A transaction cost analysis metric that quantifies the price movement of an asset after an order has been executed (filled). It measures the difference between the execution price and a subsequent market price at a defined interval, indicating potential adverse selection or alpha generation.
Mechanism
Post-fill markout calculation involves capturing the precise execution price of a crypto trade and then observing the market price of the same asset at predetermined time intervals, such as one minute, five minutes, or thirty minutes post-execution. The difference between these prices, adjusted for the trade direction, represents the markout. This data is then aggregated and analyzed across numerous trades to identify patterns and assess execution quality.
Methodology
This metric is used to evaluate the efficiency of execution algorithms and the impact of large orders on market prices. A negative markout suggests adverse price movement against the trade, potentially indicating information leakage or suboptimal execution. Conversely, a positive markout suggests favorable price movement. Analyzing markouts assists institutions in refining their smart trading strategies and selecting liquidity providers that offer superior execution quality, thereby optimizing transaction costs over time.
Data analytics mitigates RFQ adverse selection by systematically pricing information asymmetry through predictive modeling and real-time risk assessment.
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