Trade Slippage Calculator
Solve the slippage identity Slippage = ( Expected − Executed ) ÷ Expected × 100 for any of its three unknowns — the adverse slippage, the expected price, or the executed price — with a buy/sell direction toggle, step-by-step math, a live slippage-band gauge, an AMM price-impact estimator, and a tolerance check against common settings.
For a constant-product AMM, the average execution price deviates from spot by approximately trade size ÷ reserve. A $100,000 trade into a pool with $5,000,000 on the input side moves the average price by about 2% against you. This is the price impact — the deterministic component of slippage that comes from your own order consuming the book. Real slippage also includes the market moving while your transaction is pending.
Most interfaces let you set a maximum slippage tolerance — if the price moves beyond it before your transaction executes, the trade reverts. Setting it too tight causes failed transactions that still cost gas; setting it too loose leaves you exposed to sandwich attacks and MEV. The check below compares your actual slippage against the tolerance you selected.
Slippage cost = slippage % × expected notional. Fee cost = fee rate × expected notional. Together they are the true cost of execution — and on large orders slippage usually dwarfs fees. A 0.10% fee and a 2.00% slip mean you are paying twenty times more to the market than to the exchange.
Price impact and slippage are not the same thing
Price impact is the deterministic, mechanical consequence of your own order consuming liquidity — it can be calculated in advance from the pool reserves or the order book depth. Slippage is the total deviation you actually experienced, which includes price impact plus everything that happened while your transaction was in flight: other traders' orders, a block landing ahead of yours, a validator reordering the mempool, or simply a market that moved. On a quiet, deep market the two are nearly identical. On a thin or congested one, slippage can be several times the price impact you estimated.
Slippage is separate from fees
Fees are a known, fixed percentage charged by the venue. Slippage is an unknown, variable cost imposed by the market. On a large order, slippage routinely exceeds fees by an order of magnitude: a 0.10% taker fee and a 2% slip mean you paid the market twenty times more than you paid the exchange. This is why execution quality matters more than fee tiers for anyone trading size. A venue with 0.05% higher fees but half the slippage is cheaper on any order big enough to move the book.
Tolerance settings are a trade-off, not a safety net
Setting a tight slippage tolerance protects you from getting a terrible fill, but it also causes more failed transactions — and on most chains a failed transaction still costs gas. Set it too tight and you pay to fail repeatedly. Set it too loose and you become a target for sandwich attacks, where a bot sees your transaction, buys ahead of you to push the price up, and sells back into your order. The optimal tolerance depends on the asset's volatility and the chain's congestion. On a deep, liquid pair, 0.5% is often generous; on a thin long-tail token, even 3% may be reasonable.
Order size is the variable you actually control
Expected and executed prices are set by the market, but the size of your order is your decision — and on a constant-product AMM, price impact scales roughly linearly with size relative to the pool. Doubling your order doubles the impact. Splitting a large order across time or across venues is the standard way to reduce slippage, at the cost of execution risk and more transactions. There is a limit to how much this helps: if you are trading a meaningful fraction of the daily volume, the market will notice and reprice regardless of how you slice it.
How to Use This Calculator
The slippage relation links three quantities: the adverse slippage, the expected price, and the executed price. Quantity is always required so the percentage can be converted into a dollar cost.
1. Set the trade direction
Choose Sell or Buy. This determines the sign convention so that positive slippage always means adverse: on a sell, adverse is receiving less than expected; on a buy, adverse is paying more. A negative result means you got a better fill than you had any right to expect.
2. Enter the quantity
Quantity is required and always editable. It does not change the slippage percentage, but it converts it into the dollar cost that actually came out of your pocket — which is the number that matters when you are deciding whether an execution was acceptable.
3. Choose what to solve for
Pick Slippage, Expected, or Executed from the toggle. The calculator rearranges the formula automatically for whichever variable you choose and greys out that field.
4. Get the prices from your trade history
Expected price is the quote at the moment you submitted the order. Executed price is the volume-weighted average across all your fills, not the first or last one. On an AMM, divide what you received by what you put in.
5. Read the gauge, chips, and tolerance check
The result card places the slippage on a band from 0% to 100%, shows the dollar cost and basis points, and compares the result against a tolerance you select. The AMM estimator computes the price impact you should have expected from a given pool depth and order size.
6. Switch to Advanced for depth
Advanced mode adds a price-impact-vs-trade-size chart, a sensitivity check on ±1% input changes, and companion metrics including the effective fill ratio, the notional value traded, the slippage cost per unit, and the order size that would have kept you inside a target tolerance.
What This Tool Offers
Built around the slippage identity Slippage = ( Expected − Executed ) ÷ Expected × 100, the measure of how much the market charged you for the privilege of trading.
Three-way solving
Solve for the slippage percentage, the expected price, or the executed price. The calculator rearranges the formula for whichever variable you choose.
Buy/sell direction toggle
The sign convention adapts so that positive slippage always means adverse, whether you were buying or selling. Negative results are flagged as favourable fills.
AMM price-impact estimator
Enter pool reserve and trade size to compute the deterministic price impact from a constant-product pool, then apply the implied executed price with one click.
Tolerance comparison
Select a tolerance setting — 0.10%, 0.50%, 1.00%, 3.00%, or 10.00% — and see immediately whether your execution stayed inside it and how much headroom remains.
Dual comparison charts
Slippage vs. executed price for three expected-price levels, plus an advanced price-impact-vs-trade-size chart for three pool depths.
Reference tables
A live slippage converter, a slippage lookup grid, a benchmark tolerance table by venue and asset type, and a full variable reference.
Reference Tables & Conversions
A live slippage converter, a slippage lookup grid, and benchmark tolerance levels by venue and asset type.
Expected · executed · slippage converter
Slippage Lookup — Price Deviation × Expected Price
Each cell shows the dollar cost per unit at a given slippage and expected price.
| Slippage | @ $0.10 | @ $1 | @ $100 | @ $3,000 | @ $64,000 | @ $100,000 |
|---|
Typical Tolerance Levels by Venue and Asset
Indicative guidance only. The right tolerance depends on the asset's volatility, the chain's congestion, and how much you value fill certainty over price protection.
| Venue / asset | Typical tolerance | Why | Risk if set too loose |
|---|---|---|---|
| Deep stablecoin pair (CEX or AMM) | 0.01% – 0.10% | Liquidity is enormous and prices barely move | Minimal — the book is too deep to sandwich meaningfully |
| Major pair, liquid AMM | 0.10% – 0.50% | Standard for ETH/USDC and similar on tier-1 pools | Occasional sandwich attacks on larger orders |
| Major pair, centralised exchange | 0.50% – 1.00% | Book depth varies through the day; volatility is real | Fills at prices well away from the quote |
| Mid-cap token, decent liquidity | 1.00% – 2.00% | Thinner books and higher volatility | Meaningful adverse fills during volatile windows |
| Long-tail token on an AMM | 2.00% – 5.00% | Shallow pools; a single order moves the price several percent | Severe sandwich exposure and very poor average fills |
| New listing / low float | 5.00% – 15.00% | Price discovery is chaotic; depth may be a few thousand dollars | Extreme MEV extraction; fills far from the quote |
| Large block trade | Set after modelling impact | Tolerance should reflect the estimated price impact plus a margin | An unnecessarily wide band that invites front-running |
| High-congestion chain | Wider than usual | Long pending times mean more opportunity for the price to move | Failed transactions if set too tight, but costly fills if too loose |
Variable Reference
| Symbol | Meaning | Typical range | Units |
|---|---|---|---|
| Pexp | Expected price | 10⁻⁶ – 10⁶ | USD / unit |
| Pexe | Executed price (avg fill) | 10⁻⁶ – 10⁶ | USD / unit |
| Slip | Adverse slippage | −5 – 100 | % (positive = adverse) |
| bps | Basis points | −500 – 10,000 | 1 bps = 0.01% |
| Q | Quantity traded | 10⁻⁸ – 10⁹ | units |
| Cost | Slippage cost in dollars | 0 – 10⁹ | USD |
| Impact | AMM price impact | 0 – 100 | % |
| Tol | Slippage tolerance | 0.01 – 50 | % |
What Does Slippage = ( Expected − Executed ) ÷ Expected × 100 Measure?
Slippage measures the gap between the price you were quoted and the price you actually got. It is the market's charge for taking liquidity — the cost of wanting to trade right now rather than waiting for a better price. On a deep, quiet market the gap is a fraction of a basis point and nobody notices. On a thin pool, a congested chain, or a large order, it can be several percent, and it routinely costs more than the trading fee itself. The formula is trivial; understanding where the slippage came from is what matters.
Trade Slippage Formula
The defining relationship for a sell is:
Because the sign convention should always make positive mean adverse, the buy direction flips the numerator:
Rearranged to solve for the other two unknowns, using the sell convention:
Executed = Expected × ( 1 − Slippage ÷ 100 )
And for a buy, the sign inside the bracket flips:
Executed = Expected × ( 1 + Slippage ÷ 100 )
The dollar cost of slippage and the basis-point equivalent follow directly:
Basis points = Slippage × 100
Executed as % of expected = Executed ÷ Expected × 100
For a constant-product AMM, the deterministic price impact is approximately:
Slippage Variables
| Symbol | Meaning | Notes |
|---|---|---|
| Pexp | Expected price | The quote at the moment the order was submitted |
| Pexe | Executed price | Volume-weighted average across all fills |
| Slip | Adverse slippage | Positive = worse than expected; negative = favourable |
| Q | Quantity traded | Does not affect the percentage; converts it to dollars |
| Cost | Slippage cost | The dollar amount the deviation actually took from you |
| Impact | Price impact | The mechanical component from your own order |
| Tol | Tolerance | The maximum deviation you allow before the trade reverts |
How Each Variable Affects Slippage
Slippage is a ratio of two prices, so it is scale-free: trading one unit or a million units produces the same percentage if the prices are the same. What changes with size is not the slippage percentage but the dollars it costs. A 0.5% slip on a $100 trade costs fifty cents; on a $1,000,000 trade it costs $5,000. This is why the quantity field exists in this calculator even though it does not appear in the core formula — the percentage tells you how good the execution was, and the dollar cost tells you whether it mattered.
The expected price is the reference point, and getting it right matters more than it seems. If you record the quote from a minute before you submitted the order, you will attribute market movement to slippage. If you record the quote after the fill, you will attribute your own price impact to the market. The correct reference is the price at the instant of submission — the last price you saw before committing. On a centralised exchange that is the on-screen quote when you clicked confirm; on an AMM it is the pool's spot price at the block your transaction landed in, before your swap was applied.
Price impact is the portion of slippage you can predict. On a constant-product AMM it is approximately your trade size divided by the reserve on the input side: a $100,000 order into a $5,000,000 pool moves the average price by about 2%. That number is knowable before you trade, which means an unusually large gap between your predicted impact and your realised slippage is a signal that something else happened — a sandwich attack, a congested block, or a market that moved while you waited. On a centralised exchange the equivalent is walking the order book, which you can also estimate in advance from the depth chart.
Direction changes the sign convention but not the underlying reality. On a sell, you want to receive as much as possible, so receiving less than expected is adverse. On a buy, you want to pay as little as possible, so paying more than expected is adverse. This calculator applies the convention so that positive always means "worse than expected" regardless of direction, which makes results comparable across trades. A negative result means the market moved in your favour while your order was in flight — a genuine outcome, especially on volatile pairs, and worth recording rather than treating as an error.
Trade Slippage Calculation Examples
Slippage = (64,000 − 63,680) ÷ 64,000 × 100 = 0.5000% = 50.00 bps
Cost on 1 unit = 0.005 × 64,000 = $320.00
Expected = 63,680 ÷ (1 − 0.005) = $64,000.00
Executed = 64,000 × (1 − 0.005) = $63,680.00
Slippage = (2,040 − 2,000) ÷ 2,000 × 100 = 2.0000% adverse
Cost on 10 units = 0.02 × 2,000 × 10 = $400.00
Slippage = (1.00 − 1.004) ÷ 1.00 × 100 = −0.4000%
Negative slippage means you received more than expected — the market moved your way
Price impact ≈ 100,000 ÷ 5,000,000 × 100 = 2.0000%
On a $64,000 expected price, implied executed ≈ $62,720.00
Frequently Asked Questions
Price impact is the mechanical consequence of your own order consuming liquidity — it is deterministic and can be estimated in advance from pool reserves or order book depth. Slippage is the total deviation between the price you expected and the price you got, which includes price impact plus everything else that happened while your transaction was pending: other traders' orders landing first, a validator reordering the mempool, a sandwich attack, or simply a market that moved. On a deep, quiet market the two numbers are close. On a thin or congested one, realised slippage can be several times the price impact you predicted, and the gap is the part you were not compensated for.
Three common reasons. First, your transaction sat in the mempool while the price moved — on a congested chain a swap can take minutes to land, and in that window the market can move several percent. Second, you were sandwiched: a bot detected your transaction, bought ahead of it to push the price up, let your order fill at the worse price, then sold back for a profit. Third, your price impact estimate used the wrong reserve — pools change constantly as other people trade, so a pool that had $5M when you checked might have $3M when your transaction executes. A large gap between predicted impact and realised slippage is almost always one of these three.
It depends on the asset's volatility and the chain's congestion, and there is a genuine trade-off. Set it too tight and transactions fail — and on most chains a failed transaction still costs gas, so you pay to fail repeatedly. Set it too loose and you become a target for sandwich attacks, because a wide tolerance tells bots exactly how far they can push the price against you while still getting your order filled. As rough guidance: 0.10% for deep stablecoin pairs, 0.50% for major pairs on liquid AMMs, 1% for centralised exchange market orders on liquid assets, 2–5% for mid-cap tokens, and wider only for genuinely illiquid long-tail assets where you accept poor execution as the price of trading at all.
Yes, and it is not an error. Negative slippage means you got a better price than the quote you were working from — the market moved in your favour while your order was in flight, or you were filled at a better level than the top of the book suggested. On volatile pairs and on chains with long block times it happens regularly. This calculator applies the sign convention so that positive always means adverse regardless of whether you were buying or selling, which makes the result directly comparable across trades. A negative number is worth recording, not dismissing: it tells you the execution was better than expected, which is useful information about the venue and the timing.
On a constant-product AMM, price impact scales roughly linearly with your order size relative to the pool reserve: impact ≈ trade size ÷ reserve. Doubling the order doubles the impact. A $10,000 trade into a $5,000,000 pool moves the price about 0.2%; a $100,000 trade into the same pool moves it about 2%. On a centralised exchange the relationship depends on the shape of the order book — walking through several levels of depth costs progressively more. This is why large orders are split across time, across venues, or executed through algorithms that disguise their size. It is also why the same order size can have wildly different slippage on two venues with different liquidity.
No, and confusing them leads to bad venue choices. Fees are a known, fixed percentage the venue charges — 0.10% taker, 0.02% maker, and so on. Slippage is a variable cost imposed by the market and it is often far larger. On a $1,000,000 order with a 0.10% fee, you pay $1,000 in fees; if you also slipped 2%, you paid $20,000 to the market. That is twenty times more. Because of this, venues with slightly higher fees but deeper liquidity are frequently cheaper for anyone trading size. The fee tier is visible and easy to compare; the slippage is not, which is exactly why it gets ignored.
Not entirely, but it can be reduced substantially. Using limit orders instead of market orders eliminates slippage in the sense that you either get your price or you do not trade — but you take on execution risk instead, because the order may never fill. Trading on deeper venues reduces impact. Splitting large orders across time or venues reduces the footprint. Trading during liquid hours rather than at 3am reduces the chance of thin-book fills. Using private mempools or MEV protection services reduces sandwich exposure. None of these is free: each trades one kind of cost for another, and the right combination depends on whether you value certainty of fill or quality of price more.
Variables
| Symbol | Quantity | Unit |
|---|---|---|
| Slippage | Slippage percentage | % |
| Expected Price | Quoted price before execution | currency |
| Executed Price | Actual price the trade filled at | currency |
What it means
Slippage is the difference between the expected price of a trade and the actual executed price, often due to market movement or liquidity. It is a cost of trading, especially in volatile markets. Understanding this helps traders set appropriate slippage tolerance and to choose liquid trading venues. It is a key consideration in execution strategy.
Worked example
Trade Slippage Percentage – Two Detailed Examples
Real‑World| Parameter | Value |
|---|---|
| Expected Price | $60,000 |
| Executed Price | $59,700 |
| Parameter | Value |
|---|---|
| Expected | $3,000 |
| Executed | $2,985 |
Common mistakes
- Expected price: The price you anticipated before placing the trade.
- Executed price: The actual price at which the trade was filled.
- Slippage: The percentage difference – can be positive or negative.
- Limit orders: Avoid slippage; market orders incur it.
Applications
Trade slippage percentage compares the expected price to the executed price, indicating the deviation due to market movement or liquidity. This is a common metric for traders to assess the quality of execution. By monitoring slippage, they can adjust order types and timing to minimise costs. Understanding slippage is essential for effective trading, especially in volatile markets.
- Measuring execution quality and trading costs
- Adjusting order types (limit vs. market) based on slippage
- Optimising trade timing to minimise slippage
- Assessing liquidity conditions in real time
- Educational understanding of market impact
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