The RFQ Process, or Request for Quote process, is a formalized method of obtaining bespoke price quotes for a specific financial instrument, wherein a potential buyer or seller solicits bids from multiple liquidity providers before committing to a trade. It is a prevalent mechanism in OTC markets.
Mechanism
Operationally, a client initiates an RFQ by specifying the crypto asset, desired quantity, and transaction side. This request is electronically transmitted to a selected group of market makers or principal trading firms, who then respond with firm, executable two-sided prices (bid and ask) within a predefined time window. The client subsequently chooses the most competitive quote for execution.
Methodology
The methodology of the RFQ process is strategically advantageous for institutional crypto traders, particularly for large block trades or illiquid assets, as it facilitates competitive pricing, minimizes market impact, and provides access to deep, often off-exchange, liquidity. It is fundamental in institutional crypto options trading and OTC markets, enabling participants to achieve best execution by comparing multiple bids and offers.
An RFQ system reduces options spread costs by enabling private, competitive auctions that minimize information leakage and access deeper liquidity pools.
The primary drivers of information leakage in a voice RFQ are the unstructured communication protocols and the economic incentives of the participants.
Quantitative models reduce RFQ information leakage by transforming execution into a data-driven system of optimal dealer selection and dynamic order structuring.
The RFQ process provides a structured, competitive, and auditable framework for sourcing liquidity, enabling institutions to demonstrably comply with MiFID II's best execution mandate.
Proving best execution for a CLOB trade is a quantitative analysis of price against a public benchmark, while for an RFQ trade, it is a qualitative defense of a competitive process.
Proving best execution for a hybrid RFQ requires a systemic fusion of pre-trade analytics, competitive quoting, and post-trade TCA to create an auditable, data-driven defense of execution quality.
A firm quantifies RFQ information leakage by modeling the adverse price impact attributable to the inquiry itself, isolating it from general market noise.
A Request for Quote is a private auction protocol for sourcing targeted liquidity and achieving high-fidelity price discovery with minimal information leakage.
Measuring RFQ success is the systematic calibration of execution quality, information control, and counterparty performance to achieve a structural advantage.
An RFQ for undefined services shifts its function from price discovery to a strategic protocol for mapping supplier capabilities and negotiating a flexible partnership framework.
Primary metrics for RFQ information leakage are mark-out analysis and implementation shortfall, which quantify post-trade adverse selection and total execution cost.
Electronic RFQs transform opaque market execution from a relationship-based art to a data-driven system for managing information and optimizing price discovery.
We use cookies to personalize content and marketing, and to analyze our traffic. This helps us maintain the quality of our free resources. manage your preferences below.
Detailed Cookie Preferences
This helps support our free resources through personalized marketing efforts and promotions.
Analytics cookies help us understand how visitors interact with our website, improving user experience and website performance.
Personalization cookies enable us to customize the content and features of our site based on your interactions, offering a more tailored experience.
