What is Slippage?

Slippage is the gap between the price you anticipate when you send an order and the price you actually receive when it executes. It reflects how market conditions, order size, and order type interact from the moment of submission to final fill.

In crypto, slippage is shaped by fragmented venues, uneven depth, and changing spreads. Even small delays or partial fills can turn a seemingly fair quote into a worse realized price.

How it forms during execution

Slippage often starts with the spread you cross when using marketable orders. Beyond the spread, the book may not have enough size at the top levels, forcing your trade down the ladder and moving the price. That movement is the immediate market impact of your order.

Time adds another layer. If the order takes longer to complete, the market can drift away. Some of this movement is unrelated to your trade, but some may be informed reaction to your interest. Separating these effects requires careful post-trade analysis.

Measuring in practice

Traders measure slippage against a benchmark such as arrival price, decision price, mid-price, TWAP, or an index-based fair value. They compute the size-weighted average execution price across all fills and compare it to the chosen reference.

A complete figure includes explicit fees, rebates, and any conversion or funding costs. For passive orders, the effective spread captured or crossed and the probability of partial fills also enter the picture.

Practical relevance

Buy-side desks track slippage as a visible component of implementation shortfall and use it to choose schedules, venues, and order types. Brokers and algos rely on consistent slippage computation to compare performance across assets and regimes, and to defend routing decisions with data.

For market makers, patterns in client slippage reveal where books are thin, quotes are unstable, or selection risk is elevated. These insights guide quoting, inventory limits, and venue presence.

Sources and constraints

Volatility, wide or unstable spreads, and low depth-at-levels make slippage worse. Latency asymmetry and stale-quote risk can cause orders to chase prices that have already moved. Venue rules, fee tiers, and minimum increments also influence realized outcomes.

No single benchmark works for all trades. Results are sensitive to timestamp definitions, venue coverage, and how partial or unfilled quantities are treated. Transparent, repeatable rules are essential for comparisons over time.

Things to Remember

• Benchmark matters: Pick a reference that matches the decision context and lock the timestamp rules.
• Speed vs size: Faster fills reduce exposure but often raise impact; size slices to local depth.
• Stability helps: Route to venues with steadier quotes and quicker refills to cut slippage.
• Mind data quality: Clock sync and freshness checks prevent bias from stale quotes.