Definition
Slippage
Slippage is the difference between the price you expected and the price you got. Definition, formula, why it scales with size, and how it invalidates backtests.
Slippage is the difference between the price a trade was intended to execute at and the price it actually filled at, expressed as a percentage of the intended price. It arises because an order consumes available liquidity: a market order walks the book until it is filled, and the deeper it walks, the worse the average price. Slippage grows with order size, with volatility, and with thinness of the market.
- Also known as
- execution slippage · price impact
How it is calculated
Slippage = |Fill price − Intended price| ÷ Intended price × 100 %
Round-trip cost = (Fees × 2) + (Slippage × 2) + Funding held
Subtract the whole line from expectancy, not from profits.
Worked example: Intended $65,000, filled at $65,065 → 0.1% slippage, or $65 on a $65,000 order.
It scales non-linearly with size
Doubling an order does not double slippage — it takes the order deeper into the book, where each additional unit costs more than the last. This is why a strategy that is profitable at $10,000 of size can be unprofitable at $500,000 without a single rule changing, and why capacity is a property of a strategy rather than an afterthought.
It is the main gap between backtest and live
Backtests that fill at the close, at the mid, or at the signal price assume liquidity that was not available. Together with fees, unmodelled slippage is the most common reason a strategy that looked profitable in testing loses money in production, particularly for high-frequency or tight-stop systems where per-trade edge is small.
How it gets misread
Slippage is often modelled as a fixed number of basis points. Real slippage is state-dependent: it spikes in exactly the volatile conditions where a strategy trades most, so an average taken across calm periods understates the cost precisely when it matters.
Sources
- Direct Estimation of Equity Market Impact — Robert Almgren, Chee Thum, Emmanuel Hauptmann and Hong Li (Risk, July 2005; author copy hosted by the University of Pennsylvania)
- Optimal execution of portfolio transactions — Journal of Risk (Infopro Digital / Risk.net)
Definitions are educational. Nothing here is investment advice, and no metric described on this page predicts future results.
Definitions are the easy part
Knowing what drawdown means is not the same as having a system that halts on it. QANTERION applies these limits while a strategy runs.