Slippage
Slippage is the difference between the expected price of a trade at the time an order is submitted and the actual price at which the order is executed, arising from market movement between order submission and execution, bid-ask spreads, or insufficient liquidity at the desired price level. Slippage can be positive or negative and is a routine consideration in U.S. equity trading.
Every market order submitted on a U.S. stock exchange faces some degree of slippage. When a trader submits a market order to buy shares, the order is filled at the best available ask price at the moment the exchange's matching engine processes it. If the market has moved between the moment the order was entered and the moment it reached the exchange — a gap that can be as small as microseconds in a liquid large-cap stock or as long as seconds in a thinly traded small-cap — the execution price will differ from the price the trader observed on their screen.
For large institutional orders that exceed the available liquidity at the best ask price, slippage compounds across multiple price levels. If an investor submits a market order for 50,000 shares but only 10,000 shares are available at the best ask, the remaining 40,000 shares will be filled at progressively higher prices as the order works its way up the order book. This form of slippage — driven by consuming the available depth — is closely related to market impact and is the primary reason institutional investors use algorithmic execution strategies rather than large market orders.
Slippage is measured in different ways depending on the context. In quantitative trading and algorithmic strategy research, slippage is often modeled as a function of order size relative to average daily volume (ADV) and the stock's volatility. Academic and industry research has documented that slippage for institutional orders in U.S. large-cap equities has declined significantly over the past two decades as electronic trading and narrower bid-ask spreads reduced the structural costs of execution.
Limiting slippage is a central objective of execution strategy selection in institutional trading. Limit orders avoid the price uncertainty of market orders by capping the execution price, but they introduce the risk of non-execution if the market moves away from the limit price. Algorithmic strategies attempt to balance these trade-offs by working orders over time to match available liquidity without signaling the full order size to other market participants.
For retail investors in U.S. equities, slippage is most commonly encountered when trading lower-liquidity stocks with wide bid-ask spreads or when submitting market orders during periods of high volatility when quotes are rapidly changing. Payment-for-order-flow (PFOF) arrangements, in which retail brokers route orders to wholesalers in exchange for compensation, have been a subject of regulatory debate partly because of questions about whether retail investors receive full price improvement — the opposite of slippage — or experience subtle adverse execution quality relative to the NBBO at the time of their order.