Slippage¶
OVERVIEW¶
Slippage is the difference between the price you expected when you submitted an order and the price your order actually filled at. It occurs because a quoted price is a snapshot of the best bid or ask at a single instant — by the time your order reaches the exchange, that quote may have moved, been partially filled by another participant, or lacked sufficient size to fill your full order.
Note
Slippage is not a fee or broker markup. It is a structural feature of continuous markets where prices update in real time and liquidity at any single price level is finite.
CALCULATION¶
Formula: Slippage = Fill Price − Expected Price
Expressed in dollars or as a percentage of the expected price.
| Order Side | Fill Direction | Slippage Type |
|---|---|---|
| Buy | Fill price above expected | Negative (paid more) |
| Buy | Fill price below expected | Positive (price improvement) |
| Sell | Fill price below expected | Negative (received less) |
| Sell | Fill price above expected | Positive (price improvement) |
Two structural drivers determine slippage magnitude:
| Driver | Description |
|---|---|
| Bid-Ask Spread | A market buy crosses the spread to hit the ask. Minimum slippage on a market order is roughly half the spread. |
| Market Impact | An order larger than resting size at the best price walks the book, filling at progressively worse prices for remaining size. |
WORKED EXAMPLE¶
| Scenario | Spread | Expected Fill | Actual Outcome |
|---|---|---|---|
| AAPL (liquid, $308.63) | ~$0.01 | Near last trade | Fills within a fraction of a percent; deep top-of-book absorbs typical retail size |
| Thin micro-cap ($2.00 bid / $2.20 ask) | 10% | ~$2.20 | If order exceeds resting size at $2.20, subsequent shares fill at $2.25, $2.30, and beyond |
| GME (Jan 2021 squeeze) | Extreme | Pre-halt price | Market orders filled tens of dollars from last printed trade; slippage in double-digit percentages |
Tip
The GameStop January 2021 example illustrates worst-case slippage: repeated intraday halts reset the order book at each reopening auction, making market orders placed just before a halt extremely vulnerable to large adverse fills.
HOW TO USE¶
Minimizing slippage in practice:
| Technique | Detail |
|---|---|
| Use limit orders | Avoids crossing the spread in illiquid names; prevents walking the book |
| Check Level 2 depth | Assess available size at the best price before sizing your order |
| Avoid session extremes | Spreads widen and depth thins in the first and last minutes of the session and immediately after news events |
| Use execution algorithms | TWAP and VWAP algos slice large orders into smaller pieces over time to minimize market impact and hold average fill price near the benchmark |
Note
Backtested strategies that ignore slippage systematically overstate real-world returns — particularly for strategies trading small-cap or low-volume names. A backtest filling every order at the last traded price with no size or spread modeling will understate real slippage on anything but the most liquid instruments.
LIMITATIONS AND MISCONCEPTIONS¶
| Misconception | Clarification |
|---|---|
| Slippage is always negative | Positive slippage occurs as often as negative slippage in liquid names; over a large sample the two roughly offset unless orders are consistently large relative to available size |
| Slippage equals the bid-ask spread | The spread contributes to slippage but is a distinct concept; spread cost, commission, and slippage are three separate sources of drag on realized returns |
| Stop order gaps are slippage | A stop order gapping past its trigger price is a related but distinct risk, not the same as order-execution slippage |
| Backtest slippage estimates are reliable | Estimates are only as good as the liquidity assumptions built into the simulation |