Quote Acceptance Models are algorithmic frameworks used by institutional trading systems to evaluate incoming price quotes for crypto assets or derivatives, determining whether to execute a trade based on predefined criteria.
Mechanism
These models analyze various attributes of a received quote, including its price, available size, validity period, and the current market context. They compare these against internal parameters such as maximum allowable slippage, portfolio risk limits, available inventory, and the perceived fairness of the quote relative to aggregated market data. A trade is executed only if all acceptance conditions are met.
Methodology
The strategic objective is to optimize execution quality, manage risk, and prevent adverse selection in fast-moving crypto markets. By automating the decision process for quote acceptance, these models enable rapid responses, ensuring that trades are only executed under favorable conditions, thereby preserving capital and minimizing operational overhead for institutional desks engaging in RFQ or options trading.
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