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- A markout measures what happened to a reference price after an execution, commonly at horizons ranging from milliseconds to several minutes.
- Trade-to-mid markout compares the execution price with a later midpoint; mid-to-mid markout compares the midpoint at execution with a later midpoint.
- The sign depends on perspective. A favourable markout for the liquidity taker is economically unfavourable for the liquidity provider on the same trade.
- Markout is used in transaction cost analysis, market making, counterparty and venue analysis, algorithm evaluation and liquidity-quality research.
- Reliable calculation requires high-quality timestamps, accurate trade direction, quote cleaning and a consistent method for retrieving the prevailing future quote.
Markout is a post-trade metric that compares an execution price or contemporaneous reference price with the market price at a specified time after the trade. It is used to measure short-term price movement, adverse selection, information content and execution quality. Because different desks use different perspectives and benchmarks, a markout is only meaningful when its sign convention, reference price, time horizon and treatment of market data are stated explicitly.
How Is Markout Calculated?
Markout compares a trade’s execution price with a reference market price at a defined time after the trade. The reference is commonly the prevailing midpoint:
Midpoint = (best bid + best offer) / 2
One commonly used signed trade-to-mid convention is:
Markout(h) = side x [midpoint(t + h) – execution price]
- side is +1 for a buy and -1 for a sell
- t is the execution timestamp
- h is the selected markout horizon
Under this convention, a positive value means the future midpoint moved in a direction favourable to the side assigned to the execution. A negative value means it moved against that side.
There is no single universal markout convention. Firms may use different sign perspectives, quote sources, time horizons and normalisation methods. The methodology used should therefore be stated and applied consistently, including the treatment of stale or missing quotes.
Trade-to-Mid Versus Mid-to-Mid Markout
Trade-to-mid markout includes both the execution’s location within the spread and subsequent midpoint movement. For a liquidity taker, buying at the offer creates an immediate disadvantage relative to the midpoint, which must be overcome before the trade-to-mid markout becomes positive. For a liquidity provider, that same spread capture is an initial advantage that may be eroded by adverse price movement.
Mid-to-mid markout isolates the movement of the midpoint itself. It compares the midpoint at execution with the midpoint at the future horizon and is often useful for studying signed price impact or the information content of order flow. Analysts should not describe one convention using the formula of the other.
Choosing a Markout Horizon
Different horizons capture different effects. Millisecond or sub-second horizons can reflect immediate quote response, latency and very short-lived selection. Horizons of one to ten seconds often capture near-term information and the first stage of price impact. One- to ten-minute horizons can show whether the movement persists, reverses or becomes dominated by broader market factors.
There is no universally correct horizon. The appropriate choice depends on the asset class, trading frequency, typical holding period, quote update rate and the business question. A robust analysis normally reports a markout curve across several horizons rather than selecting a single point that may favour a particular conclusion.
Why Markout Matters for Market Makers
Liquidity providers earn spread and rebates but face adverse-selection risk. If the midpoint repeatedly rises after they sell or falls after they buy, the apparent spread earned at execution may be offset by an unfavourable inventory revaluation. Markouts quantify that effect and help determine whether quoting parameters, skew, size, venue exposure or counterparty segmentation should change.
Markouts are especially useful when aggregated consistently. A single negative result may be noise. A stable pattern by symbol, strategy, counterparty or venue can indicate that the provider is systematically trading against faster or better-informed flow.
Why Markout Matters for Execution Analysis
For a buy-side or agency desk, favourable markouts on completed fills can indicate that executions occurred before prices moved in the order’s direction. However, the interpretation changes for a large parent order. A rising market after early buy fills may make those fills look good while increasing the cost of the remaining quantity. Markout should therefore be considered alongside implementation shortfall, participation rate, spread cost, realised impact and completion risk.
The metric can also expose differences between venues or order types. For example, one venue may provide frequent price improvement but poor longer-horizon markouts, while another produces less immediate improvement but more stable post-trade outcomes. Results should be controlled for symbol, volatility, spread, time of day and order characteristics before drawing conclusions.
Markout and Adverse Selection
Adverse selection occurs when one side of a trade is more likely to transact immediately before an unfavourable price move. Markout is a practical way to measure that outcome after the event. Consistently unfavourable liquidity-provider markouts may indicate adverse-selection characteristics in the flow. The result can also reflect public news, systematic momentum, latency differences or the provider’s own stale quotes, so it should not be interpreted as proof that the counterparty possessed private information.
An advantageous markout is not evidence of misconduct. It is an execution-quality and market-microstructure statistic. It may provide context in a broader conduct investigation, but it cannot establish manipulation, misuse of information or predatory behaviour without additional evidence.
Common Markout Variants
- Trade-to-mid: future midpoint compared with the execution price.
- Mid-to-mid: future midpoint compared with the midpoint at execution.
- Venue markout: calculated using a venue-specific BBO or order book.
- Consolidated markout: calculated using a consolidated or national best bid and offer where available.
- Return or basis-point markout: price difference normalized by execution price or midpoint.
- Notional markout: per-unit markout multiplied by executed quantity and, where relevant, contract multiplier.
- Markout curve: the same population evaluated at multiple future horizons.
- Risk-adjusted markout: result normalized for volatility, spread, beta or another market-risk factor.
Data and Methodology Considerations
- Trade direction: use an explicit buy/sell indicator where possible rather than inferring side solely from price tests.
- Clock synchronization: trade and quote timestamps must be comparable across systems and venues.
- Quote validity: crossed, locked, stale, zero-sized or otherwise invalid quotes may need defined treatment.
- Future quote selection: specify whether the calculation uses the last quote at or before the horizon, the first quote after it, or an average over a window. Apply a maximum quote-age threshold so that a technically valid but stale quote is not treated as representative of the prevailing market.
- Corporate actions and instrument changes: adjust prices and identifiers consistently across the analysis period.
- Market closures and sparse data: define how horizons that fall after a close, halt or data gap are handled.
- Outliers: report robust statistics such as medians, percentiles and confidence intervals as well as means.
- Aggregation: use appropriate quantity, notional or risk weighting and disclose the method.
How KDB-X Can Support Markout Analysis
Markout calculation is a temporal data-alignment problem. For each trade, the analysis creates one or more target timestamps and retrieves the prevailing quote for the same instrument at each target. In q and KDB-X, an as-of join can match a trade-derived target time to the most recent quote at or before that time.
A production implementation may generate a table of trade-horizon pairs, perform temporal joins against normalized quote data, calculate signed and normalized markouts, and aggregate the results by the required dimensions. Window joins can also support methodologies that average or summarize prices over intervals rather than selecting a single quote snapshot.
Performance depends on data ordering, partitioning, attributes, symbol cardinality, horizon count and the size of the trade and quote populations. The appropriate implementation should be tested against the firm’s actual market-data schema and latency or batch requirements.
Frequently Asked Questions
What does a positive markout mean?
Under the signed trade-to-mid convention used here, a positive markout means the future midpoint moved in a direction favourable to the side assigned to the execution. If the report is expressed from the liquidity-provider perspective, the sign is reversed.
What does a negative markout mean for a market maker?
It means the market moved against the position created by the fill: for example, the market maker sold before the midpoint rose or bought before it fell. Repeated negative results can indicate adverse selection.
Is markout the same as slippage?
No. Slippage usually compares an execution with a pre-trade or contemporaneous benchmark. Markout measures price behaviour after execution. Both can appear in transaction cost analysis, but they answer different questions.
Is markout the same as realised spread?
They are closely related but convention-dependent. Realised spread is typically expressed from the liquidity-provider or market-centre perspective and compares the execution price with a later midpoint. A signed trade-to-mid markout expressed from the opposite side of the same transaction has the opposite economic sign.
Which midpoint should be used?
The choice depends on the analysis. Possible references include the venue BBO, a consolidated BBO or a reconstructed book. The report should state the source and apply it consistently.
Can markout be calculated for futures and FX?
Yes. The concept applies across asset classes, but the price reference, contract multiplier, quote source, trading calendar and normalization method must reflect the instrument.
Should markouts be averaged?
Means are common, especially when quantity- or notional-weighted, but they can be sensitive to outliers. Medians, percentiles, distributions and confidence intervals often provide a more complete view.
Does a good markout prove an execution algorithm is good?
No. It is one diagnostic. A complete evaluation should also consider completion rate, spread cost, implementation shortfall, market impact, risk, opportunity cost and the objectives of the parent order.
Related Terms
- Adverse selection: the risk of trading immediately before an unfavourable price move.
- Transaction cost analysis: the broader measurement of execution performance and trading costs.
- Slippage: the difference between an execution and a selected pre-trade or contemporaneous benchmark.
- Realised spread: a post-trade spread measure commonly expressed from the liquidity-provider perspective.
- Market impact: the price movement associated with executing an order or revealing trading demand.
- As-of join: a temporal join that retrieves the latest matching record at or before a target time.