Quote Survival Time refers to the average duration a limit order (a quote) remains active on an order book before it is either filled, cancelled, or updated due to market movements. In high-frequency crypto trading and RFQ systems, this metric indicates the stability and competitiveness of a market maker’s posted prices. Its purpose is to quantify the temporal viability of liquidity provision, serving as a critical parameter for optimizing quoting strategies and assessing market microstructure dynamics.
Mechanism
The mechanism for determining quote survival time involves logging the submission and subsequent event timestamps for every limit order placed by a market participant. Trading systems analyze these log data to calculate the duration for each quote. This data is aggregated and statistically analyzed to derive average survival times, often segmented by asset, price level, and market volatility conditions. Low-latency data capture and processing are essential for accurate measurement.
Methodology
The methodology for optimizing quote survival time is central to algorithmic market making, aiming to maximize the probability of profitable order execution while minimizing adverse selection. Strategies involve dynamic adjustment of quote prices and sizes based on observed survival times, liquidity conditions, and order book pressure. Shorter survival times may prompt wider spreads or smaller sizes, while longer times allow for tighter spreads. This continuous feedback loop helps market makers adapt to real-time market behavior and maintain efficient liquidity provision.
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