# How Does Dealer Curation in an RFQ Impact Competitive Pricing? ▴ Question

**Published:** 2025-08-01
**Categories:** Question

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![Dark, pointed instruments intersect, bisected by a luminous stream, against angular planes. This embodies institutional RFQ protocol driving cross-asset execution of digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-best-execution-system-architecture.jpg)

![Two sleek, pointed objects intersect centrally, forming an 'X' against a dual-tone black and teal background. This embodies the high-fidelity execution of institutional digital asset derivatives via RFQ protocols, facilitating optimal price discovery and efficient cross-asset trading within a robust Prime RFQ, minimizing slippage and adverse selection](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-prime-os-microstructure.jpg)

## Concept

The act of initiating a [Request for Quote](https://prime.greeks.live/area/request-for-quote/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (RFQ) is the act of creating a signal in the marketplace. Every institutional trader understands this on a visceral level. The moment an inquiry is sent, information begins to propagate through the system, and the value of that information is directly proportional to the size and urgency of the intended transaction. The central question of [dealer curation](https://prime.greeks.live/area/dealer-curation/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), therefore, is one of information control.

It is the primary mechanism for architecting the competitive environment for a specific trade, shifting the process from a wide, potentially chaotic broadcast to a series of controlled, high-fidelity negotiations. By strategically selecting which market makers are invited to price a given order, an institution is not merely picking counterparties; it is designing the very structure of the liquidity event. This act of design directly shapes the incentives of the responding dealers, which in turn governs the quality and competitiveness of the prices they return.

A non-curated, all-to-all [RFQ](https://prime.greeks.live/area/rfq/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) operates on the principle of maximizing immediate competitive tension. It assumes that a greater number of bidders inherently leads to a better price. This framework, however, fails to account for the second-order effects of [information leakage](https://prime.greeks.live/area/information-leakage/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). When a large RFQ is broadcast widely, dealers recognize it as a significant market event.

They become aware that numerous competitors are seeing the same request, which can trigger defensive pricing behavior. The fear of the “winner’s curse” ▴ winning a trade only because one was the least informed about a larger market shift or possessed the most aggressive, and perhaps inaccurate, pricing model ▴ compels dealers to widen their spreads. They price in the uncertainty and the risk that they are being adversely selected. Consequently, the apparent benefit of broad competition is systematically undermined by the information cost of achieving it.

> Dealer curation transforms a public broadcast of trading intent into a series of private, high-fidelity negotiations, fundamentally altering dealer incentives.

Strategic dealer curation functions as an intelligent filter applied to the RFQ protocol. It operates on a more sophisticated understanding of [market microstructure](https://prime.greeks.live/area/market-microstructure/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), recognizing that the optimal set of counterparties is rarely the complete set. The goal shifts from maximizing the number of bidders to maximizing the quality of the bids. This is achieved by creating a controlled environment where information leakage is minimized and dealer incentives are aligned with the institution’s objectives.

When a dealer receives a curated RFQ, the signal is different. It implies a degree of trust and the potential for future [order flow](https://prime.greeks.live/area/order-flow/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), incentivizing the dealer to provide a superior quote. The dealer understands they are part of a select group, which mitigates the fear of the winner’s curse and encourages them to price based on their true axe and risk appetite, rather than pricing defensively against a horde of unknown competitors. This curated approach converts the RFQ from a simple price discovery tool into a strategic relationship management protocol, where access to order flow is exchanged for consistent, high-quality liquidity.

This systemic view recasts dealer curation as a core component of an institution’s trading operating system. It is the logic layer that governs how the institution sources liquidity from the dealer community. The effectiveness of this system is measured not just by the competitiveness of a single quote, but by the aggregate [execution quality](https://prime.greeks.live/area/execution-quality/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) over time.

It requires a deep understanding of which dealers provide genuine liquidity in specific instruments and sizes, which ones are merely passive observers, and which ones may even use the information contained in an RFQ to trade against the institution’s interests. Curation, therefore, is the applied science of managing counterparty relationships and information dissemination to construct a more favorable and predictable pricing outcome for every trade.

![A sleek, angular Prime RFQ interface component featuring a vibrant teal sphere, symbolizing a precise control point for institutional digital asset derivatives. This represents high-fidelity execution and atomic settlement within advanced RFQ protocols, optimizing price discovery and liquidity across complex market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-control-point.jpg)

![A sleek, metallic, X-shaped object with a central circular core floats above mountains at dusk. It signifies an institutional-grade Prime RFQ for digital asset derivatives, enabling high-fidelity execution via RFQ protocols, optimizing price discovery and capital efficiency across dark pools for best execution](https://options.greeks.live/wp-content/uploads/2025/07/advanced-principal-rfq-protocol-architecture-for-institutional-digital-asset-derivatives-optimal-price-discovery-and-execution.jpg)

## Strategy

The strategic implementation of dealer curation in an RFQ workflow is a direct exercise in managing the fundamental trade-off between maximizing [competitive pressure](https://prime.greeks.live/question/how-does-dealer-hedging-pressure-manifest-in-the-volatility-skew/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and minimizing information leakage. These two forces are in constant opposition. A successful curation strategy does not seek to eliminate one in favor of the other; instead, it seeks to find the optimal balance for each specific trade, calibrated according to asset class, order size, and prevailing market conditions. This calibration is the essence of a sophisticated [liquidity sourcing](https://prime.greeks.live/area/liquidity-sourcing/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) strategy, transforming the RFQ process from a blunt instrument into a precision tool.

![Abstract forms on dark, a sphere balanced by intersecting planes. This signifies high-fidelity execution for institutional digital asset derivatives, embodying RFQ protocols and price discovery within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-platform-microstructure-execution-prime-os.jpg)

## The Core Tension Information Leakage versus Competitive Pressure

Understanding this trade-off requires a granular analysis of how information moves through the market. When an RFQ is sent to a large, uncurated list of dealers, the information about the initiator’s intent spreads rapidly. Even if dealers do not act maliciously, their own internal risk systems and traders will register the inquiry. This collective awareness can shift the perceived supply and demand balance for the asset, causing the market to move away from the initiator before a trade is even executed.

This is particularly acute for large block trades in less liquid instruments like corporate bonds or derivatives. The market impact begins with the RFQ, not with the trade. The strategic cost of this leakage is a higher execution price, as the institution is forced to chase a market that is already reacting to its own footprint.

Conversely, restricting the RFQ to a very small number of dealers ▴ perhaps one or two ▴ dramatically reduces information leakage but also severely curtails competitive pressure. The selected dealers, aware of the limited competition, have little incentive to offer their best possible price. They may widen their spreads, knowing the initiator has few alternatives. This creates a different kind of execution cost, one born of insufficient competition.

The strategic challenge is to identify the “sweet spot” ▴ the minimum number of dealers required to generate genuine price competition without triggering a cascade of information leakage. This number is not static; it changes with every trade.

![A sleek, metallic control mechanism with a luminous teal-accented sphere symbolizes high-fidelity execution within institutional digital asset derivatives trading. Its robust design represents Prime RFQ infrastructure enabling RFQ protocols for optimal price discovery, liquidity aggregation, and low-latency connectivity in algorithmic trading environments](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-execution-control-for-optimal-market-microstructure-precision.jpg)

## Strategic Curation Models

To navigate this complex landscape, institutions can deploy several distinct models for dealer curation. The choice of model depends on the institution’s technological capabilities, its trading philosophy, and the nature of its relationships with its counterparties.

![A luminous, multi-faceted geometric structure, resembling interlocking star-like elements, glows from a circular base. This represents a Prime RFQ for Institutional Digital Asset Derivatives, symbolizing high-fidelity execution of block trades via RFQ protocols, optimizing market microstructure for price discovery and capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-system.jpg)

## Relationship-Based Curation

This model is built on a foundation of trust and reciprocal value. Curation decisions are guided by qualitative assessments of dealer relationships. The institution directs its order flow to market makers who have consistently proven to be reliable partners, particularly those known to have a strong “axe” (a natural interest) in a specific asset. This approach excels at minimizing information leakage.

A trusted dealer is less likely to misuse the information from an RFQ and is more likely to provide a competitive quote to maintain the valuable relationship. The weakness of a purely relationship-based model is its qualitative nature, which can sometimes lead to overlooking better pricing from less-familiar counterparties.

![Two spheres balance on a fragmented structure against split dark and light backgrounds. This models institutional digital asset derivatives RFQ protocols, depicting market microstructure, price discovery, and liquidity aggregation](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-price-discovery-liquidity-aggregation.jpg)

## Performance-Based Curation

This model represents a quantitative and data-driven approach. It relies on the systematic collection and analysis of historical execution data for every dealer. Key performance indicators (KPIs) are tracked for each counterparty, such as response rates, hit rates, price improvement versus the arrival mid-price, and post-trade market reversion. Using this data, the [curation system](https://prime.greeks.live/area/curation-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) can dynamically select the dealers who are statistically most likely to provide the best execution for a given trade.

This method is objective and highly effective at maximizing competitive pressure among a select group. Its primary challenge is the requirement for robust data infrastructure and the risk of over-fitting to historical data, potentially missing a dealer who has recently developed a new axe or capability.

> Effective curation is a dynamic process of balancing quantitative performance metrics with qualitative relationship intelligence.

![A translucent, faceted sphere, representing a digital asset derivative block trade, traverses a precision-engineered track. This signifies high-fidelity execution via an RFQ protocol, optimizing liquidity aggregation, price discovery, and capital efficiency within institutional market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-block-trade-high-fidelity-execution-protocol-prime-os-path.jpg)

## Hybrid Curation Models

The most advanced and effective strategies typically employ a hybrid model that integrates both relationship intelligence and quantitative performance data. In this framework, a dealer’s historical performance data is weighted by a qualitative relationship score. For example, a large, critical trade might be sent to a “core” group of trusted relationship dealers, supplemented by a few “challenger” dealers selected purely on their recent performance metrics.

This allows the institution to benefit from the stability and trust of its key partners while simultaneously creating competitive pressure and discovering new sources of liquidity. This blended approach provides a robust, adaptive framework for optimizing the information-competition trade-off.

![A sleek, multi-layered device, possibly a control knob, with cream, navy, and metallic accents, against a dark background. This represents a Prime RFQ interface for Institutional Digital Asset Derivatives](https://options.greeks.live/wp-content/uploads/2025/07/precision-control-interface-for-institutional-digital-asset-derivatives-rfq-protocols-and-prime-os.jpg)

## Comparative Analysis of Curation Frameworks

The strategic implications of each curation model become clearer when compared across several key dimensions. The following table provides a structured analysis of these frameworks.

| Dimension | No Curation (All-to-All) | Relationship-Based Curation | Performance-Based Curation | Hybrid Curation |
| --- | --- | --- | --- | --- |
| Information Leakage Risk | Very High | Low | Medium | Low to Medium |
| Maximum Competitive Tension | High (Nominally) | Medium | High | Very High |
| Execution Quality Consistency | Low | Medium | High | Very High |
| Counterparty Risk Management | Poor | Excellent | Good | Excellent |
| Operational Complexity | Very Low | Low | High | Very High |
| Discovery of New Liquidity | High | Low | High | Medium |

![A teal and white sphere precariously balanced on a light grey bar, itself resting on an angular base, depicts market microstructure at a critical price discovery point. This visualizes high-fidelity execution of digital asset derivatives via RFQ protocols, emphasizing capital efficiency and risk aggregation within a Principal trading desk's operational framework](https://options.greeks.live/wp-content/uploads/2025/07/precision-institutional-digital-asset-derivatives-rfq-execution-strategy.jpg)

## How Does Curation Mitigate Adverse Selection?

From the dealer’s perspective, participating in an RFQ is a game of incomplete information. [Adverse selection](https://prime.greeks.live/area/adverse-selection/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is the risk that a client is initiating an RFQ precisely because they have superior information ▴ for example, they know a large institutional flow is about to hit the market. In a wide, uncurated auction, a dealer’s primary defense against adverse selection is to widen their spread. Dealer curation fundamentally changes this dynamic.

By creating a smaller, trusted group of participants, the client signals that the RFQ is a legitimate liquidity need, not an attempt to pick off an uninformed dealer. This reduction in perceived information asymmetry allows dealers to quote with greater confidence and, consequently, with tighter spreads. The curated process provides a layer of implicit insurance against adverse selection, the premium for which is paid by the client in the form of directed, valuable order flow.

![Symmetrical teal and beige structural elements intersect centrally, depicting an institutional RFQ hub for digital asset derivatives. This abstract composition represents algorithmic execution of multi-leg options, optimizing liquidity aggregation, price discovery, and capital efficiency for best execution](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-protocol-for-multi-leg-options-execution.jpg)

![A chrome cross-shaped central processing unit rests on a textured surface, symbolizing a Principal's institutional grade execution engine. It integrates multi-leg options strategies and RFQ protocols, leveraging real-time order book dynamics for optimal price discovery in digital asset derivatives, minimizing slippage and maximizing capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/principals-high-fidelity-rfq-execution-digital-asset-derivatives-hub.jpg)

## Execution

The execution of a dealer [curation strategy](https://prime.greeks.live/question/how-does-the-output-of-a-volatility-curation-system-influence-the-strategy-for-executing-a-large-rfq/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) moves beyond theoretical models and into the domain of operational architecture and quantitative analysis. It requires building a systematic, repeatable process for managing counterparty interactions, supported by a robust technological framework. This is where the strategic vision of optimizing liquidity sourcing is translated into a tangible, data-driven workflow that integrates directly into the institution’s trading desk.

![Translucent, overlapping geometric shapes symbolize dynamic liquidity aggregation within an institutional grade RFQ protocol. Central elements represent the execution management system's focal point for precise price discovery and atomic settlement of multi-leg spread digital asset derivatives, revealing complex market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-driving-optimal-liquidity-aggregation-for-precise-price-discovery-and-atomic-settlement.jpg)

## The Operational Playbook

Implementing a dealer curation system is a multi-stage project that involves data infrastructure, analytical modeling, and process integration. The following playbook outlines the critical steps for building a world-class curation capability.

- **Data Aggregation and Warehousing**

<li>**Source Identification** ▴ The first step is to identify and capture all relevant data points for every RFQ event. This data typically originates from the institution’s [Execution Management System](https://prime.greeks.live/area/execution-management-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (EMS) or [Order Management System](https://prime.greeks.live/area/order-management-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (OMS) and is transmitted via the Financial Information eXchange (FIX) protocol. Key FIX messages to capture include QuoteRequest (R), QuoteResponse (S), and ExecutionReport (8).

- **Metric Definition** ▴ Define a comprehensive set of metrics to be stored for each RFQ. This should include ▴ RFQ ID, Timestamp, Asset Identifier (CUSIP, ISIN), Trade Direction (Buy/Sell), Quantity, Dealer Name, Response Status (Quoted, Declined, Timed Out), Quote Price, Quoted Spread, Response Time, and Execution Status (Filled, Not Filled).

- **Post-Trade Data** ▴ It is also vital to capture post-trade data to measure market impact. This involves recording the market mid-price at intervals following the execution (e.g. 1 minute, 5 minutes, 30 minutes) to calculate price reversion.

</li>
- **Dealer Tiering and Scorecarding**

<li>**Quantitative Scorecard** ▴ Develop a standardized scorecard to evaluate each dealer’s performance. This scorecard should be updated regularly (e.g. daily or weekly) and should calculate key performance indicators from the warehoused data. The table below provides an example of such a scorecard.

- **Dealer Tiering** ▴ Based on the scorecard results, dealers can be segmented into tiers. For example:

<li>**Tier 1 (Core)** ▴ Dealers who consistently provide top-quartile performance in key asset classes and sizes. They form the foundation of the curation strategy.

- **Tier 2 (Specialist)** ▴ Dealers who may not be top performers across the board but demonstrate exceptional strength in niche products or specific market conditions.

- **Tier 3 (Challenger)** ▴ Dealers who are being evaluated or who provide opportunistic liquidity. RFQs are sent to this tier to foster competition and discover new liquidity sources.

</li>

</li>
- **Rule-Based [Curation Engine](https://prime.greeks.live/question/how-does-counterparty-curation-in-an-rfq-protocol-mitigate-signaling-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite)**

<li>**Logic Definition** ▴ The core of the execution framework is a rules engine that automates the curation process. This engine applies a set of logical rules to each outbound RFQ to determine the optimal list of dealers.

- **Example Rules** ▴ 

<li> IF AssetClass = ‘US IG Corp Bond’ AND Size > $20M THEN RFQ = Top 3 dealers from Tier 1 AND Top 2 dealers from Tier 2. 

- IF AssetClass = ‘Emerging Market Sov Debt’ AND MarketVolatility = ‘High’ THEN RFQ = All dealers in the ‘EM Specialist’ sub-tier. 

- IF Dealer ‘XYZ’ ResponseRate < 80% over last 30 days THEN Temporarily downgrade Dealer 'XYZ' from Tier 1 to Tier 2. 

</li>

</li>
- **Performance Review and System Recalibration**

<li>**Feedback Loop** ▴ The entire system must be designed as a closed loop. The results of each executed trade must feed back into the data warehouse to update the dealer performance scorecards.

- **Regular Audits** ▴ The trading desk should conduct regular reviews (e.g. quarterly) of the curation strategy’s effectiveness. This involves analyzing overall transaction costs, identifying underperforming dealers, and adjusting the rules in the curation engine to adapt to changing market dynamics and dealer behavior.

</li>

![A solid object, symbolizing Principal execution via RFQ protocol, intersects a translucent counterpart representing algorithmic price discovery and institutional liquidity. This dynamic within a digital asset derivatives sphere depicts optimized market microstructure, ensuring high-fidelity execution and atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-microstructure-orchestration.jpg)

## Quantitative Modeling and Data Analysis

The engine driving a performance-based curation strategy is its ability to quantitatively model and analyze dealer performance. The central artifact of this process is the Dealer Performance Scorecard. This scorecard provides an objective, multi-faceted view of each counterparty’s contribution to the institution’s execution quality.

| Dealer | Asset Class | RFQs Received | Response Rate | Hit Rate | Avg. Price Improvement (bps) | Avg. Response Time (ms) | 30-Min Reversion (bps) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Dealer A | US IG Corp | 500 | 98% | 25% | +1.5 | 250 | -0.2 |
| Dealer B | US IG Corp | 480 | 95% | 15% | +1.2 | 400 | -0.1 |
| Dealer C | US IG Corp | 350 | 99% | 10% | +0.8 | 200 | -0.5 |
| Dealer D | US HY Corp | 200 | 90% | 30% | +3.5 | 600 | -1.0 |
| Dealer E | US HY Corp | 210 | 85% | 20% | +2.5 | 750 | -1.2 |

From this data, a composite “Dealer Quality Score” (DQS) can be calculated. The formula for the DQS is a weighted average of the normalized KPI values, tailored to the institution’s priorities. For instance, an institution prioritizing price over speed might use a formula like:

DQS = 0.5 (Norm_PriceImprovement) + 0.2 (Norm_HitRate) + 0.2 (Norm_Reversion) + 0.1 (1 - Norm_ResponseTime)

This score allows for the objective ranking and tiering of dealers, forming the quantitative backbone of the curation engine.

![Translucent teal glass pyramid and flat pane, geometrically aligned on a dark base, symbolize market microstructure and price discovery within RFQ protocols for institutional digital asset derivatives. This visualizes multi-leg spread construction, high-fidelity execution via a Principal's operational framework, ensuring atomic settlement for latent liquidity](https://options.greeks.live/wp-content/uploads/2025/07/transparent-geometric-structures-visualizing-multi-leg-spread-rfq-protocols-for-high-fidelity-institutional-digital-asset-derivatives-execution.jpg)

## Predictive Scenario Analysis

To illustrate the profound impact of a well-executed curation strategy, consider the case of a portfolio manager at a large asset management firm who needs to sell a $75 million block of a 10-year corporate bond issued by a technology company. The bond is reasonably liquid, but a block of this size is certain to attract market attention.

In a scenario without a formal curation strategy, the trader, under pressure to demonstrate they sought the best price, might adopt an “all-to-all” approach. The RFQ is sent out to all 25 dealers on their platform. Within milliseconds, the signal is broadcast. The first few quotes are competitive, clustering around the current market mid-price.

However, as more dealers see the request, a new dynamic emerges. Dealers who do not have a natural axe to buy the bond see a large, widely distributed offer. They infer that a significant seller is present and that the price is likely to fall. Their defensive response is to either decline to quote or submit a low-quality, wide quote to protect themselves.

More problematically, some dealers’ algorithms may interpret the RFQ as actionable market information and begin to shade their own electronic quotes lower in the inter-dealer market, anticipating the coming supply. The “winner’s curse” looms large; any dealer who bids aggressively worries they are the only one missing a crucial piece of information. The initial competitive quotes begin to fade, and the best price available to the trader deteriorates. The final execution might be several basis points worse than the prices seen in the first few seconds, a direct cost of information leakage.

> A well-executed curation strategy transforms trading from a reactive process into a proactive exercise in market architecture.

Now, consider the same trade executed using a hybrid curation strategy. The institution’s curation engine analyzes the request. It identifies the asset as a US investment-grade corporate bond and notes the large size. The engine’s rules dictate a specific protocol.

It first queries the [dealer scorecard](https://prime.greeks.live/area/dealer-scorecard/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and selects the top four dealers ranked by their Dealer Quality Score for this specific asset class over the past 90 days. These are the dealers who have statistically proven to provide the tightest spreads and lowest market impact. Next, the engine cross-references this with the firm’s qualitative relationship data. It identifies two additional “core” relationship dealers who, while not in the top four quantitatively, have a known historical axe in technology sector bonds and have been reliable partners in large-size trades.

The final RFQ list contains just six dealers. This small, targeted group receives the request. The signal they interpret is one of privilege and opportunity, not of a market-wide fire sale. They know they are competing against a small number of credible peers for a valuable piece of business from a key client.

This mitigates the fear of adverse selection and incentivizes them to provide their best price. The competition is fiercer, even with fewer participants, because the quality of the competition is higher. The trader receives six tight, reliable quotes and executes the full block with minimal price decay and near-zero post-trade reversion. The value saved through this carefully architected liquidity event amounts to a significant sum, directly enhancing the fund’s performance.

![Diagonal composition of sleek metallic infrastructure with a bright green data stream alongside a multi-toned teal geometric block. This visualizes High-Fidelity Execution for Digital Asset Derivatives, facilitating RFQ Price Discovery within deep Liquidity Pools, critical for institutional Block Trades and Multi-Leg Spreads on a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-digital-asset-derivatives-rfq-execution-optimization-leveraging-proprietary-institutional-prime-os-for-optimal-price-discovery-and-latency-reduction.jpg)

## System Integration and Technological Architecture

The successful execution of this strategy is contingent on a seamless technological architecture. The system must be able to operate in real-time, integrating with the core trading infrastructure of the firm.

- **EMS/OMS Integration** ▴ The curation engine must be tightly integrated with the firm’s Execution Management System or Order Management System. It should act as an intermediary layer that intercepts an RFQ before it is sent to the market, applies the curation logic, and then routes the modified request to the appropriate trading venue or API.

- **[FIX Protocol](https://prime.greeks.live/area/fix-protocol/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) Management** ▴ The system must be fluent in the FIX protocol. It needs to parse incoming QuoteResponse messages to capture dealer quotes and execution data, and it must be able to construct and send QuoteRequest messages to the selected list of counterparties.

- **Data Analytics Platform** ▴ The dealer scorecards and performance metrics are best managed in a dedicated data analytics platform. This platform would ingest the raw FIX data from the trading systems, run the necessary calculations, and store the resulting KPIs in a structured database. This allows for historical analysis, trend identification, and the continuous refinement of the curation rules.

- **API Connectivity** ▴ Modern trading requires robust API connectivity. The curation system needs to connect to various trading venues and dealer APIs to both send RFQs and receive quote data, ensuring that the process is as automated and low-latency as possible.

By building this comprehensive operational and technological framework, an institution can move beyond a simplistic view of competition and execute a sophisticated, data-driven strategy that consistently improves execution quality by intelligently managing information and dealer incentives.

![Two intersecting metallic structures form a precise 'X', symbolizing RFQ protocols and algorithmic execution in institutional digital asset derivatives. This represents market microstructure optimization, enabling high-fidelity execution of block trades with atomic settlement for capital efficiency via a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-market-microstructure-execution.jpg)

## References

- Bergault, Philippe, and Olivier Guéant. “Liquidity Dynamics in RFQ Markets and Impact on Pricing.” arXiv preprint arXiv:2309.04216, 2023.

- Ackert, Lucy F. and Bryan K. Church. “Competitiveness and price setting in dealer markets.” Economic Review, Federal Reserve Bank of Atlanta, vol. 83, no. Q3, 1998, pp. 4-11.

- Madhavan, Ananth. “Market microstructure ▴ A survey.” Journal of Financial Markets, vol. 3, no. 3, 2000, pp. 205-258.

- Glosten, Lawrence R. and Paul R. Milgrom. “Bid, ask and transaction prices in a specialist market with heterogeneously informed traders.” Journal of Financial Economics, vol. 14, no. 1, 1985, pp. 71-100.

- Huang, Roger D. and Hans R. Stoll. “Dealer versus auction markets ▴ A paired comparison of execution costs on NASDAQ and the NYSE.” Journal of Financial Economics, vol. 41, no. 3, 1996, pp. 313-357.

![A sleek, domed control module, light green to deep blue, on a textured grey base, signifies precision. This represents a Principal's Prime RFQ for institutional digital asset derivatives, enabling high-fidelity execution via RFQ protocols, optimizing price discovery, and enhancing capital efficiency within market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/precision-control-for-institutional-digital-asset-rfq-execution.jpg)

## Reflection

The architecture of a trade begins not at the moment of execution, but at the point of inquiry. The principles outlined here provide a framework for understanding dealer curation as a system of control over the flow of information and the structure of competition. The ultimate challenge is to look beyond the mechanics of a single RFQ and examine the design of your institution’s entire liquidity sourcing operating system. How does your current process manage the inherent tension between information and competition?

Is your data being harnessed to create a feedback loop for continuous improvement, or is valuable execution intelligence evaporating after each trade? The capacity to design, implement, and dynamically recalibrate a curation strategy is a defining characteristic of a truly sophisticated trading enterprise. It is the tangible expression of market intelligence, transformed into a persistent, structural advantage.

![A central illuminated hub with four light beams forming an 'X' against dark geometric planes. This embodies a Prime RFQ orchestrating multi-leg spread execution, aggregating RFQ liquidity across diverse venues for optimal price discovery and high-fidelity execution of institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine-orchestrating-high-fidelity-execution-and-optimal-price-discovery.jpg)

## Glossary

<a href="https://prime.greeks.live/area/request-for-quote/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Two distinct components, beige and green, are securely joined by a polished blue metallic element. This embodies a high-fidelity RFQ protocol for institutional digital asset derivatives, ensuring atomic settlement and optimal liquidity](https://options.greeks.live/wp-content/uploads/2025/07/institutional-rfq-protocol-for-digital-asset-derivatives-high-fidelity-link.jpg)

## Request for Quote

Meaning ▴ A Request for Quote (RFQ), in the context of institutional crypto trading, is a formal process where a prospective buyer or seller of digital assets solicits price quotes from multiple liquidity providers or market makers simultaneously. </a><a href="https://prime.greeks.live/area/dealer-curation/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Sharp, transparent, teal structures and a golden line intersect a dark void. This symbolizes market microstructure for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-precision-execution-leveraging-granular-market-microstructure-intelligence.jpg)

## Dealer Curation

Meaning ▴ Dealer Curation refers to the strategic selection and maintenance of a specific inventory of financial instruments or digital assets by a market maker or dealer. </a><a href="https://prime.greeks.live/area/information-leakage/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Engineered object with layered translucent discs and a clear dome encapsulating an opaque core. Symbolizing market microstructure for institutional digital asset derivatives, it represents a Principal's operational framework for high-fidelity execution via RFQ protocols, optimizing price discovery and capital efficiency within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-protocol-execution-intelligence-engine.jpg)

## Information Leakage

Meaning ▴ Information leakage, in the realm of crypto investing and institutional options trading, refers to the inadvertent or intentional disclosure of sensitive trading intent or order details to other market participants before or during trade execution. </a><a href="https://prime.greeks.live/area/rfq/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precise, multi-faceted geometric structure represents institutional digital asset derivatives RFQ protocols. Its sharp angles denote high-fidelity execution and price discovery for multi-leg spread strategies, symbolizing capital efficiency and atomic settlement within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-execution-microstructure-framework.jpg)

## Rfq

Meaning ▴ A Request for Quote (RFQ), in the domain of institutional crypto trading, is a structured communication protocol enabling a prospective buyer or seller to solicit firm, executable price proposals for a specific quantity of a digital asset or derivative from one or more liquidity providers. </a><a href="https://prime.greeks.live/area/market-microstructure/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek blue surface with droplets represents a high-fidelity Execution Management System for digital asset derivatives, processing market data. A lighter surface denotes the Principal's Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-execution-for-optimal-price-discovery.jpg)

## Market Microstructure

Meaning ▴ Market Microstructure, within the cryptocurrency domain, refers to the intricate design, operational mechanics, and underlying rules governing the exchange of digital assets across various trading venues. </a><a href="https://prime.greeks.live/area/order-flow/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![An abstract institutional-grade RFQ protocol market microstructure visualization. Distinct execution streams intersect on a capital efficiency pivot, symbolizing block trade price discovery within a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-optimized-microstructure.jpg)

## Order Flow

Meaning ▴ Order Flow represents the aggregate stream of buy and sell orders entering a financial market, providing a real-time indication of the supply and demand dynamics for a particular asset, including cryptocurrencies and their derivatives. </a><a href="https://prime.greeks.live/area/execution-quality/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Metallic rods and translucent, layered panels against a dark backdrop. This abstract visualizes advanced RFQ protocols, enabling high-fidelity execution and price discovery across diverse liquidity pools for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/precision-market-microstructure-for-institutional-digital-asset-derivatives-rfq.jpg)

## Execution Quality

Meaning ▴ Execution quality, within the framework of crypto investing and institutional options trading, refers to the overall effectiveness and favorability of how a trade order is filled. </a><a href="https://prime.greeks.live/question/how-does-dealer-hedging-pressure-manifest-in-the-volatility-skew/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precision-engineered metallic discs, interconnected by a central spindle, against a deep void, symbolize the core architecture of an Institutional Digital Asset Derivatives RFQ protocol. This setup facilitates private quotation, robust portfolio margin, and high-fidelity execution, optimizing market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-core-infrastructure.jpg)

## Competitive Pressure

Dealer hedging pressure manifests in the volatility skew as a priced-in premium for managing the systemic negative gamma that amplifies downturns. </a><a href="https://prime.greeks.live/area/liquidity-sourcing/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precisely bisected, layered spheres symbolize a Principal's RFQ operational framework. They reveal institutional market microstructure, deep liquidity pools, and multi-leg spread complexity, enabling high-fidelity execution and atomic settlement for digital asset derivatives via an advanced Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-microstructure-core.jpg)

## Liquidity Sourcing

Meaning ▴ Liquidity sourcing in crypto investing refers to the strategic process of identifying, accessing, and aggregating available trading depth and volume across various fragmented venues to execute large orders efficiently. </a><a href="https://prime.greeks.live/area/curation-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sharp, metallic form with a precise aperture visually represents High-Fidelity Execution for Institutional Digital Asset Derivatives. This signifies optimal Price Discovery and minimal Slippage within RFQ protocols, navigating complex Market Microstructure](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-institutional-digital-asset-derivatives-rfq.jpg)

## Curation System

Meaning ▴ A Curation System refers to an organized framework or mechanism designed to select, process, and present information or assets based on specific quality standards or relevance criteria. </a><a href="https://prime.greeks.live/area/adverse-selection/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A central, precision-engineered component with teal accents rises from a reflective surface. This embodies a high-fidelity RFQ engine, driving optimal price discovery for institutional digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-execution-engine-for-price-discovery.jpg)

## Adverse Selection

Meaning ▴ Adverse selection in the context of crypto RFQ and institutional options trading describes a market inefficiency where one party to a transaction possesses superior, private information, leading to the uninformed party accepting a less favorable price or assuming disproportionate risk. </a><a href="https://prime.greeks.live/question/how-does-the-output-of-a-volatility-curation-system-influence-the-strategy-for-executing-a-large-rfq/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A slender metallic probe extends between two curved surfaces. This abstractly illustrates high-fidelity execution for institutional digital asset derivatives, driving price discovery within market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/precision-instrument-navigating-institutional-digital-asset-derivatives-rfq-protocols-for-optimal-price-discovery-and-high-fidelity-execution.jpg)

## Curation Strategy

A volatility curation system's output transforms RFQ execution from a price request into a strategic, data-driven negotiation of risk. </a><a href="https://prime.greeks.live/area/execution-management-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Smooth, reflective, layered abstract shapes on dark background represent institutional digital asset derivatives market microstructure. This depicts RFQ protocols, facilitating liquidity aggregation, high-fidelity execution for multi-leg spreads, price discovery, and Principal's operational framework efficiency](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-protocol-multi-leg-spreads.jpg)

## Execution Management System

Meaning ▴ An Execution Management System (EMS) in the context of crypto trading is a sophisticated software platform designed to optimize the routing and execution of institutional orders for digital assets and derivatives, including crypto options, across multiple liquidity venues. </a><a href="https://prime.greeks.live/area/order-management-system/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A translucent blue sphere is precisely centered within beige, dark, and teal channels. This depicts RFQ protocol for digital asset derivatives, enabling high-fidelity execution of a block trade within a controlled market microstructure, ensuring atomic settlement and price discovery on a Prime RFQ](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-pathway-for-institutional-digital-asset-derivatives-leveraging-rfq-protocols-and-high-fidelity-market-microstructure.jpg)

## Order Management System

Meaning ▴ An Order Management System (OMS) is a sophisticated software application or platform designed to facilitate and manage the entire lifecycle of a trade order, from its initial creation and routing to execution and post-trade allocation, specifically engineered for the complexities of crypto investing and derivatives trading. </a><a href="https://prime.greeks.live/question/how-does-counterparty-curation-in-an-rfq-protocol-mitigate-signaling-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precise, metallic central mechanism with radiating blades on a dark background represents an Institutional Grade Crypto Derivatives OS. It signifies high-fidelity execution for multi-leg spreads via RFQ protocols, optimizing market microstructure for price discovery and capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-system-microstructure-hub.jpg)

## Curation Engine

Counterparty curation mitigates signaling risk by transforming an RFQ into a secure, controlled disclosure to trusted, pre-vetted liquidity providers. </a><a href="https://prime.greeks.live/area/dealer-scorecard/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A polished metallic control knob with a deep blue, reflective digital surface, embodying high-fidelity execution within an institutional grade Crypto Derivatives OS. This interface facilitates RFQ Request for Quote initiation for block trades, optimizing price discovery and capital efficiency in digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-control-system-interface.jpg)

## Dealer Scorecard

Meaning ▴ A Dealer Scorecard is an analytical tool employed by institutional traders and RFQ platforms to systematically evaluate and rank the performance of market makers or liquidity providers. </a><a href="https://prime.greeks.live/area/fix-protocol/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A polished glass sphere reflecting diagonal beige, black, and cyan bands, rests on a metallic base against a dark background. This embodies RFQ-driven Price Discovery and High-Fidelity Execution for Digital Asset Derivatives, optimizing Market Microstructure and mitigating Counterparty Risk via Prime RFQ Private Quotation](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-best-execution-protocol.jpg)

## Fix Protocol

Meaning ▴ The Financial Information eXchange (FIX) Protocol is a widely adopted industry standard for electronic communication of financial transactions, including orders, quotes, and trade executions. </a>

**Tags:** [Order Flow](https://options.greeks.live/area/order-flow/), [RFQ](https://options.greeks.live/area/rfq/), [Dealer Curation](https://options.greeks.live/area/dealer-curation/), [Curation System](https://options.greeks.live/area/curation-system/), [Market Microstructure](https://options.greeks.live/area/market-microstructure/), [FIX Protocol](https://options.greeks.live/area/fix-protocol/)	

## Discover More

- 
### [What Are the Primary Trade-Offs When Deciding How Many Dealers to Query for an Illiquid Asset?](https://options.greeks.live/question/what-are-the-primary-trade-offs-when-deciding-how-many-dealers-to-query-for-an-illiquid-asset/)
![The image features layered structural elements, representing diverse liquidity pools and market segments within a Principal's operational framework. A sharp, reflective plane intersects, symbolizing high-fidelity execution and price discovery via private quotation protocols for institutional digital asset derivatives, emphasizing atomic settlement nodes.](https://options.greeks.live/wp-content/uploads/2025/07/systemic-interplay-for-institutional-digital-asset-derivatives-execution-via-advanced-rfq-protocols.jpg)

Optimizing illiquid asset RFQs involves balancing competitive pricing against the systemic risk of information leakage.

- 
### [How Does the RFQ Protocol Mitigate Adverse Selection Risk for Large Option Trades?](https://options.greeks.live/question/how-does-the-rfq-protocol-mitigate-adverse-selection-risk-for-large-option-trades/)
![A central, blue-illuminated, crystalline structure symbolizes an institutional grade Crypto Derivatives OS facilitating RFQ protocol execution. Diagonal gradients represent aggregated liquidity and market microstructure converging for high-fidelity price discovery, optimizing multi-leg spread trading for digital asset options.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-engine-11.jpg)

The RFQ protocol mitigates adverse selection by replacing public order book exposure with a private, competitive auction among trusted dealers.

- 
### [What Are the Key Differences between a Broadcast Rfq and a Targeted Rfq?](https://options.greeks.live/question/what-are-the-key-differences-between-a-broadcast-rfq-and-a-targeted-rfq/)
![Abstract visualization of institutional RFQ protocol for digital asset derivatives. Translucent layers symbolize dark liquidity pools within complex market microstructure. A central channel ensures high-fidelity execution and atomic settlement. Green nodes denote private quotation endpoints, enabling aggregated inquiry and price discovery.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-engine-6.jpg)

A broadcast RFQ seeks competitive pricing through broad exposure, while a targeted RFQ minimizes market impact through discreet inquiry.

- 
### [What Are the Best Practices for Constructing and Managing Dealer Panels for RFQ?](https://options.greeks.live/question/what-are-the-best-practices-for-constructing-and-managing-dealer-panels-for-rfq/)
![Sleek metallic panels expose a circuit board, its glowing blue-green traces symbolizing dynamic market microstructure and intelligence layer data flow. A silver stylus embodies a Principal's precise interaction with a Crypto Derivatives OS, enabling high-fidelity execution via RFQ protocols for institutional digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/08/institutional-digital-asset-derivatives-rfq-protocol-microstructure-os.jpg)

A dealer panel is an engineered liquidity ecosystem, continuously optimized through data to ensure execution certainty and control information flow.

- 
### [What Are the Primary Risks Associated with Using an RFQ System for Block Trading?](https://options.greeks.live/question/what-are-the-primary-risks-associated-with-using-an-rfq-system-for-block-trading/)
![A precise mechanical instrument with intersecting transparent and opaque hands, representing the intricate market microstructure of institutional digital asset derivatives. This visual metaphor highlights dynamic price discovery and bid-ask spread dynamics within RFQ protocols, emphasizing high-fidelity execution and latent liquidity through a robust Prime RFQ for atomic settlement.](https://options.greeks.live/wp-content/uploads/2025/07/precision-engineering-driving-institutional-digital-asset-derivatives-execution-across-advanced-rfq-protocols-and-prime-brokerage-frameworks.jpg)

The primary risks in RFQ block trading are information leakage and adverse selection, which are managed through a disciplined, data-driven execution framework.

- 
### [What Are the Primary Informational Risks Associated with Using an RFQ Protocol?](https://options.greeks.live/question/what-are-the-primary-informational-risks-associated-with-using-an-rfq-protocol/)
![Abstract geometric planes in teal, navy, and grey intersect. A central beige object, symbolizing a precise RFQ inquiry, passes through a teal anchor, representing High-Fidelity Execution within Institutional Digital Asset Derivatives. This depicts optimal Price Discovery and Liquidity Aggregation.](https://options.greeks.live/wp-content/uploads/2025/07/rfq-protocols-for-digital-asset-derivatives-high-fidelity-execution-liquidity-aggregation-price-discovery-market-microstructure.jpg)

The primary informational risk in an RFQ is the controlled disclosure of trading intent, which can be exploited by recipients.

- 
### [How Can Institutions Quantify Adverse Selection Risk in RFQ Protocols?](https://options.greeks.live/question/how-can-institutions-quantify-adverse-selection-risk-in-rfq-protocols/)
![Interlocking geometric forms, concentric circles, and a sharp diagonal element depict the intricate market microstructure of institutional digital asset derivatives. Concentric shapes symbolize deep liquidity pools and dynamic volatility surfaces. The diagonal signifies high-fidelity execution via RFQ protocols, supporting complex multi-leg spread strategies and efficient portfolio margin.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-and-high-fidelity-execution.jpg)

Quantifying adverse selection risk translates information asymmetry into a measurable cost, enabling superior execution management.

- 
### [What Role Does the FIX Protocol Play in the Technical Architecture of a Multi-Dealer RFQ Platform?](https://options.greeks.live/question/what-role-does-the-fix-protocol-play-in-the-technical-architecture-of-a-multi-dealer-rfq-platform/)
![A central illuminated hub with four light beams forming an 'X' against dark geometric planes. This embodies a Prime RFQ orchestrating multi-leg spread execution, aggregating RFQ liquidity across diverse venues for optimal price discovery and high-fidelity execution of institutional digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-engine-orchestrating-high-fidelity-execution-and-optimal-price-discovery.jpg)

The FIX protocol provides the standardized, machine-readable language essential for orchestrating discreet, multi-party trade negotiations.

- 
### [How Does the Aggregation of Quotes from Multiple Dealers Impact the Risk Profile of a Block Trade?](https://options.greeks.live/question/how-does-the-aggregation-of-quotes-from-multiple-dealers-impact-the-risk-profile-of-a-block-trade/)
![A precision-engineered, multi-layered system component, symbolizing the intricate market microstructure of institutional digital asset derivatives. Two distinct probes represent RFQ protocols for price discovery and high-fidelity execution, integrating latent liquidity and pre-trade analytics within a robust Prime RFQ framework, ensuring best execution.](https://options.greeks.live/wp-content/uploads/2025/08/digital-asset-derivatives-rfq-protocols-high-fidelity-execution.jpg)

Aggregating dealer quotes transforms block trade risk by balancing price competition against information leakage.

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---

**Original URL:** https://options.greeks.live/question/how-does-dealer-curation-in-an-rfq-impact-competitive-pricing/
