake networks, block space is still finite, so high demand can slow confirmations or raise fees. Congestion increases execution uncertainty because the market can drift while you wait.
How Slippage Manifests on Different Platforms
Centralized Exchanges (CEXs) – Order Books and Limit Orders
On a CEX, your trade executes against an order book, which is a list of bids and asks at different prices. Market orders prioritize execution, so they can fill across multiple levels if the top of the book is thin.
Limit orders let you set the worst price you will accept, which can reduce negative slippage. A limit order controls your price but can also fail to fill if the market moves away.
Some exchanges also add protections that reject market orders when the spread is very wide. Kraken’s Exchange Trading Rules state that Market Price Protection can reject market orders when the bid/ask spread is unusually wide (typically 2.5-20% depending on the pair).
Decentralized Exchanges (DEXs) – AMMs, Liquidity Pools, and Tolerance Settings
Many DEXs use automated market makers (AMMs) instead of order books. AMMs price trades by formulas, and Uniswap v2-style pools use a constant product relationship that adjusts price as the pool balances change.
Because the pool price moves as your trade size increases, you will usually see a “price impact” estimate before confirming. Price impact is not the same as slippage, but both can reduce your final output.
DEX interfaces also include a slippage tolerance setting that defines how far execution can deviate before the swap fails. As of September 2025, typical slippage tolerance defaults are often between 0.1% and 5%, depending on conditions and swap size.
Slippage Tolerance and Risk Management
Setting the Right Slippage Tolerance
A reasonable tolerance depends on liquidity, volatility, and whether the asset is widely traded. Higher volatility pairs need more buffer because the price can move before confirmation.
For many liquid pairs, small tolerances can work, but you should watch for failed swaps, especially on DEXs. A failed swap still costs resources on some networks because you may pay fees even if execution reverts.
Tools and Settings to Control Execution Price
On CEXs, the core tools are limit orders, stop-limit orders, and sizing that avoids eating the book. Order type selection is your first lever for controlling slippage.
On DEXs, you can also adjust settings like “Max slippage” and review the minimum received value before confirming. The “minimum received” line matters because it converts tolerance into a concrete worst-case output.
Calculating Slippage
Slippage Percentage Formula
A common way to express slippage is as a percentage difference between expected and executed price. This formula matches how many platforms describe slippage as a price change between quote and fill:
Slippage % = ((Executed Price − Expected Price) / Expected Price) × 100
For a buy, a positive result means you paid more than expected, which is negative slippage for you. Sign conventions can be confusing, so many traders track absolute value as the “size” of slippage.
Practical Examples for Buyers and Sellers
Suppose you place a market buy for a token quoted at $100, and it executes at $101. Your slippage is about 1% because (101−100)/100 equals 0.01.
For a sell, suppose you expect $100 and receive $99 at execution. You effectively lost 1% to slippage, even if fees are excluded from the calculation.
Here’s a more detailed example. Let’s say you submit a market buy for 3 tokens. The last quoted price is $100, so you expect to pay about $300.
But the available sell orders (or AMM liquidity) look like this:
1 token available at $100
1 token available at $102
1 token available at $105
Your order fills across multiple price levels:
1 × $100 = $100
1 × $102 = $102
1 × $105 = $105 Total paid = $307 → average execution price = $307 / 3 = $102.33
Slippage (using the quote as reference) = (102.33−100) / 100 = 0.0233 ≈ 2.33%
This teaches that even if the “price” shows $100, a larger market order can push you into worse prices when liquidity is thin, so you end up paying an average above the quote.
Here’s one more example. You try to market sell a token quoted at $100. Right as you submit, other sellers hit the market (or the pool price shifts), and your sell executes at $96.
Slippage = (96−100) / 100 = −4% negative slippage; 4% in absolute terms)
This shows that slippage isn’t only about fees, it’s often about timing and price movement between quote and execution. In fast markets, the execution price can be meaningfully worse even if you’re trading a small amount.
Strategies to Minimize Slippage
Using Limit Orders Effectively
Limit orders are one of the most direct ways to cap slippage on a CEX. You define the worst acceptable price, which turns slippage into a fill probability question.
If you need certainty of execution, consider a limit order close to the current price rather than a pure market order. You may accept partial fills in exchange for better price control.
Splitting Large Orders and Timing Trades
If your order is large relative to available liquidity, splitting it can reduce the price you push through. Smaller chunks can reduce market impact, especially in thinner books and smaller pools.
Timing can also help because liquidity and volatility vary by hour and event. Avoid trading into obvious spikes like major announcements, sudden pumps, or liquidation cascades.
Choosing High-Liquidity Assets and Platforms
High-liquidity pairs tend to have deeper books or larger pools, which usually reduces slippage for typical trade sizes. Liquidity is a practical advantage because it improves execution consistency.
If you are swapping a niche token, route selection matters, including which pool you use and whether aggregators find better paths. Routing can change effective slippage by accessing deeper combined liquidity.
Monitoring Market Conditions and Volatility
Before trading, check recent price movement, spread, and depth for the pair you want. A wide spread is a warning sign that slippage risk may be higher than usual.
On DEXs, also consider network conditions, because a congested mempool can increase confirmation time. Longer confirmation windows increase slippage risk, especially for volatile pairs.
Real-World Examples and Case Studies
Popular Cryptocurrencies vs Low-Liquidity Altcoins
Liquidity differences show up fastest when you compare the same trade size against how much depth is available near the current price.
CoinGecko displays “+2% depth” and “-2% depth” in the Markets table to summarize how much liquidity is available within a 2% move up or down.
For BTC/USD on Coinbase Exchange, CoinGecko shows +2% depth of $27,516,713 and -2% depth of $21,753,219. A $10,000 market buy is roughly 0.04% of the +2% depth, so it is less likely to move far from the top-of-book price in normal conditions.
For a low-liquidity altcoin example like BADGER/USD₮ on Gate, CoinGecko shows +2% depth of $141 and -2% depth of $121. A $1,000 market order is about 7.1× the +2% depth, which helps explain why small orders can still experience multi-percent slippage when the visible book is thin.
Venue can matter as much as the asset. In the same January 2026 snapshot, CoinGecko shows BADGER/WBTC on Uniswap V3 (Ethereum) with +2% Depth of $121,365 and -2% Depth of $121,000, alongside a higher displayed spread than the Gate market for BADGER.
Comparing Slippage Across Exchanges
Even for the same asset, slippage can differ across exchanges because liquidity and execution rules vary.
As of January 2026, CoinGecko shows BTC depth of $27,516,713 (+2%) on Coinbase Exchange (BTC/USD), $24,894,946 (+2%) on Binance (BTC/USD₮), and $6,159,063 (+2%) on KuCoin (BTC/USD₮); a $5,000,000 buy is roughly 18%, 20%, and 81% of those +2% depth figures, respectively.
Execution rules can also shape outcomes when markets move quickly.
Coinbase’s Advanced Trade documentation describes a 10% market protection point for non-stable pairs and a 1% protection point for stable pairs, where market orders may stop executing and return a partial fill if the protection threshold would be exceeded.
Key Takeaways: What Is Slippage in Crypto?
Slippage is the difference between the price you expect and the price you get, and it tends to increase in volatile markets, in situations where liquidity is limited, when your order is large relative to available depth, or the trade takes longer to confirm and settle.
To manage slippage well, you need to understand what is driving it in each trade and measure it consistently using a clear baseline, such as the quoted price or best available price at submission.
Practical controls like limit orders and sizing can reduce exposure on centralized exchanges, while careful slippage tolerance settings, minimum received checks, and attention to network conditions can help on decentralized exchanges.
Over time, slippage awareness becomes part of a broader trading approach that includes risk management and cost control. Strong execution habits reduce surprises more reliably than any single toggle, because they account for both market structure and changing conditions.
Clear settlement expectations improve decision-making whether you are trading or moving value onchain. When you plan for slippage up front, you can set more realistic entries and exits, size positions with less guesswork, and avoid letting execution noise derail an otherwise sound strategy.
Disclaimer: This article is for educational purposes. It is not legal, tax, or investment advice.