Slippage: measuring decision-to-execution costs
A strategy can make the right forecast and still lose the expected profit while getting into the position. The price visible when the decision was made is often not the price the portfolio actually receives.
Slippage measures that decision-to-execution difference. It is the return gained or lost between the decision price and the executed price; an unfavorable difference is an implicit trading cost.
Definition
For an order to buy, a simple slippage measure relative to the decision price \(P_{\text{decision}}\) and the volume-weighted average execution price \(P_{\text{exec}}\) is
\[s = \frac{P_{\text{exec}} - P_{\text{decision}}}{P_{\text{decision}}}.\]
For a buy, positive \(s\) records an unfavorable execution. For a sell, the numerator is reversed so that a lower execution price also produces positive slippage. At the order or strategy level, slippage is usually reported as a volume-weighted average in basis points.
Components of slippage
Market impact and delay cost make up slippage. Market impact is the price movement caused by the order: a large order consumes available liquidity and moves the price against the trader as it executes. Delay cost is the market movement between the decision and execution times. It also covers the opportunity cost of an unfilled order.
Each component calls for different controls. Slower execution, smaller child orders, and more liquid securities reduce market impact. Faster signal processing and order submission reduce delay cost. A flat basis-point charge ignores these differences and gives poor estimates when urgency, turnover, order size, or liquidity changes.
Slippage and turnover
A strategy incurs slippage on every unit of capital traded, so annual drag grows with turnover. Backtests should apply explicit transaction costs and slippage to the same turnover assumptions and report their combined effect on return.
Further reading
- André F. Perold,
“The Implementation Shortfall: Paper Versus Reality”,
The Journal of Portfolio Management, 1988. Introduces the implementation-shortfall framework for measuring the return lost between a portfolio decision and its execution.
This walkthrough is for research and educational purposes. It illustrates how strategynet.ai organizes signal evidence into factors and scenarios. It provides no recommendation, investment advice, or instruction to trade any security.
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