What is slippage?
Slippage is the deviation between an actual execution price and a reference price selected beforehand. In crypto trading, the quote seen before submission is not necessarily the final execution price. For example, against a buy reference of 100 USDT, an average execution price of 100.5 USDT means paying 0.5 USDT more per unit. USDT is the quote asset here; the numbers are illustrative.
Why does slippage occur?
In order-book-based markets, slippage mainly arises because there is insufficient quantity at the observed price or quotes change before execution. The order book lists unfilled buy and sell quotes and quantities; the trading system matches orders using them.
Quantity executable at a single price is limited. If only 1 token is offered at the lowest ask, an order to buy 3 may need higher-priced sell orders. Even with unchanged quotes, the average price exceeds the initial lowest ask.
There is a delay between seeing a quote and executing. Other trades, cancellations or new orders can change available quotes during that interval. The original price may no longer be executable, or a better one may appear.
A market order attempts to execute quickly at available quotes and may use several levels. A limit order caps the buy price or floors the sell price, but executions within the limit can still differ from the earlier quote. A price limit may also lead to a partial fill or no fill.
How is slippage calculated?
For an order with several executions, the average price is total trade value divided by total executed quantity. Calculate that average and compare it with the reference to assess the whole order’s price deviation.
Suppose a token’s spot sell orders are as follows, and 3 tokens are bought using the current lowest ask of 100 USDT as reference. Assume unchanged quotes, complete execution at the listed prices and no fees.
Ask price (USDT) | Executable quantity (units) |
|---|---|
100 | 1 |
101 | 2 |
The order buys 1 at 100 and then 2 at 101:
Total trade value: 100 × 1 + 101 × 2 = 302 USDT.
Average execution price: 302 ÷ 3, approximately 100.6667 USDT.
Extra payment versus reference: about 0.6667 USDT per token, or 302 − 100 × 3 = 2 USDT for the order.
Adverse buy slippage in this example = (average execution price − reference price) ÷ reference price × 100% ≈ 0.6667%.
Slippage can also be favorable: buying below the reference or selling above it improves the price. The reverse is adverse slippage. Reports may use different sign conventions, so specifying direction and reference is clearer than saying only “positive” or “negative” slippage.
What does its size mean?
Against the same reference, larger adverse slippage means buying further above the reference or selling further below it; smaller adverse slippage means execution closer to expectations. Favorable slippage means a better price than the reference.
Percentages can also be converted into money. For the same fully executed buy worth 1,000 USDT at the reference, excluding fees, 0.1% adverse slippage adds 1 USDT and 1% adds 10 USDT. These equal 10 and 100 basis points respectively; 1 basis point (bp, plural bps) = 0.01%. The numbers describe magnitude, not a good/bad threshold.
Order quantity matters too. Order-book depth is executable buy and sell quantity at each level; a larger order may use more levels against the same quotes. Higher slippage for a large order than a small one does not alone prove worse execution. Market changes between quoting and execution also affect outcomes.
Comparing trades requires consistent pair, direction, order amount or quantity, reference and its observation time, and confirmation of fee treatment. “10 basis points of adverse slippage on a 1,000 USDT buy against the lowest ask at submission” is more informative than “0.1% slippage.”
References and trade sizes vary across the industry; no fixed percentage evaluates every trade. Comparisons for the same pair, scale, reference convention and similar conditions can establish whether an adverse deviation is relatively large.
How does slippage relate to the spread?
The bid-ask spread describes the distance between best buy and sell quotes; slippage describes an executed order’s deviation from its reference. Both depend on quotes, but the spread contains no quantities at each level and cannot predict slippage alone.
For example, best bid 99.9 and best ask 100.1 USDT give a spread of 0.2. With 100.1 as the buy reference, an order fully executed at that level has zero slippage. If it exceeds the available quantity and uses higher asks, adverse slippage may arise. Thus a narrow spread can coexist with large slippage depending on order quantity, depth and quote changes during execution.
How do slippage, spread and fees differ?
Slippage and spread are price differences; fees are charges under trading rules. Even execution exactly at the reference can incur fees. Slippage itself is not an additional deduction.
Different references give different deviations. The midpoint averages best bid and ask. Using the ask as a buy reference differs from using the midpoint. The latter already includes the distance from midpoint to ask, so adding the spread again would double count. Confirm whether quotes include fees as well. See the spread article’s cost explanation for calculations.
Price impact and slippage in onchain swaps
On some decentralized exchanges, swaps use liquidity pools. A pool holds assets available for swaps, which smart contracts calculate and process. A smart contract is a program deployed on a blockchain that executes preset rules.
A trade changes the pool’s asset proportions. The resulting price change caused by that trade itself is price impact. A whole-trade quote obtained after entering a quantity may already reflect that effect. If other trades change the pool after submission but before onchain execution, the actual result can also differ from that quote.
When the whole-swap quote is the reference, price impact already included in it should not be counted again as new slippage. This differs from the earlier best-ask reference: a single-price reference and a whole-trade quote yield different measurements.
What does slippage tolerance control?
Slippage tolerance limits the adverse change a trade may accept. In some onchain swaps, the interface converts it into a minimum amount received or maximum amount paid, checked by the contract during execution.
If the amount actually received is below the minimum, or the amount actually paid is above the maximum, the swap will usually revert: that call’s state changes are undone instead of completing at an out-of-limit result. Products may use different fields and checks, so their specific rules apply.
An interface’s default tolerance is a product execution setting, not a prediction of actual slippage or an industry standard for “normal” slippage.
It constrains only that swap’s execution result, not price moves after execution, and does not guarantee success. If a transaction executes on a network such as Ethereum, even a failure may consume gas, the fee for onchain computation.
Related terms
Explore market orders, limit orders, the bid-ask spread and decentralized exchanges, or return to the crypto glossary.
References
FAQs
Slippage means the same in crypto as it does in other forms of trading. The term refers to a situation where the fill price you receive for an asset is different to the price you expected. However, slippage is considered more common in crypto compared to forex trading, for example, because of crypto’s higher volatility.
Slippage is generally considered to be a bad occurrence when trading because it adds another layer of uncertainty into the process. In some cases, positive slippage can also be experienced, where you’d receive better prices than expected when buying or selling an asset. However, many traders would prefer no slippage, because of the clarity this brings.
Not always, and it can be difficult to predict when slippage will occur and to what extent. However, you can minimize the chance of experiencing slippage by choosing assets with high liquidity, and only trading during busier periods when the order book should be deeper.
No, slippage can also be encountered on a decentralized exchange, and it's often caused by the same forces of low liquidity and high volatility.
