Market Impact Costs: Drivers, Measurement, and Mitigation
Summary
Market impact is an implicit trading cost measured by the difference between the pre-trade reference price and the execution price. The document separates temporary impact, which reflects the concession needed to find counterparties, from permanent impact, which reflects information conveyed by order imbalance. It illustrates execution slippage against the midpoint and distinguishes impact from explicit costs such as brokerage and taxes, as well as opportunity cost.
The discussion identifies trade size relative to market volume, urgency and manager characteristics, and trading skill as drivers. It describes splitting large orders over time, distributing orders across brokers, and investigating a small subset of trades that may account for a large share of total impact. It also reports research on Australian institutions and notes that machine-learning approaches, including neural networks, Gaussian processes, and support vector regression, outperformed a parametric benchmark on four error measures. These examples are not universal estimates: impact varies by market, order, and execution conditions, and the article provides no detailed model specification or validation protocol.
Key ideas
- Market impact is the execution-price difference from a pre-trade reference and has temporary and permanent components.
- Large orders that represent a greater share of trading volume can create more price impact.
- Urgency, manager characteristics, and execution skill can affect impact costs.
- Order slicing and spreading trades across brokers are described as ways to reduce information leakage and execution impact.
- Machine-learning models may help predict impact, but the reported comparison does not establish performance across all markets.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.